Handbook of climate change mitigation and adaptation. Volume 4 [Second edition] 9783319144085, 9783319144092, 9783319144108, 3319144081

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Wei-Yin Chen Toshio Suzuki Maximilian Lackner Editors

Handbook of Climate Change Mitigation and Adaptation Second Edition

Handbook of Climate Change Mitigation and Adaptation

Wei-Yin Chen • Toshio Suzuki Maximilian Lackner Editors

Handbook of Climate Change Mitigation and Adaptation Second Edition

With 1108 Figures and 352 Tables

Editors Wei-Yin Chen Department of Chemical Engineering University of Mississippi Oxford, MS, USA

Toshio Suzuki National Institute of Advanced Industrial Science and Technology (AIST) Nagoya, Japan

Maximilian Lackner Institute of Advanced Engineering Technologies University of Applied Sciences FH Technikum Wien Vienna, Austria

ISBN 978-3-319-14408-5 ISBN 978-3-319-14409-2 (eBook) ISBN 978-3-319-14410-8 (print and electronic bundle) DOI 10.1007/978-3-319-14409-2 Library of Congress Control Number: 2016946080 1st edition: # Springer Science+Business Media, LLC 2012 # Springer International Publishing Switzerland 2017 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Foreword

Scientific evidence is mounting that human activities have begun to change global climate. As a consequence, attention is increasingly turning in the public, private, and nonprofit sectors to the options available for dealing with that change. As we gradually begin to realize, actually only three options are available to us: mitigation, adaptation, and suffering. Mitigating climate change means cutting and sequestering emissions of greenhouse gases to prevent further increases in their atmospheric concentrations and perhaps even reducing concentrations to levels deemed less unsafe than the ones to which they have been driven since the start of the industrial revolution. Adaptation means finding ways that can help reduce the impacts of climate change on society, the various sectors of its economy, and the places in which we live – be those small rural villages or the cities and towns that by now house the majority of the human population, that account for the bulk of infrastructure investments, and that contribute most to energy consumption and carbon emissions. To the extent that mitigation and adaptation efforts are too timid, suffering will inevitably result. What are safe concentrations of greenhouse gases is a topic of vigorous debate because we do not yet fully understand the coupled earth system and human system dynamics that will play themselves out in a world of unprecedented greenhouse gas concentrations. How high is too high will be known well after the point of no return has been reached, that is when developments in the global biogeochemical system are kicked off to move in a direction and rate that cannot be undone. Ice sheets may melt and free the methane and carbon dioxide long locked up in the soils underneath, thus further accelerating climate change. Major ocean currents, which move waters and nutrients to support the biological activity in the seas, may abruptly change direction or entirely cease. The established precipitation and temperature patterns, which are so central to agriculture, may be altered in ways that further challenge our abilities to feed a growing human population. And so, the extent to which we embrace mitigation, in part, reflects our aversion – or desire – to take risks in matters pertaining not just to the stability of global climate conditions but the global human condition and that of other species more broadly. It is against this backdrop that this volume illuminates humanity’s mitigation options. From its coverage it is quite obvious that there is no magic knife with which to cut emissions, because the sources of emissions are varied and intricately woven v

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Foreword

into the very fabric of our society and economy. Movement from oil, coal, and natural gas, for example, to biological feedstocks for the production of fuels and chemicals is an essential strategy to decarbonize our economies, but the effect of this strategy hinges on the extent to which production of biomass can decouple itself from fossil-based generation of fertilizers and pesticides, minimize land conversation, and prevent the associated release of carbon from soils and impacts on biodiversity. Other, at least equally daunting, challenges surround the conversion of syngas to fuel; the deployment of geothermal, solar, and fusion technology; and the various means to sequester greenhouse gases. Policy and investment decision makers who wish to navigate and shape the resultant dynamics are further challenged in their abilities to understand and project resource and emissions trends into the future because of the rapid changes in technologies and markets, as well as the emergence of new, major players in the game, such as has happened in recent years with the proliferation of shale oil and shale gas developments. Even if the production of new sources of energy and materials can occur with lower emissions, the end use technologies and infrastructures need to be in place to take full advantage of these improvements. This will require changes in our built environment – from houses to transportation networks to energy storage to power grids and beyond. These changes, in turn, will, at least for the foreseeable future, require continued use of existing infrastructures that have developed around the use of conventional fuels and land use practices. Decarbonization at the process level, even when combined with the most aggressive efficiency improvements in the end uses of materials and energy, however only translates to net reductions in emissions if “other influences” do not overwhelm the rates at which these improvements are realized. Among these other influences are economic growth that comes from generating ever larger production of output, population growth that leads to ever more demand for goods and services, and climate change itself that is triggering a need for surplus production to built up our safety nets – from personal insurance to large-scale flood control systems – that can help us weather adverse climate conditions. In the final analysis, it is the interplay of technology change, behavioral change, institutional change, and environmental change that must be managed for mitigation to become effective. How well that interplay is orchestrated will in large part depend on our ability to provide the right incentives for climate mitigation – be it through international agreements or through unilateral action, through market-based approaches, direct government intervention, or a mix of them all. Our success will be indicative not just of the technological prowess of our age, but also of the values and institutions that guide our actions. Despite all efforts to stabilize and perhaps even reduce, in the long run, atmospheric greenhouse gas concentrations, humans have already committed themselves to decades of temperature changes and centuries of sea level rise. And, to worsen the outlook, rising global temperatures and sea levels will be accompanied by many other changes in our biophysical and socioeconomic environment. Since the heat budget of the globe will be disturbed, the frequency and severity of extreme weather events will likely increase. Disruptions in biophysical conditions will trigger, and be

Foreword

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triggered by, changes in ecosystems – including changes in the productivity of managed forests and croplands, as well as changes in the distribution of pests and diseases. The associated tightening of resource constraints will undermine the livelihoods of people, displace populations, and inflict pain and death. There are unlikely to be long-term winners from climate change. None of the places already suffering from shortages in water and food, for example, or flooding and crumbling infrastructures will, in the long run, be better off because of climate change. Even if they do feel like “winners” temporarily – perhaps because the length of growing seasons increases with rising temperatures or a melting of sea ice improves shipping and boosts their economy – those benefits are fleeting. Climate will not stop changing once optimal conditions are reached, and benefits in one sector may already be overwhelmed by costs imposed on other parts of the economy and society. Clearly, some form of adaptation will need to take place. Ideally, adaptation strategies are implemented not just as climate change unfolds, but in anticipation of any further climate change so that people, economic sectors, cities and their infrastructures, as well as natural systems such as wetlands and forests, are better prepared for, and perhaps even protected from, further disruptions. But even if there were no further climate change, there already is considerable variability in the weather conditions with which people, economic sectors, cities, and natural systems must cope. Maintaining vital wetlands well before flooding events will help provide natural buffers for coastal communities. Creating redundancies in lifeline infrastructures, such as the different ways of powering businesses and homes from centralized power plants and small-scale generators, will allow for switching across electricity sources during extreme weather events, for example. And promoting more efficient energy use in the first place will reduce the reliance on some of that energy. To the extent that adaptation helps reduce already existing inefficiencies, it can make good social, economic, and environmental sense irrespective of the details with which future climate conditions manifest themselves. The conclusion one may draw that “less mitigation today can be balanced by more adaptation in the future,” however, is misleading. It suggests that the two strategies are, at some abstract level, substitutable. In reality, though, less mitigation today means not just a need for more adaptation in the future. Rather, less mitigation today means more adaptation over more of our future, because even reduced emissions continue to add to atmospheric greenhouse gas concentrations, and because the damages that result will be cumulative in nature – heat waves, droughts, and flooding events, for example, will continuously undermine our wealth and welfare and require ever larger diversion of resources to address the causes and effects of climate change. Understanding the role of mitigation and choosing the proper mitigation strategies is, therefore, an essential forebear to anything else we may be doing about climate change. Recognizing the urgency for preparedness, given the extent to which humanity has already committed itself to a changing climate, is central to motivating investment in new technologies, changes in behaviors, and deployment of infrastructures that can better withstand the vagaries of the climate.

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Foreword

A worldview that is consistent with this understanding sees mitigation and adaptation as complements, offers them as strategies to address persistent and nascent inefficiencies, and treats them as a package that substitutes for the only other option available, namely suffering. It is in this sense that this Handbook of Climate Change Mitigation and Adaptation provides valuable insights into the preconditions for a prosperous future. School of Public Policy and Urban Affairs Northeastern University Boston, MA, USA

Matthias Ruth Director and Professor

Contents

Volume 1 Part I Scientific Evidences of Climate Change and Societal Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

Introduction to Climate Change Mitigation . . . . . . . . . . . . . . . . . . . . . . Maximilian Lackner, Wei-Yin Chen, and Toshio Suzuki

3

........

17

Paleoclimate Changes and Significance of Present Global Warming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Asadullah Kazi

47

Loss and Damage Associated with Climate Change Impacts Linta M. Mathew and Sonia Akter

Life Cycle Assessment of Greenhouse Gas Emissions . . . . . . . . . . . . . . L. Reijnders

61

Some Economics of International Climate Policy . . . . . . . . . . . . . . . . . Karen Pittel, Dirk R€ubbelke, Martin Altemeyer-Bartscher, and Sebastian Otte

93

Ethics and Environmental Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . David J. Rutherford and Eric Thomas Weber

127

Mass Media Roles in Climate Change Mitigation . . . . . . . . . . . . . . . . . Kristen Alley Swain

167

Economics for a Sustainable Planet . . . . . . . . . . . . . . . . . . . . . . . . . . . . Arif S. Malik

221

Emissions Trading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Roger Raufer, Paula Coussy, Carla Freeman, and Sudha Iyer

257

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Contents

Carbon Markets: Linking the International Emission Trading Under the United Nations Framework Convention on Climate Change (UNFCCC) and the European Union Emission Trading Scheme (EU ETS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Itziar Martínez de Alegría, Gonzalo Molina, and Belén del Río European Union (EU) Strategy to Face the Climate Change Challenge in the Framework of the International Commitments Itziar Martínez de Alegría, María-Azucena Vicente-Molina, and Cristian Moore

313

.....

341

Implications of Climate Change for the Petrochemical Industry: Mitigation Measures and Feedstock Transitions . . . . . . . . . . . . . . . . . . Simon J. Bennett and Holly A. Page

383

Venture Capital Investment and Trend in Clean Technologies . . . . . . . John C. P. Huang

427

..........

477

The Role of Aviation in Climate Change Mitigation . . . . . . . . . . . . . . . Katsuya Hihara

489

Part II

525

Analysis of the Co-benefits of Climate Change Mitigation Douglas Crawford-Brown

Impact of Climate Change and Adaptation . . . . . . . . . . . . .

Carbon Liability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yoshihiro Fujii

527

....

555

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595

Sea-Level Rise and Hazardous Storms: Impact Assessment on Coasts and Estuaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yan Ding

621

Climate Change and Carbon Sequestration in Forest Ecosystems Dafeng Hui, Qi Deng, Hanqin Tian, and Yiqi Luo Impact of Climate Change on Biodiversity David H. Reed

Projected Impacts of Climatic Changes on Cisco Oxythermal Habitat in Minnesota Lakes and Management Strategies . . . . . . . . . . . . . . . . . . Xing Fang, Heinz G. Stefan, Liping Jiang, Peter C. Jacobson, and Donald L. Pereira Impact of Climate Change on Crop Production Gamal El Afandi

..................

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Volume 2 Climate Change Impacts, Vulnerability, and Adaptation in East Africa (EA) and South America (SA) . . . . . . . . . . . . . . . . . . . . . . . . . . . Anne Nyatichi Omambia, Ceven Shemsanga, and Ivonne Andrea Sanchez Hernandez

749

Statistics in Climate Variability, Dry Spells, and Implications for Local Livelihoods in Semiarid Regions of Tanzania: The Way Forward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ceven Shemsanga, A. N. N. Muzuka, L. Martz, H. Komakech, and Anne Nyatichi Omambia

801

Climate Change Adaptation, Mitigation, and the Attainment of Food Security in the Sudano-Sahelian Belt of Nigeria . . . . . . . . . . . . . . . . . . Aishetu Abdulkadir

849

Understanding Climate Change Adaptation Needs and Practices of Households in Southeast Asia: Lessons from Five Years of Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Herminia A. Francisco and Noor Aini Zakaria

863

Impact of Climate Change, Adaptation, and Potential Mitigation to Vietnam Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Trinh Van Mai and Jenny Lovell

899

Potential Impacts of the Growth of a Mega City in Southeast Asia: A Case Study on the City of Dhaka, Bangladesh . . . . . . . . . . . . . . . . . . A. K. M. Azad Hossain and Greg Easson

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Potential of Solid Waste and Agricultural Biomass as Energy Source and Effect on Environment in Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . S. R. Samo, K. C. Mukwana, and A. A. Sohu

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The Advanced Recycling Technology for Realizing Urban Mines Contributing to Climate Change Mitigation . . . . . . . . . . . . . . . . . . . . . 1007 Tatsuya Oki and Toshio Suzuki An Introductory Course on Climate Change . . . . . . . . . . . . . . . . . . . . . 1037 Wei-Yin Chen Reducing Personal Mobility for Climate Change Mitigation . . . . . . . . . 1071 Patrick Moriarty and Damon Honnery Nontechnical Aspects of Household Energy Reductions Patrick Moriarty and Damon Honnery

. . . . . . . . . . . . 1107

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Contents

Bringing Global Climate Change Education to Middle School Classrooms: An Example from Alabama . . . . . . . . . . . . . . . . . . . . . . . . 1127 Ming-Kuo Lee, Chandana Mitra, Amy Thomas, Tyaunnaka Lucy, Elizabeth Hickman, Jennifer Cox, and Chris Rodger Climate Change: Outreaching to School Students and Teachers . . . . . . 1149 Dudley E. Shallcross, Timothy G. Harrison, Alison C. Rivett, and Jauyah Tuah Geoengineering for Climate Stabilization Maximilian Lackner

. . . . . . . . . . . . . . . . . . . . . . . 1201

Social Efficiency in Energy Conservation Patrick Moriarty and Damon Honnery

. . . . . . . . . . . . . . . . . . . . . . . 1235

Measuring Household Vulnerability to Climate Change . . . . . . . . . . . . 1251 Sofie Waage Skjeflo Fracking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1265 Qingmin Meng Transport Through Porous Media: Case Studies of CO2 Sequestration, CO2-Oxygen Reaction in Oxy-Combustion, and Oxygen Transport in Membrane at High Temperatures . . . . . . . . . . . . 1279 Aishuang Xiang Part III Climate Change Mitigation: Energy Conversation, Efficiency, and Sustainable Energies . . . . . . . . . . . . . . . . . . . . . . . . .

1307

Energy Efficiency: Comparison of Different Systems and Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1309 Maximilian Lackner Fuel Efficiency in Transportation Systems . . . . . . . . . . . . . . . . . . . . . . . 1385 Maximilian Lackner, John M. Seiner, and Wei-Yin Chen Thermal Insulation for Energy Conservation . . . . . . . . . . . . . . . . . . . . 1413 David W. Yarbrough Thermal Energy Storage and Transport . . . . . . . . . . . . . . . . . . . . . . . . 1433 Satoshi Hirano Smart Grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1465 Dawood Al Abri, Arif S. Malik, Mohammed Albadi, Yassine Charabi, and Nasser Hosseinzadeh Concentrated Solar Thermal Power . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1503 Anjaneyulu Krothapalli and Brenton Greska

Contents

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Volume 3 Harvesting Solar Energy Using Inexpensive and Benign Materials Susannah Lee, Melissa Vandiver, Balasubramanian Viswanathan, and Vaidyanathan (Ravi) Subramanian

. . . 1537

Greenhouse Gas Emission Reduction Using Advanced Heat Integration Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1581 Kailiang Zheng, Helen H. Lou, and Yinlun Huang Modern Power Plant Control for Energy Conservation, Efficiency Increase, and Financial Benefit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1631 Pal Szentannai Mobile and Area Sources of Greenhouse Gases and Abatement Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1657 Waheed Uddin Biomass as Feedstock . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1723 Debalina Sengupta Biochemical Conversion of Biomass to Fuels . . . . . . . . . . . . . . . . . . . . . 1777 Swetha Mahalaxmi and Clint Williford Thermal Conversion of Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1813 Zhongyang Luo and Jingsong Zhou Chemicals from Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1855 Debalina Sengupta and Ralph W. Pike Hydrodeoxygenation (HDO) of Bio-Oil Model Compounds with Synthesis Gas Using a Water Gas Shift Catalyst with a Mo/Co/K Catalyst . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1903 Rangana Wijayapala, Akila G. Karunanayake, Damion Proctor, Fei Yu, Charles U. Pittman, and Todd E. Mlsna Biochar from Biomass: A Strategy for Carbon Dioxide Sequestration, Soil Amendment, Power Generation, and CO2 Utilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1937 Vanisree Mulabagal, David A. Baah, Nosa O. Egiebor, and Wei-Yin Chen Wind Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1975 Manfred Lenzen and Olivier Baboulet Wave Power: Climate Change Mitigation and Adaptation . . . . . . . . . . 2007 Gregorio Iglesias and Javier Abanades Geothermal Energy Hirofumi Muraoka

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2057

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Contents

Hydropower . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2085 Jingsheng Jia, Petras Punys, and Jing Ma Nuclear Energy and Environmental Impact K. S. Raja, B. Pesic, and M. Misra

. . . . . . . . . . . . . . . . . . . . . 2133

Part IV Climate Change Mitigation: Advanced Carbon Conversion Sciences and Technologies . . . . . . . . . . . . . . . . . . . . . . .

2195

Reducing Greenhouse Gas Emissions with CO2 Capture and Geological Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2197 J. Marcelo Ketzer, Rodrigo S. Iglesias, and Sandra Einloft Chemical Absorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2239 Mengxiang Fang and Dechen Zhu CO2 Capture Using Solid Sorbents Yao Shi, Qing Liu, and Yi He

. . . . . . . . . . . . . . . . . . . . . . . . . . . . 2349

Volume 4 CO2 Capture by Membrane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2405 Teruhiko Kai and Shuhong Duan CO2 Geological Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2433 Masao Sorai, Xing Lei, Yuji Nishi, Tsuneo Ishido, and Shinsuke Nakao Conversion of CO2 to Value Added Chemicals: Opportunities and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2487 Arun S. Agarwal, Edward Rode, Narasi Sridhar, and Davion Hill Oxy-Fuel Firing Technology for Power Generation . . . . . . . . . . . . . . . . 2527 Edward John (Ben) Anthony Gasification Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2557 Lawrence J. Shadle, Ronald W. Breault, and James Bennett Conversion of Syngas to Fuels and Chemicals . . . . . . . . . . . . . . . . . . . . 2629 Steven S. C. Chuang and Long Zhang Chemical Looping Combustion Edward John (Ben) Anthony

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2647

High Temperature Oxygen Separation Using Dense Ceramic Membranes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2681 Jaka Sunarso, Kun Zhang, and Shaomin Liu

Contents

Part V

xv

Climate Change Mitigation: Advanced Technologies . . . . .

2707

Photocatalytic Water Splitting and Carbon Dioxide Reduction . . . . . . 2709 Nathan I. Hammer, Sarah Sutton, Jared Delcamp, and Jacob D. Graham Simultaneous CO2 and H2S Sequestration by Electrocatalytic Conversion for Chemical Feedstock Synthesis . . . . . . . . . . . . . . . . . . . . 2757 Nosa O. Egiebor and Jonathan Mbah Power-to-Gas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2775 Michael Sterner Reduction of Greenhouse Gas Emissions by Catalytic Processes Gabriele Centi and Siglinda Perathoner Integrated Systems to Reduce Global Warming Preben Maegaard and Anna Krenz

. . . . . 2827

. . . . . . . . . . . . . . . . . . 2881

Thermoacoustics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2967 Matthew E. Poese Hydrogen Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2995 Qinhui Wang Low-Temperature Fuel Cell Technology for Green Energy . . . . . . . . . . 3039 Scott A. Gold Solid Oxide Fuel Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3087 Nigel M. Sammes, Kevin Galloway, Mustafa F. Serincan, Toshio Suzuki, Toshiaki Yamaguchi, Masanobu Awano, and Whitney Colella Molten Carbonate Fuel Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3113 Takao Watanabe Fusion Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3139 Hiroshi Yamada 3rd-Generation Biofuels: Bacteria and Algae as Sustainable Producers and Converters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3173 Maximilian Lackner Biopolymers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3211 Maximilian Lackner Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3231 Maximilian Lackner Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3297

About the Editors

Wei-Yin Chen is a Chemical Engineering professor with degrees in Chemical Engineering and Applied Mathematics and Statistics. He initiated the Sustainable Energy and Environment (SEE) group, which was formed at the University of Mississippi in 2007 and now has over 200 collaborators around the world. The SEE group has been offering new courses on climate change and sustainable energy, edited this Handbook, been developing experimental modules for outreach with several nationally recognized awards, and been developing a multidisciplinary research program leading to efficient power generation, CO2 utilization, CO2 capture, and carbon activation. He has served as a panelist, reviewer, or advisor for research organization in the USA, China, Romania, India, Jordan, Malaysia, etc. He is an adjunct or visiting faculty of five universities in China and Taiwan. He is currently on the editorial board of five journals. He has reviewed manuscripts and book proposals for over 50 journals and publishers. He has received the outstanding research, teaching, and service awards from the School of Engineering of the University of Mississippi. His publications on pedagogy have been cited as the “Best Practice” by a review of Chemical Engineering Education in both the thermodynamics and chemical reaction engineering areas.

Toshio Suzuki is Group Leader of Functional Integration Technology Group, at Japan’s National Institute of Advanced Industrial Science and Technology (AIST), working in the fields of materials science, electrochemistry, and nanotechnology, especially on the development of next generation electrochemical devices such as solid oxide fuel cells (SOFCs). He is specializing in the design of advanced materials for energy conversion, with R&D experience in electrical, structural, and optical properties of novel ion conducting materials, correlating with microstructure. Dr. Suzuki received his xvii

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About the Editors

Ph.D. in Ceramic Engineering from University of Missouri-Rolla, USA, in 2001 and has published over 140 research articles, book chapters, and patents.

Maximilian Lackner received his Ph.D. in Technical Chemistry from Vienna University of Technology, Austria, in 2003, and his habilitation in Chemical Engineering in 2009. His research interests include: climate change mitigation, material science, lasers in chemistry, combustion, biofuels, and biobased plastics. Dr. Lackner was visiting researcher at Munich University of Technology (Germany), Darmstadt University (Germany), and Lund Institute of Technology (Sweden). He held several senior leadership positions in the petrochemical industry in Austria and China and founded five companies. Dr. Lackner has published over 100 research articles, book chapters, and patents. He is lecturer at Vienna University of Technology, the University of Applied Sciences FH Technikum Wien, and Johannes Kepler University (Austria).

Contributors

Javier Abanades School of Marine Science and Engineering, University of Plymouth, Plymouth, UK Aishetu Abdulkadir Centre for Disaster Risk Reduction and Development Studies (CDRM & DS), Federal University of Technology, Minna, Nigeria Dawood Al Abri Department of Electrical and Computer Engineering, Sultan Qaboos University, Muscat, Oman Arun S. Agarwal Materials Program, Strategic Research and Innovation, DNV GL, Dublin, OH, USA Sonia Akter Social Sciences Division, International Rice Research Institute, Los Baños, Laguna, Philippines Mohammed Albadi Department of Electrical and Computer Engineering, Sultan Qaboos University, Muscat, Oman Martin Altemeyer-Bartscher Faculty of Law and Economics, Martin-Luther University Halle-Wittenberg, Halle Institute for Economic Research, Halle (Saale), Germany Edward John (Ben) Anthony CanmetENERGY, Natural Resources Canada, Ottawa, ON, USA Masanobu Awano National Institute of Advanced Industrial Science and Technology (AIST), Nagoya, Japan David A. Baah Department of Chemical Engineering, Tuskegee University, Tuskegee, AL, USA Olivier Baboulet ISA, School of Physics-A28, The University of Sydney, Sydney, NSW, Australia James Bennett U. S. Department of Energy, National Energy Technology Laboratory, Morgantown, WV, USA xix

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Contributors

Simon J. Bennett Imperial Centre for Energy Policy and Technology, Imperial College, London, UK International Energy Agency, Paris, France Ronald W. Breault U. S. Department of Energy, National Energy Technology Laboratory, Morgantown, WV, USA Gabriele Centi Dip. Ingegneria Elettronica, Chimica ed Ingegneria Industriale (DIECII), University of Messina, ERIC aisbl and CASPE-INSTM, Messina, Italy Yassine Charabi Department of Geography, Sultan Qaboos University, Muscat, Oman Wei-Yin Chen Department of Chemical Engineering, The University of Mississippi, Oxford, MS, USA Steven S. C. Chuang First Energy Advanced Energy Research Center, Department of Chemical and Biomolecular Engineering, The University of Akron, Akron, OH, USA Whitney Colella Sandia National Laboratories, Albuquerque, NM, USA Paula Coussy Economics and Environmental Evaluation Department, CO2 Market Expert, IFP Energies nouvelles, Rueil-Malmaison, France Jennifer Cox Alabama Science in Motion Program, Alabama State University, Montgomery, AL, USA Douglas Crawford-Brown Cambridge Centre for Climate Change Mitigation Research, Department of Land Economy, University of Cambridge, Cambridge, UK Belén del Río Chair in International Studies, University of the Basque Country (UPV/EHU), Bilbao, Spain Jared Delcamp Department of Chemistry and Biochemistry, The University of Mississippi University, Oxford, MS, USA Qi Deng Department of Biological Sciences, Tennessee State University, Nashville, TN, USA Yan Ding National Center for Computational Hydroscience and Engineering, The University of Mississippi, Oxford, MS, USA Shuhong Duan Research Institute of Innovative Technology for the Earth (RITE), Kizugawa-shi, Kyoto, Japan Greg Easson Mississippi Mineral Resources Institute, The University of Mississippi, Oxford, MS, USA Nosa O. Egiebor Department of Chemical Engineering and Division of Global Engagement, The University of Mississippi, Oxford, MS, USA

Contributors

xxi

Sandra Einloft FAQUI – Faculty of Chemistry, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil Gamal El Afandi Department of Agricultural and Environmental Sciences, College of Agriculture, Environment and Nutrition Sciences, Tuskegee University, Tuskegee, AL, USA Department of Astronomy and Meteorology, Faculty of Science, Al Azhar University, Cairo, Egypt Mengxiang Fang Institute for Thermal Power Engineering, Zhejiang University, Hangzhou, Zhejiang, China Xing Fang Department of Civil Engineering, Auburn University, Auburn, AL, USA Herminia A. Francisco Economy and Environment Program for Southeast Asia (EEPSEA), Los Baños, Laguna, Philippines Carla Freeman School of Advanced International Studies, Johns Hopkins University, Washington, DC, USA Yoshihiro Fujii Graduate School of Global Environmental Studies, Sophia University, Tokyo, Japan Kevin Galloway Department of Metallurgical and Materials Engineering, Colorado School of Mines, Golden, CO, USA Scott A. Gold Department of Chemical and Materials Engineering, University of Dayton, Dayton, OH, USA Jacob D. Graham Johns Hopkins University, Baltimore, MD, USA Brenton Greska Cameron International, Houston, TX, USA Nathan I. Hammer Department of Chemistry and Biochemistry, The University of Mississippi University, Oxford, MS, USA Timothy G. Harrison Bristol ChemLabS, School of Chemistry, University of Bristol, Bristol, UK Yi He Department of Chemical and Biological Engineering, Institute of Industrial Ecology and Environment, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China Elizabeth Hickman Alabama Mathematics and Science Technology Initiative, Auburn University, Auburn, AL, USA Katsuya Hihara Graduate School of Public Policy, the University of Tokyo, Hongo Bunkyo-ku, Tokyo, Japan Davion Hill Energy and Materials, DNV GL, Dublin, OH, USA

xxii

Contributors

Satoshi Hirano Thermal and Fluids Systems Group, Energy Technology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan Damon Honnery Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, VIC, Australia A. K. M. Azad Hossain National Center for Computational Hydroscience and Engineering (NCCHE), The University of Mississippi, Oxford, MS, USA Nasser Hosseinzadeh Department of Electrical and Computer Engineering, Sultan Qaboos University, Muscat, Oman John C. P. Huang Focus Capital Group, Cupertino, CA, USA Yinlun Huang Lab for Multiscale Complex Systems Science and Engineering, Department of Chemical Engineering and Materials Science, Wayne State University, Detroit, MI, USA Dafeng Hui Department of Biological Sciences, Tennessee State University, Nashville, TN, USA Gregorio Iglesias School of Marine Science and Engineering, University of Plymouth, Plymouth, UK Rodrigo S. Iglesias FENG – Engineering Faculty, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil Tsuneo Ishido National Institute of Advanced Industrial Science and Technology (AIST), Geological Survey of Japan, Tsukuba, Ibaraki, Japan Sudha Iyer Cerebronics, LLC, Hoboken, NJ, USA Peter C. Jacobson Minnesota Department of Natural Resources, Park Rapids, MN, USA Jingsheng Jia International Commission on Large Dams (ICOLD), Paris, France Liping Jiang Department of Civil Engineering, Auburn University, Auburn, AL, USA Teruhiko Kai Research Institute of Innovative Technology for the Earth (RITE), Kizugawa-shi, Kyoto, Japan Akila G. Karunanayake Department of Chemistry, Mississippi State University, Starkville, MS, USA Asadullah Kazi Isra University, Hyderabad, Sindh, Pakistan J. Marcelo Ketzer IPR – Institute of Petroleum and Natural Resources, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil

Contributors

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H. Komakech Department of Water and Environmental Sciences and Engineering, Nelson Mandela Institution of Science and Technology-Tengeru, Tengeru, Arusha, Tanzania Anna Krenz Nordic Folkecenter for Renewable Energy, Hurup Thy, Denmark Anjaneyulu Krothapalli Department of Mechanical Engineering, Florida State University, Tallahassee, FL, USA Maximilian Lackner Institute of Advanced Engineering Technologies, University of Applied Sciences FH Technikum Wien, Vienna, Austria Ming-Kuo Lee Department of Geology and Geography, Auburn University, Auburn, AL, USA Susannah Lee Department of Chemical and Metallurgical Engineering, Chemical and Materials Engineering Department, LME 310, MS 388, University of Nevada, Reno, NV, USA Xing Lei National Institute of Advanced Industrial Science and Technology (AIST), Geological Survey of Japan, Tsukuba, Ibaraki, Japan Manfred Lenzen ISA, School of Physics-A28, The University of Sydney, Sydney, NSW, Australia Qing Liu Department of Chemical and Biological Engineering, Institute of Industrial Ecology and Environment, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China Shaomin Liu Department of Chemical Engineering, Curtin University, Perth, WA, Australia Helen H. Lou Dan F. Smith Department of Chemical Engineering, Lamar University, Beaumont, TX, USA Jenny Lovell Environmental Studies Department, University of California Santa Cruz, Santa Cruz, CA, USA Tyaunnaka Lucy Alabama Mathematics and Science Technology Initiative, Auburn University, Auburn, AL, USA Yiqi Luo Department of Microbiology and Plant Sciences, University of Oklahoma, Norman, OK, USA Zhongyang Luo State Key Laboratory of Clean Energy Utilization, College of Energy Engineering, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China Jing Ma China Institute of Water Resources and Hydropower Research, Beijing, China Preben Maegaard Nordic Folkecenter for Renewable Energy, Hurup Thy, Denmark

xxiv

Contributors

Swetha Mahalaxmi Department of Chemical Engineering, The University of Mississippi, Oxford, MS, USA Trinh Van Mai Institute for Agricultural Environment, Vietnam Academy of Agricultural Sciences, Phudo, South Tu Liem, Hanoi, Vietnam Arif S. Malik Department of Electrical and Computer Engineering, College of Engineering, Sultan Qaboos University, Muscat, Oman Itziar Martínez de Alegría Engineering School of Bilbao, University of the Basque Country (UPV/EHU), Bilbao, Spain L. Martz Department of Geography, University of Saskatchewan, Saskatoon, SK, Canada Linta M. Mathew Social Sciences Division, International Rice Research Institute, Los Baños, Laguna, Philippines Jonathan Mbah Department of Chemical Engineering, Florida Institute of Technology, Melbourne, FL, USA Qingmin Meng Department of Geosciences, Mississippi State University, Starkville, MS, USA M. Misra Department of Metallurgical Engineering, University of Utah, Salt Lake City, UT, USA Chandana Mitra Department of Geology and Geography, Auburn University, Auburn, AL, USA Todd E. Mlsna Department of Chemistry, Mississippi State University, Starkville, MS, USA Gonzalo Molina University of the Basque Country (UPV/EHU), Bilbao, Spain Cristian Moore Alcoa Inc., Alcoa, TN, USA Patrick Moriarty Department of Design, Monash University, Melbourne, VIC, Australia K. C. Mukwana Energy and Environment Engineering Department, Quaid-EAwam University of Engineering, Science and Technology (QUEST), Nawabshah, Sindh, Pakistan Vanisree Mulabagal Department of Chemical Engineering, Tuskegee University, Tuskegee, AL, USA Hirofumi Muraoka North Japan Research Institute for Sustainable Energy, Hirosaki University, Aomori, Japan

Contributors

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A. N. N. Muzuka Department of Water and Environmental Sciences and Engineering, Nelson Mandela Institution of Science and Technology-Tengeru, Tengeru, Arusha, Tanzania Shinsuke Nakao National Institute of Advanced Industrial Science and Technology (AIST), Geological Survey of Japan, Tsukuba, Ibaraki, Japan Yuji Nishi National Institute of Advanced Industrial Science and Technology (AIST), Geological Survey of Japan, Tsukuba, Ibaraki, Japan Tatsuya Oki National Institute of Advanced Industrial Science and Technology (AIST), Onogawa Tsukuba, Ibaragi, Japan Anne Nyatichi Omambia National Environment Management Authority, Nairobi, Kenya Sebastian Otte Technische Universität Bergakademie Freiberg, Freiberg, Germany Holly A. Page Imperial College, London, UK Siglinda Perathoner Dip. Ingegneria Elettronica, Chimica ed Ingegneria Industriale (DIECII), University of Messina, ERIC aisbl and CASPE-INSTM, Messina, Italy Donald L. Pereira Minnesota Department of Natural Resources, St. Paul, MN, USA B. Pesic Chemical and Materials Engineering, University of Idaho, Moscow, ID, USA Ralph W. Pike Minerals Processing Research Institute, Louisiana State University, Baton Rouge, LA, USA Karen Pittel Ifo Institute – Leibniz Institute for Economic Research and University of Munich, Munich, Germany Charles U. Pittman Department of Chemistry, Mississippi State University, Starkville, MS, USA Matthew E. Poese Applied Research Laboratory, State College, PA, USA Damion Proctor Department of Chemistry, Mississippi State University, Starkville, MS, USA Petras Punys Water Management Department, Water and Land Management Faculty, Lithuanian University of Agriculture, Kaunas-Akademija, Lithuania Dirk Rübbelke Technische Universität Bergakademie Freiberg, Freiberg, Germany K. S. Raja Chemical and Materials Engineering, University of Idaho, Moscow, ID, USA

xxvi

Contributors

Roger Raufer Hopkins Nanjing Center, Nanjing University, Nanjing, Jiangsu Province, China David H. Reed Department of Biology, University of Louisville, Louisville, KY, USA L. Reijnders Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands Alison C. Rivett Bristol ChemLabS, School of Chemistry, University of Bristol, Bristol, UK Edward Rode Materials Program, Strategic Research and Innovation, DNV GL, Dublin, OH, USA Chris Rodger Department of Mathematics and Statistics, Auburn University, Auburn, AL, USA David J. Rutherford Department of Public Policy Leadership, The University of Mississippi, Oxford, MS, USA Nigel M. Sammes Department of Metallurgical and Materials Engineering, Colorado School of Mines, Golden, CO, USA S. R. Samo Quaid-E-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, Sindh, Pakistan Ivonne Andrea Sanchez Hernandez Sustainability Development, AB Origen Fundación, Armenia, Quindio, Colombia John M. Seiner Debalina Sengupta Texas A&M University, College Station, TX, USA Mustafa F. Serincan Department of Mechanical Engineering, University of Connecticut, Storrs, CT, USA Lawrence J. Shadle U. S. Department of Energy, National Energy Technology Laboratory, Morgantown, WV, USA Dudley E. Shallcross Bristol ChemLabS, School of Chemistry, University of Bristol, Bristol, UK Ceven Shemsanga Department of Water and Environmental Sciences and Engineering, Nelson Mandela Institution of Science and Technology-Tengeru, Tengeru, Arusha, Tanzania Department of Environmental Engineering and Management, University of Dodoma, Dodoma, Tanzania David H. Reed: deceased. John M. Seiner: deceased.

Contributors

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Yao Shi Department of Chemical and Biological Engineering, Institute of Industrial Ecology and Environment, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China Sofie Waage Skjeflo UMB School of Economics and Business, Norwegian University of Life Sciences, Ås, Norway A. A. Sohu Mechanical Engineering Department, QUCEST, Larkano, Sindh, Pakistan Masao Sorai National Institute of Advanced Industrial Science and Technology (AIST), Geological Survey of Japan, Tsukuba, Ibaraki, Japan Narasi Sridhar Materials Program, Strategic Research and Innovation, DNV GL, Dublin, OH, USA Heinz G. Stefan St. Anthony Falls Laboratory, Department of Civil Engineering, University of Minnesota, Minneapolis, MN, USA Michael Sterner Forschungsstelle Energienetze und Energiespeicher (FENES), Fakultät für Elektro- und Informationstechnik, OTH Regensburg, Regensburg, Germany Vaidyanathan (Ravi) Subramanian Department of Chemical and Metallurgical Engineering, Chemical and Materials Engineering Department, LME 310, MS 388, University of Nevada, Reno, NV, USA Jaka Sunarso Department of Chemistry, University of Waterloo, Waterloo, ON, Canada Sarah Sutton Department of Chemistry and Biochemistry, The University of Mississippi University, Oxford, MS, USA Toshio Suzuki National Institute of Advanced Industrial Science and Technology (AIST), Nagoya, Japan Kristen Alley Swain Meek School of Journalism and New Media, The University of Mississippi, Oxford, MS, USA Pal Szentannai Department of Energy Engineering, Budapest University of Technology and Economics, Budapest, Hungary Amy Thomas Outreach Program, College of Sciences and Mathematics, Auburn University, Auburn, AL, USA Hanqin Tian International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL, USA Jauyah Tuah Secretariat of Brunei Darussalam Technical and Vocational Education Council, Permanent Secretary Office (Higher Education), Ministry of Education, Bandar Seri Begawan, Brunei Darussalam

xxviii

Contributors

Waheed Uddin Department of Civil Engineering, The University of Mississippi, Oxford, MS, USA Melissa Vandiver Department of Chemical and Metallurgical Engineering, Chemical and Materials Engineering Department, LME 310, MS 388, University of Nevada, Reno, NV, USA María-Azucena Vicente-Molina Economics and Business Administration College, University of the Basque Country, Bilbao, Spain Balasubramanian Viswanathan National Center for Catalysis Research, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India Qinhui Wang Institute for Thermal Power Engineering, Zhejiang University, Hangzhou, Zhejiang, China Takao Watanabe Central Research Institute of Electric Power Industry, Yokosuka, Kanagawa, Japan Eric Thomas Weber Department of Public Policy Leadership, University of Mississippi, Oxford, MS, USA Rangana Wijayapala Department of Chemistry, Mississippi State University, Starkville, MS, USA Clint Williford Department of Chemical Engineering, The University of Mississippi, Oxford, MS, USA Aishuang Xiang Chemical Engineering Department, Massachusetts Institute of Technology, Cambridge, MA, USA Hiroshi Yamada Department of Helical Plasma Research, National Institute for Fusion Science, Toki, Gifu, Japan Toshiaki Yamaguchi National Institute of Advanced Industrial Science and Technology (AIST), Nagoya, Japan David W. Yarbrough R&D Services, Inc., Cookeville, TN, USA Fei Yu Agricultural and Biological Engineering, Mississippi State University, Starkville, MS, USA Noor Aini Zakaria Economy and Environment Program for Southeast Asia (EEPSEA), Los Baños, Laguna, Philippines Kun Zhang Department of Chemical Engineering, Curtin University, Perth, WA, Australia Long Zhang Department of Polymer Science, The University of Akron, Akron, OH, USA Kailiang Zheng Dan F. Smith Department of Chemical Engineering, Lamar University, Beaumont, TX, USA

Contributors

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Jingsong Zhou State Key Laboratory of Clean Energy Utilization, College of Energy Engineering, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China Dechen Zhu Institute for Thermal Power Engineering, Zhejiang University, Hangzhou, Zhejiang, China

Part I Scientific Evidences of Climate Change and Societal Issues

Introduction to Climate Change Mitigation Maximilian Lackner, Wei-Yin Chen, and Toshio Suzuki

Contents Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Greenhouse Effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anthropogenic Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Effects of Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climate Change: What Will Change? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Impact of Climate Change Mitigation Actions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climate Change Adaptation Versus Climate Change Mitigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Handbook of Climate Change Mitigation and Adaption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Why This Book Is Needed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Audience of the Handbook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Since the first edition of the Handbook, important new research findings on climate change have been gathered. The handbook was extended to also cover, apart from climate change mitigation, climate change adaptation as one can witness increasing initiatives to cope with the phenomenon. Instrumental M. Lackner (*) Institute of Advanced Engineering Technologies, University of Applied Sciences FH Technikum Wien, Vienna, Austria e-mail: [email protected] W.-Y. Chen Department of Chemical Engineering, The University of Mississippi, Oxford, MS, USA e-mail: [email protected] T. Suzuki National Institute of Advanced Industrial Science and Technology (AIST), Nagoya, Japan e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_1

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recording shows a temperature increase of 0.5  C Le Houérou (J Arid Environ 34:133–185, 1996) with rather different regional patterns and trends (Folland CK, Karl TR, Nicholls N, Nyenzi BS, Parker DE, Vinnikov KYA (1992) Observed climate variability and change. In: Houghton JT, Callander BA, Varney SDK (eds) Climate change, the supplementary report to the IPCC scientific assessment. Cambridge University Press, Cambridge, pp 135–170). Over the last several million years, there have been warmer and colder periods on Earth, and the climate fluctuates for a variety of natural reasons as data from tree rings, pollen, and ice core samples have shown. However, human activities on Earth have reached an extent that they impact the globe in potentially catastrophic ways. This chapter is an introduction to climate change.

Climate Change There has been a heated discussion on climate change in recent years, with a particular focus on global warming. Over the last several million years, there have been warmer and colder periods on Earth, and the climate fluctuates for a variety of natural reasons as data from tree rings, pollen, and ice core samples have shown. For instance, in the Pleistocene, the geological epoch which lasted from about 2,588,000 to 11,700 years ago, the world saw repeated glaciations (“ice age”). More recently, “Little Ice Age” and the “Medieval Warm Period” (IPCC) occurred. Several causes have been suggested such as cyclical lows in solar radiation, heightened volcanic activity, changes in the ocean circulation, and an inherent variability in global climate. Also on Mars, climate change was inferred from orbiting spacecraft images of fluvial landforms on its ancient surfaces and layered terrains in its polar regions (Haberle et al. 2012). Spin axis/orbital variations, which are more pronounced on Mars compared to Earth, are seen as main reasons. As to recent climate change on Earth, there is evidence that it is brought about by human activity and that its magnitude and effects are of strong concern. Instrumental recording of temperatures has been available for less than 200 years. Over the last 100 years, a temperature increase of 0.5  C could be measured (Le Houérou 1996) with rather different regional patterns and trends (Folland et al. 1992). In (Ehrlich 2000), Bruce D. Smith is quoted as saying, “The changes brought over the past 10,000 years as agricultural landscapes replaced wild plant and animal communities, while not so abrupt as those caused by the impact of an asteroid as the Cretaceous-Tertiary boundary some 65 Ma ago or so massive as those caused by advancing glacial ice in the Pleistocene, are nonetheless comparable to these other forces of global change.” At the Earth Summit in Rio de Janeiro in 1992, over 159 countries signed the United Nations Framework Convention on Climate Change (FCCC, also called “Climate Convention”) in order to achieve “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system” (United Nations (UN) 1992). In 2001, the Intergovernmental Panel on Climate Change (IPCC) (Intergovernmental Panel on Climate Change (IPCC) 2007) wrote, “An increasing body of

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observations gives a collective picture of a warming world and other changes in the climate system. . . There is new and stronger evidence that most of the warming observed over the last 50 years is attributable to human activities.” In its fourth assessment report of 2007, the IPCC stated that human actions are “very likely” the cause of global warming. More specifically, there is a 90 % probability that the burning of fossil fuels and other anthropogenic factors such as deforestation and the use of certain chemicals have already led to an increase of 0.75 in average global temperatures over the last 100 years and that the increase in hurricane and tropical cyclone strength since 1970 also results from man-made climate change. In its fifth assessment report of 2013, the IPCC confirms their findings as “Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased” (IPCC 2013). Figures 1 and 2 show some details of IPCC’s findings. In Fig. 2, natural and man-made (anthropogenic) radiative forcings (RF) are depicted. RF, or climate forcing, expressed in W/m2, is a change in energy flux, viz., the difference of incoming energy (sunlight) absorbed by Earth and outgoing energy (that radiated back into space). A positive forcing warms up the system, while negative forcing cools it down. (Anthropogenic) CO2 emissions, which have been accumulating in the atmosphere at an increasing rate since the Industrial Revolution, were identified as the main driver. The position of the IPCC has been adopted by several renowned scientific societies, and a consensus has emerged on the causes and partially on the consequences of climate change. The history of climate change science is reviewed in (Miller et al. 2009). There are researchers who oppose the scientific mainstream’s assessment of global warming (Linden 1993). However, the public seems to be unaware of the high degree of consensus that has been achieved in the scientific community, as elaborated in a 2009 World Bank report (Worldbank 2009). In (Antilla 2005), there is a treatment of the mass media’s coverage of the climate change discussion with a focus on rhetoric that emphasizes uncertainty, controversy, and climate scepticism. Climate change skeptic films were found to have a strong influence on the general public’s environmental concern (Greitemeyer 2013).

The Greenhouse Effect A greenhouse, also called a glass house, is a structure enclosed by glass or plastic which allows the penetration of radiation to warm it. Gases capable of absorbing the radiant energy are called the greenhouse gases (GHG). Greenhouses are used to grow flowers, vegetables, fruits, and tobacco throughout the year in a warm, agreeable climate. On Earth, there is a phenomenon called the “natural greenhouse” effect, or the Milankovitch cycles.

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Without the greenhouse gas effect, which is chiefly based on water vapor in the atmosphere (Linden 2005) (i.e., clouds that trap infrared radiation), the average surface temperature on Earth would be 33  C colder (Karl and Trenberth 2003). The natural greenhouse effect renders Earth habitable since the temperature which would be expected from the thermal equilibrium of the irradiation from the sun and radiative losses into space (radiation balance in the blackbody model) is approximately 18  C. On the moon, for instance, where there is hardly any atmosphere, extreme surface temperatures range from 233  C to 133  C (Winter 1967). On Venus, by contrast, the greenhouse effect in the dense CO2 laden atmosphere results in an average surface temperature in excess of 450  C (Sonnabend et al. 2008; Zasova et al. 2007). The current discussion about global warming and climate change is centered on the anthropogenic greenhouse effect. This is caused by the emission and accumulation of greenhouse gases in the atmosphere. These gases (water vapor, CO2, CH4, N2O, O3, and others) act by absorbing and emitting infrared radiation. The combustion of fossil fuels (oil, coal, and natural gas) has led mainly to an increase in the CO2 concentration in the atmosphere. Preindustrial levels of CO2 (i.e., before the start of the Industrial Revolution) were approximately 280 ppm, whereas today, they are above 380 ppm with an annual increase of approximately 2 ppm. According to the IPCC Special Report on Emission Scenarios (SRES) (IPCC 2010a), by the end of the twenty-first century, the CO2 concentration could reach levels between 490 and 1,260 ppm, which are between 75 % and 350 % above the preindustrial levels, respectively. CO2 is the most important anthropogenic greenhouse gas because of its comparatively high concentration in the atmosphere. The effect of other greenhouse-active gases depends on their molecular structure and their lifetime in the atmosphere, which can be expressed by their greenhouse warming potential (GWP). GWP is a relative measure of how much heat a greenhouse gas traps in the atmosphere. It compares the amount of heat trapped by a certain mass of the gas in question to the amount of heat trapped by a similar mass of CO2. With a time horizon of 100 years, the GWP of CH4, N2O, and SF6 with respect to CO2 is 25, 298, and 22,800, respectively (IPCC 2010b). But CO2 has a much higher concentration than other GHGs, and it is increasing at a higher rate due to burning of fossil fuels. Thus, while the major mitigating emphasis has mainly been placed on CO2, efforts on mitigating CH4, N2O, and SF6 have also been active.

ä Fig. 1 (a) Observed global mean combined land and ocean surface temperature anomalies, from 1850 to 2012 from three data sets. Top panel: annual mean values. Bottom panel: decadal mean values including the estimate of uncertainty for one dataset (black). Anomalies are relative to the mean of 1961–1990. (b) Map of the observed surface temperature change from 1901 to 2012 derived from temperature trends determined by linear regression from one dataset (orange line in panel a). Trends have been calculated where data availability permits a robust estimate (i.e., only for grid boxes with greater than 70 % complete records and more than 20 % data availability in the first and last 10 % of the time period). Other areas are white. Grid boxes where the trend is significant at the 10 % level are indicated by a + sign (Source: IPCC (IPCC 2013))

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Fig. 2 Radiative forcing estimates in 2011 relative to 1750 and aggregated uncertainties for the main drivers of climate change. Values are global average radiative forcing (RF), partitioned according to the emitted compounds or processes that result in a combination of drivers. The best estimates of the net radiative forcing are shown as black diamonds with corresponding uncertainty intervals; the numerical values are provided on the right of the figure, together with the confidence level in the net forcing (VH very high, H high, M medium, L low, VL very low). Albedo forcing due to black carbon on snow and ice is included in the black carbon aerosol bar. Small forcings due to contrails (0.05 W m 2, including contrail induced cirrus), and HFCs, PFCs and SF6 (total 0.03 W m 2) are not shown. Concentration-based RFs for gases can be obtained by summing the likecoloured bars. Volcanic forcing is not included as its episodic nature makes is difficult to compare to other forcing mechanisms. Total anthropogenic radiative forcing is provided for three different years relative to 1750 (Source: IPCC (IPCC 2013))

Anthropogenic Climate Change The climate is governed by natural influences, yet human activities have an impact on it as well. The main impact that humans exert on the climate is via the emission of greenhouse gases. Deforestation is another example of an activity that influences the climate (McMichael et al. 2007). Figure 3 shows the share of greenhouse gas emissions from various sectors taken from (Quadrelli and Peterson 2007). The energy sector is the dominant source of GHG emissions.

Introduction to Climate Change Mitigation Fig. 3 Shares of global anthropogenic greenhouse gas emissions (Reprinted with permission from (Quadrelli and Peterson 2007))

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Waste 2.5% Agriculture 8%

Energy* 84%

CO2 95%

Industrial processes 5.5% CH4 4% N2O 1%

According to the International Energy Agency (IEA), if no action toward climate change mitigation is taken, global warming could reach an increase of up to 6 in average temperature (International Energy Association IEA 2009). This temperature rise could cause devastating consequences on Earth, which will be discussed briefly below.

Effects of Climate Change Paleoclimatological data show that 100–200 Ma ago, almost all carbon was in the atmosphere as CO2, with global temperatures being 10  C warmer and sea levels 50–100 m higher than today. Photosynthesis and CO2 uptake into the oceans took almost 200 Ma. Since the Industrial Revolution, i.e., during the last 200 years, this carbon is being put back into the atmosphere to a significant extent. This is a rate which is 107 times faster, so there is a risk of a possible “runaway” reaction greenhouse effect. Figure 4 shows the timescales of several different effects of climate change for the future. Due to the long lifetime of CO2 in the atmosphere, the effects of climate change until a new equilibrium has been reached will prove long term. A global temperature increase of 6  C would be severe, so the IEA has developed a scenario which would limit the temperature increase to 2  C (International Energy Association IEA 2009) to minimize the effects. Sea level rise will indeed be the most direct impact. Other impacts including those on weather, flooding, biodiversity, water resources, and diseases are discussed here.

Climate Change: What Will Change? An overall higher temperature on Earth, depending on the magnitude of the effect and the rate at which it manifests itself, will change the sea level, local climatic conditions, and the proliferation of animal and plant species, to name but a few of the most obvious examples. The debate on the actual consequences of global warming is the most heated part of the climate change discussion.

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Sea-level rise due to ice melting: Several millennia Sea-level rise due to thermal expansion: centuries to millennia

CO2 emissions peak: 0 to 100 years

Temperature stabilisation: a few centuries CO2 stabilisation: 100 to 300 years

CO2 emissions Today 100 years

1000 years

Fig. 4 Time scales of climate change effects based on a stabilization of CO2 concentration levels between 450 and 1,000 ppm after today’s emissions (Reprinted with permission from (Quadrelli and Peterson 2007))

Apart from changes in the environment, there will be various impacts on human activity. One example is the threats to tourism revenue in winter ski resorts (Hoffmann et al. 2009) and low-elevation tropical islands (Becken 2005). Insurance companies will need to devise completely new business models, to cite just one example of businesses being forced to react to climate change.

Impact of Climate Change Mitigation Actions The purpose of climate change mitigation is to enact measures to limit the extent of climate change. Climate change mitigation can make a difference. In the IEA reference scenario (International Energy Association IEA 2009), the world is headed for a CO2 concentration in the atmosphere above 1,000 ppm, whereas that level is limited to 450 ppm in the proposed “mitigation action” scenario. In the first case, the global temperature increase will be 6  C, whereas it is limited to 2  C in the latter (International Energy Association IEA 2009). The Intergovernmental Panel on Climate Change has projected that the financial effect of compliance through trading within the Kyoto commitment period will be limited at between 0.1 % and 1.1 % of GDP. By comparison, the Stern report estimated that the cost of mitigating climate change would be 1 % of global GDP and the costs of doing nothing would be 5–20 times higher (IPCC 2010b; Stern 2007).

Climate Change Adaptation Versus Climate Change Mitigation Individuals (Grothmann and Patt 2005), municipalities (Laukkonen et al. 2009; van Aalst et al. 2008), businesses (Hoffmann et al. 2009), and nations (Næss et al. 2005; Stringer et al. 2009) have started to adapt to the ongoing and expected state of

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Fig. 5 Conceptual framework for developing a climate change adaptation strategy. OUV Outstanding Universal Values (each World Heritage (WH) site has one or more such OUV. According to UNESCO, WH represent society’s highest conservation designation (Source: Jim Perry (2015))

climate change. Climate change adaptation and climate change mitigation face similar barriers (Hamin and Gurran 2009). To best deal with the situation, there needs to be a balanced approach between climate change mitigation and climate change adaptation (Becken 2005; Laukkonen et al. 2009; Hamin and Gurran 2009). This will prove to be one of mankind’s largest modern challenges. Figure 5 shows a conceptual framework for developing a climate change adaptation strategy. Details are presented in this Handbook.

Handbook of Climate Change Mitigation and Adaption Motivation The struggle in mitigating climate change is not only to create a sustainable environment but also to build a sustainable economy through renewable energy resources. “Sustainability” has turned into a household phrase as people become increasingly aware of the severity and scope of future climate change. A survey of

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the current literature on climate change suggests that there is an urgent need for a comprehensive handbook introducing the mitigation of climate change to a broad audience. The burning of fossil fuels such as coal, oil, and gas and the clearing of forests has been identified as the major source of greenhouse gas emissions. Reducing the 24 billion metric tons of carbon dioxide emissions per year generated from stationary and mobile sources is an enormous task that involves both technological challenges and monumental financial and societal costs with benefits that will only surface decades later. The Stern Report (2007) provided a detailed analysis of the economic impacts of climate change and the ethical ground of policy responses for mitigation and adaptation. The decline in the supply of high-quality crude oil has further increased the urgency to identify alternative energy resources and develop energy conversion technologies that are both environmentally sound and economically viable. Various routes for converting renewable energies have emerged – including energy conservation and energy-efficient technologies. The energy industry currently lacks an infrastructure that can completely replace fossil fuels in the near future. At the same time, energy consumption in developing countries like China and India is rapidly increasing as a result of their economic growth. It is generally recognized that the burning of fossil fuels will continue until an infrastructure for sustainable energy is established. Therefore, there is now a high demand for reducing greenhouse gas emissions from fossil fuel–based power plants. Adaptation is a pragmatic approach to deal with the facts of climate change so that life, property, and income of individuals can be protected. The pursuit of sustainable energy resources has become a complex issue across the globe. The Handbook on Climate Change Mitigation and Adaptation is a valuable resource for a wide audience who would like to quickly and comprehensively learn the issues surrounding climate change mitigation.

Why This Book Is Needed There is a mounting consensus that human behaviors are changing the global climate and that its consequence, if left unchecked, could be catastrophic. The fourth climate change report by the Intergovernmental Panel on Climate Change (IPCC 2007) has provided the most detailed assessment ever on climate change’s causes, impacts, and solutions. A consortium of experts from 13 US government science agencies, universities, and research institutions released the report Global Climate Change Impacts in the United States (2009), which verifies that global warming is primarily human induced and climate changes are underway in the USA and are only expected to worsen. From its causes and impacts to its solutions, the issues surrounding climate change involve multidisciplinary sciences and technologies. The complexity and scope of these issues warrants a single comprehensive survey of a broad array of topics, something which the Handbook on Climate Change Mitigation and Adaptation achieves by providing readers with all the necessary background information on

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the mitigation of climate change. The handbook introduces the fundamental issues of climate change mitigation in independent chapters rather than directly giving the detailed advanced analysis presented by the IPCC and others. Therefore, the handbook will be an indispensable companion reference to the complex analysis presented in the IPCC reports. For instance, while the IPCC reports give large amounts of data concerning the impacts of different greenhouse gases, they contain little discussion about the science behind the analysis. Similarly, while the IPCC reports present large amounts of information concerning the impacts of different alternative energies, the reports rarely discuss the science behind the technology. There is currently not a single comprehensive source that enables the readers to learn the science and technology associated with climate change mitigation.

Audience of the Handbook Since the handbook covers a wide range of topics, it will find broad use as a major reference book in environmental, industrial, and analytical chemistry. Scientists, engineers, and technical managers in the energy and environmental fields are expected to be the primary users. They are likely to have an undergraduate degree in science or engineering with an interest in understanding the science and technology used in addressing climate change and its mitigation.

Scope This multivolume handbook offers a comprehensive collection of information on climate change and how to minimize its impact. The chapters in this handbook were written by internationally renowned experts from industry and academia. The purpose of this book is to provide the reader with an authoritative reference work toward the goal of understanding climate change, its effects, and the available mitigation and adaptation strategies with which it may be tackled: • • • • • • •

Scientific evidence of climate change and related societal issues The impact of climate change Energy conservation Alternative energy sources Advanced combustion techniques Advanced technologies Education and outreach

This handbook presents information on how climate change is intimately involved with two critical issues: available energy resources and environmental policy. Readers will learn that these issues may not be viewed in isolation but are mediated by global economics, politics, and media attention. The focus of these presentations will be current scientific technological development although societal impacts will not be neglected.

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References Antilla L (2005) Climate of scepticism: US newspaper coverage of the science of climate change. Global Environ Change Part A 15(4):338–352 Becken S (2005) Harmonising climate change adaptation and mitigation: the case of tourist resorts in Fiji. Global Environ Change Part A 15(4):381–393 Ehrlich PR (2000) Human natures: genes cultures and the human prospect B&T. Island Press, Washington, DC. ISBN 978-1559637794 Folland CK, Karl TR, Nicholls N, Nyenzi BS, Parker DE, Vinnikov KYA (1992) Observed climate variability and change. In: Houghton JT, Callander BA, Varney SDK (eds) Climate change, the supplementary report to the IPCC scientific assessment. Cambridge University Press, Cambridge, pp 135–170 Greitemeyer T (2013) Beware of climate change skeptic films. J Environ Psychol 35:105–109 Grothmann T, Patt A (2005) Adaptive capacity and human cognition: the process of individual adaptation to climate change. Global Environ Change Part A 15(3):199–213 Haberle RM, Forget F, Head J, Kahre MA, Kreslavsky M, Owen SJ (2012) Summary of the Mars recent climate change workshop NASA/Ames Research Center. Icarus 222(1):415–418 Hamin EM, Gurran N (2009) Urban form and climate change: balancing adaptation and mitigation in the U.S. and Australia. Habitat Int 33(3):238–245 Hoffmann VH, Sprengel DC, Ziegler A, Kolb M, Abegg B (2009) Determinants of corporate adaptation to climate change in winter tourism: an econometric analysis. Global Environ Change 19(2):256–264 Intergovernmental Panel on Climate Change (IPCC) (2007) IPCC fourth assessment report: climate change 2007 (AR4), vol 3. Cambridge University Press, Cambridge International Energy Association IEA (2009) World energy outlook 2009. International Energy Association (IEA), Paris. ISBN 9789264061309 IPCC (2010) Special Report on Emission Scenarios (SRES). http://www.grida.no/climate/ipcc/ emission/ IPCC (2010) Intergovernmental panel on climate change. http://www.ipcc.ch/ IPCC (2013) Climate change 2013: the physical science basis, summary for policymakers. http:// www.ipcc.ch/report/ar5/wg1/ IPCC IPCC third assessment report, chap 2.3.3 was there a “Little ice age” and a “Medieval warm period”? http://www.grida.no/publications/other/ipcc_tar/?src=/climate/ipcc_tar/wg1/070.htm Jim Perry (2015) Climate change adaptation in the world’s best places: A wicked problem in need of immediate attention, Landscape and Urban Planning, 133:1–11 Karl TR, Trenberth KE (2003) Modern global climate change. Science 302(5651):1719–1723 Laukkonen J, Blanco PK, Lenhart J, Keiner M, Cavric B, Kinuthia-Njenga C (2009) Combining climate change adaptation and mitigation measures at the local level. Habitat Int 33(3):287–292 Le Houérou HN (1996) Climate change, drought and desertification. J Arid Environ 34:133–185 Linden HR (1993) A dissenting view on global climate change. Electron J 6(6):62–69 Linden HR (2005) How to justify a pragmatic position on anthropogenic climate change. Ind Eng Chem Res 44(5):1209–1219 McMichael AJ, Powles JW, Butler CD, Uauy R (2007) Food, livestock production, energy, climate change, and health. Lancet 370:1253–1263 Miller FP, Vandome AF, McBrewster J (eds) (2009) History of climate change science. Alphascript, Mauritius. ISBN 978-6130229597 Næss LO, Bang G, Eriksen S, Vevatne J (2005) Institutional adaptation to climate change: flood responses at the municipal level in Norway. Global Environ Change Part A 15(2):125–138 Quadrelli R, Peterson S (2007) The energy-climate challenge: recent trends in CO2 emissions from fuel combustion. Energy Policy 35(11):5938–5952 Sonnabend G, Sornig M, Schieder R, Kostiuk T, Delgado J (2008) Temperatures in Venus upper atmosphere from mid-infrared heterodyne spectroscopy of CO2 around 10 μm wavelength. Planet Space Sci 56(10):1407–1413

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Stern N (2007) The economics of climate change: the stern review. Cambridge University Press, Cambridge. ISBN 978-0521700801 Stringer LC, Dyer JC, Reed MS, Dougill AJ, Twyman C, Mkwambisi D (2009) Adaptations to climate change, drought and desertification: local insights to enhance policy in southern Africa. Environ Sci Policy 12(7):748–765 United Nations (UN) (1992) United framework convention on climate change. United Nations, Geneva van Aalst MK, Cannon T, Burton I (2008) Community level adaptation to climate change: the potential role of participatory community risk assessment. Global Environ Change 18(1): 165–179 Winter DF (1967) Transient radiative heat exchange at the surface of the moon. Icarus 6 (1–3):229–235 Worldbank (2009) Attitudes toward climate change: findings from a multi-country poll. http:// siteresources.worldbank.org/INTWDR2010/Resources/Background-report.pdf Zasova LV, Ignatiev N, Khatuntsev I, Linkin V (2007) Structure of the Venus atmosphere. Planet Space Sci 55(12):1712–1728

Loss and Damage Associated with Climate Change Impacts Linta M. Mathew and Sonia Akter

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Definition of Loss and Damage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conventions and Treaties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Loss and Damage in Vulnerable Countries Initiative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Warsaw International Mechanism for Loss and Damage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Approaches to Address Loss and Damage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Monetary Versus Nonmonetary Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Insurance Versus Compensation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Attribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Empirical Evidence of Loss and Damage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Global Estimate of Loss and Damage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Country-Specific Evidence of Loss and Damage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The impacts of climate change that are not mitigated, or appropriately adapted or coped with, are referred to as “loss and damage.” The global community has recently recognized that addressing and financing the “residual” loss and damage from climate change requires a different approach as such costs cannot or have not been appropriately mitigated or adapted to. Although international pressures to weigh a country’s contribution to climate change financing against their contribution to climate change has been proposed, no such legally binding climate change L.M. Mathew • S. Akter (*) Social Sciences Division, International Rice Research Institute, Los Baños, Laguna, Philippines e-mail: [email protected]; [email protected]; [email protected]; [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_55

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deals have been fashioned. Most parties have only agreed to nonbinding actions to either reduce emissions or finance loss and damage in low-income, vulnerable countries. This is because the concept of loss and damage and the approaches to address the concept have been widely contested and debated. Additionally, the lack of a global consensus on an appropriate mechanism to attribute gradual and extreme natural calamities to climate change has further intensified the debate. Given this background, this chapter seeks to synthesize the key issues surrounding this debate. The objectives of this chapter are to review the definitions of loss and damage, examine the evolution of its significance in the international climate politics, present a comparative analysis of the approaches to address climate change-induced loss and damage, and outline empirical evidence of loss and damage in geographically and economically vulnerable nations.

Introduction In its effort to combat climate change, the global community focused on rapid reduction of greenhouse gases (GHGs) by implementing enhanced mitigation efforts from the early 1990s to the mid-2000s. By the mid-2000s, scientific evidence indicated the likelihood of global temperature rising between 3  C and 4  C above the preindustrial level within this century (IPCC 2007a). This evidence suggested that mitigation efforts alone will not be sufficient to avoid climate change as some of the climate change impacts may already have started to take effect. Although steep cuts in global GHGs could stabilize atmospheric GHG concentrations at lower levels than under the status quo, they likely would be above the current levels, thus resulting in further rises in global temperatures. The projected impacts of a 3–4  C temperature rise would lead to serious consequences for humans and ecosystems due to dangerous sea-level rise, unprecedented heat waves, severe drought, and major floods in many parts of the world (IPCC 2007a). Once it became clear that mitigation efforts would be insufficient to avoid all climate change impacts, adaptation became a necessary complement to mitigation (Ott et al. 2008). Adaptation was defined by the Intergovernmental Panel for Climate Change (IPCC) (2007b) as “adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects, which moderates harm or exploits beneficial opportunities.” As of 2007, global adaptation cost estimates ranged from $4 billion to well over $100 billion a year (Parry et al. 2009). These estimates led to the establishment of the Green Climate Fund (GFC) in Durban, South Africa, in 2011 during the 16th session of the Conference of Parties (COP), with the objective of raising a minimum of $100 billion/year by 2020 to support sustainable and climate-resilient development (Institute for Policy Studies 2014; Green Climate Fund 2014). This came to be known as the “adaptation fund.” However, adaptation also appeared to have its limit. It became increasingly apparent that adaptation cannot successfully contain all the adversities invoked by climate change. Such remnants of the adverse effects of climate change came to be

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known as “residual loss and damage.” Widespread international understanding and agreement on the distinction between adaptation and loss and damage was deemed essential in recognizing that not all adversities of climate change can be successfully mitigated or adapted to. Such remnants of the ill effects of climate change impacts were forecasted to account for two-thirds of all potential impacts across all sectors over the longer term (Parry et al. 2009). This recognition highlighted the need to allocate adequate compensation and relief efforts, above and beyond the GCF, to help the victims of loss and damage in geographically and economically vulnerable countries. The term loss and damage appeared in the United Nations Framework Convention on Climate Change (UNFCCC) negotiations in 2007 at COP 13, where the Bali Action Plan called for enhanced action on adaptation including the consideration of “disaster risk reduction strategies and means to address loss and damage associated with climate change impacts in vulnerable countries” (Roberts 2012). Loss and damage was recognized as a separate concept from adaptation in 2008, when the Alliance of Small Island States (AOSIS) proposed a Multi-Window Mechanism to address and finance the distinct concept of loss and damage due to climate change impacts. This was followed by the establishment of the UNFCCC Work Program on Loss and Damage in 2010 and the Warsaw International Mechanism on Loss and Damage in 2013. In addition, the Loss and Damage in Vulnerable Countries Initiative was formed in 2012, with the aim of understanding both the national context and the range of accessible implementation options for addressing loss and damage (Roberts 2012). However, no official lifetime commitment by developed countries to provide funds to the vulnerable communities has been undertaken as yet. Hence, the initiatives could be seen as weak attempts by the rich countries to admit liability for their contributions to climate change. In this chapter, we synthesize the debates surrounding the classification of loss and damage and also uncover the issues around an appropriate compensation mechanism. The purpose of the chapter is to not add to the already substantive literature on loss and damage but to provide a review of the concept, historical treaties and conventions that finally led up to increased international focus on the issue, and the empirical heterogeneity in its estimate and impact across a multicountry sample. The remainder of this chapter is structured as follows: section “Definition of Loss and Damage” provides an in-depth examination of the definition and debates surrounding the concept of loss and damage. Section “History” accommodates a study of the international conventions and treaties on climate change and examines the gradual recognition of the need to address loss and damage in the international climate politics. This is followed by a discussion in section “Approaches to Address Loss and Damage” of the different approaches in addressing loss and damage such as monetary versus nonmonetary costs and insurance versus compensation. Finally, section “Empirical Evidence of Loss and Damage” provides empirical evidence of the global and international estimates of loss and damage as well as multi-country evidence of loss and damage experienced by some of the most geographically and economically vulnerable countries in the world.

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Definition of Loss and Damage A widely accepted definition of loss and damage does not exist. The framing of the definition and its conceptual discussion continue to evolve within the UNFCCC and the academic literature with different groups displaying heterogeneous understanding of the terminology and concept. The UNFCCC defined the concept as one of the “impacts associated with climate change in developing countries that negatively affects human and natural systems” (UNFCCC 2012). However, the definition offered by the UNFCCC was found to be at its nascent stages and was therefore found to lack much clarity. This led to the formation of the Loss and Damage for Vulnerable Countries Initiative in 2012, headed by the Government of Bangladesh, to understand the meaning of the concept and how it can be approached in vulnerable countries (Roberts 2012). The UNFCCC and Warsaw International Mechanism for Loss and Damage act as guides to the initiative. Loss was defined by the Loss and Damage in Vulnerable Countries Initiative, as the “negative impacts that cannot be repaired or restored (such as loss of geological freshwater sources related to glacial melt or desertification),” whereas damage was defined as the “negative impacts that can be repaired or restored (such as windstorm damage to the roof of a building).” Therefore, the Loss and Damage in Vulnerable Countries Initiative views loss and damage as the avoidable and the unavoidable costs associated with climate change impacts. The Loss and Damage in Vulnerable Countries Initiative definition also identified the need to include “the full range of climate change related impacts from (changes in) extreme events to slow onset process and combinations thereof.” This definition included a continuum of climate change events and not only the extreme calamities resulting from climate change. The UNFCCC’s Working Program on Loss and Damage called for a similar attempt to investigate a range of tools and approaches to address all forms of loss and damage resulting from climate change, ranging from slow onset to extreme weather conditions (UNFCCC 2012). However, the convention itself does not define loss and damage as the Work Program, which again indicates the lack of consistency and clarity of the concept. Another working definition of loss and damage, compiled by Action Aid (2010), characterized loss and damage as consequences of the adverse effects of climate change that cannot be (or have not been) adapted to. This gave rise to the ideology of “residual” loss, i.e., unavoidable and unavoided loss and damage and recognized that certain aspects of climate change cannot be appropriately adapted to, given the limited resources available by many of the vulnerable nations affected by climate change. Action Aid (2010) summarized different categories of loss and damage, of which unavoided and unavoidable loss and damage were regarded as residual loss and damage (Table 1). Unavoided costs can also be classified as the “avoidable costs of loss and damage,” i.e., the costs of climate change impacts that can be avoided through appropriate mitigation and/or adaptation. However, such costs are not always avoided due to limited capacity or resource. It is very important to regionally and internationally allocate appropriate resources, such that the resulting loss and

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Table 1 Avoided, unavoided, and unavoidable damage Avoided damage Avoidable damage avoided Damage prevented through mitigation and/or adaptation measures

Unavoided damage Avoidable damage and loss not avoided Where the avoidance of further damage was possible through adequate mitigation and/or adaptation, but where adaptation measures were not implemented due to financial or technical constraints

Unavoidable damage Unavoidable damage and loss Damage that could not be avoided through mitigation and/or adaptation measures, e.g., coral bleaching, sea-level rise, damage due to extreme events where no adaptation efforts would have helped prevent physical damage

Source: Action Aid (2010)

damage can be reduced or mitigated completely. In least developed countries (LDCs), this often implies that such resulting loss and damage will only be adapted to if national benefits from adaptation exceed national losses and damages. Therefore, the loss and damage resulting from slow onset events and its victims events are often ignored1. This remains to be one of the major, but often sidelined, issues in the international climate change debate. Additionally, even in the case of unavoidable loss and damage, appropriate financing/funding still remains to be a problem. This is due to the “attribution problem” in climate change science, which can be briefly described as the inability to completely underpin the loss and damage due to weather-related events to climate change2. A technical representation of residual (unavoidable and unavoided) loss and damage was compiled by Rothman et al. (2003). This is represented in Fig. 1, where residual unavoidable and unavoided impacts of climate change with adaptation are demonstrated by the dotted line. Unavoidable and unavoided residual loss and damage reflects ill effects that have not been mitigated and which cannot/have not been adapted to. One must also note that for stakeholders to undertake adaptation measure, the benefits from adaptation (“effect of adaptation”) must be greater than adaptation costs. Although the diagram above seems straightforward enough, the effects of adaptation and the impact of climate change (its cost) are quite hard to calculate and reproduce in such a simple two-dimensional linear frame. Another schematic representation of the residual damage as compiled by Parry et al. (2009) is presented in Fig. 2. Figure 2a represents the short-term nonlinearity of climate change impacts. Lower adaptation costs are associated with higher avoided damage, therefore giving it a low incremental adaptation cost to avoided damage ratio. This curve is estimated to fluctuate greatly across sectors and gives one a clearer picture of the variability and nonlinearity of such a concept. Figure 2b represents a longer time period of adaptation to damage, which illustrates that over the longer term, all damages will

For more information on this, refer to section “Empirical Evidence of Loss and Damage.” This “attribution problem” and the resulting financing issue will be examined in greater detail in section “Approaches to Address Loss and Damage.”

1 2

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Fig. 1 Traditional representation of climate impacts and adaptation (Source: Rothman et al. (2003))

not be adapted to, due to its lack of economic viability or structural feasibility (Parry et al. 2009). The above representation also considers the trend in damage due to asset growth, therefore normalizing asset damage, such that the increase in damage is not associated with an asset growth. The impact of loss and damage should be narrowed down to the ones that can be attributed to climate change. This can be accomplished by attempting to distinguish between bad weather and natural calamities that can be attributed to climate change. However, the lack of traceability of such events to climate change has induced reluctances by many stakeholders to officially commit to any binding financial agreements. This is commonly referred to as the “attribution problem” in climate science. Various methods of calculating the odds of relating extreme natural calamities to climate change have been devised to aid the allocation of climate changerelated funds (Hulme et al. 2011). One such event attribution, termed as the probabilistic event attribution, compiled by Stone and Allen (2005), seeks to differentiate between weather changes caused as a result of human interference and “bad luck” (Hulme et al. 2011).

History This section presents a history of evolution of the concept of loss and damage including the formation of the Loss and Damage in Vulnerable Countries Initiative and the Warsaw International Mechanism for Loss and Damage.

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Fig. 2 Avoided damages and residual costs over the short term and long term (Source: Parry et al. (2009))

Conventions and Treaties Various conventions and treaties were established over the years starting from 1979, which led up to the formation of the IPCC in 1988, followed by the creation of the UNFCCC in 1992. The role of the IPCC is to “assess on a comprehensive, objective, open and transparent basis the scientific, technical and socio-economic information relevant to understanding the scientific basis of risk of human-induced climate change, its potential impacts and options for adaptation and migration” (IPCC 2007b). The scientific evidence on climate change, gathered by the IPCC, underlined the severity of the issue and played a major role in the creation of the UNFCCC (IPCC 1995). The UNFCCC was formed to work to limit average global temperature increases and the resulting climate change and to cope with the unavoidable loss and

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damage (UNFCCC 2014e). A summary of the major climate change conventions and treaties, post the initiation of the UNFCCC, is presented in Table 2.

Loss and Damage in Vulnerable Countries Initiative The Loss and Damage in Vulnerable Countries Initiative was commenced by the Government of Bangladesh and expanded with the help of the Climate and Development Knowledge Network (CDKN), which appointed a consortium of specialists including Germanwatch, United Nations University Institute for Environmental and Human security (UNU EHS), International Centre for Climate Change and Development (ICCAD), and Munich Climate Insurance Initiative (MCII) and was implemented from 2012 (Loss and Damage in Vulnerable Countries Initiative 2014). The Loss and Damage in Vulnerable Countries Initiatives are to: Understand the scope and significance of loss and damage associated with the adverse impacts of climate change; Developing and cocreating an approach and vision for loss and damage among decision makers and relevant stakeholders; Assisting least developed countries and other vulnerable countries to develop a coherent approach to the loss and damage debate; Identifying and beginning to take necessary steps to support a paradigm shift on loss and damage in the coming years; Source: Loss and Damage in Vulnerable Countries Initiative (2014)

The activities of the UNFCCC and Warsaw International Mechanism for Loss and Damage guide the initiative. The initiative follows four main activity areas to support less developed nations in their plight to reduce and mitigate loss and damage due to climate change impact and to “create momentum in the climate change debate” (Loss and Damage in Vulnerable Countries Initiative 2014). These activities include supporting and strengthening the position of LDCs in loss and damage negotiations in the UNFCCC Work Program on loss and damage, conceptually framing loss and damage and providing policy assistance, providing country-specific insights on the adverse effects of loss and damage, and imparting the cumulative results of mitigation and adaptation efforts in Bangladesh as an analytical tool for other vulnerable countries.

Warsaw International Mechanism for Loss and Damage The Warsaw International Mechanism for Loss and Damage was established to address the loss and damage due to climate change, including “extreme and slow onset events” in economically and geographically vulnerable countries (UNFCCC 2013). Two-year work plans were drawn up for the initiative during the resumed initial meeting in September 2014, which involved understanding the concept of loss and damage of extreme and slow onset events, risk management, comprehending the

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Table 2 Precedent conventions and treaties Year 1992

Key event(s) AOSIS proposal for an insurance scheme

1995

The first Conference of Parties (COP 1): Berlin Mandate

1997

COP 3: Kyoto Protocol Adoption

2001

COP 7: Marrakesh Accords

2005

Meeting of the Parties to the Kyoto Protocol (MOP 1)

Description Proposal for an insurance scheme was put forward by the members of the Alliance of Small Island States (AOSIS), the principle objective of which was to create an International Climate Fund and an International Insurance Pool to finance measures and to provide appropriate financial insurance respectively to counter the adverse effects of climate change. However, the parties only agreed to the insurance pool 10 years onward, provided that over the 10-year period, the “rate of global mean sea-level rise will have reached an agreed figure” (Hayes and Smith 1993). The COP1 held in Germany, where the Berlin mandate established the need for developed countries to “take the lead in combating climate change” and for developing countries to achieve sustainable economic growth (UNFCCC 1995). Adoption of the Kyoto Protocol is undertaken in Kyoto, Japan, setting legally binding emission reduction targets. The summit recognized the greater role of developed countries in having historically contributed significantly to greenhouse emissions (through their previously active roles in industrial activity), and therefore placed a’heavier burden’(UNFCCC 2014) on developed nations under the notion of’common but differentiated responsibilities’(UNFCCC 1998). Formation of the Marrakesh Accords, which laid out the rules and details for the implementation of the Kyoto Protocol, set up adaptation methodologies, and formed a technology transfer framework (UNFCCC 2014a). The Kyoto Protocol entered into force as the Russian Federation submitted its compliance (United Nations 2014). Negotiations for the next phase of the protocol under the Ad Hoc Working Group on Further Commitments for Annex Parties under the Kyoto Protocol (AWG-KP), later known as the “Nairobi Work Program,” were also agreed upon. (continued)

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Table 2 (continued) Year 2007

Key event(s) COP 13: Bali Road Map

2008

COP 14: Joint Implementation Mechanism for the Kyoto Protocol

AOSIS proposal of a Multi-Window Mechanism

2009

COP 15: Copenhagen Accord

2010

COP 16: Cancun Adaptation Framework

UNFCCC Work program to address loss and damage

Description Introduction of the Bali Road Map in Bali, Indonesia, which included the “Bali Action Plan.” This plan was envisioned to charter the way toward a post-2012 outcome (UNFCCC 2014e). The Bali Action Plan is divided into categories such as shared vision, mitigation, adaptation, technology, and financing. However, it is to be noted that no significant effort was made to differentiate between adaptation and loss and damage in this stage. A joint Implementation Mechanism for the Kyoto Protocol was initiated. This was described by UNFCCC (2014d) as an initiative that “allows a country with an emission reduction or limitation commitment under the Protocol to earn emission reduction units from an emission reduction or emission removal project in another country with similar commitments”. The Alliance of Small Island States (AOSIS) proposed a Multi-Window Mechanism to address and finance loss and damage from climate change impacts (Alliance of Small Island States 2008). The Copenhagen Accord was developed at COP15 in Copenhagen, Denmark, where developed countries undertook emission reduction and mitigation and adaptation action plan for the period of 2010–2012, pledging $30 billion as start-up finance (UNFCCC 2014e; United Nations 2014). The Cancun Adaptation Framework was formed at COP16, where governments of developed countries pledged comprehensive packages to assist developing countries to deal with climate change (UNFCCC 2014e). The agreements also made the reduction pledges of the countries official, which formed the “largest collective effort to reduce emission in a manually accountable way” (United Nations 2014). The Cancun Adaptation Framework also established a work program to address the loss and damage impacts of climate change in LDCs vulnerable to the adverse effects of climate change (Roberts 2012). (continued)

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Table 2 (continued) Year 2011

Key event(s) COP 17: Durban Platform for Enhanced Action

Green Climate Fund

2012

COP 18: Doha Amendments to the Kyoto Protocol

Loss and Damage Initiative in Vulnerable Countries Initiative

2013

COP 19: Warsaw Outcomes

Description Plans to draw up a new universal climate change agreement by 2015, to deal with the adverse effects of climate change beyond 2020, were formed in Durban, South Africa. This led to the formation of the Durban Platform for Enhanced Action or the Ad Hoc Working Group on the Durban Platform for Enhanced Action (ADP) (UNFCCC 2014e). COP 17 also led to the formation of the Green Climate Fund (GCF), with an aim of raising $100 billion per year in climate financing by 2020 (Institute for Policy Studies 2014). The Doha Amendments to the Kyoto Protocol commenced. This includes new commitments for a second commitment period from January 2010 until December 2020, a revised list of greenhouse gases to be reported by the Parties, and amendments to several articles of the Kyoto Protocol to issues pertaining to the first commitment period (UNFCCC 2014b). Governments also agreed to work speedily toward drafting a universal climate change agreement by 2015 (UNFCCC 2014b). The Doha Convention further addressed international efforts and strengthened international cooperation on loss and damage as a result of climate change (European Commission 2013). Loss and Damage Initiative was implemented in February 2012, with the objective of partnering with vulnerable LDCs and other parties to better understand loss and damage (Roberts 2012). The Decision to progress on the ADP Platform was agreed upon. A rulebook for reducing emissions from deforestation and forest degradation, enhancing the conservation and sustainable management of forests and forest carbon stocks in developing countries (REDD+), establishing a mechanism to address loss and damage from long-term climate change impact, and agreeing on capitalizing the GCF in the second half of 2014, as part of the Warsaw Outcome was undertaken (UNFCCC 2014g).

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current coping and adaptation mechanisms, and drawing up socioeconomically appropriate policies to adapt to monetary and nonmonetary residual losses as a result of climate change (UNFCCC 2014f). The introduction of the mechanism was seen as a “notable step forward” as it allowed to address and implement socioeconomically appropriate policies to deal with the adversities of climate change in vulnerable communities (Warner 2013). The primary roles of the Warsaw International Mechanism are to: Facilitate support of actions to address loss and damage; Improve coordination of the relevant work of existing bodies under the Convention; Convene meetings of relevant experts and stakeholders; Promote the development of, and compile, analyze, synthesize, and review information; Provide technical guidance and support; Make recommendations, as appropriate, on how to enhance engagement, actions, and coherence under and outside the Convention, including on how to mobilize resources and expertise at different levels. Source: UNFCCC (2014f)

Approaches to Address Loss and Damage This section summarizes the different approaches and their challenges for assessing and addressing loss and damage. Monetary and nonmonetary nature of loss and damage is discussed first followed by a range of economic instruments that can be used to address these costs. Finally, the attribution problem which lies at the center of the loss and damage debate is discussed in detail.

Monetary Versus Nonmonetary Costs Climate change invokes both monetary and nonmonetary loss and damage in vulnerable countries. These categories are also known as economic and noneconomic loss and damage. Monetary or economic loss and damage refer to the costs for which economic or monetary estimates are readily available, such as structural damage and crop failure due to flooding3. Nonmonetary losses are those that cannot be measured in monetary or economic terms, such as loss of biodiversity, loss of livelihoods, or number of deaths caused by flooding. As these goods are not traded in the market, the monetary estimates of loss and damage caused to these goods are not readily available, and hence, these items are generally ignored by the loss and damage accounting (Morrissey and Smith 2013). The concept of nonmonetary 3

A wide range of the estimates of the monetary costs from climate change have been estimated in previous studies, the details of which have been covered in section “Global Estimate of Loss and Damage.”

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costs was also highlighted in COP16 in Copenhagen where the parties recognized that all social and environmental loss and damage cannot be adequately captured by monetary measures. However, as such costs are difficult to quantify and monetize, it can be quite problematic to analyze the costs for inaction for such costs. Nonmarket valuation techniques are often used to assign monetary values to the goods and services that are not traded in the market. Many studies, such as “valuing the ocean” study by the Stockholm Environment Institute (SEI), instead of employing market values to decipher loss and damage, monetized the costs of climate change to the ocean by focusing on five areas, namely, fisheries, sea-level rise, storms, tourism, and the ocean carbon sink (Stockholm Environmental Institute 2012). They pinned monetary values on such components by employing two scenarios: low climate change impact scenario, where emissions are reduced quickly, and a high climate change impact scenario, where the global emissions continue to rise for the next few decades (Stockholm Environmental Institute 2012). However, the results of the study were criticized as it only considers variables that can be “realistically altered by humans and can be monetized” (The Guardian 2012). Thus, the study only took into account the avoidable costs of loss and damage from climate change. Therefore, even though some studies have tried to monetize the marketed and nonmarketed goods affected by climate change, not all nonmarketed costs were effectively captured.

Insurance Versus Compensation The concrete proposal put forth by the AOSIS in 2008 highlighting the need to finance a “Multi-Window Mechanism to Address Loss and Damage from Climate Change Impacts” placed the issue of financing loss and damage under the limelight. The proposed mechanism suggested three interdependent components for compensation: (1) insurance, (2) rehabilitation/compensation, and (3) risk management (AOSIS 2008). The insurance component was proposed to manage financial risk from extreme weather events and to provide insurance to countries who cannot find access to insurance. The rehabilitation/compensatory component addressed the progressive unavoidable climate change impacts, such as sea-level rise and ocean acidification. Finally, the risk management component was incorporated for risk assessment and management and to inform the insurance and the rehabilitation/ compensatory component (AOSIS 2008). The insurance option is one where regular payment by an individual to a private or public insurance entity subsists, such that the entity insures against any loss and damage that may be accidentally incurred by the individual. Munich Climate Insurance Initiative (MCII) (2012) stated that “insurance options can support adaptation and risk resilience for extreme weather, but are not appropriate for many, usually slower-onset, climate-induced impacts.” Therefore, insurance was suggested to be an appropriate adaptation measure against unpredictable extreme events and not for predictable, slow onset events (Warner et al. 2012). This is because insurance companies will only be prepared to provide insurance payouts if the loss and damage

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is entirely uncontrolled for and unforeseen. Insurance was suggested to be an adaptation, as opposed to a coping measure, as it reduces the impact of loss and damage and helps a timely recovery in the aftermath of extreme unforeseen calamities (Warner et al. 2012). Insurance policies were found to be an unpopular method of financing loss and damage among the poorer households in geographically and economically vulnerable countries (Gine et al. 2008; Akter 2012). This was attributed to the lack of knowledge and affordability of insurance premiums in such countries. In some cases, coupling microcredit with insurance schemes was seen as a viable option to extend insurance services to low-income households. For instance, in a study conducted by OECD (2005), the Grameen Bima insurance programs in Bangladesh were found to offer insurance with microcredit, where no premiums were required to be a member of the fund, but payments to the fund were bundled with the interest paid on loans. However, the program was seen to be taken up by the middle class, as opposed to the low-income households, as the poor could not afford the premium (OECD 2005). Compensation schemes in the context of loss and damage financing are funds provided by states or institutions to reduce the impact of loss and damage. The compensation option is perceived to be more appropriate than insurance schemes in funding the loss and damage from the gradual and predictable impacts of climate change. Therefore, the loss and damage from gradually occurring predictable events such as rising sea levels and desertification are best funded by states or institutions. However, individuals not insured against unpredictable extreme calamities should be considered for compensation schemes. This includes individuals in the poorer counterpart of the society, who are not able to afford the insurance premiums. Additionally, the lack of sufficient resources in low-income vulnerable countries does not enable appropriate compensation for all. The effectiveness in reducing the impact of loss and damage of such compensation packages depends on the efficiency of state policies and their outreach approach.

Attribution Attributing weather-related range of slow set to extreme calamities to climate change was found to be quite difficult and operates as one of the major limitations in climate change financing. The lack of good traceability measures also provides a good justification for many developed countries to reject liability and therefore fail to make any firm commitments to financing loss and damage in low-income countries. Hence, the following paragraphs examine the effectiveness and limitations of such attribution mechanisms and their potential role in aiding the global community with financing loss and damage from negative climate change impacts. The most popular method in climate change attribution is the examination of another related variable, which is linked to the characteristics of the extreme natural event. This is done as it is difficult to gain insights from examining trends of extremely rare natural calamities (Huggel et al. 2013). However, such studies have

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confirmed the link between some natural calamities and climate change, but not all. Increasingly, studies have identified that the increase in economic damages from extreme events has been attributed to increased “exposed asset values” rather than an increased intensity of extreme natural calamities (Huggel et al. 2013). To this end, Neumayer and Barthel (2011) calculated an actual-to-potential-loss ratio (APLR), which provided a normalization method to measure the economic loss after the onset of a severe natural disaster. Even though no upward trend in normalized loss and damage was found, the authors did not account for mitigation measures, which may have compromised the findings. Additionally, even if the increased loss and damage is accounted to increased asset value, this does not imply that the resulting loss and damage must not be compensated for. Such a finding, if anything, calls for increased insurance or compensation schemes to be implemented by regional and international bodies. However, many limitations in relying on such attribution methods to allocate any loss and damage funds were found such as the unreliability of such methodologies as they are based on climate estimates without climate change, which cannot be logically verified; the inability to accurately predict the percentage of overall risk attributable to human actions; and the undesirable shift in international climate change initiative from adaptation to compensation, if such methodologies are extensively used to allocate the international adaptation finance (Hulme et al. 2011). The lack of good quality data may also affect the accuracy of such measures. However, even though many such objections to attribution measures exist, formulating attribution mechanisms should be encouraged by the international community as it helps to reduce (to some extent) the moral hazard related to adverse events, where individuals will take greater risks (for instance, building houses in flood-prone areas) in the hope of being compensated. However, care must be taken in order to not get carried away by such measures. Successfully implemented techniques can help eradicate such uncertainty, which can aid the international community to identify the victims of climate change and to allocate funds to communities who are essentially negatively affected from climate change. The global community should allocate sufficient funds such that until a clear measure of attribution is found, the civilians experiencing loss and damage, especially in geographically and economically vulnerable countries, as a result of climate change impacts, do not suffer substantially. This was highlighted by the Philippines Senate Present Juan Ponce Enrile who stated that “developing countries like the Philippines should be receiving compensation. . . Instead, however, we are accepting, or worse, being “forced” to avail of loans that are, in the long run, more disadvantageous for the country” (Climate Justice Now 2010).

Empirical Evidence of Loss and Damage This section presents monetary estimates of loss and damage due to climate change impacts both at the global and local level. The first subsection summarizes the global estimates of loss and damage available in the literature. The second subsection

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presents country-specific local estimates of loss and damage from eleven most economically and geographically vulnerable countries in the world. It also outlines the existing loss and damage-coping strategies used by the households in these countries.

Global Estimate of Loss and Damage Various global estimates of loss and damage have been produced over the years. Global monetary estimates of loss and damage can be measured in terms of the social costs of carbon, which is defined as the “net economic costs of damages from climate change aggregated across the globe and discounted to the present” (IPCC 2007). IPCC’s Fourth Assessment Report (AR4) disclosed that the peer-reviewed estimate of the social cost of carbon in 2005 has an average value of US$12/t of carbon dioxide. However, the range from 100 estimates was found to be large ($3–$95/t of carbon dioxide), which demonstrates a substantial degree of disagreement on its measurement (IPCC 2007). Natural disasters are estimated to have doubled from an average of 200/year in 1998 to an average of 400/year in 2008, whereas costs of natural disasters in monetary terms have increased sevenfold (United Nations 2009; cited in Action Aid 2010). Therefore, future estimates of climate change have painted a dull portrait of an impending catastrophe. Monetary values of loss and damage can also be calculated from the overall loss and damage caused by climate change after accounting for certain scenarios of mitigation and adaptation (Action Aid 2010). One such probabilistic estimation method, known as the Policy Analysis for the Greenhouse Effect (PAGE), calculates the regional and global impacts of climate change, social costs of greenhouse gases, and also the cost of abatement and adaptation (UNFCCC 2014d). This model helps one to calculate the economic loss from such climate change adversities. Action Aid (2010) put together a table for global loss and damage under a scenario of no mitigation and the lowest emission scenario proposed by UNFCCC. Adaptation costs were also derived from UNFCCC reports. The costs are accrued over the years 2000–2200 and presented in discounted net present values (NPV). From the analysis presented in Table 3, it was inferred that with respect to the cost of impact, the optimal action is to combine mitigation and adaptation. However, even with successful mitigation, a residual loss of US$275 trillion was found. However, this method of calculation was found to be more appropriate to predict global, as opposed to regional, loss and damage. Regional calculations of loss and damage are mostly obtainable from local insurance estimates. However, such estimates in low-income developing countries may only adumbrate monetary loss and damage to important sectors such as energy and infrastructure and neglect or overlook the loss and damage to most households. In such circumstances, national statistics are ones’ best gamble in obtaining regional loss and damage statistics. Although the calculation of residual loss and damage has been highly debated, as demonstrated by the noteworthy range of the formulated estimates, a common underlying theme of globally increasing loss and damage was found. Additionally, the calculations of monetary loss and damage also suggested that if appropriate

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Table 3 Monetary estimates under “no mitigation” and “mitigation and lowest emission” scenarios

Cost of impact (without adaptation) Cost of impacts (with adaptation) Adaptation costs Mitigation costs

Trillion US$ No mitigation Lower end Mean 270 1,240

Higher end 3,290

170

890

2,340

60

275

760

4

6

9

4 50

6 110

9 170

Lowest emission scenario Lower Higher end Mean end 100 410 1,070

Source: Action Aid (2010)

measures are not taken to constantly curb global emissions, loss and damage, particularly to low-income vulnerable countries, would only increase exponentially over time. Therefore, communities with a higher exposure to the risks of climate change and with lower adaptive capacity would experience a greater burden of loss and damage in comparison to others. Such vulnerable countries include the Alliance of Small Island States (AOSIS), threatened by the rise in sea level, and low-income developing countries, where a large proportion of the population relies on agricultural income, particularly susceptible to climatic fluctuations. Although developed rich nations may experience greater monetary losses from extreme events due to a higher proportion of exposed assets, the loss and damage as a percentage of GDP is peripheral in comparison to the low-income vulnerable nations. This is demonstrated in the figure below which compares the monetary damage to the monetary damage as a percentage of GDP in both developing and developed countries. Figure 3 shows the damages as a percentage of GDP are higher for low-income developing countries than for the developed rich nations. On average, the agricultural sector contributes substantially to a poor developing nations’ GDP, which is particularly vulnerable to the weather changes that have resulted from climate change. Additionally, poorly built infrastructure and households in low-income developing countries are often unable to withstand extreme weather disruptions, causing greater damage as a proportion of GDP in such countries.

Country-Specific Evidence of Loss and Damage Country-level evidence of loss and damage occurring due to climate change impacts in vulnerable countries is crucial in assessing the future risks of climate change in such countries. Table 4 summarizes the environmental and economic vulnerability facing eleven low-income countries due to climate change impacts. The specific nature of the vulnerability, monetary estimate of loss, and damage resulting from unavoidable climate change impacts and coping strategies are summarized in the following paragraphs.

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Fig. 3 Disaster losses, total and as a share of GDP, in the richest and poorest nations, 1985–1999 (Source: United Nations Inter-Agency Secretariat for the International Strategy for Disaster Risk Reduction (2003))

Bangladesh In the case of Bangladesh, it was found that climatic susceptibility along with increased climate change has adverse consequences, especially in the coastal region. Frequent cyclones, such as Sidr in 2007 and Aila in 2009, caused massive loss and damage to the coastal population. Cyclone Sidr claimed 4,234 lives, injured 55,282 people, and damaged 8.9 million people’s livelihood (Ministry of Disaster Management and Relief 2014). The economic damage caused by Cyclone Sidr was equivalent to US$1.67 billion (Ministry of Disaster Management and Relief 2014). Eleven out of the 19 coastal districts were severely affected by Cyclone Aila. It claimed 190 lives, injured 7,000 people, killed 100,000 livestock, and caused US$170 million worth of economic damage (United Nations Development Fund 2010 cited in Akter and Mallick 2013). The loss and damage experienced by a cyclone as powerful as Cyclone Sidr are expected to rise nearly fivefold to over $9 billion by 2050, accounting for 0.6 % of GDP (World Bank 2010). These cyclones forced saline water into the agricultural lands (Rabbani et al. 2013). The rise in sea level, also attributed to global climate change, is expected to push saline water further inland, therefore severely affecting the agricultural productivity and the quality of drinking water in the coastal districts of

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Table 4 Climatic susceptibility, long-term climate change threat, and livelihood impact in the nine disaster-prone areas Climatic susceptibility Cyclones

Country Bangladesh

Region Sathkira

Bhutan

Punakha

Burkina Faso

Sahel

Glacial lake outburst floods Drought

Ethiopia

Gambella

Floods

Gambia

North Bank

Drought

Kenya

Budalangi

Floods

Micronesia

Kosrae

Storms

Mozambique

South/ Central

Floods/ droughts

Nepal

Udayapur

Floods

Pakistan

Baluchistan

Philippines

Tacloban

Flood, glacial lake outbursts Cyclones

Long-term threats Sea-level rise, salinity intrusion Changing monsoon Changing rainfall patterns Changing rainfall patterns Changing rainfall patterns Changing rainfall patterns Sea-level rise, coastal erosion Changing rainfall patterns Changing rainfall patterns Changing rainfall patterns Changing storm intensity

Impacts Rice, drinking water

Rice

Livestock, crops

Habitability, crops, livestock

Agriculture

Livestock, crops, property, disruption of social and economic activities Crops, livestock, fish

Housing, livelihood

Staple crops

Agriculture, transport and communication Lives, agriculture, livestock, and property

Source: Warner and van der Geest (2013) and (Roberts et al. 2014)

Bangladesh (Rabbani et al. 2013). High yielding rice varieties were unable to withstand the increase in soil salinity (Rabbani et al. 2013). New varieties, such as BINA 8 and BRRI 47, henceforth developed after 2009, to resist high-salinity levels, were however found to be inappropriate for the chosen region (Rabbani et al. 2013). It is also estimated that the region incurred a decrease in its rice production by 0.1 million tons between 2008 and 2010. The total cost of loss to rice production due to salinity was estimated to be US $1.9 million from 2009 to 2011. The dangers of massive rural–urban and coastal-central migration looms in the near future if the region continues to experience such frequent calamities.

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Bhutan The district of Punakha is referred to as Bhutan’s “rice bowl,” where a substantial proportion of the population engages in small-scale farming (Kusters and Wangdi 2013). Kusters and Wangdi (2013) conducted a study on this region. A large proportion of the research participants recognized a pattern of unreliable monsoon and overall annual precipitation. This observation was confirmed by rainfall data collected over 1990–2008. This changing water availability was reported to have a negative effect on crop production. Coping measures adopted by the households include ritual performance (costing households between US$700 and US$900 per year), developing or modifying water-sharing arrangements, maintaining irrigation channels, changing cropping pattern, buying irrigation water from upstream villages, and using water pumps. Improved availability of fertilizers and modern technology was found to greatly enhance agricultural productivity for many farmers. Nevertheless, most adaptation measures were not without costs, some of which are monetary and some are nonmonetary. For instance, unsuccessful watersharing arrangements led to local conflicts, disrupting social cohesion. Maintenance of irrigation canals required a substantial contribution, which was typically found to be unaffordable by the poor households, and therefore they were excluded from such water-sharing arrangements. Some farmers changed the cropping pattern from rice to maize resulted in an economic loss equivalent to US$2,000/acre. Even though improved seed varieties and the availability of fertilizers and pesticides led to an overall increase in rice production in the district between 2002 and 2010, this improvement was not uniform across the whole region as poorer households failed to access these inputs. Therefore, the need to promote equal access to agricultural inputs is identified in the study. Additionally, the local officials often perceive the issue of glacial lake outburst floods due to the melting of glaciers and the threat of destabilizing ice-cored dams as a policy priority in comparison to changes in precipitation levels. This allowed them to overlook the problem of gradual changes in water availability, as the effects were less visible and less severe in relation to the impact of floods. Burkina Faso Burkina Faso is a semiarid, landlocked country in western Africa. Ninety percent of its population is engaged in agriculture and livestock sectors (Traore and Owiyo 2013). The high reliance on the agricultural and livestock by a large proportion of the population in the Sahel region of Burkina Faso implied that a substantial proportion of the population is engaged in activities that are weather sensitive. Therefore, their livelihoods depend significantly on climatic conditions. Traore and Owiyo (2013) found draught to be the main climatic stressor in the region. The occurrence of draught was confirmed by rainfall data, which indicated a high variation of rainfall and also a recent history of draught in the Sahel region. Severe negative impact on crop and livestock rearing was reported by a large percentage of the sampled households. Coping measures included reducing food consumption, selling property and livestock, cutting expenditure, receiving external support, migrating, earning extra income, transhumance, and a small proportion of the sample reported resorting

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to begging. Modifying food consumption and selling property were found to be the most popular coping mechanisms. However, from the households that reported to undertake coping mechanism, 71 % indicated that they were still experiencing negative effects of the drought. The destruction caused by the onset of draughts, such as the lack of water for crop yields, led to the unavailability of water for the local people and their livestock, which further limited their future coping and adaptation ability. The range of average crop production loss was reported to be between US$577 and US$636 per household, whereas the range of average livestock loss was found to be between US$1,922 and US$8,759 per herder in the region.

Ethiopia Ethiopia is heavily dependent on rain-fed agriculture. Historically, the country is prone to extreme weather events mostly characterized by highly variable rainfall pattern. Using spatially explicit analyses of climate change effects on selected key sectors of Ethiopia’s economy, Robinson et al. (2013) found that the residual loss and damage might cost an annual average of US$0.4–3.0 billion. A case study was conducted by Haile et al. (2013) in the lowlands of Gambella, Ethiopia. The area experienced frequent river flooding that severely affected its people and their livelihoods. The main source of livelihood of the participants was crop cultivation and livestock rearing. The 2007 extreme flooding severely damaged the crops of three quarters of the respondents of the study and damaged the household properties of a quarter of the respondents. Most of the participants described the effect of the flood as either “very severe” or “disastrous” (Haile et al. 2013). However, unlike in the case of Sahel in Burkina Faso, the ability to relocate livestock ensured a better source of livelihood for the livestock owners as opposed to the farmers, most of who reported that the yield of their next cropping season severely suffered as a result of the floods. Coping mechanisms included relying on assistance from NGOs, social networks, government support, and religious organizations. NGOs and social networks provided support to the largest proportion of the affected households. Nevertheless, the erosive quality of some coping measures is highlighted, where the respondents believed that the goodwill and resources of their reliable contacts will gradually diminish, inhibiting their future coping ability. Hence, the reliance on social networks was not perceived to ensure a long-term adaptation solution. Moreover, a majority of the households who had undertaken preventive measures such as increasing the floor height, harvesting premature crops, and constructing a high stage for livestock were unable to fully evade the negative effects of the 2007 flood. Additionally, as voluntary government resettlement plans are underway, the villagers are questioning its habitability as the new villages are lacking essential services such as health services and potential security. Gambia A study by Njie et al. (2007) estimated the residual damages from climate change in Gambia to range between US$123 million and US$130 million/year in the near term. For the more distant 2070–2099 period, residual damage cost estimated to

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range from US$955 million to US$1.0 billion (Njie et al. 2007). A case study conducted by Yaffa (2013) in severely drought-prone regions of Gambia found that the varying level of rainfall and shorter duration of the rainy season along with rising temperatures implied severe calamity for its community that was mostly reliant on agriculture for their livelihoods. The prominent ill effects incurred by the community included food shortage, rise in food prices and reduction in crop production, and livestock ownership. Similar coping measures, as seen in the previous case studies, were adopted, where most of the measures were seen to aid short-term relief.

Kenya Climate change poses a serious threat to Kenya’s economy. Currently climate change accounts for an approximate monetary loss of approximately US$0.5 billion/year which is equivalent to 2 % of the country’s GDP (Stockholm Environment Institute 2009). This cost is expected to rise and eventually claim 3 % of Kenya’s GDP by 2030 (Stockholm Environment Institute 2009). A forecasted increase in rainfall in Kenya, due to climate change, along with human activities such as deforestation and overgrazing, is speculated to have increased the severity of flooding in the low-lying coastal regions of Kenya (Opondo 2013). The main sources of livelihood in the flood-prone regions are crop cultivation, livestock rearing, and other nonagricultural activities such as fishing, small-scale trade, and manual labor. It was found that more than three fourths of the farmers in the affected region reported that their livelihood had been severely affected by the flooding. Additionally, almost three fourths of all participants from all the occupational and income categories had reported that they were severely affected. The most common coping strategies included reducing food consumption and receiving help from local governments, NGOs, and religious organizations. However, most coping strategies, as in the case of the previous case studies, were found to be short-term solutions and most of such coping mechanisms implied “long term negative effects on the household economy” (Van der Geest and Dietz 2004 cited in Opondo 2013). For instance, undertaking the sale of property implied a reduced household asset base, unfavorable for a longer-term sustainable means of adaptation. Micronesia The case study examined below demonstrates a principal environmental concern of Micronesia as well as other small island states of the Pacific Ocean. Monnereau and Abraham (2013) confirmed that the rising sea level (attributed to climate change) has led to severe coastal erosion in the coastal region of Kosrae and has threatened the livelihood and habitability of many of its inhabitants. A rise in the sea level and coastal erosion is particularly dangerous to such island territories as it leads to a reduction in island size. The study revealed that the households who had adopted coping measures such as building seawalls, reinforcing their homes, and planting trees provided only temporary protection for the local inhabitants and had adverse long-term environmental effects. For instance, the building of sea walls and the

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planting of trees only provided short-term solutions and only protected small sections of coastline. This highlighted the requirement of a large-scale or even state-level investment to provide sufficient barriers for the coastline. However, no initiatives have been successfully implemented to date as previous studies had indicated that the building of sea walls was found to have caused current changes and beach loss. The majority of the participants had indicated that they suffered from the effect of coastal erosion and that the coping strategies pursued was not sufficient to counter its adverse effects.

Mozambique With a large coastline, Mozambique was found to experience severe floods in the lowlands (central), which adversely affected the livelihood of the rural farmers. In the year 2007 itself, Mozambique experienced a total economic loss and damage of $71 million from severe flooding (United Nations Office for Disaster Risk Reduction 2014). Brida et al. (2013) provided an account of the struggle of the community and the coping and adoption measures adopted and their effectiveness. The government of the country undertook resettlement projects, relocating communities to the uplands (south). However, this turned out to be as disastrous to the community as the uplands experienced frequent draughts, forcing many to go back to the lowlands and endure the negative effects of the floods. Crop cultivation, livestock rearing, and fishing were the most prominent sources of income in decreasing order of importance. Overall, a “double blow” from both the floods and the droughts was found to affect the entire sample interviewed, where the greatest ill effect was experienced by the farmers (Brida et al. 2013). As a result of food shortage, food prices increased, therefore further intensifying the adversity. The most prominent coping mechanisms included looking for other sources of income that includes laboring for the better-off households and selling property. However, as seen in previous case studies, such measures did not provide any long-term solutions. Moreover, the government resettlement initiative was found to worsen the situation for many. Nepal Frequent floods are one of the recurrent natural disasters that affect Nepal. Between 1971 and 2007, a staggering amount of 2,500 floods were recorded, which claimed more than 3,000 lives and damaged at least 150,000 buildings. The region of Udayapur in Nepal was found to be particularly susceptible to increasingly severe floods and vulnerable to the impact of climate change (Bauer 2013). The two main rivers in Udaypur reported increased rate of flooding. This was worsened by man-made obstructions such as roads and bridge piers, along with other activities such as deforestation which made the rivers shallower and accelerated sedimentation. Agriculture constituted the largest source of livelihood for many. More than 4/5 of all households reported that their agricultural output has decreased over the past years. Prevention and coping mechanisms undertaken by the farmers such as constructing stonewalls and seeking help from institutions such as NGOs was inadequate to avoid the recurrent loss and damage. Another frequent coping

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mechanism was labor migration to cities and overseas. The relatives of the migrants often relied on their remittances as an extra source of income, but often male migration was associated with increased work load for the women.

Pakistan Flooding and overflowing rivers caused substantial damage to 14 districts, particularly to the southern and northern parts of the district in 2010. It directly affected an estimated 14-20 million people, and killed over 1,700 (Kirsch et al. 2012). The floods also severely affected crops and livestock, where the crops were either partially or completely submerged and the livestock suffered from a lack of fodder availability. A total country-wide loss of US$9.7 billion was expected to have occurred in the agricultural sector (Kirsch et al. 2012). Food insecurity and malnutrition were also reported to have occurred in poorer societies. The average reported household monthly income of the affected community decreased by 50% (Kirsch et al. 2012). National response mechanisms included the use of military-affiliated rescue and aid operations, civil society relief operations included aid and establishment of social welfare infrastructure, and international donor aid and assistance was provided to affected areas (Asian Development Bank 2011). Rebuilding projects are being undertaken with the aim of constructing a flood-resilient society. However, the lack of proper pre-disaster awareness techniques prevents adequate preparation procedures. Therefore, loss and damage due to extreme flooding can almost be perceived as an unavoidable consequence. Additionally, even though civilians were requested to not reside in low-lying areas or near rivers, such a request is unfeasible as most of the rural poor reside in such vulnerable areas. Philippines According to National Disaster Reduction and Management Council (NDRRMC) (2014) 6,201 persons were killed, 28,626 were injured and 1,785 are missing over the entire Philippines in the aftermath of Typhoon Haiyan. The typhoon was the most powerful typhoon to make landfall to date which also caused significant economic damage to infrastructure and property. The damage to infrastructure and agriculture damages were estimated at US$802 million (Mori et al. 2014). Most of the residents were recorded to have taken sufficient coping and adopting mechanisms to frequent storms that hit the country. Local residents were reported to have never experienced a typhoon even remotely as brutal as Haiyan and were therefore defenseless. National and international relief efforts were mobilized post disaster, although the collapse of the local airport slowed down the process. Local inhabitants, with little or no socioeconomic assets and connections, are still known to be suffering from the adversities of the typhoon and were soon after subject to the adversities. After the onset of such a calamity, the Philippines hosted the Conference of United Nations Risk Reduction and Management in Manila to emphasize the importance of an available, accessible, and affordable disaster risk information system as part of the “Post-Haiyan Tacloban Declaration” (The United Nations Office for Disaster Risk Reduction 2014). During the 2013 Warsaw Conference, the Philippine Climate Change Commissioner, Naderev Yeb Sano, fought back tears while warning the

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international community that his country is particularly suffering as a result of climate change, reflecting on the recently acquired news of his family’s safe residence after Typhoon Haiyan (Galarraga and Roman 2013).

Conclusions Loss and damage was recognized as a separate concept from adaptation in 2008, when the AOSIS proposed a Multi-Window Mechanism to address and finance the distinct concept of loss and damage arising due to climate change impacts. This was followed by the establishment of the UNFCCC Work Program on Loss and Damage in 2010 and the Warsaw International Mechanism on Loss and Damage in 2013 to further comprehend and address the issue. The Loss and Damage in Vulnerable Countries Initiative, formed in 2012, was the largest independent entity solely dedicated to building a common understanding of loss and damage. However, despite current global efforts in understanding the concept of loss and damage, the exact definition is still as elusive as ever and is still widely contested among the stakeholders. Additional issues such as distinguishing between avoidable and unavoidable loss and damage, slow onset and extreme events, and monetary and nonmonetary loss and damage were also highlighted in this chapter. Discriminating between such categories of loss and damage from climate change adversities is essential as each category would require a different approach. For instance, in the case of avoidable and unavoidable loss and damage, it was pointed out previously that institutions and individuals must dedicate resources such that avoidable losses and damages can be successfully mitigated or adapted to and unavoidable losses and damages can be appropriately financed. Additionally, the debate regarding the constituents of loss and damage impacts from climate change makes it quite difficult to converge on a global estimate, therefore impeding a concrete commitment to tackle such an adversity. However, a global climate deal is being furnished and will be executed in 2015, where parties have agreed to adhere to a legally binding international climate change deal. Nevertheless, this agreement was only concurred by the EU, some other European nations, and Australia. Although this can be seen as a significant step forward, the lack of commitment by all developed countries still poses a great obstacle in obtaining an ideal climate change deal. The biggest limitation in forming a concrete deal to address loss and damage was found to be the attribution problem. This can be described as lack of solid traceability of adverse weather impacts to climate change, which was found to impede any solid commitments by countries. To resolve the attribution problem, many studies have devised mechanisms to examine the extent to which adverse weather impacts can be attributed to climate change. However, as of now, no globally agreed upon mechanism has been fashioned. Additionally, the degree of impact of loss and damage due to climate change on livelihoods differed substantially across developing and developed countries. On the one hand, civilians in developed countries were mostly insured against the loss and damage from natural calamities or their losses and damages were mostly compensated for, where insurance or compensation policies

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depended on country-specific requirements and regional policies. On the other hand, the poor farmers and livestock owners in vulnerable low-income countries were found to suffer substantially as a result of such climatic changes. Country-specific loss and damage estimates and coping strategies from some of the most economically vulnerable countries have been analyzed in this chapter. The degree to which such adversities affected households depended on their socioeconomic status and geographical location. The livelihood of the poorer farmers and livestock owners was generally seen to be affected the most due to their restricted mobility and limited livelihood options (after a partial/complete destruction of their farms and livestock from extreme natural calamities). Common coping measures for predictable events included modifying food consumption, selling property and livestock, cutting expenditure, receiving external support, and finding extra income sources. However, many of the coping strategies adopted by the locals were seen as temporary and some measures even eroded their long-term coping capacity. Additionally, extreme and unexpected events, such as typhoon Haiyan in the Philippines, addressed the need to identify disaster identification technologies to reduce the loss and damage from such natural calamities. Overall, the case studies of economically and geographically vulnerable countries highlighted the need to identify and implement long-term measures to mitigate loss and damage and the need for active collaboration between international organizations, NGOs, and local governments to draw up cost-effective and feasible policies to combat such residual loss and damage.

Future Directions Future directions for research include extended research work on regional- or countryspecific insurance or compensation schemes for low-income countries, such that financing options that are best suited to address the environmental and social vulnerability of the region can be devised. Additionally, it was found that one of the biggest limitations in the climate change debate was the “attribution problem.” Therefore, such a problem must be appropriately conceptualized and addressed, where better attribution techniques should be thoroughly examined and critiqued, and its applicability to the entire range of slow on set to extreme climatic conditions should be studied.

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Paleoclimate Changes and Significance of Present Global Warming Asadullah Kazi

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Paleoclimate Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ice Core Records of Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Changing Atmospheric Chemical Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Current Climate Change and Global Warming Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Counteracting Present-Day Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Awareness and Mitigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Adaption and Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reversal of Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Earth’s climate has been changing since the conceivable beginning of the geological history of Earth. This is reflected by paleoclimate occurrences of ice ages, followed by consequent warmer interglacial episodes. The most recent ice age has been tentatively traced back to some three million years ago. However, the onslaught of industrial revolution has greatly affected the framework of climate change. Atmospheric carbon dioxide levels are now 40 % higher than before the industrial revolution. This, in turn, has given rise to increase in temperature during the past couple of centuries. Glaciers have recently started melting, and the global average sea level has risen by more than 25 cm. Study of core records from Antarctica and Greenland disclose that paleoclimate ice cores dating back to 800,000 years revealed that the current concentrations of greenhouse gases exceeded the concentration of these gases, preserved in those A. Kazi (*) Isra University, Hyderabad, Sindh, Pakistan e-mail: [email protected]; [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_56

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ice cores. Currently, global warming has emerged as the most serious environmental threat to mankind, and unless a drastic cut is made in the emission of greenhouse gases, the world would be heading toward an unretractable disaster. Consequently, this requires a global approach for development to combat the situation. To start with, there has to be awareness and preparedness, followed by capacity building through community education and training, as well as enforcement of regulations. This approach supports strategy of adaptation to vulnerability reduction and readiness to policy-supporting development, as the future course of action.

Introduction Earth’s climate is a global challenge. It is an ever-changing long-term phenomenon, whose incidence is manifested by repeated ice ages and the corresponding warmer interglacial periods, during paleoclimate episodes, in the geological history of Earth. Incidentally, such glacial and interglacial events occur in a cyclic pattern in conformity with average global temperature. A number of ice ages have occurred throughout Earth’s history; the earliest was over two billion years ago, and the most recent one began approximately three million years ago and is followed by an interglacial stage of events. Earth was warmer than at present for most of this time interrupted by sporadic ice ages (Fig. 1). Carbon dioxide is the primary greenhouse gas resulting from human activities (such as burning fossil fuels for energy and transportation). Incidentally, human activity-derived greenhouse gases are the largest potential cause of global warming. It is reported that there is a direct relationship between the concentration of greenhouse gases, particularly carbon dioxide (CO2) in the atmosphere, and the temperature of Earth, during the past 400,000 years (NOAA 2008) (Fig. 2). It is also important to recognize that CO2, CH4, and NO2 show high concentration during interglacial times and lower concentrations during the glacial episode. The atmosphere already contains over 25 % more CO2 than it had done for the last 160,000 years (Leggett 1990). In his lecture, “Changing Planet: Past, Present, Future – Earth’s Climate back to the Future,” Schrag (2012) portrayed a history of how the Earth’s climate changed over since its birth. Table 1 shades light on sources and buildup of common greenhouse gases and their relative contribution in the atmosphere. Currently, we are in a warm interglacial episode that began about 11,000 years ago. The main question that worries us is what if the continuing buildup of greenhouse gases in the atmosphere, resulting in the warm-up of Earth, would lead to abundant melting of ice? And if so, what needs to be done to circumvent this impending devastation? NASA (2014) is preparing to launch a satellite to measure atmospheric concentrations of CO2, a greenhouse gas that contributes almost 55 % to global warming (Table 1). It is stated that CO2 levels have reached their highest concentration in the

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Fig. 1 Time history of five major ice ages of Earth’s history (Adapted from Saltzman (2002), and Eldredge and Biely (2010))

Fig. 2 Temperature change and carbon dioxide change observed, in ice core records (Adapted from NOAA (2008))

past 800,000 years or so. In the northern hemisphere, it has reached 400 parts per million by volume (ppmv), for the first time in human history. This level is 40 % up since the wide use of fossil fuels began with the industrial revolution. The World Meteorological Organization expects the global average concentration to be above 400 ppmv in 2015–2016. Rising concentration of this heat-trapping gas raises risks of more heat waves, droughts, and rising sea level. It may be mentioned that during the last 800,000 years, the level of atmospheric CO2 fluctuated between 180 and 280 ppmv and has probably not been above 400 ppmv. The UN panel of experts, on greenhouse gas, suggested that the concentration of CO2 gas would have to be kept below 450 ppmv to give a good chance of achieving less than 2  C increase in global temperature, before the end of this century.

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Table 1 The common greenhouse gases, their origins, rates of buildup in the atmosphere, and their contribution to global warming in the 1980s (Source: Leggett 1990)

Gas Carbon dioxide (CO2)

Chlorofluorocarbons (CFCs) and related gases (HFCs and HCFCs) Methane (CH4)

Nitrous oxide (N2O)

Principal sources Fossil fuel burning (77 %), deforestation (23 %) Various industrial uses: refrigerants, foamblowing solvents Rice paddies, enteric fermentation, gas leakage Biomass burning, fertilizer use, fossil fuel combustion

Current rate of annual increase and concentrationa 0.5 % (353 ppmv)

Contribution to global warming (%) 55

4 % (764 pptv)

24

0.9 % (1.72 ppmv)

15

0.8 % (310 ppbv)

6

a

ppmv parts per million by volume, ppbv parts per billion by volume, pptv parts per trillion by volume

Human activities are altering the carbon cycle, both by adding more CO2 to the atmosphere and by influencing the ability of natural sinks, like forests and oceans, which absorb and trap (capture) CO2 and keep the temperature rise within permissible limits. Slightly different values of greenhouse gas contribution to global warming are quoted by the UN Framework Convention on Climate change (UNFCCC) (1992). Nevertheless, estimated contribution of greenhouse gases to global warming, during the last 100 years, as reported by the UNFCCC is as follows: CO2

66%; CH4

23%; CFC’s

8%; N2 O

3%:

Comparing these concentrations with those in 1980s, by UNFCCC, reveals that in terms of contributions to global warming, CO2 has increased by 17 %, CH4 has decreased by 5 %, HCFCs increased by 6 %, and NO2 increased by 3 %. The increase in the magnitude of CO2 can obviously be attributed to higher consumption of fossil fuels in the energy mix; United States, China, and India, among others, are the countries that make the maximum use of fossil fuels in the energy sector of their strong economies.

Paleoclimate Perspective Carbon dioxide, as described above, is a major greenhouse gas, which contributes to Earth’s global warming leading to climate change. Paleoclimate sources of information, leading to an assessment of conditions that prevailed during the life history of Earth, are important in predicting likely climatic changes in the future (Fig. 3). Research in the study of ice cores drilled in Greenland and Antarctica provides much-needed information about variations in past temperatures and composition of

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Fig. 3 Climatic changes during glacial and interglacial episodes of the history of Earth

atmospheric gases such as CO2, NO2, and CH4, as well as many other aspects of the global environment. It is also understood that, among other things, the warming of glacial periods is essentially synchronized by gradual shift in Earth’s rotation (USEPA 2014a; Hansen and Sato 2011). However, changes in climate change are accompanied mainly by changes in CO2, NO2 and CH4, leading to changes in the temperature.

Ice Core Records of Temperature Crucially, the ice cores enclose small bubbles of air in the atmosphere, and from these, it is possible to measure the past concentration of gases. According to briefings of British Antarctic Survey (BAS), pertaining to “ice cores and climate change,” the oldest ice core records extend to 123,000 years in Greenland and 800,000 years in Antarctica. The longest ice cores lengthen to 3 km in depth. Analysis of these ice core records reveals details of Earth’s past climate and is, therefore, useful in recreating long-term records of temperature as well as other environmental counterparts that allow us to explore the past climate. It may be pointed out that in the instance of temperature, no direct measurement of temperature is available (www.climatedata.info, 2010). However, the ratio of heavy oxygen (18O) to light oxygen (16O) is helpful in elucidating climate changes, which occurred in the past. Water molecules, containing light oxygen, evaporate easily as compared to water molecules containing heavy oxygen atom. At the same time, water vapor molecules, containing the heavy oxygen, condense more easily. Furthermore, the concentration of 18O in precipitation decreases with temperature. As shown in Fig. 4, the difference in 18O concentrations in annual precipitation, compared to

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Fig. 4 Concentration of 18O decreases with temperature (Adapted from Jonzel et al. (1994))

the average annual temperature, at the present-day ice-capped locations is fairly obvious. As explained in the feature articles of NASA (paleontology: the oxygen balance), air cools by moving toward the poles, and the moisture begins to condense and falls as precipitation. Initially, the rain contains a higher ratio of water made of heavy oxygen molecules, which condense more easily than water vapor containing light oxygen. The remaining moisture in the air becomes depleted in of heavy oxygen, as the air continues to move toward colder upper latitudes. Consequently, the falling rain or snow now is made up of more water-containing light oxygen. Less heavy oxygen in the frozen water means that temperatures were cooler. According to NASA (2010), the Earth moved out of ice ages, over the past millions of years; the glacial temperature rose by a total of 4–7  C, over approximately 5,000 years. The stage of changes in temperature and CO2 across glacial–interglacial episodes in the past is consistent with the proposition that CO2 acts as an important amplifier of climate changes in the natural system (Wolff 2011). In the past century alone, the temperature in response to increase in CO2 has climbed 0.7  C, which is roughly 10 times faster than the average rate of ice age recovery warming. This leaves many questions to answers in the context of the present global warming.

Changing Atmospheric Chemical Composition Unlike temperature, the ice cores allow direct measurements of atmospheric gases, like carbon dioxide and methane. The fastest natural increase in carbon dioxide (CO2) and methane (CH4), measured in older ice cores, is 20 parts per million by

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volume, in 1000 years. This is seen as the order of magnitude during Earth’s emergence from the last ice age, around 12,000 years ago. The concentration of carbon dioxide (CO2) increased in the last two centuries by the same amount. Similarly, methane (CH4) also shows unprecedented increase in concentration over the last 200 years. Its concentration is now much more than double its preindustrial levels. Nitrous oxide (NO2) is yet another constituent which increased from a preindustrial concentration of about 265 ppb to the present-day value of 319 ppb (Forster et al. 2007). Atmospheric CO2 levels are now 40 % higher than before the industrial revolution (British Antarctic Survey 2014). The increase in the magnitude of global temperature is crucially important as it is proportional to increase in CO2. UN Secretary-General, Ban Ki-moon (2013), pointed out, “We must limit global temperature rise to 2 . We are far from there, and even that is enough to cause dire consequences. If we continue along current path, we are close to 6 increase.” At the end of most interglacial episodes, NO2 remains considerably longer on interglacial levels than methane. This is substantiated by studies on glacial–interglacial and millennial scale variations in the atmospheric NO2 concentrations during the last 800,000 years (Schilt et al. 2010). Furthermore, it is noted that increase in the nitrous (NO2) concentration starts before the onset of the warming period (Fl€uckiger et al. 2004).

Current Climate Change and Global Warming Perspective Global warming, resulting from climate change, has emerged as the most serious environmental threat, suggesting that the mankind is heading for deep trouble unless a drastic cut is made in emission of greenhouse gases into the atmosphere. In a report by the Intergovernmental Panel on Climate (IPCC), a body set by the UN General Assembly in 1988, emissions resulting from human activities are substantially increasing the atmospheric concentration of greenhouse gases. If this increase in the greenhouse gas continued at the present rates, the world average temperature will rise by one degree centigrade or thereabouts within just 30 years.

Counteracting Present-Day Climate Change From the human point of view, “if you change climate, you change everything.” It is, therefore, pertinent to build a future in which humans live in harmony with nature. Table 2 presents a summary of the potential of greenhouse gases and the effects that occur over a period of about 100 years, after a particular mass of a gas is emitted (USEPA 2014c). Some gases stay longer in the atmosphere than others. Indeed, there is no doubt that there is a climate change, and part of this change is caused by human activities (Cook et al 2013). But, is the part played by humans significant enough to bring about change in the natural glacial–interglacial cycle of episodes, prior to the existence of humans on the Earth?

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Table 2 Major long-lived greenhouse gases and their characteristics (USEPA 2014b)

Greenhouse gas Carbon dioxide

Methane

Nitrous oxide

Fluorinated gases

How it is produced Emitted primarily through the burning of fossil fuels (oil, natural gas, and coal), solid waste, and trees and wood products. Changes in land use also play a role. Deforestation and soil degradation add carbon dioxide to the atmosphere, while forest regrowth takes it out of the atmosphere Emitted during the production and transport of coal, natural gas, and oil. Methane emissions also result from livestock and agricultural practices and from the anaerobic decay of organic waste in municipal solid waste landfills Emitted during agricultural and industrial activities, as well as during combustion of fossil fuels and solid waste A group of gases that contain fluorine, including hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride, among other chemicals. These gases are emitted from a variety of industrial processes and commercial and household uses and do not occur naturally. Sometimes used as substitutes for ozone-depleting substances such as chlorofluorocarbons (CFCs)

Average lifetime in the atmosphere

100-year global warming potential 1

12 years

28

121 years

265

A few weeks to thousands of years

Varies (the highest is sulfur hexafluoride at 23,500)

Figure 5 shows the impact of climate change in terms of projected increase in temperature by the year 2100. Five types of risk factors are identified together with the likely future temperature. There is a range of scenarios and uncertainties accompanied with each risk factor. Under worst conditions, if the future temperature rises above 3  C, there will be a risk of irreversible large-scale and abrupt transition. Knowing that the present-day anthropological factors have accelerated the climate change, efforts must be to stop, or adapt or mitigate, the arrival of the advent of the natural cycle of events, which can be nothing less than disastrous. It may not be humanly possible to stop; nevertheless, efforts must be made to adapt or mitigate and continue to make developments in the fast-moving socioeconomic setup of knowledge-based society.

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Fig. 5 Risks and impact of climate change (Source: Smith et al. 2009)

For a sustainable development, holistic approach integrating climate change in policy making for resource development is presented, in a guideline entitled “Training Manual on Climate Change Adaptation and Development,” compiled by Geene et al. (2010). In 1997, the Kyoto Protocol was concluded and established legally binding obligations for developed countries to reduce their greenhouse gas emissions. Furthermore, Millennium Development Goals (MDG) of the United Nations (2014) also put emphasis on efforts to ensure environmental sustainability (goal number 7) and to develop a global partnership for development (goal number 8). Figure 5 shows the impact of climate change in terms of projected increase in temperature by the year 2100. In order to control and reverse the process of global warming, it is essential to look into adaption and development together with awareness and mitigation measures.

Awareness and Mitigation Climate change is a global challenge. This challenge will continue to affect all forms of life. Apparently, there was little awareness of this calamity prior to preindustrial period (prior to 1760 AD), but at the present time, if nothing is done to curb this menace, irreparable damage may jeopardize the entire ecosystem and the human development process. Management of greenhouse gases includes measures, which are necessary before a catastrophic situation appears. Emphasis is placed on awareness and

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Control of Climate Change

Awareness and Preparedness

Capacity Building through Community Education & Training

Regulation and Enforcement

Fig. 6 Steps to control climate change

preparedness, capacity building through community education and training, as well as enforcement of regulations (Fig. 6), meant to reduce or capture emissions. This requires a global partnership, for development to combat the situation. The principal cause of climate change as noted in Fig. 3 is attributed to three principal greenhouse houses, namely, CO2, NO2, and CH4. The former is the utmost contributor of change in temperature, which has affected the climate, both in the paleoclimate and the present scenario. The IPCC (2001, 2007) has clearly spelled out that “adaptation will be necessary to address impacts resulting from warming, which is already unavoidable due to past emissions.” This supports the idea that adaptation and development should be treated as a complimentary response strategy to awareness and mitigation.

Adaption and Development Adaption to climate change can either be planned or automatic. Plants and animals have no plan to control over environment. For them, adaptation in response to environmental changes is necessary for their survival else they will disappear. For humans, in spite of being aware of the effects of climate change, it is necessary to take measures which may not stop but at least reduce the impact of environmental changes through specific policy framework (F€ussel and Klein 2006). Adaption can, therefore, be taken as an option after mitigation. It implies reduction of impacts rather than vulnerability for development (Fig. 7). Indeed, climate change is a reality, and there is a general agreement that “we must stop and reverse this process now or face a devastating cascade of natural disasters that will change life on earth, as we know it.”

Reversal of Climate Change Climate change can be looked into paleoclimate and preindustrial perspectives. It is only in the postindustrial period that the effects of climate change were noticed. Nevertheless, there is growing and convincing evidence that climate change has

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Fig. 7 Development preceded by adaptation

been occurring throughout the geological history of Earth due to natural causes. However, the anthropogenic activities have added to causes of climate change manifested by a growing increase in temperature in the postindustrial instance. It is, therefore, pertinent to control as well as reverse the process of global warming by awareness, mitigation, and adaptation to bring about the much-needed development (Fig. 8). Reducing deforestation and encouraging reforestation can reduce emission from fossil fuels by trapping CO2 and thus play a significant role in the long run to curtail global warming (Union of Concerned Scientists 2013). But, this may not be the only solution. At the global community level, it may be useful to reverse the global warming process and follow adaptation and development together with awareness and mitigation. This is well and good, but research is being conducted to curb the release of CO2, which acts as cover to stop it from escaping into the upper layers of atmosphere and as a result raises the temperature of Earth. Today, the power sector alone represents global CO2 emissions approximating 40 %. As reported by Curry (2004), researchers in the MIT Laboratory for Energy and the Environment have been studying a global climate change mitigation technology called “carbon dioxide capture and storage,” since 1989, under the auspices of a program currently called the “Carbon Capture and Sequestration Technologies Program.” Similar research is being conducted at centers and institutes of research and development elsewhere. Basically, there are three steps involved in this venture. The first step is to trap and separate CO2 from other gases. In the second step, this gas is taken to a far-flung storage location, away from the atmosphere, and lastly, the gas is carefully stored deep inside the Earth’s crust or deep in oceans. Furthermore, there are three methods of capture, namely, post-combustion carbon capture, pre-combustion capture, and oxyfuel carbon capture (GreenFacts 2014).

Future Directions Paleoclimate sources of information, leading to an assessment of conditions that prevailed during the life history of Earth, are important in predicting likely climatic changes in the future. The Earth’s climate is constantly changing. There are a number of processes that can influence this fluctuation. Increase in CO2, among

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Fig. 8 Historic perspective of climate change and reversal approach of combating climate change

other variables, is the main ingredient of this variation. Comparison with prehistoric records reveals that the concentration of CO2 has been on the rise since postindustrial times. This has led to fears that the consequent rise in the temperature of atmosphere may be extraordinarily difficult to handle. The UN panel of experts on greenhouse gases, led by CO2, suggested that the concentration of this gas would have to be kept below 450 ppmv to give a good chance of achieving less than 2  C increase (2014) in global temperature, before the end of this century. Failure to control the rising concentration of CO2 can be nothing less than disastrous in this regard. The best way of control would be to reduce emission from the fossil fuel (oil, gas, and coal)-based power plants, industrial units, or the transport sector in this situation. Reducing deforestation and encouraging reforestation can reduce emission from fossil fuels by trapping CO2 and thus play a significant role in the long run to curtail global warming. The concern is that anthropogenic emissions of greenhouse gases may be driving average global temperature higher than previously recorded or estimated. At the global community level, it may be useful to reverse the global warming process and follow adaptation and development together with awareness and mitigation. Research is being conducted in some developed countries to find a technically feasible and economically affordable solution to capture CO2 at source and store the same at depth either in the sea or in the Earth’s crust.

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References British Antarctic Survey (2014) Ice cores and climate change. www.antarctica.ac.uk/bas-research/ science-briefings/icecorebriefing.php Climate Data Information (2010) www.Climatedata.info Cook J, Nuccitelli D, Green SA, Richardson M, Winkler B, Pointing R, Way R, Jacobs G, Skuce A (2013) Quantifying the consensus on anthropogenic global warming in the scientific literature. Environ Res Lett 8(2):024024, 7pp Curry TE (2004) Public awareness of carbon capture and storage: a survey of attitudes towards climate change mitigation: a thesis submitted to the Engineering Systems Division in partial fulfillment of the requirements for the degree of Master of Science in Technology & Policy at the Massachusetts Institute of Technology Eldredge S, Biely B (2010) Ice Ages- what are they and what causes them? Utah Geological survey. Surv Notes 42(3):2 Fl€uckiger J, Blunier T, Stauffer B, Chappellaz J, Spahni KR, Schwander J, Stocker TF, Jensen D (2004) N2O and CH4 variations during the last glacial epoch: insight into global processes. Global Biogeochem Cycles 18:GB1020 Forster P, Ramaswamy V, Artaxo P, Berntsen T, Betts R, Fahey DW, Haywood J, Lean J, Lowe DC, Myhre G, Nganga J, Prinn R, Raga G, Schulz M, Van Dorland R (2007) Changes in atmospheric constituents and in radiative forcing. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of Working Group 1 to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK/New York F€ussel H-M, Klein RJT (2006) Climate change vulnerability assessments: an evolution of conceptual thinking. Clim Change 75(3):301–329 Geene J. van, Terwisscha Van Scheltinga CTHM, Gordijn F, Jaspers AMJ, Argaw M (2010) Trainer’s manual on climate change adaptation and development: integrating climate change in policy making for sustainable development in agriculture and natural resources management. Wageningen UR GreenFacts (2014) CO2 capture and storage. www.greenfacts.org/en/co2-capture-storage/ Hansen J, Sato M (2011) Paleoclimate implications for human-made climate change. In Climate Change at the Eve of the Second Decade of the Century: Inferences from Paleoclimate and Regional Aspects: Proceedings of the Milutin Milankovitch 130th Anniversary Symposium. In: Berger A, Mesinger F, Sˇijaci D (eds). Springer, (in press) IPCC (2001) Third assessment report of the IPCC. Cambridge University Press, Cambridge IPCC (2007) Working Group II, summary for policy makers. Cambridge University Press, Cambridge Jonzel J, Koster RD, Snozzo RJ (1994) Stable Water isotope behavior during the last glacial maximum: a general circulation model analysis. J Geophys Res 99:25791–25802 Leggett J (1990) The nature of the greenhouse threat, Chapter 1, pp 14–43. In: Global warming, the greenpeace report, Introduction. Oxford University Press, Oxford, pp 1–9 NASA (2014) NASA readies satellite to measure atmosphere CO2. The Necos International, 20 June 2014 NASA Earth Observation (2010) Global Warming Goddard Space Flight Center, USA NOAA (2008) A Paleo perspective on global warming. Temperature change and carbon dioxide, National Oceanic and Atmospheric Administration, paleo@ hoaa.gov Saltzman B (2002) Dynamical paleoclimatology: generalized theory of climate change. Academic/Elsevier Science, Santiago, 354 p Schilt A, Baumgartner M, Blunier T, Schwander J, Spahni R, Fischer H, Stocker TF (2010) Glacial–interglacial and millennial-scale variations in the atmospheric nitrous oxide concentration during the last 800,000 years. Quat Sci Rev 29(1-2): 182–192 Schrag D (2012) Changing planet: past, present, future – earth’s climate back to the future, Lecture 3. Harvard University

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Smith, JB, Schneider, SH, Oppenheimer M, Yohe GW, Hare W, Mastrandrea MD, Patwardhan A, Burton I, Corfee-Morlot J, Magadza CHD, Fussel HM, Pittock AB, Rahman A, Suarez A, van Ypersele JP (2009) Assessing dangerous climate change through an update of the Intergovernmental Panel on Climate Change (IPCC) ‘reasons for concern’. In: Proceedings of the National Academy of Sciences 106(11):4133–4137. doi:10.1073/pnas.0812355106. PMC 2648893. UN Secretary General Ban Ki-moon (2013) United Nations global issues: climate change. www. un.org/en/globalissues/climatechange/. 3p UNFCCC (1992) United Nation framework convention on climate change. United Nations Publisher, New York. Union of Concerned Scientists (2013) Global warming. www.ucsusa.org/gobal_warming/solu tions/stop-deforestation/ United Nations (2014) United Nations Millennium Development Goals. Last retrieved: 01 July 2014. http://www.un.org/millenniumgoals/bkgd.shtml USEPA (2014a) Climate change indicators in the United States. United States Environment Protection Agency. EPA Headquarters, Washington, DC, 99p USEPA (2014b) A student’s guide to climate change, United States Environmental Agency. EPA Headquarters, Washington, DC USEPA (2014c) Climate change indicators in the United States. Green House Gases. United Agency, EPA’s Office of Research and Development, EPA Headquarters, Washington, DC, 4pp Wolff EW (2011) Greenhouse gases in the earth system: a paleoclimate perspective. Philos Trans R Soc A Math Phys Eng Sci 369(1943):2133–2147

Life Cycle Assessment of Greenhouse Gas Emissions L. Reijnders

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . What Is Life Cycle Assessment and How Does It Work? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Goal and Scope Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Inventory Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Impact Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Life Cycle Assessments Focusing on Greenhouse Gas Emissions or a Part Thereof . . . . . . Simplified Life Cycle Assessments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Published Life Cycle Assessments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Main Findings from Life Cycle Studies of Greenhouse Gas Emissions . . . . . . . . . . . . . . . . . . . . . . . Energy Conversion Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Products Consuming Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conventional and Unconventional Fossil Fuels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Green Energy Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Biofuels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chemicals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Polymeric Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Crop-Based Lubricants and Solvents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Recycling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nanotechnology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reduction of Life Cycle Greenhouse Gas Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Change in Carbon Stocks of Recent Biogenic Origin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Indirect Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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L. Reijnders (*) Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_2

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Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Comprehensives of Dealing with Climate Warming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Consequential Life Cycle Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Life cycle assessments of greenhouse gas emissions have been developed for analyzing products “from cradle to grave”: from resource extraction to waste disposal. Life cycle assessment methodology has also been applied to economies, trade between countries, aspects of production, and waste management, including CO2 capture and sequestration. Life cycle assessments of greenhouse gas emissions are often part of wider environmental assessments, which also cover other environmental impacts. Such wider-ranging assessments allow for considering “trade-offs” between (reduction of) greenhouse gas emissions and other environmental impacts and co-benefits of reduced greenhouse gas emissions. Databases exist which contain estimates of current greenhouse gas emissions linked to fossil fuel use and to many current agricultural and industrial activities. However, these databases do allow for substantial uncertainties in emission estimates. Assessments of greenhouse gas emissions linked to new processes and products are subject to even greater data-linked uncertainty. Variability in outcomes of life cycle assessments of greenhouse gas emissions may furthermore originate in different choices regarding functional units, system boundaries, time horizons, and the allocation of greenhouse gas emissions to outputs in multi-output processes. Life cycle assessments may be useful in the identification of life cycle stages that are major contributors to greenhouse gas emissions and of major reduction options, in the verification of alleged climate benefits, and to establish major differences between competing products. They may also be helpful in the analysis and development of options, policies, and innovations aimed at mitigation of climate change. The main findings from available life cycle assessments of greenhouse gas emissions are summarized, offering guidance in mitigating climate change. Future directions in developing life cycle assessment and its application are indicated. These include better handling of indirect effects, of uncertainty, and of changes in carbon stock of recent biogenic origin and improved comprehensiveness in dealing with climate warming.

Introduction This handbook is about climate change mitigation. In decision-making about climate change mitigation, question marks about proper choices regularly emerge. Is going for electric cars a good thing, when power production is largely coal based? Do the extra inputs in car production invalidate the energy efficiency gains of

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hybrid cars? Should a company focus its greenhouse gas management on its own operations or on those of raw material suppliers? Is material recycling better or worse for climate change mitigation than incineration in the case of milk cartons? And what about biofuels: should their use be encouraged or not? Regarding all these questions, assessment of the life cycle emission of greenhouse gases, or more in general the environmental burden, is important for giving proper answers. Life cycle assessments may lead to anti-intuitive results. This can be illustrated by the case of liquid biofuels (Hertwich 2009). It has been argued that biofuels are “climate neutral” (e.g., Sann et al. 2006; De Gorter and Just 2010). The CO2 which emerges from burning biofuels has been recently fixed by photosynthesis, so, it has been argued, there should be no net effect of burning biofuels on the atmospheric concentration of CO2. However, if one looks at the “seed-to-wheel” life cycle of biofuels, a different picture may emerge. Consider, e.g., corn ethanol used as a transport biofuel in the USA. In the actual production thereof, there are substantial inputs of fossil fuels (Fargione et al. 2008; Searchinger et al. 2008). Corn cultivation also leads to emissions of the major greenhouse gas N2O (Crutzen et al. 2007). And corn cultivation is associated with changes in carbon stocks of agroecosystems (Searchinger et al. 2008). Considering the life cycle emissions of greenhouse gases leads to the conclusion that bioethanol from the US corn is far from “climate neutral” but is rather associated with larger greenhouse gas emissions than conventional gasoline (Searchinger et al. 2008; Reijnders and Huijbregts 2009). This has clearly implications for making good decisions about mitigating climate change linked to fuel choice (Hertwich 2009). Against this background, this chapter will consider current life cycle assessment, with a focus on the life cycle emission of greenhouse gases. First, it will be discussed what life cycle assessment is and how it is done. It will appear that such assessment may give rise to substantial uncertainty. Notwithstanding such uncertainty, life cycle assessments can be helpful in making proper choices about climate change mitigation. To illustrate this, main findings from available peerreviewed life cycle assessments of greenhouse gas emissions will be summarized.

What Is Life Cycle Assessment and How Does It Work? Life cycle assessment has been developed for analyzing current products from resource extraction to final waste disposal, or from cradle to grave. Apart from analyzing the status quo, life cycle assessments may also deal with changes in demand for, and supply of, products and with novel products. The latter type of assessment has been called consequential, as distinguished from the analysis of status quo products, which has been called attributional (Sanden and Kalstro¨m 2007; Frischknecht et al. 2009). The assessment of novel products has also occasionally been called: prospective attributional (Hospido et al. 2010; Song and Lee 2010). Different data may be needed in attributional and consequential life cycle assessment. Whereas in attributional life cycle assessment one, e.g., uses electricity data reflecting current power production, in consequential life, one needs data regarding

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changes in electricity supply. For the short term, assessing a marginal change in capacity of current electricity supply may suffice to deal with changes in electricity supply. When the longer term is at stake, major changes in energy supply, including complex sets of energy supply technologies, should be assessed (Lund et al. 2010). When novel products go beyond existing components, materials, and processes, knowledge often partly or fully relates to the research and development stage or to the limited production stage. These stages reflect immature technologies. Comparing these with products of much more mature technologies may be unfair, as maturing technologies are optimized and tend to allow for better resource efficiency and a lower environmental impact (Wernet et al. 2010; Mohr et al. 2009). Also, novel products may be subject to currently uncommon environmental improvement options and may have to operate under conditions that diverge from those that are currently common (Sanden and Kalstro¨m 2007; Frischknecht et al. 2009). The latter conditions may, e.g., include constraints on resource availability which currently do not exist, new infrastructures, budget constraints, higher resource costs which are conducive to resource efficiency, and strict caps on greenhouse gas emissions. A solution to such divergence from “business as usual” may be found in assuming technological trajectories and/or constructing scenarios which include assumptions about the environmental performance of future mature technologies under particular conditions (Frischknecht et al. 2009; Mohr et al. 2009; Jorquera et al. 2010; Spatari et al. 2010). It should be realized that the assumptions involved lead to considerable uncertainty regarding the outcomes of consequential life cycle assessments, as these assumptions may be at variance with “real life” in the future. Life cycle assessment is generally divided in four stages (Guinee 2002; Rebitzer et al. 2004): – – – –

Goal and scope definition Inventory analysis Impact assessment Interpretation

Goal and Scope Definition In the goal and scope definition stage, the aim and the subject of life cycle assessment are determined. This implies the establishment of “system boundaries” and usually the definition of a “functional unit.” A functional unit is a quantitative description of service performance of the product(s) under investigation. It may, for instance, be the production of a megawatt hour (MWh) of electricity. This allows for comparing different products having the same output: e.g., photovoltaic cells, a coal-fired power plant, a gas-fired power plant, and a wind turbine. It should be noted though that the functional unit may cover only a part of the service performance, because products may have special properties. For instance, in the case of power generation, the production of a MWh of electricity as a functional unit does not take account of the

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phenomenon that a coal-fired power plant is most suitable for base load and a gas-fired power plant for peak load. In the goal and scope definition stage, a number of questions have to be answered. For instance, the life cycle of products usually includes a transport stage. As to transport the question arises what to include into the assessment: production of the transport vehicle? road building? building storage facilities for products? Similarly, in the life cycle assessment of fishery products, questions arise such as: should one include the bycatch of fish which is currently discarded? the energy input in shipbuilding and ship maintenance? and/or the energy input in building harbor facilities? In the goal and scope definition stage, one should also consider the matter of significant indirect effects of products. A well-known example thereof is the rebound effect in the case of more energy-efficient products with lowered costs of ownership. Such products may, for instance, increase use of the product and may lead to spending of money saved by the energy-efficient product, which in turn may impact energy consumption, and associated greenhouse gas emissions (Schipper and Grubb 2000; Thiesen et al. 2008; Greene 2011). Another case in point concerns biofuels from crops that currently serve as source for food or feed. When carbohydrates or lipids from such crops are diverted to biofuel production, this diversion may give rise to additional food and/or feed production elsewhere, because demand for food and feed is highly inelastic (Searchinger et al. 2008). This, in turn, may have a substantial impact on estimated greenhouse gas emissions. Similarly, the use of waste fat for biodiesel production may have the indirect effect of reducing the amount of fat available for feed production, which in turn might lead to an increased use of virgin fat, which will impact land use and may thus change carbon stocks of recent biogenic origin. However, indirect effects of decisions about biofuels do not end with the consideration of indirect effects on land use. It may, for instance, be argued that not expanding biofuel production may increase dependency on mineral oil and that this may increase military activities to safeguard oil installations and shipping and associated emissions of greenhouse gases (De Gorter and Just 2010). Still another example of indirect effects regards wood products. These may have the indirect effect of substituting for non-wood products, and including such substitution has a significant effect on estimated greenhouse gas emissions (Sathre and O’Connor 2010). Decision-making about significant indirect effects is not straightforward. This has led some to the conclusion that including indirect effects is futile (e.g., De Gorter and Just 2010), whereas others have argued that including at least some indirect effects is conducive to good decision-making (e.g., Searchinger et al. 2008; Sathre and O’Connor 2010). System boundaries refer to what is included in life cycle assessment. In general, system boundaries are drawn between technical systems and the environment, between relevant and irrelevant processes, between significant and insignificant processes, and between technological systems. An example of the latter is, for instance, a boundary between the motorcar life cycle and the life cycle of the building in which the car is produced. The choice of system boundaries may have a substantial effect on the outcomes of life cycle assessments (also: Finnveden et al. 2009; Gandreault et al. 2010).

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Inventory Analysis The inventory analysis gathers the necessary data for all processes involved in the product life cycle. This is a difficult matter when one is very specific about a product: for instance, the apples which I bought last Saturday in my local supermarket. However, databases have been developed, such as Ecoinvent (Frischknecht et al. 2005), the Chinese National Database (Gong et al. 2008), Spine (www. globalspine.com), JEMAI (Narita et al. 2004), and the European Reference Life Cycle Data System (ELCD 2008), which give estimates about resource extraction and emissions that are common in Europe, China, the USA, and Japan for specified processes (for instance, the production and use of phosphate fertilizer). Also, there are databases which extend to economic input–output analyses and give resource extraction and emission data at a higher level of aggregation than the process level (Tukker et al. 2006). A study of De Eicker et al. (2010), which also gives a fuller survey of available databases, suggests that among available databases the Ecoinvent database is preferable for relatively demanding LCA studies. If only greenhouse gas emissions are considered, the 2006 guidelines for national greenhouse gas inventories of the IPCC (Intergovernmental Panel on Climate Change; www.ipcc.ch/) were found to be useful (De Eicker et al. 2010). Available databases do not always give the same emissions for the same functional units. For instance, according to a study of Fruergaard et al. (2009), data about the average emission of greenhouse gases linked to 1 kWh electricity production in 25 EU countries varied between databases by up to 20 %. For similar estimates in the USA, an even greater between-database uncertainty (on average 40 %) was found (Weber et al. 2010). Though such uncertainties are substantial, they should not detract from using databases such as Ecoinvent, Spine, and JEMAI, if only because between-process differences often exceed uncertainty. This may be illustrated by the geographical variability in greenhouse gas emissions linked to electricity production. For instance, country-specific average emissions of greenhouse gases per kWh of electricity in such databases vary by a factor of 160 (Fruergaard et al. 2009). For marginal emissions of greenhouse gases per kWh of electricity (which are used to assess changes in supply or demand as needed for consequential life cycle assessment), variations were even larger: up to 400–750 times (Fruergaard et al. 2009). In the inventory stage of life cycle assessments of greenhouse gas emissions, the focus is evidently on the latter emissions. In wider-ranging life cycle assessments, the inventory may comprise all extractions of resources and emissions of substances causally linked to the functional unit for each product under consideration, within the system boundaries that were established in the stage of goal and scope definition. Such wider-ranging life cycle assessments have a benefit over life cycle assessments, which only focus on greenhouse gas emissions. First, they give a better picture of the overall environmental impact, for which life cycle greenhouse gas emissions may well be a poor indicator (Huijbregts et al. 2006, 2010; Laurent et al. 2010). Also, such wider-ranging LCAs allow for considering “trade-offs”

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between environmental impacts and the occurrence of co-benefits linked to reducing greenhouse gas emissions (Nishioka et al. 2006; Haines et al. 2009; Markandya et al. 2009; Chester and Horvath 2010; Walmsley and Godbold 2010). For instance, Walmsley and Godbold (2010) concluded that stump harvesting for bioenergy may not only impact greenhouse gas emissions but may have the co-benefit of reducing fungal infections and may have negative co-impacts linked to erosion, nutrient depletion and loss, increased soil compaction, increased herbicide use, and loss of valuable habitat for a variety of (non-pest) species. Many current transport biofuels have larger life cycle greenhouse gas emissions than the fossil fuel which they replace but have the benefit that dependence on mineral oil is reduced (Reijnders and Huijbregts 2009). A large part of the impacts which go beyond climate change can be covered by standard wider-ranging LCAs. Aspects of environmental impact which are, apart from the emission of greenhouse gases, often covered by such wider-ranging life cycle assessments are summarized in Box 1. In evaluating buildings, the indoor environment may also be a matter to consider (Demou et al. 2009; Hellweg et al. 2009). New operationalizations of some of the aspects of environmental impact mentioned in Box 1 and additions to the list of Box 1 are under development. The latter include ecosystem services (Koellner and de Baan 2013) and the impacts of freshwater use (Boulay et al. 2011; Verones et al. 2013). Adding to the aspects often covered in wide ranging LCAs, a proposal has been published for the inclusion into life cycle assessment of change in albedo which is relevant to climate, characterized in terms of CO2 equivalents (Munoz et al. 2010). An estimate of the contribution inclusion of black carbon emissions to climate change has also become available (IPPC Working Group I 2013). In life cycle assessments, the problem arises that many production systems have more than one output. For instance, rapeseed processing not only leads to the output oil, which may be used for biodiesel production, but also to rapeseed cake, which may be used as feed. Similarly, mineral oil refinery processes may not only generate gasoline but also kerosene, heavy fuel oil, and bitumen, and biorefineries produce a variety of product outputs too (Brehmer et al. 2009). In the case of multi-output processes, extractions of resources and emissions have to be allocated to the different outputs. There are several ways to do so. Major ways to allocate are based on physical units (e.g., energy content or weight of outputs) or on monetary value (price). There may also be allocation on the basis of substitution. In the latter case, the environmental burden of a coproduct is established on the basis of another, similar product. Different kinds of allocation may lead to different outcomes of life cycle assessment (Reijnders and Huijbregts 2009; Finnveden et al. 2009; Fruergaard et al. 2009; Sayagh et al. 2009). The usual outcome of the inventory analysis of a wide ranging life cycle assessment is a list with all extractions of resources and emissions of substances causally linked to the functional unit for the product considered and, apart from the case of nuisance, commonly disregarding place and time of the extractions and emissions.

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Box 1: Aspects of Environmental Impact Which Are Often Considered in Wide Ranging Life Cycle Assessments

Resource depletion (abiotic, biotic) Effect of land use on ecosystems and landscape Desiccation Impact on the ozone layer Acidification Photooxidant formation Eutrophication or nitrification Human toxicity Ecotoxicity Nuisance (odor, noise) Radiation Casualties Waste heat Water footprint

Impact Assessment The next stage in life cycle assessment is impact assessment. This firstly implies a step called characterization. In this step, extractions of resources and emissions are aggregated for a number of impact categories. When only greenhouse gas emissions are considered, the aggregation aims at establishing the emission of other greenhouse gases in terms of CO2 equivalents (CO2eq), which means that the emission of greenhouse gases like N2O, CH4, and CF4 are recalculated in terms of CO2 emissions. To do so, one needs to choose a time horizon (e.g., 25 years, 100 years, 104 years), because the greenhouse gas effect of emitted greenhouse gases may be different dependent on the time horizon chosen (see Table 1). The time-dependent differences in Table 1 reflect differences in atmospheric fate of greenhouse gases. For instance, the removal of CH4 from the atmosphere is much faster than the removal of CO2 (Myrhe et al. 2013). In practice, often a time horizon of 100 years is chosen and the global warming potentials (GWP) from the corresponding column of Table 1 are commonly used in life cycle assessments. Table 1 considers only direct impacts or effects of the greenhouse gases. There are however also indirect impacts. For instance, the emission of CH4 may affect the presence of ozone, which is also a greenhouse gas. There have been proposals for including such indirect effects in global warming potentials. Using a 100-year time horizon and assuming the GWP of CO2 to be 1, Brakkee et al. (2008) proposed, for instance, a GWP for CH4 of 28 and for non-methane volatile organic compounds, a GWP of 8. The latter have a direct GWP of 0. A number of estimated examples of global warming potentials calculated with and without indirect effects are in Table 2.

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Table 1 Estimated global warming potentials (GWP) in CO2eq of CH4 and N2O for time horizons of 20 and 100 years as proposed by the Intergovernmental Panel on Climate Change (IPCC) (Myrhe et al. 2013). Apart from climate–carbon interactions, only direct effects are considered Gas/time horizon CO2 CH4 N2O

20 years 1 86 268

100 years 1 34 298

Table 2 Estimated global warming potentials (GWP) with a time horizon of 100 years relative to the GWP of CO2 for a number of gases as calculated by Brakkee et al. (2008) Gas/type of GWP CH4 CO Non-methane volatile organic compounds (NMVOC) Chlorofluorocarbon (CFC) 11 Chlorofluorocarbon (CFC) 12 Chlorofluorocarbon (CFC) 113 CF4 CO2

GWP, direct effect only; time horizon 100 years 18 0 0

GWP, including indirect effects; time horizon 100 years 28 3 8

4,800 11,000 6,200

3,300 6,100 4,700

6,100 1

6,100 1

Table 3 Global warming potentials in CO2eq for a number of gases

Gas/global warming potential CH4 Chlorofluorocarbon (CFC) 11 CF4 CO2

GWP assuming 70 % removal from atmosphere (direct effect only) (Sekiya and Omamoto 2010) 10.6 2,249

GWP as in Table 1 with a time horizon of 100 years as calculated by IPCC (Myrhe et al. 2013) 34 5,350

1,560,558 1

7,350 1

One may note that Brakkee et al. (2008) give an estimate for the GWP of CH4 (direct effect only), which is different from the value in Table 1. Still another possibility is to calculate GWPs on the basis of a similar percentage of greenhouse gas remaining in, or lost from, the atmosphere. This is exemplified by Table 3, with values as calculated by Sekiya and Okamoto (2010). In the case of life cycle assessment of greenhouse gas emissions, calculating the emission in terms of CO2eq is where the impact assessment stage often ends, though there is also the option to quantify the impact in terms of damage to public

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health (e.g., Haines et al. 2009), human health, and ecosystems (De Schryver et al. 2009) and in terms of negative effects on the economy (e.g., Stern 2006). Such damage-based characterizations facilitate weighing of trade-offs and co-benefits, when a variety of environmental impacts (cf. Box 1) are included in life cycle assessment. Having CO2eq emissions as an outcome of life cycle assessment is often sufficient to guide the selection of product life cycle options, policies, and innovations aimed at mitigation of climate change, because the emission of greenhouse gases is in a first approximation directly causally linked with environmental impact (climate change). Still, it should be noted that the temporal pattern of greenhouse emissions may affect the rate of climate change, which in turn is, e.g., a major determinant of impact on ecosystems. When the temporal pattern of the emissions is important, as, for instance, in the case of land use change or capital investments in production systems, it is possible to adapt life cycle assessment by including the estimated temporal pattern of greenhouse gas emissions linked to the object of life cycle assessment (cf. Reijnders and Huijbregts 2003; Kendall et al. 2009). Also, one may note that effect of activities on climate may go beyond the emission of greenhouse gases. For instance, agricultural activities may change albedo, evaporation, and wind speed, which may in turn affect climate (Reijnders and Huijbregts 2009). Also, the greenhouse effect of air traffic may be different than expected solely on the basis of CO2, N2O, and CH4 emissions, because air traffic triggers formation of contrails and cirrus clouds (Lee et al. 2010a). A direct causal link between emission and impact for greenhouse gas emissions may be at variance with other environmental impact categories. For instance, lead emissions which do not lead to exceeding a no-effect level for exposure of organisms will have no direct environmental impact. Also, specificity as to time and place can be very important for other impacts than climate change caused by greenhouse gases, such as the impacts of the emissions of hazardous and acidifying substances (Scho¨pp et al. 1998; Hellweg et al. 2005; Pottimg and Hauschild 2005; BassetMens et al. 2006). It may be noted, however, that in such cases time and place specificity may be introduced by adaptation of life cycle assessment or combining life cycle assessment with other tools (e.g., Hellweg et al. 2005; Huijbregts et al. 2000; Rehr et al. 2010).

Interpretation The interpretation stage connects the outcome of the impact assessment to the real world. Much of the practical usefulness of life cycle assessments of greenhouse gas emissions in this respect depends upon the uncertainty of outcomes, which has a variety of sources (e.g., Finnveden et al. 2009; Huijbregts et al. 2001, 2003; Geisler et al. 2005; De Koning et al. 2010; Williams et al. 2009). These can be categorized as uncertainties due to choices, uncertainties due to modeling, and parameter

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uncertainty (Huijbregts et al. 2001, 2003). Parameter uncertainty and uncertainty due to choice (e.g., regarding time horizon, type of allocation, system boundaries, and functional unit) would seem to be the most important types of uncertainty in the case of estimating life cycle greenhouse gas emissions. Uncertainty in the outcomes of life cycle assessments of greenhouse gas emissions partly depends on the reliability of input data (categorized as parameter uncertainty). As pointed out above, databases regarding fossil fuel use in industrialized countries such as the USA, China, and Japan and EU countries allow for substantial uncertainties in this respect (Sann et al. 2006; Fruergaard et al. 2009). Similar data regarding other countries tend to be still more uncertain. Greenhouse gas emissions linked to land use, N2O emissions, and animal husbandry are also characterized by a relatively large uncertainty (Reijnders and Huijbregts 2009; Ro¨o¨s et al. 2010). Additional variability in outcomes of life cycle assessments of greenhouse gas emissions may originate in different choices regarding system boundaries. This has, for instance, been shown by Christensen et al. (2009) and Gandreault et al. (2010), who analyzed life cycle greenhouse gas emissions of forestry products. They found that different assumptions about the boundary to the forestry industry and interactions between the forestry industry on one hand and on the other hand the energy industry and the recycled paper market might lead to substantial differences in outcomes of life cycle assessments. Choices regarding time horizons and the allocation of greenhouse gas emissions to outputs in multi-output processes may also have major consequences for such outcomes (Reijnders and Huijbregts 2009). Sensitivity analysis may be part of the interpretation stage and, for instance, consider the dependence on different assumptions regarding allocation and time horizon. Similarly, uncertainty analysis may be part of the interpretation stage. Several approaches to uncertainty analysis have been proposed, using Monte Carlo techniques (Huijbregts et al. 2003; Hertwich et al. 2000), matrix perturbation (Heijungs and Suh 2002), or Taylor series expansion (Hong et al. 2010). In practice, uncertainty analysis has been applied in a limited way. Also, in the interpretation stage, conclusions can be drawn. For instance, stages or elements of the product life cycle can be identified, which are linked to relatively high greenhouse gas emissions. These can be prioritized for emission reduction options and policies. Also, it may be established that, given a functional unit and specified assumptions, one product has lower greenhouse gas emissions (in CO2eq) than another. Examples of conclusions which can be drawn from life cycle assessments are given in section “Main Findings from Life Cycle Studies of Greenhouse Gas Emissions.” Though life cycle assessment has been developed for products, in practice the methodology has been applied more widely (cf. “Published Life Cycle Assessments”). To the extent that life cycle assessment methodology, which does not focus on products, essentially assesses parts of product life cycles (e.g., the nickel industry, waste incineration, and CO2 capture and sequestration), the usefulness of assessment may be similar to the assessment of products: one may find, prioritize, and validate emission reduction options.

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Some of the applications of life cycle assessments, which go beyond products, give rise to additional problems. For instance, applying life cycle assessments to state economies and trade may give rise to double counting of emissions (Lenzen 2008). On the other hand, e.g., expansion of life cycle assessments to trade between states may give useful insights about the actual environmental impacts of imports and exports. This is a useful addition to climate regimes such as the Kyoto protocol, which focus on greenhouse gas emissions within state borders. Also, economy-wide LCAs may help in prioritizing product categories or economic sectors for policy development (Jansen and Thollier 2006).

Life Cycle Assessments Focusing on Greenhouse Gas Emissions or a Part Thereof The emergence of climate change as a major environmental concern has led to a rapid increase in life cycle assessments focusing on the emission of greenhouse gases. However, it should be pointed out that there are also life cycle assessments which cover only a part of the greenhouse gases. In this context, one may note the growing popularity of “carbon footprinting” (e.g., De Koning et al. 2010; Barber 2009; Johnson 2008; Weber and Matthews 2008; Schmidt 2009). There is no generally agreed upon definition of carbon footprinting. In practice, the focus of carbon footprinting is often on the emission of carbonaceous greenhouse gases, if the footprinting is not being “slimlined” to covering CO2 only (e.g., Schmidt 2009). Also, there is an increasing interest in life cycle assessments focusing on the cumulative input of fossil fuels, which in turn is closely related to the life cycle emission of the major greenhouse gas CO2 (Laurent et al. 2010; Nishioka et al. 2006). The focus on carbonaceous greenhouse gases may lead to outcomes which substantially deviate from overall greenhouse gas emissions. As several authors (Crutzen et al. 2007; Reijnders and Huijbregts 2009; Laurent et al. 2010; Nishioka et al. 2006) have pointed out, cumulative energy demand may be substantially at variance with overall environmental performance and life cycle emissions of greenhouse gases, in the case of agricultural commodities and in other cases in which life cycles impact land use. The same will hold in the case of a number of compounds, such as adipic acid, caprolactam, and nitric acid, when syntheses are used which generate N2O in a poorly controlled way (Fehnann 2000; PerezRamirez et al. 2003). Also, there can be a major divergence of “carbon footprinting” from overall life cycle greenhouse gas emissions when there are substantial emissions of halogenated greenhouse gases. The latter, e.g., applies to the case of halogenated refrigerant use (Ciantar and Hadfield 2000), the use of halogenated blowing agents for the production of insulation (Johnson 2004), to primary aluminum production, which is associated with the emission of potent fluorinated greenhouse gases such as CF4 (Fehnann 2000; Weston 1996), and to circuit breakers using SF6 and magnesium foundries (Fehnann 2000; Harrison et al. 2010). In the following, only assessments will be used which give an estimate of all greenhouse gas emissions, recalculated as CO2eq emissions.

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Simplified Life Cycle Assessments Full life cycle assessments require extensive data acquisition, which tends to be laborious and time-consuming, and this may well be beyond what practice in industry and policy requires (Bala et al. 2010). This has led to the emergence of simplified tools for the life cycle assessment of greenhouse gas emissions, such as screening LCAs. These tend to focus on major causes of life cycle greenhouse gas emissions (“hotspots”) and are often useful in identifying and prioritizing emission reduction options (Andersson et al. 1998; Rehbitzer and Buxmann 2005).

Published Life Cycle Assessments A wide variety of products has been the object of life cycle assessments of greenhouse gas emissions. Examples range from teddy bears to power generators, from pesticides to motorcars, from tomato ketchup to buildings, and from a cup of coffee to tablet e-newspapers. Products have not been the only objects of life cycle assessments of greenhouse gas emissions. Life cycle assessment has also been used for state economies, trade between countries, branches of industry, industrial symbiosis, aspects of production and product technologies, networks, soil and groundwater remediation, and waste management options, including CO2 capture and sequestration.

Main Findings from Life Cycle Studies of Greenhouse Gas Emissions Though, as pointed out in section “Goal and Scope Definition,” there are substantial uncertainties in assessments of life cycle greenhouse gas emissions, some outcomes of such assessments are robust to such an extent that they provide a sufficiently firm basis for conclusions. The latter are summarized here, assuming a time horizon of 100 years, using the values for global warming potentials as given by IPCC (Myrhe et al. 2013) (see Table 1), and focusing on direct effects only, unless indicated otherwise. After this summary, options for life cycle greenhouse gas emission reduction which commonly emerge from life cycle assessments will be briefly discussed.

Energy Conversion Efficiency Improvements in efficiency of the conversion of primary energy to energy services, including reduction of heat loss, often lead to lower life cycle greenhouse gas emissions for energy services (e.g., Erlandsson et al. 1997; Citherlet et al. 2000; Nakamura and Kondo 2006; Citherlet and Defaux 2007;

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Boyd et al. 2009) when only direct effects are considered. There are some exceptions. Phase change materials, which may be used in buildings to improve energy conversion efficiency, have been shown to not significantly reduce the life cycle greenhouse gas emission of buildings in a Mediterranean climate (De Gracia et al. 2010). Electric heat pumps, though generally giving rise to lower life cycle greenhouse gas emissions for space heating, may increase life cycle greenhouse gas emissions when electricity generation is coal based (Saner et al. 2010). Also, the III/V solar cells, which contain, e.g., In (indium) and Ga (gallium) and have higher conversion efficiencies for solar energy into electricity than Si (silicium)-based photovoltaic cells, do not appear to have lower life cycle greenhouse gas emissions per kWh than multicrystalline Si solar cells (Mohr et al. 2009). Noteworthy is the potential for indirect effects linked to improvements of energy efficiency. As noted before: in the case that improvements in energy conversion lead to lower costs of ownership, there may be a rebound effect on energy use because money linked to such lower costs tends to be spend on increased use of the product or elsewhere, which in turn entails additional energy consumption and emission of greenhouse gases (Schipper and Grubb 2000; Thiesen et al. 2008; Greene 2011). Lower costs may also be conducive to economic growth (Thiesen et al. 2008). When only microeconomic effects of improved energy efficiency are considered, life cycle greenhouse gas emissions tend to be still lowered, though less so than when only the effect of energy efficiency by itself is considered (Schipper and Grubb 2000; Greene 2011). Including economy-wide rebound effects in life cycle assessments of improved energy conversion efficiency has as yet no firm empirical basis (Thiesen et al. 2008).

Products Consuming Energy Life cycle greenhouse gas emissions of products which consume energy are often dominated by emissions during the use stage of the life cycle, when shares of fossil fuels in the production and consumption stages are similar (Nakamura and Kondo 2006; Boyd et al. 2009, 2010; Finkbeiner et al. 2006; Kofoworola and Gheewala 2008; Yung et al. 2008; Cullen and Allwood 2009; Duan et al. 2009; Ortiz et al. 2010; Rossello-Batle et al. 2010). There are exceptions, however, such as, for instance, a personal computer for limited household use (Choi et al. 2006), mobile phones (Andrae and Andersen 2010), and very energy-efficient dwellings (Citherlet and Defaux 2007). The latter illustrates a more general point. To the extent that energy conversion efficiency in the use stage improves, energy embodied in the product (e.g., Kakudate et al. 2002; Blengini and di Carlo 2010) and in the case of transport also energy embodied in infrastructure (e.g., Frederici et al. 2009) often become a more important factor in life cycle greenhouse gas emissions. It may be noted, though, that there are exceptions as to the growing importance of energy embodied in the product, such as CMOS chips for personal computers and other electronics (Boyd et al. 2009, 2010).

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Transport At continental distances in the order of 0). In the maximization the Nash assumption is employed, i.e., the welfare-maximizing country supposes that its choices do not affect the behavior of the other countries, i.e., it takes X~ i to be exogenous. From the first-order conditions for the welfare maximum, we get MRSi ¼

@U i =@X ¼ c: @U i =@yi

(4)

Consequently, it is optimal for the individual country to provide climate protection up to the level where the marginal rate of substitution (left-hand side of Eq. 4)

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between public good and private good becomes equal to the unit price ratio (righthand side of Eq. 4) between public and private good (i.e., 1c). To put it plainly, when deciding about allocating its income between private goods and climate protection, a country fares best when it invests in climate protection until the benefit from spending another dollar on the climate compared to the benefits from spending another dollar on private goods is equal to the relative costs of buying the two goods. While this provision level is optimal from an individual country’s point of view, it is not optimal from a global perspective. Global welfare could be raised by deviating from the provision levels associated with condition (4). In order to illustrate this, global welfare is maximized in a next step. It seems reasonable to assume that global welfare is a function of the individual countries’ welfare levels. The global welfare level attainable from the consumption of private goods and climate protection is, however, restricted by the aggregate income that the countries can spend on private goods and climate protection. Thus the global welfare maximization problem reads max UðU 1 ðy1 , XÞ, U2 ðy2 , XÞ, . . . , Un ðyn , XÞÞ

y1 , ..., yn , X

(5)

s.t. n n X X yi þ cX ¼ Ii : i¼1

(6)

i¼1

Let us – for simplicity – assume that each individual country’s welfare has an equal weight with respect to global welfare, i.e., U ðU1 ðy1 , XÞ, U 2 ðy2 , XÞ, . . . , U n ðyn , XÞÞ ¼ U1 ðy1 , XÞ þ U 2 ðy2 , XÞ þ . . . þ U n ðyn , XÞ. Then, optimization yields the so-called Samuelson condition (see Samuelson 1954, 1955) n n X X @U i =@X MRSi ¼ ¼ c: @U i =@yi i¼1 i¼1

(7)

Therefore, in order to maximize global welfare, an individual country should provide climate protection up to a level where the sum of all countries’ marginal rates of substitution between public and private good becomes equal to the unit price ratio between public and private good. Such outcomes, where no country can improve its welfare without harming another one, are called Pareto optima. Condition (7) deviates from condition (4), since – without international coordination – an individual country would only take into account its own marginal rate of substitution between public and private goods (i.e., its own benefits from the two goods) when deciding about its climate protection efforts, while Pareto efficiency requires that countries also take into account spillovers exerted on other countries (i.e., the global benefits generated by its climate protection efforts). Therefore also the other countries’ marginal rates of substitution between the public and private good have to be included in the efficiency condition.

Some Economics of International Climate Policy Fig. 4 Prisoner’s dilemma game

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B’s strategy no participation

participation

no participation

0, −1

6, −3

participation

−4, 7

5, 6

A’s strategy

On a national level, efficient public good provision can be enforced by the government, but on the global scale there is no central coercive authority which can enforce an efficient global climate protection level. Therefore, the only option is for countries to voluntarily negotiate a climate protection agreement in order to get closer to the globally efficient protection level.

International Negotiations in Normal Form Games Such international negotiations on climate change can be comfortably depicted in a game-theoretical setting. Regularly, such negotiations are described as a prisoner’s dilemma game which captures the free-rider incentives associated with the provision of public goods. A normal form game in the shape of a prisoner’s dilemma (PD) situation with two agents or countries is presented in Fig. 4. Both considered countries have the choice between “participation” in an international climate protection agreement (or climate protection efforts) and “no participation” in international climate protection efforts. In the matrix, the numbers in front of the commas represent the payoffs for country A, while the numbers behind the commas stand for the payoffs received by country B. In the prisoner’s dilemma case of Fig. 4, the dominant strategy for each agent is to choose “no participation” in an international climate protection agreement (a dominant strategy is a strategy which always yields the highest payoff for the agent choosing this strategy, regardless of the choice of the opponents. For a more detailed discussion of these and related game theoretic concepts, see, e.g., Fudenberg and Tirole (1991)). This outcome is the so-called Nash equilibrium where no country has anything to gain by changing only its own strategy unilaterally. While this equilibrium is stable, the payoffs of countries A and B are merely 0 and
1, respectively. However, “From an economic viewpoint an ideal state of cooperation has two features: It is a Paretooptimum and it is stable” (Buchholz and Peters 2003, p. 82). The Nash equilibrium in the depicted PD situation is of course not Pareto optimal. Both agents would obtain a higher payoff if they would both participate in the international agreement.

110 Fig. 5 Chicken game

K. Pittel et al. B’s strategy no participation

participation

no participation

−6, −6

6, −3

1 –p

participation

−3, 6

3, 3

p

1– q

q

A’s strategy

Alternatively, a “Chicken” game setting can be employed in order to illustrate the negotiation situation. Lipnowski and Maital (1983) provide an analysis of voluntary provision of a pure public good in general as the game of Chicken. In fact, a Chicken game tends to describe international negotiations on the provision of the specific public good “climate protection” in a more adequate way than the prisoner’s dilemma game (see Carraro and Siniscalco 1993). The case of a Chicken game, which belongs to the group of coordination games, is depicted in Fig. 5. In contrast to the PD situation, there exists no dominant strategy. There are a couple of papers investigating the differences associated with the two, PD and Chicken, games. Ecchia and Mariotti (1998) investigate coalition formation in international environmental agreements and compare different versions of the two game types using simple three-country examples. In their paper, Rapoport and Chammah (1966) stress the difference between both games with respect to the attractiveness of retaliation decisions. Snyder (1971) examines differences in the logic and social implications of PD and Chicken games in the context of international politics. Lipman (1986) and Hauert and Doebeli (2004) analyze how the evolution of cooperation differs in the two games. Rabin (1993), R€ubbelke (2011), and Pittel and R€ubbelke (2013) investigate fairness in these settings. Pittel and R€ubbelke (2012) depict negotiations on climate change in (3  3) matrices in which they integrate both Chicken and PD settings simultaneously. Hence, in their study they allow for a broader range of choices for the involved countries. The main difference between both games, i.e., between PD and Chicken games, is that the agents in the PD situation obtain the lowest payoffs when they play unilateral “participation,” while in the Chicken game, they face the lowest payoffs if they mutually play “no participation.” This outcome is the reason why the Chicken game is said to represent international negotiations better: in case of mutual non-participation, the whole world is threatened by a global warming catastrophe. This catastrophe can be prevented in the best way by means of mutual cooperation in international climate protection. However, if the other agent refuses to cooperate, then unilateral participation in international climate protection efforts would be the best choice since this is the only remaining way to prevent the global warming

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catastrophe. Yet, if the other agent provides climate protection (and thus chooses “participation”), it would be best to choose “no participation” and thus to take a free ride. Each agent hopes that the other agent provides climate protection, such that he himself can take a free ride in climate protection. As can be observed from Fig. 5, there exist multiple Nash equilibria, which are associated with pure and mixed strategies. The Nash equilibria in connection with pure strategies prevail where the payoffs (
3,6) and (6,
3) arise. Given possible uncertainties regarding the countries’ behavior, mixed strategies become germane. Agents form probabilities about the other agent’s behavior. Country A assesses the likelihood with which country B will participate (q) or not participate (1
q) and vice versa for country B ( p and 1
p). In order to determine the mixed strategies in the Chicken game situation in Fig. 5, the likelihood q (resp. p) of participation by country B (country A) has to be calculated that makes country A (country B) indifferent between playing “participation” and “no participation.” Probability q is determined by calculating the level of q, for which the expected payoffs of both strategies of A (“participation” and “no participation”) are equal. This is the case if
3ð1
qÞ þ 3q ¼
6ð1
qÞ þ 6q:

(8)

The left-hand side represents A’s expected payoff from participation, and the righthand side reflects A’s expected payoff from defection. Analogously p can be determined from solving
3ð1
pÞ þ 3p ¼
6ð1
pÞ þ 6p

(9)

for p. In this case, the mixed-strategy equilibrium requires q ¼ p ¼ 1⁄2:

(10)

If country A or country B is uncertain whether the other country participates or defects, then it should cooperate (participate) provided it expects the antagonist to play “participation” with a probability of less than ½.

Integration of Ancillary Benefits into the Negotiations Climate policies regularly generate side effects. Afforestation and reforestation, for example, do not only mitigate CO2-induced global warming by sequestering carbon; these measures also increase the habitat for endangered species. Furthermore, forests can serve as recreational areas and reduce soil erosion. As Ojea, Nunes, and Loureiro (2010) stress, forests’ “provision of goods and services plays an important role in the overall health of the planet and is of fundamental importance to human economy and welfare.” Furthermore, Sandler and Sargent (1995, p. 160) point out that tropical

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K. Pittel et al. Climate Policy (e.g., Carbon-Tax)

GHG Abatement Measures

Climate Protection

Primary (ClimateProtection Related) Benefits

Reduction in Local Air Pollution

Ancillary Benefits

Fig. 6 Climate policy generating primary and ancillary benefits, see R€ ubbelke (2002, p. 36)

forests provide a bequest value which the current generation derives from passing on the forests to future generations. Concerning the case of Brazil, Fearnside (2001, p. 180) stresses: “The environmental and social impacts of mitigation options such as large hydropower projects, mega-plantations or nuclear energy, contrast with the “ancillary” benefits of forest maintenance.” An overview of studies assessing the co-effects of afforestation is provided by Elbakidze and McCarl (2007, p. 565). Similarly, side effects arise from the implementation of more efficient technologies, the reduction of road traffic, and the substitution of carbon-intensive fuels. Ancillary or secondary benefits induced by these CO2-emission-reducing activities accrue, for example, when the emissions of other pollutants like particulate matter are reduced simultaneously (see Fig. 6). There are a number of terms which convey the idea of ancillary or secondary benefits. The others are co-benefits and spillover benefits (see IPCC 2001). The main difference is the relative emphasis given to the climate change mitigation benefits versus the other benefits (Markandya and R€ubbelke 2004, p. 489). In fuel combustion processes, CO2 emissions are accompanied by emissions of, e.g., NOX, SO2, N2O, and others. Therefore, fuel combustion reductions do not only cause a decrease in CO2 emissions but also diminish the emissions of other pollutants. In general, positive health effects of air pollution reduction that accompany climate protection measures are assessed to represent the most important category of secondary benefits. (However, Aunan et al. (2003, p. 289) annotate that “some particulate air pollution has a cooling effect on the atmosphere, reducing it may exacerbate global warming.”) Further negative impacts of air pollution, like accelerated surface corrosion, weathering of materials, and impaired visibility are mitigated by fuel combustion reductions, too. But, road traffic mitigation does not only produce ancillary benefits by reducing the emission of air pollutants, but it is also accompanied by lower noise levels and reduced frequency of accidents, less traffic congestion, and less road surface damage.

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While primary benefits accrue globally from the prevention of climate changeinduced damages, ancillary benefits are mostly local or regional (IPCC 1996, p. 217; Pearce 1992, p. 5). They represent domestic public goods for individual countries. (However, regarding the abatement of the greenhouse gases chlorofluorocarbons (CFCs), the ancillary effect of ozone layer protection and the respective ancillary benefits can be enjoyed globally.) Local air pollution mitigation generated by climate policy, for example, can be exclusively enjoyed by the protecting country. Therefore, ancillary effects can be considered to be private to the host country of a climate policy. Consequently, they differ from climate protection-related primary benefits which exhibit global publicness. Global damages arise, e.g., in the form of droughts caused by global warming. R€ubbelke and Vögele (2011, 2013) recently analyzed the effects of such droughts on the power sector. Several studies ascertaining the level of ancillary benefits found that such benefits even represent a multiple of climate protection-related primary benefits, as Pearce (2000, p. 523) illustrates in an overview. In the next stage, ancillary benefits will be explicitly introduced into our normal form game. It will be taken into account that ancillary benefits are enjoyed (mainly) privately by the host country of the climate protection activity. Ancillary benefits arise regardless of the behavior of the antagonist. In Fig. 7, ancillary benefits (ABA, ABB) are explicitly included into the matrix of the Chicken game, where it is assumed that ABA< ABB. Analogously to the procedure concerning the Chicken game situation without ancillary benefits, the mixed strategies can be investigated here. Again, probability q is determined by identifying the level of q, where the expected payoffs of both strategies of A (“participation” and “no participation”) balance. This is the case if ð
3 þ ABA Þ ð1
qÞ þ ð3 þ ABA Þq ¼
6 ð1
qÞ þ 6q:

(11)

Analogously p can be specified ð
3 þ ABB Þ ð1
pÞ þ ð3 þ ABB Þp ¼
6 ð1
pÞ þ 6p: Fig. 7 Chicken game with ancillary benefits

(12)

B’s strategy no participation

participation

no participation

−6, −6

6, −3 + ABB

participation

−3 + ABA, 6

3 + ABA, 3 + ABB

1–q

q

A’s strategy

1–p

p

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From Eqs. 11 and 12, q and p can be derived. Scientific studies largely assess that there are especially important co-benefits of local/regional air pollution reduction in developing countries; an overview of a selection of studies investigating ancillary benefits in developing countries can be found in Appendix 1. Neglecting potential differences in the primary benefits and supposing that A represents the group of industrialized countries, while B represents the developing world, we obtain: q ¼ 1⁄2 þ ABA =6 < p ¼ 1⁄2 þ ABB =6:

(13)

If country A (resp. country B) is uncertain whether the antagonist participates or defects, then it should participate provided it expects the antagonist to play “participation” with a probability of less than 1⁄2 þ ABA =6 (resp. 1⁄2 þ ABB =6). Comparison of Eqs. 10 and 13 shows that q and p rise due to the inclusion of ancillary benefits into the analysis. Consequently, for the Chicken game example illustrated above, it is found that taking ancillary benefits into account will increase the likelihood of cooperative behavior in international negotiations on climate change. According to Eq. 13, the inclusion of ancillary benefits into the reasoning brings about especially an increase in the likelihood that developing countries will participate in international climate protection efforts (for a more general analysis of the influence of ancillary benefits in international negotiations on climate change, see Pittel and R€ ubbelke 2008). Consequently, these results confirm Halsnæs and Olhoff (2005, p. 2324) who stress that “the inclusion of local benefits in developing countries in GHG emission reduction efforts will [. . .] create stronger incentives for the countries to participate in international climate change policies.” Yet, in their analysis of qualitative and strategic implications associated with ancillary benefits, Finus and R€ubbelke (2013) find a more moderate influence of co-benefits on the participation in international climate agreements and on the success of these treaties in welfare terms. They employ a setting of noncooperative coalition formation in the context of climate change. According to their results, ancillary benefits will not raise the likelihood of an efficient global agreement on climate change to come about although ancillary benefits provide additional incentives to protect the climate. The rationale behind this result is that countries taking the private ancillary benefits to a greater extent into account will undertake more emission reduction, irrespective of an international agreement. However, if we consider the high local/regional pollution levels in developing countries, it remains at least highly disputable whether developing countries conduct efficient local/regional environmental policies. Hence, the commitment in an international climate protection agreement will most likely help to raise the efficiency in local/regional environmental protection in these countries. Consequently, ancillary benefits – although not being the major impetus for immediate action – may take the role of a catalyst to climate policy (rather than that of a direct driver). Joining international climate protection efforts may become politically more feasible for

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developing countries (like China and India) which face serious local/regional pollution problems, when ancillary benefits are included in the political reasoning.

Price Ducks: An Approach to Break the Deadlock? Due to the inefficiency of the Kyoto Protocol scheme, which is a quantity duck since it stipulates emission-reduction quantity targets, there arose an intense discussion about general alternatives to such quantity ducks (which are more than just technology-focused climate policy partnerships like the APP). Nordhaus (2006, p. 31) points out: “Unless there is a dramatic breakthrough or a new design the Protocol threatens to be seen as a monument to institutional overreach.” • Price-influencing international climate protection schemes have been proposed by Nordhaus (2006) as a proper successor of the quantity approach of the Kyoto type. “This is essentially a dynamic Pigovian pollution tax for a global public good” (Nordhaus 2006, p. 32). An international carbon tax scheme where no international emission limits are dictated is considered to have several significant advantages over the Kyoto mechanism. This scheme could also contain side payments in order to motivate countries to participate: “Additionally, poor countries might receive transfers to encourage early participation,” Nordhaus (2006, p. 32). • Such a scheme is a price duck, because via the taxes, the prices of polluting activities are increased, such that there are additional incentives to mitigate the level of such polluting activities. • In contrast to taxing polluting activities in order to protect the climate, of course, prices can be influenced by subsidizing climate-protecting activities (e.g., energyefficient appliances or carbon sequestration measures could be subsidized). The subsidy will reduce the effective price of climate-protecting activities, and hence the agents receiving the subsidy will raise their provision level of climate protection. • Recently, Altemeyer-Bartscher, R€ubbelke, and Sheshinski (2010) elaborated Nordhaus’ proposal of an international carbon tax scheme. They analyze how individual countries or regions could negotiate the design of such a tax scheme in a decentralized way. In the scheme they suggest countries offer side payments to their opponents that are conditional on the level of the environmental tax rates implemented in the transfer-receiving opponent country. As can be shown, such a side-payment scheme might yield the first-best optimal tax policy and hence an efficient global climate protection regime. The scheme does not require the coercive power of a central global authority as the individual countries implement carbon taxes voluntarily. Altemeyer-Bartscher, Markandya, and R€ubbelke (2014) investigate the effects of ancillary benefits on the outcomes of this scheme.

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• Other price-influencing schemes which work in a similar way and do not require an international coercive authority are matching schemes which were first developed by Guttman (1978, 1987). Danziger and Schnytzer (1991) provide a general formulation of Guttman’s matching idea which allows for income effects, nonidentical players, and nonsymmetric equilibria. Guttman’s matching approach has been applied to the sphere of international environmental agreements by R€ ubbelke (2006) and Boadway, Song, and Tremblay (2007, 2011). Guttman’s basic scheme consists of two stages. Each agent i’s contribution xi to the public good can be written as: x i ¼ ai þ bi

n X aj

ðj 6¼ iÞ;

(14)

j¼1

where ai is the agent’s unconditional or flat contribution to the public good (in our case “climate protection”) and bi is his matching rate, which he provides for each unit of flat public good contributions by other agents. Therefore, the agent’s n X matching contribution is bi aj ðj 6¼ iÞ. The unit costs of the goods are supposed j¼1

to be equal to unity. The budget constraint of the agent in the shape of the income restriction is: yi þ ai þ bi

n X

aj ¼ I i

ðj 6¼ iÞ:

(15)

j¼1

Ii is again the monetary income of the considered agent i. In the first stage of the game, each agent makes a decision on the level of the matching rates he wants to offer to the other agents. It could be assumed that this decision is stipulated in an international agreement on matching rates, where all negotiating agents or decision makers – as representatives of their nations – agree on the matching rates their countries will provide (see R€ubbelke 2006). All the agents’ actions in both stages of the game are guided by welfare-maximizing behavior, i.e., the agents aim to maximize their individual countries’ welfare as represented by the function in Eq. 2. In the second stage, all agents will make decisions about their flat contributions. Total public good contribution of all agents then becomes equal to: X¼

n X i¼1

ai þ bi

n X

! aj

ðj 6¼ iÞ:

(16)

j¼1

Given the matching rates of the other agents, the considered agent will contribute flat contributions to the public good up to the level where the marginal rate of

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substitution between public and private good is equal to the effective price of the public good, i.e., where MRSi ¼

1þ

1 Xn

b j¼1 j

ðj 6¼ iÞ:

(17)

The decline in the effective price, from unity to the level specified on the right-hand side of Eq. 17, induces an increase in the private provision of the public good. Comparison of the right-hand sides of Eq. 4 (for which it is assumed that c = 1) and of Eq. 17 shows that in the matching scheme the considered agent or country faces a decline in the effective price of the public good “climate protection” as long as at least one other agent provides a positive matching rate bj. As Bergstrom (1989) illustrates, there are indeed incentives to announce positive matching rates. Consequently, the matching scheme has a price-influencing effect (similar to that of a subsidy) which the quantity targets stipulated by the Kyoto Protocol do not exert. Due to the decline in the effective price, the agent tends to raise the level of his public good provision. Put differently, within the matching scheme, individual countries manipulate (via their matching commitments) the effective price of climate protection from other countries’ point of view in order to influence these opponent countries to raise their public good provision levels. And as Boadway, Song, and Tremblay (2007, p. 682) point out: “the notion that countries might attempt to influence other countries’ contributions by preemptive matching commitments is not far-fetched in light of recent examples of disaster relief or international campaigns to combat the effects of infectious diseases.” In the case of identical agents, Summing (Eq.17) up over all i generates n X i¼1

MRSi ¼ n

1 ðj 6¼ iÞ 1 þ ðn
1Þbj

(18)

Hence, a Pareto optimum is attainable if each agent would choose bi ¼ 1 . As Buchholz, Cornes, and R€ubbelke (2009) demonstrate, matching may work better if there is a large number of agents/countries (than when there is a small number of agents), which is an important result if it is taken into account that international negotiations involve many countries.

Future Directions The Kyoto Protocol has been an inefficient agreement, although its flexible mechanisms (CDM, Joint Implementation, ETS) helped to mitigate this inefficiency. Efficiency would require that the cheapest GHG abatement options are abated first, which is not generally the case under the Kyoto Protocol. Furthermore, the

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emissions of large greenhouse gas emitters in the industrialized world, e.g., Russia and the USA, are not restricted under the protocol in the second commitment period. The immense threat of global warming necessitates an improved global climate protection regime, since otherwise the world might experience dramatic and lifethreatening consequences. Among the possible negative effects are the melting of glaciers, a decline in crop yields (especially in Africa), rising sea levels, sudden shifts in regional weather patterns, and an increase in worldwide deaths from malnutrition and heat stress (Stern 2007, Chap. 3). An improved future international climate protection regime has to organize climate protection more effectively, and it has to stipulate significant GHG emission reductions for all major polluters. Developing countries like China and India belong to the group of major emitter countries. Consequently, if international climate policy is to succeed in combating global warming, developing countries will also have to commit to emission reductions under an international agreement. Since there is no global coercive authority which could enforce countries to conduct an efficient climate protection in the future, mutual voluntary negotiations are the only means by which international coordination in climate protection can be accomplished. Put differently, “international treaties have to rely on voluntary participation and must be designed in a self-enforcing way” (Eyckmans and Finus 2007, p. 74). Yet, international easy- or free-rider incentives which are due to the global public good property of climate protection make the agreement on such an international treaty a difficult task. Another way to protect the global climate, which deviates from the Kyoto concept of stipulating GHG emission-reduction quantities, is the negotiation of international price-influencing regimes. These regimes manipulate effective prices via taxes, subsidies, or matching grants in order to influence the behavior of individual countries in such a way that globally efficient climate protection levels are reached. An international carbon tax, as suggested by Nordhaus (2006), might indeed yield a more efficient outcome, but due to the lack of will in the political arena to launch such a tax, it might be more promising to base the future global climate protection architecture on the already established structures associated with the Kyoto scheme. Yet, the advantages of price ducks like matching schemes are remarkable, and international price-influencing concepts like the global carbon tax or matching schemes should not be dismissed with levity. Private ancillary benefits may take the role of a catalyst to climate policy rather than a direct driver to international climate negotiations. Joining international climate protection efforts may become politically more feasible for developing countries (like China and India) which face serious local/regional pollution problems when ancillary benefits are included in the political reasoning. Not only co-effects in terms of reduced local/regional air pollution are relevant but also co-benefits in the shape of, e.g., economic development, energy security, and employment.

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Appendix 1 See Table 1 Table 1 Ancillary benefit studies regarding developing countries Study Aunan et al. (2003)

Country China

Pollutants (local/regional) PM, SO2, TSP

Aunan et al. (2004) Aunan et al. (2007) Bussolo and O’Connor (2001) Cao (2004)

China

SO2, particles

China

NOX, TSP

India

NOX, particulates, SO2 SO2, TSP

China

Cao et al. (2008)

China

Chen et al. (2007) Cifuentes et al. (2000) Cifuentes et al. (2001)

China

Dadi et al. (2000) Dessus and O’Connor (2003) Dhakal (2003)

Chile Brazil, Chile, Mexico China

NOX, particulates, SO2

CO, PM, NOX, SO2 Ozone, particulates SO2

Model/approach Comparison of studies that comprise a bottomup study, a semi-bottom-up study, and a top-down study using a CGE model Analysis and comparison of six different CO2abating options CGE model CGE model

Technology assessment, sensitivity to discount rate Integrated modeling approach combining a top-down recursive dynamic CGE model with a bottom-up electricity sector model Comparison of partial and general equilibrium MARKAL models No economic modeling Development of scenarios that estimate the cumulative public health impacts of reducing GHG emissions Linear programming model

Chile

CO, lead, NO2, ozone, PM, SO2

CGE model

Nepal

Analysis of long-range energy system scenarios

Eskeland and Xie (1998)

Chile, Mexico

Garbaccio et al. (2000) Garg (2011)

China

CO, HC, NOX, SO2, particles, lead NOX, particulates, SO2, VOCs PM, SO2

India

PM10

Gielen and Chen (2001)

China

NOX, SO2

Technology and cost-curve assessment

CGE model Health impacts (mortality and morbidity) quantified for different socioeconomic groups in Delhi MARKAL, technology assessment, and alternative policy scenarios (continued)

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Table 1 (continued) Country China

Pollutants (local/regional) SO2, TSP

Model/approach CGE model

China

Particulates

Shanghai MARKAL model

China

SO2

Li (2006) Markandya et al. (2009)

Thailand China, India

Particulates Particles

McKinley et al. (2005)

Mexico

Mestl et al. (2005) Morgenstern et al. (2004) O’Connor et al. (2003) Peng (2000)

China

CO, HC, NOX, particulates, SO2 PM, SO2

MARKAL of energy sector; base vs. advanced technology scenarios for controlling CO2 and SO2 Dynamic recursive CGE model Use of the POLES and GAINS models as well as of a model to estimate the effect of PM2.5 on mortality on the basis of the WHO’s comparative risk assessment methodology Analysis of five pollution control options in Mexico City

China

SO2

China

NOX, SO2, TSP

China

Particulates, SO2 SO2, development benefits NOX, SO2

RAINS-Asia for local and GTAP for economy-wide effects CGE model

China

SO2

Simulation model

China

SO2, TSP

China

Particulates, SO2

Synthesis of a significant body of research on co-benefits of climate policy in China No economic modeling

Mexico

CO, HC, NOX, particulates, SO2 SO2

Study Ho and Nielsen (2007) Kan et al. (2004) Larson et al. (2003)

Rive and R€ubbelke (2010) Shrestha et al. (2007) Smith and Haigler (2008) Van Vuuren et al. (2003) Vennemo et al. (2006) Wang and Smith (1999a, b) West et al. (2004) Zheng et al. (2011)

China

Thailand

China

China

Project-by-project analysis Survey of recent banning of coal burning in small boilers in downtown area of Taiyuan CGE model

Four scenarios, use of end-use-based AsiaPacific Integrated Assessment Model (AIM/Enduse) Sample calculations regarding interventions in the household energy sector

Linear programming model

Using a panel of 29 Chinese provinces over the period 1995–2007, application of panel cointegration techniques

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Ethics and Environmental Policy David J. Rutherford and Eric Thomas Weber

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Understanding Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Terminology and Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Perceptions, Communication, and Language of Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions: The State of Climate Change Knowledge and Future Predictions . . . . . Types of Mitigation Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Uncertainties and Moral Obligations Despite Them . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ethics and Reporting About Climate Science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Avoiding the Fallacy of Appealing to Ignorance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Limits of Challenges About Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Traditions and New Developments in Environmental Ethics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sources of Value in Environmental Ethics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Persons Who Experience Benefits and Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . New Developments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

This chapter offers a survey of important factors for the consideration of the moral obligations involved in confronting the challenges of climate change. The first step is to identify as carefully as possible what is known about climate change science, predictions, concerns, models, and both mitigation and adaptation efforts. While the present volume is focused primarily on the mitigation side of reactions to climate change, these mitigation efforts ought to be planned in part with reference to what options and actions are available, likely, and desirable for adaptation. Section “Understanding Climate Change,” therefore, provides an D.J. Rutherford (*) • E.T. Weber Department of Public Policy Leadership, The University of Mississippi, Oxford, MS, USA e-mail: [email protected]; [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_5

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overview of the current understanding of climate change with careful definitions of terminology and concepts along with the presentation of the increasingly strong evidence that validates growing concern about climate change and its probable consequences. Section “Uncertainties and Moral Obligations Despite Them” addresses the kinds of uncertainty at issue when it comes to climate science. The fact that there are uncertainties involved in the understanding of climate change will be shown to be consistent with there being moral obligations to address climate change, obligations that include expanding the knowledge of the subject, developing plans for a variety of possible adaptation needs, and studying further the various options for mitigation and their myriad costs. Section “Traditions and New Developments in Environmental Ethics” covers a number of moral considerations for climate change mitigation, opening with an examination of the traditional approaches to environmental ethics and then presenting three pressing areas of concern for mitigation efforts: differential levels of responsibility for action that affects the whole globe, the dangers of causing greater harm than is resolved, and the motivating force of diminishing and increasingly expensive fossil fuels that will necessitate and likely speed up innovation in energy production and consumption that will be required for human beings to survive once fossil fuels are exhausted.

Introduction Few subjects are as complex and as frequently oversimplified as climate change. After big snowfalls in winters past, news outlets have featured various observers of these local events, who dismiss the idea of global warming with statements such as “so much for the global warming theory” (LaHay 2000). On the other hand, climate scientists note that Earth’s average temperature has risen over time, and as a result, they predict increases in temperature extremes and vaporization of water that, in turn, lead to an expectation of increased snowfall in some years. Problems of understanding and misunderstanding such as these are important causes of confusion in discussions about climate change, and those problems and that confusion combined with the complexity of the issues at stake add considerable challenge to addressing the topic of focus in this chapter: the ethics of climate change mitigation. This chapter will argue that despite limitations to knowledge about the complexities of the climate system, certain efforts must be undertaken to prepare for and address the developments in climate change. The science on the subject is growing increasingly compelling, showing that there is need to work toward mitigating the causal forces that are bringing about climate change along with preparing adaptations to changes in climate, some of which have already begun (Walther et al. 2002). Furthermore, the existence of uncertainties with respect to climate science calls for more study of the subject of climate change, with greater collaboration than is already at work. Calling for further study of the subject, however, does not imply the postponement of all or any particular measure of precaution and potential action. This chapter will examine the current knowledge about climate change as well as the

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moral dimensions at issue in both seeking to minimize those changes and working to prepare for the changes and their effects. When the term “mitigation” arises in this chapter, it is important to keep in mind a consistent meaning. To mitigate something generally means to make it less harsh and less severe, but in relation to climate change, mitigation carries a more precise meaning. The term refers to human actions taken to reduce the forces that are believed responsible for the increase of the average temperature of the Earth. The primary concern with climate change is the increase of global average temperature, and mitigation is aimed at decreasing the rate of growth of this global temperature and stabilizing it or even decreasing it should it rise too high. Mitigation is sometimes referred to as abatement. Generally, the idea of abatement is either to reduce the rate of growth that is or will likely be problematic or to actually reverse the trend and reduce global average temperature. In contrast to mitigation, a second category of response to climate change is to find ways of adapting life to new conditions, the method of adaptation. Adaptation refers to adjustments made in response to changing climates that moderate harm or exploit beneficial opportunities (Intergovernmental Panel on Climate Change 2007a). The interesting issue that arises in focusing on climate change mitigation – the efforts to decrease the causal forces of rising global temperatures – is that subtle changes in temperature might be the kind to which some or even many people will be able to adapt relatively easily. For instance, if people live on coastal lands that are increasingly inundated, there are ways of reclaiming land from water or places to which people can move in adaptation to the climate changes. Other adaptations might include systems of planned agricultural crop changes prepared to avoid problems that could arise in growing food for the world’s increasing population. An important consideration about adaptation is that while humans may be able to change and adjust to changing climates, natural ecosystems and habitats may not, a point that will also be addressed in this chapter. There are certainly reasons to worry about sudden, great changes, but more gradual and less severe changes raise a host of ethical issues. For instance, it is reasonable to ask whether a farmer has the moral right to grow a certain crop. If so, then it may be that people have a responsibility to avoid changing the climate. Belief in such a right, however, could be considered highly controversial. What if farmers could reasonably expect some help in adapting the crops that they raise to new conditions? This idea would lessen the moral concern over the ability to grow a certain crop in a particular region, and thus a matter of adaptation would have bearing on the moral dimensions of climate change mitigation. It is likely that the best solution to address the ill effects of climate change will require a combination of mitigation and adaptation strategies. A central claim of this chapter, therefore, is that the ethics of climate change mitigation must not be considered in isolation from the options available for adaptation. Of the two, however, the more controversial, morally speaking, are abatement efforts or mitigation. This is because when climate conditions change, there will be no choice for people but to adapt to new circumstances if presented with serious challenges for survival, at least until humans are able to exert control in a desirable way on the trends in global climate. But abatement efforts, on the other hand, require sacrifices

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early, before certainty exists about the exact nature and extent of the problems to come and whom the problems, benefits, and mitigating efforts will most affect and how. Accompanying the problem of complexity that exists in climate change is a necessary challenge of uncertainty. The approach of addressing change through adaptive measures can be started early and is also possible as some more gradual changes occur, such as in the evacuation of islands that slowly disappear under the rising level of the sea. Other problems, however, are predicted to occur swiftly, such as in the potential disruption of the ocean conveyor, a “major threshold phenomenon” that could bring “significant climatic consequences,” such as severe droughts (Gardiner 2004, pp. 562–563). The problem of knowledge, of the limits to human abilities to identify where suffering or benefits will occur, under what form, by which mechanisms, implies that preventive adaptations may be impossible in the face of sudden changes in global climates. Furthermore, if there existed no idea of changes that might occur, this limited knowledge might render the effects of changing conditions less troubling morally speaking. But the fact is that today many scientists have devised models that suggest potential outcomes of climate change and so undercut the option of ignorant dismissal or avoidance of moral obligation. Limited knowledge about climate change first and foremost calls for increasing the knowledge and study of the subject, but it also demands consideration of the kinds of problems that can be expected, weighed against the anticipated costs of alleviating the worst of the threats. This chapter will offer a survey of a number of important factors for the consideration of the moral obligations involved in confronting the challenges of climate change. The first step is to identify as carefully as possible what is known about climate change science, predictions, concerns, models, and both mitigation and adaptation efforts. While the present volume is focused primarily on the mitigation side of reactions to climate change, these mitigation efforts ought to be planned in part with reference to what options and actions are available, likely, and desirable for adaptation. Section “Understanding Climate Change,” therefore, provides an overview of current understanding of climate change with careful definitions of terminology and concepts along with the presentation of the increasingly strong evidence that validates growing concern about climate change and its probable consequences. Next, section “Uncertainties and Moral Obligations Despite Them” will address the kinds of uncertainty at issue when it comes to climate science. The fact that there are uncertainties involved in human understanding of climate change will be shown to be consistent with there being moral obligations to address climate change. As mentioned above, these are obligations to know more than is currently known, to develop plans for a variety of possible adaptation needs, and to study further the various options for mitigation and their myriad costs. Plus, Gardiner (2004) presented a convincing case for the weighing of options that concludes in accepting the consequences of a small decrease in GNP from setting limits on global greenhouse gas emissions. Gardiner’s argument is compelling even in the face of uncertainty. After all, the uncertainties involved in climate change resemble uncertainties that motivate moral precaution in so many other spheres of human conduct. Finally,

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section “Traditions and New Developments in Environmental Ethics” covers a number of moral considerations for climate change mitigation. This section opens with an examination of the traditional approaches to environmental ethics and then presents three pressing areas of concern for mitigation efforts: differential levels of responsibility for action that affects the whole globe, the dangers of causing greater harm than is resolved (with geoengineering efforts, among others), and the motivating forces of diminishing and increasingly expensive fossil fuels that will necessitate and likely speed up innovation in energy production and consumption that will be required for human beings to survive once fossil fuels are exhausted.

Understanding Climate Change Given the complexity of addressing global climate change, it is crucial to clarify the meaning of a number of key terms, forces, and strategies for mitigation, so this first section will begin with a description of central terms and concepts at issue. The section then covers perceptions and methods for describing climate change because ideologies and affective influences on discourse about climate change can be used to mislead the public about the nature and the state of climate science. After that, the section examines the state of scientific knowledge and the predictions that the scientific community has presented about the future of climate change. This is important in order to grasp the extent of concern that world leaders and publics ought to feel about the future of the world’s climates. Finally, this section will close with a brief description of the various proposals that have been considered for mitigating climate change.

Terminology and Concepts Uncertainty, confusion, and misunderstanding result from poorly or ambiguously defined terminology and concepts, and this is especially the case with the topic of climate change. Climate change is complex and often elicits heated and impassioned public discourse. To reduce such problems, this section provides definitions for terms and concepts that are essential for both an explanation of what is known about climate change and for consideration of the broader topic of ethics and climate change mitigation. Some of these definitions are contested, and in such cases, the preferred definitions presented here will be contrasted with other definitions found in the literature, along with provision of an explanation for the selections made.

Weather and Climate The term “weather” refers to short-term atmospheric conditions occurring in a specific time and place and identified by the sum of selected defining variables that can include temperature, precipitation, humidity, cloudiness, air pressure, wind (velocity and direction), storminess, and more. Weather is measured and reported at the scale of moments, hours, days, and weeks. Climate, on the other hand, is defined

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(in a narrow sense) as the aggregate of day-to-day weather conditions that have been averaged over longer periods of time such as a month, a season, a year, decades, or thousands to millions of years. Climate is a statistical description that includes not just the average or mean values of the relevant variables but also the variability of those values and the extremes (McKnight and Hess 2000; Intergovernmental Panel on Climate Change 2007b).

The Climate System Understanding climate entails more than consideration of just the aggregated day-today weather conditions averaged over longer periods of time. Those average atmospheric conditions operate within the wider context of what is called the climate system that includes not just the atmosphere but also the hydrosphere, the cryosphere, the Earth’s land surface, and the biosphere. • The atmosphere is a mixture of gasses that lie in a relatively thin envelope that surrounds the Earth and is held in place by gravity. The atmosphere also contains suspended liquid and solid particles that “can vary considerably in type and concentration and from time to time and place to place” (Kemp 2004, p. 37). On average, 50 % of the atmospheric mass lies between sea level and 5.6 km (3.48 miles or 18,372 ft) of altitude. To highlight how thin this is, consider that the peak of Mt. McKinley in Alaska is 6.19 km (20,320 ft) above sea level and, as a result, the density of air is less than 50 % of that available at sea level or that the peak of Mt. Everest at 8.85 km (29,029 ft) has less than 32 % of the air density that is available at sea level. Commercial jet airliners generally fly at about 10.5 km (35,000 ft) above sea level, and humans would lapse into unconsciousness very quickly if cabin pressure were to decrease suddenly at this altitude (Strahler and Strahler 1978). • The hydrosphere consists of liquid surface water such as the ocean, seas, lakes, and rivers, along with groundwater, soil water, and, importantly, water vapor in the atmosphere. • The cryosphere consists of all snow, ice (glaciers and ice sheets), and frozen ground (including permafrost) that lie on and beneath the surface of the Earth. • Earth’s land surface consists of the naturally occurring rock and soil along with the structures (buildings, roads, etc.) that humans have constructed. • The biosphere consists of all living organisms, both plant and animal, on land, in fresh water, and in the ocean, including derived dead organic matter such as litter, soil organic matter, and ocean detritus. The climate system functions by means of complex interactions among these five components in which flows and fluxes of energy and matter take place through myriad processes such as radiation, convection, evaporation, transpiration, chemical exchanges, and many more (Climate Change 2007c). Given this complexity, climate science is an interdisciplinary endeavor that necessarily involves the interactions and contributions of a wide range of the physical sciences such as physics, chemistry, biology, ecology, oceanography, and the atmospheric sciences. Moreover, because

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human existence involves interactions with climate, the social sciences such as psychology, political science, and sociology also play important roles in human understanding. In addition, climate operates over time and space, so the synthesizing disciplines of history and geography have much to contribute as well. Furthermore, as shown later in this chapter, the humanities contribute to the understanding of the social dimensions of climate systems when it comes to considering the moral implications of various situations and actions in response to climate change.

Climate Change The most recent definition of climate change developed by the Intergovernmental Panel on Climate Change (IPCC) will be used in this chapter: Climate change refers to a change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean and/or the variability of its properties, and that persists for an extended period, typically decades or longer (Climate Change 2007c, p. 78; see also USCCSP (United States Climate Change Science Program) 2007).

Importantly, this definition is solely descriptive and includes no reference to causation, particularly no indication of the extent to which any changes in climate result from natural or human (anthropogenic) causes. Other definitions of climate change include causation, such as the United Nations Framework Convention on Climate Change: “Climate change” means a change of climate which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods (UNFCCC (United Nations Framework Convention on Climate Change) 1992, p. 3).

The first definition was selected for use in this chapter because it focuses on identifying and describing observed changes in climate and specifically refrains from assigning causation to either natural or anthropogenic processes. As a result, it draws attention to the distinction between two aspects of inquiry: (1) questions related to the presence, extent, and direction of changes in climate and (2) questions about causation of any observed changes, especially determinations of natural or anthropogenic causes. Views about (2) are often disconnected from questions about presence, extent, and direction of change and also tend to generate more contentious debate, especially in public and political discourse. As means to reduce contention, it is helpful to make the clear distinction between these two aspects of inquiry, and such clarity is especially important in this chapter, considering issues of ethics, mitigation, and adaptation. Additionally, and importantly, the selected definition implies no specific type of change(s) but instead fosters recognition that changes can occur in all manner of the variables that constitute climate such as temperature, precipitation, humidity, cloud cover, etc. (this point is further elaborated below with respect to the terms “climate change” and “global warming”). An additional reason to clarify the difference between (1) and (2) is that consideration of (1) generally engenders less controversy, while the task of determining

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who should act in addressing any needs that arise from climate change will depend in part on how one addresses issue (2). As such, (2) is not to be ignored in addressing the ethics of climate change, but after untangling (1) from (2), the problems to be addressed can be recognized for what they are more easily.

Climate Variability Most definitions of climate variability found in the literature differ little from the above definitions of climate change. For example, as defined in the Synthesis Report for the IPCC Fourth Assessment (Climate Change 2007c, pp. 78–79), the two terms actually seem synonymous in that they both refer to changes occurring on timescales of multiple decades or longer and they both allow for natural and anthropogenic causes. Other definitions of climate variability retain the focus on timescales of multiple decades or longer but limit climate variability to only natural causes (Batterbee and Binney 2008; Climate Research Program 2010). In this chapter, however, the term will refer to something different from either of these uses. The term “climate variability” is used in this chapter in recognition that the longterm, statistical averages of the variables that define climates can contain substantial variation around the mean. Droughts, rainy periods, El Niño events, etc., occur in time periods of a year to as much as three decades within climates that are considered to be stable as well as within climates that are experiencing changes in the longer term. This variability is different from extreme weather events such as floods and heat waves that occur on timescales of hours, days, and weeks, and it is also different from the long-term climate changes that occur on scales that span multiple decades to millions of years (which have already been defined above as “climate change”). The reasons to differentiate climate variability from climate change in this way are twofold. First, climate variability can generate considerable “noise” in the data that can lead to erroneous conclusions about climate change. For example, Fig. 1 shows two levels of variability – interannual and multi-decadal – that are present in the observed global temperature record that extends from 1880 to 2009. Interannual Global land-ocean temperature index .6 Temperature anomaly (°c)

Fig. 1 A line plot of the global land-ocean temperature index from 1880 to 2009, with the base period 1951–1980. The dotted black line is the annual mean and the solid black line is the 5-year mean. The gray bars show uncertainty estimates (GISS (Goddard Institute for Space Studies) 2010a)

Annual mean 5-year mean

.4 .2 .0 −.2 −.4 1880

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1920

1940

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variability (variability from year to year) is as much as 0.3  C (0.54  F), a range that could be expressed as 1 year with a very hot summer and a mild winter followed by a second year with a mild summer and a very cold winter. The conditions present in either of these years could lead people to make poor judgments about climate. In particular, the long-term warming trend that the graph shows occurring across the full 119-year period is sometimes dismissed because people generally give greater weight in decision making and opinion formation to immediate affective sensory input over cognitive consideration of statistics (Weber 2010) (more will be said below about human decision making that is affect based compared to a basis on statistical description). The variability over several decades is exhibited in Fig. 1 for the time period 1940–1980, which shows a plateau within the longer-term, 119-year warming trend. During this shorter time period, media reports and even a few researchers erroneously forecast “global cooling” based on the observational record at the time that included inadequate and uncertain data from years earlier than this time period and, obviously, no data beyond 1980 (de Blij 2005, p. 85). The second important reason for distinguishing between climate variability and climate change in the way defined in this chapter is related to dynamic equilibrium in ecosystems. Dynamic equilibrium results as ecosystems adapt to dynamic, ongoing forces that are not so extreme as to produce catastrophic changes. This dynamic equilibrium occurs because the change forces are not dramatic enough (or they cancel each other out), so that relative stability in the ecosystem can be perpetuated as the organisms (plants and animals) and the physical environment respond with adjustments that are within their adaptive capacities. In general, ecosystem adaptive capacity is not exceeded (and dynamic equilibrium is maintained) as a result of climate variability as defined here, but climate change, on the other hand, often exceeds this capacity and leads to fundamental alterations of the ecosystems. Such fundamental alterations occurring in natural ecosystems include processes such as species extinction, changes in community compositions, changes in ecological interactions, changes in geographical distributions, etc. Fundamental alterations can also occur within ecosystems upon which humans depend, leading to such changes as increases/decreases in agricultural productivity and the availability of water, changes in storm patterns, etc. (Intergovernmental Panel on Climate Change 2007a). These effects on both natural and human ecosystems will be discussed in more detail in what follows, but the important point here is that climate variability rarely produces such fundamental alterations, whereas climate change frequently can.

Global Warming and Global Average Temperature Global warming is defined as an increase in the average temperature of Earth’s surface NASA (National Aeronautics and Space Administration) 2007. As Fig. 1 illustrates, this average surface temperature has increased by 0.75  C  0.3  C (1.35  F  0.54  F) between 1880 and 2009. While this change might seem small, the paleoclimate record demonstrates that even “mild heating can have dramatic consequences” such as advancing or retreating glaciers, sea level changes, and changes in precipitation patterns that can all force considerable changes in human activity and

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push natural ecosystems beyond dynamic equilibrium (Hansen 2009). The graph in Fig. 1 comes from NASA’s Goddard Institute for Space Studies Surface Temperature Analysis (GISTEMP) database which contains temperature observations from land and sea from 1880 to the present (GISS (Goddard Institute for Space Studies) 2010b). It is one of the three such large databases of Earth surface atmospheric observations that all begin in the mid- to late nineteenth century and extend to the present. The National Oceanic and Atmospheric Administration (NOAA) maintains the second database that is titled the Global Historical Climatology Network (GHCN), and while this database contains observations from land stations only, it includes precipitation and air pressure data as well as temperature (National Climatic Data Center 2008). The third database is abbreviated HadCRUT3 which reflects the source of the dataset being a collaborative project of the Met Office Hadley Center of the UK National Weather Service (“Had”) and the Climate Research Unit (“CRU”) at the University of East Anglia. The Hadley Center provides marine surface temperature data, and the Climate Research Unit provides the land surface temperature data. These three databases are not completely independent because they share some of the same observation stations, but nevertheless, some differences in the raw data exist, and the three centers work independently using different approaches to the compilation and analysis done on the datasets. As such, the comparisons of results from the different databases allow for verification. Considerable consistency is apparent across the databases, especially in the overall trend of global warming since 1880. The different centers “work independently and use different methods in the way they collect and process data to calculate the global average temperature. Despite this, the results of each are similar from month to month and year to year, and there is definite agreement on temperature trends from decade to decade. Most importantly, they all agree that global average temperature has increased over the past century and this warming has been particularly rapid since the 1970s” (Stott 2011). Figure 2 shows the temperature record for each of the three datasets superimposed upon one another, and the consistency among them is clear. In addition, research has been done to identify and quantify uncertainty in the data, and good estimates of the uncertainty indicate that the data are valid. As one such study stated: Since the mid twentieth century, the uncertainties in global and hemispheric mean temperatures are small, and the temperature increase greatly exceeds its uncertainty. In earlier periods the uncertainties are larger, but the temperature increase over the twentieth century is still significantly larger than its uncertainty (Brohan et al. 2006, p. 1).

The temperature records shown in Fig. 2 for each of the three centers are developed as each center uses its dataset to calculate a “global average temperature,” both for the past and for monthly updates, and it is these values that are displayed on the graphs in the figure. While these calculations are done differently at the three centers, all three use the following general procedure. First, they expend considerable efforts to obtain the most accurate data possible and define the uncertainty that remains in those data. Then, the monthly average temperature value for each

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Anomoly (°C) relative to 1961– 1990

0.6 HadCRUT3 NCDC GISS

0.4 0.2 0 −0.2 −0.4 −0.6 −0.8 1850

1900

1950

2000

Fig. 2 Correlation between the three global average temperature records. All three datasets show clear correlation and a marked warming trend, particularly over the past three decades. The HadCRUT3 graph shows uncertainty bands which tighten up considerably after 1945 (WMO (World Meteorological Organization) 2010)

reporting station is converted into what is called an “anomaly.” The anomaly of each reporting station is calculated by subtracting the monthly average value from the average value that the station has maintained over some relatively long-term “base period” (e.g., the HadCRUT3 uses the period 1961–1990 as its base period). The reason for using anomalies is stated as follows: For example, if the 1961–1990 average September temperature for Edinburgh in Scotland is 12  C and the recorded average temperature for that month in 2009 is 13  C, the difference of 1  C is the anomaly and this would be used in the calculation of the global average (Stott 2011).

One of the main reasons for using anomalies is that they remain fairly constant over large areas. So, for example, an anomaly in Edinburgh is likely to be the same as the anomaly further north in Fort William and at the top of Ben Nevis, the UK’s highest mountain. This is even though there may be large differences in absolute temperature at each of these locations. The anomaly method also helps to avoid biases. For example, if actual temperatures were used and information from an Arctic observation station was missing for that month, it would mean the global temperature record would seem warmer. Using anomalies means missing data such as this will not bias the temperature record (Stott 2011; see National Climatic Data Center 2010a for additional explanation of the calculation and use of anomalies as used for the National Climate Data Center’s GHCN system). Even though using anomalies produces the most accurate record of Earth’s global average temperature, it is still interesting to calculate one single absolute “global

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average temperature.” Using the GHCN dataset (National Climatic Data Center 2010b), the average value for the last 10 years, the warmest decade on record (GISS (Goddard Institute for Space Studies) 2010a; Atmospheric Administration 2009; WMO (World Meteorological Organization) 2009), produces a global average temperature for planet Earth of 14.4  C or 58  F.

Climate Forcing and Climate Feedback Climate forcing refers to the processes that produce changes in the climate. The word force is generally defined as “strength or energy that is exerted or brought to bear [and that often] causes motion or change” (Merriam-Webster 2003). With respect to Earth’s climate system, a variety of forces cause climates to change. These are called “climate forcings,” and they are all related to Earth’s “energy balance,” that is, the balance between incoming energy from the Sun and outgoing energy from the Earth. The forcings can be internal or external. “Internal forcings” occur within the climate system and include processes such as changes in atmospheric composition or changes in ice cover that cause different rates of absorption/reflection of solar radiation. “External forcings” originate from outside the climate system and include processes such as changes in Earth’s orbit around the Sun and volcanic eruptions. Forcings can be naturally occurring, such as those resulting from solar activity or volcanic eruptions, or anthropogenic in origin, for example, the emission of greenhouse gases or deforestation (Intergovernmental Panel on Climate Change 2007a, p. 9). A feedback is defined as a change that occurs within the climate system in response to a forcing mechanism. A feedback is called “positive” when it augments or intensifies the effects of the forcing mechanism or “negative” when it diminishes or reduces the effects caused by that original forcing mechanism (Intergovernmental Panel on Climate Change 2007a, p. 875). Forcing and feedback mechanisms often interact in complex ways that make it difficult to decipher the processes and dynamics of climate change. This difficulty also frequently frustrates policymakers, the media, and the public, and it can result in the dissemination of misinformation, both intentional and unintentional, into the public discourse. One example of this relates to the relationship between carbon dioxide (CO2) and temperature. While it is relatively easy to understand that increasing concentrations of atmospheric CO2 can increase the naturally occurring greenhouse effect thereby causing global warming, confusion and misinformation result when research brings to light a climate record in which changes in the atmospheric CO2 level lag behind changes in temperature by 800–1,000 years. The legitimate question arises as to how it could be possible that CO2 causes global warming if the rise in temperature occurs before the increase in the atmospheric concentration of CO2. While the question is legitimate, unfortunately, some who are disposed to doubt claims of global warming neither seek answers to the question nor pursue additional investigation. Instead, they simply assert the premise that because CO2 lags temperature, it cannot possibly be the cause of global warming. However, a more objective review of the scientific literature emphasizes the importance of distinguishing between forcings and feedbacks.

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The initial, external forcing that begins the temperature changes observed in the climate record stems from fluctuations in the orbital relations between the Sun and Earth, and these fluctuations produce rather small changes in the amount of solar radiation reaching Earth (Hays et al. 1976). This relatively weak forcing action causes small temperature changes that are then amplified by other processes (Lorius et al. 1990). One such amplifying process that appears to be quite significant occurs because ocean temperature changes also change the ocean’s capacity to retain soluble CO2. As this capacity changes, it causes CO2 to either be released from the oceans into the atmosphere (during times of warming temperatures) or removed from the atmosphere and dissolved into the oceans (during times of cooling temperatures). Consequently, CO2 operates in these situations as a positive feedback mechanism that augments the temperature change. In other words, it enhances the greenhouse effect and amplifies temperature increases during times of warming and reduces the greenhouse effect and reinforces temperature decreases during times of cooling (Martin et al. 2005). Careful analysis therefore suggests that a climate record which shows CO2 operating as a feedback mechanism neither negates nor renders less likely the potential that CO2 could operate as an initial forcing mechanism as well. Considering that the atmospheric concentration of CO2 has increased by 25 % in the last 50 years (Atmospheric Administration 2010), it is entirely possible that this increasing CO2 concentration is functioning as the forcing agent for contemporary global warming. Simply put, it is a false premise to claim that CO2 could not be causing contemporary global warming because CO2 has been observed to lag behind temperature changes in the past. This false premise has been lampooned by the analogous statement that “Chickens do not lay eggs, because they have been observed to hatch from them” (Bruno 2009).

Global Warming Versus Climate Change The terms “global warming” and “climate change” have been defined above, and those definitions will not be repeated here. But it is important to emphasize the difference between the two terms and the significance of exercising precision in use of them. While “global warming” is a useful way to refer to the increase of global average temperature that strong scientific evidence shows has occurred over the last 130 years (Fig. 2), for some people, the term carries the automatic connotation that human activity is the cause of this observed temperature increase. As stated earlier, a clear distinction should be made between questions that, on the one hand, relate to the changes in climate, if any, that are occurring and, on the other hand, the causes of any identified changes, specifically, naturally occurring or anthropogenic. Because the term “global warming” carries the more polemical and politicized connotation, it poses a higher probability of conflating the two questions than does the term “climate change” which has not yet attracted such politicized interpretations. Consequently, in general, the term “climate change” is preferable. A second deficiency with the term “global warming” is the one-dimensional and totalizing change that it implies. Although the average temperature of planet Earth is increasing, the temperature change that any particular place on the Earth might

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experience could be cooling instead of warming, or perhaps that place might be experiencing no change in temperature at all. But the term “global warming” is easily, and perhaps most naturally, understood to mean that all places on the Earth will experience warming. Moreover, even if the term is explained, it does not readily lend itself to the broader understanding that although the global average temperature is increasing, it is not necessarily the case that temperature is increasing at any given place on Earth. The term “climate change,” on the other hand, does not imply this uniform nature of change and thus possesses greater capacity to communicate the potential for different changes occurring in different places and regions. In addition, the term “global warming” implies a narrow view of the nature of changes that can occur in the climate system, namely, an exclusive focus on temperature. But the possible changes to climate are not restricted to just the climate variable of temperature, and the observed increase in global average temperature has been associated with changes in a range of other climate variables that include precipitation amounts, timing and patterns, cloudiness, humidity, wind direction and velocity, storminess, and more. While the term “global warming” places the focus on temperature, the term “climate change” offers a much richer capacity to incorporate these other types of changes as well and, as a result, is generally emerging as the preferred term.

Thresholds and Tipping Points The term “threshold” in ecology and environmental science means “a fixed value at which an abrupt change in the behavior of a system is observed” (Park 2008, p. 450). In climate science, the term “climate threshold” means the point at which some forcing of the climate system “triggers a significant climatic or environmental event which is considered unalterable, or recoverable only on very long time-scales, such as widespread bleaching of corals or a collapse of oceanic circulation systems” (Intergovernmental Panel on Climate Change 2007a, p. 872). Substantial research indicates that climate changes are prone to such thresholds, or “tipping points,” at which climate on a global scale or climates at regional scales can suddenly experience major change (Committee on Abrupt Climate Change 2002; Lenton et al. 2008). A wide number of complex systems exhibit similar threshold events – financial markets, ecosystems, and even epileptic seizures and asthma attacks – in which the system seems stable right up until the time when the sudden change occurs (Scheffer et al. 2009). Research has provided general ideas on where these thresholds or tipping points might operate with respect to climate – the loss of Arctic sea ice or Antarctic ice shelves, the release of methane into the atmosphere from the melting of Siberian permafrost, or the disruption of the “oceanic conveyor belt” – but this knowledge is rudimentary at best. Scheffer and colleagues (2009) report tentative efforts to identify “early warning signs” that precede threshold events, and with respect to climate, they state that “flickering,” “rapid alterations,” or increased weather and climate “variability” seem to have preceded sudden changes observed in the climate record. But at present, predicting these climatic thresholds is vague at best. One of the authors explained the idea of thresholds and the uncertainty about them in an interview with Time magazine, “Managing the environment is like

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driving [on] a foggy road at night by a cliff.. . .You know it’s there, but you don’t know where exactly” (Walsh 2009).

Defining and Communicating Uncertainty Clearly, climate science contains uncertainties that are endemic to the data sources used, to the understanding of processes involved, and to predictions of future trends, impacts, and outcomes. Consequently, it is essential to accompany any study of climate change with careful, explicit, and candid assessments of the levels of certainty or confidence associated with the findings or claims made. Indeed, reports or studies are suspect if they fail to include such information and/or if they make unequivocal statements about “proving” their points. To some extent, the same can be said about commentaries, news reports, or various information sources. While the politicized environment in which climate change is debated might encourage strong and definite affirmations, such statements can prove counterproductive if they are perceived or exposed as exaggerated (Weber 2010; Hodder and Martin 2009). Numerous approaches exist for defining and communicating uncertainty, and this brief discussion here does not attempt a comprehensive overview. Instead, it focuses on the approach that the IPCC has developed for its assessment reports. The main function of the IPCC is to “assess the state of our understanding and to judge the confidence with which we can make projections of climate change, its impacts, and costs and efficacy of options,” but in its first and second assessments (1990 and 1995, respectively), the IPCC gave inadequate attention to “systematizing the process of reaching collective judgments about uncertainties and levels of confidence or standardizing the terms used to convey uncertainties and levels of confidence to the decision-maker audience” (Moss 2006, p. 5 emphasis added). Consequently, the IPCC conducted a comprehensive project to rectify these inadequacies (Moss and Schneider 2000; Manning et al. 2004), and the result was the following system for defining and communicating uncertainties in the Fourth Assessment Report published in 2007. The first step is to present a general summary of the state of knowledge related to the topic being presented. This summary should include (1) the amount of evidence available in support of the findings and (2) the degree of consensus among experts on the interpretation of the evidence (Climate Change 2005). Figure 3 illustrates how these two factors form interacting continua that produce qualitative categories. The IPCC guidance notes for addressing uncertainty (Climate Change 2005, p. 3 emphasis in original) state that in cases where the level of knowledge is determined to be “high agreement, much evidence, or where otherwise appropriate,” additional information about uncertainty should be provided through specification of a level of confidence scale and a likelihood scale. The level of confidence scale addresses the degree of certainty that the results are correct, while the likelihood scale specifies a probability that the occurrence or outcome is taking place or will take place. The IPCC guidelines state that the level of confidence scale “can be used to characterize uncertainty that is based on expert judgment as to the correctness of a model, an analysis or a statement. The last two terms in the scale should be reserved for areas of major concern that need to be considered from a risk or opportunity perspective, and

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Established but Incomplete High agreement / Limited Evidence

Speculative Low agreement / Limited evidence

Well Established High agreement / Much evidence

Competing Explanations Low agreement / Much evidence

Increasing amounts of evidence (theory, observations, models)

Fig. 3 Conceptual framework for assessing the current level of understanding (Moss 2006; Climate Change 2005)

the reason for their use should be carefully explained” (Climate Change 2005, p. 4). Table 1 shows the scale. The likelihood scale is used to refer to “a probabilistic assessment of some well defined outcome having occurred or occurring in the future” (Climate Change 2005, p. 4).

Adaptation and Mitigation The terms “adaptation” and “mitigation” were briefly discussed in the introduction of this chapter, but the more detailed definition and explanation in Table 2 outline important distinctions that will be helpful for the sections of the chapter that follow.

Perceptions, Communication, and Language of Climate Change Moser (Moser 2010, p. 33) writes that “a number of challenging traits make climate change a tough issue to engage with,” and she implies that something in the nature of climate change itself makes it more challenging for people to perceive and communicate about than many other, even related issues (environmental, hazards, health). She lists the following characteristics of climate change that produce this substantial challenge: • Invisible causes: Greenhouse gasses are not visible and have no direct or immediate health implications. The same is true for other forcing agents such as Earth/ Sun relations. • Distant impacts: The lack of immediacy in temporal and geographic distance. • Insulation of modern humans from their environment: This diminishes the perception of any changes in the climate or their significance. • Delayed or absent gratification for taking action: Action taken today is not likely to reduce global average temperature within the lifetime of the person taking the action. • The lack of recognition that humans have of their technological power: This produces disbelief that humans have the capacity to alter the global climate.

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Table 1 Scales of uncertainty used in the IPCC Fourth Assessment Report, 2007. None of these are statistically significant because no tests are conducted to determine the values. Instead, they are based on expert judgment Qualitatively calibrated levels of confidence (Climate Change2005) Terminology Degree of confidence in being correct Very high confidence At least 9 out of 10 chances of being correct High confidence About 8 out of 10 chances of being correct Medium confidence About 5 out of 10 chances of being correct Low confidence About 2 out of 10 chances of being correct Very low confidence Less than 1 out of 10 chances of being correct Likelihood scale (Intergovernmental Panel on Climate Change2007b) Terminology Likelihood of the occurrence or outcome (%) Virtually certain >99 Extremely likely >95 Very likely >90 Likely >66 More likely than not >50 About as likely as not 33–66 Unlikely 20 ktCO2/year (any year of 2011–2014) New regulation: Industry >10 ktCO2/year, mandatory reporting when >5 ktCO2/year, Non industrial sectors: with > 5 ktCO2/year Transport: threshold TBD

New entrants reserve (20 Mt). New project (including capacity extension or

metals, glass and paper)

commercial) construction.

In case of closure or displacement of activity, compliance obligation is

and paper, rubber, chem. fiber); other sectors (aviat., ports, rail., comm.,etc.) 191 companies Threshold: 20 ktCO2/year (any year of 2010 or 2011) for industrial companies; 10 ktCO2e/ year for other sectors. Mandatory emissions reporting for about 600 firms. Threshold: 10 ktCO2/year

Reserve (2 % of total cap). New fixedasset projects with over ¥ 200 million

832 companies Threshold: 5 ktCO2e/ year 197 large buildings. Threshold: 20,000 m2 for public buildings and 10,000 m2 for state office buildings. Mandatory reporting. Threshold: emissions btw. 3-5 ktCO2e/year +

under consideration.

(continued)

114 entities Threshold: 20 ktCO2/ year (any year since 2009) Mandatory reporting for carbon intensive industries and civil buildings with >10 ktCO2e/year (steel, iron, power, heating, (petro) chemicals). Compliance obligation in case of closure.

civil buildings.

Emissions Trading 287

Allocation

Grandfather method (2009–2011)

allowance change.

Beijing

Grandfather (2008–2012)

Chongqing

Sources: Zhong (2014), Wu et al. (2014), Quemin and Wang (2014)

Pilots

Table 1 (continued)

Grandfather method (2010–2012)

reconstruction) with >10 ktCO2/year should purchase all quotas prior to operation. Quota reallocation for activity change, reduction and closure.

Guangdong

Comprehensive method; grandfather

Hubei

Grandfather (2009–2011) Benchmarking

due and 50 % of followingyear allowances after obligation shall be taken back.

Shanghai

invest. should submit emission eval. report. In case of closure or displacement of activity, compliance due and 50 % of followingyear allowances shall be taken back. Carbon Emission per Industrial Value Added

Shenzhen

Grandfather (base year not specific)

Tianjin

288 R. Raufer et al.

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Table 2 Economic structure of the seven carbon market pilot regions (% share of GDP, 2012) Pilots Beijing Chongqing Guangdong Hubei Shanghai Shenzhen Tianjin

Primary sector 0.9 % 8.6 % 5% 13.4 % 0.7 % 0.1 1.6

Secondary sector 24 % 55 % 50 % 48.7 % 42.1 % 47.5 % 52.4 %

Tertiary sector 75.1 % 36.4 % 45 % 37.9 % 57.2 % 52.4 % 46.0 %

Energy mix (coal) 43 % 50 % 22 % 72.5 % 30 % 59 % 71 %

Sources: PMR (2014), Liu and Xu (2012), UNDP China and Institute for Urban and Environmental Studies, CASS (2013)

Despite the variation among them, the seven pilots also share many fundamental features. All pilots include both indirect and direct emissions of carbon dioxide (ICAP 2014b). Most pilots use grandfathering as the principal method by which to allocate initial allowances (PMR 2014). Nearly all pilots distribute allowances for entities mandated to participate in the cap-and-trade system at the beginning of a compliance year without a charge. (In Shenzhen and Guangdong, however, a small number of allowances are also allocated via fixed-price sale or auction (King and Wood Mallesons 2014).) The majority of pilots allow offsets that may or may not include CCERs and other offset types (such as Hubei, which includes forest offsets from within the Province; Chongqing is also considering doing so). Finally, most, with the exception of Shenzhen, which bases its cap on a set of criteria, set their cap based on a minimum quantitative level of carbon emissions. Carbon trading transactions reached approximately USD 140 million by September 2014 (Carbon Eight Group 2014). Every pilot region has its own carbon exchange; membership in the exchange is a prerequisite for trading. Allowances are tradable only in the regional exchanges. During the first year in which trading took place, price volatility was a feature of most of the pilot regions. Prices also varied considerably from one region to the next, not surprisingly, given the variation in design and economic structures among the pilot markets (see Fig. 13). Trading volumes have also been quite low. As one study points out, Shenzhen, which has been the most active of the pilot markets, traded just 4 % of the total allowances available in its market during his first compliance year (Munnings et al. 2014). Pilots have been experimenting with ways to boost liquidity. To date, Chinese authorities have prohibited futures contracts in carbon trading out of concerns that doing so would invite destabilizing speculation in its financial markets. However, Guangdong, Tianjin, and Hubei have allowed some investors to trade permits with entities bound by emissions limits. Shanghai allows registered institutional investors to trade permits; Shenzhen plans to allow foreign investors to do so, reportedly allowing trading in foreign currency (Chen and Reklev 2014b).

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Fig. 13 Prices for Chinese ETSs, July 2013–October 2014 (Source: Bifera 2014)

China ETS Phase II The announcement by a senior climate policy official from the NDRC in late August 2014 that China would launch a national carbon market by 2016, with regulations for a national market to be sent to the State Council for approval by the end of the year, was an unequivocal commitment by China’s central authorities to scale up carbon market development (Chen and Reklev 2014b). Launching a national carbon market would be an ambitious undertaking for even the most developed economy; to implement cap-and-trade on a nationwide scale for a transitional economy the size and complexity of China’s requires authorities to tackle numerous challenges. They must not only arrive at a functional design but also construct the institutions necessary to create a national market for buying and selling carbon. Doing so requires substantial numbers of technically capable trained personnel along with regulatory institutions that can set emissions caps, support an emissions trading registry, and monitor trading and enforce compliance. Pilots have taken on these challenges at the local level. However, as will be discussed below, the development of regional schemes has also revealed the challenges of designing an effective market in a political-economy in which transparency is limited. For a market to function, an accurate accounting of carbon emissions must be made in order for legitimate transactions to take place. China’s official data collections systems are highly opaque, a feature that must be adjusted for cap-and-trade to work. Specifically, a national MRV system capable of inspiring confidence in trade for an intangible commodity must be developed (Kong and Freeman 2013). In short, on the institutional front, as China’s proposal for market readiness observes, what is required is a “reliable statistical system, effective program management system and necessary laws and/ or regulations.” (PMR 2013). The latter includes the passing by the National People’s Congress of a national environmental law that defines carbon as a commodity and explicitly enables enforcement of compliance by regulated firms (Munnings et al. 2014).

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In addition to institutional development and implementation, it is also necessary that the central government determine which specific sectors will be covered by the national carbon market, with an eye to future emissions trends, mitigation potential, and other factors such as international linkages (PMR 2013). China has already published monitoring and reporting guidelines for the national level, covering ten sectors: power generation, power transmission and distribution, aviation, cement, ceramics, flat glass, electrolytic aluminum, magnesium smelting, chemicals, and iron and steel. Among the considerations to be addressed are the development of policies to mitigate potential constrains on firm competitiveness and leakage from cap-andtrade; ways of encouraging liquidity without excessive risk to China’s fragile financial system; and management of potential new entrants to ensure that increased participation does not add to carbon emissions (Munnings et al. 2014).

China ETS Challenges and Opportunities Ahead China’s bottom-up approach to carbon market development offers numerous lessons for the NDRC as it moves forward. However, the differences among the protocols established for measuring emissions among pilots alone reflects a heterogeneity which will pose challenges to future efforts at harmonization. The seven pilots applied different rules for monitoring, reporting, and verifying emissions; however, a national market requires a single set of enforceable procedures (Kong and Freeman 2013). Chinese authorities, led by the NDRC, are in the process of drafting a National Climate Change law that could provide a legal foundation for a national trading system. The NDRC has also published guidelines for some industries to date but a national registry for greenhouse gas emissions is still under development (Song and Lei 2014). Moreover, for a cap-and-trade system to function, China must develop a system for data reporting, and for collecting greenhouse gas emissions data about industrial sources that is transparent. In addition, China’s lack of a welldeveloped legal system means that compliance by individual firms is heavily dependent on administrative enforcement, which in turn relies on the capacity and will of local authorities to do so. Currently, local officials’ (cadres’) promotion opportunities are closely linked to economic growth. China’s central authorities will have to complete the retooling of China’s “cadre evaluation system” to increase the effectiveness of local implementation, as they move ahead with legal development in the country. Other key systems structuring China’s economy also require reform and development for a national cap-and-trade system in China to function effectively. First, reforms are needed in how China manages power pricing. Currently, there are centrally-determined price caps on electricity in place that prevent power producers from passing on the cost of carbon to consumers. This explains why local pilots exclude the power sector or limit coverage to implied (i.e., emissions divided by activity) rather than direct emissions from power consumption. To fully bring the power sector– among the largest sources of carbon emissions in China – into the carbon trading system, difficult national policy changes in this area will be required (Kong and Freeman 2013). Second, China’s financial system remains undeveloped and fragile. Concerned about risk, China’s NDRC took futures trading off the table

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of options for local carbon trading pilots’ design. However, most experts see trading in derivative products as necessary for China’s carbon market to have the liquidity to be an effective tool in reducing the cost of cuts to emissions (Song and Lei 2014). China’s authorities are actively engaged in pushing reforms in the financial sector that will bring it into line with more mature economies; however, this process is a delicate one that will take time. Finally, national tools must be developed to mitigate against the potential for carbon leakage. This requires the ability to assess the risks of leakage accurately so that provisions can be made for regulated enterprises subject to this risk – something the European cap-and-trade system does through rebates in the form of allocations (Munnings et al. 2014). These are just some of the tasks ahead for China as it develops carbon trading on a national scale. Thus, while China’s pilot markets mark significant progress toward the development of cap-and-trade, the country still has a long way to go to build an effective national carbon trading system.

US Carbon Trading Programs While the US played a key role in introducing emissions trading through its ETP and acid rain regulatory programs, and also introduced the market-oriented approach into the Kyoto Protocol, the Bush Administration’s withdrawal from the Kyoto process in early 2001 led to a significantly diminished role for the country. European countries, initially quite skeptical about emissions trading, assumed the lead with the launch of the EU ETS in January 2005. The US did not pursue national carbon trading during the Bush administration, but expectations grew as the 2008 elections approached, because all three major candidates – Hillary Clinton and Barack Obama on the Democratic side and John McCain on the Republican one – espoused support for cap-and-trade legislation during the Presidential campaign. The build-up to the Copenhagen meeting thus assumed that the US would rejoin international efforts, and perhaps link its own national carbon market to ongoing EU ETS and Kyoto Protocol efforts. Such enthusiasm was enhanced when the American Clean Energy and Security Act (ACES) passed the US House of Representatives less than 6 months after Obama’s inauguration in January 2009. It contained an allowance-based program that required a 17 % CO2 reduction by 2020 (from a 2005 base year) and an 83 % reduction by 2050. Often referred to as the Waxman-Markey bill (after its two principal sponsors), ACES provided for the use of international offsets and also included an allowance price floor. Very similar legislation, entitled the American Power Act (APA), was submitted to the US Senate by Senators Kerry and Lieberman in May of 2010 – but a special election in the State Of Massachusetts earlier that year meant that the Democrats no longer had a “filibuster-proof” Senate (i.e., a Senate able to pass legislation over the objections of Republicans). The overwhelming Republican victory in mid-term elections later in 2010 ensured that such cap-and-trade legislation would not be enacted at the national level, and that party’s efforts have since then focused on rolling back existing environmental legislation (and US EPA’s budget) rather than passing new mandates. Prospects for new emissions trading legislation thus appear quite bleak; as one recent

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article in Foreign Policy noted: “Congress will never pass cap-and-trade, at least until Miami starts flooding” (Galbraith 2014). Despite such problems, market-oriented GHG control efforts continued at the state level (in California); at the regional level (in the Northeast’s Regional Greenhouse Gas Initiative [RGGI]); and even at the national level, through previous legislation initially designed for CAC regulation. These three levels of programs in the US are described below:

California’s Emissions Trading Program California’s cap-and-trade program is a result of the California Global Warming Solutions Act of 2006 (AB 32), which required the state’s Air Resources Board to develop regulations and market mechanisms to cut the state’s GHG emissions back to 1990 levels by 2020 – a reduction of approximately 25 %. Its emissions trading program is thus part of a larger regulatory effort (including a Low Carbon Fuel Standard as well as other energy efficiency standards) to achieve that target. The market-oriented program went into effect in January, 2012, with compliance obligations beginning 1 year later. The first two compliance years focus solely on electricity and industrial sectors, but the program will expand after that to include transportation and heating fuels (see Fig. 14). It is thus the first multisector carbon trading plan in the US, and given its emissions coverage, is second in size only to the EU ETS.

450 400 350 Offsets 300 Allowances

250 e2 /year 200 MMTCO 150

Narrow Scope Projected BAU Emissions Broad Scope Projected BAU Emissions

100 50 0 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Year

Fig. 14 California’s GHG Cap compared with BAU projections (Source: Center for Climate and Energy Solutions 2014; adapted from CARB 2010)

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The market covers the same six pollutants as the first commitment period of the Kyoto Protocol, as well as NF3 and other fluoridated gases. It covers approximately 350 business (with 600 facilities), and has been designed to link with similar trading programs in other states and regions. The California market has several notable features, including both cost containment and market flexibility mechanisms. There is an auction floor price (starting at $10 per allowance in 2012, rising at 5 % above inflation annually) and a strategic reserve (rising from 1 % to 7 % over time, with higher tiered prices similarly rising at 5 % above inflation). There are thus both floor and ceiling mechanisms in place to contain prices (as long as there are sufficient allowances in the reserve). There are three compliance periods: (a 2-year period [2013–2014]), followed by two 3-year periods [2015–2017 and 2018–2020]). At the end of every year, a source must provide allowances and offsets to cover 30 % of its previous year’s emissions. Then, at the end of each compliance period, it must provide the remaining allowances and offsets. This provides sources with the ability to cover any annual variation in product output. If the source does not do so and is not in compliance, then four allowances must be surrendered for every ton not covered within the compliance period. Offsets are allowed in the California program, but were initially restricted to US emission reduction projects from four targeted types: forestry; urban forestry; dairy digesters; and the destruction of ozone depleting substances. A linkage with Quebec’s emissions trading scheme began in January 2014, and linkages with other systems are ultimately expected to occur as well.

Regional Greenhouse Gas Initiative The Regional Greenhouse Gas Initiative (RGGI) was the first regulatory US capand-trade scheme addressing GHGs. It was designed to reduce CO2 emissions from power plants in ten Northeastern US states – although this was subsequently reduced to nine states when the Republican Governor of New Jersey withdrew his state from the program in 2011. RGGI is a regional program, but it is implemented through legislation adopted by each individual state. A “Model Rule” was drafted in 2006 and finalized in 2008, with requirements for individual facilities (i.e., fossil-fueled power plants greater than 25 MW generating capacity) beginning on January 1, 2009. RGGI initially sought to cap CO2 emissions at a steady rate through 2014, and then drop them annually by 2.5 % – and thus achieve a 10 % reduction one decade later. A significant fuel shift towards natural gas at power plants in the region, however, coupled with lower electricity demand and increased levels of both nuclear power and renewables led to an overallocation of allowances. Prices reflected that, and the clearing price for allowances at RGGI auctions was often less than $2. RGGI’s target was revised when New Jersey left, and was then significantly changed as a result of a 2012 Program Review. The new cap called for a reduction of 45 % by 2020 (from 2005 levels), with a 2.5 % reduction occurring annually from the revised 2014 cap levels. This new Model Rule also introduced other provisions, including a Cost Containment Reserve (CCR), and an interim compliance period requiring sources to hold specific allowance levels in time periods before final

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compliance dates (Bifera 2013). Most of the allowances in RGGI are sold through auctions, and the collected funds are dedicated for energy efficiency, renewable and clean energy, as well as bill support for low-income energy consumers. RGGI allows offsets to achieve compliance, but only from five categories: (1) Landfill methane capture and destruction; (2) Reduction in emissions of sulfur hexafluoride (SF6) in the electric power sector; (3) Sequestration of carbon due to US forest projects (reforestation, improved forest management, avoided conversion) or afforestation (for CT and NY only); (4) Reduction or avoidance of CO2 emissions from natural gas, oil, or propane end-use combustion due to end-use energy efficiency in the building sector; and (5) Avoided methane emissions from agricultural manure management operations (RGGI n.d.). Despite the significant drop in target levels in 2014, Fig. 15 shows that the actual emissions in recent years were not significantly above the new cap (i.e., 92 million short tons in 2012, just above the 91 million ton target in 2014). The cap will tighten in coming years, however, and it is not clear that the fuel shifts and other downward trends evident in recent years will continue. Thus, it is anticipated that the RGGI cap could become more binding in the future (EIA 2014).

The US EPA’s Clean Power Plan President George Bush promised to address CO2 emissions during the 2000 Presidential campaign, but reneged on this shortly after taking office. In 2003, his Administration’s EPA overturned a previous Clinton Administration decision, and declared that it did not have the authority to regulate CO2 under the Clean Air Act – and further noted that it would refrain from doing so, even if it did have the authority. The State of Massachusetts and others filed suit against EPA for its failure to act, a suit which was subsequently decided in their favor in 2007 by the US Supreme Court. The Court ruled that EPA did have such authority, but the law required EPA to determine whether or not such emissions could reasonably be anticipated to endanger public health or welfare. In 2009, under the Obama Administration, US EPA issued such an “Endangerment Finding,” and proceeded to issue new standards for light, medium and heavy duty vehicles in the following years. The Agency also proposed GHG standards for new power plants in 2012 and then revised and proposed them once again in September 2013. On June 2, 2014, it proposed standards for existing power plants, under a program called the Clean Power Plan. Utility emissions are the largest source of carbon pollution in the US, accounting for roughly one-third of all domestic GHGs (EPA 2014b). The Clean Power Plan tackled this in two ways: (1) It set state-specific goals, which were based on achieving a level of carbon intensity in the state by 2030. This would have the effect of reducing CO2 emissions from the power sector by 30 % (from a 2005 base) and (2) The EPA provided guidelines for the states in how they might achieve such goals. Under the Clean Power Plan, states would have until June 2016 to submit plans to achieve these goals, with the possibility of a 1-year extension – or 2 years if states join together in a multistate plan. The states were also required to make “reasonable progress” in achieving such goals by 2020.

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million short tons RGGI goes into effect in 2009

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Fig. 15 Regional Greenhouse Gas Initiative CO2 emissions cap vs. actual emissions (Source: EIA 2014)

Section 111(d) of the Clean Air Act requires US EPA to issue “standards of performance” reflecting the “best system of emission reduction” (BSER), and the Agency has used four “building blocks” of BSER to set the state-by-state goals: (1) heat rate improvements; (2) dispatch changes among affected units (e.g., coal to natural gas units); (3) expanded low- or zero-carbon generation (e.g., renewables and nuclear); and (4) use of demand-side energy efficiency, thereby reducing generation requirements. US EPA has offered the states considerable flexibility in determining how they might meet their goals. They are able, for example, to: • Look broadly across the power sector for strategies that get reductions • Invest in existing energy efficiency programs – or create new ones • Consider market trends toward improved energy efficiency and a greater reliance on lower-emitting power sources • Expand renewable energy generation capacity • Tap into investments already being made to upgrade aging infrastructure • Integrate their plans into existing power sector planning processes • Design plans that use innovative, cost-effective regulatory strategies • Develop a state-only plan or collaborate with each other to develop plans on a multistate basis (USEPA 2014c) Note that these last two options allow individual states to team up with other states if they choose – and also to employ market-based mechanisms to achieve their goals. Not only would this would allow them to accomplish their reductions in the most cost efficient manner – they will also get an extension on the time required to develop such an approach. The Clean Air Act of 1970 is a piece of legislation now almost 45 years old, and its principal architecture was developed within the CAC framework. It was never

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intended to tackle a problem as complicated and as comprehensive as GHG control. The failure of the political system to pass legislation (such as ACES or APA) means that it must now serve as the foundation for such control, given the fact that the problem is real (as indicated in the Endangerment Finding) and the courts have indicated that US EPA has the authority (and, indeed, the responsibility) to address it. The US EPA has developed a creative regulatory approach that will allow states to utilize emissions trading, if they so choose – and to do so on a multistate basis. This plan will surely be modified in response to public comment, and must also survive the inevitable lawsuits when it is promulgated. Opponents have already attacked the Plan, based upon media reports that environmentalists played a key role in its development (Davenport 2014; Chait 2014). The final 111(d) rule is due to be released in June 2015, and while states must begin to make reductions by 2020, full compliance with the CO2 emission performance level in the state plan must be achieved by no later than 2030.

Voluntary Carbon Market In addition to the “compliance” markets discussed above, a corollary, voluntary market has developed that provides carbon trading opportunities for companies, individuals, and other entities not subject to mandatory limitations, but still wishing to offset their GHG emissions. As the name implies, the voluntary carbon market includes all carbon offset trades that are not required by regulation. Over the past several years, this market has not only provided an opportunity for consumers to alleviate their carbon footprint, but also provided an alternative source of carbon finance. The instrument of trading is called a Voluntary Emission Reduction (VER), although it should be noted that some market participants consider this acronym to mean “Verified Emission Reduction.” While still very much smaller than the compliance market ( 5.2 m
0.5 (As in m2 and Hmax in m) were simulated to typically not support cisco oxythermal habitat under past climate conditions and the future climate scenario (MIROC 3.2). Mediumdepth lakes are projected to be most vulnerable to climate warming with most

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increase in the number of years with cisco kill. The mean daily TDO3 values over a 31-day fixed and variable benchmark periods were calculated for each of simulated years and then averaged over the simulation period for each lake type. Projected increases of the multiyear average TDO3 (called AvgATD3) under the two future climate scenarios and relative to the 47-year simulation period from 1962 to 2008 had averages from 2.6  C to 3.4  C. Isopleths of AvgATD3 were interpolated for the 30 simulated virtual lakes on a plot of Secchi depth versus lake geometry ratio used as indicators of trophic state and summer mixing conditions, respectively. Marking the 620 Minnesota lakes with identified cisco populations on the plot of AvgATD3 allowed to partition the 620 lakes into three tiers depending on where they fell between the isopleths: lakes with AvgATD3  11  C (tier 1 lakes) were selected to be most suitable for cisco; lakes with 11  C < AvgATD3  17  C (tier 2 lakes) had suitable habitat for cisco; and non-refuge lakes with AvgATD3 > 17  C (tier 3 lakes) would support cisco only at a reduced probability of occurrence or not at all. About 208 (one third) and 160 (one fourth) of the 620 lakes that are known to have cisco populations are projected to maintain viable cisco habitat under the two projected future climate scenarios using the fixed and variable benchmark periods, respectively. These selective lakes have a Secchi depth greater than 2.3 m (mesotrophic and oligotrophic lakes) and are seasonally stratified (geometry ratio less than 2.7 m
0.5). Management strategies were developed and implemented for some of the refuge lakes.

Introduction The potential significance of climate change for inland aquatic ecosystems (e.g., streams, lakes, reservoirs) caught the attention of water resource professionals and scientists in the early 1990s. An increase of carbon dioxide (CO2) and/or other greenhouse gases in the atmosphere is projected to cause climate warming (NRC 1983; IPCC 2007), which would alter water temperature (T), ice/snow cover, and dissolved oxygen (DO) characteristics in lakes (Blumberg and Di Toro 1990; Stefan et al. 1996). These changes are in turn expected to have an effect on indigenous fish populations: cold-water, cool-water, and warmwater fish species (Coutant 1990; Magnuson et al. 1990; Chang et al. 1992; Stefan et al. 1995; De Stasio et al. 1996). Chapter 16 in the previous edition of the handbook has summarized some basic information on effects of climate change on water quality (water temperature, dissolved oxygen, snow and ice covers) and fish habitat for three fish guilds (8, 7, and 14 species of cold-water, cool-water, and warmwater fish guilds, respectively) in lakes in Minnesota and the contiguous USA (Fang and Stefan 2012). This chapter summarizes simulation results and model validation of cisco oxythermal habitat in Minnesota lakes that were used to identify cisco “refuge lakes” under future climate scenarios and develop management strategies for them. A “refuge lake” is a cisco lake that is projected to provide suitable cold-water habitat under future climate scenarios.

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Cisco Coregonus artedi is the most common cold-water stenothermal fish in northern lakes in Minnesota, Wisconsin, and other northern states, and it is a common forage fish for walleye Sander vitreus and northern pike Esox lucius among other prized sport fishes. The Minnesota (MN) Department of Natural Resources (DNR) has sampled cisco from 648 lakes in netting assessments since 1946 (MN DNR files). These lakes are typically deeper and more transparent than average lakes in Minnesota (Fang et al. 2009). The lakes are scattered throughout much of the central and northern portions of the state (Fig. 1) and cross several land uses (agricultural, urban, and forested). The wide distribution suggests that ciscoes are somewhat more eurythermal than other native, lentic cold-water stenotherms such as lake whitefish Coregonus clupeaformis (sampled in 155 Minnesota lakes), lake trout Salvelinus namaycush (124 Minnesota lakes), and burbot Lota (233 Minnesota lakes). Cisco physiologically requires cold, well-oxygenated water to survive, grow, and reproduce (Cahn 1927; Frey 1955). The combination of a wide distribution (Fig. 1) and a requirement for cold, oxygenated water (Frey 1955) make cisco an excellent “canary in a mineshaft” species that is a sensitive indicator of ecological stresses such as eutrophication and climate warming. For example, 18 lakes in north-central Minnesota experienced cisco mortality in the unusually hot summer of 2006 (Jacobson et al. 2008), and one example of cisco mortality is given in Fig. 2. The climate warming is projected to warm the water and increase hypolimnetic oxygen depletion during periods of stratification in lakes (Blumberg and Di Toro 1990; Fang and Stefan 1999, 2000, 2009). Fish habitat is constrained by water temperature, available DO, food supply, human interference, and other environmental factors (Frey 1955; Fry 1971). In lakes, water temperature and DO are the two important water quality parameters that affect survival and growth of cold-water fishes (Magnuson et al. 1979; Coutant 1985, 1990; Christie and Regier 1988; Jacobson et al. 2010; Fang et al. 2012a, b; Jiang et al. 2012). Therefore, projected changes of water temperature and DO characteristics due to climate warming have the potential to reduce cold-water fish habitat (such as cisco) in lakes (Magnuson et al. 1990; Schindler et al. 1996; Stefan et al. 1996; Fang et al. 2004b). Ciscoes have been declining in recent years in Minnesota lakes, likely because of climate warming (Jacobson et al. 2012). Recently, Sharma et al. (2011) estimated that 30–70 % of the cisco population in about 170 of Wisconsin’s deepest and coldest lakes could become a climate change casualty and disappear from most of the Wisconsin cisco lakes by the year 2100. The goal of the study was to simulate daily water temperature and DO profiles in different cisco lakes to project the quality of cold-water fish habitat in 620 known cisco lakes in Minnesota under future climate scenarios and to identify potential cisco refuge lakes and impacts of climate change on cisco habitat. To make projections of water quality and fish habitat in lakes under future climate scenarios, numerical simulation models of daily temperature and DO profiles are useful. It is infeasible to simulate 620 cisco lakes in Minnesota using MINLAKE2010/MINLAKE2012 (Fang et al. 2012a). In this study, simulations of daily water temperature and DO profiles were made for the 30 virtual lakes

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Fig. 1 Geographic distribution of 620 cisco lakes grouped by latitude, three weather stations (stars), and associated grid center points (crosses) of CGCM 3.1 and MIROC 3.2 used for model simulations. Background shades identify ecoregions of Minnesota. Cisco lakes are essentially in two ecoregions: (1) Northern Lakes and Forests and (2) North Central Hardwood Forests (modified from Jiang et al. 2012)

(Fang et al. 2012b; Jiang et al. 2012) and 44 representative lakes (Fang et al. 2014) in Minnesota before cisco oxythermal habitat and lethal conditions were examined in these lakes. The overall modeling methodology for the study is discussed in detail in the next section (Fig. 3).

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Fig. 2 Lake Andrusia in Minnesota had cisco mortality in July 2006 (Photo: Peter C. Jacobson, Minnesota Department of Natural Resources)

In this study, cold-water oxythermal fish habitat was identified using three different methods (Fig. 3): (1) constant lethal limits (lethal temperature, LT and DO survival limit), (2) lethal-niche-boundary curve (Jacobson et al. 2008) (also called variable lethal limits), and (3) a single oxythermal habitat variable TDO3, temperature at 3 mg/L of DO (Jacobson et al. 2010). Depths at the good-growth temperatures and lethal limits and TDO3 values were calculated day by day from simulated daily lake water temperature and DO profiles obtained from the processoriented, one-dimensional year-round water quality model MINLAKE2010/ MINLAKE2012 (Fang et al. 2012a). The model was run in daily time steps over a continuous 48-year simulation period for past (1961–2008) climate conditions and for two projected future climate scenarios (CGCM 3.1 and MIROC 3.2). Monthly (31-day) fixed and variable benchmark periods (Fang et al. 2012b; Jiang et al. 2012; Jacobson et al. 2010) were used to identify future cold-water fish habitat in lakes based on projected future temperature and DO profiles.

Overall Modeling Methodology Figure 3 shows a flowchart of the study to project impacts of climate changes on cisco oxythermal habitat in Minnesota. Past climate conditions (1961–2008, 48 years) and two future climate scenarios at different weather stations were assembled and used as model inputs (atmospheric boundary conditions) to the deterministic, unsteady, one-dimensional (vertical) lake water quality model MINLAKE2010/MINLAKE2012 which can simulate T and DO profiles in cisco lakes continuously for 48 years over the open-water seasons and winter ice-cover periods. A cisco habitat model with three different modeling options were developed, validated, and used for the study. The first option is to use the constant lethal limits to model cisco habitat in Minnesota lakes. The constant limits for fish survival (lethal) and good growth do not change with time, and the method was previously used to

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Fig. 3 Flowchart of the study to project impacts of climate changes on cisco oxythermal habitat in Minnesota lakes

project cold-water, cool-water, and warmwater fish habitat in small lakes in Minnesota and over the contiguous USA (Stefan et al. 2001). The constant lethal limits of cisco were calculated from the lethal-niche-boundary curve of adult cisco (Jacobson et al. 2008) and then determined through model validation in 23 Minnesota lakes using cisco mortality and survival data in the summer of 2006. The second option is to use a fitted regression equation as the lethal niche boundary of adult cisco. The equation was developed by Jacobson et al. (2008) and gives DO survival limits at different temperatures, which are temperature-varying lethal limits. The third option is to use a single oxythermal variable TDO3 to identify cisco refuge lakes

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(Fang et al. 2012b; Jiang et al. 2012). TDO3 has been a useful parameter for quantifying the oxythermal niche of cold-water fish (Jacobson et al. 2010). TDO3 was calculated from simulated daily T and DO profiles for every simulated day except days in 1961 to avoid effects of initial conditions. In the third option of cisco oxythermal habitat modeling, the daily TDO3 values were averaged over either the fixed benchmark (FB) period (ATDO3FB) (Fang et al. 2012b) or the variable benchmark (VB) period (ATDO3VB) (Jiang et al. 2012) for each simulated lake and year. Using the variable benchmark periods for each simulated year gave the maximum average TDO3 over a 31-day period in different years and different lake types (Jiang et al. 2012). The oxythermal habitat options 1 and 2 determine which day lethal conditions can occur. In the first option, when the LT isotherm and the DO limit isopleth for cisco intersect in a particular day (Stefan et al. 2001; Fang et al. 2004a; Fang and Stefan 2012), the entire depth of a stratified lake is under lethal conditions on that day. The lethal conditions are because water temperature is higher than LT from the water surface to or below the intersecting depth and DO is lower than the DO limit from the lake bottom to or above the intersecting depth. In the second option, lethal conditions for cisco are assumed to occur if the simulated DO is less than the DOlethal value in all water layers (from the lake water surface to the lake bottom) on that day when DOlethal is calculated from simulated water temperature using the lethal-nicheboundary curve (Jacobson et al. 2008). To understand climatic variability, the water quality model and fish habitat model were run using the weather data from 1961 to 2008 for the past climate conditions in 30 virtual deep lakes and 44 representative lakes (Table 1) in Minnesota (Fig. 3). A number of years with cisco kill and number of cisco lethal days were determined during the simulation period for the habitat modeling options 1 and 2. The cisco kill was assumed to occur when the continuous lethal days of cisco last 3 or 7 days (Fang et al. 2014). To assess the quality of cisco habitat in a lake and identify refuge lakes, the 47-year averages of annual ATDO3FB and ATDO3VB values in the 1962–2008 simulation period (i.e., AvgATD3FB and AvgATD3VB) were calculated in 30 virtual deep lakes (Table 2) and compared to TDO3 limits (11  C and 17  C determined by the analysis of field data) to divide cisco lakes into three tiers: tiers 1 and 2 refuge lakes and tier 3 non-refuge lakes (Fang et al. 2012b; Jiang et al. 2012). To implement the above modeling approach, 44 “representative” Minnesota lake types (Table 1 and Fig. 3) and 30 “virtual” cisco lake types (Table 2 and Fig. 3) were chosen as representative of the entire set of Minnesota lakes in general and 620 cisco lakes, respectively; a similar approach using 27 “generic” lake types had been used to study climate warming impact on fish habitat in small lakes in Minnesota (Stefan et al. 1996) and in the contiguous USA (Stefan et al. 2001; Fang et al. 2004a, b), because it was not viable to run the deterministic model for all 620 cisco lakes over 47 years. To apply the oxythermal habitat results to the hundreds of cisco lakes that could not all be simulated, the virtual and representative simulated lakes had to be characterized in a generic way. Following previous practice (Stefan et al. 2001; Fang et al. 2004a, b), two parameters were chosen for this purpose: a lake geometry ratio (GR) as an indicator of a lake’s potential for strong or weak summer stratification (Gorham and Boyce 1989) and mean summer Secchi depth (SD) as an indicator of

Surface area AS (km2) 0.2 1.7 10 0.05 0.2 1.7 10 0.2 1.7 10 2.32

Secchi depth, SD (m) 1.2 2.5 LakeR01a LakeR02 LakeR04 LakeR05 LakeR07 LakeR08 LakeR37 LakeR38 LakeR10 LakeR11 LakeR13 LakeR14 LakeR16 LakeR17 LakeR19 LakeR20b LakeR22 LakeR23 LakeR25 LakeR26 LakeR41c LakeR42 4.5 LakeR03 LakeR06 LakeR09 LakeR39 LakeR12 LakeR15 LakeR18 LakeR21 LakeR24 LakeR27 LakeR43

7.0 LakeR28 LakeR29 LakeR30 LakeR40 LakeR31 LakeR32 LakeR33 LakeR34 LakeR35 LakeR36 LakeR44

Geometry ratio (GR) As0.25/Hmax 5.29 m
0.5 9.03 m
0.5 14.06 m
0.5 1.15 m
0.5 1.63 m
0.5 2.78 m
0.5 4.33 m
0.5 0.88 m
0.5 1.50 m
0.5 2.34 m
0.5 1.63 m
0.5

Note: a The first 28 shallow and medium-depth lakes were used for fish habitat modeling of the constant lethal limits method b These highlighted lakes are strongly stratified mesotrophic and oligotrophic deep lakes used for fish habitat modeling of the lethal-niche-boundary curve method c These four deep lakes (LakeR41–LakeR44) have the same geometry ratio but different surface areas as four medium-depth lakes LakeR10–LakeR12 and LakeR31 for comparison study

Hmax = 24 m (deep)

Hmax = 13 m (medium depth)

Maximum depth (m) Hmax = 4 m (shallow)

Table 1 Morphometric characteristics and “names” of the 44 representative or regional lake types in Minnesota simulated with the MINLAKE2010/ MINLAKE2012 model

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Table 2 Morphometric characteristics and “names” of the 30 virtual cisco lakes simulated with the MINLAKE2010/MINLAKE2012 model (maximum lake depth Hmax = 24 m) Surface area AS (km2) 0.1 0.5 1.5 5.0 13.0 50.0

Secchi depth SD (m) 1.2 LakeC01 LakeC06 LakeC11 LakeC16 LakeC21 LakeC26

2.5 LakeC02 LakeC07 LakeC12 LakeC17 LakeC22 LakeC27

4.5 LakeC03 LakeC08 LakeC13 LakeC18 LakeC23 LakeC28

7.0 LakeC04 LakeC09 LakeC14 LakeC19 LakeC24 LakeC29

8.5 LakeC05 LakeC10 LakeC15 LakeC20 LakeC25 LakeC30

Geometry ratio, GR =As0.25/Hmax 0.74 1.11 1.46 1.97 2.50 3.50

lake trophic state and transparency. These virtual and representative lakes are described in detail in a separate section.

Simulation Models for Year-Round Water Quality To make projections of water quality and fish habitat in small lakes under future climate scenarios, numerical simulation models of daily temperature and DO profiles are indispensable. The one-dimensional (vertical) year-round lake water quality model MINLAKE2010 was developed to run continuously over many simulation years for both the open-water season and the ice-cover period (Fang and Stefan 1996a). The model uses a stacked layer system (Fig. 4); the layers consist of lake water and lake sediments during the open-water season and additional ice cover and snow cover during the winter ice-cover period (Fang and Stefan 2009). It simulates daily water temperature profiles in a lake using daily weather data as input. Figure 4 is a schematic of a stratified lake including heat transfer components, oxygen sources and sinks for the year-round water temperature and DO models, and typical temperature and DO profiles in the summer and winter (Fang and Stefan 1996a, b, c). MINLAKE2010 uses a mixed layer approach (Chapra 1997), which considers a mechanical energy balance (kinetic and potential energy), to predict the thickness of the mixed layer (epilimnion) after the heat diffusion equation is solved and convective mixing is considered (Ford and Stefan 1980). A lake is divided into a series of well-mixed horizontal water layers (Fig. 4) because the horizontal variations of water quality parameters are typically much smaller than the vertical variations in a small stratified lake. The one-dimensional, unsteady heat transfer equation in a lake is solved for daily vertical water temperature profiles (Hondzo and Stefan 1993):   @T 1 @ @T Hw ¼ K zT A þ @t A @z @z ρCp

(1)

where T(z, t) is the water temperature ( C) in a horizontal layer, t is the time (day), A(z) is the horizontal area (m2) as a function of depth z (m) based on lake bathymetry

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Meteorological forcing T= 0°C

Ice cover season

Open water season

TA

HSN HA HBR HE

U

HSN HE

HC

HC

TA T= 0°C U

Snow Ice Water HSED

HSED Sediment

Sediment Sediment Temperature profile in summer DO = 0 mg L

Temperature profile in winter

–1

O2

DO = 0mg/l

Fs

Ua

Phytoplankton P (Chl-a)

Snow Ice R BOD SOD

Water

Phytoplankton P (Chl-a) WODR

R=0

Sediment Sediment

DO profile in summer Oxygen source

Sediment

Oxygen sink

DO profile in winter

Fig. 4 Schematic of a stratified lake showing heat transfer components, oxygen sources and sinks for the year-round water temperature and DO model MINLAKE96/MINLAKE2010/ MINLAKE2012, and typical temperature and DO profiles in summer open-water season (left) and winter ice-cover period (right) including sediment, water, ice, and snow layers (Fang and Stefan 2009)

input data, KzT is the vertical turbulent heat diffusion coefficient (m2 day
1), ρCp is the density of water (ρ) times heat capacity of water (Cp) and represents heat capacity per unit volume (J m
3  C
1), and Hw is the internal heat source strength per unit volume of water (J m
3 day
1). Solar radiation absorption in the water column is the main contributor to the heat source term during the open-water season (Stefan and Ford 1975). Heat exchange with the bottom sediment layer included in MINLAKE2010 can be important in the shallow water layers and during the winter ice-cover periods (Fang and Stefan 1996b). Heat exchange between the lake and the atmosphere is treated as a source or sink term (Fig. 4) for the topmost water layer of a lake during the open-water season due to the surface wind mixing, i.e., Hw(1) in Eq. 1 = As/V(1)  (HSN + HA– HBR– HE– HC), where As is the lake surface area and V(1) is the volume of the topmost/first water layer. It includes surface heat fluxes in J m
2 day
1 such as net incoming heat from shortwave solar radiation (HSN), long-wave radiation (HA), outgoing heat from back radiation (HBR), evaporation/condensation (HE), and conduction/convection (HC) related to wind speed (U, Fig. 4). The computation of above surface heat fluxes and the internal heat source term (Hw) using daily weather input data has been discussed by Hondzo and Stefan (1993), among others. During the ice-cover period (Fang and Stefan 1996b, c), the model first simulates snow/ice thicknesses

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and sediment temperature profiles (heat conduction equation), then determines the heat source/sink terms, and finally solves the heat transfer equation to obtain water temperature profiles below the ice. The heat budget components through the water surface are directly linked to climate parameters that are related to future climate changes. Dissolved oxygen concentration is viewed as one of the most important lake water quality parameters which indicate a lake’s overall ecological health. The vertical DO profiles in the lake are computed from a balance between oxygen sources (surface reaeration and photosynthesis, Fig. 4) and oxygen sinks (sedimentary oxygen demand (SOD), biochemical oxygen demand (BOD), and plant respiration (R)). The numerical simulation model for daily DO profiles in a lake solves the one-dimensional, unsteady transport equation: @C @t

¼

  1 @ @C Sb @A T
20 AK Z θ þ PMAX θpT
20 Min½L Chla
A @A @z A @z s 1 kr θr T
20 Chla
kb θb T
20 BOD
YCHO2

(2)

In Eq. 2, C(z, t) is the DO concentration in mg/L as a function of depth (z) and time (t), Kz(z, t) is the DO vertical turbulent diffusion coefficient in m2 day
1, and Sb is the coefficient for SOD at 20  C in mg O2 m
2 day
1. PMAX is the maximum specific oxygen production rate by aquatic plants at 20  C under saturating light conditions in mg O2 (mg Chla)
1 day
1. Min[L] is the light limitation determined by Haldane kinetics (Megard et al. 1984). Chla is the chlorophyll-a concentration in mg/L to represent the biomass of aquatic plants in a lake. YCHO2 is the yield coefficient, i.e., the ratio of mg chlorophyll-a to mg oxygen. The first-order decay rate coefficients are kb and kr for BOD and plant respiration (day
1), respectively. The temperature adjustment coefficients for SOD, photosynthesis, BOD, and plant respiration are θs, θp, θb, and θr, respectively. Typical values and ranges of temperature and DO model parameters have been summarized elsewhere (Fang and Stefan 2012). Oxygen production is related to chlorophyll-a concentration and limitation of available light determined by Haldane kinetics. In the DO model, chlorophyll-a is specified by a mean annual value which depends on the specified trophic state of a lake and a function that calculates typical seasonal chlorophyll-a cycles (Stefan and Fang 1994a) based on observational data from 56 lakes and reservoirs in Europe and North America (Marshall and Peters 1989). Annual mean chlorophyll-a concentration that represents biomass or phytoplankton in the MINLAKE2010 model was calculated from the relationship between chlorophyll-a and Secchi depth used in the Carlson trophic index (Carlson 1977) for virtual and representative lakes in Minnesota (Tables 1 and 2) or measured data for calibration lakes. In the model, the oxygen transfers through the water surface (reaeration) during the open-water season is used as an oxygen source or sink term in the topmost water (surface) layer of the lake after the reaeration is multiplied by the surface area and divided by the layer volume, and the surface oxygen transfer coefficient is calculated as a function of wind speed. SOD is treated as a sink term for each water layer

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because each water layer is in contact with lake sediments. BOD occurs in the water column along all water depths, and plant respiration for all water layers is a function of chlorophyll-a concentration. BOD (mg/L) is used to reflect biodegradable detritus in lake water column. Diffusive oxygen flux at the lake bottom is set equal to zero as a boundary condition (the flux is not explicitly modeled, but SOD is used as surrogate of the flux). For the DO simulations in a lake during the ice-cover period (Fig. 4), modifications must be made to account for the presence of an ice cover and low temperatures. For example, reaeration is zero because the lake ice cover prevents any significant gas exchange between the atmosphere and the water body. The water column oxygen demand (WOD in Fig. 4) is set at 0.01 g O2 m
3 per day after model calibration. DO concentrations are simulated after water temperature and snow/ice covers have been simulated. Equations 1 and 2 are solved numerically for time steps of 1 day and layer thicknesses from 0.02 m (near the water surface and the ice-water interface) to 1.0 m (when z > 1.0 m) for small lakes using an implicit finite difference scheme and a Gaussian elimination method. Model parameters and detailed formulations of the year-round DO model (Eq. 2) have been described elsewhere (Stefan and Fang 1994a; Fang and Stefan 1997). Several modifications and refinements were made to develop MINLAKE2010 from MINLAKE96 for relative deep cisco lakes in Minnesota and have been reported by Fang et al. (2012a). Most recent version MINLAKE2012 (Fang et al. 2014) used in a part of the study is a spreadsheet model developed from MINLAKE2010. The most important upgrades of MINLAKE2012 compared to MINLAKE2010 are the conversion to a user-friendly Excel spreadsheet (for data input and displaying basic graphic results) and the introduction of variable temporal resolution, allowing the model to run at hourly and daily time steps. The MINLAKE model was calibrated and validated against extensive Minnesota lake data: first, using 5,378 water temperature and DO measurements for 48 lake years in 9 lakes for MINLAKE96 (Fang and Stefan 1996) and then using 7,384 water temperature and DO measurements for 439 lake years in 28 lakes for MINLAKE2010 (Fang et al. 2012a). Twenty-one cisco lakes and seven non-cisco lakes were selected for model calibration of MINLAKE2010 based on multiyear data availability; more than half of these 28 lakes had maximum depths greater than 24.0 m, which is Hmax used for the 30 virtual lakes in Table 2, and 23 of the 28 lakes were either mesotrophic or oligotrophic lakes (Fang et al. 2012a). After calibration, the average standard error of estimates against measured data for all 28 lakes was 1.47  C for water temperature (range from 0.8  C to 2.06  C) and 1.50 mg/L for DO (range from 0.88 to 2.76 mg/L) (Fang et al. 2012a).

Cisco Lakes in Minnesota The modeling analysis was conducted for 620 known cisco lakes in Minnesota (Fig. 1); the MN DNR had netting assessments for these lakes since 1946. On average, Minnesota cisco lakes are deeper and more transparent (larger Secchi

670

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depth) and have lower chlorophyll-a concentrations than other lakes in Minnesota (Fang et al. 2009). The 620 cisco lakes vary in mean Secchi depth (SD) and lake geometry ratio (GR) as shown in Fig. 5. The lake GR is defined as As0.25/Hmax in m
0.5 when surface area As is in m2 and maximum depth Hmax in m. The strength of the seasonal lake stratification is related to the GR (Gorham and Boyce 1989). Polymictic lakes such as large shallow lakes have the highest GR numbers, while strongly stratified lakes have the lowest GR numbers; the transition from weakly to strongly stratified lakes occurs when GR is between 3 and 5 (Gorham and Boyce 1989). Lake geometry ratios of Minnesota cisco lakes range from 0.47 to 22.7 m
0.5 (Fig. 4), and about 73 % of these lakes have GR less than 3.0 m
0.5 (Fang et al. 2009). Only 6 % or 39 of these lakes have GR greater than 5.0 m
0.5; these are very weakly stratified or unstratified lakes during the summer. Lake of the Woods is located at the border of the USA and Canada and has the largest surface area (3847.8 km2) with the largest GR = 22.7 m
0.5 and a maximum depth of 10.97 m. Mille Lacs Lake has the second largest GR = 11.9 m
0.5 with a maximum depth of 12.8 m and surface area of 536.5 km2. Maximum depths of the 620 cisco lakes range from 3.0 to 64.9 m, and 25 % of these lakes have maximum depth greater than 24 m (Fang et al. 2009). For these 620 cisco lakes in Minnesota, there are 14 shallow lakes with Hmax < 5.0 m, 385 medium-depth lakes (Fig. 5 top) with 5.0 m  Hmax < 20.0 m, and 221 deep lakes with Hmax > 20.0 m (Fig. 5 bottom) based on regional lake classifications in Minnesota (Stefan et al. 1996). Surface areas of these lakes range from 0.04 to 3,847.8 km2 (Fang et al. 2009) and mean summer Secchi depths from 0.7 to 9.5 m. Nineteen percent and 81 % of the 620 cisco lakes (Fang et al. 2009) have mean summer Secchi depth greater than 4.5 m (oligotrophic lakes) and 2.5 m (mesotrophic lakes), respectively, based on regional lake classifications in Minnesota (Stefan et al. 1993). For modeling purposes, the 620 Minnesota cisco lakes were grouped by either shortest distance or latitude to associate with three Class I National Weather Service (NWS) weather stations in Minnesota (International Falls, Duluth, and St. Cloud; Fig. 1). Weather data from only these three Class I NWS weather stations were useful and available for cisco lake long-term simulations for the period from 1961 to 2008. Three options (methods) were used to associate each lake with one of the three weather stations: (1) association by shortest distance (Fang et al. 2012b), (2) association by latitude (Jiang et al. 2012), and (3) association of one single weather station with all lakes simulated (Fang et al. 2010b). Refuge lakes were determined using each of the three options (Fang et al. 2010b), but results were similar; simulation results by methods (1) and (2) are presented here.

Representative Lake Types in Minnesota Simulations of daily water temperature and DO profiles and oxythermal habitat parameters were made for 30 virtual cisco lakes and 44 representative lakes (lake types or classes) in Minnesota before fish habitat was examined in 620 cisco lakes. The 44 representative lake types in Table 1 were expanded from the 27 lake types

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Fig. 5 Distribution of 14 shallow and 385 medium-depth cisco lakes (top) and 221 deep cisco lakes (bottom) from 620 cisco lakes in Minnesota including 44 regional or representative lakes (Table 1) and 30 virtual deep lakes (Table 2) plotted using Secchi depth and lake geometry ratio as axes

672

X. Fang et al.

used to study fish habitat in Minnesota (Stefan et al. 1996) and in the contiguous USA (Fang et al. 2004a). Lakes were classified by lake geometry (surface area As and maximum depth Hmax) and trophic state as related to Secchi depth (SD in Tables 1 and 2). The representative surface areas chosen for the 27 lake types were 0.2, 1.7, and 10.0 km2 for small, medium-size, and large lakes (Stefan et al. 1996; Fang et al. 2004a), respectively. The representative maximum depths chosen were 4, 13, and 24 m for shallow, medium-depth, and deep lakes (Stefan et al. 1996; Fang et al. 2004a), respectively. With these numbers for As and Hmax, nine lake types were obtained ranging from relatively large and shallow lakes to relatively small and deep lakes. Secchi (disk) depth (SD) is a common limnological parameter to measure transparency of a lake (Hutchinson 1957; Horne and Goldman 1994). It was used in previous fish habitat studies (Stefan et al. 1996; Fang et al. 2004a) to represent both trophic state (primary productivity of biomass or photosynthesis of plants) and solar radiation attenuation in a lake, which is used to quantify how much solar energy reaching the water surface can penetrate through a water column to heat water and to support photosynthesis of aquatic plants (Fig. 4). Lake turbidity from suspended inorganic sediment is relatively rare in Minnesota, and total phosphorus or chlorophyll-a in most Minnesota lakes is well correlated with SD (Stefan and Fang 1994b). Therefore, SD is a representative parameter to characterize trophic state of each of the 620 cisco lakes in the database. Contours (isotherms or isopleths) on plots with SD versus GR as axes have been previously used successfully by the authors to give/present generic, but regional, patterns or variations of different characteristic parameters in lakes, e.g., maximum surface water temperatures, maximum lake bottom temperatures, minimum DO at the sediment/water interface, and various fish habitat parameters in lakes (Stefan et al. 1996; Fang and Stefan 1997, 1999). The representative Secchi depths of 1.2, 2.5, and 4.5 m were previously selected for eutrophic, mesotrophic, and oligotrophic Minnesota lakes (Stefan et al. 1996; Fang et al. 2004a), respectively, using Carlson’s trophic state index (Carlson 1977). Ten percent or 62 lakes of 620 cisco lakes have mean summer Secchi depths of 5.0–9.5 m. Therefore, the fourth Secchi depth of 7.0 m was added creating nine new representative lake types for the study. A set of virtual cisco lakes (Table 2) with SD = 7.0 m was first used before to study cisco refuge lakes in Minnesota (Jiang et al. 2012). Therefore, the first 36 representative lake types (Table 1) were characterized by a 3  3  4 matrix consisting of (a) three different lake surface areas, (b) three lake maximum depths, and (c) four Secchi depths. The first 28 shallow and medium-depth lakes in Table 1 were used for fish habitat modeling of the constant lethal limits method (Fang et al. 2014). Four medium-depth lakes LakeR37–LakeR40 were added to have a lake geometry ratio of 1.15 to reflect some of the medium-depth cisco lakes with smaller GR (Fig. 5). Four deep lakes (LakeR41–LakeR44) were added to have the same geometry ratio but different surface areas as four medium-depth lakes LakeR10–LakeR12 and LakeR31 to compare fish habitat parameters in these two groups of lakes (Fang et al. 2014). With above eight additional regional lakes, there

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are a total of 44 representative lakes (Table 1 and Fig. 5 top) used for cisco habitat modeling in Minnesota. These representative or regional values for each parameter (As, Hmax, and SD in Table 1) were selected from the data analysis of these parameters in the Minnesota Lakes Fisheries Database containing lake survey data for 3,002 lakes (Hondzo and Stefan 1993) and 620 cisco lakes (Fang et al. 2009). The lake bathymetry of these 44 lakes (the shape of the lake basin as part of model input data) is characterized by three functions A(z)/As versus z/Hmax for small, medium-size, and large lakes, which are regression equations developed from 122 Minnesota lakes by Hondzo and Stefan (1993). More important than the geometric characteristics of each lake type is the likelihood of relating a strong or weak stratification in a lake to the lake’s geometry ratio GR = As0.25/Hmax (Gorham and Boyce 1989). The above 44 lake types cover geometry ratios from 0.88 to 14.06 m
0.5 (Table 1). Polymictic lakes, i.e., large shallow lakes, have the highest geometric ratio, while strongly stratified lakes, i.e., small deep lakes, have the lowest geometry ratio. Hence, these 44 lake types selected for the study include the full range of stratification behavior. The set of 30 virtual cisco lakes (Fig. 5 bottom) comprised lakes with five different SD values (1.2, 2.5, 4.5, 7.0, and 8.5 m) and six different surface areas (0.1, 0.5, 1.5, 5.0, 13.0, and 50 km2). The maximum depth of all 30 virtual lakes was set at 24 m (Fang et al. 2009, 2012; Jiang et al. 2012). Combinations of the maximum depth and surface areas gave six different geometry ratios for the 30 virtual lakes, i.e., 0.74, 1.11, 1.46, 1.97, 2.50, and 3.50 m
0.5 (Table 2). Twenty of the 30 virtual cisco lake types were strongly stratified with GR < 2 m
0.5; the other ten lake types were weakly stratified (Table 2). The 30 virtual cisco lakes (Table 2) did not include any polymictic lakes because they likely would not provide suitable cold-water habitat in Minnesota after climate warming. For example, Fang et al. (2012a) studied the oxythermal habitat variable TDO3 in 21 study cisco lakes in Minnesota and found that two cisco lakes with GR > 4.0 m
0.5 (White Iron Lake and South Twin Lake) had high annual maximum TDO3 values indicating unfavorable conditions for cisco survival and growth. Values of TDO3 extracted from observed temperature and DO profiles were lowest in lakes with small geometry ratios (GR < 2 m
0.5); a geometry ratio of 4 m
0.5 effectively marked the transition between stratified and unstratified lakes (Jacobson et al. 2010). Even though the lake bathymetry (surface area and maximum depth) and Secchi depth of the 30 virtual cisco lakes were subjective, the selected values were representative of most of the 620 Minnesota cisco lake database (Fang et al. 2009). The 30 virtual cisco lakes were all stratified lakes based on geometry ratio and included eutrophic to oligotrophic lakes (Table 2). The 30 virtual cisco lakes were more or less uniformly distributed on the plot of SD vs. GR (Fig. 5 bottom) (Fang et al. 2012b). None of the 30 virtual cisco lakes in Table 2 have the same lake surface areas as 44 representative Minnesota lakes in Table 1. These two groups of generic lake classes (types) were used in the different fish habitat modeling options (Fig. 3): 44 representative lakes for the oxythermal model options 1 and 2 using lethal limits (Fig. 5) and 30 virtual lakes for the model option 1 (constant lethal limits) and the model option 3 using TDO3 (Fig. 3) during different study periods.

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Past Climate and Future Climate Scenarios Climate conditions control water temperature and DO distribution in a lake. Climate scenarios are model inputs of MINLAKE2010/MINLAKE2012 for producing water temperature and DO concentration scenarios for the simulated lakes (Tables 1 and 2), which are used to assess potential changes in cisco habitats in these lakes. To identify refuge lakes, we need to project whether a lake that currently has a cisco population can support cisco habitat under future climate scenarios, i.e., after climate warming. To make the projection, the model outputs from two coupled general circulation models (CGCMs) of the earth’s atmosphere and oceans (i.e., CGCM 3.1 and MIROC 3.2) were used as input to the MINLAKE2010 model to calculate a range of future water quality conditions. Forty-eight years (1961–2008) of recorded daily weather data, which were obtained from the Solar and Meteorological Surface Observation Network (SAMSON) and Midwestern Regional Climate Center, were used to describe past climate conditions for the study lakes. Weather data used for lake modeling consist of daily air temperature, dew point temperature, wind speed, solar radiation, percent sunshine, and precipitation (both rainfall and snowfall). The CGCM 3.1 (Kim et al. 2002, 2003) is the third generation of CGCMs from the Canadian Centre for Climate Modeling and Analysis (CCCma). The CCCma CGCM 3.1 uses the ocean component from the earlier second-generation CGCM (McFarlane et al. 1992) and applies a substantially updated atmospheric component – the third-generation atmospheric general circulation model. Output of the CGCM 3.1 model with a coarse global surface grid resolution of roughly 3.75 latitude and longitude or approximately 410 km in Minnesota was used for the study because it was available to be downloaded from the Intergovernmental Panel on Climate Change (IPCC) data center in 2008. When CGCM 3.1 is used for the study, there is one grid center point within Minnesota and another grid center point in Canada that is the closest grid point to International Falls weather station (Fig. 1). The MIROC 3.2 (Hasumi and Emori 2004) was developed by the Center for Climate System Research, University of Tokyo; the National Institute for Environmental Studies; and the Frontier Research Center for Global Change – Japan Agency for Marine-Earth Science and Technology. Output of the MIROC 3.2 model with a high spatial surface grid resolution of roughly 1.12 latitude and longitude or approximately 120 km in Minnesota was used. The MIROC 3.2 model has 17 grid center points in Minnesota, and Fig. 1 shows three grid center points from MIROC 3.2 that are the closest to three weather stations (St. Cloud, Duluth, and International Falls) used for the model study. At all CGCM grid center points, the differences or ratios known as “change fields” were produced and reported at a monthly interval. The 2070–2099 change field data, 30-year averages compatible with the Third Assessment Report of the IPCC (2007), were downloaded from the IPCC’s website and used in the study. These monthly climate parameter differences or ratios predicted by CGCM models were then applied to measured daily climate conditions (1961–2008) month by month to produce the projected daily future climate scenario. Monthly increments

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Table 3 Monthly changes of air temperature ( C) and solar radiation (Langley/day) projected by MIROC 3.2 and CGCM 3.1 for the three principal Minnesota weather stations Station Month January February March April May June July August September October November December Average

International Falls Taira SRADb 5.15/
20.34/ 6.89c
5.69 4.70/
25.36/ 5.07
9.51 4.64/
24.84/1.83 3.90 4.52/
3.32/ 4.31
18.77 4.37/
4.43/ 4.12
29.39 3.62/
3.82/9.63 4.59 3.53/
5.38/14.43 3.80 3.75/
0.49/7.63 3.30 3.80/ 16.57/10.69 3.49 4.46/
2.76/3.94 3.19 4.10/
4.22/ 2.89
1.82 4.18/
12.80/ 4.14
4.86 4.24/
7.60/ 4.14
1.82

Duluth Tair 4.67/ 4.84 4.67/ 8.09 4.53/ 6.25 3.89/ 3.60 4.21/ 3.47 3.59/ 3.28 3.68/ 3.25 3.82/ 3.32 3.81/ 3.34 4.29/ 3.39 3.89/ 3.06 3.99/ 2.91 4.09/ 4.07

SRAD
15.92/
7.49
23.42/
38.21
15.75/
55.05 0.78/
25.99
15.22/
19.96
3.92/2.28 10.36/14.78 0.52/3.66 19.27/0.34 3.03/
1.18 3.03/
2.16
9.24/
1.32
3.87/
10.86

St. Cloud Tair 4.35/ 4.84 4.17/ 8.09 4.08/ 6.25 3.88/ 3.60 4.33/ 3.47 3.67/ 3.28 3.67/ 3.25 3.92/ 3.32 3.87/ 3.34 4.30/ 3.39 3.87/ 3.06 3.92/ 2.91 4.00/ 4.07

SRAD
4.60/
7.49
9.13/
38.21 0.35/
55.05 9.80/
25.99 2.45/
19.96 0.36/2.28 17.08/14.78 3.64/3.66 24.14/0.34 9.87/
1.18 5.79/
2.16
3.16/
1.32 4.71/
10.86

Conversion of temperature changes, 1.0  C = 1.8  F Stands for solar radiation, 1.0 Langley/day = 0.484 W/m2 c The first value is for MIROC 3.2 and the second value is for CGCM 3.1

a

b

from the grid center point closest to a weather station were used to specify the future climate. For the MIROC 3.2 future climate scenario, each of the three Class I NWS weather stations (International Falls, Duluth, and St. Cloud) used for the study had a closest grid center point (Fig. 1); for the CGCM 3.1 future climate scenario, Duluth and St. Cloud used the grid center point in Minnesota (Fig. 1), and International Falls used a grid center point in Canada (Fig. 1). Monthly air temperature increases projected by MIROC 3.2 range from 3.53  C to 4.70  C with annual averages of 4.00–4.24  C for the three weather stations (Table 3); CGCM 3.1 projection has a range from 2.89  C to 8.09  C with annual averages of 4.07–4.14  C for the three weather stations (Fang et al. 2010b). The average monthly increases in air temperature range from 3.6  C to 4.7  C (3.6–3.8  C from July to September) in Bemidji, Minnesota, which was also used for the oxythermal habitat option 2 (lethal-niche-boundary curve).

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Simulation and Validation of Cisco Oxythermal Habitat Using the Constant Lethal Limits The physiological response of adult populations of different fish species to T and DO levels has been the subject of numerous laboratory and field studies, e.g., by Coutant (1970), McCormick et al. (1972), and Hokanson et al. (1977). These studies correlated fish survival, growth, reproduction, and other responses to chronic levels of T and DO exposure. Simulation of oxythermal fish habitat in lakes was conducted in small lakes (up to 10 km2 surface area) in Minnesota and the contiguous USA using constant survival limits (Stefan et al. 1996; Fang et al. 2004a, b). The oxythermal habitat approach commonly used in cold-water fish niche modeling (Dillon et al. 2003) defines an upper boundary for T and a lower boundary for DO, which are lethal temperature (LT) and DO survival limit (DOlethal). These oxythermal habitat models determine the water volume or layer thickness in a stratified lake between the upper temperature and lower DO bound that represent either optimal thermal habitat (Dillon et al. 2003) or nonlethal/useable habitat (Stefan et al. 2001). The “uninhabitable spaces” or “lethal conditions” for a fish species in a lake are where temperature is above or DO is below the survival limits (Stefan et al. 2001). This study uses the oxythermal habitat approach to investigate the lethal conditions and fish kill in summer for a cold-water fish species – cisco Coregonus artedi in Minnesota lakes. The goals of the study were to first validate cisco survival and lethal conditions in 23 Minnesota lakes (Tables 4 and 5) under 2006 weather conditions and then simulate daily T and DO profiles in 58 lake types (28 shallow and medium-depth lakes in Table 1 and 30 virtual lakes in Table 2) to project cisco survival and potential lethal conditions in 620 cisco lakes in Minnesota under future climate scenarios. The 28 shallow and medium-depth lakes include LakeR01–LakeR18, LakeR28–LakeR33, and LakeR37–LakeR40 in Table 1.

Prediction of Cisco Lethal Conditions Using Constant Lethal Limits Cisco habitat (survival) and lethal conditions were determined using simulated daily T and DO profiles in lakes, similar to the approach by Christie and Regier (1988). Temperature and DO limits of lethal conditions for adult cisco were applied to simulated water temperature and DO profiles day by day to examine whether lethal conditions occur or not in each specific day, as shown in Fig. 6 for Pine Mountain Lake. Simulated T and DO profiles were not averaged during the simulation period as was done in previous studies (Stefan et al. 1996; Fang et al. 2004a, b). When the LT isotherm and the DOlethal isopleth for cisco intersect in a particular day, the entire depth of a stratified lake is under lethal conditions on that day. The lethal conditions are because water temperature is higher than LT from the water surface to or below the intersecting depth and DO is lower than the DOlethal from the lake bottom to or above the intersecting depth. When the maximum daily water temperature is lower than the LT, the LT isotherm does not show up in the plot of depth-time contours of cold-water habitat (the upper and lower good-growth temperature contours used in previous

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Table 4 Lethal days simulated in the 23 Minnesota lakes using the constant value method with eight different lethal temperatures (LT) and DO survival limits Number of days with lethal conditions 22.0  C LT = 23.4  C DO = 2 mg/L 3 mg/L 4 mg/L 2 mg/L 3 mg/L 27 29 29 58 62 19 25 29 55 60 1 3 5 5 15

Lake name Little Turtle Andrusia Little Pine (Otter Tail) Cotton 37 37 37 Pine Mountain 12 23 35 Leech 24 24 24 Itasca 26 27 28 Gull 0 0 17 Woman 27 28 29 Little Pine 18 50 68 (Crow Wing) Eighth Crow 28 29 30 Wing Straight 0 0 5 Mille Lacs 36 36 36 Star 0 0 6 Bemidji 0 0 0 Seventh Crow 3 10 19 Wing Long 0 0 0 Carlos 0 0 0 Reference lakes without cisco kills in 2006 Big Trout 0 0 0 Kabekona 0 0 0 Scalp 0 0 0 Ten Mile 0 0 0 Rose 0 0 0

21.2  C 22.6  C 4 mg/L 63 66 21

2 mg/L 71 62 15

4 mg/L 48 51 15

57 35 36 48 4 55 39

58 56 36 53 22 59 54

59 72 36 55 54 61 106

72 56 56 59 29 67 59

52 55 28 41 28 46 45

53

55

47

67

47

0 49 9 0 17

5 49 15 7 20

20 49 29 16 23

2 56 16 6 22

9 43 20 8 20

0 0

4 0

12 0

1 0

7 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

studies were not used/shown in Fig. 6). Therefore, the DO lethal/survival limit becomes the only lethal criterion during the early spring, late fall, and winter ice-cover period, but the study only deals with lethal conditions of cisco during the summer months. Figure 6 shows cisco habitat results from April 15 to October 31, i.e., the day of year (DOY) 105–304, which is during the typical open-water season in Minnesota. The LT is the water temperature to which fish cannot be acclimated without causing death. In early publications by authors, it was called as the upper survival temperature limit (Stefan et al. 1996), which was the 95th percentile of the weekly mean temperatures from an updated national fish/temperature database (Stefan

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Table 5 Maximum depth (Hmax), lake geometry ratio (GR), and fish habitat validation results using constant lethal limits (LT = 22.0  C and DOlethal = 3 mg/L) for 23 Minnesota lakes. Simulated and observed days with lethal conditions or mortality for cisco are given Lake name (Hmax in m, GR in m
0.5) Little Turtle (9.1, 4.02) Andrusia (18.3, 2.75) Little Pine (Otter Tail) (23.8, 2.26) Cotton (8.5, 6.07) Pine Mountain (23.8, 2.11) Leech (13.0, 10.91) Itasca (13.7, 3.32) Gull (24.4, 3.26) Woman (16.5, 4.02) Little Pine (Crow Wing) (11.0, 2.90) Eighth Crow Wing (9.1, 4.11) Straight (19.2, 1.94) Mille Lacs (10.7, 14.14) Star (28.7, 2.26) Bemidji (23.2, 3.13) Seventh Crow Wing (12.2, 2.61) Long (39.0, 1.22) Carlos (49.7, 1.15)

Lethal conditions No. First Last of day day days 180 241 62

Simulated lethal days in 2006 180 (62)a

Observed mortality day in 2006 200 (7/19)b

Model agreement Yes (Yes)c

192

251

60

192 (59)

202 (7/21)

Yes (Yes)

202

216

15

202 (15)

203 (7/22)

Yes (Yes)

184

241

58

184 (58)

205 (7/24)

Yes (Yes)

193

250

56

193 (36); 232 (20)

207 (7/26)

Yes (Yes)

188

225

36

211 (7/30)

Yes (Yes)

188

241

53

188 (3); 193 (31); 224 (2) 188 (38); 227(15)

209 (7/28)

Yes (Yes)

206

227

22

206 (22)

210 (7/29)

Yes (Yes)

183

241

59

183 (59)

210 (7/29)

Yes (Yes)

186

250

54

214 (8/2)

Yes (Yes)

187

241

55

186 (2); 192 (34); 227 (2); 230 (7); 238 (4); 246 (5) 188 (55)

216 (8/4)

Yes (Yes)

211

215

5

211 (5)

213 (8/1)

Yes (Yes)

203

251

49

203 (49)

204 (7/23)

Yes (Yes)

203

217

15

203 (15)

200 (7/19)

Yes (No)

211

217

7

211 (7)

208 (7/27)

Yes (No)

196

215

20

196 (20)

216 (8/4)

Yes (No)

213

216

4

214 (4)

218 (8/6)

Yes (No)

0

No kill

239 (8/27)

No (continued)

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Table 5 (continued) Lethal conditions No. Lake name Last of (Hmax in m, GR First day day days in m
0.5) Reference lakes without cisco kill in 2006 Big Trout 0 (39.0, 1.24) Kabekona 0 (40.5, 1.38) Scalp (27.4, 0 1.15) Ten Mile (63.4, 0 1.06) Rose (41.8, 0 1.12)

Simulated lethal days in 2006

Observed mortality day in 2006

Model agreement

No kill

No kill

Yes

No kill

No kill

Yes

No kill

No kill

Yes

No kill

No kill

Yes

No kill

No kill

Yes

Note: Stands for a DOY in 2006 and the number of continuous cisco lethal days from the lethal day predicted by the fish habitat model b DOY followed by month and date in 2006 inside brackets c The first Yes/No gives the agreement of cisco lethal prediction and reported cisco mortality in 2006, and Yes/No inside brackets gives the agreement whether or not cisco lethal days from the model include reported date with cisco mortality a

et al. 1996) that includes observed stream temperature and fish observations. The LT values compared favorably with laboratory test results involving exposures of fish in several days (Stefan et al. 1992). The LT = 23.4  C used for the cold-water fish guild in previous studies (Stefan et al. 1996, 2001) was the mean value of LT values for nine cold-water fish species (pink salmon, sockeye salmon, chinook salmon, chum salmon, coho salmon, brown trout, rainbow trout, brook trout, and mountain whitefish), which do not include cisco. The LT of cold-water fish species ranged from 22.1  C (brook trout) to 26.6  C (brown trout) in the 1992 study (Stefan et al. 1996). Eaton et al. (1995) updated the LT values that ranged from 19.8  C (chum salmon) to 24.1  C (brown trout) with guild mean of 22.9  C. The DO concentration of 3.0 mg/L requirement for the cold-water fish guild, below which mortality is more likely to occur or growth is impaired (US EPA 1976), was developed from an available US EPA database (Chapman 1986). Jacobson et al. (2010) selected a benchmark oxygen concentration of 3 mg/L which is probably lethal or nearly so for many cold-water species. Frey (1955) also used an oxygen concentration of 3 mg/L in his definition of cisco habitat. Several benchmark DO concentrations (2, 3, 4, and 5 mg/L) were considered by Jacobson et al. (2010), and they were highly correlated (Table 4). Before appropriate LT and DO limits for adult cisco were determined/used for cisco oxythermal modeling, a sensitivity analysis using 22.0  C and 23.4  C as LT and 2, 3, and 4 mg/L as DO survival limit was performed. The lethal temperature of 22.0  C used for the sensitivity analysis was determined from the lethal-nicheboundary curve (Jacobson et al. 2008) (Eq. 3) at DOlethal = 3 mg/L. The 22.0  C

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Fig. 6 Simulated isopleths of lethal temperatures (LT) and DOlethal limits in 2006 for Pine Mountain Lake for eight LT-DO limit combinations. Selected LT are 21.2 and 22.6  C (top) 22.0  C (middle) and 23.4  C (bottom), and selected DO survival limits are 2, 3, and 4 mg/L

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LT compares favorably with lower LT values for other cold-water fish species in previous studies (Stefan et al. 1992, 1996; Eaton et al. 1995). Using the lethal-nicheboundary curve (Jacobson et al. 2008), the lethal temperatures were 21.2  C and 22.6  C for DOlethal = 2 and 4 mg/L, respectively, and these two LT-DO combinations were also used for the sensitivity analysis (Table 4). The combinations of four LTs and three DO limits resulted in eight constant LT-DO criteria for the sensitivity analysis of the fish habitat model. The final LT-DO criteria, LT = 22.0  C and DOlethal = 3 mg/L, were chosen according to fish habitat model validation based on the cisco mortality field data in 2006 (Table 5) as discussed below.

Fish Habitat Model Validation in 23 Lakes Against 2006 Observations The fish habitat model uses simulated daily temperature and DO profiles in a lake to check day by day whether cisco habitable or lethal conditions occur. When the LT isotherm and the DO limit isopleth for cisco do not intersect in a day, cisco is survivable in that day; otherwise, the entire depth of a stratified lake is under lethal conditions (too warm temperature or lower DO) in that day. A number of days with cisco lethal conditions in 2006 under eight different criteria are given in Fig. 5 for Pine Mountain Lake as an example. Pine Mountain Lake located in Cass County, Minnesota, has a maximum depth of 23.8 m (deep lake) and a surface area of 6.36 km2. Pine Mountain Lake is a mesotrophic stratified lake because of its mean Secchi depth 2.4 m, mean chlorophyll-a concentration 6.5 μg/L, and GR = 2.11. The total number of lethal days in 2006 increases from 35 to 72 days (Fig. 5b and Table 4) when LT = 22.0  C and the DO survival limit changes from 2 to 4 mg/L. The 35 lethal days were not continuous as shown in Fig. 5b and were 2 days from DOY 196 (July 15–16, 2006), 26 days from 199 (July 18–August 12), 1 day from 227 (August 15), 2 days from 235 (August 23–24), and 4 days from 238 (August 26–29). When LT increases to 23.4  C (mean LT for cold-water fish species not including cisco), the total number of lethal days in 2006 decreases to 12–35 days (Fig. 5c), respectively, when DO survival limits are 2–4 mg/L. With LT = 21.2  C and DOlethal = 2 mg/L limits (Fig. 5a) from the lethal-nicheboundary curve, Pine Mountain Lake was simulated to have 56 lethal days: 196 (37 continuous lethal days) and 230 (21); with LT = 22.6  C and DOlethal = 4 mg/L limits, Pine Mountain Lake was simulated to have 55 lethal days: 186 (2), 192 (37), 231 (13), and 248 (3). With DOlethal = 4 mg/L, lethal days started 10 days early, but prevalent lethal conditions occurred after DOY 196 (July 15) for all three LT-DO limit combinations from the lethal-niche-boundary curve. Results of the sensitivity analysis using eight LT and DO survival limits in all 23 lakes are summarized in Table 4. The period of lethal conditions (lethal days) simulated using LT = 22.0  C is typically longer than the lethal days using LT = 23.4  C. When DO survival limits increase from 2 to 4 mg/L, cisco lethal days increase also (Fig. 5 and Table 4) when LT is fixed. Using LT = 23.4  C, Star, Little Pine (Otter Tail County), Bemidji, Gull, Straight, Long, and Carlos lakes were simulated to have zero or a few days with lethal conditions in 2006, which indicates

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that LT = 23.4  C used in previous studies for the cold-water guild is little too high for cisco. Three LT-DO combinations, where LT was computed using DOlethal and the cisco lethal-niche-boundary curve, resulted very similar values on lethal days in 23 lakes (Table 4), but starting days of lethal conditions could be somewhat different as shown in Fig. 5 for Pine Mountain Lake. Detailed simulation results of LT = 22.0 and DOlethal = 3 mg/L are given in Table 5 for 23 Minnesota lakes for model validation against cisco mortality observations in 2006. Table 5 lists the first DOY, the last DOY, and the total number of days with cisco lethal conditions predicted by the model (using constant lethal limits) in 2006 (hindcast or backtesting). It also lists the DOYs and the number of continuous days from DOYs with cisco lethal conditions predicted in 2006. For example, Little Turtle Lake has “180(62)” under “simulated lethal days in 2006” in Table 5 that means lethal conditions were simulated on DOY 180 (June 29, 2006) and the number of continuous cisco lethal days is 62 (DOYs 180–241). The DOY and month/day in 2006 inside brackets when cisco mortality was reported in each lake is listed under “observed mortality date in 2006” in Table 5 and used to examine model agreement. In the last column of Table 5, the first Yes/No gives the agreement of cisco lethal prediction and reported cisco mortality in 2006, and the second Yes/No inside brackets gives the agreement whether or not cisco lethal days from the model include reported date with cisco mortality. For example, for Mille Lacs Lake, the fish habitat model predicted a total of 49 days from July 22 (DOY 203) to September 8 (DOY 251) having cisco lethal conditions, which agree with reported cisco mortality in 2006, and the period of predicted cisco lethal conditions includes the reported day with cisco mortality, i.e., July 23 or DOY 204. Therefore, the model agreement with mortality observation is “Yes (Yes)” as listed in Table 5. The fish habitat model predicted the “Yes (Yes)” agreement in 13 of the 18 lakes that experienced cisco mortality in 2006 (Table 5). For four lakes (Bemidji, Star, Seventh Crow Wing, and Long), the model predicted cisco lethal conditions, but the predicted lethal periods did not include corresponding reported cisco mortality days in 2006; these lakes have the “Yes (No)” agreement (Table 5). For two lakes (Bemidji and Star), cisco lethal conditions were predicted to occur after the reported cisco mortality days in 2006. For Seventh Crow Wing Lake, cisco lethal conditions were predicted to occur from DOY 196 to 215 (August 3) in 2006, and the cisco mortality was reported on August 4. For Long Lake, cisco lethal conditions were predicted to occur from DOY 213 to 216 (August 4) in 2006, and the cisco mortality was reported on August 6. These two cases can be considered as “Yes (Yes)” agreement because cisco mortality might be reported one or a few days after cisco mortality occurred when study lakes were not constantly monitored and observed. Long Lake was predicted with only 4 days of lethal conditions. Long Lake located in Otter Tail County, Minnesota, has a maximum depth of 39.0 m (deep lake) and a surface area of 5.1 km2. Long Lake is a mesotrophic strongly stratified lake because of its mean Secchi depth 3.0 m, mean chlorophyll-a concentration 7.2 μg/L, and GR = 1.22. There was only 1 day in 2006 with observed temperature and DO profiles in Long Lake for model calibration.

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For Lake Carlos, the model did not predict cisco lethal conditions, but they had cisco mortality in 2006; the model has the No agreement with mortality observation (Table 5). Lake Carlos located in Douglas County, Minnesota, has a maximum depth of 49.7 m and a surface area of 10.5 km2. Lake Carlos is a mesotrophic strongly stratified lake because of its mean Secchi depth 3.0 m, mean chlorophyll-a concentration 5.0 μg/L, and GR = 1.15. The late summer cisco mortality event that occurred on August 27 (DOY 239) in Lake Carlos did not fit the lethal-nicheboundary curve developed from the midsummer events in 16 lakes (Jacobson et al. 2008). Based on the lethal-niche-boundary curve and measured profiles on September 1, 2006 (Jacobson et al. 2008), cisco could exist in some surface layers with low temperatures and high DO, but could not exist in the hypolimnion with anoxic conditions. Jacobson et al. (2008) also studied the five reference lakes that did not experience cisco mortality in 2006. These five reference lakes are all deep strongly stratified lakes (GR < 1.4). The fish habitat model using constant LT and DOlethal limits predicted no lethal conditions for cisco in all five reference lakes (Table 5). Therefore, the fish habitat model has an overall good agreement in the 23 study lakes with and without cisco mortality reported in 2006. With LT = 21.2  C and DOlethal = 2 mg/L limits, Straight Lake changed the agreement from “Yes (Yes)” to “Yes (No)” and Seventh Crow Wing from “Yes (No)” to “Yes (Yes)”; with LT = 22.6  C and DOlethal = 4 mg/L limits, Star Lake changed the agreement from “Yes (No)” to “Yes (Yes)” when comparing with cisco mortality observations in 2006. Therefore, three LT and DOlethal limit combinations derived from the lethal-niche-boundary curve (Jacobson et al. 2008) had similar overall agreement with cisco mortality observations in 2006, and all of them could be used for constant lethal limits for adult cisco when there is no additional laboratory and field data support on survival limits. To be consistent with previous studies with DO survival limit (Stefan et al. 1996, 2001; Fang et al. 2004a, b) or benchmark DO (Jacobson et al. 2010; Fang et al. 2012b; Jiang et al. 2012) of 3 mg/L, LT = 22.0  C and DOlethal = 3 mg/L limits were used for remaining of the oxythermal habitat modeling with constant lethal limits.

Simulation Results of 28 Regional Lakes and 30 Virtual Lakes Both 28 regional lakes (LakeR01–LakeR18, LakeR28–LakeR33, and LakeR37– LakeR39 in Table 1) and 30 virtual lakes (Table 2) were first simulated using MINLAKE2010 to generate daily temperature and DO profiles over 48 simulation years (1962–2008 under the past climate conditions) and then simulated using the fish habitat model to determine number of days with cisco lethal conditions year by year (excluding the first year 1961) using constant lethal limits. Results for shallow or medium-depth lakes and deep lakes were grouped and analyzed separately as recommended by Fang et al. (2014). Figure 7 shows contour plots of total number of years with cisco lethal days and average cisco kill days for the years with lethal conditions under past (left frames)

Fig. 7 Contour plots of total number of years with cisco lethal days (top) and average cisco lethal days for the years with lethal conditions (bottom) under past (1962–2008) and future (MIROC 3.2) climate scenarios. Duluth weather data were used for model simulations. Contours were derived by interpolation from simulated points for 28 regional lakes

684 X. Fang et al.

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685

and future (right frames for MIROC 3.2) climate scenarios. Duluth weather data over 47 years were used for model simulation results presented in Fig. 7. Contours were derived by interpolation from simulated points for 28 regional/representative lakes (Fig. 7). Under the past climate conditions, shallow lakes with a geometry ratio >5.2 m
0.5 had 23–47 years with lethal conditions and are projected to have all 47 years with lethal days under MIROC 3.2 (Fig. 7). Average cisco lethal days for the years with lethal conditions under the past climate conditions ranged from 11 to 26 days and are projected to range from 38 to 65 days in shallow lakes under MIROC 3.2 climate scenario. Therefore, 12 shallow regional lakes simulated (Fig. 7) and 14 shallow lakes in the 620 cisco lake database (Fig. 5) do not provide suitable habitat conditions to support cisco. For 16 medium-depth lakes simulated under the past climate conditions, there were 0 (GR = 1.63 m
0.5) to 8 (GR = 4.33 m
0.5) years with lethal conditions with average lethal days ranging from 0 to 14 days (Fig. 7). Under future climate scenario (MIROC 3.2), they are projected to have 20–47 years with lethal conditions with average lethal days ranging from 12 to 52 days (Fig. 7). It seems medium-depth lakes are most vulnerable to climate change with largest increases in lethal days and the number of years with lethal conditions. When simulated under past climate conditions, none of the 30 virtual deep lakes (Hmax = 24 m) have cisco lethal conditions; therefore, deep lakes provided relatively good fish habitats compared with shallow and medium-depth lakes. The results for virtual deep lakes under past climate conditions seem to have certain disagreement with cisco mortality observations (Table 5). Minnesota lakes with Hmax < 20.0 m were classified as deep lakes (Stefan et al. 1996), and 7 of the 18 study lakes with cisco mortality in 2006 are deep lakes with GR ranging from 1.15 to 3.26 m
0.5 (Table 5). Generalized model parameters (Fang et al. 2010a) were used for simulations in the 30 virtual lake types, but for the 23 lakes (Table 5), model parameters were first calibrated against measured profiles before the cisco habitat model was applied. Differences in model parameters are one of the major reasons for disagreement in habitat projections and suggest that other oxythermal habitat parameters, e.g., TDO3 (Jacobson et al. 2010), should be used for studying cisco fish habitat in relatively deep lakes. Under the future climate scenario (MIROC 3.2), projected number of years with lethal conditions are up to 20 years with average lethal days up to 23 days (Fig. 8). Distributions of total number of years with cisco lethal days and average cisco kill days for the years with lethal conditions under MIROC 3.2 are given in Fig. 8, which shows eutrophic deep lakes are projected with more lethal days. Figure 8 was not used to divide 221 deep cisco lakes into tier 1 to tier 3 refuge lakes as it was done using TDO3 (Fang et al. 2012; Jiang et al. 2012). Under MIROC 3.2 climate scenario, those lakes with 0–2 years (Fig. 8 top) and 0–3 days (Fig. 8 bottom) with lethal conditions provide most suitable habitat for cisco, and lakes with 2–5 years (Fig. 8 top) and 3–6 days (Fig. 8 bottom) with lethal conditions also provide suitable habitat for cisco. Good-growth habitat areas and volumes used in previous studies (Stefan et al. 1996, 2001; Fang et al. 2004a, b) may be used to classify refuge lakes in the future.

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Fig. 8 Contour plots of total number of years with cisco lethal days (top) and average cisco lethal days for the years with lethal conditions (bottom) in deep lakes under future (MIROC 3.2) climate scenarios. Duluth weather data were used for model simulations. Contours were derived by interpolation from simulated points for 30 virtual lakes (Hmax = 24 m)

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Simulation and Validation of Cisco Oxythermal Habitat Using the Lethal-Niche-Boundary Curve For oxythermal habitat modeling of cisco, the second option is to use temperaturevarying lethal DO limits. The fish habitat model uses a fitted regression equation as the lethal niche boundary of adult cisco developed by Jacobson et al. (2008). The equation mapped the DO concentrations and water temperatures from the profiles measured in 16 Minnesota lakes that experienced cisco mortality in 2006 (Table 6). One profile was measured in each of the 16 lakes on the same day or a few days after reported mortality. The shifted exponential function given in Eq. 3 is a fit of the 99th quartile nonparametric regression line bracketed the lethal combinations of observed oxygen and temperature in 16 lakes with midsummer (July 19 to August 6) mortality events in 2006 (Jacobson et al. 2008). First, the fish habitat model (the option 2) was validated in 23 Minnesota lakes (Table 6) and then used to project cisco lethal conditions in 36 representative lake types under past (1992–2008) climate conditions and a future climate scenario (MIROC 3.2) at Bemidji, Minnesota. Based on the number of years with cisco kill and the number of annual cisco lethal days, lake types that most likely could not support cisco were identified, and lake types that can support cisco under both the past climate and the future climate scenarios were identified as potential cisco refuge lakes.

Fish Habitat Projection Model There were 18 Minnesota lakes with reported cisco mortality in 2006, but no temperature and DO profiles were measured in Mille Lacs Lake, which had automated temperature recorder data at 2 m below the surface (Jacobson et al. 2008). Measured temperature and DO profiles in Lake Carlos, which had late summer cisco mortality event occurred on August 27, were not used to fit the lethal-niche-boundary curve (Jacobson et al. 2008). The lethal-niche-boundary curve of adult cisco developed from measured temperature and DO profiles in 16 Minnesota lakes is given as DOlethal ¼ 0:40 þ 0:0000060 e0:59T

(3)

where DOlethal and T are the DO concentrations (in mg/L) and the water temperatures (in  C), respectively, which define the lethal niche boundary (Jacobson et al. 2008). The computed DOlethal is the required minimum DO concentration at a given water temperature T for cisco to survive. For the regression Eq. 3, the coefficients 0.40 and 0.0000060 are in mg/L, and the coefficient 0.59 for the exponent is in  C
1. Equation 3 indicates the DO survival limit for adult cisco is not constant but depends on water temperature. The lethal-niche-boundary curve for cisco (Eq. 3)

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Table 6 Fish habitat validation results using the lethal-niche-boundary curve for 23 Minnesota lakes. Simulated and observed days with lethal conditions for cisco are given as DOYs

Lake name Little Turtle

Lethal conditions No. First Last of day day days 181 222 38

Andrusia Little Pine (Otter Tail) Cotton

192 199

234 216

39 17

188

225

36

Pine Mountain Leech

192

241

49

189

217

22

Itasca Gull Woman

189 209 183

222 227 224

31 19 36

Little Pine 183 240 48 (Crow Wing) Eighth Crow 195 222 28 Wing Bemidji 212 217 6 Mille Lacs 216 241 26 Star 212 216 5 Seventh 196 215 20 Crow Wing Long 216 216 1 Carlos 0 Straight 0 Reference lakes without cisco kill in 2006 Big Trout 0 Kabekona 0 Scalp 0 Ten Mile 0 Rose 0

Observed mortality day in 2006 200 (7/19)b

Model agreement Yes (Yes)c

202 (7/21) 203 (7/22)

Yes (Yes) Yes (Yes)

188(1), 190(1), 192(34) 192(45), 238(4)

205 (7/24)

Yes (Yes)

207 (7/26)

Yes (Yes)

189(1), 195(6), 203(15) 189(1), 193(30) 209(19) 183(2), 187(1), 190(1), 193(32) 183(5), 190(39), 233(3), 240(1) 195(28)

211 (7/30)

Yes (Yes)

209 (7/28) 210 (7/29) 210 (7/29)

Yes (Yes) Yes (Yes) Yes (Yes)

214 (8/2)

Yes (Yes)

216 (8/4)

Yes (Yes)

212(6) 216(26) 212(5) 196(20)

208 (7/27) 204 (7/23) 200 (7/19) 216 (8/4)

Yes (No) Yes (No) Yes (No) Yes (No)

216(1) No kill No kill

218 (8/6) 239 (8/27) 213 (8/1)

Yes (No) No No

No kill No kill No kill No kill No kill

No kill No kill No kill No kill No kill

Yes Yes Yes Yes Yes

Simulated lethal days in 2006 182(4)a, 187(4), 193(30) 192(37), 233(2) 199(1), 201(16)

Note: a Stands for a DOY in 2006 and the number of continuous cisco lethal days from the lethal day predicted by the fish habitat model b DOY followed by month and date in 2006 inside brackets c The first Yes/No gives the agreement of cisco lethal prediction and reported cisco mortality in 2006, and Yes/No inside brackets gives the agreement whether or not cisco lethal days from the model include reported date with cisco mortality

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Fig. 9 Simulated DO versus simulated temperature for selected days to show three different types of fish habitat in Pine Mountain Lake and Lake Itasca (Table 6) and the lethal-niche-boundary curve of adult cisco (Eq. 3)

was plotted in Fig. 9 for two Minnesota lakes (Pine Mountain Lake and Lake Itasca). In comparison with the previous constant lethal temperature for cold-water fish species, i.e., 23.4  C (Eaton et al. 1995), the lethal temperature from Eq. 3 is only 22.0  C when 3.0 mg/L is used as the DO survival limit (Jacobson et al. 2008). In this study, the required DO concentration DOlethal was computed from the simulated water temperature in each water layer of a lake for each simulated day using Eq. 3. The computed DOlethal value was then compared with the simulated DO concentration in the same layer; lethal conditions for cisco were assumed to occur if the simulated DO concentrations were less than the DOlethal values in all water layers (from the lake water surface to the lake bottom) on that day. In Fig. 9, simulated DO was plotted against simulated temperature for selected days in the two lakes. In Pine Mountain

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Lake, from July 11, 2006 (DOY 192 in Table 6) to August 29, 2006 (DOY 241), there were 49 days (Table 6, one discontinuous lethal day) that all simulated T-DO data points (shown by the crosses) are located at the right side of or below the lethal-nicheboundary curve when simulated DO concentrations were below computed DOlethal values at simulated temperatures at all water depths. The same situation of cisco lethal conditions was predicted to occur on July 31, 2006 in Lake Itasca. If simulated DO concentrations are less than the DOlethal values in only some of the water layers, lethal conditions for cisco are not assumed to occur on that day because cisco can swim to other water layers having suitable T and DO condition. These days with habitat at some depths are shown as filled triangles in Fig. 9. Pine Mountain Lake on July 9, 2005 had lower DO at higher temperatures near the surface and near anoxic DO (0.2 mg/L) in the hypolimnion. Therefore, layers near the surface and in the hypolimnion could not support cisco habitat, but some intermediate layers had high enough DO at simulated temperatures to support cisco habitat. Lake Itasca on August 7, 2008 had suitable cisco habitat in the surface layers and no cisco habitat in the bottom layers (Fig. 9). Lake Itasca located in Clearwater County, Minnesota, has a maximum depth of 13.7 m and a surface area of 4.3 km2. Lake Itasca is mesotrophic due to its mean Secchi depth 2.8 m and mean chlorophyll-a concentration 10.4 μg/L and has relatively weak stratifications because of its GR = 3.32 (Gorham and Boyce 1989; Stefan et al. 1996). When simulated DO concentrations are greater than the DOlethal values in all water layers, fish can live in any depth of the lake, i.e., filled circles in Fig. 9 (e.g., October 15, 2004 in Pine Mountain Lake and September 12, 2008 in Lake Itasca).

Validation of Fish Habitat Model Figure 9 shows simulated DO versus simulated temperature during two periods (July 11, 2006–August 24, 2006 and August 26–29, 2006) in Pine Mountain Lake when cisco lethal conditions were predicted by the fish habitat model using the cisco lethal-niche-boundary curve. Surface water temperatures in Pine Mountain Lake (As = 6.36 km2, Hmax = 23.77 m, and GR = 2.11 m
0.5) reached 29.4  C on July 31, 2006. When the lethal temperature of 22.0  C for adult cisco was used, for the 49 days in Pine Mountain Lake (Fig. 9), 43 % of water depths had temperatures greater than 22.0  C, and 58 % of water depths had DO < 3 mg/L. The cisco mortality in Pine Mountain Lake was reported on July 26, 2006 (Jacobson et al. 2008) when the fish habitat model predicted continuous 16 days of lethal conditions starting from July 11, 2006. The fish habitat modeling using the cisco lethal-niche-boundary curve was validated in the 23 Minnesota lakes that Jacobson et al. (2008) studied first in 2006. Validation results are summarized in Table 6 for each lake, which shows similar information as Table 5 does but using different oxythermal lethal limits. For example, Lake Andrusia has “192(37), 233(2)” under “simulated lethal days in 2006” in Table 6 that means lethal conditions were simulated on DOY 192 (July 11, 2006) with the number of continuous cisco lethal days of 37 (DOYs 192–228)

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and on DOYs 233–234 (August 21–22, 2006). Lethal conditions were not simulated for DOYs 229–232 (August 17–20, 2006) in Lake Andrusia. In comparison to “Observed mortality day in 2006” in Table 6, the model agreement with mortality observation is “Yes (Yes)” for Lake Andrusia (Table 6). Using the lethal-niche-boundary curve, for five lakes (Bemidji, Mille Lacs, Star, Seventh Crow Wing, and Long), the model predicted cisco lethal conditions, but the predicted lethal periods did not include corresponding reported cisco mortality days in 2006; these lakes have the “Yes (No)” agreement (Table 6). For three lakes (Bemidji, Mille Lacs, and Star), cisco lethal conditions were predicted to occur after the reported cisco mortality days in 2006. In the Seventh Crow Wing Lake, cisco lethal conditions were predicted to occur from DOY 196 to 215 (August 3) in 2006, and the cisco mortality was reported on August 4. This case can be considered as “Yes (Yes)” agreement because cisco mortality might be reported one or a few days after cisco mortality occurred when study lakes were not constantly monitored and observed. Long Lake was predicted with only 1 day of lethal conditions. There are two lakes (Straight Lake and Lake Carlos) that the model did not predict cisco lethal conditions, but they had cisco mortality in 2006; the model has the No agreement with mortality observation (Table 6). Lake Carlos had a late summer cisco mortality event occurred on August 27, which might be due to the formation of the metalimnetic oxygen minimum during part of the summer (Smith et al. 2014). The five reference lakes (deep strongly stratified) that Jacobson et al. (2008) studied did not experience cisco mortality in 2006. The fish habitat model using simulated temperature and DO profiles predicted no lethal conditions for cisco in all five reference lakes (Table 6). Therefore, the fish habitat model using the lethalniche-boundary curve has overall good agreement in the 23 study lakes with and without cisco mortality reported in 2006. The overall good agreement is very similar but not exactly the same as the agreement using the constant lethal limits (LT = 22.0  C and DOlethal = 3 mg/L, Table 5).

Fish Habitat Simulations in 36 Representative Lake Types To understand cisco habitat and to determine cisco kill in 36 different lake types (LakeR01–LakeR36 in Table 1), daily water temperature and DO profiles were simulated using MINLAKE2012 under past (1991–2008) climate conditions from Bemidji weather station and the corresponding future climate scenario (MIROC 3.2). Bemidji weather station is close to most of the 23 study lakes (Tables 5 and 6) and has 18 years of weather data. The fish habitat model for cisco was applied every day year by year from 1992 to 2008 using simulated daily water temperature and DO profiles. Results for the first simulation year (1991) were not used for cisco modeling in order to remove the possible effect of initial conditions.

Total Days of Cisco Lethal Conditions in Each Year Total days of lethal conditions for cisco in each year over 17 simulation years were used to create box plots showing the maximum and minimum and 25 %, 50 %, and

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75 % quartile values simulated for each of the 36 representative lake types in Minnesota under past climate conditions and MIROC 3.2 future climate scenario (Fang et al. 2014). Lethal conditions may be continuous for many days or discontinuous for some days (Fig. 9 and Table 6). For the 12 shallow lakes with GR  5.29 m
0.5, median annual days of cisco lethal conditions ranged from 13 to 22 days under past climate conditions and are projected to range from 47 to 55 days under the future climate scenario (Fang et al. 2014). These results indicate again that shallow lakes typically cannot support cisco habitat. In the MN DNR cisco lake database, there are a total of 620 cisco lakes, of which 37 lakes have GR  5.29 m
0.5 and maximum depths less than 11.0 m. There are 14 lakes with Hmax < 5.0 m that are classified as shallow lakes in Minnesota (Stefan et al. 1996), of which 13 lakes have GR > 5.29 m
0.5 and one lake has GR = 4.4 m
0.5. These lakes had cisco observed in the past, but, most likely, they cannot sustain cisco habitat. For the 12 medium-depth lakes with Hmax = 13.0 m (LakeR10–LakeR18 and LakeR31–LakeR33), GR values are 1.63, 2.78, and 4.33 m
0.5 (Table 1). Median annual days of cisco lethal conditions ranged from 0 to 1 day under past climate conditions and are projected to range from 19 to 49 days under the future climate scenario. Under past climate conditions, cisco lethal conditions reached a maximum of 30 days for medium-depth lakes during the unusual hot summer in 2006. These lakes are vulnerable to climate warming because lethal conditions are projected up to 80 days (Fang et al. 2014). For the 12 deep lakes with Hmax = 24 m (LakeR19–LakeR27 and LakeR34–LakeR36), eutrophic deep lakes (LakeR19, LakeR22, and LakeR25) and mesotrophic large deep lake (LakeR26 with GR = 2.34 m
0.5) are projected to have some cisco lethal days under the future climate scenario (Fang et al. 2014). Cisco lethal conditions, however, were not simulated to occur under past climate conditions (1992–2008). Large deep lakes with GR = 2.34 m
0.5 seem to require Secchi depth more than 2.5 m to have nonlethal conditions under the future climate scenario. Other strongly stratified mesotrophic and oligotrophic deep lakes (LakeR20, LakeR21, and LakeR34 with GR = 0.88; LakeR23, LakeR24, and LakeR35 with GR = 1.50; and LakeR27 and LakeR36 with GR = 2.34 in Table 1) are possible to support cisco habitat under both past and future climate conditions. These deep lakes are good candidates of cisco refuge lakes (Fang et al. 2012b; Jiang et al. 2012). Annual cisco lethal days are strongly dependent on lake stratification characteristics (i.e., GR) but vary relatively weakly with trophic status (i.e., SD). The four lakes with the same GR but different Secchi depths were grouped together to compute mean and standard deviation of annual cisco lethal days under past climate conditions and the future climate scenario (Fig. 10). There are consistent patterns of average annual lethal days for each group of lakes with the same maximum depth (shallow, medium-depth, and deep). Shallow lakes (GR > 5.2 m
0.5) have large numbers of cisco lethal days, medium-depth lakes (GR = 1.63, 2.78, and 4.33 m
0.5) have cisco lethal days increasing with geometry ratio (Fig. 10), and deep lakes (GR = 0.88, 1.50, and 2.34 m
0.5) have little or no cisco lethal days. The four lakes with GR = 1.63 m
0.5 (LakeR10–LakeR12 and LakeR31) are small medium-depth lakes (As = 0.2 km2 and Hmax = 13.0 m). Cisco lethal days

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Fig. 10 Number of annual cisco lethal days (mean  standard deviation) simulated for the 36 representative lake types with nine GR values under past climate conditions and the future climate scenario (Fang et al. 2014)

projected for these four lakes (especially under the future climate scenario) are different from deep lakes with GR just less or greater than 1.63 m
0.5 (Fig. 10). These results may indicate that fish habitat modeling for deep lakes should be separated from the modeling for medium-depth lakes. To further prove the point, four deep lakes (LakeR41–LakeR44, Table 1) having GR = 1.63 m
0.5 with larger As = 2.32 km2 and deeper Hmax = 24.0 m were created, and daily temperature and DO profiles were simulated using MINLAKE2012 under past climate conditions and the future climate scenario. The simulated number of annual cisco lethal days in these four deep lakes is zero for all years (1992–2008) under past climate conditions and is projected to be zero under the future climate scenario except for LakeR41, which is an eutrophic deep lake having 1 year with 4 days of cisco lethal projection. Therefore, simulations of cisco lethal days in these deep lakes (LakeR41–LakeR44) are consistent with other deep lakes but different from medium-depth lakes with the same geometry ratio. Other fish habitat parameters, e.g., good-growth period for cold-water fish in 27 Minnesota lake types, had similar discontinuous patterns in some medium-depth and deep lakes in a previous study (Fang et al. 2004b). In the MN DNR cisco lake database, there are 385 medium-depth lakes with 5 m  Hmax < 20 m and 221 deep lakes with Hmax  20 m. Therefore, it is recommended to model cisco habitat and survival separately for medium-depth lakes and deep lakes in the future.

Number of Years with Cisco Kill It is still uncertain how many days that exceed non-survival or lethal niche limits are necessary to result fish mortality. In previous regional fish habitat projections (Stefan et al. 1996) when daily water temperature and DO concentration profiles used for fish habitat simulations were long-term (30-year) averages, fish kill was assumed to occur when the number of non-survival days (either consecutive or discontinuous) totaled at

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least seven. In this study, a sensitivity analysis on the number of continuous lethal days for determining cisco kill was performed when daily profiles were not averaged over 17 years (1992–2008), but cisco lethal conditions were checked in each day year by year. A cisco kill was assumed to occur if the number of continuous lethal days was greater than 3, 7, and 14 days for the sensitivity analysis. The 3 days are the half of 7 days used before, and 14 days are the double of 7 days. For the 11 Minnesota lakes (Table 6) in which the simulated lethal days included the reported cisco mortality days in 2006, the number of continuous lethal days to the mortality day was calculated and ranged from 2 (Gull Lake) to 25 (Little Pine Lake in Crow Wing County) days. Median value of the number of continuous lethal days to the mortality day was 14 days (mean value 13 days with a standard deviation 7 days). This result provides another reason to use 14 days for the sensitivity analysis. When 3, 7, and 14 continuous lethal days were used for determining cisco kill, Fig. 11 shows the numbers of years with cisco kill simulated for the 36 representative lake types in Minnesota for 17 simulation years under past (1992–2008) climate conditions (blue triangles) and the future climate scenario (red circles). The x axis gives lake’s geometry ratio, and the four lake types with the same geometry ratio (Table 1) were grouped together to compute mean and standard deviation of the number of years with cisco kill. Under past climate conditions, the 12 shallow lakes (LakeR01–LakeR09, LakeR28–LakeR30, GR = 5.29, 9.03, and 14.06 m
0.5) were simulated to have cisco kills on average in 14–15 years when 3 continuous lethal days were used to determine whether cisco kill happens or not. Under the future climate scenario (MIROC 3.2), the 12 shallow lakes are projected to have cisco kills in all 17 simulation years. These results provide strong evidence to indicate that shallow lakes cannot sustain cisco habitat under future warmer weather. The shallow lakes in MN cisco database are weakly stratified or polymictic with relatively high temperatures from surface to bottom during the summer which caused summer cisco kill almost every year from 1992 to 2008. Although cisco was observed in these 14 lakes in the past, whether cisco still exists in them is unknown. The projection under the future climate scenario shows they are not favorable to support cisco habitat every year. When 7 continuous lethal days were used to determine whether cisco kill happens, the 12 shallow lakes were simulated to have cisco kills on average in 11–12 years (range from 9 to 13 years) under past climate conditions and are projected to have 17 years of cisco kills under the future climate scenario. When 14 continuous lethal days were used to determine whether cisco kill happens, the 12 shallow lakes were simulated to have only 1 year (2006) with cisco kill under past climate conditions and are projected to have 11–12 years of cisco kills under the future climate scenario. It projects there are more years with cisco kills in some medium-depth lakes than in the 12 shallow lakes under the future climate scenario (Fig. 11). This finding may indicate that 14 continuous lethal days for determining cisco kill may be longer than how many lethal days would be needed for cisco mortality to occur because it gives inconsistent results on fish habitat projections.

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Fig. 11 Numbers of years with cisco kill simulated for the 36 representative lake types in Minnesota under past climate conditions (triangles) and the future climate scenario (circles) using 3, 7, and 14 continuous lethal days for determining cisco kill (Fang et al. 2014)

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Therefore, the 14 continuous lethal days for determining cisco kill are not recommended for further fish habitat study. Using 3 continuous lethal days for determining cisco kill, the 12 medium-depth lakes were simulated to have cisco kills on average in 2–7 years (range from 1 to 8 years) under past climate conditions and are projected to have 16–17 years of cisco kills under the future climate scenario. Using 7 continuous days for determining cisco kill, the 12 medium-depth lakes were simulated to have cisco kills on average in 1–5 years (range from 0 to 6 years) under past climate conditions and are projected to have 15–17 years (range from 13 to 17 years) of cisco kills under the future climate scenario. Figure 11 shows medium-depth lakes are most vulnerable to climate warming with average increase of 13 years with cisco kill (range from 9 to 15 years). The 12 deep lakes (LakeR19–LakeR27, LakeR34–LakeR36) were simulated to have no cisco kill under past climate conditions using either 3, 7, or 14 continuous lethal days for determining cisco kill (Fig. 11). The 12 deep lakes are projected to have on average 1–4 years (range from 0 to 9 years) or 0–2 years (range from 0 to 6 years) of cisco kills under the future climate scenario when 3 and 7 continuous lethal days were used for determining cisco kill, respectively. Only eutrophic deep lakes (SD = 1.2 m, LakeR19, LakeR22, and LakeR25) and large mesotrophic deep lake (As = 10 km2, SD = 2.5 m, LakeR26) are projected to have a few years with cisco kill under the future climate scenario. Figure 11 shows most mesotrophic and oligotrophic deep lakes can support cisco habitat under both past climate conditions and the future climate scenario and are good candidates for cisco refuge lakes, as supported by previous studies (Fang et al. 2012b; Jiang et al. 2012). It seems that 3 or 7 continuous lethal days for determining cisco kill provide quite reasonable results for cisco kill simulations in shallow, medium-depth, and deep lakes in Minnesota. The box plots of the numbers of annual continuous lethal days greater than or equal to 3 and 7 days simulated for the 36 lake types in Minnesota under past climate conditions (1992–2008) and the future climate scenario (MIROC 3.2) were presented elsewhere (Fang et al. 2014). Those lethal days that are not continuous for 3 or 7 days were excluded. Under past climate conditions, 1 to a few years with cooler summers did not result in cisco kills in the 12 shallow lakes, but most other years had cisco kills with annual continuous lethal days up to 36 days (Fang et al. 2014). Under the future climate scenario, projected annual continuous lethal days are up to 94 days and 40 days in shallow lakes and eutrophic deep lakes, respectively. Medium-depth lakes are projected to have relatively large change in annual continuous lethal days.

Identification of Cisco Refuge Lakes Using the Fixed Benchmark Period Cisco Habitat Criteria and Selection of Cisco Refuge Lakes The oxythermal habitat approach used in the oxythermal fish niche modeling options 1 and 2 (Fig. 3) uses lethal limits for temperature and oxygen. In the third option, the quality of oxythermal habitat for cisco was determined using a single variable,

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TDO3, i.e., water temperature at 3 mg/L of DO, proposed by Jacobson et al. (2010). A higher TDO3 value represents higher oxythermal stress for the cold-water fish. For example, if TDO3 is high, then fish must choose between well-oxygenated water that is too warm and live in hypoxic water that is of a proper temperature. The oxygen concentration of 3 mg/L is probably lethal or nearly so for many cold-water species (Frey 1955; US EPA 1986; Evans 2007) and therefore represents a desirable benchmark for a presence/absence niche model. Oxythermal habitat niche relationships developed for several cold-water fish (including cisco) by Jacobson et al. (2010) were used to identify potential refuge lakes for cisco under future climate scenarios. Niche breadth measures, i.e., central response borders used by Heegaard (2002), were used by Jacobson et al. (2010) to identify values of TDO3 measured in the period of greatest oxythermal stress in late summer (maxTDO3) useful for describing the quality of cold-water habitat for cisco. Central response borders essentially bracket the core range of a habitat variable required for a species to thrive (Heegaard 2002). The central species response borders for cisco ranged from maxTDO3 of 4.0  C to 16.9  C (Jacobson et al. 2010). TDO3 can be determined by interpolation from measured or simulated (vertical) temperature and DO profiles in a stratified lake. When non-monotonic profiles generate low oxygen concentrations with more than one TDO3 value, the coldest TDO3 was used (Jacobson et al. 2010). Temperature and DO profiles simulated for the first year (1961) were not used to compute TDO3 in order to avoid possible effects of assumed initial conditions. Figure 12 illustrates the procedure how TDO3 can be extracted from either measured or simulated temperature and DO profiles. Elk Lake (Fig. 12) has a maximum depth of 27 m and mean summer Secchi depth of 3.6 m (mesotrophic lake). Elk Lake has a lake geometry ratio of 1.16 and is a strongly stratified (dimictic) lake; it has excellent cold-water oxythermal habitat with TDO3 = 5.8  C on June 24, 2008 (using observed temperature and DO profiles) and is projected to have a TDO3 value of 6.3  C on June 24 under the future climate scenario MIROC 3.2. There were 99 measured T and DO profiles that had adequate data to extract TDO3 values for the 21 cisco lakes (Fang et al. 2010b). The standard error of TDO3 determined from simulated profiles against TDO3 from 99 measured profiles was 2.19  C with correlation coefficient R = 0.88 (Fang et al. 2010b). Through cisco habitat modeling, cisco refuge lakes were selected and identified in two categories: tier 1 refuge lakes and tier 2 refuge lakes. Tier 1 refuge lakes have TDO3 less than or equal to 11  C, and tier 2 refuge lakes have TDO3 less than or equal to 17  C but greater than 11  C. Lakes having TDO3 greater than 17  C are classified as tier 3 or non-refuge lakes. The limit of 17  C corresponds to the upper cisco central response border of TDO3, and the limit of 11  C is near the midpoint of the cisco central response borders of TDO3, as well as the upper central response border of TDO3 for lake whitefish Coregonus clupeaformis (Jacobson et al. 2010). Therefore, tier 1 refuge lakes identified for cisco in this study are also useful to the management of lake whitefish in Minnesota. The multiyear average TDO3 over a fixed benchmark (FB) period was used to identify cisco refuge lakes in Minnesota. The benchmark period is the period of greatest oxythermal stress for cold-water fish. It is defined as the month (31-day

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Fig. 12 Examples of measured (a) and simulated (b) temperature and DO profiles in Elk Lake for past (a) and a future (b) climate to show the determination of TDO3 (temperature at 3 mg/L DO) and (c) time series of simulated daily TDO3 values for Elk Lake in 2004 and for future climate scenarios CGCM 3.1 and MIROC 3.2. The fixed benchmark periods for stratified lakes are between the vertical dashed lines (Fang et al. 2012b)

period) with the highest value of TDO3 and typically occurs in late summer (Jacobson et al. 2010). From a total of 9,521 T and DO profiles measured in 1,623 Minnesota lakes in the years 1993 through 2005, associated maximum TDO3 values were computed in summer periods, and then Jacobson et al. (2010) determined that the period of greatest oxythermal stress for cold-water fish differed by stratification status of a lake. The stress occurred earlier in unstratified lakes. In this study, the fixed benchmark (FB) period from July 28 through August 27 proposed by Jacobson et al. (2010) was chosen to calculate the monthly (31-day) average of daily TDO3, called ATDO3FB, in each simulated year over the 47-year simulation period because the 30 simulated virtual cisco lakes (Table 2) are strongly stratified lakes. The overall modeling approach of the option 3 was depicted in Fig. 3 and discussed in detail by Fang et al. (2012b). To pursue the overall objective, we had to (1) review how the T and DO habitat constraints on cold-water fishes in lakes can be quantified (oxythermal fish habitat criteria), (2) develop a method to quantify

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oxythermal fish habitat under past climate and by how much climate warming will change it in existing cisco lakes, (3) validate that the methods under (1) and (2) would give results for past climate conditions that would match actual cisco observations in lakes, (4) apply the method to make projections for a representative number of lakes in the future, and (5) extrapolate those results to 620 cisco lakes of Minnesota. To implement the above modeling approach, 30 “virtual” cisco lake types (Table 2) were chosen as representative of the entire set of 620 lakes. For step (4), to assess the quality of cisco habitat in 30 virtual cisco lakes and to identify refuge lakes, the 47-year average of annual ATDO3FB values in the 1962–2008 simulation period (i.e., AvgATD3FB, Fig. 3) was calculated and compared to TDO3 limits (11  C and 17  C determined by the analysis of field data) to divide 620 Minnesota cisco lakes into three tiers. It is impossible to validate the projected number of refuge lakes for future climate scenarios, but a model validation on 23 cisco study lakes was performed (Table 7). Adult cisco mortality was reported in 18 lakes in Minnesota during the unusually hot summer of 2006, and no cisco mortality was reported in five reference lakes (Jacobson et al. 2008), which is shown in the last column “Reported 2006 cisco mortality” of Table 7. Water temperature and DO profiles in all 23 lakes were simulated under 2006 weather data from the closest weather station after necessary model calibration (Fang et al. 2014). ATDO3FB in 2006 was calculated for each lake and used to classify the lake into tier 1 and tier 2 refuge lakes or tier 3 non-refuge lake. The ATDO3FB values in 2006 range from 13.2  C (Lake Carlos) to 25.3  C (Little Turtle Lake) for 18 Minnesota lakes with cisco mortality (Table 7). Except Lake Carlos (tier 2 refuge lake), all other 17 cisco lakes with 2006 cisco mortality are classified as tier 3 non-refuge lakes because their ATDO3FB values in 2006 are greater than 17  C. The ATDO3FB values in 2006 for five reference lakes range from 6.4  C (Big Trout Lake) to 14.3  C (Rose Lake): four references are classified as tier 1 refuge lake, and only Rose Lake is classified as tier 2 non-refuge lake in 2006 (Table 7). Rose Lake has one profile for model calibration. Out of 23 cisco study lakes, there are two lakes (Lake Carlos and Rose Lake) having sort of disagreement with 2006 observations. Overall, there is a remarkable agreement between model predictions of refuge lake classification using ATDO3FB and observed adult cisco mortality and survival lakes in 2006 (Table 7). This study was to develop a method to rank the quality of fish habitat for cisco in Minnesota lakes and the identification of potential refuge lakes if and when projected future (warmer) climate scenarios become reality. When a fish species is eliminated by changes in water temperature, it is not only a loss but also opens the habitat for other, exotic invasive species. For these reasons, a method to identify potential refuge lakes is important.

Multiyear Average of Oxythermal Stress (AvgATDO3FB) From the time series of daily TDO3 for each year in the 47-year (1962 to 2008) simulation period, different TDO3 statistics can be extracted, e.g., the annual

Lake name Little Turtle Star Mille Lacs Andrusia Little Pine (Otter Tail) Cotton Pine Mountain Leech Bemidji Itasca Gull Woman Straight

ATDO3FB ( C)b 25.28

22.63 22.75 24.08 21.09

25.25 24.21

23.91 21.82 23.66 23.23 25.23 21.55

Stratified or nota No

Yes No Yes Yes

No Yes

No Yes Yes Yes No Yes

23.92 22.04 24.55 23.43 25.32 22.34

25.25 24.99

23.15 24.20 24.62 22.44

ATDO3VB ( C) 25.31

3 3 3 3 3 3

3 3

3 3 3 3

Tier of refuge lakec 3

20.77 19.37 20.71 20.45 21.36 16.69

22.00 21.83

20.02 20.76 21.10 19.49

AvgTDO3FB ( C)d 21.88

21.10 19.75 21.43 20.68 21.90 17.08

22.30 22.45

20.69 22.09 21.52 20.20

AvgTDO3VB ( C) 22.18

3 3 3 3 3 2 or 3

3 3

3 3 3 3

Tier of refuge lakee 3

26.15 23.25 26.33 24.41 27.13 24.06

26.62 26.77

24.82 24.83 25.80 24.56

TDO3AM ( C) 27.04

Table 7 Simulated habitat parameters in 23 Minnesota lakes that had cisco mortality or habitat observations in 2006

Yes Yes Yes Yes Yes Yes

Yes Yes

Yes Yes Yes Yes

Having lethal daysf Yes

Yes Yes Yes Yes Yes Yes

Yes Yes

Yes Yes Yes Yes

Reported 2006 cisco mortality Yes

700 X. Fang et al.

24.07

21.50

24.46

21.84 13.21 6.43 9.60 7.06 8.99 14.26

Yes

Yes

No

Yes Yes Yes Yes Yes Yes Yes

22.01 16.54 9.31 13.48 8.61 10.86 16.33

24.50

23.06

25.29

3 2 1 1 or 2 1 1 2

3

3

3

19.23 9.14 6.20 8.57 8.60 8.40 11.87

21.57

19.71

21.39

19.57 14.41 8.85 12.25 12.32 10.30 14.40

21.89

20.68

22.10

3 2 1 1 or 2 1 or 2 1 2

3

3

3

23.38 17.27 10.04 14.43 9.31 11.19 17.25

25.78

24.72

27.15

Yes No No No No No No

Yes

Yes

Yes

Yes Yes No No No No No

Yes

Yes

Yes

a

Note: Stratification classification based on Jacobson et al. (2008) b ATDO3FB and ATDO3VB are 31-day average TDO3 for 2006 c Tier classification of refuge lakes based on ATDO3FB and ATDO3VB d AvgTDO3FB and AvgTDO3VB are averaged ATDO3 over the simulation period based on available weather data (e.g., 1962–2012 or 1992–2008), 2006 e Tier classification of refuge lakes based on AvgTDO3FB and AvgTDO3VB f Lethal condition predicted from the constant lethal limits (LT = 22  C and DOlethal = 3 mg/L) and TDO3AM

Little Pine (Crow Wing) Seventh Crow Wing Eighth Crow Wing Long Carlos Big Trout Kabekona Scalp Ten Mile Rose

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Fig. 13 Examples of annual time series of mean daily TDO3 values for the fixed benchmark periods for past climate (1962–2008) and for the future climate scenario MIROC 3.2. Averages (AvgATDO3FB) over the 47-year simulation period are presented as dashed horizontal lines. Weather data from the closest Class I NWS weather station were used for the model simulations (Duluth for White Iron Lake and International Falls for Little Trout Lake)

maximum of daily TDO3 (TDO3AM), monthly (31-day) averages over fixed benchmark periods (ATDO3FB), multiyear averages of the above, etc. Twelve options of TDO3 characteristic values or statistics were calculated and explored (Fang et al. 2010b). Examples of daily TDO3 time series for Elk Lake are given in Fig. 12. The TDO3AM value was 15.5  C in 2004 for Elk Lake (bottom of Fig. 12); the day of occurrence of TDO3AM was DOY = 222 (August 10). The TDO3AM value is projected to increase by 3.8 or 4.3  C in Elk Lake under the future climate CGCM 3.1 and MIROC 3.2 scenarios, respectively (Fig. 12). Two of the 21 cisco study lakes (Fang et al. 2012a, b), White Iron Lake and Little Trout Lake, were selected to illustrate examples of time series of mean daily TDO3 in the 31-day FB periods, ATDO3FB (Fig. 13). Lake geometry ratios for White Iron

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Lake and Little Trout Lake are 4.27 and 1.08 m
0.5, respectively. White Iron Lake is a weakly stratified lake or a relatively shallow, large, and eutrophic lake (maximum depth Hmax = 14.3 m, surface area As = 13.9 km2, Secchi depth SD = 1.4 m). Little Trout Lake (Hmax = 29.0 m and SD = 6.3 m) is a strongly stratified and oligotrophic lake. Values of ATDO3FB ranged from 17.2  C to 22.9  C for White Iron Lake (using fixed benchmark period for unstratified lakes) and from 4.5  C to 6.9  C for Little Trout Lake under past climate conditions. ATDO3FB values in weakly stratified eutrophic White Iron Lake are much larger than ATDO3FB in strongly stratified oligotrophic Little Trout Lake. Under the future climate scenario MIROC 3.2, values of ATDO3FB are projected to range from 20.9  C to 26.2  C for White Iron Lake and from 4.6  C to 7.1  C for Little Trout Lake (Fig. 13). Mean daily TDO3 values over the fixed benchmark (ATDO3FB) period for each simulated year were averaged over the simulation period to obtain the parameter value AvgATDO3FB, which had been chosen as the TDO3 characteristic parameter for the selection of cisco refuge lakes (Fang et al. 2010b, 2012b). The AvgATDO3FB value is one value for the 47-year simulation period (1962–2008) for each lake and each climate scenario, whereas ATDO3FB has one value for each simulated year and 47 values in the simulation period. The AvgATDO3FB values were 20.0  C (standard deviation STD = 1.19  C) for White Iron Lake and 5.4  C (STD = 0.44  C) for Little Trout Lake under past climate conditions (1962–2008). AvgATDO3FB is typically higher for weakly stratified lakes (e.g., White Iron Lake) than for stratified lakes (Little Trout lakes, Fig. 13). Values of AvgATDO3FB for the future climate scenario MIROC 3.2 are projected to be 23.5  C for White Iron Lake and 5.7  C for Little Trout Lake; the projected increases of AvgATDO3FB are 3.5  C and 0.2  C for these two lakes, respectively. Simulated AvgATDO3FB values in 23 Minnesota lakes using available climate data (ranging 17–50 years) from a closest weather station are listed in Table 7. Based on AvgATDO3FB, the tier of the refuge lake is signed for each lake. Results of the refuge lake classification based on ATDO3FB and AvgATDO3FB are almost the same except Straight Lake. Straight Lake has AvgATDO3FB of 16.7  C, which is slightly less than 17  C, and is classified as tier 2 refuge lake based on AvgATDO3FB instead of tier 3 non-refuge lake based on ATDO3FB in the warmer summer of 2006. Overall agreement between refuge lake classification using AvgATDO3FB and observation of cisco mortality and suitable habitat in 2006 is very good. Table 7 also lists the maximum TDO3 in 2006 (TDO3AM) for each lake that was used to determine whether lethal days could occur or not based on the constant lethal limits (LT = 22  C and DOlethal = 3 mg/L). The projection of having lethal days based on TDO3AM in 2006 has almost perfect agreement with 2006 cisco mortality observation except Lake Carlos (Table 7). Simulated AvgATDO3FB values are affected by lake bathymetry and trophic state (Fig. 14) for stratified lakes, but they are less dependent on Secchi depth (trophic status) when a lake is weakly stratified, e.g., GR > 4. This is very similar to the findings by Jacobson et al. (2010) that lake productivity did not significantly affect TDO3 in the unstratified lakes. Simulated AvgATDO3FB values are lower in northern Minnesota (International Falls, Fig. 14) than in north-central and central

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Fig. 14 Contour plots of AvgATDO3FB values under the future climate scenario MIROC 3.2 at International Falls, Minnesota. Contours were derived by interpolation from simulated data points for 30 virtual cisco lakes

Minnesota (Duluth and St. Cloud), but they have similar relationships (patterns) as function of GR and SD at all three locations (Fang et al. 2012b). The AvgATDO3FB values ranged from 6.1  C to 19.6  C under past climate conditions and from 6.3  C to 23.3  C under two future climate scenarios at three weather stations for the 30 virtual cisco lakes (Fang et al. 2012). The projected increases of AvgATDO3FB values from past climate to future scenarios were from 0.0  C to 6.5  C in the 30 virtual lakes, and average increases are projected to be from 2.6  C to 2.9  C (Fang et al. 2012b), which is about 1.0–1.5  C less than projected annual air temperature increases under the climate scenarios MIROC 3.2 and CGCM 3.1 (Table 3), respectively.

Identified Cisco Refuge Lakes in Minnesota The selection of cisco refuge lakes was based on TDO3 parameters projected under the CGCM 3.1 and MIROC 3.2 future climate scenarios using the temperature boundaries derived from 30 simulated lakes (e.g., AvgATDO3FB in Fig. 14). Cisco refuge lakes were also determined by simulations for past climate conditions (1962–2008) because the results would be expected to match actual cisco lakes in Minnesota and would be a useful reference to gage both the reliability of the selection procedure and the impact of climate warming on cisco lakes in Minnesota.

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Fig. 15 Geographic distribution of 620 cisco lakes in Minnesota assigned by shortest distance to one of the three weather stations (International Falls, Duluth, and St. Cloud). The three weather stations (stars) and the grid center points (crosses) of MIROC 3.2 GCM are shown. Background shades identify ecoregions of Minnesota. Cisco lakes are found in two ecoregions: (1) Northern Lakes and Forests and (2) North Central Hardwood Forests

For the 620 cisco lakes, lakes were grouped by the shortest distance to one of the three Class I NWS weather stations in Minnesota; 169, 189, and 262 lakes were associated with International Falls, Duluth, and St. Cloud, respectively (shown by different symbols, Fig. 15).

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Fig. 16 Distribution of tier 1 and tier 2 refuge lakes and tier 3 non-refuge lakes on a plot of Secchi depth versus lake geometry ratio for 169 cisco lakes close to International Falls. The boundary contour lines between tiers 1, 2, and 3 are for AvgATDO3FB = 11  C and 17  C, respectively, and were determined by the fixed benchmark method for the future climate scenario MIROC 3.2

The cisco lakes assigned to International Falls, Duluth, and St. Cloud weather stations were divided into tier 1 and tier 2 refuge lakes and tier 3 non-refuge lakes by the 11  C and 17  C isotherms of AvgATDO3FB simulated using corresponding climate input. The selection of refuge lakes shown in Fig. 16 was based on contour lines of AvgATDO3FB for the fixed benchmark period simulated under the future climate scenario MIROC 3.2. It was projected that 66 (23 + 43 in Fig. 16), 89, and 56 lakes associated with International Falls, Duluth, and St. Cloud, respectively, would be tier 1 plus tier 2 refuge lakes. A total of 211 or 205 lakes of 620 cisco lakes were identified as refuge lakes (tier 1 plus tier 2) under the future climate scenarios MIROC 3.2 and CGCM 3.1, respectively (Fang et al. 2012b). It means that about one third of the 620 lakes that currently have cisco populations are projected to maintain cisco habitat under future projected warmer climate scenarios. Under past climate conditions (1962–2008), 483 lakes or 78 % of the 620 lakes with documented cisco populations were classified as refuge lakes (tier 1 plus tier 2) (Fang et al. 2012b). Mean values of gillnet catch per unit effort (CPUE, number of cisco gillnet) were determined from standard MN DNR netting assessments of cisco in 474 lakes. The CPUE is used as a measure of relative abundance. Mean CPUE values were 5.1, 4.1, and 3.6 for 49 tier 1 (out of total 474 lakes MN DNR studied), 97 tier 2, and 328 tier 3 refuge lakes, respectively. The netting assessment data show that there is a correlation between the tier and relative abundance, i.e., cisco abundance diminishes from tier 1 to tier 3 lakes. The geographic distribution or a division of the 620 Minnesota cisco lakes into 84 tier 1 refuge lakes (large green circles), 127 tier 2 refuge lakes (medium-size pink pentagons), and 409 non-refuge cisco lakes (small black hexagons) is projected for

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Fig. 17 Geographic distribution of tier 1 and tier 2 cisco refuge lakes and tier 3 non-refuge cisco lakes obtained from simulations for the future climate scenario MIROC 3.2. The boundary limits for tier 1 and tier 2 refuge lakes were contour lines of AvgATDO3FB = 11  C and 17  C, respectively. The fixed benchmark method and weather data from principal weather stations in International Falls, Duluth, and St. Cloud, Minnesota, were used

the future climate scenario MIROC 3.2 (Fig. 17). Twenty-three (23) tier 1 and 43 tier 2 cisco refuge lakes (Fig. 16 and Table 8) are associated with International Falls where there is little urban or agricultural development (protected by the Superior National Forest); 39 tier 1 and 50 tier 2 refuge lakes (Table 8) are near Duluth where more development pressure exists and more protection may be necessary; and there

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Table 8 Number (%) of lakes selected as tier 1 and tier 2 refuge lakes and tier 3 non-refuge lakes from cisco lakes partitioned by shortest distance to weather stations in International Falls, Duluth, and St. Cloud, Minnesota. The total number of lakes considered is 620 Closest weather station International Falls

Duluth

St. Cloud

All three stations

Climate scenario Past CGCM 3.1 MIROC 3.2 Past CGCM 3.1 MIROC 3.2 Past CGCM 3.1 MIROC 3.2 Past CGCM 3.1 MIROC 3.2

Tier 1 refuge lakes 49 (8) 23 (4)

Tier 2 refuge lakes 88 (14) 39 (6)

Total number of refuge lakes 137 (22) 62 (10)

Nonrefuge lakes 31 (5) 106 (17)

Total number of lakes 169 (27.2) 169 (27.2)

23 (4)

43 (7)

66 (11)

103 (17)

169 (27.2)

78 (13) 36 (6)

91 (15) 51 (8)

169 (27) 87 (14)

20 (3) 102 (16)

189 (30.5) 189 (30.5)

39 (6)

50 (8)

89 (14)

100 (16)

189 (30.5)

49 (8) 19 (3)

128 (21) 37 (6)

177 (29) 56 (9)

85 (14) 206 (33)

262 (42.3) 262 (42.3)

22 (4)

34 (5)

56 (9)

206 (33)

262 (42.3)

176 (28) 78 (13)

307 (50) 127 (20)

483 (78) 205 (33)

137 (22) 415 (67)

620 (100) 620 (100)

84 (14)

127 (20)

211 (34)

409 (66)

620 (100)

are 22 tier 1 and 34 tier 2 refuge lakes (Table 8) associated with the St. Cloud area and its moderate development pressure. It was found that 84 tier 1 refuge lakes have mean summer Secchi depths from 3.20 to 9.46 m (oligotrophic lakes), lake geometry ratios from 0.47 to 1.83 m
0.5 (strongly stratified lakes), maximum depths from 13.7 to 64.9 m, and surface areas from 0.08 to 21.27 km2 (Fang et al. 2012b). The upper 50 % of the 127 tier 2 refuge cisco lakes have a mean summer Secchi depth greater than 3.89 m, a geometry ratio from 1.56 to 2.66 m
0.5, and a maximum depth greater than 21.3 m (Fang et al. 2012b). On the other hand, the lower 50 % of the 409 tier 3 non-refuge lakes have a mean summer Secchi depth less than 2.9 m, a geometry ratio from 2.72 to 11.89 m
0.5, and a maximum depth less than 13.4 m. Tier 1 plus tier 2 refuge lakes selected under the MIROC 3.2 climate scenario have a Secchi depth greater than 2.3 m, a lake geometry ratio less than 2.7 m, and a maximum depth greater than 11.6 m (Fang et al. 2012b). The geographic distribution of the projected cisco refuge lakes in Minnesota was surprisingly uniform (Fig. 16). Refuge lakes are not exclusively found in the northern and colder region; in fact, many non-refuge lakes are in the north, and a few refuge lakes are near St. Cloud in the south. This is because stratification characteristics related to lake geometry ratio

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and trophic status play an important role in determining cold-water habitat for cisco in addition to climate conditions.

Identification of Cisco Refuge Lakes Using the Variable Benchmark Periods In the third option of the oxythermal habitat modeling for cisco, single variable TDO3 can be determined by interpolation from simulated temperature and DO profiles in a stratified lake such as Elk Lake shown in Fig. 12. To determine refuge cisco lakes, average TDO3 in each simulation year can be quantified in two different periods, i.e., fixed benchmark period (Fang et al. 2012b) and variable benchmark periods (Jiang et al. 2012). Jacobson et al. (2010) determined that the period of greatest oxythermal stress for cold-water fish differed by stratification status of a lake. The 31-day fixed benchmark period of greatest oxythermal stress went from July 13 through August 12 (DOY 194 to DOY 224) for unstratified lakes and from July 28 through August 27 (DOY 209 to DOY 239) for stratified lakes; these benchmark periods explained 65 % of the deviance in TDO3 for the stratified lakes and 68 % for the unstratified lakes (Jacobson et al. 2010). However, fixing the benchmark period in time may introduce a bias for some lakes (Jiang et al. 2012). The highest average daily TDO3 value in any 31-day sliding (variable) benchmark (VB) period, called ATDO3VB (Fig. 3), was calculated for each simulated lake and year. Multiyear average of annual maximum oxythermal stress ATDO3VB, i.e., AveATDO3VB (Fig. 3), was then used to compare with the TDO3 limits of 11  C and 17  C to identify cisco refuge lakes. Figure 18 shows time series of daily TDO3 values in Big Trout Lake under 2006 and future climate scenarios (CGCM 3.1 and MIROC 3.2). The annual maximum daily TDO3 (TDO3AM) was 9.8  C, and the day of its occurrence was at DOY = 283 (October 10) in 2006 in Big Trout Lake. The TDO3AM value is projected to increase by 1.2–1.8  C in Big Trout Lake under the future climate CGCM 3.1 and MIROC 3.2 scenarios, respectively (Fig. 18). Big Trout Lake, with a maximum depth of 39.0 m and a lake geometry ratio of 1.24, is a seasonally stratified (dimictic) lake and is projected to have a smaller increase in TDO3 under the future climate scenarios than White Iron Lake which has a maximum depth of 14.3 m and a geometry ratio of 4.27 and is a weakly stratified lake (Jiang et al. 2012). The variable benchmark periods were determined using sliding window of 31 days to find the highest average daily TDO3 (called ATDO3VB) over any 31-day period in each simulated year. The variable (sliding) 31-day benchmark period retained for each simulation year must not only have the highest mean daily ATDO3VB but must also contain the maximum daily TDO3 in that year (i.e., TDO3AM). Using time series of daily TDO3 in each simulated year, the mean daily TDO3 over each sliding benchmark period of 31 days was calculated, and only the highest mean value in any of the sliding benchmark periods of a year (i.e., ATDO3VB) was retained in the fish habitat program. For example, the beginning date of the VB period in Big Trout Lake was DOY 262 (September 19) in 2006 (Fig. 18),

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Fig. 18 Time series of simulated daily TDO3 for Big Trout Lake in 2006 and for future climate scenarios CGCM 3.1 and MIROC 3.2. The beginning dates of variable benchmark periods of highest mean daily TDO3 in 2006 for Big Trout Lake are DOY 262 (September 19)

which was quite different from the fixed benchmark period (DOYs 209 to 239). Under the future climate scenarios MIROC 3.2 and CGCM 3.1, the beginning dates for the ATDO3VB period are projected (simulated) to be DOYs 273 and 265 in Big Trout Lake, respectively; these dates are not much different from the beginning dates of the ATDO3VB for the past climate conditions. The VB period in White Iron Lake was DOY 199 (July 18) in 2006, which was about 2 months earlier than the VB period in Big Trout Lake. To further illustrate the variability of the VB periods that give the annual ATDO3VB values, the beginning dates of these VB periods for virtual cisco LakeC06 and LakeC08 were determined for past climate (1962–2008) and for the future climate scenario MIROC 3.2 (Jiang et al. 2012). Duluth weather data were used as model simulation input. The beginning dates of these VB periods ranged from DOY 192 to 226 for LakeC06 and from DOY 241 to 271 for LakeC08 under past climate conditions. Average beginning dates were DOY 210 (July 29) for LakeC06 and DOY 253 (September 10) for LakeC08 under past climate conditions (1962–2008). These two small virtual lakes have the same lake geometry but different Secchi depths (Table 2); LakeC06 is an eutrophic lake with SD = 1.2 m, and LakeC08 is an oligotrophic lake with SD = 4.5 m. Isolines that give simulated average beginning dates of the VB periods of greatest oxythermal stress over the 47-year simulation period as a function of Secchi depth and lake geometry ratio were developed and studied (Jiang et al. 2012). Averages of the beginning dates of the VB periods for ATDO3VB ranged from DOY 207 (July 26) to DOY 269 (September 26)

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for the 30 virtual lakes under past climate conditions (1962–2008). It was found that the beginning date of greatest oxythermal stress for cisco can vary considerably from year to year depending on weather, but it can also vary by lake type, i.e., stratification characteristics and trophic status (Jiang et al. 2012). Later dates occur in lakes with lower geometry ratio and higher Secchi depth, i.e., stratified oligotrophic lakes produce oxythermal stress for cisco later in the season than other lakes. The differences between the latest and earliest average beginning dates of the greatest oxythermal stress period for cold-water fish in Minnesota lakes were ranged from 59 to 89 days under past and future climates using weather data from three Class I weather stations. Therefore, variable (sliding) benchmark periods (ATDO3VB) performed better than fixed benchmark periods to quantify the maximum oxythermal stress to cisco. The differences in average beginning dates of VB periods are much smaller (nearly negligible) between projected future climate and past climate than the differences between different lake types and the differences from year to year (Jiang et al. 2012).

Oxythermal Parameters (ATDO3VB and AveATDO3VB) for VB Periods To evaluate oxythermal stress for cisco in different lake types and under different climate scenarios, the AvgATDO3VB was chosen as the TDO3 parameter to identify and select cisco refuge lakes for the study (Fang et al. 2010b). The time series of ATDO3VB for virtual cisco LakeC06 and LakeC08 (Table 2) were analyzed under past climate (1962–2008 at Duluth) and the future climate scenario MIROC 3.2 (Jiang et al. 2012). Over the simulation period (1962–2008), ATDO3VB values ranged from 7.3  C to 12.1  C for LakeC06 and from 11.8  C to 19.9  C for LakeC08 under past climate conditions. Averages of ATDO3VB over the 47-year simulation period (i.e., AvgATDO3VB) were 9.3  C with standard deviation of 1.0  C for LakeC06 and 15.6  C with standard deviation of 1.5  C for LakeC08 under past climate conditions (1962–2008). Values of AvgATDO3VB for the MIROC 3.2 future climate scenario are projected to be 12.6  C for LakeC06 and 20.7  C for LakeC08; the projected increases are 3.3  C and 5.1  C, respectively (Jiang et al. 2012). Figure 19 shows contour plots of AvgATDO3VB under the past climate conditions and the CGCM 3.1 and MIROC 3.2 future climate scenarios using Duluth weather data. Contours were derived by interpolation from simulated AvgATDO3VB data points for the 30 virtual cisco lakes (dots in top frame of Fig. 19). Statistics of AvgATDO3VB values under past climate and future scenarios for three weather stations (International Falls, Duluth, and St. Cloud) were summarized by Jiang et al. (2012). The AvgATDO3VB values ranged from 7.48  C to 19.91  C under past climate conditions and from 8.02  C to 23.28  C under two future climate scenarios for the 30 virtual cisco lakes (Jiang et al. 2012). The projected increases of AvgATDO3VB values from past climate to future scenarios are from 0.30  C to 5.11  C, and average increases are projected to be from 2.79  C to 3.40  C. These increases are crucial, when cisco refuge lakes for future climate scenarios are identified and selected. Values of AvgATDO3VB vary by lake type depending on

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30 regional cisco lakes

PAST (1962 - 2008)

8 3 25 2 23 1 2 9 1

15

11

9

4

13

6 17

21

Secchi Depth (m)

10

2 0

Location: Duluth

CGCM 3.1

8

17

21

11 13

19

7

9

4

15

6

5 27 2

25

23

23

Secchi Depth (m)

10

2 0 MIROC 3.2 8

15

25

13

17

9

23

11

4

29 27

25

6

19

21

Secchi Depth (m)

10

2 0 0.3

0.5

0.8 1.0

2.0

3.0

4.0 5.0 6.0

Geometry Ratio (m –0.5)

Fig. 19 Contour plots of averages of mean TDO3 over variable benchmark periods (AvgATDO3VB) under past (1962–2008), CGCM 3.1, and MIROC 3.2 future climate scenarios. Duluth weather data was used for past climate condition. Contours were derived by interpolation from simulated data points for 30 virtual lakes

stratification characteristics and trophic status (Fig. 19); stratified oligotrophic lakes produce lower AvgATDO3VB values or lower oxythermal stress for cisco.

Cisco Refuge Lakes in Minnesota Contour lines of 11  C and 17  C in the contour plots of AvgTDO3VB in Fig. 19 were used to identify cisco refuge lakes in the database of 620 Minnesota cisco lakes. The final selection of cisco refuge lakes was based on AvgTDO3VB projected under

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Table 9 Number (%) of lakes selected as tier 1 and tier 2 refuge lakes and tier 3 non-refuge lakes from cisco lakes grouped by latitude (Fig. 1). Weather input data from three principal weather stations (International Falls, Duluth, and St. Cloud) are each assigned to a different range of latitudes for use in the simulations (Jiang et al. 2012) Weather station by latitude Northern (International Falls)

Mid-latitude (Duluth)

Southern (St. Cloud)

All three latitudes

Climate scenario Past CGCM 3.1 MIROC 3.2 Past CGCM 3.1 MIROC 3.2 Past CGCM 3.1 MIROC 3.2 Past CGCM 3.1 MIROC 3.2

Tier 1 refuge lakes 41 (7) 24 (4)

Tier 2 refuge lakes 96 (15) 43 (7)

Total number of refuge lakes 137 (22) 67 (11)

Tier 3 non-refuge lakes 29 (5) 99 (16)

Total number of lakes 166 (27) 166 (27)

19 (3)

43 (7)

62 (10)

104 (17)

166 (27)

52 (8) 10 (2)

285 (46) 83 (13)

337 (54) 93 (15)

62 (10) 306 (49)

399 (64) 399 (64)

10 (2)

84 (14)

94 (15)

305 (49)

399 (64)

1 (X2-value) 0.00000*** % Correct prediction 74.46 No. of observations 1,711 Base category: no adaptation

Reactive measures 0.9650***

Proactive measures 0.7882***

0.0405

0.0369

0.1049**

0.0976**

0.0264

0.0214

0.1586*** 0.0981***

0.1496*** 0.0992***

0.0187 0.0185 0.1139***

0.0269 0.0279 0.1037***

0.0120* 0.0168*** 0.0020 0.0452

0.0085 0.0157*** 0.0010 0.0513

0.0600**

0.0638**

0.0597*** 0.0392 0.0031 0.0014 0.2183*** 0.3696*** 0.5946***

0.0523*** 0.0252 0.0017 0.0009 0.2400*** 0.2960*** 0.5312***

Cf: Francisco et al. (2011) Note: ***, **, * = significant at 1 %, 5 % and 10 % level, respectively a 1 = yes, 0 = otherwise b 1 = more severe than what was experienced, 0 = otherwise

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livelihood from extreme climate change disasters. In fact, everyone should also be thinking of mitigation because while it is true that our generation is already committed to climate change, there are efforts that can be done to slow down climate change for future generations.

Coastal Communities’ Vulnerability and Adaptation Practices Coastal areas in Asia face “an increasing range of stresses and shocks,” which are intensified by climate change (Cruz et al. 2007). This is supported by a 170-country assessment by Harmeling (2011) on the impacts of extreme weather-related events such as storms, flood, and extreme temperatures. The assessment showed six Asian countries to be among the most vulnerable, namely, Bangladesh (rank 1), Myanmar (rank 2), Vietnam (rank 5), the Philippines (rank 7), Mongolia (rank 9), and Tajikistan (rank 10). That coastal communities are highly vulnerable to climate change is widely recognized (IPCC 2007, 2014; ADB 2009, 2014). Their vulnerability comes from the rising sea level that accompanies the overall warming of temperature as well as the storm surges that accompanies the increased frequency and intensity of typhoons. Low physical and financial capacity for disaster preparedness also contributes, to some extent, to these areas’ vulnerability to extreme climate events (Ward and Shively 2011; Adger 1999); wealthier countries typically suffer lower social losses than poorer countries (Kahn 2005). The threat from sea level rise has been in the radar of climate discussions during the last few years, but the threat from storm surges became real only with the Philippines’ experience during super Typhoon Haiyan in November 2013. In just less than an hour, the 13 ft storm surges with strong current experienced during Haiyan left a death toll of 6,300 with 1,785 left unaccounted for. A few months after the super typhoon, more than 52,000 families are still living in tents in the danger zone in Tacloban City as the local government struggled to find a 100-hectare relocation site for these people (Lowe 2014; Stevens 2014). Given the critical situation that coastal communities face as a result of the changing climate, EEPSEA also supported several research projects on CCA in coastal areas. This effort was done in collaboration with the WorldFish Philippine Country Office (WF-PCO) and came in two sets of projects. The first project focused on understanding the adaptation practices and assessing the vulnerability of selected coastal communities in the Philippines, Vietnam, and Indonesia. The various studies part of this first project looked into the impacts and adaptation practices used in dealing with typhoons/flooding, coastal erosion, and saltwater intrusion at the household, community, and local government levels. Several planned adaptation options were then evaluated using cost-effectiveness analysis (CEA). The second project, which is still ongoing, looks into intra-household impacts of climate change, how the various members are affected, and how they can be engaged to generate a stronger household adaptation plan. Table 11 shows the

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Table 11 Summary of climate change hazards, impacts, and compounding issues in the study sites Batangas, Philippines Hazards Sea level rise Confounding environmental issues Coastal erosion Sand quarrying Illegal charcoal making from mangroves Illegal fishing using blasting and cyanide Fishing with fine mesh net and superlight Impacts Damage to property (hotels, resort, houses, and boat) during typhoon Coral bleaching and increasing number of crown of thorns Impacts to livelihood and tourism in vulnerable coastal areas House relocation due to coastal erosion Mangrove areas, coral reefs, marine protected areas, and beaches now at risk

Palawan, Philippines Hazards More frequent and intense typhoons Floods Confounding environmental issues Mangrove cutting for charcoal, housing, and fencing materials Weak enforcement of coastal management laws Illegal fishing Burning of some upland areas for rice farming (kaingin) Expansion of private beachfront property Inadequate protection of the fish sanctuary Impacts Change in the fish species caught More houses and boats destroyed by typhoons Coral bleaching Decreased land area due to coastal erosion Loss of traditionally gleaned shells along the coastline Seawater is hotter during the 3–4 pm gleaning activity Bangus fry collected for the past 5–6 years declined significantly

Jakarta, Indonesia

Ben Tre, Vietnam

Hazards Coastal erosion and seawater intrusion Coastal or tidal flooding Sea level rise Confounding environmental issues Loss of most of mangrove and coastal ecosystems Large population Pollution that affects water quality, soil erosion Absence of strong fisheries policy and overlapping jurisdictions Impacts Land subsidence, coastal inundation, and coastal abrasion Seawater intrusion has reached the National Monument Increased turbidity of water affecting photosynthesis Decreasing water quality Change in the pattern of flow, bathymetry, and coastline Sediment accumulation in the entrance of harbor lanes increases dredging costs

Hazards More frequent and intense typhoons Destructive flood and tidal surges from 1996 to 2008 Confounding environmental issues Sand mining Salinity intrusion Heavy traffic of sea vessels Impacts Loss of shelter and livelihood from typhoons Land encroachment Saltwater intrusion during the dry season leads to a shortage of freshwater for domestic and production uses

Cf: Perez et al. (2013), shown as Table 3 in the original study

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climate change impacts considered in the different study sites and the compounding environmental stresses that those communities face in addition to climate change. In particular, most communities had to deal with coastal erosion, sand quarrying, deforestation of forests and mangroves, and rampant illegal fishing, all of which could compound the impacts of climate change. What Table 11 further tells us is that efforts to address the development needs of these coastal communities need to be holistic since theirs is a complex environment that is not necessarily affected only by their coastal location. Instead, it is important to note that coastal communities live in an environment that traverses several ecosystems, some of which are linked to one another. They are also affected by an economic and governance system that influences their livelihood and hazard vulnerability, be it climate change or other hazards. Moreover, they are also assisted by the government and other development agencies in how they cope with climate change impacts. These coping measures are further discussed in the next section.

Adaptation Practices in Selected Coastal Villages In the Philippines, it is noticeable that all local governments have formed a municipal disaster risk management council (MDRMC) that is funded using 5 % of the 20 % Development Fund (Table 12). This fund is used to provide disaster victims with food, particularly those who stay in evacuation centers during disaster events. The fund is also used to undertake information, education, and communication (IEC) campaigns on disaster risk reduction (DRR). In addition, local governments conduct dredging and river widening activities to reduce the flooding threat as well as to rehabilitate mangroves, which are now widely believed to provide protection from coastal erosion and flooding. The same efforts are reported in the Indonesia and Vietnam study sites. In addition, Vietnam reports of technological support to farmers in the form of drought/flood-tolerant varieties and modified farming systems to suit the new climate (Table 12). Vietnam is also doing more structural measures, in the form of dike and pond system, to support livelihood. Indeed, as noted by Francisco (2008), there are a lot that countries in the region could learn from Vietnam on how they have been living with flooding. Adaptation practices at the community and household levels were also obtained during the study. It is worth noting that most local government initiatives involved the community. Community folk participated in mangrove replanting, dike repairs and construction, and in other activities to improve their environment and help prepare for disasters. At the household level, adaptation practices included relocating and strengthening of houses, putting up defense structures like cement dikes, engaging in alternative livelihood activities to enhance financial security, and shifting fishing/farming practices to suit new and changed environments, particularly in Vietnam.

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Table 12 CCA and disaster mitigation strategies in the study sites, 2012 Government-led initiatives San Juan, Batangas, Philippines Organized MDRMC, which is financed by 5 % of the 20 % Development Fund Gave out cash support (e.g., PhP 1,000–2,000 to affected fisher folk) River dredging and widening to prevent flooding Regular IEC campaigns Maintenance of Marine Protected Areas, mangrove replanting, and engagement in “Billions of Trees Project” in 400 ha of upland, lowland, and beach side areas Honda Bay, Palawan, Philippines Passed an ordinance to conserve, protect, and restore (CPR) the Puerto Princesa City’s sources of life Flood control project implementation and construction of breakwaters Mangrove reforestation Established a barangay disaster risk management council (BDRMC) with fund allocation

Jakarta Bay, Indonesia Implemented measures related to watershed management and coastal and marine resources protection Conducted capacity building and community empowerment activities to implement watershed and marine and coastal resources management Promoted policies that integrate environmental concerns in economic development Encouraged institutional strengthening for river basin management and coastal and marine bay management

Community-based initiatives

Autonomous household adaptation practices

Aquaculture and fish processing projects Mangrove replanting Crown-of-thorns starfish removal, as spearheaded by resort owners Typhoon warning system improvement and preparation for emergency evacuation Cleanup of drainage and flood control structures

Relocate or strengthen house structures Plant and sell mangrove seedlings Temporarily remove light structures in beach areas Join savings/credit cooperative Modify planting schedules

Establishment/ maintenance of fish sanctuary Participation in riverbank bioengineering projects (e.g., sea dike construction, mangrove reforestation) to reduce erosion and siltation Establishment of community-based early warning system and provision of temporary evacuation center

Use of indigenous materials to strengthen housing structures Use of cement and rocks to build dikes

Community involvement in various initiatives to protect watershed and coastal and marine resources Construction of permanent embankments Drainage improvement and river dredging Mangrove planting

Clean the beach fronting their houses

(continued)

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Table 12 (continued) Government-led initiatives Ben Tre Province, Vietnam Coastal zone management: road construction, dike upgrading, and mangrove protection Freshwater resources management“Acknowledgements” section has been deleted as it is not a part of the contribution structure. investment on irrigation systems for water storage, construction of dikes to prevent saltwater intrusion, and watershed management to protect water sources Supported agricultural adaptation: switch to salt-tolerant crops, investment on drought-tolerant crops, improvement of early warning system Supported CCA for aquaculture and capture fisheries: technological innovation in pond construction for improved water storage, introduction of fish-rice model in saline areas, and research to identify rich fishing grounds Information and awareness campaign on how to prepare for climate change

Community-based initiatives

Autonomous household adaptation practices

Mangrove forest protection Ensuring supply of freshwater for agriculture, aquaculture, and domestic needs (e.g., storage structure construction and provision of containers to harvest rainwater) Relocation of at-risk houses Participation in sea dike construction

Harvest rainwater Switch from black tiger shrimp to whiteleg shrimp to adapt to saline water Change cultivation schedules to avoid saltwater intrusion Use of sandbags to build dikes around the farm to prevent saltwater intrusion and seawater inflow

Source: Perez et al. (2013)

Cost-Effectiveness Analysis of Selected Adaptation Options The results of a CEA of selected adaptation options, which were identified by LGUs as priority projects, are presented in Tables 13, 14, and 15. For the analysis, the researchers selected a common denominator, such as cost per unit of area protected or per household saved or protected. However, this is a very crude comparison as multiple types of benefits may be delivered by each of the adaptation options. For instance, a mangrove protection project will produce other types of benefits than what can be “produced” by installing a dike to protect a given area. As such, the comparison should be interpreted with caution. The last column in each of the next three tables provides some additional information regarding the interpretation of results. For San Juan, Batangas, in the Philippines, sea wall construction and mangrove reforestation were compared, and results showed that it is a lot cheaper to prevent a kilometer of shoreline erosion using mangrove reforestation (Table 13). In addition,

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Table 13 Cost-effectiveness analysis results for San Juan, Batangas, Philippines

Objective Protect the coastline from erosion

Planned adaptation strategies Sea wall construction

Mangrove reforestation

Increase the number of households safe from typhoon/flooding

Zoning provisions and relocation

CE ratio USD 0.16 M/ linear km of erosion prevented USD 0.01 M/ linear km of erosion prevented USD 0.07 M/ HH saved

Notes Mangrove reforestation is not only more cost-effective but also offers other co-benefits like additional sources of income and marine biodiversity preservation

The changing zoning provisions need to be accompanied by the removal of communities from areas they currently occupy, a very costly and socially unattractive option

Source:

this option produces other forms of benefits from the mangrove resources, both in terms of provisioning and regulating functions; if valued, these benefits will make this measure even more attractive. The use of early warning system and the provision of evacuation shelter were also compared with improvement of zoning regulation and relocation. As expected, the latter was a lot more costly to implement as a way of protecting households from the negative impacts of flooding and/or typhoons. The early warning system is being put in place in many parts of the country. A similar analysis was carried out for the Palawan, Philippines, study site (Babuyan in Honda Bay). Several options were evaluated: to protect households from storm surges (i.e., breakwater construction, dike construction, and mangrove reforestation), to protect them from inland flooding (i.e., upland reforestation, IEC with provision of temporary evacuation shelter, and household relocation), and to protect production areas (i.e., dike construction, riverbank rehabilitation, and river dredging). The results show the superiority of mangrove reforestation over structural measures, the cost-effectiveness of river dredging and riverbank rehabilitation, and support for an effective early warning system supplemented by IEC as part of DRR strategies (Table 14). For the study sites in Jakarta Bay, Indonesia, several options with varying objectives were compared as shown in Table 15. River dredging1 was found to be more cost-effective than the construction of new canals or embankment and even

1

Note: The study did not indicate how often this has to be done.

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Table 14 Cost-effectiveness analysis for Honda Bay, Palawan, Philippines Objectives Protect households from storm surges and loss of property and minimize sand erosion

Planned adaptation strategies Breakwater construction Dike/levee construction Mangrove reforestation

Prevent river overflow and minimize siltation, which damage coconut plantations and fishponds

Riverbank rehabilitation using vetiver grass Riverbank rehabilitation using vetiver grass combined with mechanical method Dike construction

River dredging

Protect households from inland flooding

Upland reforestation IEC/early warning system establishment and provision of temporary evacuation area Household relocation

CE ratio USD 0.276 M/ HH USD 0.032 M/ HH USD 0.019 M/ HH USD 0.004 M/ ha USD 0.034 M/ ha

USD 0.032 M/ ha USD 0.002 M/ ha USD 926/HH USD 120/HH

Notes Mangrove reforestation is cost-effective in protecting households and properties and in minimizing sand erosion where mangroves are seen to thrive well

The discussion on the planned options and costeffectiveness (CE) ratios focused on prioritizing riverbed dredging together with riverbank rehabilitation using vetiver grass alone

IEC is cost-effective but success depends on the maturity of the residents to react accordingly

USD 2,234/ HH

Source:

mangrove rehabilitation. The high cost of mangrove rehabilitation is attributed to the need to purchase land from private landowners who already have rights over the areas previously occupied by mangroves. However, mangrove restoration is likely to make an even bigger contribution to the local economy in the face of climate change and the resulting increase in typhoon frequency and intensity (Tuan and Duc 2013). Mclvor et al. (2012) suggested that mangroves can potentially play a significant role in coastal defense and DRR. Overall, one can see that the CEA results tend to favor mangrove reforestation over structural measures and river dredging in order to increase flood control function. The scientific basis for this claim was found in the study by Mazda

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Table 15 Cost-effectiveness analysis for Jakarta, Indonesia Planned adaptation strategies Construction of East flood canal Dredging of Sunter river

Site Rorotan

Objectives Reduce the no. of HH affected by flooding

Marunda

Reduce the no. of HH affected by flooding and coastal flooding

Construction of permanent embankment Mangrove rehabilitation

Kalibaru

Reduce the no. of HH affected by flooding, coastal flooding, and saltwater intrusion

Road elevation

Kamal Muara

Reduce the no. of HH affected by flooding and coastal flooding

Dredging of Pesanggrahan river Mangrove rehabilitation

Muara Angke

Reduce the no. of HH affected by flooding and coastal flooding

Road elevation

Dredging of Cakung river

Mangrove rehabilitation

CE ratio USD 307 M/ HH USD 0.695 M/ HH USD 2.5 M/ HH USD 13.37/ HH USD 2.64 M/ HH USD 2.09 M/ HH USD 2.09 M/ HH USD 2.43 M/ HH

USD 0.311 M/ HH USD 2.07 M/ HH

Notes The cost-effective option suitable in this area is the dredging of Sunter river

The cost-effective option is planting mangroves

The more cost-effective solution is to dredge Cakung river

The more cost-effective solution is to dredge Pesanggrahan river. A large portion of the cost of planting mangroves is the value of coastal land owned by private individuals or groups The more cost-effective solution is to elevate roads. Like in Kamal Muara, a large portion of the cost of planting mangroves is the value of privately-owned coastal land

Source: Agus et al. (2013)

et al. (2006) and cited in Andrade et al. (2010). Moreover, the early warning system supplemented by evacuation shelter provision was found to be quite cost-effective compared with the other options evaluated. This finding is consistent with other studies’ findings which validate the use of an early warning system as one of the most cost-effective measures to reduce damage cost (Hallegatte 2012; Linham and Nicholls 2010). The next section describes efforts to link research with local government adaptation planning based on the experience from two cross-country projects implemented from 2011 to 2013.

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Working with Local Governments in Adaptation Planning Climate change will affect everyone. Differences on the impacts felt will depend on the locality’s hazard exposure, the people’s adaptive capacity, and the LGU’s level of preparedness. This means that adaptation planning has to be locale specific to suit the conditions and capability of different local governments. In order to bring research to the level where it can have impact, EEPSEA supported two multi-country projects to engage local government planners in adaptation planning in 2011–2013.

CBMS-EEPSEA Project The main funding source of EEPSEA, the International Development Research Centre (IDRC), also supports a Community-Based Monitoring System (CBMS), a global project with presence in the Philippines, Vietnam, and Indonesia. The CBMS-EEPSEA partnership was carried out to pilot test the application of the EEPSEA framework on climate change vulnerability assessment and mapping at the local level using CBMS data and supplemented by data from other government sources. There are two outcomes that were expected from this initiative: (1) LGU level capacity building on understanding how to assess climate change vulnerability and (2) identification of adaptation strategies based on research done on this topic. The study sites included (1) Vietnam, Kim Son district of Ninh Binh province in the North, Nghia Lo municipal of Yen Bai province in the North Mountainous Region, and Tam Ky town of Quang Nam province in the Central Region; (2) Indonesia, two villages in the province of Kota Pekalongan (Pasirsari village, Kecamatan Pekalongan Barat, and Panjang Wetan village, Kecamatan Pekalongan Utara); and (3) the Philippines, municipality of Carmona in Cavite province and Marinduque province. Experience in pilot testing the climate change vulnerability framework shows that its main advantage is its simplicity, which allows local government decisionmakers to understand what factors they should consider when doing such an assessment. The ability to map information that allows government officials to immediately see how they fare relative to their neighbors was also found attractive. Experience in using vulnerability mapping to aid in identifying suitable adaptation strategies varies across the participating country teams. The Philippine teams managed to bring the discussion to the point that they were able to identify the adaptation practices that need to be strengthened and those that need to be implemented as listed in Table 16 (Reyes 2012). The Vietnamese team shares that the process helped them understand the location and the sources of vulnerability but that these were not sufficient to assess what the community needs in order to adapt to the changing climate. In a way, identifying the adaptation practices that the community or the local government could undertake is indeed only the first step. Given limited resources

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Table 16 Adaptation strategies identified in the Philippine CBMS-EEPSEA project Study site Carmona, Cavite

Marinduque province

Adaptation strategies identified Strengthen current efforts in: river cleanup, solid waste management, and de-clogging of canals and waterways Conduct more orientations on DRR management, enhance DRR communication capability and early warning system with new equipment and strengthen flood forecasting, and upgrade evacuation and health facilities Install diversion canals, dams, and reservoirs to protect industrial and agricultural lands Review/update and enhance the provincial DRR management plan Strengthen the rehabilitation of watershed areas and reforestation projects through the National Greening Project (NGP), Bamboo Greenbelt Project, and other forest rehabilitation projects Build LGU and community capability and capacity on the various facets of DRR (i.e., warning, search and rescue, emergency relief, logistics and supply, communication and information management, emergency operation management, evacuation planning and management, health emergency education, and post disaster management) Establish/construct evacuation centers in safe areas and improve and construct roads and feeder roads, drainage facilities, footbridges, spillways, and floodways in priority areas Produce and disseminate natural hazard and geographic info system susceptibility maps and IEC materials and install Integrated Warning/ Communication and Response System Install automatic weather station in major critical areas such as Boac and Sta. Cruz

Source: Reyes (2012)

and varying capacity, an assessment of the economics of these measures and their technical and social acceptability must be carried out as well; these are not within the scope of the CBMS-EEPSEA project. In the case of the Indonesian team, the adaptation policies and programs of the national and local governments were discussed and analyzed as a separate activity from the vulnerability mapping. The analysis revealed that current adaptation planning is largely addressing the hazard component of vulnerability, which they pointed out is a major limitation on account of the findings of the project. In particular, the CBMS-EEPSEA project showed clearly that adaptive capacity and sensitivity are equally important sources of vulnerability and should therefore be addressed as well. All the project country teams recommended that similar efforts be done to assist other LGUs to better understand their vulnerability situation and to help them identify adaptation practices. To help evaluate the economic viability and acceptability of these identified strategies would require a longer time and a different set of skills, as demonstrated in EEPSEA’s project with IDRC’s Climate Change and Water program, which is discussed in the next section.

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CCW-EEPSEA Project In February 2011, EEPSEA and the IDRC program on climate change and water (CCW) awarded three 3-year research grants to institutions based in the Philippines, Vietnam, and Cambodia. The project, entitled “Building Capacity to Adapt to Climate Change in Southeast Asia,” aimed to enhance the capacity of university researchers, provincial officials, LGU representatives, and other mass organizations in selected SEA countries by equipping them with knowledge on how to assess climate change causes and impacts and how to undertake an economic analysis of selected adaptation options. Specifically, the collaborating partners were expected to undertake vulnerability analysis, prioritize adaptation options, and develop sound and feasible project proposals for funding. Based on the highly vulnerable sites identified in Yusuf and Francisco (2009), the project selected the following study sites: Kampong Speu in Cambodia (highly vulnerable to drought), Laguna in the Philippines (highly vulnerable to flooding), and Thua Thien Hue in Vietnam (exposed to flooding and typhoons). The project adopts a multidisciplinary and participatory approach. Each country research team is composed of researchers with backgrounds in natural science, sociology, and economics. Their mandate was to work with their study site’s local government officials in undertaking vulnerability assessment, in identifying and evaluating adaptation projects, and in developing the CCA proposal/plan for submission to donor agencies. During project implementation, the research team implemented a series of training courses, joint field visits, and dialogues with community members. The key skills that the training courses addressed are vulnerability assessment and mapping following the framework used in Yusuf and Francisco (2009), evaluation of climate change impacts, economic analysis of adaptation options, and proposal development for adaptation funding support. Interestingly, many of the team members are now being involved in providing consultancy services on these areas in their own countries – a sure offshoot of their engagement in this project. The engagement of the local government people in the project had brought about several benefits, namely, (1) greater awareness on climate change risks; (2) generation of risk maps, which were used to develop agricultural production plans for three subregions in Thua Thien Hue; (3) integration of climate risks in the socioeconomic development plan; and (4) improved knowledge on how to conduct vulnerability assessment and economic analysis of adaptation options as well as proposal development. They were also able to network with government people from other countries as the project hosted sharing and training meetings as part of the capacity building activities designed for the collaborators. A post project survey was implemented to assess changes in knowledge and skills of the people involved in the project. All team members across the three countries demonstrated improved understanding of the climate change problem and a higher level of knowledge on the various tools that were used by the team. The

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biggest improvement was noted among the research team members from Cambodia. In terms of concrete actions taken up, local government partners in Thua Thien Hue have developed agricultural production plans based on the results of the climate change vulnerability map that was prepared through the project. The Thua Thien Hue LGU staff developed proposals to raise funds for the construction of local CCA measures, particularly better use of water in rice production. The LGU partners in Laguna, Philippines, now have better appreciation and knowledge on how to implement vulnerability assessment and mapping and how to package proposals, but they acknowledged that they may not be able to carry these out on their own. Their reservation regarding their independent implementation/ conduct of such activities is not due to perceived capacity constraint but more as a result of their busy schedules as they are responsible for multiple projects at the provincial office. The project research findings also affirmed the findings of previous studies. First, that vulnerability to climate change is quite high and that it varies across areas. In Thua Thien Hue, Vietnam, households living in delta communes had higher adaptive capacity compared with households living in coastal and upland communes. The social capital was found to be generally high but limited infrastructure support, access to technology, and lower financial resources contributed to lower adaptive capacity for many households. In Laguna, Philippines, higher vulnerability was noted among coastal communities compared with agriculture-based households. Interestingly, it was found that a big proportion of the vulnerable households are not knowledgeable about the threats posed by climate change. The most vulnerable households are often the most poor as well and so it probably makes no difference where their poverty stresses are coming from. In terms of experience with climate-related hazards, majority identified typhoons and flooding as the hazards posing the greatest threat based on experienced damages over the years, most intensely in the last few years. The biggest losses/damages come in the form of damages to houses and furniture. About 16 % of the households regularly experience evacuation, and a tenth of those interviewed had experienced permanent relocation as supported by the local government of Sta. Cruz, Laguna. The important role played by social capital, particularly those involving women’s organizations, in accessing DRR programs was also highlighted in the Philippine study site. The study site in Kampong Speu, Cambodia, is predominantly a farming community and is threatened mostly by drought, with flash floods occurring in certain areas only. Vulnerability was found highest in the eastern and central western regions of the province on account of the highest concentration of vulnerable communes in these areas. Farming households in lowland areas have been coping with drought conditions by shifting to short-duration crop varieties. Those in mountainous areas were found less willing to shift to new varieties, but they generally have more resources to cope with the impacts of a changing climate. For both sites, other adaptation strategies included: constructing and renovating canals, selling household assets, and migrating to

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work outside the village (e.g., work in a garment factory, as household help, and in construction). The teams also packaged adaptation proposals, which the LGUs can then submit for funding support: (1) a technology-based flood early warning system for the Sta. Cruz River Watershed in Laguna, Philippines; (2) improved irrigation system for Kampong Speu, Cambodia; and (3) upgrading of the An Xuan tributary banks and river dredging in Thua Thien Hue, Vietnam. These projects were found to be the most economically efficient option for the three sites based on the economic analysis of several alternative projects.

Lessons in Action Research: Working with Local Government Units The researchers of the two projects considered working with the local governments both rewarding and productive. They are able to immediately share and discuss with local government planners their research results as the study progresses. The local government collaborators were involved more deeply in data analysis and presentation as they were engaged all throughout the project. Hence, there is joint ownership of the research reports, which was linked to adaptation planning more directly, unlike in the traditional research process. More importantly, there is improvement in the knowledge and skills of not only the researchers but also of their collaborating local government partners. All these are expected to result in a better understanding of the problem and a higher capacity to assess, evaluate, and decide on how it can be addressed. Nonetheless, it must be mentioned that the heavy workload of the local government partners prevented them from being more engaged in the research process. They are only engaged in the project part time with DRR/climate change being only one of their many other responsibilities in their capacity as local government staff. The same can be said of the university researchers who are only working part time with the research. They meet and work with their collaborators only during meetings or major activities. Perhaps, the project duration for the CCW-EEPSEA project is too long (i.e., 3 years), and that of the CBMS-EEPSEA project (i.e., 1 year) is too short. The CCW-EEPSEA project differs from the CBMS-EEPSEA project in that it is longer and thus has more resources. Its idea is to fully understand the various aspects of vulnerability by forming three teams (i.e., economic, social, and mapping teams) and to analyze and characterize who are the most vulnerable sectors in the locality. The team is comprised of university researchers, LGU representatives, and representatives from NGOs working in the community. On the second year, the potential and existing adaptation practices were identified and evaluated. An economic analysis of those options was carried out. In the last year, the team assisted the LGU in developing a proposal to seek support from donor organizations to fund their adaptation plans. This 3-year project completely contrasts with the 1-year duration of the CBMS-EEPSEA project, both in terms of depth of analysis and resources.

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From a program point of view, it will appear that having 2 years for both projects will be a Pareto improvement. The CBMS-EEPSEA project would have more time to expand its adaptation analysis. On the other hand, 3 years may have been too long for the CCW-EEPSEA team as the members managed to do multiple assignments that took them away from a more concerted, focused analysis of the problem on hand. Somewhere in between these two project durations could result in a more intensive interaction between researchers and their local government partners as well as richer data collection and analysis.

Lessons from EEPSEA-Funded Climate Change Adaptation Research in Southeast Asia: Future Directions Climate change is here to stay and is likely to get worse given that serious commitment to reduce greenhouse gas (GHG) emission will only happen starting 2020 if, and only if, the 2015 International Agreement with significant GHG reduction commitment will be signed by all countries in Paris. The prospect of having such a stronger agreement in place does not look good given how previous talks have failed on this front. We can only hope that our global leaders will come to their senses and put in place serious efforts to reduce GHG emission to slow down climate change. On the positive side, it is good to hear about various countries’ efforts to move toward a green economy by using more efficient technologies, building high energy savings, and investing on ecosystem reforestation or protection. However, these efforts cannot be done at a microscale – we need government commitment to pass stronger measures to reduce carbon emission. Surely, a carbon tax supplemented by programs to reduce impacts on the poor is a step in the right direction but is opposed in many countries because of strong lobbying pressure by those sectors who will be hit by this measure. With the exception of climate deniers, everyone agrees that climate change poses a real threat to people, with some countries facing (and in fact, already experiencing) more serious challenges than others and the poor being more vulnerable to it. The various research supported by EEPSEA on CCA in SEA proved that the impact of extreme climate events on those affected is huge with an extreme event costing households up to 44 % of their annual household income. Depending on the number of extreme climate events (which unfortunately is expected to be more frequent and intense in the future), future damage can be even bigger and will most likely drive vulnerable households to extreme poverty. Despite the severity of the situation, adaptation actions by SEA households are generally very crude and mostly in the form of reactive measures (e.g., strengthening housing units, using sandbags during flooding, storing of food, evacuation) rather than preventive ones (e.g., relocation, building multistorey and stronger housing units). Largely, this is explained by the limited resources available to most vulnerable households for investment in stronger measures. Moreover, in

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many cases, there is still the hope that extreme events will not occur that often in the future or that they are used to this condition already and will be able to manage. This complacency is now being addressed by enhanced IEC campaigns that most governments are launching toward DRR/climate change. A lot of this effort needs to be done more widely and intensely, but stronger adaptation investments need to be made if adaptation capacity or resilience is to be enhanced in areas most vulnerable to climate change. The financial resources available to these communities are undoubtedly small in relation to needs and efforts must be done to provide more resources and/or use more wisely the limited resources available. Hopefully, developing countries in the region will be able to access some of the adaptation funds available, and the economic analysis done on some of these measures was found to be economically viable. Local governments need support in adaptation planning. The two action research projects carried out with funding support from EEPSEA and the collaborating organizations (IDRC’s CBMS and CCW) showed that local government officials are receptive to such research collaborations and are very much willing to learn science-based planning. With more resources provided to free up some of their time during the conduct of such action research projects, a higher-level and more fruitful engagement can perhaps be expected from them. In addition, our experience shows that there are existing programs (e.g., CBMS, WorldFish, etc.) in most communities that researchers can tie up with so that synergy can be achieved in getting more resources and technical expertise in the action research. Finally, given the urgency of the situation and the relatively higher level of research information now available from different organizations working in SEA, it is high time to move toward research that feeds directly into concrete actions, to not simply come up with plans and proposals but with adaptation projects/measures that can be readily implemented on the ground. This calls for action research with some funding available to pilot test adaptation projects that will be evaluated as part of the research. This is not going to be easy as there seems to be a dichotomy between research and development. In most cases, research organizations just do research while development organizations focus on development projects. This is so unfortunate in this instance since concrete actions supported by science are what we need to help prepare local governments, communities, and households to better adapt to climate change. Research alone oftentimes translates to just pure talk; action research is walking the talk.

References ADB (Asian Development Bank) (2009) The economics of climate change in Southeast Asia: a regional review. Asian Development Bank, Manila ADB (Asian Development Bank) (2014) Climate change and rural communities in the greater Mekong Subregion: a framework for assessing vulnerability and adaptation options. Asian Development Bank, Bangkok Adger WN (1999) Social vulnerability to climate change and extremes in coastal Vietnam. World Dev 27(2):249–269

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Impact of Climate Change, Adaptation, and Potential Mitigation to Vietnam Agriculture Trinh Van Mai and Jenny Lovell

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climate Change in Vietnam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Extreme Events in Vietnam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climate Change and Sea Level Rise Scenarios in Vietnam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vietnam Agricultural Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Impact of Climate Change on Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Agriculture Vulnerability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Damages in Agriculture Production Associated with Climate Change . . . . . . . . . . . . . . . . . . . . Quantify the Impacts Through Calculating Indexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climate Change Adaptation for Crop Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Experiences in Climate Change Adaptation in Vietnam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climate Change Adaptation Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climate Change Mitigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . GHGs Emission in Crop Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Identify and Analyze Technologies to Reduce GHG Emission in Agriculture . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

900 900 901 902 902 903 903 903 910 911 911 913 916 916 918 922 922

Abstract

The Institute for Agricultural Environment of Vietnam conducted a research to study climate change impacts on agriculture, develop climate change adaptation measures, and identify mitigation options. Climate change impacts were

M. Van Trinh (*) Institute for Agricultural Environment, Vietnam Academy of Agricultural Sciences, Phu do, South Tu Liem, Hanoi, Vietnam e-mail: [email protected] J. Lovell Environmental Studies Department, University of California Santa Cruz, Santa Cruz, CA, USA e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_87

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assessed through past, current, and future conditions. Past information showed damages due to extreme weather events. Current production and climate conditions showed potential vulnerability. Future climate change scenarios and crop growth modeling predicted long-term impacts on crop production. The impacts of many adaptation measures and mitigation options were evaluated to reduce risks and losses from climate change and to reduce greenhouse gas emissions. Results showed that climate change has caused strong impacts on agriculture in Vietnam. It has caused severe damages in the past, and it is likely to cause high vulnerability and heavy crop production losses in the future. Flat lands experience stronger impacts than highlands, with the Mekong River Delta suffering the strongest impacts, followed by the Coastal Central area and Red River Delta. As a country strongly impacted by climate change, it has suffered many extreme events and disasters. The agricultural sector has developed suitable adaptation measures to cope with the extreme events. Vietnam maintains a high agricultural productivity not only to feed more than 70 million people but also to export a high amount of food and foodstuffs. Vietnam is the leading cashew nut exporter, second highest rice exporter, and third highest coffee exporter in the world. However, with extensive areas of rice paddy production and high animal populations, Vietnam’s agriculture contributes substantial greenhouse gas (GHG) emissions. As a result, the Vietnamese agricultural sector is developing and implementing many mitigation options, such as alternative wetting and drying irrigation, biogas digestion, composting, and converting rice land to non-rice land. These policies target a 20 % GHG emission reduction by 2020 in comparison to the “business-asusual” scenario.

Introduction Climate Change in Vietnam Climate change is projected to impact human and ecosystems health at global, regional, country, and local scales. Due to human-induced greenhouse gas (GHG) emissions to the atmosphere, climate change will cause a cascade of environmental changes. These effects will particularly impact agricultural production. The main causes of climate change are the accelerated increase of GHG-emitting activities, combined with the exploitation of carbon sinks, such as forests, and the destabilization of natural carbon sequestration mechanisms, such as oceans. The Kyoto Protocol aims to prevent and stabilize the emission of six main GHGs including carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrochlorofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6). Of these GHGs, the most abundant and concerning is CO2, which originates primarily from anthropogenic fossil fuel combustion of coal, oil, and gas. The second most important GHG is CH4, which is emitted from landfills, enteric fermentation, air-cooling systems, coalmines, and natural gas.

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These emissions increase GHG concentrations in the atmosphere, causing global warming and higher temperatures; glacial melting leading to the loss of lowlands and islands; shifting borders between ecological and agroecological zones that have existed for thousands of years; altering atmospheric, hydrologic, and biogeochemical cycles; and altering the functional components and quality of the hydrosphere, biosphere, and geosphere. These impacts ultimately result in profound changes in natural and human system productivity. Because Vietnam is considered one of the countries most strongly impacted by climate change Dasgypta et al. (2007), the Government of Vietnam has paid a lot of attention to this issue. Climate change and sea level rise scenarios were developed for Vietnam as a foundation for assessment of impacts on sectors and regions in order to take proper responsive actions.

Extreme Events in Vietnam Temperature Changes in annual temperature over the past 50 years in Vietnam have been inconsistent in different regions. Overall, the average annual temperature increased by approximately 0.5 degrees Celsius ( C). The maximum temperature change ranged between 3.0  C and 3.0  C, and the minimum temperature change varied between 5.0  C and 5.0  C compared with the historical average (MONRE 2012), similar to the global temperature trends. Rainfall During the past 50 years, rainfall tended to decrease in northern regions but increased in southern regions. In the northern climate zones, rainfall has changed insignificantly in the dry season (from November to April) but decreased between 5 % and 10 % in the rainy season (from May to October). In the southern climate zones, rainfall decreased dramatically in the dry season but increased from 5 % to 20 % in the rainy season (MONRE 2012). However, the overall trend of average annual rainfall is to decrease in north and to increase in the south. In particular, rainfall increased by about 20 % in the southern central region compared to other regions (Table 1). Typhoon Annually there is an average of 12 typhoons or tropical depressions that affect Vietnam. Of these storm systems, 45 % originate from the Eastern Sea and 55 % originate from the Pacific Ocean (MONRE 2012). The Central Coastal areas of Vietnam, lying between 16 N and 18 N, and the Northern regions above 20 N, have the highest frequency of typhoons and tropical depressions. Drought Drought, including monthly water scarcity and seasonal scarcity, has increased overall but inconsistently. Drought impacts shift depending on the region and weather station within the same climate zone. Overall, the number of hot days

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Table 1 Increase of temperature and changing of rainfall during 50 years in agro-climate zones of Vietnam Temperature ( C) Agro-climate zone Northern West Northern East Red River Delta North Central South Central Central Highlands Mekong River Delta

January 1.4 1.5 1.4 1.3 0.6 0.9

July 0.5 0.3 0.5 0.5 0.5 0.4

Year 0.5 0.6 0.6 0.5 0.3 0.6

Rainfall (%) Period November–April 6 0 0 4 20 19

0.8

0.4

0.6

27

Period May–October 6 9 13 5 20 9

Year 2 7 11 3 20 11

6

9

Source: IMHEN (2010a)

increased significantly across the country, especially in the Central and Southern regions.

Sea Level Rise Satellite data from 1993 to 2010 indicated that the sea level in the Eastern Sea is rising at a rate of 4.7 mm per year. This translates to an average sea level rise along Vietnam’s coastline of 2.9 mm per year. However, the coastal areas in the Central regions and the Southwestern region have higher sea level rise than other coastal areas.

Climate Change and Sea Level Rise Scenarios in Vietnam In 2009, the Ministry of Natural Resources and Environment (MONRE 2009) published the first edition of Climate Change and Sea Level Rise Scenarios. The report included low-resolution forecasting for the seven climatic zones of Vietnam. MONRE designated the Vietnam Institute of Meteorology, Hydrology and Environment (IMHEN) as the leading agency on detailing and updating climate change and sea level rise scenarios for Vietnam. In collaboration with other research institutes, government agencies, and departments, the team prepared updates in 2010 and developed climate models and selective statistical tools specialized for Vietnam. Through this collaborative work, MONRE published the second edition of higher-resolution climate change and sea level rise scenarios for Vietnam in 2012 (MONRE 2012). The report included details at regional scales and an additional climatic extreme section.

Vietnam Agricultural Production Although the agricultural sector only accounts for 20 % of Vietnam’s gross domestic product (GDP), the industry plays a crucial role in Vietnam’s economy. The sector is

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responsible for feeding more than 70 million people. While Vietnam has seen a substantial increase in industrial production, the agricultural production has continued to increase at a slower rate over the past 10 years. The average annual growth rate of agriculture remained at about 3.5 % but has decreased in recent years due to the severe effects of climate and soil conditions. For example, in 2005 it accounted for 19.3 % of the GDP, and in 2012 it had only increased to 19.67 % of the GDP. The makeup of Vietnam’s agricultural outputs shows no significant change in recent years. Food crops are the biggest proportion of Vietnam’s agricultural sector, accounting for 74.6 % of the total production. Crops are followed by livestock production, which accounts for 23.8 %, and agricultural services makes up the remaining 1.58 %. Crop production still plays the biggest role by far. There was a very slight decrease of the proportion of crop production between 2005 and 2012, from 76.39 % to 73.81 %. During this time livestock production filled that gap with an increase from 21.95 % to 24.65 %. Crop production is dominated by annual crops, which account for 83.4 % of the area under production, and perennial crops, which account for 16.6 %. Most of the annual crops are cereals such as rice, maize, and soybeans, which make up 78.5 % of the annual crop production area. The remainders are commodity and annual industrial crops, covering about 9.4 % of the annual crop area. Because Vietnam’s agricultural sector is dominated by annual crops, it is a highly important resource for food and economic security. Annual crop systems are highly vulnerable to weather and will be strongly impacted with a more variable and changing climate (Table 2).

Impact of Climate Change on Agriculture Agriculture Vulnerability According to Patnaik and Narayanan (2005) and Iyengar and Sudarshan (1982), agricultural vulnerability can be calculated using an index based on three factors: exposure to a hazard, sensitivity, and adaptability. This index approach is shown in Table 3.

Damages in Agriculture Production Associated with Climate Change Damages Due to Natural Disaster, Drought, and Flood Vietnam is located on the eastern seaboard of Southeast Asia, an area frequented by natural disasters. Climate change adds complexity to this system, increasing the frequency of typhoons and extreme hot and cold weather, droughts, landslides, and flooding. According to historical meteorological data, an average of 6.96 typhoons hit Vietnam annually between 1950 and 2008. The number of typhoons increased over the years, and, more importantly, these typhoons occurred later in the rainy season between 1990 and 2008. Between 1950 and 1990, typhoons would normally

Source: GSO (2013)

Perennial cops In which

Year Agriculture land In Which Annual crops In which Spring rice Autumn summer rice Summer rice

Industrial Fruit tree

Maize Soybean Peanut Sugarcane Annual industrial crop

Cereals crops Rice

Table 2 Area dynamics of some key crops in Vietnam 2000 12,644.3 10,540.3 8399.1 7666.3 3012.3 2292.8 2360.3 730.2 2000 244.9 302.3 778.1 2104.0 1451.3 565.0

2005 13,287.0 10,818.8 8383.4 7329.2 2942.1 2349.3 2037.8 1052.6 2005 269.6 266.3 861.5 2468.2 1633.6 767.4

2010 14,061.1 11,214.3 8615.9 7489.4 3085.9 2436.0 1967.5 1125.7 2010 231.4 269.1 797.6 2846.8 2010.5 779.7

2011 14,363.5 11,420.5 8777.6 7655.4 3096.8 2589.5 1969.1 1121.3 2011 223.8 282.2 788.2 2943.0 2079.6 772.5

2012 14,579.2 11,481.5 8872.3 7753.2 3124.3 2659.1 1977.8 1118.3 2012 220.5 297.9 727.2 3097.7 2215.0 765.9

904 T. Van Mai and J. Lovell

Sensitivity condition

Group of factor Exposure condition

Parameter Average max temp Average min temp Trend or temp increase within 50 years (1958–2007) Annual rainfall Percentage of agricultural land Water surface area Population Poor household Coastal length Jobless % Woman %

Year 2010 2010 2010

2010 2010 2010 2010 2010 2010 2010 2010

Unit  C  C  C

mm %

1000 ha head/km2 % km % %

+ + + + + +

+ +

Relationship + + +

124.900 939 8.3 267 2.61 50.72

1614.2 38.268

RRD 26.4 22.0 0.60

69.860 117 29.4 250 1.21 50.11

1450.6 14.913

NM 25.7 21.6 0.55

Table 3 Agriculture and aquaculture production from seven different agroecological zones in 2010

54.500 189 20.4 639 2.94 50.46

2785.3 15.842

NCC 29.1 23.9 0.50

25.100 289 20.5 1010 2.94 50.79

2526.5 17.769

SCC 30.8 24.1 0.30

11.100 95 22.2 0 2.15 49.33

1287.3 29.775

HL 30.5 22.3 0.60

61.700 502 2.3 447 3.91 51.25

1162.7 46.036

SE 32.1 24.3 0.55

(continued)

727.400 426 12.6 684 3.59 51.28

2244.4 63.066

MRD 31.9 25.2 0.60

Impact of Climate Change, Adaptation, and Potential Mitigation to Vietnam. . . 905

Group of factor Adaptability condition

Parameter Agricultural value Rice yield Maize yield Peanut yield Fishing production Raising aquaculture production Raised fish production Raised shrimp production Aquaculture export value

Table 3 (continued) Year 2010 2010 2010 2010 2009 2010

2010 2010 2010

Unit Bil. VND Tons/ha Tons/ha Tons/ha Tons

Tons

Tons

Tons

Bil. VND

Relationship

463.6

294

4859

50,162

RRD 4235 5.92 4.52 5.28 10,744

3843

14,511

243,818

322,146

NM 510 4.64 3.32 8.85 175,051

2538.5

13,713

62,437

89,728

NCC 2771 5.07 3.99 2.04 219,583

5080

33,073

12,325

58,198

SCC 7060 4.82 3.99 2.04 452,213

146.3

61

14,702

1502

HL 157 5.07 4.92 2.93 3412

4119.5

19,664

62,433

91,727

SE 3071 4.49 5.2 5.16 412,116

33,891.1

307,070

1,419,010

1,838,638

MRD 34,991 5.43 5.29 3.1 863,289

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occur in August. However, between 1990 and 2008, they appeared regularly in October and November, much later in the season. There are also more extreme typhoons with higher intensity affecting the whole country. Historically, the highest typhoon speed was between 118 and 133 km per hour (km/h), which is an intensity of 12 on the typhoon Beaufort scale. In recent years typhoons have reached speeds of between 134 and 183 km/h, an intensity of 13–15. As a consequence of these more extreme events, there have been stronger impacts on agriculture production. Data in Table 4 indicates that the average annual damage to agriculture during the period between 1995 and 2007 was 781.74 billion VND (equivalent to 54.9 million USD). This accounts for 0.67 % of agriculture’s GDP (comparing to the 1.24 % GDP loss of all sectors caused by natural disasters). While agricultural production is a small portion of the country’s income, the industry feeds more than 71.41 % of the population. Any damages to agriculture caused by natural disasters resulted in severe impacts on poor people, for whom it is very difficult to recover from a shock (Table 5).

Damages Due to Sea Level Rise Without major action such as dyke reinforcements and improved drainage systems, a 1 m rise in mean sea levels along the coastline of Vietnam would cause an estimated threat of inundation to 17,423 km2 (km2) or 5.3 % of Vietnam’s total land area (IMHEN 2010a). Specifically, it would threaten 39 % of the Mekong Delta, 10 % of the Red River Delta, and over 2.5 % of the Central Coast provinces. Moreover, 33 out of 63 provinces and municipalities, or 5 out of 8 economic regions, are threatened by severe inundation (IMHEN 2010a). The effects of sea level rise on saline water intrusion are significant, especially for the Mekong River Delta. In the period between 1980 and 1999, the 4 % salinity level reached 22.0 kilometers Table 4 Damages in agriculture caused by natural disasters in Vietnam (1995–2007)

Year 1995 1996 1997 1998 1999 2000 2001 2006 2007 Average damage/ year Loss in GDP (%)

Agriculture VND (million) 58,369 2,463,861 1,729,283 285,216 564,119 468,239 79,485 954,690 432,615 781,764.11

USD (million) 4.2 178.5 124.4 20.4 40.3 32.2 5.5 61.2 27.7 54.9

All sectors VND (million) 1,129,434 7,798,410 7,730,047 1,797,249 5,427,139 5,098,371 3,370,222 18,565,661 11,513,916 6,936,716.6

0.67

–

1.24

Source: MARD (1995–2007) a Percentage rate of agricultural GDP loss and total GDP loss

USD (million) 82.1 565.1 556.1 128.4 387.7 350.2 231.5 1190.1 738.1 469.9

(%)a 5.2 31.6 22.4 15.9 10.4 9.2 2.4 5.1 3.8 11.6

Ha Ha Ha Ha Ha Ha Ha Ha Ton Ton Ha Ha Ha Ha Tree Ha Ha M Piece Piece Piece Piece Piece Board Board

Total flooded rice area + Strong damaged + Lost Total flooded non-rice area + Strong damaged + Lost Flooded rice bed + Lost Cereal wetted and lost Seed wetted and lost Lost industrial crop area Damaged industrial crop Damaged sugarcane Damaged planted forest Falling tree Damaged fruit tree + Died Channel slide Brocken bridge and water inlet Brocken water resources works Damaged small water resource works Lost water plank Flooded irrigation station Sunk and lost board Damaged board 132755.15 6678 15847.8 85528 4600 3027 3158.5 302 17237 287.7 4796 48824 17296 5328 786995 51221 7 282542 1335 240 620 974 180 2033 344

2001 51025.4 2846 2669.2 43761.94 0 10434 5.1 2.5 46065 726.025 33 1655 1368 7 13984 33637.3 201 731124 638 23 451 509 29 26 0

2002

Sources: Department of Natural Disaster Management, MARD 2001–2008

Unit

Item

Table 5 Impact of extreme events on agriculture 210514.2 22987 41076 52617.9 0 5924.9 4.2 1.7 43650.1 311 831.1 6939.4 11638.5 738.2 467063 7910.8 500 73263 3 26 326 669 92 184 1

2003 433790.7 9035.3 105336.5 44093.6 195 3071.9 5327 75 1029.5 442.01 0 505 990.2 302 13975 3881.5 0 702904 7 39 148 981 19 97 122

2004 537133.3 0 30372.1 161455.3 11 1709.5 0 0 6915.2 1128.038 306 26171.2 1829 23524 4014390 66 0 166448 70 113 750 36 47 382 89

2005 139230.8 5370 21348.1 122459.8 749.2 23488.07 0.5 0.5 13345.5 2565 1825.8 68842 3064 34028.4 27549424 86433 3000 106720 140 61 117 377 20 1151 1095

2006 173830.2 4709.7 33063.8 215059.2 951.24 37767.8 2115 0 79118.1 8569 0 16293.78 33769.1 5403.88 3100042 30647.16 1761 994853 132 42 1926 1276 89 266 163

2007

146945.5 29932.35 44627.54 325614 0 189395.1 0 601.75 73392.9 902.2 0 63753.33 6302.2 3525.3 735191 5395.8 0 628230.8 450 376 1438 943 184 226 52

2008

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Impact of Climate Change, Adaptation, and Potential Mitigation to Vietnam. . .

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(km) inland on the Red River. With 1 m mean sea level rise, by the end of the twentyfirst century, the 4 % contour line will penetrate 4.5 km further inland into the Red River (IMHEN 2010b; Table 6). Based on projected impacts due to sea level rise scenarios developed in 2009 and updated in 2012 by MONRE (2009, 2012), potential loss in rice production (rice equivalent) of the Mekong Delta will be about 7.6 million tons per year, equivalent to 40.52 % of the total rice yield toward 2100. If climate change and sea level rise happen as predicted in the scenarios and if the average annual yield of rice production remained unchanged, Vietnam would face serious problems of food shortages in 2100 with a 21.39 % rice yield lost.

Damages Caused by Changes in Climate Factors on Crop Production For this damage, the impact of climate change on crop production was determined using crop growth models performed by the Institute for Agricultural Environment (Mai Van Trinh and Nguyen Hong Son 2011). The model used long-term climate factors such as maximum temperature, minimum temperature, rainfall, sunshine hour, humidity, and evaporation as the data inputs for the model. Potential rice, maize, and soybean yield in the spring and summer seasons, as well as yield changes due to altered climatic parameters, were determined in seven different ecological regions. Two provinces were selected for each region (Table 7).

Table 6 Forecast of rice yield loss according to 1 m sea level rise scenarios in MDR

Province Ben Tre Long An Tra Vinh Soc Trang Ho Chi Minh Vinh Long Bac Lieu Tien Giang Kien Giang Can Tho Total

Total area (1000 ha) 231.5 449.2

Flooded area (1000 ha) 113.1 216.9

Flooded agricultural land (1000 ha) 81.7 160.0

Average rice yield (ton/ha/ season) 4.06 4.08

Rice season (season) 2.0 2.0

Rice yield loss (1000 t) 663.7 1305.3

222.6 322.3

102.1 142.5

83.5 116.6

4.43 4.93

2.0 2.0

739.9 1150.1

209.5

86.2

39.2

3.17

2.0

248.6

147.5

60.6

49.2

4.77

2.0

468.9

252.1

96.2

80.4

4.66

2.0

749.0

236.7

78.3

60.1

4.90

2.0

588.5

626.9

175.7

112.8

4.61

2.0

1040.5

298.6 2996.8

75.8 1147.4

64.6 848.1

5.18 44.79

2.0 2.0

669.6 7597.4

Source: Tran Van The et al. 2010 MDR Mekong Delta River

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Table 7 Damages of climate change on major crops of Vietnam

Parameter 1. Rice Yield loss Spring rice Summer rice 2. Maize 3. Soybean 

2030 forecast Production (1000 t) Percentage (%)* 1.966,4 8.18 1.966,6 8.10 1.222,8 7,93 743,8 8,40 500,4 18,71 14,38 3,51

2050 forecast Production (1000 t) 3.634.7 3.634,7 2.159,3 1.475,4 880,4 37,01

Percentage (%)* 15,06 14.97 14,01 16,66 32,91 9,03

Compare to 2008 production

IAE simulated crop yield for the years 2030 and 2050 under climate change conditions compared with normal climatic conditions. The simulation showed that rice yield will be reduced by 8.18 % and 15.06 % in 2030 and 2050; maize yield will be reduced by 18.71 % and 32.91 %; and soybean yield will be reduced 3.51 % and 9.03 %, respectively (Mai Van Trinh and Nguyen Hong Son 2011).

Quantify the Impacts Through Calculating Indexes Vulnerability Index Vulnerability indices of the agricultural sector for seven ecological zones were calculated following Patnaik and Narain (2005) and Iyengar and Sudarshan (1982). Results (Fig. 1) show that agricultural production in the Mekong River Delta and the South Central region are the most impacted by climate change with the highest vulnerability score. Their vulnerability is due to high annual rainfall, high average annual temperatures, high unemployment rate, long coastal exposure, and a large proportion of agricultural land. Damage Index Table 5 shows impacts of extreme events on agriculture, and Fig. 1 shows a damage index from 2001 to 2008. From these estimates, IAE concluded that South Central, North Central, and the Mekong River Delta were the most damaged by climate change. The Central Highlands, Northern Midlands, and Mountainous Areas are less affected. Particularly, in 2010 and 2011, there were 10 and 6 typhoons, respectively. These typhoons hit the North and South Central regions, causing extreme property damage, human injuries, and deaths. Impact on Crop Production Based on climatic changes such as temperature and rainfall under the scenarios from 2020 to 2025 and crop yields under regular cultivation conditions, a crop production impact index for seven ecological zones in Vietnam was calculated and presented in Fig. 1. The Red River Delta, Mekong River Delta, and North Central areas are the top three regions that scored the highest on the impact index.

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Fig. 1 Vulnerability indices, damages, crop yield prediction, and climate change impact

Indicators for Climate Change’s Impact Assessment on Agricultural Sectors An average of three indices were used as indicators to calculate impacts of climate change on different agricultural zones: a damage index, potential impact index (vulnerability), and forecasted impact index (impact of crop production). According to these indices, climate change will impact the Mekong River Delta the most, followed by the North and South Central Coast regions, and the Red River Delta. This result is also in line with the historical documentation of climate change in the regions. It can be used as a validated model to fully understand the impact of climate change and to develop adaptation measures and mitigation options for that region.

Climate Change Adaptation for Crop Production Experiences in Climate Change Adaptation in Vietnam In Vietnam, agricultural production is widely distributed in all ecological zones with climatic, geographic, soil, and crop characteristics. Because of this diversity, it is necessary and important to develop climate change adaptation measures for sustainable agricultural production in each region. – Northern Midlands and mountainous areas: Rainfed crops that demand less water (such as sugarcane, cassava, and edible canna) are recommended to replace paddy rice. Additionally, upland rice and other crops that demand less water are

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–

–

–

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recommended for sloping land with the purpose of reducing dependence on the irrigation system and preventing soil erosion and degradation. In specific microecological zones in the high mountain areas with temperate climatic condition, Mai Van Trinh et al. (2014) recommend that farmers plant high-value medicine and herbal plants, such as black cardamom. This approach allows growers to gain the economic benefits of agricultural production while reducing impacts of extreme weathers, such as freezes and droughts, on perennial industrial crops. Farmers can also apply soil conservation methods on sloping land such as terrace farming, contour farming, windbreak, shading plants, and agro-forestry (Ha Dinh Tuan 2005). These valuable experiences can be transferred to other regions with the same conditions, facing the same climate change impacts. Red River Delta: The key crops of this region are paddy rice and annual industrial crops. Regarding climate change adaptation, changing the crop rotation, crop type, cropping calendar, and water supply are among the most popular methods to reduce risks from extreme events such as, drought, flood, and salinization. Specifically, for paddy rice production in the Red River Delta, the crop calendar can be changed with late transplanting of spring rice to avoid cold weather and increase rice yield. More importantly, changing of the crop calendar for an earlier summer season allows winter crops after the double rice crop. The farmers can achieve a better harvest with this modified crop calendar. Central Coastal areas: Adaptation measures in the Central Coast areas mainly focus on drought and desertification prevention for high water demand crops. Drought-tolerant crops are introduced to suitably grow in limited water supply conditions. New water sources, new farming methods, and modified cultivation techniques have also been introduced and implemented successfully in the region. For example, there is a new crop rotation including an annual rice, sweet potato, and cassava crop (Binh Dinh PPC 2010). Southeast region: As a semiarid ecological zone, adaptation measures in the Southeastern region mainly focus on changing the crop pattern and preventing drought for key crops such as cashew, peanut, sesame, sugarcane, and other annual industrial crops. IAE-ICRISAT (2010) showed that farmers in this region also want to reduce the rice production area and introduce other upland crops with lower water demand and higher profit values. These new crops, such as grapes and apples, improve grower’s incomes and are more sustainable in drought conditions. Central Highlands: The main crops of the Central Highlands region are coffee, pepper, rubber, tea, and fruit tree. Most of adaptation measures aim to reduce water stress for these crops. In the same time, legume cover crops, fruit trees, and intercropping between annual crops and perennial crops should be implemented. These techniques increase income while maintaining soil moisture, protecting soil from erosion, and saving irrigation water. Mekong River Delta: As the most agriculturally productive region of the country, many adaptation measures, tools, and techniques are transferred to farmers in the Mekong River Delta. For example, extension workers promote suitable crop

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selection, changing crop patterns or rotations, and integrating crop management to optimize crop production and reduce investment cost (Pham Quang Ha 2013).

Climate Change Adaptation Technologies Prioritized Climate Change Adaptation Technologies in Agriculture Plant Breeding Using annual data on key crops between 1995 and 2008, IAE notes that rice, cassava, soybean, and sugarcane yields increased significantly (Table 8). Yield increase under climate impact is a sign of strong adaptability in terms of food security. With the exception of a reduction in sweet potato production, yields from rice, maize, soybean, and peanut increased greatly between 1995 and 2008. Specifically, annual yields of rice, maize, and cassava production increased by 13.8, 3.3, and 5.0 million tons, respectively. The side benefits from yield improvements include increased photosynthetic biomass production, and therefore increased carbon sequestration in belowground biomass. Climate change also causes changes in the frequency and severity of precipitation surplus and deficits. For example, Vietnam is experiencing a high number of rainfall events during the rainy season, which can lead to flooding and flash flooding. Conversely, less rainfall is associated with drought and salinization and works to increase the effects of sea level rise and saltwater intrusion. Observed data shows that saltwater intrusion moved inland from approximately 20 to 30 km from the shoreline in the Northern coastal line and between 50 and 70 km in the Southern coastal line (Mai Van et al. 2014). For this reason, the government encourages farmers to introduce and implement flood-, drought-, and salt-tolerant varieties. Many of rice varieties were introduced and successfully implemented in practice,

Table 8 Increase of crops’ yield during 1995–2008 Unit, 1000 t Crop 1. Rice 2. Maize 3. Sweet potato 4. Peanut 5. Soybean 5. Cassava 6. Sugarcane 7. Coffee

RRD 1568.4 172.7 275.0

NMR 1228.6 1.150.6 25.8

CCR 2238.0 674.9 288.6

CH 508.3 981.5 55.8

SE 372.8 229.0 0.9

MRD 7857.5 142.6 119.2

Whole country 13,773.6 3351.3 361.9

51.0 66.8 23.1 77.5 0.0

55.1 41.0 721.7 858.5 4.4

100.3 4.4 2206.2 3605.8 10.2

7.9 33.3 2072.4 1172.3 821.9

31.1 7.8 2133.7 169.2 1.3

16.1 7.4 27.2 311.4 0.0

199.3 143.1 7184.3 5416.9 837.8

RRD Red River Delta, MRD Mekong River Delta, CH Central Highland, SE South East

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such as rice varieties of OM5464 (Tran Thi Cuc Hoa 2011), OM5629, OM5981, and OM7368 (Lang et al. 2011). Water-Saving Irrigation (WSI) One of the impacts of climate change on agriculture is reducing available irrigation water. Many reservoirs in the upland areas tend to run out of water before the rainy season comes, causing drought late in the dry season. Hence, water-saving irrigation helps to save water, better contribute water resources for the whole season, and secure crop harvesting in the dry season. System of Rice Intensification (SRI) SRI was first introduced in Vietnam in 2003 in three provinces (Hanoi, Hoa Binh, Quang Nam). SRI uses the following practices: (i) using young seedlings (2.5 leaves or 8–15 days old); (ii) transplanting one plant per hill (instead of three or four); (iii) irrigating with a minimum of water (a thin water layer of 1–2 cm deep); (iv) applying more organic fertilizers and reducing nitrogen fertilizer; and (v) hand weeding (Uphoff 2002). These practices could be modified to suite local conditions. SRI practices were highly recognized and accepted by farmers and local authorities in the Northern region. The Ministry of Agriculture and Rural Development (MARD) officially adopted SRI as a good farming package by issuing Decision Number 3062/QĐ-BNN-KHCN on October 15, 2007. In 2011, 21 of 33 provinces in the Northern region applied and implemented SRI with total area of 185,065 ha and 1,070,384 participant farmers (PPD 2011). Produce Compost from Crop Residues Previously, crop residues or by-products were mostly used as fuel for cooking, roofing material, animal fodder, or tilled back into the fields. Recently, because rural areas are urbanizing, the traditional rice straw roof is being replaced by brick and concrete; wood cooking stoves are being replaced by gas, electricity, and coal; and crop residues are becoming obsolete. Burning these residues after harvesting is becoming popular practice but causes a serious air pollution and GHG emission problem. One of the suitable solutions is to produce compost using effective microbials. Rice straw is shown to have many positive effects when used as a crop residue. Pham Thi Nhung (2006) carried out field experiments during the winter maize seasons of 2004 and 2005 with fertilizer application of 8 t manure per hectare (ha); 150 kilograms (kg) of nitrogen (N), 90 kg of phosphorus pentoxide (P2O5), and 90 kg of potassium oxide (K2O) per ha; and 5 t of dried rice straw per ha. Results indicated that rice straw increased rice yield by 6–8 % compared to the control of no rice straw application. Rice straw supplementation with 10 % N, 10 % P2O5, and 10–20 % K2O increased maize yield by 7–8 % above the control treatment. Increasing the supplement to 30–40 % K2O does not change the maize’s yield, and at 50 % the maize’s yield’s reduced 4 %. This illustrates that rice straw is a nice complement to input supplementation, increasing the efficiency and reducing the amount of nitrogen, potassium, and phosphorus needed.

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Reduced Tillage On sloping land: Tillage is one important field activity for cultivating maize, cassava, pachyrhizus, and edible canna in the central and mountainous provinces. Adoption of reduced tillage has significantly expanded with labor-saving benefits and introduction of better fertilizer and herbicide use (CYMMIT 1991). For example, in Son La Province (Northwest region), over 23 % of the area under production applied reduced tillage. This includes more than 30,000 ha out of total 130,000 ha of maize production. Farmers were interested with this farming technique, and they learned to practice it. The technique has also been widely implemented in five other mountainous provinces. On flatland: No till is mainly applied in the winter crops after a double rice crop. For example, no till is used in soybean, potato, and maize by directly sowing the seeds on soil surface after harvesting of the summer rice and then covering the seed with rice straw. This farming technique has gradually expanded and is implemented in between 25 % and 60 % of the total winter soybean and potato crops in the Red River Delta (MARD 2009). Biochar Application Biochar, or charcoal, is produced by pyrolysis of biomass under the absence of oxygen or oxygen-limited conditions. Many scientists consider biochar “black gold” in agricultural production. Biochar contains carbon in stable pools with slowed decomposition that transforms to active forms (CO2, CH4, and other GHGs) recommend to use (Feng et al. 2012; Liu et al. 2011). Therefore, biochar has high potentials in improving soil properties by increasing the soil’s water- and nutrientholding capacity and protecting soil microorganisms and in improving yields. More importantly, biochar is considered an effective approach to carbon sequestration by storing carbon permanently in the soil. The agricultural sector of Vietnam produces huge amounts of crop residues which can be pyrolyzed to become biochar. With an annual production of 61 million tons of rice straw and other annual crop residues (IAE 2012), there is a large source of inputs for biochar production in Vietnam. Soil Surface Cover Farmers cover soil surface in well-drained land (on terraces); high-evaporative, arid land; and sandy land with low water-holding capacity. The materials for covering include rice straw, tree leaves and trunks, and nylon. The technique is widely applied in the Central region of Vietnam. The area is characterized by large areas of sandy soil with low soil organic matter, nutrient content, high vulnerability to drought, and low crop yield. Surface cover helps seeds to germinate more fully and faster, prevents weeds from emerging, maintains soil moisture, and reduces nitrogen volatilization. Soil cover is most often used on peanut, soybean, and sugarcane fields (Le Duy Thanh 2004). Change Land Use from Rice to Fruit Tree In many areas, rice is not the most suitable crop for the conditions. For example, in areas where land is elevated and unfavorable for irrigation infrastructure, soil fertility

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is low, or soil is waterlogged due to a depression or sea level rise, usually rice yields are very low. One of the effective measures is converting rice to fruit tree orchards, especially in Mekong River Delta. Large areas of lowland paddy rice were shifted into fruit-fish systems, sculpting the land into alternating bunches of fruit trees and ditches for fish ponds. Change Intensive Rice to Rice and Aquaculture (i) Paddy rice and fish/shrimp system Fish/shrimp systems are a growing trend in Mekong River Delta as an option for breaking away from solely rice farming. The old systems include an annual triple rice crop (three rice seasons per year) or double rice crop (two rice seasons per year). Because of changing climate and hydrological conditions, the low-elevation areas were deeply flooded and could not support the triple crop. Rice crops that are flooded at harvest time maintain low and unstable yields, usually in the rainy season in mid-September. In the fish/shrimp systems, the flooded land is used for raising fish or shrimp instead of growing rice in the late rainy season (third or second rice season). This land use is growing quickly in Mekong River Delta. As of 2008, there were 120,000 ha under fish/shrimp production. This trend is in line with the MARD policy to expand this land use type in Mekong River Delta to adapt to climate change and diversify production. (ii) Rice/duck system The rice/duck system has been implemented for a long time in the Mekong River Delta. The duck populations in the region as of 2010 reached 20 million (GSO 2011–2014), 70 % of which was released into the rice fields to seek food left after harvesting. However, in recent years, as the severe impacts of bird flu, field-free duck breeding is not recommended. It is recommended that ducks be raised in planned areas to reduce disease outbreaks (Table 9).

Climate Change Mitigation GHGs Emission in Crop Production Because agriculture is a leading sector for GHG emission reduction, MARD issued a plan for reducing GHG emissions by the year 2020 (Decision No. 3119, 2011). The plan focuses on the following solutions: (i) Applying advanced farming techniques. This set of practices is aimed at rice production and includes water-saving irrigation such as SRI. Another part of the advanced farming techniques program is the “three reductions and three gains” program, which includes a reduction of seed, nitrogen fertilizer, and other chemical inputs and gains of crop yield, product quality, and economic

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Table 9 Potential prioritized mitigation practices in agriculture # 1

Practice Genetics

2

WSI (water-saving irrigation)

3

SRI

4

Production of organic fertilizers from agricultural residues/byproducts

5

Biogas

6

Minimum cultivation

7

Biochar

8

Soil cover

9

Conversion from rice production to fruit tree plantation Conversion from three rice season system to two combined rice/fish/ shrimp system

10

Properties Increase carbon sequestration, increase biomass and yield Increase flood tolerance, salt tolerance, and drought tolerance Water saving and reduction in irrigation Increase fertilizer use efficiency Reduce CH4 emission Reducing costs on seeds, fertilizers, pesticides, and irrigation Reduce CH4 emission Replacement of inorganic fertilizers Reduce emission of N2O (from dry land) and CH4 (from flooded land) Reduce environmental pollution from burning agricultural residues or agricultural waste Prevent environmental pollution from livestock production Reduce N2O emission Collect biogas to replace other fuels (wood, coal, gas, etc.) Reduce soil erosion, soil run-off, and carbon loss Reduce costs on tillage and plowing Recovery of 50 % carbon in crop biomass Stabilized carbon in soil for long time and reduce emission Significantly improve soil properties including fertility Increase fertilizer efficiency, reduce N2O emission Use as alternative fuel Reduce soil erosion and carbon loss Reduce N2O emission Save irrigation, fertilizers, and weeding labor Reduce using pesticides Reduce CH4 emission Increase efficiency and bring more benefit of lowlands

Prospect High

High

High

Medium

High

Medium

Medium

Low

Medium Medium

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benefit. This strategy is nicknamed the “3R3G.” Another campaign is called the “1M5R” and focuses on reducing adoption of one standard seed variety and reductions of overall seed inputs, nitrogen fertilizer, chemicals, water, and postharvest loses. Alternate wetting and drying irrigation (AWD) is also encouraged to save water and reduce GHG emissions. AWD application has been shown to reduce the global warming potential (GWP) of rice production. Pandey et al. (2014) reported that AWD irrigation reduced methane emissions by approximately 67–71 %. While there is a slight increase in nitrogen oxide, overall, there is a 62–67 % reduction in CO2 emissions. (ii) Change land use type from rice to short-duration industrial crops The total area of rice cultivation in Vietnam was 7.89 million ha (about 4.1 million ha rice land) in 2013 (GSO 2011–2014). However, according to development planning for the agricultural sector Mard (2010), rice cultivation will see a reduction to 3.8 million ha (about 7.0 million ha of cultivated rice land). Firstly, 0.266 million ha of rice cultivation will be converted to higher value annual industrial crops to reduce GHG emissions. This transition is expected to decrease emissions by 1.29 million tons of CO2e (2.27 %). (iii) Change low yield/benefit rice land to high-value aquaculture (shrimp, fish) The main advantages of rice and fish/shrimp farming systems include obtaining higher economic benefits, reducing pesticide costs by 48–56 %, and increasing income by approximately $1375 per ha. According to MARD, in the Mekong River Delta, more than 600,000 ha of rice cultivation area could be converted to rice and fish/shrimp systems in order to reduce GHGs emission by 5.37 %, equivalent to a reduction of 3.06 million tons of CO2. (iv) Effectively use rice straw Rice straw is increasingly going unused after the harvest, which poses a problem for disposal. However, the unused straw could represent a potential source for efficient reuse of waste materials and a reduction in GWP for crop production. It is reported that straw compost has also shown potential for maintaining N2O emissions at a low level (Yao et al. 2010). Pandey et al. (2014) carried field experiment in Red River Delta of Vietnam and found that the reuse of composted rice straw can reduce methane emissions by about 25–29 %, reduce nitrogen oxide by 5–20 %, and reduce CO2 emissions by 24–28 %. In addition to compost, biochar that is pyrolyzed from rice straw Yanai et al. (2007) can improve soil fertility and crop yield (Table 10).

Identify and Analyze Technologies to Reduce GHG Emission in Agriculture GHG reduction technologies are primarily applied in rice cultivation, in livestock breeding, and in altered fertilizer application on arable land.

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Table 10 Potential GHG emission reduction from some crop production (Gg of CO2e) Measure Business as usual (BAU) Compost Biochar Short-duration variety ICM 3R3G NH4SO4 SRI

Rice 9078.29 3755.06 9633.38

Maize 1.020 0.589 0.255

Crop Soybean 0.177 0.029 0.006 0.060 0.074

Peanut 0.239 0.113 0.020 0.243 0.239

Cassava 0.089 0.014 0.001 0.090 0.086

Sugarcane 1.270 0.625 0.897 1.300 1.205

7230.52 7858.27 1304.26

Source: Mai Van Trinh et al. 2012

Rice Production Rice production is the most important agricultural subsector in Vietnam. According to Mai Van et al. (2014), GHG reduction technologies in rice cultivation should meet the following requirements: (1) increase rice yield, (2) increase economic benefits for farmers, (3) decrease investment costs, and (4) be sustainable. Currently, two promising GHG reduction technologies in rice cultivation are being studied: irrigation management and nutrient management. Irrigation management includes irrigating less, draining the soil, and keeping the soil humid during rice growth stages. The key stage to keep the soil humid is after top tillering until just before flowering and after ripening. By using this combination of irrigation management, experiments have shown a decrease in CH4 emissions from rice as well as increased soil aeration and, hence, increase plant available nutrient. This option could be easily applied in lowlands with sufficient irrigation. There are several options for mitigating GHG emissions using nutrient management techniques. Results of studies on emissions from rice fields indicate that both organic manure and nitrogen fertilizers increase CH4 and N2O emissions. Thus, increasing manure application needs to be paired with draining the soil to reduce CH4 emission and increase N fertilizer use efficiency. By applying the correct N fertilizer amount to meet plant requirement in each growing stage, studies show reductions in N2O emissions. Other mitigation options include changing the land use type from rice to upland crops; introducing drought-, flood-, and salt-tolerant crops; shifting the crop calendar; and implementing SRI. Farmers can also combine N fertilizer management and crop management to practice integrated crop management (ICM). Based on the program of integrated pesticide management (IPM), ICM aims to optimize water, soil, and solar conditions to optimize potential yield, reduce yield gaps, and lower GHG emissions. Irrigation management is considered the most important approach for reducing CH4 emissions from rice fields. Approaches can be implemented by mid-season drainage, AWD irrigation, and field expose-shallow irrigation (Table 11). All these

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Table 11 Prioritized climate change mitigation technologies in agriculture No. 1

Technology Suitable nitrogen fertilization rate

2

Field water drainage during rice growth stages

3

Surface expose drying and irrigation

4

Application of short duration varieties

5

Nutrient improvement by oriented additions of animal’s feed Application of stimulants in livestock production

6

7

Biogas

8

Crop rotation to reduce soil organic carbon (SOC) loss

9

Plant cover crops on sloping land to reduce soil erosion and maintain soil moisture

10

Nutrient improvement by mechanical and chemical processes

11

Gene modification for livestocks

Description Establish nitrogen formula suitable for soil property and crop characteristics; deep fertilizing, plant winter crops for better use of nitrogen residues from previous season Drain field water out during two stages: tillering and ripening in order to reduce CH4 emission and increase rice yield Application cycle of shallow irrigation and water drain out (20–25 day/cycle) after transplanting in order to reduce CH4 emission and increase rice yield Application of short-term rice varieties (approximate 100 days of growth duration) with high yield and high disease and pest resistance to replace long duration varieties (more than 140 days of growth duration) Oriented addition of nutrients in animal’s feed (BMU cakes, urea, etc.) Applying stimulants such as bovine somatotropin (BST) and anabolic steroid to improve and increase meat and milk quality and yield as well as reduce CH4 emission Store livestocks’ wastes under anaerobic condition to generate CH4 (biogas) for fuels. By-products from biogas are used as fertilizers or animal’s feed Applying conservation farming to maintain soil’s water content. Planting legumes to increase soil’s nitrogen fixation. Applying crop rotation suitable for soil properties and climate conditions Planting different cover crops following contour line on sloping land. Digging holes to prevent soil erosion and recover soil from water run-offs Processing animal’s feed through mechanical methods (grinding and blending) and chemical methods (fermentation, compost, micro-nutrient increase, etc.) in order to increased iggestiverate and meat yield Apply gene engineering to create new livestock varieties with ability of rapid growth, high disease resistance

Prospect

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mitigation options are suitable with local conditions but prioritized following the technology needs assessment (TNA) procedure (Quach Tat Quang et al. 2012).

Fertilization The emission of N2O is related to nitrogen in the soil and N fertilizer. Nitrogen is the key element in creating and increasing crop yield, making it both essential and potentially harmful in agricultural management. Fertilizer management can include many techniques. Farmers can perform a soil quality assessment in order to identify soil potential supply. Yield modeling can be used to identify the rate and amount of fertilizers to apply, based on soil properties and crop characteristic. Simple nutrient budgets and N testing can be used to identify the rate and time of fertilizer application. Farmers can also calculate their N balance from crop uptake, absorption, run-off, and emissions. Efficient use of manure and organic wastes used as fertilizers can reduce N emissions. Growers can also use winter crops to sequestrator remaining nitrogen from previous seasons or apply deep fertilization. Finally, growers can implement proper irrigation techniques and management to avoid fertilizer loss and check the soil’s pH and acidity. Cropland, Noncultivated Land, and Bare Land Cropland On actively cultivated croplands, farmers can conserve the soil by using alley cropping, contouring, terracing, crop residues to cover soil surface, reduced tillage, or no tillage. Mulching is practiced widely in sloping land areas to protect the soil from rain and wind erosion, limit evaporation, maintain water content in the soil, and prevent organic matter degradation. It also returns organic carbon and nutrients into the soil and reduces the costs of chemical fertilizer. Fallow Land and Bare Land Fallow and bare lands usually occur where there are unstable rainfall conditions, poor irrigation regimes, unfavorable transportation conditions, and poor humus. These lands occupy about 23 % of the nation. In these unfavorable soil conditions, many pedological processes lead to continued soil degradation and GHG emissions. Improvement and rehabilitation of these lands will improve ecological conditions, control soil erosion, reduce leaching, and reduce GHG emissions. It is recommended to apply the following techniques to reduce GHG emission for noncultivated and bare lands: – Plant green manure or grasses along the contour lines to prevent surface flows and retain sediment during high rainfall. Simultaneously, these buffers make terraces and soil traps along the contour lines to trap soil and prevent sedimentation from gently sloping surfaces. – Apply intercropping, agro-forestry, and mix planting of annual crops and perennial crops. These practices have been implemented widely in hilly and mountainous areas. They were especially promoted as a key activity of the National Project

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(Project 327) of regreening noncultivated and bare lands to protect against natural disasters, flash floods, and droughts in highlands – Application of Sloping Agricultural Land Technology or SALT. SALT has certain advantages over both the traditional techniques of slash-and-burn (swidden agriculture) and conventional terrace farming. SALT enables farmers to stabilize and enrich the soil and to grow food crops economically. There is also a reduced need for expensive inputs like chemical fertilizers. In addition, SALT also conserves soil moisture and reduces pests and diseases. But most importantly, to a financially harried farmer, the technology can increase his or her annual income to almost threefold after only a period of 5 years.

Conclusion Climate change strongly impacts Vietnam’s agricultural sector. Damages have been documented in the past, the existing environment is highly vulnerable, and projections show high crop losses in the future. Flatlands are more strongly affected than highlands, in which the Mekong River Delta shows the most impacts. The Coastal Central area and Red River Delta follow the Mekong Delta. Vietnam experiences many extreme events and disasters each year. Climate change is projected to increase the frequency and severity of these weather events, damaging agricultural outputs. The agricultural sector has developed suitable adaptation measures to cope with climate change and keep production ongoing, not only feeding over 76 million people but also exporting a high amount of food and foodstuffs. Vietnam is the leading cashew nut exporter, second rice exporter, and third coffee exporter in the world. With a large area of paddy rice land and a large livestock sector, production processes in Vietnam have high GHG emissions. Thus, the agricultural sector is striving to implement many mitigation options such as AWD irrigation, composting, and converting rice land to non-rice land. With these mitigation measures, the sector plans to reach the target of reducing GHG emission by 20 % by 2020.

References Binh Dinh PPC (2010) Binh Dinh province people committee report in 2010 CIMMYT (1991) Annual report: improving the productivity of maize and wheat in developing countries – an assessment of impact Dasgypta S, Laplante B, Meisner C, Wheeler D, Yan J (2007) The impact of sea level rise on developing countries: a comparative analysis. World Bank policy research working paper 4136 Decision No. 3062 (2007) Decision No. 3062/QĐ-BNN-KHCN. In 15/10/2007 MARD issues a decision to acknowledge innovative/advance techniques and methods in rice cultivation Decision No. 3119 (2011) Decision No. 3119/QĐ-BNN-KHCN. On approving programme of Green House Gas (GHG) emission reduction in the agriculture and rural development sector upto 2020 Decision no. 899/QĐ-TTg (2013) Approving the project “Agricultural restructuring towards raising added value and sustainable development”

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Dobermann A, Walters DT, Adviento-Borbe MAA (2007) Global warming potential of highyielding continuous corn and corn-soybean systems. Better Crops 91(3):16–19 Feng Y, Xu Y, Yu Y, Xie Z, Lin X (2012) Mechanism of biochar decreasing methane emission from Chinese paddy soils. Soil Biol Biochem 46:80–88 GSO (2013) General statistical office of Vietnam 2013 GSO (2011–2014) General Statistical Office of Vietnam from 2011–2014 Ha Dinh Tuan (2005) Farming techniques on sloping land. Selected proceeding from scientific conference of Vietnam Agriculture Science Institute (VASI) IAE (2012) Potential of crop residue in “Viet Nam” agriculture, workshop proceeding on efficiency use g crop residue in Viet Nam agriculture, Hanoi 12/2013. IAE-ICRISAT (2010) To the report of ICRISAT/ADB-RETA6349 IMHEN (2010a) Sea level rise scenarios and possible disaster risk reduction in Viet Nam, Institute of Meteorology, Hydrology and Environment, pp 24–25 IMHEN (2010b) Impacts of climate change on water resources and adaptation measures, Institute of Meteorology, Hydrology and Environment, pp 70–71 Iyengar NS, Sudarshan P (1982) A method of classifying regions from multivariate data. Econ Pol Wkly 2048–2052. Special Article Le Duy Thanh (2004) Study technique of nylon covering crop to increase peanut yield on degraded soil in Viet Yen district, Bac Giang province, Hanoi University 124 pp Liu Y, Yang M, Wu Y, Wang H, Chen Y, Wu W (2011) Reducing CH4 and CO2 emissions from waterlogged paddy soil with biochar. J Soils Sediments 11:930–939 Mai Van Trinh, Nguyen Hong Son (2011) Study the impact of climate change on cereal crop production in Vietnam, Science and Technology Journal of Agriculture and Rural Development. Minist Agric Rural Dev 12:3–9 Mai Van Trinh, Tran Viet Cuong (2012) Pyrolysis of rice straw and rice husk to produce biochar, material for improving soil fertility, crop yield and reducing Green House Gas (GHG) emission. In: Nguyen Van Tuat, Bui Chi Buu, Nguyen Van Viet, Nguyen The Yen (eds) Trends in rice research to overcome stresses in a changing climate. Agricultural Publishing House, Ha Noi, pp 366–372 Mai Van Trinh, Tran Van The, Dinh Vu Thanh (2014) Climate change and crop production. Agricultural Publishing House Ha Noi, pp 153 (Vietnamese) MARD (2009) Ministry of agriculture and rural development’s Agriculture production and plan to 2020 Mariam Trinh, Tran van The, Bui Thi Phuong (2012) An estimation of GHG reduction for the agriculture sector in Viet Nam, project's report for United Nations development (UNDP). MONRE (2009) Climate change, sea level rise scenarios for Vietnam. Ha Noi, Vietnam MONRE (2012) Climate change, sea level rise scenarios for Vietnam. Ha Noi, Vietnam Lang NT, Van Tao N, Buu BC (2011) Marker-assisted backcrossing (mab) for rice submergence tolerance in Mekong delta. Omonrice 18:11–21 Patnaik U, Narayanan K (2005) Vulnerability and climate change: an analysis of the eastern coastal districts of India, Human security and climate change: an international workshop, Asker Pham Quang Ha (2013) Survey and assessment impacts of climate change on agriculture and develop adaptation and mitigation measures for crop production and aquaculture in Vietnam. Research project report. Ministry for Agriculture and Rural Development Pham Thi Nhung (2006) Study influence of burying agriculture residues to potassium pools in soil and crop yield on Eutric Fluvisols soil, Dan Phuong, Ha Tay province. MSc thesis, Hanoi Agriculture University PPD (2009) Statistical data about implementation of SRI, Plant Protection Department Quach Tat Quang, Nguyen Van Anh, Nguyen Thanh Hai (2012) Vietnam technology needs assessment for climate change mitigation and adaptation, summary report of technology needs assessment for climate change adaptation and mitigation of Vietnam, The Global Technology Needs Assessment, Ha Noi

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Tran Thi Cuc Hoa (2011) Development of transgenic rice lines resistant to insect pests using Agrobacterium tumefaciens- mediated transformation and mannose selection system. Omonrice 18:1–10 Tran van The, Pham Quang Ha, Mariam (2010) Impact of climate change on Mekong delta river, scientific workshop proceeding, institute for agricultural environment. Uphoff N (2002) Supporting food security in the 21st century through resource-conserving increases in agricultural production. Agric Food Secur 1:1–18 Yanai Y, Toyota K, Okazaki M (2007) Effects of charcoal addition on N2O emissions from soil resulting from rewetting air-dried soil in short-term laboratory experiments. Soil Sci Plant Nutr 53:181–188 Yao Z, Zhou Z, Zheng X, Xie B, Mei B, Wang R, Bal Butterbach K, Zhu KJ (2010) Effects of organic matter incorporation on nitrous oxide emissions from rice-wheat rotation ecosystems in China. Plant Soil 327:315–330

Potential Impacts of the Growth of a Mega City in Southeast Asia: A Case Study on the City of Dhaka, Bangladesh A. K. M. Azad Hossain and Greg Easson

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Research Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Normalized Difference Vegetation Index (NDVI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Land Surface Temperature (LST) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Changes in Greenness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Changes in the Urban Heat Island (UHI) Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discussion and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Research Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Megacities with populations of more than ten million people in compact urban areas are the most vulnerable environments on the earth. The impacts of climate change on these megacities will be multi-faceted and severe, especially in developing countries, due to fast growth rate and inefficient adaptation. It is very important therefore to understand the contributions of the growth of megacities to climate change, especially in the developing countries. Dhaka, the capital of Bangladesh, is one of the fastest-growing megacities in the world; its population

A.K.M.A. Hossain (*) National Center for Computational Hydroscience and Engineering (NCCHE), The University of Mississippi, Oxford, MS, USA e-mail: [email protected] G. Easson Mississippi Mineral Resources Institute, The University of Mississippi, Oxford, MS, USA e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_68

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increased from 6.621 million (in 1990) to 16.982 million (in 2014). Today, Dhaka is the 11th largest megacity in the world and is projected to be the 6th largest megacity in the world with a population of 27.374 million by the year 2030. Remote sensing technology has been successfully used for mapping, modeling, and assessing urban growth and associated environmental studies for many years. This research investigates how the intensity of the urban heat island (UHI) effects correlates with continuous decrease in the greenness of the city of Dhaka, as measured from satellite observations. The results of this study indicate that Landsat imagery-derived normalized difference vegetation index (NDVI) can be used to investigate the changes in greenness in the city of Dhaka from 1980 to 2014. The changes in greenness can be correlated with the increase in the intensity of UHI effects in the city of Dhaka as determined using Landsat thermal data from 1989 to 2014.

Introduction Urban populations grew rapidly throughout the nineteenth century, more by migration from the rural areas to the cities and manufacturing centers than by absolute population growth. Throughout the twentieth century, the number and sizes of cities grew, along with the percentage of the total population living in the cities (Schubel and Levi 2000). Since 1950, the worldwide urban population has grown from 746 million to 3.9 billion in 2014, 54 % of the total global population (United Nations 2014). Continued population growth and urbanization are predicted and it is projected to add 2.5 billion more people to the world’s urban population by 2050 (United Nations 2014). A large percentage of the urban growth is concentrated in the developing world, where the average urban growth rate for developing countries is 3.5 % per year, compared with a rate of less than 1 % per year for the developed countries (United Nations 1997; WRI 1998). Asia, despite its lower level of urbanization, is home to 53 % of the world’s urban population. By 2050 it is projected that 90 % of the world’s urban population will be in Asia and Africa (United Nations 2014). The past several decades have seen the emergence of megacities, a metropolitan area with a total population in excess of ten million people (New Scientist Magazine 2006). A megacity can be a single metropolitan area or two or more metropolitan areas that have converged. The concept of megacities was initiated in 1987 to combine both theory and practice in the search for successful approaches to improve urban management and the conditions of daily life in the world’s largest cities. The megacities concept was based on a collaborative effort among government, business, and community leaders of these megacities, in an attempt to shorten the time between the introduction of innovative ideas and their implementation and diffusion. The idea was coined not simply to identify, distill, and disseminate positive approaches but to strengthen the leaders and groups who are evolving the approaches and find sources of

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support to multiply their efforts. The idea promotes a dual strategy that functions simultaneously at the practical and theoretical levels: (1) sharing “best practices” among the cities and putting the lessons of experience in the hands of decision makers and the public and (2) gaining a deeper understanding of the process of innovation and the consequences of deliberate social changes in the cities. In 1950, New York and London were the world’s only megacities (Schubel and Levi 2000). In 1990, the number of megacities had increased to 10, with a population of 153 million people, representing less than 7 % of the global urban population. By 2014, the number of megacities had nearly tripled to 28. The urban population in these megacities has grown to 453 million, and these areas now account for 12 % of the world’s urban residents. The number of megacities is projected to increase to 41 by 2030 (United Nations 2014). Since most of the recent urban growth is concentrated in the developing world, the majority of the megacities are expected to be located in the developing world (Schubel and Levi 2000). Currently, 15 out of the 28 megacities are located in Asia, with the number projected to increase to 23 in Asia by 2030 (United Nations 2014). Table 1 shows the list of the current and projected megacities in the world. The most vulnerable environments on the earth are the urban areas, especially the megacities. It is increasingly recognized that airborne emissions from major urban and industrial areas influence both air quality and climate change on scales ranging from regional to continental and global. The viability of important natural and agricultural ecosystems in regions surrounding highly urbanized areas is severely affected by the deteriorating urban air quality. Megacities also influence regional atmospheric chemistry. This situation is particularly acute in the developing world where the rapid growth of megacities is producing atmospheric pollution at unprecedented severity and extent (Gurjar et al. 2014). The impacts of climate change due to urbanization are multi-faceted and severe. The impacts differ dramatically among the megacities in the developed and in the developing countries. The impacts in the developed countries are already adapted or being adapted with efficient technologies/policies/regulations, whereas in the developing countries, due to fast growth rate and inefficient adaptation, the impact is imminent and severe. There are also no signs that the governments in the developing countries will prove to be more capable in the future. These swarming, massive urban areas will continue to grow and should concern the world (Liotta and Miskel 2012). It is very important therefore to understand the impacts of the growth of megacities on climate change. Studies on megacities at different spatial and temporal scales using various models will be required to understand their local-to-global impacts and implications (Gurjar et al. 2014). Lawrence et al. (2007) employed a global model to examine the outflow characteristics of pollutants from megacities. That model demonstrated the trade-offs between pollutant buildup in the region surrounding each megacity versus export to downwind regions or to the upper troposphere. Unfortunately, the coarse resolution of global atmospheric models and source inventories still presents difficulties to capturing the details of the impact of megacity emissions temporally and spatially (Gurjar et al. 2014).

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Table 1 List of megacities (United Nations 2014)

Megacity Tokyo Delhi Shanghai Mexico City Sao Paolo Mumbai Osaka Beijing New York*** Cairo Dhaka Karachi Buenos Aires Kolkata Istanbul Chongqing Rio de Janeiro Manila Lagos Los Angeles* Moscow Guangzhou Kinshasa Tianjin Paris Shenzhen London Jakarta

Country Japan India China Mexico Brazil India Japan China USA Egypt Bangladesh Pakistan Argentina India Turkey China Brazil Philippines Nigeria USA Russian Federation China Congo** China France China UK Indonesia

Population (thousands) 2014 2030 37,833 37,190 24,953 36,060 22,991 30,751 20,843 23,865 20,831 23,444 20,741 27,797 20,123 19,976 19,520 27,706 18,591 19,885 18,419 24,502 16,982 27,374 16,126 24,838 15,024 16,956 14,766 19,092 13,954 16,694 12,916 17,380 12,825 14,174

Rank 2014 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

2030 1 2 3 10 11 4 13 5 14 8 6 7 18 15 20 17 23

Last 5 years’ average growth (2010–2015) 0.6 3.2 3.4 0.8 1.4 1.6 0.8 4.6 0.2 2.1 3.6 3.3 1.3 0.8 2.2 3.4 0.8

12,764 12,614 12,308 12,063

16,756 24,239 13,257 12,200

18 19 20 21

19 9 26 31

1.7 3.9 0.2 1.2

11,843 11,116 10,860 10,764 10,680 10,189 10,176

17,574 19,996 14,655 11,803 12,673 11,467 13,812

22 23 24 25 26 27 28

16 12 22 33 29 36 25

5.2 4.2 3.4 0.7 1 1.2 1.4

*

Los Angeles-Long Beach-Santa Ana Democratic Republic of the Congo *** New York-Newark **

Dhaka, the capital of Bangladesh, is one of the fastest-growing megacities in the world; its population increased from 6.621 million (in 1990) to 16.982 million (in 2014) (Table 1). Today, Dhaka is the 11th largest megacity in the world and is projected to be the 6th largest megacity in the world with a population of 27.374 million by the year 2030 (United Nations 2014).

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The urban heat island (UHI) effect is an important impact of urbanization. Urban and suburban areas experience elevated temperatures compared to their surrounding rural areas (EPA 2015). The annual mean air temperature of a city with one million people or more can be 1.8–5.4
F (1–3
C) warmer than the surrounding area (OKe 1997). On a clear, calm night, this temperature difference can be as much as 22
F (12
C) (OKe 1987). The UHI effect for the city of Dhaka has already been recorded by several reports and articles (Ahmed et al. 2013). It is not yet however completely understood how the intensity of the UHI effect changes with the continuous growth of the city. Remote sensing technology has been successfully used for urban growth and associated environmental studies for many years. This research investigates how the intensity of the UHI correlates with continuous decrease in the greenness of the city, as measured from satellite observations and using digital image processing techniques. The specific objectives include: (1) evaluating the changes in greenness from 1973 to 2014 using Landsat imagery-derived normalized difference vegetation index (NDVI), (2) estimating land surface temperatures (LST) using Landsat thermal imagery, and (3) investigating the potential of the Landsat-derived LST to evaluate the changes in the UHI effect.

Research Data A time series of ten Landsat images covering Dhaka, Bangladesh, acquired from 1973 to 2014 were used in this research. The time series of imagery includes data acquired by Landsat 1 and Landsat 3 Multispectral Scanner (MSS), Landsat 4 and Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS). Table 2 lists the imagery acquisition dates and corresponding sensors and their characteristics. All ten data sets were used for visual analysis, but only selected imagery were used for vegetation and land surface temperature (LST) analysis. Table 3 shows the data usage matrix. The spatial distribution of vegetation in Dhaka was mapped to evaluate the changes in greenness over time. A normalized difference vegetation index (NDVI) was used to detect the changes in greenness. NDVI was calculated for the imagery acquired in 1973, 1980, 1989, 2000, 2010, and 2014. The thermal sensor of the Landsat series became available with the launch of Landsat 4. The earliest thermal data available for this region was acquired in 1989, started the time series of LST data for 1989, 2000, 2010, and 2014 (Table 3). The gradual changes in land use and land cover in and around the city of Dhaka from 1973 to 2014 are shown in Fig. 2. Figure 3 shows the net change in land cover and land use between 1973 and 2014.

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Table 2 Satellite data acquired Date Dec. 05, 1973 Feb. 20, 1980 Jan. 28, 1989 Feb. 28, 2000 Mar. 24, 2003 Jan. 16, 2005 Nov. 03, 2006 Jan. 11, 2009 Feb. 15, 2010 Jan. 25, 2014

Sensor Landsat 1 MSS Landsat 3 MSS Landsat 4 TM Landsat 7 ETM+ Landsat 7 ETM+ Landsat 5 TM Landsat 5 TM Landsat 5 TM Landsat 5 TM Landsat 8 OLI

VNIR bands 4,5,6, and 7 4,5,6, and 7 1,2,3, and 4 1,2,3, and 4 1,2,3, and 4 1,2,3, and 4 1,2,3, and 4 1,2,3, and 4 1,2,3, and 4 2,3,4, and 5

Spatial resolution (m) 60a 60a 30 30 30 30 30 30 30 30

Thermal bands NA NA 6 6 6 6 6 6 6 10, 11

Spatial resolution (m) NA NA 30b 30c 30c 30b 30b 30b 30b 30d

Original MSS pixel size was 79  57 m; production systems now resample the data to 60 m TM Band 6 was acquired at 120-m resolution but is resampled to 30-m pixels (after February 25, 2010) c ETM+ Band 6 is acquired at 60-m resolution but is resampled to 30-m pixels (after February 25, 2010) d TIRS bands are acquired at 100 m resolution but are resampled to 30 m in delivered data product a

b

Table 3 Satellite data used Date Dec. 05, 1973 Feb. 20, 1980 Jan. 28, 1989 Feb. 28, 2000 Mar. 24, 2003 Jan. 16, 2005 Nov. 03, 2006 Jan. 11, 2009 Feb. 15, 2010 Jan. 25, 2014

Sensor Landsat 1 MSS Landsat 3 MSS Landsat 4 TM Landsat 7 ETM+ Landsat 7 ETM+ Landsat 5 TM Landsat 5 TM Landsat 5 TM Landsat 5 TM Landsat 8 OLI

Visual inspection X X X X X X X X X X

NDVI X X X X

Thermal analysis

X X

X X

X X

Methods This research is based on the hypothesis that satellite observation-based normalized difference vegetation index (NDVI) and land surface temperature (LST) can monitor changes in urban greenness in a megacity and the changes in the intensity of urban heat island (UHI) effect. Data acquired by Landsat satellites would be the best available option to achieve these results due to the extensive archive of imagery and consistency of the sensors.

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Fig. 1 Location of the study site (not scaled)

A time series of Landsat 1-3 MSS, Landsat 4-5 TM, Landsat 7 ETM+, and Landsat 8 OLI imagery for a period of 41 years (1973-2014) for Dhaka City, Bangladesh Dhaka City: December, 1973

Dhaka City: March, 2003

District Boundary

0

5

Dhaka City: February, 1980

Dhaka City: January, 1989

Dhaka City: January, 2009

Dhaka City: February, 2010

Kilometers

Fig. 2 Changes in land cover in Dhaka City

Dhaka City: February, 2000

Dhaka City: January 25, 2014

False color composite of Landsat data. Green: Vegetation. Light Purple: Urban areas

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Dhaka City as Observed by Landsat 1 MSS Imagery December 05,1973

Dhaka City as Observed by Landsat 8 OLI Imagery January 25,2014

False color composite of 4 (as red), 6 (as green), 5 (as blue) band combination. False color composite of 3 (as red), 4 (as green), 2 (as blue) band combination. Green color represents vegetation. Light purple represents urban developments. Green color represents vegetation. Light purple represents urban developments.

Legend District Boundary

0

2.5

5

10 Kilometers

N

Fig. 3 Land use and land cover changes as observed by Landsat data

Normalized Difference Vegetation Index (NDVI) The normalized difference vegetation index (NDVI) is an image enhancement technique, which can be used to describe the greenness or relative density and health of vegetation in an image. It is one of the most widely accepted and widely used vegetation indices. NDVI was first attributed by Rouse et al. (1973), but the concept was discussed by Kriegler et al. (1969). NDVI is commonly used as an indicator of relative biomass and greenness (Boone et al. 2000). The calculation of NDVI is based on the nature of the variation of reflectance values obtained from vegetated surfaces in the near-infrared (NIR) and red regions of the electromagnetic spectrum (EMS). The reflectance values of vegetation in the near-infrared (NIR) region are higher than that in the red region. NDVI provides a ratio of the NIR and the red bands (Eq. 1), eliminating any discrepancies that may occur in the imagery due to sensor differences or image quality issues, such as brightness and other interference (Hossain and Easson 2011). The NDVI can be computed for a wide variety of sensors depending on the availability of measurements in the NIR and red bands. NDVI ¼

ðNIR  RÞ ðNIR þ RÞ

(1)

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where NIR and R are pixel values of NIR and R bands, respectively. Landsat data has been used for vegetation studies for many years. Since all the sensors used in Landsat data acquisitions consist of both visible and near-infrared (VNIR) channels (Table 2), it is possible to calculate NDVI using image data from all Landsat sensors. In this study, NDVI was calculated using imagery acquired by Landsat 1 MSS, Landsat 3 MSS, Landsat 4 TM, Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI satellites (Table 3). The NDVI calculation equations are as follows: NDVILandsat1_MSS ¼

ðBand7  Band4Þ ðBand7 þ Band4Þ

(2)

NDVILandsat3_MSS ¼

ðBand7  Band4Þ ðBand7 þ Band4Þ

(3)

NDVILandsat4_TM ¼

ðBand4  Band3Þ ðBand4 þ Band3Þ

(4)

NDVILandsat5_TM ¼

ðBand4  Band3Þ ðBand4 þ Band3Þ

(5)

NDVILandsat7_ETMþ ¼ NDVILandsat8_OLI ¼

ðBand4  Band3Þ ðBand4 þ Band3Þ

ðBand5  Band4Þ ðBand5 þ Band4Þ

(6) (7)

Land Surface Temperature (LST) Land surface temperatures (LSTs) in and around the city of Dhaka were estimated using the Level 1 thermal data acquired by Landsat 4–5 TM, Landsat 7 ETM+, and Landsat 8 TIRS sensors. The unitless digital number (DN) values of the thermal bands were digitally processed to corresponding radiance values. The processed radiance values were then used to calculate LST.

Conversion of DN to Radiance Landsat 4–5 TM and Landsat 7 ETM+ During the generation of Level 1 data, pixel values from raw unprocessed imagery (Level 0 data) were converted to units of absolute radiance using 32-bit floatingpoint calculations. These absolute radiance values were then scaled to 8-bit values representing calibrated digital numbers (Qcal) before output to the distribution media. Conversion of these calibrated digital numbers (Qcal) in L1 products back

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to the “at-sensor spectral radiance” (Lλ) requires knowledge of the original rescaling factors. The following equation (Eq. 8) was used to perform a radiance conversion for the Level 1 Landsat 4–5 TM and Landsat 7 ETM+ imagery (Chander and Markham 2003; Chander et al. 2009). Lλ ¼

  LMAXλ LMINλ ðQcal Qcalmin Þ þ LMINλ Qcalmax Qcalmin

(8)

where Lλ = spectral radiance at the sensor’s aperture in W/(m2.sr.μm) Qcal = quantized calibrated pixel value in DNs Qcalmin = minimum quantized calibrated pixel value corresponding to LMINl (DN = 0) Qcalmax = maximum quantized calibrated pixel value corresponding to LMAXl (DN = 255) LMINλ = spectral radiance that is scaled to Qcalmin in W/(m2.sr.μm) LMAXλ = spectral radiance that is scaled to Qcalmax in W/(m2.sr.μm) The required parameters were obtained from the Level 1 product metadata to process the acquired thermal data using Eq. 8. Equation 8 was modified to Eqs. 9, 10, and 11 and was used to obtain the at-sensor radiance values for the imagery acquired in 1989, 2000, and 2010, respectively. 

 15:303  1:238 LλðL4 TM_1989Þ ¼ ðDNBand6  1Þ þ 1:2378 255  1   12:650  3:20 LλðL7 ETM_2000Þ ¼ ð DNBand62  1Þ þ 3:20 255  1   15:303  1:238 ð DNBand6 Þ þ 1:238 LλðL5 TM_2010Þ ¼ 255  1

(9) (10) (11)

Landsat 8 TIRS Landsat 8 TIRS data has two different thermal bands (Band 10 and Band 11), unlike Landsat 4–5 TM and Landsat 7 ETM+. The center wavelength and bandwidth of Band 10 are 10.9 and 0.6 μm respectively, whereas the center wavelength and bandwidth of Band 11 are 12.0 and 1.0 μm, respectively. In this study, Band 11 was used to estimate LST to be more comparable with Landsat TM and ETM+ thermal data. As proposed by USGS (2014), the conversion of DN values (Qcal) to the “at-sensor spectral radiance” (Ll) was done using different approaches (comparing to Landsat TM and ETM+). Equation 12 was used in this case. This approach was also used in several recent research projects (e.g., Sameen and Kubaisy 2014).

Potential Impacts of the Growth of a Mega City in Southeast Asia: A Case. . .

Lλ ¼ M:Qcal þ B

935

(12)

where M is the radiance multiplier B is the radiance add The values of “radiance multiplier” and “radiance add” were obtained from Landsat 8 TIRS metadata (Table 4) for Band 11. These values were used in Eq. 12 to obtain Eq. 13, which was used to estimate LST for 2014 imagery acquisition date. LλðL8 TIR2014 Þ ¼ M  DNBand11 þ B

(13)

Conversion of Radiance to LST The obtained radiance values for all Landsat thermal data were converted to land surface temperature (LST) using Eq. 14. Since the obtained radiance values are of top of the atmosphere (at-sensor radiance), Eq. 14 was modified by adding an emissivity factor (Ɛ) to minimize the influence of atmospheric distortion in the calculation (Eq. 15). Table 4 provides the values of K1 and K2 for Landsat 8 TIRS (Maher and Kubaisy 2014). Table 5 provides the values of K1 and K2 for Landsat 4–5 TM and Landsat 7 ETM + (Coll et al. 2010). K2   K1 ln þ1 Lλ K2  Tk ¼  K1 :ε ln þ1 Lλ Tk ¼

(14)

(15)

where Tk = effective at-satellite temperature in Kelvin K2 = calibrated constant 2 in Kelvin Table 4 Landsat 8 TIR parameters TIR parameters

TIR bands Band 10 Band 11

Radiance multiplier (M ) 0.0003342 0.0003342

Radiance add (B) 0.1 0.1

Thermal constants K1 W/(m2.sr.μm) 774.89 480.89

K2 Kelvin 1,321.08 1,201.14

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A.K.M.A. Hossain and G. Easson

Table 5 Landsat TM and ETM+ thermal band calibration constants

Constants K1 Units W/(m2.sr.μm) 671.62 607.76 666.09

Sensor type Landsat 4 TM Landsat 5 TM Landsat 7 ETM+

K2 Kelvin 1,284.30 1,260.56 1,282.71

K1 = calibrated constant 1 in W/(m2.sr.μm) Lλ = spectral radiance at the sensor’s aperture e = emissivity (typically 0.95) Equation 15 was then modified to form Eqs. 16–19 to calculate LST, in degrees Kelvin, for each different Landsat sensor by using corresponding values of Lλ, K1, and K2. After calculating LST in absolute temperature, the values were converted to degrees Celsius, using Eq. 20. TkðL4 TM1989 Þ ¼

1260:56   607:76  0:95 ln þ1 LλðL4 TM_1989Þ

TkðL7 ETM2000 Þ ¼

1282:71  666:09  0:95 ln þ1 LλðL7 ETM_2000Þ

TkðL5 TM2010 Þ ¼

1260:56   607:76  0:95 ln þ1 LλðL5 TM_2010Þ





TkðL8 TIR2014 Þ ¼ ln

1201:14  480:89

LλðL8 TIR_2014Þ

Tc ¼ Tk  273:15

(16)

(17)

(18)

(19) þ1 (20)

Results and Analysis The processed NDVI and LST data were subset for Dhaka metropolitan area for analysis of changes in greenness and land surface temperature. The time series of Dhaka NDVI data was used to study the changes in greenness since 1980. The time series of Dhaka LST data was used to evaluate the changes in the intensity of urban heat island (UHI) impact since 1989.

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937

Changes in Greenness On the basis of the minimum and maximum values of NDVI, the lookup table of the entire time series data was scaled from 0.5 to 0.65 to visualize the changes in greenness over time. Figure 4 shows the NDVI time series for Dhaka city from 1980 to 2014. In Fig. 4, it is clearly seen that the average NDVI values decreased continuously from 1980 to 2014. The most dramatical change occurred between 1989 and 2000. The net change in greenness from 1980 to 2014 is also substantial as seen in Fig. 5.

Changes in the Urban Heat Island (UHI) Effects The variation in the intensity of urban heat island (UHI) effects due to the changes in greenness in the city of Dhaka was evaluated by determining the changes in the nature of spatiotemporal distribution of land surface temperature (LST) over time. The Landsat satellite observed LST time series data were used in different ways to study the changes in the nature of spatiotemporal distribution of LST over time.

Fig. 4 Changes in greenness from 1980 to 2014 as observed by the Landsat data

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A.K.M.A. Hossain and G. Easson

Fig. 5 Detailed changes in greenness from 1980 to 2014 as observed by the Landsat data (Thana is a kind of local administrative boundary like county)

At first, the LST distribution was visually analyzed by stretching the data lookup table from red to green. The red and green ends represent the maximum and minimum temperatures for each date. The areas covered by yellow represents approximately mean temperature for each date. Figure 6 shows the spatiotemporal distribution of Landsat observed LST in the city of Dhaka from 1989 to 2014. The LST imagery time series in Fig. 6 clearly shows that the areas characterized by high temperature extended substantially from 1989 to 2014, with significant increase from 1989 to 2000. Since the satellite imagery used in this study were acquired in different seasons of different years, it was not found reasonable to determine the absolute changes in LST variation by detecting the net changes in LST values. The second approach focused on the variation in LST along specific cross-section profile. A cross-section line A-B was selected in the east-west direction on each LST data set to extract the temperature values along the line (Fig. 6). The extracted LST values along line A-B were plotted and compared with the mean LST value for the corresponding data acquisition dates. Figures 7, 8, 9, and 10 show the variation in LST along A-B in 1989, 2000, 2010, and 2014, respectively. This analysis supports

Potential Impacts of the Growth of a Mega City in Southeast Asia: A Case. . .

939

Fig. 6 Land surface temperature (LST) from 1989 to 2014 as observed by the Landsat data

the visual analysis performed earlier and also provided a more quantitative understanding of how the LST values changed over time in reference to the mean values. The changes in the LST distribution pattern observed along line A-B provide a good quantitative evaluation of the changes in the intensity of UHI effects over time. However, the observation is limited in a particular direction and areas. The potential of image classification techniques was therefore evaluated to extend the quantitative analysis. The classification was performed based on the statistics of the satelliteobserved LST imagery (Fig. 6) as shown in Table 6 and Figs. 11 and 12.

940

Fig. 7 Variation in LST along A-B in 1989

Fig. 8 Variation in LST along A-B in 2000

A.K.M.A. Hossain and G. Easson

Potential Impacts of the Growth of a Mega City in Southeast Asia: A Case. . .

Fig. 9 Variation in LST along A-B in 2010

Fig. 10 Variation in LST along A-B in 2014

941

942 Table 6 Temperature statistics

A.K.M.A. Hossain and G. Easson

Date 1989 2000 2010 2014

Sensor Landsat 4 TM Landsat 7 ETM+ Landsat 5 TM Landsat 8 TIR

Temperature statistics (
C) Min Max Mean 22.09 32.66 25.17 21.61 36.63 26.41 21.63 31.81 25.52 17.47 25.38 20.49

Each LST imagery was classified into five classes around the mean temperature to map the spatiotemporal distribution of the areas characterized by different levels of above mean temperature. The classes are as follows: • • • • •

Class 1: Areas with temperature equal or less than mean Class 2: Areas with temperature 1
higher than mean Class 3: Areas with temperature 2
higher than mean Class 4: Areas with temperature 3
higher than mean Class 5: Areas with temperature >3
higher than mean

Figures 13, 14, 15, and 16 show the distribution of LST pixels above mean LST in the city of Dhaka as observed in 1989, 2000, 2010, and 2014, respectively. The classified raster LST data were converted to vector data and polygons were simplified. The vector data with simplified polygons were used to calculate the areas covered by each LST regime (class). The area calculations were plotted for different classes to compare them graphically. The area comparison plots improve the understanding of the changes in the intensity of UHI effect over time. Figure 17 shows the comparison of the size of the areas characterized by total above mean temperature in the city of Dhaka from 1989 to 2014. The total size of the areas where LST remained above the mean increased continuously from 1989 to 2010 but decreased in 2014. Figure 18 shows the comparison of the size of the areas characterized by 1
above mean temperature in the city of Dhaka from 1989 to 2014. The total size of the areas where LST remained 1
above the mean decreased from 1989 to 2000, but increased since then continuously. Figure 19 shows the comparison of the size of the areas characterized by 2
above mean temperature in the city of Dhaka from 1989 to 2014. The total size of the areas where LST remained 2
above the mean increased from 1989 to 2000, but decreased since then. Figure 20 shows the comparison of the size of the areas characterized by 3
above mean temperature in the city of Dhaka from 1989 to 2014. The total size of the areas where LST remained 3
above the mean increased significantly from 1989 to 2000 and remained above 1989 since then.

Discussion and Conclusions The number and size of megacities are increasing with the majority of the growth occurring in developing countries, especially in Asia and Africa. Understanding the potential impacts of the growth of megacities on the climate in Southeast Asia will

Potential Impacts of the Growth of a Mega City in Southeast Asia: A Case. . . January 28, 1989

943

Mean

50000

Number of pixels

40000

30000

20000

10000

0 22.09

24.72

27.36 Temperature (C)

30.00

32.62

29.12

32.88

36.63

February 28, 2000 Mean 50000

Number of pixels

40000

30000

20000

10000

0 21.61

25.37

Temperature (C)

Fig. 11 LST mean for 1989 and 2000

provide insight for understanding the relationship between climate change and urban growth in the developing world. The analysis of the results obtained in this research for Dhaka, Bangladesh, shows that:

944

A.K.M.A. Hossain and G. Easson February 15, 2010 Mean 50000

Number of pixels

40000

30000

20000

10000

0 21.63

24.17

26.72

29.27

31.81

23.40

25.38

Temperature (C) January 25, 2014 Mean 50000

Number of pixels

40000

30000

20000

10000

0 17.47

19.45

21.42 Temperature (C)

Fig. 12 LST mean for 2010 and 2014

• The land use and land cover change due to urban growth and development can be mapped and quantified using time series data acquired by the Landsat satellite programs from 1973 to date (Landsat 1–3 MSS, Landsat 4–5 TM, Landsat 7 ETM+, and Landsat 8 OLI and TIRS).

Potential Impacts of the Growth of a Mega City in Southeast Asia: A Case. . .

945

Fig. 13 Distribution of above mean temperature on January 28, 1989

• Landsat imagery-derived NDVI can be used to map and monitor the changes in greenness in growing megacities. It was observed that the average NDVI values in Dhaka decreased continuously from 1980 to 2014 with a significant change between 1989 and 2000. • The changes in the land surface temperature (LST) can be used to determine the changes in the intensity of urban heat island (UHI) effect as a result of the growth

946

A.K.M.A. Hossain and G. Easson

Fig. 14 Distribution of above mean temperature on February 28, 2000

and development in a megacity. The Landsat satellite-observed thermal data can be used to estimate continuous LST at 80–30 m spatial resolution from 1980 to date. • It is possible to study the changes in the intensity of UHI effects in megacities, such as Dhaka, using the thermal data acquired by Landsat 4–5 TM, Landsat 7 ETM+, and Landsat 8 TIRS from 1989 to 2014. Visual inspection of the

Potential Impacts of the Growth of a Mega City in Southeast Asia: A Case. . .

947

Fig. 15 Distribution of above mean temperature on February 15, 2000

Landsat-derived LST estimation can be used to interpret the changes in the intensity of UHI effects. However, a quantitative assessment of the changes in the spatiotemporal distribution of the LST over time is necessary to quantify the changes in the intensity of UHI effects. Image classification technique of the LST distribution can provide a reasonable solution in this regard. A five-class image classification scheme based on mean LST and 1, 2, 3, >3
above mean LST

948

A.K.M.A. Hossain and G. Easson

Fig. 16 Distribution of above mean temperature on January 25, 2014

provided a good understanding of the spatiotemporal variation of the above mean LST in Dhaka from 1980 to 2014. • The imaging technology of LST (thermal data) by the Landsat 8 TIRS is different from that of the other Landsat sensors. The Landsat 8 TIRS data calibration approach used by NASA is also different. More research is needed to make the

Potential Impacts of the Growth of a Mega City in Southeast Asia: A Case. . .

949

Fig. 17 Comparison of the size of the areas characterized by above mean temperature in the city of Dhaka (1989–2014)

Fig. 18 Comparison of the size of the areas characterized by 1
above mean temperature in the city of Dhaka (1989–2014)

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A.K.M.A. Hossain and G. Easson

Fig. 19 Comparison of the size of the areas characterized by 2
above mean temperature in the city of Dhaka (1989–2014)

Fig. 20 Comparison of the size of the areas characterized by 3
above mean temperature in the city of Dhaka (1989–2014)

Potential Impacts of the Growth of a Mega City in Southeast Asia: A Case. . .

951

thermal data acquired by Landsat 8 TIRS and other Landsat sensors (TM and ETM+) comparable and reduce uncertainty. • The interpretation of the changes in the greenness in the city of Dhaka was qualitative in nature in this study. It is recommended to use the surface reflectance-based NDVI calculation for the quantitative change detection studies.

Future Research Directions The research presented in this chapter shows the potential of remote sensing data and image processing techniques to improve our current understanding about the impact of the growth of megacities in Southeast Asia on climate change. This study provides a good platform for future research to contribute in climate change studies following the emerging “bottom-up approach” (Hossain 2013). As part of this approach, initiatives are underway to extend the current research in the following directions. • Categorize the NDVI and LST data for specific seasons and months so that the seasonal and monthly variations in land use and land cover and LST are minimized. • Develop more statistically based methods to determine the changes in the intensity of UHI effects over time by normalizing the seasonal and monthly variations of LST. • Extend this study to selected other megacities in both developing and developed countries to investigate if the developed methods/techniques work globally to determine the changes in the intensity of UHI effects due to urban growth. Acknowledgments Thanks are due to NASA and USGS for providing all the Landsat data used in this research at free of charge. Thanks are also due to the National Center for Computational Hydroscience and Engineering (NCCHE) and Mississippi Mineral Resources Institute (MMRI) at the University of Mississippi for providing all the logistics and computing facilities for conducting this research.

References Boone RB, Galvin KA, Lynn SJ (2000) Generalizing El Nino effects upon Maasai livestock using hierarchical clusters of vegetation patterns. Photogramm Eng Remote Sens 66:737–744 Chander G, Markham BL (2003) Revised Landsat-5 TM radiometric calibration procedures, and post-calibration dynamic ranges. IEEE Trans Geosci Remote Sens 41(11):2674–2677 Chander G, Markham BL, Helder DL (2009) Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sens Environ 113:893–903 Coll C, Galve JM, Sánchez JM et al (2010) Validation of Landsat-7/ETM+ thermal-band calibration and atmospheric correction with ground-based measurements. IEEE Trans Geosci Remote Sens 48(1):547–555 EPA (2015) Heat island effect. http://www.epa.gov/heatisland/. Accessed 20 Apr 2015

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Gurjar BR, Nagpure AS, Singh TP et al (2014) Air quality in Megacities. The encyclopedia of earth. http://www.eoearth.org/view/article/149934/. Accessed 26 Jan 2015 Hossain A (2013) Flood inundation and crop damage mapping: a method for modeling the impact on rural income and migration in humid deltas. In: Roger P Sr (ed) Climate vulnerability: understanding and addressing threats to essential resources, vol. 5. Elsevier, Academic Pres, p 357–374. http://store.elsevier.com/product.jsp?locale=en_US&isbn=9780123847034 Hossain A, Easson G (2011) Predicting shallow surficial failures in the Mississippi river levee system using airborne hyperspectral imagery. Geomatics Nat Hazards Risk 3(1):55–78 Kriegler FJ, Malila WA, Nalepka RF et al (1969) Preprocessing, transformations and their effects on multispectral recognition. In: Proceedings of the sixth international symposium on remote sensing of environment. University of Michigan, Ann Arbor, pp 97–131 Lawrence MG, Butler TM, Steinkamp J et al (2007) Regional pollution potentials of megacities and other major population centers. Atmos Chem Phys 7:3969–3987 Maher IS, Kubaisy MHA (2014) Automatic surface temperature mapping in ArcGIS using Landsat8 TIRS and ENVI tools, case study: Al Habbaniyah lake. J Environ Earth Sci 4(12):12–17 New Scientist Magazine (2006) How big can cities get? 17 June 2006, p 41 Oke TR (1987) Boundary layer climates. Routledge, New York Oke TR (1997) Urban climates and global environmental change. In: Thompson RD, Perry A (eds) Applied climatology: principles & practices. Routledge, New York, pp 273–287 Rouse JW, Haas RH, Schell JA et al (1973) Monitoring vegetation systems in the Great Plains with ERTS. In: Third ERTS Symposium, NASA SP-351 I, pp 309–317 Schubel JR, Levi C (2000) The emergence of megacities. Med Glob Surviv 6(2):107–110 United Nation (2014) World urbanization prospects, the 2014 revision. Department of Economic and Social Affairs, United Nations, New York United Nations (1997) The state of world population 1996: changing places: population, development and the urban future. United Nations, New York USGS (2014) Using the USGS Landsat 8 product. http://landsat.usgs.gov/Landsat8_Using_Prod uct.php. Accessed 20 Apr 2015 World Resources Institute (1998) World resources 1996–97: a guide to the global environment: the urban environment. Oxford University Press, Oxford

Potential of Solid Waste and Agricultural Biomass as Energy Source and Effect on Environment in Pakistan S. R. Samo, K. C. Mukwana, and A. A. Sohu

Contents Part A: Solid Waste and Its Management in Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Solid Waste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Composition of Solid Wastes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Solid Waste Issue in Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Current Status of Solid Waste Generation in Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Common Composition of Solid Wastes in Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Environmental Problems Due to Solid Waste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Major Constraints in Solid Waste Management in Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Integrated Solid Waste Management Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Solid Waste Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Waste Management Through Source Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Landfill Operations for Municipal Solid Waste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Infectious Waste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hazardous Waste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Changes in Solid Waste Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Part B: Agricultural Biomass of Major Crops Produced in the Province of Sindh, Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Historical Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

955 955 956 956 957 958 959 960 961 968 969 974 977 978 978 979 980 980 981

S.R. Samo (*) Quaid-E-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, Sindh, Pakistan e-mail: [email protected] K.C. Mukwana Energy and Environment Engineering Department, Quaid-E-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, Sindh, Pakistan e-mail: [email protected]; [email protected] A.A. Sohu Mechanical Engineering Department, QUCEST, Larkano, Sindh, Pakistan e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_92

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The Irrigation System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 983 Pattern of Cropping and the Yield of Major Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 990 The Rain-Fed (Nonirrigated) Area of Sindh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 993 Biomass Residue of Agricultural Crops in the Province of Sindh . . . . . . . . . . . . . . . . . . . . . . . . 995 Energy Content of Biomass Residue of Agricultural Crop in the Province of Sindh and Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 998 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1004 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1006

Abstract

The issue of waste management is now a global problem because it is not only damaging soils but also deteriorating the natural state of air and water. This chapter focuses on two important aspects of solid waste in Pakistan, i.e., domestic solid waste and agricultural solid waste. The industrial and commercial activities are contributing heavily in large quantity of solid waste. Solid waste comprises of heterogeneous substances. The most common substances may belong to paper, aluminum, plastic, glass, ferrous materials, nonferrous waste, yard waste, construction and demolition wastes, etc. The issue of management of solid waste in Pakistan is a major environmental problem. Various research findings indicate that solid waste generation in Pakistan varies from 0.283 to 0.612 Kg/capita/day, while various studies indicate that the waste generation growth rate is 2.4 % per year. As a general practice, solid waste is commonly dumped on low-lying land or open vacant land area. Then, it is burned by sanitary staff to reduce its volume so that the life span of the dumpsite can be enhanced. However, the dumped solid waste does not burn completely but rather produces clouds of smoke that can be seen from miles away. This causes obnoxious smell and creates a breeding ground for flies and rats. Various findings indicate that currently, about 60,000 t/day of solid waste is generated in Pakistan. No weighing or segregation facilities are located at any disposal sites. The wastes generated from hospitals and industrial activities are simply treated as ordinary wastes. They are jointly collected and shifted to the dump sites. The research findings indicate that common composition of solid waste in Pakistan contains plastic, rubber, metal, paper, cardboard, textile waste, glass, food, animal waste, leaves, grass, straws and fodder, bones, wood, stones, and fines to certain extent. Out of this the food wastes are 8.4–21 % of the total solid waste; paper waste 15–25 %; leaves, grass, straw, and fodder 10.2–15.6 %; fines 29.7–47.5 %; and recyclables 13.6–23.55 %. Keeping in view this proportion of solid waste, a sustainable and viable management of solid waste may be adopted by recycling, composting, and waste to energy. In the other part of the chapter, focus is on agricultural waste which is actually agricultural biomass. Being an agricultural country, huge quantity of biomass is generated and remains unutilized or burned in the agricultural fields causing air pollution. It can be observed from Tables 6, 7, 8, and 9 the biomass residue of

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various crops such as wheat straw, rice husk, rice straw, cane trash, bagasse, and cotton stalk is in different ratios. These ratios are wheat and wheat straw ratio 1:1, 20 % rice husk found as waste in paddy, paddy and rice straw ratio 1:1, 23 % cane trash found as waste in sugarcane harvest, 30 % wet bagasse found as waste in sugarcane industry, and cotton and cotton sticks ratio 1:3. Keeping in view the availability factor, the different agricultural residue biomass is used as animal feed and also as a raw source of energy at local level; hence, we theoretically consider 40 % availability of total average amount of agricultural residue biomass, i.e., 5354.73  103 t/year. Theoretically considering average calorific value of agricultural residue biomass 3500 KCal/Kg, then the theoretical energy content = 3500 k Cal/Kg  5354.73  106 Kg = 1.91  1013KCal (heating value) if this amount of heat energy is multiplied by 4.81 for converting K Cal into KJ = 7.97  1013 KJ or KW-S. Hence, the power plants of about 10,000 MW are possible to be installed in the province of Sindh with the use of only 40 % of single source by agricultural residue biomass of only major crops. This step will help in reducing air pollution in the region as a whole, and on larger scale it will help in restoring the climatic changes occurring around the world.

Part A: Solid Waste and Its Management in Pakistan Solid Waste Solid waste can be explained as the waste that is discarded by the society as unwanted material with the understanding that it is of no any productive use and has passed through its ultimate use. Mostly it is in solid, semisolid, or liquid state and is thrown out from residential, commercial, or industrial premises. The Basel Convention defines wastes as, “substances or objects which are disposed of or are intended to be disposed of or are required to be disposed of by the provisions of the law” (Basel Convention 1989). With the advancements, solid waste generation has increased enormously and consequently has started to cause environmental problems. In the past whatever the small quantity of solid waste used to be produced by the society, it was thrown in the open environment and the nature was capable to absorb it slowly and gradually without causing any significant harm or effect to the natural environment and the valuable environmental components of it. But the situation changed over time with the generation of large quantities of solid waste, and nature turned unable to replenish the damaging environment as the quantities of waste started to be disposed of in larger quantities. The issue of waste management is now a global problem because it is not only damaging soils but also deteriorating the natural state of air and water.

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The large quantity of generation of solid waste is taking place due to changing lifestyles; increasing use of disposable items and excessive packaging are all adding to an increase in the quantity of solid waste being generated. The industrial and commercial activities are contributing heavily in large quantity of solid waste. Solid waste comprises of heterogeneous substances (APO 2004). The most common substances may belong to paper, aluminum, plastic, glass, ferrous materials, nonferrous waste, yard waste, construction and demolition wastes, etc. (UNEP 2005). The issues associated with solid waste management are complicated because of the quantity and diversity of the nature of waste as well as financial limitations in large cities. It is due to this reason that nowadays the authorities of municipal organizations, planners, and managers are concentrating on proper management of the solid waste so that it does not cause any adverse problem to the environment in general and human society in particular. The municipal solid waste management (MSWM) is generation, segregation, collection, transferring, transportation, and final dumping to the designated place. By this way it succeeds in addressing public health concerns, economics, conservation, aesthetics, and the environment. For proper management it is essential to understand sources and types of solid waste (Hoornweg and Thomas 1999). These are given in Table 1.

Composition of Solid Wastes Waste composition is used to describe the individual ingredients present in solid waste stream and their relative distribution. Knowledge of composition of solid wastes is important in evaluating and assessing the equipment needed, system and management programs, and plans needed for solid waste management. The municipal and commercial portion adds up about 50–75 % of total municipal solid waste generated in a society. The actual percentage distribution depends on the extent of the municipal services provided, location, season, economic conditions, population, social behavior, climate, market for waste materials, and other factors.

Solid Waste Issue in Pakistan Like the rest of the world’s urban areas, the issue of management of solid waste in Pakistan is a major environmental problem. Various research findings indicate that solid waste generation in Pakistan varies from 0.283 to 0.612 Kg/capita/day, while various studies indicate that the waste generation growth rate is 2.4 % per year. As a general practice solid waste is commonly dumped on low-lying land or open vacant land area. Then, it is burned by sanitary staff to reduce its volume so that the life span of the dumpsite can be enhanced. However, the dumped solid waste does not burn completely but rather produces clouds of smoke that can be seen from miles away. This causes obnoxious smell and creates a breeding ground for flies and rats.

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Table 1 Sources and types of solid waste Locations from where solid waste is generated Single or multifamily housing units

S. no. 1

Sources Domestic

2

Factories

3

Commercial

4

Institutional

Schools, hospitals, prisons, government and private offices

5

Construction or demolition

6

Municipal services

7

Agricultural

New construction sites, road repair, renovation sites, demolition of buildings, broken pavements Street cleaning, landscaping, parks, beaches, recreational areas, water and wastewater treatment plants Crops, orchards, feedlots, agricultural farms, etc.

All locations where light and heavy manufacturing takes place, construction sites, power and commercial plants Departmental stores, hotels, restaurants, markets, office buildings, etc.

Types of solid waste Food waste, paper, cardboard, plastic, textiles, leather, yard waste, wood, glass, metals, ashes, special waste bulky items, consumer electronics, goods, batteries, oil Manufacturing process waste, scrap materials, construction and demolition wastes, rubbish, ashes, and special wastes Paper, cardboard, plastics, wood, food wastes, glass, metals, special wastes, hazardous wastes Paper, cardboard, plastic, wood, food wastes, glass, metals, special waste Wood, steel, concrete, dirt, etc.

Street sweepings, landscape and tree/plant trimmings, general waste from parks, beaches, and other recreational areas, sludge Spoiled food wastes, agricultural waste, rubbish, hazardous wastes

Source: Solid Waste Management in Asia Urban Development Sector Unit

This soil may have been used for more useful purposes and most important is that the possible recyclable materials are lost (ESMF 2009). There is no proper waste collection system in any urban area at all. The solid waste is dumped on the streets. Different types of waste are not collected separately. There are no controlled sanitary landfill sites. Citizens are not aware of the relationship between ways of disposing of waste. As a result the overall natural environmental and public health problems emerged frequently. Figures 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, and 17 given below reflect the solid waste dumped in an improper way in an open area (Pakistan’s garbage disposal 2001).

Current Status of Solid Waste Generation in Pakistan Various findings indicate that currently, about 60,000 t/day of solid waste is generated in Pakistan. No weighing or segregation facilities are located at any

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Fig. 1 Improper dumping of solid waste in the vicinity of vacant residential area

disposal sites. The wastes generated from hospitals and industrial activities are simply treated as ordinary wastes. They are jointly collected and shifted to the dump sites (Wastes in Pakistan 2006). The estimated waste generations in different cities of Pakistan are given in Table 2. Dumping of solid waste at abandoned open places and then its burning are the common practice. This thrown away waste has got lot of potential for recycling and is lost away easily. The total collection varies from 51 % to 70 %, while the rest of the solid waste stays behind on the streets. No relevant disposal facilities exist anywhere. It is unfortunate that no any city in Pakistan has acceptable solid waste management system right from generation of solid waste up to its final disposal. All such uncollected waste poses certain risk to the human health as well as results in clogging of drains and formation of stagnant pools of dirty water. This situation provides breeding ground for mosquitoes and flies that result in spreading malaria and cholera.

Common Composition of Solid Wastes in Pakistan The research findings indicate that the common composition of solid waste in Pakistan contains plastic, rubber, metal, paper, cardboard, textile waste, glass, food, animal waste, leaves, grass, straws and fodder, bones, wood, stones, and fines to certain extent. Out of this the food wastes are 8.4–21 % of the total solid

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Fig. 2 Improper dumping of solid waste in the low-lying area

waste; paper waste 15–25 %; leaves, grass, straw, and fodder 10.2–15.6 %; fines 29.7–47.5 %; and recyclables 13.6–23.55 % (UNEP 2005).

Environmental Problems Due to Solid Waste Ground Pollution As water whether surface or rain infiltrates deep down through solid waste, it causes leachate that comprises organic matter and may contain metallic substances like iron, mercury, lead, and zinc from discarded batteries and appliances. The leachate may also contain paints, chemical substances, pesticides, detergents, printing inks, etc. Such polluted water may cause serious impact on all living beings, including humans, and on an ecosystem. Air Pollution When solid waste is burned away in such an open place, heavy metals like iron and lead and harmful gases spread over the populated areas and result in air pollution. The blowing of wind also transfers finer solid waste substances, dust particles, and gases to the far-flung areas. The disintegration of solid waste in sunlight results in obnoxious smells and reduced visibility.

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Fig. 3 Scavengers searching and collecting valuable items from improperly dumped solid waste

Health Hazards The open dumping of solid waste initiates skin and eye infections and turns common in the prevailing area. Finer dust particles in the ambient air at or in the vicinity of dumpsites can cause respiratory problems in children and elders. The insects like flies breed on openly dumped waste and spread diseases like diarrhea, typhoid, all types of hepatitis, and cholera. Mosquitoes’ bites transfer many viruses and parasites that cause diseases like malaria and yellow fever. Stray animals like dogs, cats, and rats staying and wondering around the dump site turn carriers of a variety of diseases including plague and fever. Even the sanitary staff engaged in handling and transferring of solid waste suffers from intestinal and skin diseases.

Major Constraints in Solid Waste Management in Pakistan The proper management is missing in Pakistan because of numerous problems and issues. They include lack of infrastructure, inadequate budgetary allocations, lack of clear roles and responsibilities, uncontrolled disposal of solid waste (dumped in suburb and city boundaries), threat to public health and sanitation, and environmental pollution. In all such circumstances, solid waste solutions are not only with the engineers but can equally be distributed in between 50 % engineering and 50 % social – policy and institutional lack of participation and involvement (UNEP 2005).

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Fig. 4 Scavengers intentionally burning the dumped solid waste and collecting exposed metallic items

Integrated Solid Waste Management Practices Integrated solid waste management (ISWM) can be explained as a comprehensive waste prevention, recycling, composting, and disposal program through which the generated solid waste is managed in an environment-friendly way. A successful ISWM system focuses on prevention, recycling, and managing solid waste in such a way that it effectively protects human health and the natural environment. ISWM concentrates on sustainable solid waste management and involves in examining local needs and conditions. After this it selects the most suitable solid waste management methodologies for their strategies. Each and every activity needs careful collection and transportation of the waste to the final disposal point (Landfill design, U.S 1993).

Waste Prevention Waste prevention is a term used for “source reduction” under which efforts are launched to prevent waste from being produced. The methodologies for waste prevention are the use of less packaging material, designing and manufacturing such items that can stay longer, and reusing repeatedly the products and materials which are once produced. Waste prevention supports in reduced handling, reduced treatment, and minimized disposal costs and in the end reduces the generation of methane. Waste Recycling Waste recycling may be defined as a process of collecting, reprocessing, and recovering certain waste substances, e.g., metals, glass, plastics, and paper, to

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Fig. 5 Improperly dumped solid waste and its burning cause smoke and air pollution

Fig. 6 Improper dumping of solid waste causes damage to water and soil resources

produce new items. After collection, substances are segregated and forwarded to facilities that process them to manufacture new products and items and are made available as new products for their use. Recycling is the excellent option to resolve solid waste management issues. This technique of recycling exists in most cities. However, the recycling system differs from developing countries and developed countries. The advanced countries have established well-organized at-source segregation and recycling system, while in the developing countries, the system of recycling is not effective.

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Fig. 7 Solid waste skip fully filled with waste and dropping down on the ground

Recycling converts materials into valuable raw materials that otherwise would have become useless waste and initiates a host of environmental, financial, and social benefits (Environment Protection 2011). There are at least five benefits for recycling of solid waste and they are as under: (a) Economic Possible economic benefit of waste prevention includes reduced waste disposal fees as the waste is not usually disposed free of cost; rather, substantial charges are to be paid by the producer. On the other hand, revenues can be earned from recycling commodities by selling the recyclable substances. (b) Environmental The environmental advantage lies in reduced energy consumption, reduced pollution, conservation of natural resources, and extension of valuable landfill capacity, which stimulate the development of greener technologies and prevent emissions of many greenhouse gases and water pollutants. (c) Employee Morale Employees’ morale improves when they see the company taking steps to reduce waste through recycling. This enhanced morale certainly increases employee interest, productivity, and more waste prevention measures. Some companies use recycling revenues for employee recreation (i.e., picnics, holiday parties, etc.). (d) Corporate Image When customers and the surrounding neighborhoods see that the company is environmentally conscious, it creates a favorable image of the company. An enhanced corporate image might attract customers. It is noted from various surveys that more consumers now give preferences to a firm’s environmental record when making purchasing decisions.

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Fig. 8 Improperly dumped waste material alongside a wall of a residential house

(e) Compliance Reducing solid waste through recycling means compliance with local or state solid waste regulations. Some stakeholders and organizations restrict the quantities or types of waste accepted at solid waste management facilities. By implementing an extensive and sustainable recycling program, the business can help ensure compliance with these requirements.

Waste Composting Composting is the term used for degradation of organic materials under controlled conditions. This practice results in a marketable soil amendment or mulch. It is in fact a natural process that can be carried out with very simple human efforts. It can be systematically executed by reducing the composting time and space required and by minimizing the objectionable smells. The stabilized end products obtained after composting are rich in organic matter. These end products can act as a fine soil conditioner. But the concentrations of key nutrients such as nitrogen, phosphorus, and potassium are typically low in comparison to commercially manufactured fertilizers. In the simplest composting systems, yard wastes are stacked in long, outdoor piles called windrows. A typical windrow might be 2 m high, 3 or 4 m wide, and tens of meters long. Their length is determined by the rate of input of new materials, the length of time that materials need for decomposition, and the cross-sectional area of the pile. The composting process is affected by temperature, moisture, pH, nutrient supply, availability of oxygen, bacteria, and fungi. These are principal players in the decomposition process. But microorganisms such as nematodes,

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Fig. 9 Animals like dogs contract pathogens from the dumped solid waste material which spreads within the human settlements

mites, bugs, earthworms, and beetles also play a key role by physically breaking down the materials into smaller bits that are easier for microorganisms to attack (Integrated Agricultural Systems 2002). A number of nutrients must be available to the microorganisms that are attacking and degrading the compost pile. The most important nutrients needed are carbon for energy, nitrogen for protein synthesis, and phosphorus and potassium for cell reproduction and metabolism. In addition, a number of nutrients are needed in trace amounts, including calcium, cobalt, copper, magnesium, and manganese.

Disposal (Landfilling and Combustion) The landfilling and combustion activities are adopted to manage that solid waste which cannot be prevented or recycled. Under the method of landfilling, the solid waste is placed in properly designed, constructed, and managed landfills. In the landfills the dumped solid waste is safely contained permanently. The other method to handle this waste is through combustion. Combustion is the controlled burning of waste, which helps reduce its volume, and the burning process is called as incineration. The Three Rs (Reduce, Reuse, and Recycle) In today’s world, reduce, reuse, and recycle, commonly referred as the three Rs for waste management, are effective measures that serve as alternatives to disposing

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Fig. 10 Open dumping practice of solid waste in huge quantity on a large area

waste in landfills. Nowadays, various methods are available for properly managing the solid waste that is produced. The relevant municipal authority introduces an integrated approach to manage the generated solid waste along with combination of substitute options. The strategies of three Rs assist in reducing down the quantities of waste disposed away. The strategies of three Rs presently are helping out in conserving natural resources, landfill capacities, and energy. In addition to this, the three Rs save land and money. Choosing a new landfill has become complicated and more costly due to environmental bindings and opposition from the public living in the vicinity (Margaret Cunningham 2010). (a) Reduce The concept behind the option of reduce is not to produce the solid waste. This option can be practiced by purchasing carefully and being familiar with few guidelines like purchasing products in bulk quantity. Larger, economy-size items or those products that are confined in less packaging may be opted, avoiding overpackaged products, especially those which are packed with several materials such as foil, paper, or wooden boxes. Avoid disposable goods, such as paper plates, cups, napkins, razors, and lighters as their disposal contributes to the problem. Additionally, they are expensive because they are replaced again and again. Purchase long-lasting products that are durable or that carry good warranties. They will be long-lasting, save money in the long run, and save landfill capacities. At the office environments, make two-sided copies whenever possible. Maintain one master file instead of using several files.

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Fig. 11 Scavenger is busy in openly burning the solid waste

Adopt the practice of using electronic mails or maintain a bulletin board for correspondence and communication. Also, adopt the practice of usage of cloth napkins instead of paper napkins. (b) Reuse The concept behind reuse is using again and again the products that are capable to do that. By adopting this practice, the paper material and plastic bags can be saved in larger quantities. More importantly, the broken appliances like furniture and toys can be repaired and made ready for reuse. Similarly, use a coffee can to act as a lunch box. Reuse successfully plastic microwave dinner trays as picnic dishes. Sell old clothes, appliances, toys, and furniture in garage sales or donate them to charities. Use resealable containers rather than plastic wrap. Use a ceramic coffee mug instead of paper cups. Reuse grocery bags or bring your own cloth bags to the store. Avoid taking any a bag from the shops until and unless they are really needed. (c) Recycling Recycling practice may be explained as a series of steps in which the used materials are processed and converted into raw material again and new products are remanufactured. These remanufactured items are sold as it is as a new product. The concerned organizations advise to purchase products made from recycled material. The remanufactured products are identified by a symbol called a recycling symbol. The recycling symbol indicates out one of the two things –

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Fig. 12 Smoldering smoke coming out from dumped solid waste

either the product is made of recycled material or the item can be recycled. For instance, many plastic containers have a recycling symbol with a numbered code that indicates out the type of plastic resin it is made from. The users of the relevant plastic product can check out collection centers and curbside pickup facilities to see what they accept and start collecting those materials. Most commonly, the recyclable materials may include metal cans, newspapers, paper products, glass, and plastics. Preferences must be given to buying recycled materials at work when materials for office supply, office equipment, or manufacturing are needed. Speak to store management and ask for products and packaging that help in reducing down the solid waste. Prefer purchasing those items made from substances that are collected for recycling in the local area. Adopt practices for recycled paper for letterhead, copier paper, and newsletters.

Solid Waste Collection Solid waste collection is the first operation of the solid waste management stream. More significantly, three parties play an important role in this operation, i.e., the producers of the waste, the municipal authority, and the sanitary staff. In order to execute this system, all the three parties have to work in close coordination; else, it will be difficult to yield the success. The producers must be familiar with their roles

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Fig. 13 Improper dumping of solid waste and emerging smoke in the vicinity of vacant residential area

and responsibilities, and then there come the responsibilities of the municipal authorities and then the sanitary staff. For better performance the collection system can be classified in residential refuse collection systems, commercial waste collection, and recyclable material collection. In executing waste collection system, there may be some influence of prevailing climate, topography, available transportation systems, traffic, roads, types of wastes, and population density. However, they can be managed by adopting best waste collection practices.

Waste Management Through Source Reduction The solid waste that is not produced does not have to be collected is a simple concept. That is not the case in many other advanced countries in the world – especially those with modest domestic resources and limited land space for disposal, such as Germany and Japan. In such circumstances, strategies like good green design practices can be considered successful in reducing solid waste.

Green Product Design Strategies The design that reduces the environmental impacts associated with the manufacture, use, and disposal of products is an important part of any pollution prevention

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Fig. 14 Improper dumping of solid waste in the vicinity of vacant residential area

strategy. Companies that engage in such green product design are finding products that combine environmental advantages with good performance and price. The Office of Technology Assessment, USA, identifies two complementary goals of green design: (a) Waste prevention (b) Better material management Waste prevention can be achieved by reducing the weight, toxicity, and energy use of products along with increasing the useful life of products. Better material management facilitates remanufacturing, recycling, and composting along with enhanced energy recovery opportunities.

Product System Life Extension Products that do not wear out as quickly do not have to be replaced as often, which usually means that resources are saved and less waste is generated. Sometimes, products are discarded for reasons that have nothing to do with their potential lifetime. For example, computers become obsolete and clothing fashions change, but many products can continue to remain in service for extended periods of time if they are designed to be durable, reliable, reusable, remanufacturable, and repairable. Extending product life means consumers replace their products less often, which translates into decreased sales volume for manufacturers. Market share in the future may be driven to some extent by

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Fig. 15 Improper dumping of solid waste and exposure of pollutants to the passersby

consumer demand for greener products. Consumers, of course, must make that happen.

Material Life Extension Once a product has reached the end of its useful life, the materials from which it was made may still have economic value, and additional savings can result from avoiding disposal. The key design parameter for extending the life of materials is the ease with which they can be recycled. Products that have been designed to be recycled easily are becoming especially common in Germany. For example, Germany’s requirement that automakers take back and recycle old automobiles has stimulated green design in companies such as BMW and Volkswagen. BMW already sells cars with plastic body panels that have been designed for disassembly and that are labeled as to resin type so they may more easily be recycled. Material Selection A critical stage in product development is selection of appropriate materials to be used. In green design, attempts are made to evaluate the environmental impacts associated with the acquisition, processing, use, and retirement of the materials under consideration. In some cases substituting one material for another can have a modest impact on the quality and price of the resulting product but can have a considerable impact on the environmental consequences.

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Fig. 16 Large number of scavengers busy in searching valuable items from solid waste

Process Management Manufacturing products requires raw materials and energy inputs. Both of which often can be managed more efficiently. The energy required to manufacture a product is an important component of a life cycle assessment. Process improvements that take advantage of waste-heat recovery, more efficient motors and motor controls, and high-efficiency lighting are almost always very cost effective. Efficient Distribution Methods of packaging and transporting products greatly affect the overall energy and environmental impacts associated with those products. Transportation costs are affected by the quantity and type of material shipped, which is in turn affected by packaging, trip distance, and type of carrier. The type of carrier is constrained by the terrain to be covered as well as the speed required for timely arrival. In general, shipping by boat is the least energy-intensive option, followed by rail, truck, and then air, which is fastest but requires the most energy per ton-mile transported. Policy Options Germany has shifted the burden of packaging disposal from the consumer back to manufacturers and distributors. Germany’s Packaging Waste Law requires manufacturers and distributors to recover and recycle their own packaging wastes. The concept may even be extended to large durable goods, such as household appliances and automobiles. Germany’s take-back policy is one of many examples of approaches that governments can take to encourage reduction in the environmental costs of products.

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Fig. 17 Open transportation of collected solid waste and the sanitary staff involved in loading activity without relevant safety measures Table 2 Estimated waste generation in different cities of Pakistan

S. no. 1 2 3 4 5

Name of city Karachi Hyderabad Peshawar Faisalabad Quetta

Population 1,66,31,255 14,96,163 13,44,967 28,08,982 6,57,788

Waste generation rate Kg/capita/day 0.613 0.563 0.489 0.391 0.378

Daily waste generation (tons/day) 10,195 842 658 1098 248

Annual waste generation (tons/ year) 37,21,160 3,07,454 2,40,056 4,00,883 90,755

Source: Sustainable Development Policy Institute Islamabad Pakistan

Labeling Surveys have consistently shown that American consumers purchase products that are environmentally superior to competing products, even if they cost a bit more. Attempts by manufacturers to capture that environmental advantage have led to an overuse of poorly defined terms such as recyclable, recycled, eco-safe, ozone friendly, and biodegradable on product labels. Unfortunately, without a uniform and consistent standard for such terms, these labels are all too often meaningless or even misleading. For example, all soaps and detergents have been “biodegradable” since the 1960s. Aerosols “CFC-free, ozone friendly” have been the norm in the USA since the banning of CFCs for such applications in 1978.

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Landfill Operations for Municipal Solid Waste The properly designed landfills for disposal of municipal solid waste have brought a revolution in the place of traditional dumping of waste in the outskirts of residential settlements. The traditional waste dumping used to develop a variety of environmental pollution problems, viz., emergence of large number of flies, rats, airborne diseases, obnoxious smells/odors, and a black cloud of smoke. The term landfill refers to physical facilities adopted for the final placement of solid wastes in the ground. There are few more terms which are used in this exercise of solid waste dumping. For example, sanitary landfill refers to engineered mechanism for the dumping of domestic solid wastes into the ground to reduce the public health and environmental impact, while the term secure landfill refers to the engineered facility for the dumping of hazardous wastes. When the waste is placed in the landfills, biotransformation of organics takes place, and landfill gases and liquids are generated. The aerobic process starts to take place; then, it is followed by anaerobic processes. The aerobic processes produce and release carbon dioxide (CO2) and liquid (H2O), while the anaerobic process produces carbon dioxide (C2O), methane (CH4), and trace amounts of ammonia and hydrogen sulfide (Landfill manuals 1993). Nowadays, the proper dumping of municipal solid waste in the properly designed and constructed land areas is referred as municipal solid waste landfills. The term landfill refers to physical facilities adopted for the final placement of solid wastes in the ground. There are few more terms which are used in this exercise of solid waste dumping. For example “Sanitary landfill” refers to engineered mechanism for the dumping of domestic solid wastes into the ground to reduce the public health and environmental impact. While the term “Secure landfill” refers to the engineered facility for the dumping of hazardous wastes. When the waste is placed in the landfills biotransformation of organics take place and landfill gases and liquids are generated. The starting take place aerobic process, then it is followed by anaerobic processes. The aerobic processes produce and release carbon dioxide (CO2) and liquid (H2O). While the anaerobic process produces carbon dioxide (C2O), methane (CH4) and trace amounts of ammonia and hydrogen sulfide (Environment Protection 2011).

Solid Waste Management Landfill Methods There are various landfill methods which are discussed as under: (a) The trench method The trench method of landfills is used in level terrain. The trenches are dug by excavation in the ground. Solid waste is filled in the trenches and dirt is replaced on top of the buried material. After completion the trench is compacted. (b) The area method The area method is the most popular landfill method. In this method a side of a hill or a sloped area is found out. Then, refuse is dumped on the side of the slope and then covered with dirt. It continues until the entire slope is leveled.

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(c) The valley or ravine method The valley or ravine method is commonly used where large quantities of waste are generated by large cities. This method is used in an area with large depression or slope such as a valley or ravine. Usually, an area naturally developed is considered most suitable. Refuse is dumped in the depression and filled with dirt. The area is then compacted and built up.

Landfill Operation Classification There are three classifications of landfills: (a) Class I landfills or secure landfills These landfills are designed for dumping of hazardous waste. (b) Class II landfills or monofills These landfills are designed for dumping of designated wastes, which are particular types of wastes such as incinerator ash or sewage sludge that are relatively uniform in characteristics. (c) Class III landfills or sanitary landfills These landfills are designed for dumping of municipal solid waste. Though landfills remain the primary means of municipal solid waste disposal, three Rs of reduce, reuse, and recycling are beginning to have greater attraction in the waste management system.

Landfill Site Construction Requirements The construction of a landfill site requires a step-by-step approach. The landfill activity planners and designers are basically concerned with the viability of a suitable site (Pak EPA 2011). In order to construct commercially and environmentally feasible landfill site, specific requirements must be kept in consideration. The specific requirements are discussed below: (a) Location The landfill site should be in easy access to transport the solid waste by road. The transfer stations may be established if the haul distance is far away or rail network is used for solid waste transportation. In addition to this, land value (cost of land), cost of meeting government requirements, and prospects of overall community served through the operation may also be considered before making any final decision. Types of construction, i.e., more than one landfill, may be used at a single site in order to enhance the life of the planned site for a very long time. (b) Stability It is the complete study of underlying geology at the planned landfill site, by studying the nearby area for earthquake faults or any such weak strata, underground water table, and location of nearby rivers, streams, and flood plains so that the landfill site stays intact. (c) Capacity Capacity refers to the quantity of solid waste that is to be dumped in the landfill area. The calculation of solid waste capacity is based on quantity of the wastes,

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amount of intermediate and daily cover applied to it, and amount of settlement that the waste will undergo following tipping. The thickness of capping the landfill operation is considered along with construction of lining and drainage layers when it is completely filled at its end. (d) Protection of soil and water The solid waste is permanently dumped in the landfills. This permanent placement of solid waste needs installation of liner and collection systems. In addition to this arrangement for storm water control, leachate management and landfill gas migration may be seriously considered. (e) Nuisance and hazard management The overall operation of solid waste landfills is of critical nature. The solid waste is transported from one place to its final disposal. It is ensured that it does not cause any nuisance as there is a chance of it falling down from the loaded vehicle on its hauling path. The waste may possibly emit odor that is again a nuisance for the residents living on the haul-way path or near the landfill site. In some cases the solid waste may be infectious or hazardous in nature, and in that case special attention must be given while collection is performed.

Basic Features of Landfills Moisture or water content in a landfill is important if the wastes are to decompose properly. The initial moisture contained in the wastes themselves is quickly dissipated, so it is water that percolates through the surface, sides, and bottom that eventually dominates the water balance in the landfill. Water percolating through the wastes is called leachate. Its collection and treatment is essential to the protection of the local groundwater. Municipal solid waste landfills require composite liners and leachate collection system to prevent groundwater contamination. The composite liner consists of a flexible membrane liner (FML) above a compacted clay soil. Leachate is collected with perforated pipes that are situated above the FML. A final cover over the completed landfill is designed to minimize infiltration of water (BC Ministry of Environment 2013). During waste decomposition, methane gas is formed so completed landfills need collection and venting system. Sources of Methane: Landfill On a global scale the methane gas emissions from landfill activities are estimated to be in between 30 and 70 million tons each year. It is believed that major releases of this landfill methane presently come from developed countries, where the levels of waste tend to be highest and no comprehensive methane recovery mechanism is adopted. Landfills provide most suitable conditions for methanogenesis, with huge quantity dumping of organic material and prevailing anaerobic conditions. The larger quantities of waste which are dumped in landfills can produce methane for years to come after the closure of the landfills, as the waste passes through slow decay under the ground. The municipal solid waste landfill activities are the largest human-related methane emissions. This landfill gas is easily captured and redirected if relevant

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arrangement is made. Firstly, the commercial landfill gas energy (LFGE) recovery project was started in 1975 in Los Angeles. Gases are released during decomposition in landfills. When captured and converted to an alternative energy source, LFG is called biogas. The municipal solid waste decomposition releases methane ~50 %, CO2  45 %, and N2  5 % (Ahmed et al. 2013). Methane release takes place from landfills either directly to the air or by diffusion through the soil cover and causes impacts on the natural environment.

Infectious Waste Infectious waste is a waste that possesses potential risk of diseases or illness to human beings or a waste that is capable of causing infectious diseases. Segregation and labeling of infectious waste is carried out at its source of generation. When performing handling of infectious waste, it should be ensured that it must be carefully managed. The intactness of the packaging must be maintained and quicker bacterial growth and putrefaction is repressed. The containers in which sharps are placed must be impervious, rigid, puncture resistant, leak resistant, and sturdy so that they can sustain the risk. Infectious waste may include human blood, body fluids, separated or removed away body organs through surgical operation, syringes, sharps, glassware, or all items used during the treatment activity on an infected patient.

Training for Handling Infectious Waste Persons working with blood may be trained about blood-borne pathogens. The engaged staff working with animal contact may be trained with relevant training. The staff working with any waste that carries a potential risk of transmitting illness or disease to humans may be trained with infectious waste management. The staff engaged with infectious organisms having risk to cause illness or disease in healthy people, animals, or plants may be trained in biosafety. Personal Protective Equipment for Handling Infectious Waste The people who are engaged in handling infectious waste must be advised to wear relevant personal protective equipment (PPE), for example, wearing impermeable gloves for handling infectious waste. For splashing risk, wearing of eye protection or wearing shoe covers for walk-through hazards is advised. Infectious Waste Storage The noninfectious waste must be kept separate from infectious waste. If infectious waste is mixed by mistake with noninfectious waste, then it must be considered as infectious waste. Efforts should be made to minimize storage time duration. The area where infectious waste is placed must only be accessible by authorized personnel. The infectious waste storage area must be ventilated to outdoors. The area must be labeled with a warning sign in a clear and visible manner. The area must thwart exposure to common people, animals, and insects and disclosure to

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weather. Red- or orange-colored bags are generally used for putting the infectious waste and are also called biohazard bags. The colored bags must be correctly sealed when filled. For leakage or seep hazards, leak-proof bins or bags should be used.

Labels for Infectious Waste The universal biohazard symbol must be displayed at the place where infectious waste is placed. The biohazard symbol should be understandable from at least seven meters away from the placed bags containing infectious waste. A written message like “biohazard” or “biohazardous,” “infectious waste,” or “biomedical waste” must also be displayed.

Hazardous Waste Wastes containing harmful components that are too dangerous to be handled in ordinary manner and sent to the landfill, dumped into the sewer system, or released into the atmosphere are hazardous substances. These can be in a form of a solid, liquid, contained gas, or sludge. Improper release of hazardous waste may seriously threaten the environment and human health. Hazardous waste is regulated from the moment it is created through the time of final disposal. Identification of listed hazardous wastes: F-Listed Wastes • Wastes from nonspecific sources • Solvents from cleaning and degreasing operations • Wastewater treatment K-Listed Wastes • Created from specific sources • Chemical or pesticide manufacturing P-Listed Wastes • Acutely hazardous discarded commercial chemical products • Arsenic trioxide U-Listed Wastes • Less hazardous discarded commercial chemical products

Future Changes in Solid Waste Composition In terms of solid waste management planning, knowledge of future trends in the composition of solid waste and quantities is of great importance. As the time is passing, we are experiencing new lifestyles and for that we too adopt many practices; some of them are pointed as under:

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(a) Food waste The quantity of kitchen food waste collections has been changed significantly with the passage of time as a result of technological advancements and change in public health. Food processing and packaging industry and the use of kitchen food waste have affected the quantity of food waste. The proportion of food waste, by weight, has decreased as it is preserved or refrigerated for some time and used later on. (b) Paper and cardboard The proportion of paper and cardboard found in municipal solid waste stream has increased greatly over the past 50 years. All this happened due to excessive use of paper in offices and newspaper publications. This is expected to increase further in coming times. (c) Yard wastes The proportion of yard waste has also increased significantly, primarily due to passage of the relevant legislations that prohibit burning of yard wastes. By weight, yard waste currently accounts for about 16–24% of the waste stream. (d) Plastics The proportion of plastics in solid waste has increased significantly during the past 50 years. It is anticipated the use of plastic will continue to increase, but at a slower rate than during the past 25 years.

Future Directions The way in which currently the solid waste is being managed is not an environment friendly. The incomplete collection of generated waste, lack of awareness from the common person to the chain of municipal authority, and ignorance toward segregation and open burning of waste are few issues out of many which need engineering and administrative approaches. The improper disposal has started causing numerous problems. The air is being polluted by addition of air pollutants in the atmosphere due to this open burning. The sewerage system is clogged and starts malfunctioning due to fallen down solid waste material. The freshwater bodies including canals and lakes as well as ocean water are heavily polluted, and its aquatic life and ecosystem are damaged. The receiving soils lose their fertility and deteriorate the landscaping. The scattered waste causes nuisance and foul smells in the prevailing area. The solution lies in systematic approach of integrated solid waste management (ISWM). The individuals, the authorities of health-providing facilities, commercial areas, institutions, manufacturing facilities, etc. all need awareness and have to play participatory roles in order to perform their due responsibilities. The most important responsibility no doubt is on the part of municipal authorities. The municipal authorities should introduce separate waste collection system for recyclable waste for recycling, organic waste for composting, combustible waste for incineration, and the left out waste for properly maintained landfills. This will certainly help in properly managing the solid waste problem in Pakistan to a greater extent, and resultantly, the overall environment will be saved.

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Fig. 18 Mohenjo-daro: Renowned place of archeological importance (Source: http://www. mohenjodaro.net)

Part B: Agricultural Biomass of Major Crops Produced in the Province of Sindh, Pakistan Introduction The province of Sindh, Pakistan, is historically important due to one of the oldest civilizations of the world, the Indus Valley Civilization, and the archeological site of Mohenjo-daro (Fig. 18). Since histories back the Indus Valley Civilization grew agriculture with Indus River as the source, agriculture is the backbone of our economy. In Sindh the major crops of wheat, rice, sugarcane, and cotton are on average annually grown on 2,41,22,600 ha, which produce an average of 1,87,98,930 t of major crops; as a result there is 1,36,34,340 t of average agriculture residue biomass annually. If only 40 % of this biomass residue is utilized for power generation, there will be more than 10,000 MW of power plant generation capacity which is almost 81 % replacement of fossil fuel power generation and 52 % of overall generation capacity of Pakistan with Sindh province as the only source, while, if 35 % of agricultural biomass residue of only major crops of Pakistan is utilized, there would be almost double of the installed capacity of Pakistan up to 2013 (Installed Capacity of Pakistan 19,360 MW). Though there is a huge potential available in this region, if it is properly utilized, there could be double of our crop yields resulting double amount of agricultural

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biomass residue, hence more poverty reduction and more environment-friendly energy generation for the future needs and development of the country at large.

Historical Background History is evident about the emergence of the world’s oldest civilizations, most of these civilizations born and flourished on the banks of the rivers – they needed freshwater to drink, to grow grains to feed, and to sail as a way of transportation. The first ancient civilizations arose in the Middle East, the Mesopotamia (land between two rivers Tigris and Euphrates); Egypt (Nile River); modern-day Pakistan, the Indus Valley Civilization (Indus River); and China, the Huang He (Yellow River) Valley. The common factors of flourishing of these civilizations among all these were water and agriculture. The Indus Valley remained the host of ancient civilization of the world’s human history; it is learned that the cloth used for the mummification in Egypt was exported from Mohenjo-daro. After the extermination of the Indus Valley Civilization, the new settlements grew slowly in the region (especially in the “doabs,” the region lying between and reaching to the confluence of two rivers). Most of today’s irrigation systems we have were an effort of the British authorities in the middle of the nineteenth century who managed the already existing system of low irrigation occurrences which evolved much earlier before the British rule; such systems were the small dams and inundation canals (Ghar Wah, the famous inundation canal constructed by the then Kalhora rulers of Sindh before the British in the region now known as Larkano District of Sindh). The British authorities expanded and modernized the whole irrigation water supply system of the Indus Basin known as Indus Basin Irrigation System (IBIS). On the part of the British, they constructed in 1932 AC one the most famous barrages on the Indus River near Sukkur city of Sindh (known as Lord Lloyd or Sukkur barrage with seven canals taking from it) in the Sindh irrigation system (Sindh irrigation system is a part of IBIS). The Sindh irrigation system with three barrages, one pre-independence and two post-independence, and 14 main canals is one of the world’s largest irrigation systems; the agricultural area of the province is irrigated by these 14 main canals. The size of the area irrigated by the irrigation system in Sindh province is more than the area irrigated in Egypt, and it is one-and-a-half times the area irrigated in Mexico (van Steen Bergen 2014). The economy of the province is of dual nature; on the one side it has the country’s biggest metropolitan city with Bin Qasim seaport and capital of Sindh province Karachi, which accounts for about 40 % of the population of the province and is the economic hub of the country as a whole. The rural population and area on the other side is mostly agricultural. The rural Sindh is the most poverty stricken with huge manpower still with 35 % of the population below poverty line in 1999; one of the causes of this

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A I Main area A II Piedmont soil region B I Non-perennial Guddu command area

India

B II Perennial Sukkur command area C Main area Kotri command D Thar and Nara deserts E Kohistan

Balochistan

Arabian sea

Rann of Kutch

A. Rice/Wheat zone of right bank of upper Sindh B. Cotton/Wheat zone of left bank C. Rice/Wheat Sugarcane zone of lower Sindh

Fig. 19 Agricultural and ecological zones of Sindh province. Source: PARC

poverty is the great extent of inequity in land distribution. Big landlords with large farm cultivate their land through the tenants and land laborers and with mechanized equipments; mostly these equipments are tractors. Officially classified small farms are only 33 % the area of the size less 8 hectares (ha) (van Steen Bergen 2014). Almost the entire agricultural area of the Sindh province is irrigated with 14 canals except limited areas in the west with spate irrigation, and agriculture in Tharparkar desert is rain fed. Rice, wheat, cotton, and sugarcane are the major crops mostly grown in the province; Fig. 19 gives the detail of command area and crops grown and includes desert area (van Steen Bergen 2014). The yield compared to the rest of the world which is much below is graphically shown in letter pages of this write-up. Mango and banana orchards are in districts of Hyderabad and Sanghar, guava is grown in Larkano District, and date palms are grown in Khairpur District. All are limited but high-valued horticulture, while mango and date palms are exported too. The agricultural production of the province has increased more or less at the pace of population increase at a rate of 2–3 % a year, over the last 15 years (van Steen Bergen 2014).

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Table 3 Barrages on Indus River in Sindh province 1. Guddu barrage (i) Left bank canals: one 01. The Ghotki Feeder (non-perennial) canal (ii) Right bank canals: 01. Desert Pat Feeder and 02.The Begari Sindh Feeder, (both are two canals non-perennial canals) 2. Sukkur/Lord Lloyd barrage (i) Left bank canals: four 01. Khairpur West Canal, 02. Rohri Canal, 03. Khairpur East Canal, canals and 04. Eastern Nara Canal (ii) Right bank canals: 01. North West Canal, 02. Rice Canal, and 03. Dadu Canal three canals 3. Kotri barrage (i) Left bank canals: 01. The Akram Wah (Lined Canal), 02. The Fuleli Canal, and 03. three canals The Pinyari Canal (ii) Right bank canals: 01. Kalri Baghar Feeder one canal Courtesy: Sindh Irrigation Department

The Irrigation System The three gigantic barrages (namely, Guddu, Sukkur, and Kotri) on the Indus River in Sindh province (Table 3) supply irrigation water; the Sukkur barrage construction was completed in year 1932 pre-independence, while the other two barrages Kotri barrage construction completed in 1955 and Guddu barrage construction completed in 1962 both are post-independence barrages. Figures 20, 21, and 22 show the view of these three barrages. The 14 main canals are fed by the above three gigantic barrages; further, the larger canals are subdivided into branches. Through the branches, distributaries, and minors, irrigation water is supplied to the agricultural lands through water courses. In the province of Sindh, there are 109 branch canals, 509 distributaries, and 902 minors (Courtesy: Sindh Irrigation Department). Rohri Canal, and Eastern Nara Canal these off take from Indus river at Sukkur barrage on the left bank, both these serve command near about 1 million ha such is the huge size of Sindh irrigation system, these are one of the largest single Canal in the world (van Steen Bergen 2014). Out of these 14 main canals, some are non-perennial larger canals which flow seasonally (in summer season only when the river is in its high flows), and others are perennial which flow year-round (only closed in month of January for maintenance purpose). The IBIS network for agriculture of our country Pakistan (Fig. 23) provides 90 % of fiber and food needs, while 10 % is provided through rain-fed (locally called barani) area. The IBIS has three dams, of which Tarbela Dam is a mega dam of Pakistan; the system also contains 19 barrages on river, 12 inter-river link canals, 45 big canal commands, and more than 1 million tube wells, including disposal network of agricultural effluent about 18,000 km length, with one drain carrying much part of agricultural saline effluent direct into the Arabian Sea known as Left Bank Outfall Drain (LBOD). The drainage network is still not connected as the

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Fig. 20 Guddu barrage (Courtesy: Sindh Irrigation Department)

Fig. 21 Sukkur/Lord Lloyd barrage (Courtesy: Sindh Irrigation Department)

irrigation network is, resulting in such a large irrigated agricultural system that has not achieved the objective of poverty reduction. Further to the effect, the system even more deteriorated as time passes; the causes are detached management of different sectors (irrigation system, agriculture, environment, and social), as there is

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Fig. 22 Kotri barrage (Courtesy: Sindh Irrigation Department)

deficiency in coordination among various water-related stakeholders and dearth of linkage of systemic process between economic, social, and environment; deficiency in execution of modern water management technologies; deprived water polices, especially in groundwater management; and poor maintenance and operation of the system as a whole (Lashari and Mahesar 2012). As about 60 % population of the Sindh province of Pakistan is rural and their source of income is almost agriculture, so the economy of Sindh is agriculture dependent. The major crops are rice, wheat, cotton, and sugarcane; these crops make use of 68 % of area under crop, though in Sindh some horticulture crops are grown too, such as dates, bananas, and mangoes, including vegetables almost of all kinds seasonally. Total gross command area (GCA) of Sindh is 5.76 million hectare (Mha), and it is estimated that production of major crops in Sindh is reduced by 40–60 % as about 37.6 % of the total GCA is under waterlogging and salinity problems (Lashari and Mahesar 2012). On the other hand, Table 4 shows the detail of 14-year data, where the net production of major cops and net cropped area vary from year to year depending upon availability of surface water and other factors such as to some extent introduction of modern techniques of hybrid seeds. The contribution of Sindh province in overall national production of major agricultural crops from the 14-year data (i.e., from financial years 1997–1998 to

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Fig. 23 Map of Pakistan and Sindh province showing IBIS (Source: SIDA.org.pk)

2010–2011) shows an average of 14 % to maximum 17 % in 2010–2011 in wheat, average of 34 % to maximum 36 % in 2008–2009 in rice, average of 27 % to maximum 29 % in 2007–2008 in sugarcane, and average of 23 % to maximum 33 % in 2009–2010 in cotton (Pakistan Statistical Year Book of 2008 and 2011).

Production (000) ton 2659.4 2675.1 3001.3 2226.5 2101 2109.2 2172.2 2508.6 2750.4 3409.1 3411.4 3540.2 3703.1 4287.9 40,555.4 2896.81

Rice (paddy) Area Production ha. (000) (000) ton 689.3 1840.9 704.1 1930.3 690.4 2123 540.1 1682.3 461.1 1159.1 488.3 1299.7 551.2 1432.8 543.9 1499.6 593.2 1721 598.1 1761.8 594 1817.7 733.5 2537.1 707.7 2422.3 361.2 1230.3 8256.1 24,457.9 589.72 1746.99

Courtesy (Pakistan Statistical Year Book 2008 and 2011)

Cropping year 1997–1998 1998–1999 1999–2000 2000–2001 2001–2002 2002–2003 2003–2004 2004–2005 2005–2006 2006–2007 2007–2008 2008–2009 2009–2010 2010–2011 Total Average of 14 years

Wheat Area ha. (000) 1120.2 1123.7 1144.2 810.7 875.2 863.7 878.2 887.4 933.2 982.2 989.9 1031.4 1092.3 1144.4 13,876.7 991.19

Sugarcane Area ha. (000) 261.6 270.8 230.6 238.8 240.7 258.6 259.9 214.9 183.2 214.7 308.8 263.9 233.9 226.5 3406.9 243.35

Table 4 The production of major agricultural crops in Sindh province 14-year data Production (000) ton 15,999.6 17,050.7 14,290.8 12,049.7 11,416.3 13,797.6 14,611.8 9357.4 11,243.4 12,529.2 18,793.9 13,304.3 13,505.4 13,766.4 1,91,716.5 13,694.04

Cotton Area ha. (000) 600.3 630.2 633.5 523.6 547.4 542.6 561.4 635.1 637.1 570.1 607.4 651.5 634.7 457 8231.9 587.99

Production (000) bales (375 lbs each) 2335.5 2134.1 2377.4 2141.1 2443.2 2411.8 2242.8 3016.7 2648 2398.2 2536.2 2978.3 4270.7 3536.8 37,470.8 2676.49

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Cotton-wheat Rice-wheat Mixed crops Pulses-wheat Maize-wheat-oilseed Maize-wheat Orchard-vegetables-wheat Peri-urban around Quetta

Fig. 24 Crop production regions (Source: FAO of UN)

The province of Sindh is the second largest province of Pakistan in terms of population and economy and is also known as the “Valley of Mehran.” Mehran and Sindhu are the two well-known names of the Indus River. The name of province Sindh is also derived from word Sindhu – the Indus River – and it is the third largest province in terms of area which is 54,407 sq-miles (1,40,914 sq-km). The total gross command area (GCA) of the province is 5.76 million hectares (Mha), and its culturable command area (CCA) is 2027Mha. The major crops grown are wheat, rice, sugarcane, and cotton; these major crops are cultivated on 68 % of total cropping area, and the rest is the horticulture crops. The irrigation network provides 48.76 million acre foot (MAF) of surface water to irrigate the command area, though the availability is generally 10–12% less than the above quantity of surface irrigation water. 5 MAF is the groundwater availability that is too unregulated, while the rainwater has good potential, but it is also not properly explored (Lashari and Mahesar 2012). In horticulture, Sindh produces 88 % of chilies, 34 % of mangoes, and 73 % of banana grown in Pakistan. Others are the fodder crops, pulses, oil seeds, condiments, fruits, and vegetables (Kiani 2008).

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Fig. 25 (a, b) Image of paddy crop sowing (Source: SARSO Sindh, Pakistan)

Figure 24 gives the detail of the entire Pakistan including the Sindh province region-wise major crops grown. In addition to this, in different regions various vegetables and other horticulture crops are also grown (Figs. 25, 26, 27, 28, 29, 30, 31, 32, 33, and 34).

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Fig. 26 Image of grown paddy crop (Source: SARSO Sindh, Pakistan)

Fig. 27 Image of cotton crop sowing (Source: SARSO Sindh, Pak)

Pattern of Cropping and the Yield of Major Crops Figure 35 gives the detail of cropping pattern of the entire country and Sindh province district and region wise; Table 4 shows the yield of major crops and area of each cultivated crop per year (wheat, rice, sugarcane, and cotton), while Fig. 36 and Table 5 show yield in kg/ha of different major crops for each year of Sindh province. From Table 4, Table 5, and Fig. 36, it is very clear that all major crops from last 14-year data are in increasing trend in terms of cropping area, yield, and especially the average yield per hectare; the increase of average yield per hectare predicts the

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Fig. 28 Image of grown cotton crop

future of agricultural production of the province on the positive side. For example, the cropping pattern and yield of major crops for the last 6 years (i.e., from 2004–2005 to 2010–2011) have remained worth noting as under: Wheat in 2004–2005 area under crop was 887,400 ha and yield was 2827 Kg/ha, and in year 2010–2011 area under crop was 11,44,400 ha and yield was 3747 Kg/ha; cropping area increased by 22 % and yield per ha increased by 25 %. Rice in 2004–2005 area under crop was 5,43,900 ha and yield 2757 Kg/ha, and in year 2010–2011 area under crop was 3,61,200 ha and yield 3406 kg/ha; cropping area decreased by 51 % (the reason is Sindh province was the most affected region due to floods of cropping year 2010–2011) even though yield per ha increased by 19 %, and if we compare cropping year 2008–2009 with that of 2004–2005, then the area under crop was 7,33,500 ha and yield 3459 Kg/ha; here cropping area increased by 26 % and yield per ha increased by 25 %. Cotton in 2004–2005 area under crop was 6,35,100 ha and yield 808 Kg/ha, and in year 2010–2011 area under crop was 4,57,000 ha and yield 1316 Kg/ha; cropping area decreased by 39 % (the reason is Sindh province was the most affected region due to super floods of cropping year 2010–2011) even though yield per ha increased by 39 %, and if we match cropping year 2008–2009 with 2004–2005, then the area under crop was 651,500 ha and yield 902 Kg/ha; here cropping area increased by 2.5 % and yield per ha increased by 10 %.

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Fig. 29 Image of ready cotton crop (Source: SARSO Sindh, Pakistan)

Sugarcane in 2004–2005 area under crop was 2,14,900 ha and yield was 43,543 Kg/ha, and in year 2010–2011 area under crop was 2,26,500 ha and yield 60,779 Kg/ha; cropping area increased by 5 % and yield per ha increased by 28 %. From Table 5 it is clear from colored data and from Fig. 36 that the yield of major crops has gone under speedy increase in the last 6 years. The yield of wheat was 3747 Kg/ha and the yield of rice was more than 3400 Kg/ha. However, it is also observed through data that some of the districts of Sindh Nawabshah and Khairpur were receiving the yield wheat around 4000 Kg/ha, while from field visits and meeting with progressive zamindars (land growers), the maximum was around 6000 Kg/ha. It is also observed through data and field visits that some of the paddy-growing districts of Sindh, Larkano, Shikarpur, Jacobabad, and Kandhkot, Kashmore, were getting paddy (using hybrid seed) yield around 5930 Kg/ha on average and some of the progressive zamindars (land growers) of the same area get yield maximum around 7907 Kg/ha. From Figs. 37 and 38, evaluating the yield of wheat and rice in Sindh with the rest of the world’s most advanced in yield of wheat and rice, the province of Sindh is 3747 Kg/ha, France 7280 Kg/ha, Germany 7750 Kg/ha, and the USA 8250 Kg/ha of wheat. Likewise, the yield of rice crop in Sindh is 3406 Kg/ha, the USA is more than 8000 Kg/ha, and Egypt is even more than 10,000 Kg/ha. But it is worth mentioning here that Sindh province has the capability to yield wheat of

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Fig. 30 Image of grown wheat crop (Source: SARSO Sindh, Pakistan)

4000 Kg/ha to 6000 Kg/ha and rice about 6000 Kg/ha to 8000 Kg/ha as mentioned in the above paragraph regarding progressive land growers. The province of Sindh has the capability of improving its yields as the trend shows in Fig. 36; the only requirement is the proper management of irrigation system and utilization of modern technologies and machinery while educating the farmers, tenants, and land growers.

The Rain-Fed (Nonirrigated) Area of Sindh There are three prospective areas in Sindh where rain feed can be achieved; these are Thar desert, Khirhar hills, and Ubhan Shah hills; as shown green areas are canalirrigated lands, while white areas are the rain-fed areas in Fig. 39 (Lashari and Mahesar 2012). From Fig. 36, it is clear that the yield of major crops is on increasing trend but it is still low at national levels as of some progressive land growers are getting even more than the yields shown in Fig. 20, it means there is a potential gap that should be filled to increase the yield. Another point of focus is the rain-fed areas which are almost ignored and less considered which require more consideration that will result in significant growth in the production and yield. The sustainable irrigated agriculture is under threat from a number of issues which include increasing need of

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Fig. 31 Image of wheat crop harvesting (Source: SARSO Sindh, Pak)

Fig. 32 Image of wheat grain (Source: SARSO Sindh, Pakistan)

water to meet raising population demand; poor maintenance of canal system causing inefficient service; waterlogging and salinity problems; excess use of groundwater resources resulting in exhausted groundwater aquifers, thus leaving large areas not viable for the poor farmers; insufficient field drainage system (even the existing field drainage effluent network not properly connected) which could dispose of agricultural effluent in due time; improper pricing or valuation of water; and scarce participation of consumers. Therefore, for the optimum production and crop yield, these areas need to be focused: competent and resourceful management including conservation of present water resources, equitable distribution of water in different areas and canal commands (from head to tail users), efficient drainage effluent interventions with well-connected networks for the maximization of crop

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Fig. 33 Image of grown sugarcane crop

production, and reforms to be introduced within institutions to make the managing organizations more responsive, efficient, and dynamic (Lashari and Mahesar 2012). The distribution and supply of irrigation water from head to tail has not remained reliable; people at the head get more water than the water users at the tail. As a result the set targets and objectives of irrigated agriculture are not being achieved, so the productivity is much lesser in quantity than it should have been. If reforms in irrigation sector are executed wholeheartedly, then farmers can play their important role to improve the productivity. Poor working of irrigation system since the 1960s is mainly due to water shortage which resulted into defective and unreliable supply, distribution, and finally inefficient use of irrigation water (Lashari and Mahesar 2012).

Biomass Residue of Agricultural Crops in the Province of Sindh It can be observed from Tables 6, 7, 8, and 9 in columns from a to f that the biomass residue of various crops such as wheat straw, rice husk, rice straw, cane trash, bagasse, and cotton stalk is in different ratios, which is given below. These ratios are verified on-site and from research studies (Cerqueira et al. 2010; Figs. 40, 41, 42, and 43). (a) Wheat and wheat straw ratio 1:1 (b) 20 % rice husk found as waste in paddy (c) Paddy and rice straw ratio 1:1

996 Fig. 34 Image of harvested sugarcane crop (Source: SARSO Sindh, Pakistan)

Fig. 35 Cropping pattern (Source: PARC)

(d) 23 % cane trash found as waste in sugarcane harvest (e) 30 % wet bagasse found as waste in sugarcane industry (f) Cotton and cotton sticks ratio 1:3

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Yield of major Crops in Sindh 4000

Yield Kg/ha

3500 3000 2500 2000 1500 1000 500 2010-11

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1999-00

1998-99

1997-98

0

Cotton Production Kg/ha (Sindh)

Wheat Production Kg/ha (Sindh) Rice (Paddy) Production Kg/ha (Sindh)

Fig. 36 Yield of major crops in Sindh Table 5 Yield of major crops in Kg/ha of Sindh province Cropping year 1997–1998 1998–1999 1999–2000 2000–2001 2001–2002 2002–2003 2003–2004 2004–2005 2005–2006 2006–2007 2007–2008 2008–2009 2009–2010 2010–2011

Wheat production Kg/ha 2374 2381 2623 2746 2401 2442 2473 2827 2947 3471 3446 3432 3390 3747

Rice (paddy) production Kg/ha 2671 2742 3075 3115 2514 2662 2599 2757 2901 2946 3060 3459 3423 3406

Cotton production Kg/ha 662 576 638 696 759 756 680 808 707 716 710 902 1145 1316

Sugarcane production Kg/ha 61,161 62,964 61,972 50,459 47,430 53,355 56,221 43,543 61,372 58,357 60,861 50,414 57,740 60,779

It may be observed from Tables 6, 7, 8, and 9 that annual average production of various agricultural major crops based on 14 years of data is a huge quantity which is given as under in Table 10. From Tables 6, 7, 8, and 9, the total biomass residue of various agricultural major crops of 14 years and its average production are given as under in Table 11.

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2010-11 Wheat 60000 Yield kg/ha

50000 40000 30000 20000 10000 0

Area (1000)ha Yield kg/ha Total Yield (1000)ton

Pak

France

Germany

U.K

1144.4

5400

3320

1940

3747

7280

7750

8250

25213.8

49300

25120

16000

Fig. 37 Wheat crop production and yield in the world

Yield kg/ha

2010-11 Rice 35000 30000 25000 20000 15000 10000 5000 0 Pak Area(1000)ha Yield kg/ha Total Yield (1000)ton

Egypt

U.S.A

Japan

China

2365.3

640

1370

1620

29800

630

3406

10100

8070

6660

6590

4930

4823.3

4200

7620

7850

13500

2050

Iran

Fig. 38 Rice crop production and yield in the world

Total average amount of agricultural residue biomass of Sindh = 13,634.34  103t/year.

Energy Content of Biomass Residue of Agricultural Crop in the Province of Sindh and Pakistan Keeping in view the availability factor, the different agricultural residue biomass is used as animal feed and also as a raw source of energy at local level; hence, we theoretically consider 40 % availability of above total average amount of agricultural residue biomass, i.e., 5354.73  103 t/year. Theoretically considering average calorific value of agricultural residue biomass 3500 KCal/Kg, then the theoretical energy content = 3500 KCal/Kg5354.73  106

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Fig. 39 Rain-fed and canal-irrigated lands (Source: Lashari and Mahesar (2012))

Kg = 1.91  1013KCal (heating value) if this amount of heat energy is multiplied by 4.81 for converting K Cal into KJ = 7.97  1013 KJ or KW-S. With this theoretical heat content if converted into electrical energy with 40 % overall power plant efficiency, then we have 3.2  1013 KW-S (el energy). Converting this for power plant to be installed, we’ll have 8.9  1010 KWh = 10,120 MWYear. Hence, the power plants of about 10,000 MW are possible to be installed in the province of Sindh with the use of only 40 % of single source by agricultural residue biomass of only major crops. By the end of the year 2013, the installed capacity of Pakistan is given in Table 12. Then, the 10,000 MW through agricultural residue biomass of major crops of Sindh province only will be 52 % of total installed capacity and 81 % of total fossil fuel installed capacity of Pakistan. As already mentioned, that the province of Sindh contributes significantly toward overall national production of major agricultural crops from the 14-year data (i.e., from financial years 1997–1998 to 2010–2011) shows an average of 14 % to maximum 17 % in 2010–2011 in wheat, average of 34 % to maximum 36 % in 2008–2009 in rice, average of 27 % to maximum 29 % in 2007–2008 in sugarcane,

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Table 6 Production of agricultural crop wheat and biomass residue in province of Sindh Wheat Cropping year 1997–1998 1998–1999 1999–2000 2000–2001 2001–2002 2002–2003 2003–2004 2004–2005 2005–2006 2006–2007 2007–2008 2008–2009 2009–2010 2010–2011 Total Average of 14 years

Area (000) ha. 1120.2 1123.7 1144.2 810.7 875.2 863.7 878.2 887.4 933.2 982.2 989.9 1031.4 1092.3 1144.4 13,876.7 991.19

Production (000) ton 2659.4 2675.1 3001.3 2226.5 2101 2109.2 2172.2 2508.6 2750.4 3409.1 3411.4 3540.2 3703.1 4287.9 40,555.4 2896.81

a Wheat straw (000) ton 2659.4 2675.1 3001.3 2226.5 2101 2109.2 2172.2 2508.6 2750.4 3409.1 3411.4 3540.2 3703.1 4287.9 40,555.4 2896.81

Table 7 Production of agricultural crop rice (paddy) and biomass residue in province of Sindh Rice (paddy)

Cropping year 1997–1998 1998–1999 1999–2000 2000–2001 2001–2002 2002–2003 2003–2004 2004–2005 2005–2006 2006–2007 2007–2008 2008–2009 2009–2010 2010–2011 Total Average of 14 years

Area (000) ha. 689.3 704.1 690.4 540.1 461.1 488.3 551.2 543.9 593.2 598.1 594 733.5 707.7 361.2 8256.1 589.72

Production (000) ton 1840.9 1930.3 2123 1682.3 1159.1 1299.7 1432.8 1499.6 1721 1761.8 1817.7 2537.1 2422.3 1230.3 24,457.9 1746.993

b 20 % rice husk (000) ton 368.18 386.06 424.6 336.46 231.82 259.94 286.56 299.92 344.2 352.36 363.54 507.42 484.46 246.06 4891.58 349.40

c Rice straw ratio 1:1 (000) ton 1840.9 1930.3 2123 1682.3 1159.1 1299.7 1432.8 1499.6 1721 1761.8 1817.7 2537.1 2422.3 1230.3 24,457.9 1746.99

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Table 8 Production of agricultural crop sugarcane and biomass residue in province of Sindh Sugarcane

Cropping year 1997–1998 1998–1999 1999–2000 2000–2001 2001–2002 2002–2003 2003–2004 2004–2005 2005–2006 2006–2007 2007–2008 2008–2009 2009–2010 2010–2011 Total Average of 14 years

Area (000) ha. 261.6 270.8 230.6 238.8 240.7 258.6 259.9 214.9 183.2 214.7 308.8 263.9 233.9 226.5 3406.9 243.4

Production (000) tons 15,999.6 17,050.7 14,290.8 12,049.7 11,416.3 13,797.6 14,611.8 9357.4 11,243.4 12,529.2 18,793.9 13,304.3 13,505.4 13,766.4 1,91,716.5 13,694.0

d Cane trash 23 % (000) ton 3679.908 3921.661 3286.884 2771.431 2625.749 3173.448 3360.714 2152.202 2585.982 2881.716 4322.597 3059.989 3106.242 3166.272 44,094.795 3149.6

e Bagasse 30 % (000) ton 4799.88 5115.21 4287.24 3614.91 3424.89 4139.28 4383.54 2807.22 3373.02 3758.76 5638.17 3991.29 4051.62 4129.92 57,514.95 4108.2

Table 9 Production of agricultural crop cotton and biomass residue in province of Sindh Cotton

Cropping year 1997–1998 1998–1999 1999–2000 2000–2001 2001–2002 2002–2003 2003–2004 2004–2005 2005–2006 2006–2007 2007–2008 2008–2009 2009–2010 2010–2011 Total Average of 14 years

Area ha. (000) 600.3 630.2 633.5 523.6 547.4 542.6 561.4 635.1 637.1 570.1 607.4 651.5 634.7 457 8231.9 587.99

Production (000) bales (375 lbs each) 2335.5 2134.1 2377.4 2141.1 2443.2 2411.8 2242.8 3016.7 2648 2398.2 2536.2 2978.3 4270.7 3536.8 37,470.8 2676.49

f Cotton stalk ratio 1:3 (000) ton 1192.2 1089.0 1212.5 1093.3 1246.4 1230.6 1145.3 1539.5 1351.3 1224.6 1293.8 1763.0 2180.2 1804.2 19,365.78 1383.3

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Sindh Province 1997-2011. 5000 4500

(000)

4000 3500 3000 2500

Wheat Area (000) ha.

2010-11

2009-10

2008-09

2007-08

2006-07

2005-06

2004-05

2003-04

2002-03

2001-02

2000-01

1999-00

1998-99

0

1997-98

2000 1500 1000 500

Wheat Production(000) Ton Wheat a wheat straw(000) Ton

Fig. 40 Wheat crop and biomass residue wheat straw

and average of 23 % to maximum 33 % in 2009–2010 in cotton (Pakistan Statistical Year Book of 2008 and 2011). Production of agricultural residue biomass in Pakistan is shown in Table 13 (by the production of major crops data of major crops Pakistan Statistical Year Book of 2008 and 2011) on same considerations as Table 11 for Sindh agricultural residue biomass. Total average amount of agricultural residue biomass of Pakistan = 60,088.05103 t/year as shown in Table 13. If the 35 % above total biomass agricultural residue produced in Pakistan could be utilized, about 39,026 MW can be produced, which is very near to about 200 % of total installed capacity of all power plants in Pakistan. This shows that there is huge potential of biomass that is available in Pakistan which could be utilized to meet the energy requirement and can overcome the energy crisis problem. At present, Alternative Energy Development Board Ministry of Water and Power Government of Pakistan has planned two power plants based on biomass waste in the province of Sindh; the details are given as under: 1. 12 MW biomass to energy power plant at Mirwah Gorchani Town, Mirpur Khas, Sindh 2. 9 MW biogas power plant at Pak Ethanol, Matli, Sindh. Letter of interest (LoI) issued to Pak Ethanol (Pvt) Ltd. for setting up power plant

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Sindh Province 1997-2011. 3000 2500

(000)

2000 1500 1000

2010-11

2009-10

2008-09

2007-08

2006-07

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2004-05

2003-04

2002-03

2001-02

2000-01

1999-00

1997-98

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1998-99

500

Rice(Paddy) Areaha. (000)

Rice(Paddy) Production (000) Ton

Rice(Paddy) b 20% Rice Husk (000) Ton

Rice(Paddy) c Rise straw ratio (000) Ton

Fig. 41 Paddy/rice crop and biomass residue rice husk and rice straw

Sindh Province 1997-2011. 20000

(000)

15000 10000 5000

2010-11

2009-10

2008-09

2007-08

2006-07

2005-06

2004-05

2003-04

2002-03

2001-02

2000-01

1999-00

1998-99

1997-98

0

Sugarcane Area ha. (000)

Sugercane Production (000) Ton

Sugercane d Cane Trash 23% (000) Ton

Sugarcane e Bagsse 30% (000) Ton

Fig. 42 Sugarcane crop and biomass cane trash and bagasse

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Sindh Province 1997-2011. 4500 4000 3500

(000)

3000 2500 2000 1500 1000

Cotton Area ha. (000)

2010-11

2009-10

2008-09

2007-08

2006-07

2005-06

2004-05

2003-04

2002-03

2001-02

2000-01

1999-00

1998-99

0

1997-98

500

Cotton Production (000)bales (375 Ibs each)

Cotton f cotton Stalk ratio 1:3(000)Ton

Fig. 43 Cotton crop and biomass residue cotton stalk

Table 10 Annual average productions based on 14 years of data of various agricultural major crops of Sindh

Crop Wheat Rice (paddy) Sugarcane Cotton

Production (000) ton 2896.81 1746.99 13,694 2676.5(000 bales, 375 lbs each)

Future Directions Pakistan is bestowed by God with such great potentials which need to be exploited properly; it has such a climate with temperatures ranging from 50  C to +50  C; though we are facing difficulties with modernizing our agricultural and irrigation systems with the world today, still it has sufficient food to feed its population and to export, but there remains huge gap to be filled. Our irrigation system is one of the largest systems of the world, and our agricultural command area is so expanded and large that it can also be compared to the huge agricultural commands of Egypt and Mexico. Our agricultural lands have capability to produce yields to the world’s best producing countries; to get such yields we have to improve all our systems related to agriculture as it is the backbone of our economy. To achieve such targets of which our agricultural lands and irrigation system are capable of, we must interlink various sectors which are helpful and beneficial to our agroeconomy. For this task, the irrigation department, agriculture department including farm water

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Table 11 Production of agricultural residue biomass for Sindh province Biomass total production in Category Agribiomass residue 14 years (million tons) a Wheat straw (000) ton 40.56 b Rice husk (000) ton 4.90 c Rice straw ratio (000) ton 24.50 d Cane trash (000) ton 44.10 e Bagasse (000) ton 57.52 f Cotton stalk ratio (000) ton 19.40 Total average amount of agricultural residue biomass of Sindh (000) ton/year

Table 12 Total power installed capacity of Pakistan by 2013

Oil and gas Coal Total fossil fuel installed Others Total installed as a whole

Average production per year (000) tons 2896.81 349.40 1746.99 3149.63 4108.21 1383.30 13,634.34

12,340 160 12,500 6860 19,360

MW MW MW MW MW

Table 13 Production of agricultural residue biomass for Pakistan Category Agribiomass residue a Wheat straw (000) ton b Rice husk (000) ton c Rice straw ratio (000) ton d Cane trash (000) ton e Bagasse (000) ton f Cotton stalk ratio (000) ton Total average amount of agricultural residue biomass of Pakistan (000) ton/year =

Average production per year (000) tons 20,947.40 1034.35 5171.77 11,780.10 15,365.33 5789.10 60,088.05

management, revenue department, and finance department should be interlinked starting from union council level by a focal person from each department to resolve related issues and to report to the higher authorities; every complaint must be recorded online and weekly progress-based reporting should be submitted, and to tackle the issue related to water with proper and well-connected agricultural drainage effluent networks, modernizing agriculture with farm water management and farm power machinery while at the same time educating the farmers, tenants, and land growers and revenue collection should be made accordingly while financing the growers and the tenants for better yields and proper pricing of the crops. As our economy is agrobased, hence research and development must be carried out in

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every sector to improve our irrigation system, effluent drainage system, and agriculture at large. Better yields will result in more production of agricultural residue biomass; consequently, we will have better economy at grassroots levels and poverty reduction, and we will be able to cater our energy requirements by utilizing some portion of agricultural residue biomass which is our own resource; this will further improve our economy.

References (1999) Solid waste management in Asia. Hoornweg, Daniel with Laura Thomas. Working paper series no. 1. Urban Development Sector Unit. East Asia and Pacific Region (2001) A comprehensive research on Pakistan’s issues concerning garbage disposal and Government & Social efforts to improve them (2002) The art and science of composting, A resource for farmers and compost producers. Center for Integrated Agricultural Systems (2006) Techno-economic disposal of hospital wastes in Pakistan. J Med Res 45(02) (2009) Environmental and Social Management Framework (ESMF), 4th edn (2010) The 3 Rs of reducing solid waste: reuse, reduce & recycle, Margaret Cunningham (2011) Characteristics of emissions from municipal waste landfills. Environ Prot Eng 37(4) (2013) Revisiting Solid Waste Management (SWM): a case study of Pakistan. Sustainable Development Policy Institute Islamabad Pakistan. Int J Sci Footprints Ahmed SI, Johari A, Hashim H, Mat R, Alkali H (2013) Landfill gas and its renewable energy potentials in Johor. Malaysia Int J Emerging Trends Eng Dev Issue 3:1 Asian Productivity Organization (2004–2005) Solid waste management: “issues and challenges in Asia”. Report of the APO, Survey on solid waste management, Asian Productivity Organization, Japan, 2004–2005 BC Ministry of Environment (2013) Landfill criteria for municipal solid waste, 2nd edn. BC Ministry of Environment, Victoria Cerqueira L, Edye LA, Wegener MK, Scarpare F, Renouf MA (2010) Report on “optimising sugarcane trash management for bio fuels production in Australia and Brazil” 2010 Director General Pak EPA, Environment, economic analysis of resources efficiency policies, Final report, August 2011 Draft guidelines for Solid Waste management, Pakistan Environmental Protection Agency, June 2005 http://en.wikipedia.org/wiki/Bagasse International Environmental Technology Centre (UNEP) (2005) Solid waste management. International Environmental Technology Centre (UNEP) Kiani A (2008) TFP and MIRR in the agricultural crop sub- sector of Sindh. Eur J Soc Sci 7 Landfill manuals, landfill design, U.S, Environmental Protection Agency, 26 July 1993 Lashari BK, Mahesar MA (2012) Potentials for improving water and agriculture productivity in Sindh, Pakistan. Sixteenth international water technology conference, IWTC 16 2012, Istanbul Rice Knowledge Bank http://www.knowledgebank.irri.org/ The Basel convention on the control of hazardous wastes and their disposal adopted on 22 March 1989 by the conference of Plenipotentiaries in Basel, Switzerland United Nations, Environment Program (2009) Developing Integrated Solid Waste Management plan, training manual van Steen Bergen F (2014) Water charging in Sindh, Pakistan – financing large canal systems. Meta Meta Research

The Advanced Recycling Technology for Realizing Urban Mines Contributing to Climate Change Mitigation Tatsuya Oki and Toshio Suzuki

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Recent Development of Urban Mines in Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . From “Quantity Recycling” to “Quality Recycling” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Technical Challenges of Quality Recycling: Liberation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Technical Challenges of Quality Recycling: High-Quality Separation . . . . . . . . . . . . . . . . . . . . “Strategic Urban Mining” that Japan Aims for . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Missing Link of Resource Circulation and Resource Circulation Interface Function . . . . . Aiming for Establishing Strategic Urban Mines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Prospects of Strategic Urban Mines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Coping with sustainable civilization and utilization of renewable energy, climate change mitigation is one of the big challenges. Obtaining metal resources from urban mines (waste) for supporting the civilization of human races will contribute not only to support sustainable development of civilization society to the future but also to mitigate climate change. Urban mines are one of the promising resources especially for poor natural metal resource countries such as Japan. Fortunately, Japan is one of the major rare metal consumers and also is capable of smelting rare metal by its own. Japan’s urban mine will be more practical with top class recycling technology. In addition to these technological developments, it T. Oki (*) National Institute of Advanced Industrial Science and Technology (AIST), Onogawa Tsukuba, Ibaragi, Japan e-mail: [email protected] T. Suzuki National Institute of Advanced Industrial Science and Technology (AIST), Nagoya, Japan e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_69

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is necessary to reform the society system in order to realize productive and economical urban mines which overcome the natural mine. Furthermore, in order to continue a steady development of rare metal recycling, it is necessary to conduct well-planned technology development based on the prediction of the future material usage. In this chapter, the authors show the technical subjects for realizing total circulating usage of metal resources including rare metals and an attempt currently tackled in Japan.

Introduction Huge metal resources are needed to support the civilization of mankind. Not only developed countries but also the remarkably developing Asian region has been consuming metal resources. In the past time, a lot of metal resources have been acquired from natural mines. Although a true depletion of the resources may be in the far future, the metal content of mines continues to decline gradually, and the amount of associated heavy metals and radioactive substances tend to increase. Total material requirement (TMR) which indicates the total amount of material usage to produce 1 ton of metal is usually utilized to compare the material consumption for production (Yamasue et al. 2009). For example, copper ore grade is decreasing year by year worldwide; as a result, the TMR of copper is increasing. This means that total energy consumption involved in the copper production increases. TMR increases especially for minor metals, which nowadays are very important for supporting advanced industries. Japan is being the world’s largest minor metal-consuming country (in Japan, 47 species of minor metal are called “rare metals,” as shown in Fig. 1), while the production of rare metals tends to be monopolized by certain countries and the world production volume of each rare metal is small. Therefore, the access to these metals can be easily restricted by the control of the production. In addition, environmental destruction is becoming a serious problem because the regulation for metal production is not well effective in such areas. Figure 2 shows the estimated UO (urban ore)-TMR compared with NO (natural ore)-TMR (Yamasue et al. 2009). As can be seen, utilization of urban ore is already effective for minimizing the total energy consumption for almost all metal elements, and thus utilization of UO is considered to lead to mitigate the climate change in the future. In addition, considerably not far in the future, some of the metals are suspected to fall into critical shortage, and as a result, it is considered that maintenance of the substance society could be threatened. Deterioration of metal production efficiency and increase in the metal consumption mean an increase of the energy consumption for maintaining civilized society, which easily impacts on the climate change, too. Thus, an improvement of rare metal production technology for suppressing energy consumption for the metal production will be a significant step for climate change mitigation as well.

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Fig. 1 Definition of the rare metals in Japan Fig. 2 The estimated UO-TMR compared with NO-TMR (From Ref. Yamasue et al. 2009)

On the other hand, almost all metal products remain somewhere on earth after usage. Some of them are soluble in water, but basically they exist in the solid state. According to the law of conservation of mass, most metals yielded ever from natural mines stay somewhere on earth, accumulated in the close area of human activities. Even in the narrow land of Japan, it is said that the total amount of accumulated metals in Japan is to surpass the annual metal consumption in the world. Thus, used products that are accumulated in the land have become to be called “urban mines.” Most urban mines include products that have been routinely used without harmful substances and radioactive materials and are considered to be relatively safe

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resources. Even when the metal quality of urban mines is not as high as that of natural mines where metals are concentrated by taking an enormous amount of time, for urban mine, it is possible to control of the distribution and concentration of the waste products for easy recycling. In the future, it will be possible to deliberately control the formation of urban mines, which will contribute not only to the sustainable development of civilized society but also to suppression of energy consumption due to the metal production, by extension, to contribute to climate change mitigation. Although Japan is poor in natural resources, Japan has been supplying high-tech products to the world by importing the raw materials produced from natural mines overseas over the years. In recent years, however, due to the rise of resource nationalism, one experienced the soaring of metal prices and the imminence of supply itself. From such a background, a strategy is considered to attempt to collect resources, including rare metals from urban mines, and the strategic program has been carried out in Japan for the first time in the world. The purpose is not for recycling to reduce diffusion and waste of harmful substances but for thorough resource recovery. In this chapter, the recent efforts of the strategy in Japan will be shown, and a discussion will be presented on the development of urban mines that realize sustainable civilized society and the relaxation of climate change.

Recent Development of Urban Mines in Japan From “Quantity Recycling” to “Quality Recycling” Japan relies for most of the natural metal resources to support its manufacturing industry on imports from abroad, and in recent years Japan encountered a situation that stable supply of the resources, especially “rare metals,” has been imminent by sudden export restriction and steep rises in metal prices. Since the characteristic of each rare metal is different from each element, it is difficult to be replaced by other rare metals, unlike energy resources. Therefore, even when weight-wise the usage of rare metals is negligible in the products, the shortage of the supply can lead to the stop of the production. True depletion of metal resources is considerably ahead of the future, and a sufficient amount of metals should exist somewhere on earth; however, the stable supply is not a guaranteed issue. In addition, production efficiency of natural metal resources in the process will gradually decrease toward the depletion, which will require enormous energy and cost. This will become a significant impact on the manufacturing industry and the world economy. By keeping the current situation that the society strongly depends on the natural metal resources, the world will become unsustainable at some point. On the other hand, the metals from natural mines, always, exist somewhere on earth. Most of them are already buried as wastes; some are used in the social infrastructure. Fossil energy disappears once it is used. Organic resources such as resin and paper are not possible to use repeatedly for a long period of time. However, the metals can be recycled forever in theory. Even if they lose product value, they still have industrial

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value in the element itself; the smelting process can completely restore the original raw material. The amount of recyclable metal is dependent on the degree of living standards and population in the area. Used products that are accumulated in a certain area (city) are called “urban mine” in contrast to the natural mine. In urban mine, resources can be acquired by recycling technology, not mine technology for a natural mine. Currently still good natural mines exist, and developing urban mines is not economical since recycling technologies are still costly. However, as the extraction of natural mines progresses to reduce the amount of reserves, the amount of reserves for urban mines increases. As described above, with the decline of natural mine production efficiency, one day, development of urban mines would become economically realistic. The pseudo-phenomenon actually occurred in Japan around 2010 due to import restrictions from soaring overseas metal prices. Therefore, in Japan, the development of urban mines was seriously considered in order to adapt the critical situation. In Japan, recycling has been actively carried out since 1990. At the time, recycling was encouraged due to the shortage of waste disposal sites, and the aim of recycling was to reduce the amount of wastes, the so-called quantitative recycling. Target materials are abundant materials such as resin, glass, iron, and aluminum, and a major goal is to reduce the volume of wastes, not to recover the resource to reuse. Until now, mass metals such as iron, aluminum, and precious metals have been recycled. But this time, “rare metal,” which is not used in large quantities and not expensive as precious metals, attracted attention the most. Rare metals are also called “vitamins for industry” in Japan. Even if the usage is negligible, without it, it is no longer possible to manufacture a number of high-tech products. That temporal collapse of the balance of supply and demand, the situation that would be anticipated in the future, would be completely upsetting Japan. Currently, there are few metal mines running in Japan, and raw materials have been imported and consumed by 120 million of Japanese people over the decades, and the several decades worth of materials has been accumulated in the national territory. This situation cannot still be called “urban mines” until the resource can be retrieved within a certain economy. While natural mines are formed by concentrating resources over incredibly long time, urban mines are not naturally formed by gathering a large amount of waste products. In other words, “urban mines” are not something to look for but to be intentionally developed (urban mining). Actually, urban mine development technology that realizes the reduction of the entropy of metal spread in land should be efficient and economical. When the urban mine development for retrieving rare metals was started in Japan, landfilled and reused wastes were not targeted, but the products owned by each person, “hoarding goods.” The hoarded goods refer to digital home appliances that were not in use, sleeping in a desk drawer without being discarded. In the early stage of urban mine development in Japan, where recycling infrastructure associated with the legislation in the 1990s is well established, it is thought that the rare metal can be easily recovered once the hoarded goods from the public are collected. The recovery operations of rare metal from small household appliances

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in the designated area were conducted in 2008 in Japan. However, in reality, it was not possible to recycle the rare metals utilizing the existing recycling facilities. Currently, among metals contained in the waste products, only noble metals (gold, silver, platinum, palladium, etc.) and some of base metals (iron, aluminum, copper, etc.) are recycled. Rare metals except for platinum and palladium are rarely recycled from waste products once available in the market. To realize the recovery system of rare metals from waste products, at least two problems must be overcome. First, used products widely spread to the consumers need to be stably collected when they are discarded. This requires the construction of rules and social systems. Second, it is required to develop the technology that realizes a high purity metal extraction from the collected waste products, high enough to be directly used by rare metal smelting and raw material manufacturers. Although rare metal density is relatively high in small appliance wastes, the system for collecting these product wastes systematically did not exist until recently. Therefore, Small Appliances Recycling Act was made effective in Japan in 2013. It made it possible to collect small appliance wastes widely across the administrative area, being one breakthrough for the first problem. No obligation, however, exists on rare metal recovery. Without overcoming the latter technical problem, recycling of metals will only stay on recovering precious metals and part of the base metal even for small appliances wastes. Unlike recycling a conventional iron and aluminum used in construction materials, various rare metal concentrations in the waste products are about several hundreds to several thousands ppm. Thus, there exists a technical leap for recycling rare metals from small appliances in traditional recycling infrastructure, like trying surgery by using the pickaxe. At this time, “quality recycling” was started to be more paid attention to than “quantitative recycling,” and the need for technological transformation had been widely recognized around 2010 in Japan.

Technical Challenges of Quality Recycling: Liberation Physical Sorting Techniques and the Composition of the Waste Products Because the amount of rare metals in waste products is very low compared to construction materials such as iron and aluminum, economical recovery of rare metals is difficult, and it is not practical to use hydrometallurgy processes with chemicals. Pyrometallurgy processes with high temperature, which are effective methods for recovering low concentrated copper and precious metals, are not ideal either because most of rare metals thermally dissolve and disperse into glass slug. Thus, it is of importance to separate copper and precious metals from the waste products by physical sorting before using smelting processes for rare metals. Development of low-cost physical sorting technology will be a key for realizing low concentrating rare metal recycling systems. Each waste product is thought to be consisting of various metal particles (hybrid particles) including rare metal particles. High purity sorting of rare metal strongly relies on the concentration and dispersion of the rare metal particles in the products.

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Fig. 3 Schematic image showing the existence status of rare metal in the waste product

Figure 3 is a schematic image showing the existence status of rare metal in the waste product. As can be seen, rare metal X is one of more than ten rare metals used in a smartphone and is considered to be concentrated by physical sorting. It is a great possibility of recovery if the concentration of the rare metal X is high enough after sorting. On the other hand, the possibility also depends on the dispersion of the rare metal X in the product. Here, dispersion is defined as the domain size (or distribution) of the rare metal X in the product. If the domain size is larger or the rare metal is concentrated in a particular area in the product, the dispersion of the rare metal X is considered to be small. Rectangular boxes in Fig. 3 show the rare metal X distribution in the product (smartphone). Status A is the best for physical sorting processes. The rare metal X exists in high concentration, locally in the product. In this case, it is quite easy to separate the particles with highly concentrated rare metal X from the rest of the particles by crushing or dismantling processes. This process is called “liberation – single separation.” This is a very important operation in the physical sorting process and will be discussed later. Status A is not only easy for single separation but also for the rest of sorting operation due to the fact that the concentration of the rare metal X is high in the particles. The next best status for physical sorting is Status B at the upper left in Fig. 3. Even though the total amount of the rare metal X is low, it is expected to have liberation as good as Status A. Only this will cause difficulty at the latter operations in the process due to small amount of the rare metal X. Status C, even though the concentration of the rare metal X is high, is more difficult for liberation due to high distribution of X in the product. Status D is the worst scenario for physical sorting processes. In the case of a smartphone, they

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typically have maldistribution of elements in the product, and thus it is not possible to apply physical sorting for single separation – liberation. Rather, they require very fine crushing processes to extract rare metal X. The required particle size after crushing totally depends upon the dispersion of the rare metal X. Usually, ordinal sorting processes can be applied down to several micron particle size, and it is not possible to apply physical sorting if liberation cannot be achieved still in this particle size. Even when the liberation is possible for such small particles, it requires large amounts of energy for fine grinding. In addition, as discussed later, it also requires separation processes in the wet condition for less than 0.5 mm particles, while the millimeter size of particles can be applied to dry separation processes. The wet processes require another electric power for pumping water, water treatment process unit, which adds more energy consumption and cost. The product obtained by wet process is still not as good as that by dry sorting processes in the millimeter range. There is a trade-off between the purity and the recovery of X. Thus, the combination of fine grinding and wet separation processes is the last to be chosen in the physical sorting processes. These processes, however, are cost-effective compared to chemical processes and are effective for collecting the rate metals that are considered to be difficult to recycle. In the case of electrode and fluorescent materials that are used as fine powder, no crushing process is required and can be applied to wet sorting process in the ordinary recycling facility.

Importance of Liberation Physical sorting processes for collecting metals from waste products require the decomposition of “hybrid” components into small “individual element” pieces in the first step. Large products may be decomposed by hand, and then, the pieces are sent to crushing processes. In many industrial processes, the purpose of crushing is to obtain uniform fine particles from complex particles, and the processes improve physical properties of the particles such as mobility, processability, and reactivity (Owada 2007). On the other hand, the goal of the physical sorting is to complete liberation. The ideal status is that a single element is a single particle. The element that is the target material for recycling can be atom, alloy metal or parts, etc. In the case of the particle including more than two elements, it is called “locked.” It would be no problem when the locked material includes highly concentrated target material, and crushing processes would be effective for such locked constituents. If it is not the case, it is not possible to improve the purity of the element by utilizing physical sorting only. In the course of physical sorting processes, the crushing process is considered to be a pre-sorting process to realize the status of liberation, single separation of the target particle. Figure 4 shows the 2D matrix model of liberation process, proposed by A. M. Gaudin (1939). It is a classical model, yet not enough for modeling the actual situation, but it helps in the understanding of the concept of liberation. Figure 4a shows the status before the crushing process, including target material in the matrix. “a” in the matrix is the size of locked and assuming that the product is cut into pieces

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Fig. 4 2D matrix model of liberation process

uniformly with the size of “a,” as shown in Fig. 4b, not influenced by the interface between the target material and the matrix. Some particles can be the status of liberation, but in the most of the pieces, the target material is still the status of locked. Another crushing process, the size less than “a,” may lead to liberation status for the target material. In the actual process, such random crushing does not likely occur and the status of liberation can be easily obtained. Only the efficiency can be different for each crushing method; thus, wise choice of the method is crucial in order to realize high-quality liberation. Figure 5 shows the schematic image of the relationship between progress of liberation and nonuniformity of crushed pieces. Let us consider Status A in Fig. 3 and apply crushing process in order to liberate the rare metal X. As crushing time proceeds, the particles become finer, and, eventually, particles of rare metal X are liberated. If this happens in a short period of time, which is the best scenario, the Status A shown in Fig. 5 will be realized, which leads to best pretreatment for physical sorting process. On the other hand, if longer crushing process time is required for liberating rare metal X, finer particles tend to be obtained, being Status B in Fig. 5 that is relatively difficult for physical sorting. Typically, Status B includes a wide range of particle size distribution, and it is almost impossible to collect particles under several microns by physical sorting process. Therefore, even when the nonuniformity of individual particle is realized, toward the right-hand side in Fig. 5, the status of well-mixed finer particles makes it difficult to separate the target particle. Also the same is applied to Status C in Fig. 5 where all particles are locked. To summarize, the process of liberation refers to achieving nonuniformity of individual particle by sacrificing the nonuniformity of the target material in the crushed product. The ideal situation is that nonuniformity of both individual particles and the target material is realized. Solid and broken lines in Fig. 5 show when the selective, optimized crushing process and random crushing process, respectively, are selected, which shows the idea of actual crushing process. Selective crushing is a very important technique to realize liberation at the coarse particle size. In order to realize efficient selective crushing, it is important to proceed to the breakup at the boundary

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Fig. 5 Schematic image of the relationship between progress of liberation and nonuniformity of crushed pieces

of the rare metal X domain and the matrix. Since the waste products’ properties are different, even considering culler phone, each one has different structure; strength, depending upon the model; manufacturer; and year of product; there is no all-fitted selective crushing machine. Currently, the selective crushing property of particular products is investigated by utilizing an existing crushing machine. Study of theoretical and systematic approaches is expected for realizing ideal selective crushing process.

Grinding Method Aiming at the Promotion of Liberation Mechanical Crushing Mechanical crushing is one of most realistic choices for early introduction to actual recycling plants. Mechanical crushing tends to break up products uniformly, and it is not easy to break up only at the interface as shown in Fig. 6a. It may, on the other hand, be possible to expect selective crushing as shown in Fig. 6b or c if there is a difference between mechanical properties of the target and the matrix. Figure 6b can be realized by combining thermal treatment and crushing processes, which were actually applied to the process for separating bone steel from concrete wastes (Mitsubishi Material Co, Ltd 2003; Matsumura 2003). Figure 6c can be realized by combining stirring and surface friction destruction processes.

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Fig. 6 Example of selective crushing for liberation

Not many cases are reported for metal recycling using mechanical crushing, but there is one good example, printed circuit boards. Actually, for the recycling of metal (copper) from the printed circuit board, the swing-type hammer mill process machine was applied, and it was found that the copper could be recycled as sphere particles due to its ductility (Furuyanaka et al. 1999). The selectivity of metal and nonmetal parts in the printed circuit board can be further improved by controlling the operating condition of the machine. Other new processes are also under development (Koyanaka et al. 2006; Furuyanaka 2006; Koyanaka et al. 2006). One of them is the so-called active crushing method. It controls multiple operating conditions of impact crushing simultaneously during the actual operation. Single separation of target material, control of particle size, and ejection of crushed materials are optimized timely and continuously during the crushing operation. Figure 7a shows the schematic image of the active crushing system (Furuyanaka 2006; Koyanaka et al. 2006). The system is based on the fast swing-type hammer mill, and the inverters for controlling hammer and feeder, electric air valve, and servo amplifier are connected to a PC, in which a certain operating pattern is programmed for automatic operation. In addition, the shape of the lining plate is also specially designed. Figure 7b and c shows examples of operating patterns for the speed of impact and the period of opening screen, which were actually applied to crushing circuit boards for TV after crushed using the cutter mill. As can be seen, the speed of hammer increases to 60 m/s with (b) 14 s and (c) 3 s, respectively. Using the pattern (c), one could obtain the metal separation efficiency of 50.6 %, with average particle sizes of 421 μm and 188 μm for metal and nonmetal, respectively. It was also shown that 59.6 % efficiency could be obtained by further optimization (Fig. 7b). As can be seen, accurate operation of mechanical crushing can provide realistic liberation of target materials. Not much verification so far is reported, but it is expected to increase the application of such techniques on recycling for portable devices. Electrical Crushing In order to realize the liberation of target materials without excess crushing, it is ideal to have selective separation at the boundary of target materials and the matrix.

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Fig. 7 (a) Schematic image of the active crushing system and (b, c) examples of operating patterns

Ordinal mechanical crushing methods, on the other hand, tend to result in uniform breakage, and it is difficult to crush designated area only. Therefore, electrical crushing is being considered, which allows crushing selectively along the boundary of the target material and the matrix. Mainly, there are two electrical crushing methods: electrical disintegration (ED) and electrohydraulic disintegration (EHD) methods. The ED method utilizes high voltage and large current in the liquid where particles (consisting of target material and matrix) are dispersed in a container. The particles are close to or touched at one electrode, and the other electrode is placed at

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the other side of the container. The high-voltage pulse of several 10 kV in several 10 μs is applied, so the large current only flows at the boundary in the particles that leads to crush the particles along the boundary (Fujita et al. 2002). Many studies are reported especially for rocks, coals, and concretes and, in recent years, for liberation from used products on recycling purposes. For example, the method was applied to liquid crystal panels used for cellular phones and laptop computers, and it was confirmed that the panel was separated into two glass substrates, and indium (ITO) could be collected after different treatments (Shibayama et al. 2002). The EHD method, on the other hand, utilized a shock wave generated by the large current flow in the liquid (Fujita et al. 2002). Explosives can be utilized instead of using the current flow. In either case, the shock wave generates tensile stress at the boundary and promotes selective crushes along the boundary. In the case of the cellular phone, it was reported that the shock wave propagated along the boundary between metal and resin and confirmed that metal parts were removed from the matrix (Kejun et al. 2001). As explained above, the electric crushing for liberation of used products is under development, and in the near future, it has a potential to be an innovative recycling method; however, it may also be difficult to introduce in the existing facilities due to the use of large current or explosives. Alternative Technologies for Hand Dismantling and Picking: Easy Sensing The most certain way to break up a complex product into pieces is dismantling. Dismantling is usually done by hand, while crushing is done by machines, and industrial robots may take human’s place for dismantling processes in near future. From the technical point of view, dismantling is defined as liberating operation for individual product, while crushing as liberating operation for massed products. Thus, crushing is much more efficient and also cost-effective compared to dismantling. Nevertheless, hand dismantling is still the major method for recycling because it is an easier process for liberation. Actually, even in Japan (where the labor cost is considered to be higher), hand dismantling is applied for recycling motors, which are relatively large pieces, from used appliances. Since there is no almighty method for liberation, hand dismantling is still applied in many cases, even in some that are not cost-effective. Another advantage of hand dismantling is that breaking up and separation of pieces proceed in the same time. Although this method is very useful for applying for the variety of products, there is a limitation of this method from economical point of view, especially in Japan. Thus, the development of automated dismantling machines has been carried out, and some processes are successfully automated, for example, sorting process utilizing advanced sensing technology. This technology is very useful for getting rid of impurities from the uniform particle, but it cannot be applied to widely scattered pieces from dismantled products. Under circumstances, the authors have been developing a cost-effective sorting machine utilizing “easy sensing” technology, alternative technologies for hand dismantling and picking. Instead of using expensive, high-performance sensors, this machine utilized a combination of cost-effective sensors, which were close to human sensibility, and highly controlled operation procedure based on the nature of target products.

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Fig. 8 Automatic collection of Nd magnet from HDD by HDD cutting separator (HDD hard disk drive)

For example, the authors have proposed a two-step crushing separation method for collecting neodymium magnets including rare-earth metal from hard disk drives (HDDs), “HDD cutting separator (HDD-CS)” as shown in Fig. 8. When HDD is normally crushed, the very strong neodymium magnets can be attached inside the crushing machine and cause many problems such as blockade at the screen. Even though they are luckily extracted out of the machine, they are agglomerated with metal pieces and not possible to be liberated. Thus, demagnetization process is typically applied in such case. Neodymium magnets have relatively low Curie temperature and can be demagnetized at around 350  C. However, it is not costeffective to use thermal energy only for extracting the magnet, 2 wt% of HDD, meaning that it requires 50 times more thermal energy for demagnetization. The HDD-CS solves such a problem by utilizing four magnetic sensors and location sensors that identify the leakage magnetic flux density and the position of magnets in the HDD without destruction. Then, the magnet is punched out with a nonmagnetic cutter. The accuracy of sensing is kept improving by optimizing the machine using the database of the leakage magnetic flux density for each HDD. This, small and cost-effective, machine realizes an automatic separation process of 400,000–1,000,000 HDD per year and can concentrate the magnet component ten times. After demagnetization, impact crushing, and screening processes, 94–97 % of magnetic alloy particles are successfully collected (Oki et al. 2011). Another “easy sensing” technology, called “Arena Sorter,” a sensor-based sorting technology, is also developed as an alternative hand selecting sensing technology. It

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utilizes laser 3D measurement unit and weight detector that obtain the parameters (size, weight, and so on) of waste products, and they are recorded on the database. The system is operated using discrimination algorithm that utilizes neural network and the database (Koyanaka and Kobayashi 2011). For example of recycling cellular phones, the system successfully realized 90 % accuracy of automatic separation for tantalum capacitors from the cellular phones (Koyanaka et al. 2006).

Technical Challenges of Quality Recycling: High-Quality Separation Challenges for the Optimization of Physical Sorting Processes Even when ideal liberation is realized, particles still remain in a mixed status, and thus separation is required. For example, let us consider liberated metal particles including 100 ppm of target metal. This separation means that we need to pick up a target particle from a bucket filled with 10,000 particles. In the case of particles with centimeter order, separation by hand can be applied with high accuracy; however, it is not economical at the end. As described above, one of the practical systems is sensor-based sorting system that utilizes materials’ information obtained from the sensor. This can be costeffective for such separation and is also called individual separation. Pressured air can be applied to the particle separation in the range of several mm–300 mm (Furuyanaka 2010). In addition, a variety of sensing technologies, such as color, images, transmission X-ray, and fluorescence X-ray, can be applied, and they are effective for the separation of specific particles (Owada et al. 2010). In the case of mixed particles consisting of many kinds of materials, on the other hand, accurate sensing cannot be expected. As the particle size decreases, it becomes more difficult to separate the particles. In this case, it may be more efficient to handle the particles as an aggregate. This is called “bulk separation” or “mass separation,” which usually utilizes the difference in the properties of particles, such as density, magnetism, and wettability. In addition, the process can be categorized as dry separation and wet separation (usually in water). A dry separation process allows for high throughput and easy collection after separation, and a dry process unit is easy to install and costeffective. On the other hand, a wet separation process utilizing bulk properties is expected to improve the separation efficiency compared to a dry separation process; however, it also has disadvantages that it consumes more energy for water circulation, dehydration, and drying processes. In addition, in many cases a surfactant is utilized in a wet separation process, which enlarges load for effluent treatment. After all, these two process types have an optimum range of particle sizes for separation as shown in Fig. 9. We conveniently define low-limit particle sizes shown in Fig. 9, and under certain reliability, low-limit particle sizes for dry and wet separation using bulk properties are 1 mm and 50 μm, respectively. As described above, if the liberation is achieved at the stage of coarse particles, dry separation can be applicable, and it realizes economical and highly efficient separation. Once the crushing process is applied, it always generates fine particles less than 1 mm. Some rare metals in certain products have a tendency to be concentrated in the

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Fig. 9 Category of separation technology and concept of low limit of applicable particle size

particles, and thus, such fine particles will also need to be separated and collected (Oki 2008a; Oki et al. 2008). So far, the particles below 50 μm required wet separation processes utilizing surface property, such as flotation process. A recent study, on the contrary, showed the possibility of a dry process that realizes gravity concentration up to 10 μm particles using strong centrifugal force (Oki 2009). On the contrary, one cannot achieve complete metal recycling no matter how individual elemental technology for recycling was developed. A great variety of products are manufactured and abolished in every year. Thus, construction of a flexible sorting process is necessary to cope with a change of such variations or the chronological changes. However, at the moment, the techniques to build these processes are not yet established, and one has to keep working on the development of these techniques to realize the most suitable sorting process and to derive the most suitable sorting condition. Figure 10 shows the model of the simplest separation process, combining a grinder and a sorter. The targets fed to the sorting process have a variety of constituents such as various kinds of printed circuit boards and electric parts. The grinder itself also has a variety of models operable in the different treatment conditions. In addition, there are so many options for separation of crushed particles. Thus, although the model shown in Fig. 10 has only seven items, it gives ten million ways of separation processes, supposing that each item provides ten conditions. If 20 conditions were given for each item, 1.28 billion ways will exist. Since the efficiency of the liberation is determined as multiplication of grinding efficiency and separation efficiency, both processes need to be well optimized. Even if the simple model shown in Fig. 10 has one grinding and one separation process, the combination of possible patterns will be more than 100 million. In the actual case, a couple of grinding processes and three to ten of separation processes will be applied, which is an astronomical figure. Only a small portion of

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Fig. 10 The model of the simplest separation process

these patterns can actually be ideal physical separations for urban mine resources, and what makes it more difficult is that the cycle of product release is short and the amount and kind of rare metal are different from each product. Thus, one optimum separation pattern will no longer be effective in a short period. Because of this, it is very difficult to optimize the separation pattern, and in reality, they are operated under inefficient conditions. Although the improvement of liberation processes by selecting optimum grinding and separation processes is important, it is very difficult to recognize the importance of the processes. Figure 11 shows the schematic image of a physical separation process that extracts and purifies rare metal X from waste product. For example, let us think about cellular phones as a feed. As described in Fig. 3, rare metal X can be located anywhere at the variety of status points in the cellular phone, and this affects the difficulty of liberation using a crushing process. In the crushing process, as shown in Fig. 5, the type of grinding machine and its operating conditions determine the size of particles and the degree of liberation. Even if the ideal liberation is realized such as Status A (or Status B) in Fig. 11, the results can be different depending upon the efficiency of the latter separation process. However, efficient separation after Status D does not often achieve higher purity of rare metal X than that of Status B with inefficient separation. Here, the information that can be obtained from typical recycle plants through the series of processes is threefold: (1) purity of rare metal X in the feed, (2) particle size after grinding, and (3) purity and yield of rare metal X after separation. Actually, important parameters that determine the quality of the entire process, such as the dispersion of rare metal X

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Fig. 11 The relationship between the selection of separation method and the degree of liberation

in the waste product and handy analysis method for the degree of liberation, do not exist. Important parameters in the processes from product feed to collection of separated particle are in the black box, and it is not possible to find out the source of problems such as poor purity of rare metal X after recycling. It could be due to the quality of liberation or separation. In this current situation, the concept of liberation and importance of selective grinding are not well recognized, and in not a few cases, only latter separation process is discussed without considering the degree of liberation. In addition, component analysis of separated products does not provide sufficient feedback to the process for improvement, and this makes it difficult to optimize the process of physical separation. Development of simple and easy liberation measuring equipment, and the optimization of the selective grinding and sorting systems which depends on the liberation data, are indispensable issues for success of the rare metal recycling.

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Selection of Sorting Technologies and Challenges During the crushing process, particles with various sizes are generated. The ideal particle size range for better sorting results differs depending upon each sorting technology. Typically, the particles are separated into two or three particle size groups by a screening process, and an optimum sorting process is applied. The particles in the range below several hundred microns are usually not collected; however, collection of such particle range is becoming important especially for recycling precious metals and rare metals, as well as the sorting technology for such particle range. In order to realize highly efficient, low-cost, and low-environmental impact sorting technologies, it is necessary to broaden the applicable particle range of each sorting technology, possibly of the technology in the right-hand side of the image shown in Fig. 8. For the example of improvement for the columnar pneumatic sorter, one of dry sorters, separation of 0.1 mm copper and aluminum particles is realized using model particles (Oki et al. 2007). A wet process can be utilized for finer particle separation where a dry process is no longer efficient. On the other hand, wet gravity concentration, based on particle bulk properties, still has the problem that the separation accuracy decreases as the particle size decreases due to low inertia. Typical particle size range for accurate separation is about 50 μm for conventional wet gravity concentrators such as shaking tables and spiral gravity concentrators. For the particle size below that, wet separation processes such as flotation using the surface properties of the particles can be effective. For the example of removal of ink from waste paper, flotation works very effectively. On the contrary, this process is not ideal for waste products with surface contamination that lower the separation efficiency significantly. Currently, application of wet separation techniques utilizing bulk property of particles is expected even for the particles below 50 μm. Another gravity concentration technology utilizing strong centrifugal fields has been developed since the 1980s and has shown the possibility of gravity concentration up to 10 μ particles. Figure 12 shows a modified image of applicable particle sizes for each separation technology based on the literature by F. F. Aplan (2003). Among them, detailed information for conventional sorting technologies that can be used for mineral processing and metal recycling is available in the literature (Wills 2006). In this chapter, the authors focus on the gravity concentration technology that realizes wet separation of fine particles utilizing bulk properties. As the particle size decreases to below 50 μm, it becomes difficult to separate particles using wet gravity concentration. One of the reasons is that the mobility of particles in the water decreases and separation takes a lot of time. Another reason can be that it is difficult to separate the particles using the specific gravity difference as the inertia of the particles decreases. Gravity concentration using strong centrifugal fields, on the other hand, improves not only the mobility of particles but also the efficiency of separation. Figure 13 shows the category of wet gravity concentration devices and the acceleration of gravity or centrifugal field affecting the separation (OKi 2008b).

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6mm

Sorting

Air Table

75µm 75µm

50mm 25mm

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6mm Heavy Media Separation 13mm HMS Cyclone

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Without Cyclone

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Original figure:F.F.Aplan principles of mineral processing (2003)

Fig. 12 Applicable particle sizes for each separation technology

Here, it shows the acceleration of rather small, lab-scale devices. Wet gravity concentration devices can be categorized into three types: 1. Water flow separation, method to separate utilizing particle sedimentation rate and velocity of the water stream 2. Film flow separation, method to separate utilizing the resistance between particles and water film on the slope and the friction between particles and the slope 3. Pulsatile flow separation, method to separate utilizing the upward and downward motion of water to differentiate the time reaching the bottom Among these methods, separation by gravity settling, especially shaking table and jig, has been widely used for a long time as typical wet separation method. Hydro-cyclone using rotational flow and spiral separation devices are conventional installations for fine particles utilizing wet gravity concentration. In addition, the compulsive rotational wet gravity concentration method realized 10 μ particle separation utilizing strong centrifugal forces given by a mechanical rotating force. For the device shown in Fig. 13, maximum acceleration is in the range of 30–300 G (1 G = 9.80665 m s 2). Although it is not possible to define the low-limit particle

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Fig. 13 Category of wet gravity concentration devices and settling acceleration

size or separation accuracy by the acceleration due to the difference in the particle motion or the method of particle collection, it is clear that the velocity and inertia of particles are increased by the acceleration. So far, compulsive rotational devices were utilized mainly overseas; however, the mechanism of particle separation and operability is still not clarified, and only few cases were applied to rare metal recycling. Since the wet process is promising, more application is expected in the future.

New Sorting Technology for Urban Mine Development: Smart Operation A physical sorting process is usually combined from three to ten separation stages, and the combination of separation stages yields astronomical figures. Thus, most cases are abandoned before finding out the true performance of each device. To solve this situation, the authors have examined a system that promptly derives the optimum condition using a database and computer simulation. Without relying on experienced workers, the “smart operation” system realized automated operation at optimum condition. The system has been applied to recycling of printed circuit boards, and the author succeeded in the development of a sorting process that could collect tantalum capacitors at high purity for the first time in the world and achieved practical use upon introduction to a Japanese recycling plant in 2012. Since tantalum is one of the most expensive rare metals and most of it is not recycled, the Japanese Government chose tantalum as one of five important metals (tungsten, tantalum, cobalt, neodymium, and dysprosium) that are preferentially recycled in 2012. Tantalum is mostly used in a tantalum capacitor on printed circuit

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boards. At first, the recycling process of the printed circuit board for tantalum is developed based on the conventional liberation method (see Fig. 5). Considering the tantalum atom as the species of liberation, the authors aimed at the improvement of the liberation by fine grinding of the printed circuit board. After fine grinding, the authors conducted separation process based on the physical property of tantalum oxide, resulting in the concentration of tantalum to several times. Tantalum was, however, collected with a precious metal and other heavy metals due to low weight ratio of tantalum in printed circuit boards, around 1,000 ppm. As described before, rare metals such as tantalum need to be separated from copper or precious metals before pyrometallurgical treatment, and the recycling of tantalum could not be accomplished by the method mentioned above. At first, it was considered that it was almost impossible to collect a certain electric element from a printed circuit board where various electronic elements were mixed. A phenomenon, however, was found that an electronic element was exfoliated from a printed circuit board as the original form by using a certain crushing device. Thus, we made an attempt to find out the most optimum separation pattern, considering the tantalum capacitor as the species of liberation and each electronic element has peculiar sorting properties. The authors classified over 400,000 electric elements in 320 categories according to the size and the function and built the database for their physical and sorting properties. Then, three kinds of separation methods, viz., size, specific gravity, and magnetic properties, are considered, and by numerical computation, the authors predicted the sorting result of approximately 2,055 trillion ways of patterns that include repetition use and performed narrowing of the optimum that a tantalum capacitor could concentrate afterward. As a result, the authors found the sorting process that realizes over 80 % of recovery of tantalum capacitors and purity of tantalum capacitors, from the mixture of exfoliated electric elements (Fig. 14, Oki et al. 2010). Although the optimum sorting process pattern was clarified, there was no device that could realize the process pattern. Thus, the development of such device “inclined and low-intensity magnetic-shape separator” was conducted as the next step. This small device, rather used as an auxiliary unit, was a hybrid device that collected aluminum electrolytic capacitors at the inclined conveyor and collects quartz resonators at the low-magnetic field sorter. The device could collect iron and aluminum separately, and the rest that includes tantalum capacitor is sent to a special pneumatic sorter. This “double-tube pneumatic separator” is the main device of the sorting process and can control the airflow rates in the columns precisely using single blower. In the first column, elements heavier than the tantalum capacitor are collected by gravity, and in the second column, only tantalum capacitor is collected by gravity. The flow rate of the first column is slightly faster than that of the second one based on the numeric calculation. In order to realize highly accurate gravity concentration, this device introduces new operating parameters for both software and hardware. Especially, it is possible to operate automatically from the calibration of the device to the collection of elements by selecting the target elements (not only tantalum capacitor but also other elements) on the display, by operation control using electric element database (Oki et al. 2010).

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Fig. 14 Tantalum capacitor collecting process optimized by the simulation based on the database

It used to be assumed that the maximum separation efficiency of the tantalum capacitor was around 10–30 %; however, after such device development described above, the separation efficiency of 97 % was achieved by the trial run with a recycling plant where the device was installed (Oki et al. 2010, 2011). In this way, by using product information appropriately, it is possible to derive the most suitable sorting condition quickly and to recalculate the most suitable sorting condition by substitution of the information in the case of altering product specification, without going through again from the beginning. Use of the easy sensing technology and the smart operation technology just began, and it is expected that the development of recycling technology for other resources will progress further by the innovation of such physical sorting technology.

“Strategic Urban Mining” that Japan Aims for Missing Link of Resource Circulation and Resource Circulation Interface Function In recent years, the development of sensor-based sorting technology for recycling has been active around Europe, and in most of the cases, the mineral processing technology that was applied to the natural mine is converted into the physical

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separation in the recycling. The mineral processing technology at the natural mine does not only utilize magnets for iron and gravity concentration for heavy metal but also make the most of the property of “minerals” based on the knowledge of geology and mineralogy, and minute sorting was conducted. In addition, natural mines are usually developed for several decades, and there is enough time to optimize the mineral processing technology for a specific mineral. As a result, it is possible to obtain a variety of metals including rare metals economically. On the other hand, when the technology is applied to urban mines, only the separating technology based on the element characteristic can be utilized due to less information of the waste products. As a result, except for precious metals, metals used for structural materials such as iron, aluminum, and copper became targets of the recycling. In recent years in Japan, urban mines are expected to develop for supplying rare metals enough to manufacturing products; however, the technology still requires improvement from the conventional “quantity recycling” technology. The collection of rare metals was difficult in the old urban mine concept, but it can be said that a technical breakthrough will be achieved by compiling the characteristics of the waste products into a database and utilizing it for the separation process, as shown in the example of the tantalum capacitor. On the other hand, however, the urban mining without considering infrastructure and system surrounding it does not realize efficient resource recovery as much as a natural mine can supply, even when new technology is introduced into a part of the resource circulation loop. Even if the recycling is promoted by both production and consumption sides, the resources do not circulate without considering an interface between both sides. In order to realize sustained circulation use of the strategic metals, it is important to construct a series of systems from the supply of reproduced raw materials to a product design, not only to develop resource recycling technology such as physical sorting. The authors thought that the introduction of innovative sorting technology and the eco-design functioned as a mediation technology, and the technology was named “resource circulation interface” (Fig. 15). As discussed above, even if advancement of the physical sorting technology is accomplished, it will be difficult to apply it to all product forms with that alone due to the variety of the product designs released up to now. Thus, an easy recycling design (eco-design) can be considered to compensate for the technology gap. The effective and minimum easy recycling design can be achieved by the suggestion to the products as well as the design guidance of the parts and products that realized easy to sort without spoiling products’ original function and charm. In this way, the improvement of the physical sorting technology is a key for the development of the urban mine including the interfacial function of global resource circulation of materials.

Aiming for Establishing Strategic Urban Mines In order to succeed with efficient and deliberate urban mining, it is of importance to build a society system that introduces product eco-design and physical sorting

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Fig. 15 Missing link and interfacial function of resource circulation

technology utilizing artifact databases. For this purpose, the authors have conducted a project called “Strategic Metal Resource Circulation Technology (Urban Mining)” between 2012 and 2014, aiming for the total development of urban mining in Japan. In this project, the authors specified important metals as “strategic metals” that are necessary to continue industrial activity and potentially have supply risk and evaluated the potential of urban mining and efficient collecting technologies. Venous industry (recycling industry), as shown in the upper part of Fig. 15, mainly focuses on the short-midterm technological subjects aiming for the development of urban mines that are scattered and disorderedly accumulated. Arterial industry (manufacturing industry) of the lower part of Fig. 16, on the other hand, focuses on the mid-long-term technological subjects for realizing a practical urban mining plan utilizing eco-design from manufacturer aspects. As described above, by considering the demand and supply risk of metal resources, as well as the system that realizes deliberately and efficiently collecting strategic metals, the authors named their initiative “Strategic Urban Mine” in contrast to conventional disordered urban mines. In addition, in November 2013, a new research base “Strategic Urban Mining Research Base (SURE)” was established in the National Institute of Advanced Industrial Science and Technology (AIST) for continuous research activity based

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Fig. 16 Summary of Strategic Metal Resource Circulation Technology (Urban Mining) Project

on the project’s concept. SURE holds 37 researchers from AIST (Fig. 17). And SURE maintains a laboratory for evaluation of sorting technology (SURE LATEST) at the AIST Tsukuba West site, aiming at the improvement of physical sorting technology. The laboratory has large space room and four separate rooms that hold about 60 physical sorting devices for grinding, crushing, and separation processes. Twenty of them were originally developed at the AIST (Oki 2012, 2013a, b, c, 2014a, b, c). Such open laboratory, the core of physical sorting technology, is the first attempt in Japan and expected to contribute accelerating development of urban mining development. In order to introduce the strategic urban mine into the society, the support from industry side is necessary. For this purpose, the SURE consortium was organized in October 2014, together with companies related to metal resource circulation, aiming at an early realization of strategic urban mines by extracting needs from industry and society. Currently, the members of the consortium are 45 companies and 20 industry groups and public organizations and institutes. Members of the SURE consortium discuss common subjects in the industry group or individual company’s subjects such as eco-design and utilization technologies of recycled materials, in order to promote the strategic urban mining concept from the manufacturers’ point of view. In addition, they can utilize the facility in SURE LATEST aiming at the extraction of potential problems at recycling plants for

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Fig. 17 Structure of Strategic Urban Mining Research Base

better improvement of the technology. The SURE consortium is expected to propose a variety of new ideas related to urban mine development.

Future Prospects of Strategic Urban Mines Obtaining enormous amount of metal resources from urban mines for supporting the civilization of human races will contribute not only to support sustainable development of civilization society to the future but also to mitigate climate change. While several incidents had happened in Japan, which accelerated the development of urban mining, up to now, there are still many issues that need to be solved from both technical and society system points of view. In this chapter, the authors showed the technical subjects for realizing total circulating usage of metal resources including rare metals and an attempt currently tackled in Japan. Japan has already selected five important metals that need to be recycled and conducted related research on the nation level. It is, however, not possible to realize practical resource circulation with high international competitiveness if the technologies are developed individually.

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Furthermore, even when one recycling technology has been established, the period of validity is not very long due to fast product cycle. The concentration of rare metal in the product also changes year by year, as well as characteristics of separation and crushing. In addition, the more a particular rare metal becomes important, the less material will be used in the product by promoting the use of alternative materials. It takes a lot of time to determine an ideal sorting pattern for a product from the enormous combination of crushing-sorting technologies, and when the process is ready, it is not a few cases that the target rare metal is no longer used anymore. Because of this, in the recycling process in many cases, a hand dismantling and picking process is used under inefficient conditions, and thus, the technology development does not always catch up with it. In order to continue a steady development of rare metal recycling, it is necessary to conduct well-planned technology development based on the prediction of the future. From this point of view, there are two important forecasts: One is that which rare metals will be more important in the next 5 years and 10 years, in other words, which rare metals will be necessary to be recycled from urban mines. The other one is that we have to choose products from which rare metals are recycled. Currently in Japan, for the first one, five kinds of rare metals are selected as strategic rare metals; however, it is difficult to predict their true demand and price trend. At least, for the second one, those rare metals are already used in the products, and one can easily select appropriate products. In order to proceed strategic urban mine development, the authors organized the Strategic Urban Mining Research Base (SURE) in the National Institute of Advanced Industrial Science and Technology (AIST). In this research base, the metals considered to be important in the next generation, not only rare metals, are designated to be “strategic metals,” and they are evaluated for their recycling potential. In addition, the database of physical properties for waste products is being constructed, and based on the database, automatic sorting technology for products including “strategic metal” and pre-smelting treatment technology are under development for preparing raw materials by recycling. These efforts will contribute to economical collection of strategic metal from the current “disordered urban mine” accumulated in the land. Urban mines are one of the promising resources for Japan as a poor natural metal resource country. Fortunately, Japan is one of the major rare metal consumers and also is capable of smelting rare metal by its own. Japan’s urban mine will be more practical with the world top class recycling technology. In addition to these technological developments, it is necessary to reform the society system in order to realize productive and economical urban mine which overcomes the natural mines. The number of researchers and scientists will also be expected to increase for speeding up the development of technological aspect. Coping with sustainable civilization, utilization of renewable energy, and climate change mitigation is one of big challenges. All of them are interconnected, and from developing urban mine point of view, the activity of SURE including collaboration with private companies, and cultivation of human resources, is expected to contribute the climate change mitigation in the future.

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References Aplan FF (2003) Gravity concentration principles of mineral processing. SME, Colorado, pp 185–219 Fujita T et al (2002) Liberation as pre-treatment of recycling process by electrical crushing and water explosion. Resour Treat Technol 49:187–196 Furuyanaka S (2006) Active crushing of waste products – selective crushing technology for composite waste materials. Funtai Kogyou 38:57–64 Furuyanaka S (2010) Crushing technology and eco-recycle. NGT, Tokyo, pp 110–115 Furuyanaka S et al (1999) Evaluation of liberation property for impact crushing and gravity concentration of waste printed electric circuit board. Funtai Kogyou 36:479–483 Gaudin AM (1939) Principles of mineral dressing. McGraw-Hill, New York, pp 70–91 Kejun L et al (2001) Extraction of metals from disposed fragmented portable telephones by various leaching solution. Mater Trans 42:2519–2522 Koyanaka S, Ohya H, Endoh S (2006) New grinding technique to simplify the recycling process of scrap electronic devices. Rev Automot Eng 27:353–355 Koyanaka S et al. AIST web page. https://staff.aist.go.jp/s-koyanaka/ARENNA.pdf Koyanaka S, Kobayashi K (2011) Res Conserv Recycl 55:515–523 Koyanaka S, Endoh S, Ohya H (2006) Effect of impact velocity control on selective grinding of waste printed circuit boards. Adv Powder Technol 17:113–126 Matsumura (2003) Concrete recycle technology. Consult Hokkaido 106:13–19 Mitsubishi Material Co, Ltd. (2003) Development of low environmental load type concrete from waste concrete. MITI Report of FY2003, Ministry of Economy, Trade and Industry Oki T (2008) Proceeding of 16th environmental resource engineering symposium. pp 24–30 OKi T (2008) Screening, separation and gravity concentration. Min Mater Process Inst Jpn Tech Semin Book: 31–44 Oki T (2009) Funtai Gijutu 1(5):39–48 Oki T (2011) Proceedings of the conference of metallurgists (COM2011). pp 69–77 Oki T (2012) Physical sorting technology for rare earth recycle. Automob Technol 66(11):74–79 Oki T (2013a) Physical sorting technology for strategic development of urban mine – unused, refractory resources and Japan’s resource vision. Systhesiology 6(4):238–245 Oki T (2013b) Physical sorting technology for strategic development of urban mine and future prospective. Kankyo Kanri 49(3):62–65 Oki T (2013c) Collection of electric element from waste printed circuit board based on the concept of strategic urban mining. Ceram Jpn 49(1):30–34 Oki T (2014) Urban mine development. Denki Hihyou 2014(2): 27–28 Oki T (2014b) Technical problems of rare metal recycle from waste portable appliances. Energy Resour 35(4):234–238 Oki T (2014c) Development of gas flow sorting device for the realization of strategic urban mine. Funtai Kogaku Gakkai-shi 51(7):527–531 Oki T et al (2007) Establishment of environmental friendly metal recycle system. AIST Environ Energy Symp Ser 1:20–24 Oki T et al (2008) Proc Spring Symp Min Mater Process Inst Jpn 2:91–92 Oki T et al (2010) IMPC2010. pp 3839–3844 Oki T et al (2011) Development of crushing and sorting device for collecting rare earth magnet from HDD. Kido-rui 58:34–35 Owada S (2007) Crushing/sorting technology. J Min Mater Process Inst Jpn 123:575–581 Owada S et al (2010) J Min Mater Process Inst Jpn: 153–156 Shibayama A et al (2002) Collection of materials from crushed liquid crystal panel using electrical crushing. J Min Mater Process Inst Jpn 118:490–496 Wills BA (2006) Will’s mineral processing technology, 7th edn. Butterworth-Heinemann, Oxford Yamasue E et al (2009) Novel evaluation method of elemental recyclability from urban mine – concept of urban ore TMR. Mater Trans 50(6):1536–1540

An Introductory Course on Climate Change Wei-Yin Chen

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Course Scope, Format, and Title . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Textbooks and References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lectures Presented by Faculty and Scholars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction to Climate Change: Causes, by Wei-Yin Chen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction to Climate Change: Impacts, by Wei-Yin Chen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reasoning Economically About Potential Environmental Catastrophes, by Neil Mason . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Atmospheric Physics and Chemistry, by Nathan Hammer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Global Climate Change: Scale and Complexities, by Charles Wax . . . . . . . . . . . . . . . . . . . . . . . Climate Change and US Laws, by David Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climate Change and International Protocols, by David Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Assessment of Impact of Sea Level Rise on Costal and Estuarine Infrastructure Using Numerical Simulation Model, by Yang Ding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Effects of Climate Changes on Water Resources, by Cristiane Queiroz Surbeck . . . . . . . . . Impacts of Global Climate Change on Biodiversity, by David Reed . . . . . . . . . . . . . . . . . . . . . . Ocean and Human Health Consequences, by Deborah Gochfeld and Kristie Willett . . . . Surface Chemistry and Nanotechnology: An Approach to Green Energy, by Scott Gold . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Energy Conservation: Use of Foil Radiant Barriers to Reduce Residential/Commercial Energy Usage in Summer/Winter for Cooling/Heating, by Jeff Roux . . . . . . . . . . . . . . . . . . . . Biological Conversion of Biofuels, by Clint Williford . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chemistry of CO2, by Walter Cleland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mobile and Area Source of Greenhouse Gas (GHG) and Abatement Strategies, by Waheed Uddin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nuclear Energy: Statistics, by Elizabeth Ervin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fuel Efficiency in Transportation Systems, by Jack Seiner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Photochemical Reduction of CO2 and Water Splitting, by Nathan I. Hammer . . . . . . . . . . . Carbon Sequestration, by Robert Holt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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W.-Y. Chen (*) Department of Chemical Engineering, The University of Mississippi, Oxford, MS, USA e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_54

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Introduction to Climate Change: Solutions, by Wei-Yin Chen . . . . . . . . . . . . . . . . . . . . . . . . . . . . Integrated Gasification Combined Cycle (IGCC), by Robert Dahlin . . . . . . . . . . . . . . . . . . . . . . Oxy-firing and Chemical Looping, by Thomas K. Gale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fuel Cells, by Amala Dass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Computational Chemistry, by Steven Davis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Activities of the Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The University of Mississippi offered a seminar course entitled Climate Change – Causes, Impacts and Solutions twice in the last 4 years. The immediate goal of this course is to raise the public awareness of the climate change issue. The second objective is to consolidate a knowledge base for the various outreach, education, and research activities on mitigating the climate change. Junior, senior, and graduate students of science and engineering majors were encouraged to take this course. About 25 speakers from Mississippi, Alabama, and Louisiana gave lectures that covered their expertise in a wide spectrum of areas that include causes, impacts, and solutions of climate change. The slides used in these lectures are posted on the course web site for public dissemination: http://home.olemiss. edu/~cmchengs/Global%20Warming/. Students chose a specific research topic for approval in the early stage of the class. They submitted their research papers and made presentations at the end of the semester. Their overall performance is based on their classroom enthusiasm, final report, and presentation. When the course was offered for the first time, they also made recommendations to the Chancellor’s Ole Miss Green Initiative of the University of Mississippi on the reduction of carbon emissions in the community. This chapter discusses the motivation, content, and outcomes of this course in detail.

Introduction Climate change is arguably the most serious environmental issue. As discussed in the previous chapters of this handbook, from the greenhouse gas emissions to the affected areas of climate change, it is an environmental problem unprecedentedly large in quantity and space. The causes of climate change are complex. Its impacts on weather, ecology, and economy are potentially severe. Technologies for mitigating climate change are costly, and the infrastructure of green technology has just started to emerge. The decline in the supply of high-quality crude oil has further increased the urgency to identify alternative energy resources and develop energy conversion technologies that are both environmentally sound and economically acceptable. Although the concept of sustainability is not new, it has become a household phrase as people become increasingly aware of the severity and scope of future climate change. Climate change has thus become the central issue of sustainability literacy. At the same time, there has been a shortage of workforce

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in the organizations that require some, if not much, knowledge about climate change. Scientists and engineers play a pivotal role in developing green technologies leading to climate change mitigation. Therefore, there is an urgent need to equip the graduates with adequate knowledge about climate change so that they can function effectively in their careers. Under such demand, a campaign on climate change mitigation was planned in fall 2007. Personally, it was another twist in my life. I came to the USA in 1973 as a graduate student in applied mathematics, but the “energy crisis” in 1974 changed my plan. I switched back to chemical engineering in 1975 and started my research in coal hydropyrolysis. I have been maintaining activities in areas of hydrocarbon fuel conversions and pollution control since then. Coal was called “black gold” and “king coal” in the 1970s. Coal remains a major and indispensible energy source, particularly for developing countries such as China and India. However, coal suffered a severe image problem in the last decade because of the concern of its greenhouse gas emissions. As a fossil fuel researcher, offering solutions to the climate change concern becomes not only an obligation but also a serious challenge. About 30 faculty members of the University of Mississippi (UM) and scholars in the region enthusiastically joined the “climate change study group” in fall 2007. The activities of this group include offering courses, editing a handbook, collaborating on clean energy production and conservation research, sponsoring workshops, and developing outreach and public awareness activities. The climate change class is discussed herein, and this handbook has outgrown from this exercise. The engineering school at the University of Mississippi has a relatively small faculty and student population. Faculty has a fairly tight teaching arrangement. Fortunately, the administrators shared the same views and enthusiasm about the course. Students also have tight curricula with 128 credit hours requirement for engineering majors that have been imposed by the Institute of Higher Learning of the State of Mississippi. Most students of the engineering school have to take two elected courses in science and engineering before they graduate. Sixteen students enrolled the climate change class before the course application was approved by the administrator. Some of them were from Chemistry Department and School of Pharmacy. They were seniors and graduate students. This size is about the average for the engineering classes at the university. The course was offered for the first time in spring 2008 and subsequently in spring 2009.

Course Scope, Format, and Title Students signed up for the class with curiosities, more or less, in different aspects: the course content, the instruction format, as well as the instructors’ change in teaching style. The reports about global warming and climate change they heard in the news media just about every day had profoundly promoted their curiosity and interests in the issue. They were notably happy to see an introductory course on climate change. Students in sciences and engineering were used to analytical courses in rigid setting

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that include formal lectures covering relatively narrow scope of subjects with welldeveloped techniques for the analyses. At the outset of the preparation for this course, it was decided to deliver the materials in seminar style for several reasons. Naturally, the broadness of the course subject requires multiple lecturers from many different fields. The question-and-answer session at the end of each lecture allows students to express their thoughts and imaginations. Different lecture topics for different sessions inspire their thoughts about the relations among these subjects. Students are indeed eager to learn a serious subject through in much relaxed atmosphere. Most of the students had taken my engineering mathematics and chemical engineering thermodynamics courses (the second semester course in thermodynamics) prior to my offer of the climate change class. They were pleasantly surprised to know that a course of quite different delivery and learning styles was offered. The Intergovernmental Panel on Climate Change (IPCC) and Al Gore were awarded the Nobel Peace Prize when the course request was approved by the university. The gigantic three-volume IPCC’s Fourth Assessment Report (AR4) provides a comprehensive assessment of many aspects of climate change analytically written and edited by a selected group of 559 scholars. At the outset of the course planning, it was decided to cover the same three areas as those covered by AR4, and the course was entitled Climate Change: Causes, Impacts and Solutions. The detailed structure of the course is discussed later in this chapter. Speakers of the lectures were invited mainly from the UM as well as the universities in the region to cover the topics in the fields of causes, impacts, and solutions of climate change. Most of them accepted the invitations without hesitation since the invited lectures were their expertise. There were 25 formal lectures when the course was offered for the second time in 2009. About 60 % of these lectures focused on mitigation technologies. Each lecture lasts about 60 min followed by a 15-min question-and-answer session. Two sessions at the end of the semester were reserved for student presentations. Formal lecturers were asked to assign homework, which they will be asked to grade in the following week.

Textbooks and References Vanek and Albright’s Energy Systems Engineering: Evaluation and Implementation was chosen as the textbook (Vanek and Albright 2008). The authors introduce the system concept in the analysis of energy conversion technologies at its outset. It is an interesting and beneficial approach, although the “system” concept has been introduced in several engineering courses such as process control, dynamics, reaction engineering, engineering economy, etc.; this textbook applies the concept to several different aspects of the energy systems including material and energy balances, economics analysis, carbon cycle, etc. They are uniquely demonstrated in energy systems in one place. The authors introduce the science and engineering fundamentals, technological costs, and impact on natural environment of each of the selected energy systems. Major working equations associated with the technology are identified; the functions of these equations are consciously illustrated by short

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representative examples. These equations effectively link the current issues of energy systems and climate change with materials introduced in other courses, such as economics, heat transfer, thermodynamics, etc. They also provide the readers with an overview of the context within which these systems are being implemented and updated today and into the future. Their presentation centers around the utilizations of alternative energy resources and their roles in climate change mitigation. An extensive online ancillary package for instructors provides an instructor’s manual, solution files, course syllabus, MATLAB scripts, and teaching PowerPoint files. Vanek and Albright indeed made it a friendly book to both the students and the instructors. The book was published in late 2008, i.e., after the price surge of oil; therefore, the economic analysis is based on fairly reasonable data. Moreover, this textbook contains representative homework exercises that serve the pedagogical needs and broad in nature. The cost of this book is moderate. These features render it suitable for a one-semester, introductory textbook for engineering students who would like to know the alternative energy options. Specifically, it covers energy supply and demands, issues surrounding CO2 emissions, factors affecting and models of energy systems, economic tools for energy systems, climate change and climate modeling, fossil fuel resources, stationary combustion systems, carbon sequestration, nuclear energy systems, solar resource, solar photovoltaic technologies, solar thermal applications, wind energy systems, transportation energy technologies, systems prospective on transportation energy, and a conclusion chapter on creating the twenty-first-century energy system. The book, however, lacks coverage on a number of important areas including biomass conversion systems, energy efficiency for buildings, geothermal energy, and advanced combustion systems including oxy-fuel combustion and chemical looping systems. The seminar class did not cover all the topics in this handbook; however, several scholars in the regions were invited to cover most of these topics. IPCC’s AR4 (Intergovernmental Panel on Climate Change 2007a, b, c) was introduced to the class early mainly because it provides the most comprehensive and up-to-date scientific, technical, and socioeconomic information about climate change. It is available online at no cost; the paper copies are available from Cambridge University Press at moderate costs. The students were asked to read the “Summary for Policy Makers and Technical Summary” for each volume (with a total size less than 300 pages) in the first 3 weeks of the course so that they can have a general understanding of the subject. Some of the slides for the introductory sessions were extracted from the online version of these reports. While AR4 presents the most detailed advanced analysis presented by the IPCC and others, it does not contain textbook-level explanations about most of the scientific and technological terminologies. The major portions of the AR4 (other than the “Summary for Policy Makers and Technical Summary”) serve as an indispensable reference to the complex subject, which deserve frequent visits during their study. The ambitious book written by Tester et al. (2005) was adopted as a reference. This decadelong effort of five MIT professors is the first single source of the sustainable energy utilizations when it was published in 2005. It assesses technologies of converting fossil fuels (oil, gas, and coal), nuclear energy, and renewable

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energies (solar, biomass, wind, hydro-, and geothermal) and discusses energy storage, transmission, end use, and efficiency/conservation issues. These technologies are assessed in a political, social, economic, and environmental context with life cycle assessment and systems integration methods. This textbook has been used in a graduate course on sustainable energy many times at MIT. The book was recommended as an advanced reference. Dessler and Parson (2010) provide an integrated treatment of the science, technology, economics, policy, and politics of climate change. Aimed at the educated nonspecialist, and at courses in environmental policy or climate change, the book clearly lays out the scientific foundations of climate change, the issues in current policy debates, and the interactions between science and politics that make the climate change debate so contentious and confusing. This new edition is brought completely up to date to reflect the rapid movement of events related to climate change. In addition, all sections have been improved; in particular, a more thorough primer on the basic science of climate change is included. The book also now integrates the discussion of contrarian claims with the discussion of current scientific knowledge, extends the discussion of cost and benefit estimates, and provides an improved glossary. Web sites of major international and US organizations were introduced to the students: • Intergovernmental Panel on Climate Change, http://www.ipcc.ch/ • United Nations Framework Convention on Climate Change, http://unfccc.int/ 2860.php • United Nations Environment Programme, http://maps.grida.no/theme/ climatechange • World Meteorological Organization, http://www.wmo.int/pages/themes/climate/ index_en.php# • International Energy Agency, http://www.ieagreen.org.uk/ • United States Global Change Research Program, http://www.globalchange.gov/ • United States Climate Change Science Program, http://www.climatescience.gov/ default.php • United States Climate Change Technology Program, http://www. climatetechnology.gov/ • US Department of Energy, http://www.eia.gov/, http://www.energy.gov/environ ment/climatechange.htm, http://www.netl.doe.gov/technologies/carbon_seq/ • National Oceanic and Atmospheric Administration, http://www.noaa.gov/cli mate.html • US Environmental Protection Agency, http://www.epa.gov/climatechange/ • US National Aeronautics and Space Administration, http://climate.nasa.gov/ • US National Science Foundation, http://www.nsf.gov/news/special_reports/ climate/ • US Department of State, http://www.state.gov/g/oes/climate/ • National Academy of Science, http://www.koshland-science-museum.org/ exhibitgcc/index.jsp • Earth Policy Institute, http://www.earth-policy.org/

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Table 1 2009 lectures Session 1 2 3

Speakers Wei-Yin Chen Wei-Yin Chen Neil Manson

4 5 6 7 8

Nathan Hammer Charles Wax David Case David Case Yan Ding

9 10 11 12

Cris Surbeck David Reed Deb Gochfeld, Kristie Willett Scott Gold

13

Jeff Roux

14 15 16 17 18 19 20 21 22 23

Clint Williford Walter Cleland Waheed Uddin Elizabeth Ervin John Seiner Nathan Hammer Robert Holt Wei-Yin Chen Robert Dahlin Tom Gale

24 25 26 27

Amala Dass Steve Davis

Title of lecture Overview of the causes of climate change – causes Overview of the impacts of climate change – impacts Reasoning economically about potential environmental catastrophes Atmospheric physics and chemistry Climate change – evidences and contrarian viewpoints Climate change and US laws International protocols and climate change Assessment of impact of sea level rise on coastal and estuarine infrastructure using numerical simulation model: CCHE2Dcoast Effects of climate change on water resources Global climate change – impacts on biodiversity Ecological and health impacts of climate change Surface chemistry and nanotechnologies: an approach for green energy Energy conservation – use of foil radiant barriers to reduce residential/commercial energy usage in summer/winter for cooling/heating Biological conversion of biomass Chemistry of CO2 Mobile and aerial sources of CO2 and abatement strategies Nuclear energy: statistics Fuel efficiency in transportation systems Photocatalytic reduction of CO2 and water splitting Carbon sequestration Overview of the impacts of climate change – solutions Integrated gasification combined cycle (IGCC) Combustion on the horizon – oxy-fuel combustion and chemical looping Fuel cells Computational chemistry Student presentations Student presentations

Lectures Presented by Faculty and Scholars Table 1 lists the lectures and speakers of the course in spring 2009. Among the 25 lectures, sessions 1, 3, 4, 5, 6, and 7 cover subjects in the “causes” category of climate change, sessions 2, 8, 9, 10, and 11 the “impacts,” and the remaining 14 sessions the “solutions.” Two sessions at the end of the semester are reserved

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for students’ project presentations. The contents of these 25 lectures are summarized below. More information about these lectures can be found in the slides used in these lectures, which have been uploaded for public dissemination: http://home.olemiss. edu/~cmchengs/Global%20Warming/.

Introduction to Climate Change: Causes, by Wei-Yin Chen This is the first of three overview lectures given in this class that bore the same title of the course, one each on the causes, impacts, and solutions of climate change. The first two lectures covered the first two topics using one set of slides. The first introductory lecture on the causes covered the following topics: • The rationale of offering a climate change class • Impacts of increasing energy demand and lack of energy infrastructure on climate change challenges • United Nation’s efforts on climate change mitigation • UNFCCC and Kyoto Protocol • Total CO2 emissions by country and CO2 emission per capita • Developed and developing nations’ different views on CO2 emission limits • Paleoclimate archives and the scientific observations of greenhouse effects caused by human activities • Greenhouse gases and their geographic and sectoral sources • Radiative forcing of different greenhouse gases and their implication of human activities • Nature climate change (i.e., the Milankovitch cycles) and its causes • Thermohaline circulation and ice age • Anthropogenic causes of climate change • Natural carbon emission, carbon sinks, and carbon cycle and their relation with temperature rise and mitigation technologies Finally, IPCC’s comparison of economic development, population growth, and energy usage was used to illustrate the societal causes of global warming. The recent increase in CO2 emissions was fueled more by economic growth than growing populations. It is not the poor masses, but the new and old rich that fuel global warming. And while energy and emission intensities have steadily decreased since the oil crisis in the 1970s, carbon intensity (carbon emission to energy consumption) has not. One conclusion could be drawn is that fixing prices for greenhouse gas emissions can help achieve emissions reduction, just like rising oil prices helped reduce energy and emissions intensity in the last decades. Some of these slides were extracted from the IPCC’s AR4 reports. Reading materials were assigned. Students were asked to start searching a term research topic.

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Introduction to Climate Change: Impacts, by Wei-Yin Chen The second lecture was on the impacts of climate change. History has shown that civilizations rise and fall to the pulse beats of climate. Erik Thorvaldsson’s (known as Erik the Red) discovery of Greenland in 982 A.D. and the subsequent collapse of the Norse settlement less than 500 years later due to severe weather was one example. Flooding is generally believed to have caused the collapse of the Harappan civilization of India, 2500–1600 B.C. The outset of the lecture discussed how the analysis of climate predictability had actually promoted the evolution of modern chaos theory in the 1960s and 1970s. Water’s specific volume increases when the temperature rises. Sea level rise causes the most direct impact of temperature rises. Ice cap melting contributes a lesser degree of impact on sea level rise. Temperature rise also causes decline in biodiversity and natural disasters including droughts, heat waves, flooding, and cyclones. Sea level rise can contribute to disease spread and loss of traditional lifestyle. The natural disasters, in turn, can generate loss of traditional lifestyle, losses of water and food resources, biodiversity losses, economic losses, famines, casualties, and disease spread. The abovementioned impacts were then discussed in more detail. IPCC’s statistics and projections of these impacts are presented. The projected impacts on water resources, ecosystems, food productivity, coasts, and human health were presented as a function of warming from 1990 to 2100. As of 2007, there are concerns in all of these five areas. The projected sea level rise and its effects on land area, population, and GDP showed that Asia will have the most severe consequences. Records show an increasing trend of natural disasters, especially flooding and cyclones. The natural fluctuation of climate, El Nino and La Nina, was introduced. El Nino and La Nina originate in the Pacific Ocean but affect climate globally. The increase in El Nino frequency as the climate changes since 1970 has only recently been appreciated. The potential impact of sea level rise on the Nile Delta is presented. Its impacts on freshwater resources (ground- and surface water) of small islands and low-lying coastal area were explained. Freshwater, in turn, has profound influences on agriculture, ecosystems, and human health. Food production is affected by water, temperature, CO2 level and ultraviolet radiation, and pest and diseases. Developing countries are expected to be affected more than the developed countries. Effects on tea and coffee productions in Kenya and Uganda were illustrated. Finally, the projected biodiversity loss between 2000 and 2050 and spread of several diseases, including malaria, were presented.

Reasoning Economically About Potential Environmental Catastrophes, by Neil Mason At the outset of his lecture, Neil Mason, a philosophy professor, explained why environmental scientists should care about economics. It is known that economic evaluation mediates science and policy. The results of science never get translated

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into action without some form of economic evaluation, either by private industry or by governmental regulators. Less obvious about the importance of economics is its role in moving forward a debate such as climate change. Skepticism about or outright denial of the results of scientific investigation can seem baffling, if not downright evil. Oftentimes, however, what is really going on is that skeptics or deniers (e.g., “intelligent design” proponents) wish to avoid the perceived evaluative implications (ethical, philosophical, religious, or economic) of the results of scientific investigation. Sometimes, the best way to move the debate forward is not to reiterate the science, but to address directly the evaluative presuppositions of the skeptics or deniers (e.g., “Why even think evolution is incompatible with belief in God?”). The major portion of the lecture covered the two competing approaches in making environmental policy decisions: the cost-benefit analysis (CBA) that has been the ascendancy in the USA (Sunstein 2005) and the precautionary principle (PP) that has been commonly adopted by the European Union and many of its member nations, as well as by the United Nations (Manson 2002; Sunstein 2005). The basic idea of CBA (Sunstein 2005) is to identify all potential costs and all potential benefits of a given course of action, assign to each cost and benefit both a probability of occurrence and a dollar value (positive or negative) of occurrence, crunch the numbers, and see whether the result is overall positive or negative. Using CBA, courses of action can be compared to see which course of action has the highest overall positive rating (or least bad negative rating). Then, policymakers should approve the course of action that maximizes net benefits or at least give some presumption in favor of that course of action (Sunstein 2005). Posner’s CBA calculations (Posner 2003) regarding the building of the Brookhaven particle accelerator are illustrative (Sunstein 2005). With CBA, in order for a potential cost to factor into the decision, there is some estimate both of its dollar value and of its probability of occurrence that must be available; otherwise, that potential cost is a nonfactor. The PP is considerably more vague than CBA, with a host of competing formulations (Manson 2002), but the basic idea is “better safe than sorry.” Given that the results of our industrial/technological innovations cannot be foreseen, regulators are justified in restraining such innovations unless and until enough evidence comes in that the activity in question will not produce harmful results. The approach is “risk averse.” Standard objections to these approaches and responses are presented. Many examples are given. It is one of the lectures of this class that promotes critical thing about the basis in policymaking. As a homework exercise, the instructor asked the students to write an essay on what approach they would choose in determining the policies toward climate change.

Atmospheric Physics and Chemistry, by Nathan Hammer Chemistry professor Nathan Hammer presented a lecture on atmospheric physics and chemistry. At its outset, the dynamical evolution of the Earth’s atmospheric gas

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since the primordial solar nebula 4.6 billion years ago was presented: from a composition similar to the emissions of today’s volcanoes (rich in CO2, H2O, and H2) to oxidizing gas that is rich in N2 and O2. O2 has been stable in the atmosphere for 400 million years, as a result of photosynthesis and decay of organics on Earth. Trace gases are introduced. Among them, CO2, CH4, and N2O are considered greenhouse gases due to their capabilities of absorbing vibration bands of the reflected sunlight from Earth’s surface. Dr. Hammer presented the infrared absorption bands of these compounds and that result in trapping a fraction of reflected energy in the atmosphere. These trace greenhouse gases increase over time as the result of increasing use of fossil fuel combustion and activities of chemical industries. Human behaviors have caused increases in trace gas emissions that lead to the formation of photochemical smog from automobile tail gas and ozone depletion from chlorofluorocarbons (CFCs). Geostrophic flow is driven by uneven distribution of pressure and temperature of Earth and the rotation of Earth (i.e., the Coriolis Effect); it, in turn, transports energy pole wards and reduces equator-to-pole temperature contrast. Prolonged temperature rise in this atmospheric circulation across the Pacific Ocean is called El Nino, or Southern Oscillation; similarly, prolonged temperature decrease is called La Nina. El Nino and La Nina usually happen 2–7 years with 9-month to 2-year durations. They cause global weather effects including droughts, hurricanes, moisture, and temperature patterns. Their causes, including global warming, are under active investigation. The four layers of atmosphere were introduced: troposphere, stratosphere, mesosphere, and thermosphere. The chemical characteristics of their gas components and the temperature and pressure variations in these layers were discussed. In the troposphere, the main concerns are acidic gases, photochemical smog, and greenhouse gases. In the stratosphere, O2 photochemically dissociates; the main issues are ozone depletion by nitrogen oxide (NO) and CFCs. The mesosphere is characterized by photochemical reactions of small diatomic molecules and reactions of atoms and ions. The thermosphere is characterized by ultraviolet radiation and ionic reactions. Dr. Hammer then discussed the mechanisms of the following chemical reactions or processes: • Formation of photochemical smog starts with photochemical decomposition of NO2 followed by ozone formation and a series of reaction involving volatile hydrocarbons. • Ozone destruction by NO. • Ozone destruction by hydroxyl radicals. • Ozone destruction by CFCs. • Aerosol formation dynamics. • Ionic reactions. The students were asked to write an essay about their understandings of the climate change as homework. The textbook by Wayne (1985), Seinfeld and Pandis (1998), and Jacob (1999) was recommended for additional information.

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Global Climate Change: Scale and Complexities, by Charles Wax The State climatologist and Mississippi State University Geosciences professor Charles Wax gave this lecture. At its outset, it covered the nature of climate change including the causes of Milankovitch cycles, sunspot activity, and emission of volcanic debris, which results in glaciations every 100,000 years and interglacials every 10,000 years. The correlations between the observed historical data between these nature phenomena were then discussed. The temperature decline after the medieval maximum, or the “little ice age,” that took place between 1400 and 1900 AD, was at least partially due to the maunder minimum, or the prolonged sunspot minimum. It was suggested that the observed El Nino may be correlated with the Atlantic multidecadal oscillation documented in history. Coupled with changes in instrumental measurements and data interpretation methods, he mentioned the possibility that what have been observed may be part of a long story of ups and downs.

Climate Change and US Laws, by David Case Law professor David Case gave two time-sensitive lectures, one on climate change and US laws and the other on climate change and international protocols. These lectures were given only weeks after President Obama was inaugurated. The proposals for climate change legislation at that time were discussed in detail: to include cap and trade, carbon tax, and Clean Air Act Amendment for regulating greenhouse gas emissions by EPA. The lecture covered the details of the process and subsequent developments, including Dr. Case’s expectations on Obama administration’s policy, of the 2007 Massachusetts v. U.S. Environmental Protection Agency (EPA), 549 U.S. 497 (http://www.supremecourt.gov/opinions/06pdf/05-1120.pdf, 2007). Massachusetts v. EPA is a US Supreme Court case decided 5-4 in which 12 states and several cities of the USA brought suit against the EPA to force the agency to regulate carbon dioxide and other greenhouse gases as pollutants. Finally, the lecture covered the status of the National Environmental Policy Act (NEPA), Endangered Species Act (ESA), and common law litigation, such as Connecticut v. American Electric Power (S.D. N.Y. 2005) and California v. General Motors (N.D. Cal. 2007).

Climate Change and International Protocols, by David Case Dr. Case’s second lecture on international protocols focuses on the contributions of the multinational scientific body Intergovernmental Panel on Climate Change (IPCC). It covered IPCC’s publications of the periodic Assessment Reports (AR), establishment of United Nations Framework Convention on Climate Change (UNFCCC), the functions of the Conference of Parties (COP), the journey of Kyoto Protocol, negotiations on post-Kyoto commitments, and skepticism about post-Kyoto regime. In addition to the Massachusetts v. EPA link mentioned above,

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Dr. Case assigned three other reading assignments extracted from the book by Gerrard (2007).

Assessment of Impact of Sea Level Rise on Costal and Estuarine Infrastructure Using Numerical Simulation Model, by Yang Ding Prof. Yan Ding of the National Center for Computational Hydroscience and Engineering gave a lecture on the impacts of sea level rise on costal and estuarine infrastructure using numerical simulation model. The lecture started with an overview on costal hazards due to hurricane, storm, and tides, current instrumental records for climate change, impacts of sea level rise, coastal zone structure, and coastal flood hazard zones. Most of this lecture was devoted to detailed numerical analysis of coastal and estuarine hydrodynamic and morphodynamic processes. Special cases were presented with comparison with recorded data. A list of references (including the slides on the web) was given, and the following homework assignments were assigned: 1. Find tidal datums in the Bench Mark Sheets of Gulfport Harbor, MS on the web site of NOAA Observational Data Interactive Navigation at http:// tidesandcurrents.noaa.gov/gmap3/. Draw a figure to display the MSL, NGVD, and NAVD. Then, retrieve tidal datums in the Bench Mark Sheets of the USCG New Canal Station, Lake Pontchartrain, LA. Find the differences of the tidal datums between the two locations. Explain why they are different. 2. What are the impacts of sea level rise on coasts and coastal communities? 3. What are coastal zones? How are coastal flood hazard zones defined by Federal Emergency Management Agency? 4. What is the CCHE2D-Coast model? What are the model’s capabilities to simulate coastal processes related to assessment of impacts of sea level rise?

Effects of Climate Changes on Water Resources, by Cristiane Queiroz Surbeck Civil engineering professor Cristiane Queiroz Surbeck gave a lecture about the effects of climate changes on water resources. At its outset, the lecture covered the global ocean conveyor belt (thermohaline circulation), the effects of climate change on the circulation and therefore the distribution of Earth’s water resource and quality and the hydrologic cycle. Then, the effects of climate change on water resources in the different regions of the North America were discussed. Through this case study, a few concepts and methods were discussed: the method for the estimation of hydrologic water budget through rainfall analysis, intensity-duration-frequency curves, and return period. A numerical example was given, and a specific water budget problem was given as homework.

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Impacts of Global Climate Change on Biodiversity, by David Reed Biology professor David Reed gave a lecture on the impacts of global climate change on biodiversity. At its outset, the definition, importance, and measure of biodiversity were covered. Origination and extinction through time have been observed in fossil record. The huge end-Permian mass extinction about 30,000 year ago marked the beginning of the diversity decline. The present extinction rate is shown to be at least 50 times higher than that of the post-Permian period. Cases of human-caused extinction were discussed. These cases led to the systematic and focal presentation of this lecture on the functions and importance of ecosystem services to the environment on Earth. These environmental services include food production, raw materials, recreation and water supply, atmospheric gases, water recycling, erosion control, soil formation, nutrient cycling, and purification of wastes. Plants are not only the sources of food, they are valuable sources of genetic materials, natural pesticides, and medicines. Climate change has shifted the range of 1,700 species toward the poles at an average rate of 6.1 km per decade, spread of diseases to higher elevations and more northerly latitudes, and population declines of polar bears and penguins. Since species habitats are more fragmented than in the past and are smaller than in the past, the impact of future climate change is expected to cause a higher rate of extinctions. About 10–20 % of all species on Earth are expected to go extinct by 2050.

Ocean and Human Health Consequences, by Deborah Gochfeld and Kristie Willett Prof. Deborah Gochfeld of the National Center for Natural Products Research and Prof. Kristie Willett of Pharmacology made two related presentations in a joint seminar on ecological impacts of climate change. Dr. Gochfeld discussed the ocean health and Dr. Willett the human health consequences. These two lectures extend David Reed’s biodiversity lecture into a more detailed analysis. Dr. Gochfeld first introduced the ocean stressors imposed by humans: overfishing, pollution/sedimentation/eutrophication, and habitat modification, which reduce the resilience of species, communities, and ecosystems to climate change efforts. It was explained how local economies near major coral reefs benefit from an abundance of fish and other marine creatures as a food source and how drugs are produced from corals. The major portion of the lecture was devoted to the discussions about how climate change affects the seawater temperature, ocean chemistry (especially the decrease of carbonate ion, CO32
, with increasing atmospheric CO2 concentration), sea level rise, ocean circulation, solar and UV irradiance, and pathogen distribution and virulence. The results of these immediate effects were discussed in detail. For instance, changes in natural ocean circulation induce extreme weather, terrestrial climate, and disappearance of shallow water and intertidal habitats. Extreme weather, in turn, causes increased coastal erosion, especially beaches, increased river volume, flooding, drought, runoff (freshwater, sediment,

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pollutants, nutrients), destruction of salt marshes, seagrass beds, mangroves, and coral reefs. Moreover, harmful algal blooms result from runoff of sediment, and nutrients are enhanced by elevated temperatures and solar radiation. Decrease in carbonate ion reduces the abilities of corals and other calcifying organisms (clams, oysters, mussels, and other important fish species) to produce skeletons or shells. Seawater rise causes flooded coastlines, wetlands, estuaries, disappearance of shallow water and intertidal habitats, and loss of nursery grounds, nesting, and feeding habitats of many organisms. Dr. Willett’s lecture covered stress-related problems, increased infectious disease, extreme events, increased number of poor, and increased agricultural yields. World Health Organization’s (WHO) climate change site at http://www.who.int/ globalchange/en/index.html was introduced at its outset. The primary, secondary, and tertiary impacts of climate change on human health at the outset were discussed. Temperature rise causes ozone and photochemical smog concentrations that induce several respiratory diseases and alleges. Statistics also illustrate that temperature correlates the populations of mosquitoes, ticks, snails, and parasites in contaminated water, which, in turn, transmit dengue fever, malaria, Lyme disease, schistosomiasis, and cholera. Extreme weather leads to flooding and drought that cause food shortage and malnutrition. The correlations between the temperature rise and the health issues observed in different parts of the world between 1990 and 1999 (Intergovernmental Panel on Climate Change 2007b) were also discussed. In addition to the IPCC report, WHO report (World Health Organization 2003) and EPA’s climate change site, http://www.epa.gov/climatechange/ were assigned as the reading materials.

Surface Chemistry and Nanotechnology: An Approach to Green Energy, by Scott Gold Prof. Scott Gold of the Louisiana Tech University gave a lecture on the surface chemistry and nanotechnology: an approach to green energy. This lecture covered two major portions: the sciences and technologies of template wetting nanofabrication and their technological applications in fuel cells and electrochemical supercapacitors. At the outset, it introduced the template materials, methods of wetting porous materials, reactive ion etching, sputtering processes, and posttreatment reactions that convert nanotube precursor to desired materials. He then discussed the applications of nanostructures from template wetting that include: • Ceramics such as sulfated zirconia (superacid) for proton exchange membrane for fuel cells and acid catalysis • Nanotubes of metals such as platinum, palladium, and gold as catalysts in fuel cells, and Raman spectroscopy • Piezoelectric microelectromechanical systems (MEMS) • Conductive and semiconducting polymers as electrical supercapacitors, photovoltaics, LEDs, photodiodes, sensor, and hydrogen storage

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The second half of Dr. Gold’s lecture focuses on fuel cells. Different types of fuel cells were introduced: alkaline, proton exchange membrane, direct methanol and other liquid fuels, phosphoric acid, molten carbonate, solid oxide, and enzymatic biofuel. Their applications and operating conditions were discussed. Research in fuel cells has been growing rapidly due to its low emissions, high-energy efficiency, and higher energy density than batteries. Reaction efficiency, design (current collection, fuel transport to catalyst, proton transport to membrane, and waste removal), material issues, and cost remain as technological barriers and research areas. Dr. Gold then presented the works of his group on nanofabrication: gold and platinum nanotubes on grapheme oxide (GO) and semiconducting polymer such as poly (3-hexylthiophene) (P3HT) nanotubes. Nanotube preparation and their enhancement in electron transfer rate coefficients for biofuel cell and supercapacitors were discussed in detail.

Energy Conservation: Use of Foil Radiant Barriers to Reduce Residential/Commercial Energy Usage in Summer/Winter for Cooling/Heating, by Jeff Roux Prof. Jeff Roux of mechanical engineering gave this lecture on building design for energy conservation. At the outset, he presented the important role of energy conservation in climate change mitigation. IPCC AR4 concluded that the buildings sector will have the highest economical potential for global mitigation as a function of carbon price in 2030. Major currently available commercial technologies and practices for this sector include efficient lighting and daylighting, more efficient electrical appliances, heating and cooling devices, improved cook stoves, improved insulation, passive and active solar design for heating and cooling, alternative refrigeration fluids, and recovery and recycle of fluorinated gases. Key mitigation technologies and practices projected to be commercialized before 2030 include integrated design of commercial buildings including technologies such as intelligent meters that provide feedback and control and solar photovoltaic integrated in buildings. The research at the University of Mississippi on improved insulation for residential dwellings was then discussed. The lecture presented the characteristics and properties of various fibrous materials (fiberglass, rock wool, cellulose, and polystyrene and polyurethane foams) and their principles of operation. The large surface area of fibers inhibits the air within the insulation from moving. Air has a low thermal conductivity and is an excellent insulator if it can be made to remain stationary. The lecture also presented experimentally measured data (including summer and winter) at an occupied north Mississippi residence, which were transformed to various profiles such as time histories of temperature, heat flux, and water vapor concentrations. A mathematical model that incorporated conduction and radiation heat transfer and moisture transport was developed to predict the changes in total heat flux. Model predictions showed good correlations with the experimentally measured heat flux.

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Biological Conversion of Biofuels, by Clint Williford Dr. Clint Williford, professor of chemical engineering, gave a lecture entitled biological conversion of biofuels. The lecture started with an introduction on the historical correlations among oil price, supply, and demand. It then covered the greenhouse gas emissions from different sectors and fuel sources. Looking ahead, biomass conversion to fuels has been considered one of the seven wedges to maintain a constant CO2 emission level between 2005 and 2055. This reduction corresponds to one billion tons of CO2 per year, or an increase of bioethanol usage by 50 times. Nevertheless, the investment on biomass conversion grew rapidly in the last decade due to higher energy cost, concern for energy security, climate change, political supports, and technological maturity. The major portion of this lecture was on the current biofuel technologies: biodiesel, grain corn ethanol, cellulosic ethanol (cell EtOH), and biobutanol. In addition to the details of their conversion technologies, he explained the heat content of the products, pollutant emissions (unburned hydrocarbons, CO, particulate matter, and NOx), fossil fuel replacement ratio, economics, and other issues during their usages. He then discussed his research on alternative biomass pretreatments for improved lignocellulosic ethanol production. Celluloses are abundant and widely spread. Conversion of cellulose to ethanol can relieve food demand from corn and cane; it is virtually eternal. Moreover, its positive impacts on CO2 emission and nonrenewable replacement are both high (over 90 %) and have been spurring biofuel mandate. The technological difficulties of the conversion and its cost remain bottlenecks in its development. The separation of cellulose from lignin, however, requires innovations in the areas of the selections of enzymes, pretreatment process, and improved lignin utilizations. Dr. Williford also discussed the controversies of biofuels including the impact of deforestation, nitrous oxide emission from fertilizer, food price, and food export.

Chemistry of CO2, by Walter Cleland Professor of chemistry Walter E. Cleland gave a lecture on the chemistry of CO2. This lecture was selected to promote critical thinking for developing innovative technologies for CO2 capture and utilization. It started with an introduction of the various stable oxides of carbon, physical properties of CO2, phase diagram, and Walsh diagram. Industrial processes involving CO2 production and utilizations were then presented. CO2 utilizations based on the physical properties of CO2 include refrigeration fluid, cleaning solvent, solvent as a reaction media and extraction, and food and agrochemical applications such as beverage additives and fumigant. CO2 utilizations based on the chemical properties of CO2 include the production of urea, salicylic acid, inorganic carbonates and pigments, propylene carbonate, naturalization of caustic waste water, and CO2 capture by various liquid and solid sorbents. The majority of this lecture covered more detailed discussions of the CO2 reactions for its production and utilizations. Productions of CO2 mainly come from combustion and gasification of fossil fuels and their derivatives in stationary and

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mobile sources. Fermentation, lime-kiln operations sodium phosphate manufacture, and natural gas wells also produce fairly sizable quantities of CO2. CO2 in these gas streams can be captured by amines (Girbotol process) and sodium or potassium carbonate process. CO2, along with KMnO4 (permanganate process) or K2Cr2O7 (dichromate process), has been used to chemically reduce H2S in gaseous streams to elemental sulfur. The lecture then covered the reactions that involve CO2 either as a reactant or as a product in the following categories: CO2 reaction with H2O; reaction with O2, CO, and O2; CO2 with H2 (reversed water-shift reaction); CO2 with NH3 (urea formation); CO2 reactions with organics that have been used in carbon capture; coordination chemistry of CO2 and metals; reaction of M-CO2; reactions in biological systems; use of CO2 as a C1 feedstock; carboxylation; polymerization; CO2 reductions; and photochemical reduction of CO2. The reactions of CO2 with organics are of three major types: organic reaction with RO
to form ROCOO
, with RNH2 to form RNHCOO
or RNHCONHR, and with RMgX or RLi to form RCOO
. CO2 is a poor ligand, but it does form a number of complexes and bonding modes with metals, which are important for activation of CO2 in catalytic reduction reactions. For instance, M-CO2 reacts proton or electrophile, such as R+, and converts to M-CO or M-C(O)OR, respectively. CO2 reacts with hydride, M-H, and forms M-O2CH. Organophosphines, PR3, react with M-CO2 and O = PR3. Isocyanide, M(CNR)-(CO2), decomposes and forms RNCO and M-CO. Reactions of CO2 in biological systems include animal metabolism, photosynthesis, enzyme-catalyzed carbonic acid decomposition, carboxylation of ribose, and catalytic reduction of CO2 to CO. Using CO2 as a C1 feedstock leads to the formation of carboxylates, lactones (RCOOR0 ), carbonates (RR0 NCOOR00 , ROC(O)OR0 ), ureas (RR0 NCONRR0 ), and isocyanates (RNCO). Moreover, as a C1 feedstock, CO2 reduces to formats (HCOO
), oxalates (
O2C-CO2
), formaldehyde (H2CO), CO, methanol, and methane. Carboxylation results in the formation of COO
group on carbon, nitrogen, or oxygen atom in an organic compound such as direct carboxylation in ionic liquid from imidazolium carbonate. With metal-salen catalyst, polycarbonates form from epoxides and CO2. Through metal and enzymatic catalytic mechanisms, CO2 has been hydrogenated to formic acid and methanol. Finally, the fundamentals of photoelectrochemical reduction of CO2 to formic acid and methanol were briefly discussed. A recent review by Beckman (2004) would be a valuable reading beyond this class.

Mobile and Area Source of Greenhouse Gas (GHG) and Abatement Strategies, by Waheed Uddin Civil engineering professor Waheed Uddin gave a lecture on mobile and area source of greenhouse gas (GHG) and abatement strategies. This lecture introduced five topics: • Quantifying traffic and built environment impacts on mobility and traffic congestion

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• Evaluation of traffic and built environment impacts on GHG emissions and global warming • Assessment of traffic and built environment impacts on air quality and public health • Application of remote sensing and geospatial technologies and air pollution models for traffic visualization • Environmental assessment and evaluation of abatement strategies The transportation sector accounts for 28 % of total GHG emissions in the USA and 33 % of the nation’s energy-related CO2 emissions (EIA 2007). The USA in turn is responsible for 22 % of CO2 emissions worldwide and for close to a quarter of worldwide GHG emissions (Energy Information Agency (EIA) 2007). Report has shown that GNP has been linearly proportional to the density of paved road, and GHG emissions have increased with increasing use of fossil fuels for the economic growth. Although average mileage per gallon of gasoline has increased 40.60 % from 1970 to 2000, average total fuel consumption per vehicle has decreased only 13.25 % from 1970 to 2000. Percent increase in vehicle mile traveled showed a strong correlation with increase in GDP. In addition to passenger cars, long haul tracks, light-duty trucks, aviation, marines, locomotives, motorcycles, and space missions are major portions of carbon emissions from mobile sources. Public transportation is one of the most significant means to reduce household carbon footprint. Moreover, traffic congestion and gridlock have steadily grown, and commuters spend 46 h annually stuck in traffic and waste five billion gallons of gas annually. The lecture then covered carbon emission from buildings, whose carbon footprint can be extracted from high-resolution satellite imagery more cost effectively than traditional aerial photography. Large urban built-up areas (heat islands) demand more energy causing more carbon emissions and consequently more air quality degradation. As temperature rises, so does the likelihood that smog will exceed national standards of air quality; more power generation will produce more carbon emissions. As a result, sustainable transportation development must consider the following factors: land use, urbanization and social integration, built-up area effects on environment (air, water), built environment impacts on physical inactivity, traffic fatalities and injuries, traffic-related emissions and air pollution, traffic-related pavement noise impacts, construction process and material resources, energy demand, and diminishing natural resources. To improve the spatial management and urban transport, it will be necessary to structure urban development with adequate transport policies and systems, manage efficiently the urban/rural/regional interfaces, and develop and implement enhanced GIS-based transport infrastructure asset management systems. Using the policy recommended by California’s Climate Action Team (2007), Dr. Uddin stated the importance of “smart land use and intelligent transportation system (ITS)” to make the second-largest contribution toward meeting the state’s ambitious GHG reduction goals. These policies include conservation and compact urban growth – by all government levels and by public, efficiency in vehicles by

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vehicle manufacturer and consumers, efficiency in traffic flow by transport agency, better commercial truck fleet management by transporters, public mass transit, high-occupancy vehicle lanes, carpooling, flexible work hours, nonmotorized transport by government levels and by public, equity in road user charges for pollution and vehicle-mile traveled (VMT), and development in clean fuel and energy sources.

Nuclear Energy: Statistics, by Elizabeth Ervin Civil engineering professor Elizabeth Ervin gave a lecture on nuclear energy with emphasis on statistical data. It was postulated at the outset that there are three motivations for developing nuclear energy today: it produces no controlled pollutants such as sulfur dioxides, nitrogen oxides, particulates, and GHG; it creates jobs and capital; and its image has changed in peoples’ mind – 73 % of people approved its development in 2006. As a result, 36 new plants were under construction in 14 countries, and 223 had been proposed in 2006. A major human error at Chernobyl caused 56 deaths. However, the US civilian nuclear reactor program had resulted in zero fatality, compared to 33,134 coal miner and coal transporter deaths from 1938 to 1995 and 54,000 aviation deaths. Moreover, coal-fired power plant releases 100 times more radiations than equivalent nuclear reactor. At the presentation in 2008, there were 439 nuclear reactors operating in 31 countries; they provided 15.2 % of the world’s electricity production in 2006 (34 % of EU and 20 % of USA). There were 104 commercial nuclear power reactor plants in the 64 sites and in 31 states in the USA. For seven states in 2006, nuclear energy made up the largest percentage of their electricity generated. Major unit operations of a nuclear power plant were introduced. Nuclear power generates economically competitive electricity, 1.82 cents per kWh, as compared to coal at 2.13 cents per kWh and natural gas 3.69 cents per kWh. Their power plants require much smaller spaces than those for biomass conversion plants, coal-fired power plants, and solar power plants. Disposal methods of nuclear fuel waste and low-level radioactive waste (LLRW) that consist of items that have come in contact with radioactive materials such as personal protective clothes have been developed. Fund, with an average of about 3.76 metric tons of dried used fuel per million dollars in the USA, has been committed to the management of nuclear waste. As of 2004, more than 690 containers have been loaded at 30 nuclear sites. This number is expected to grow to about 712 by 2015. Water discharged from a nuclear power plant contains no harmful pollutants and even meets regulatory standards for temperature. Prof. Ervin gave some facts about fission energy that are not commonly known. Nuclear energy has been widely adopted in medical procedures and cosmic. Many fruits and vegetables possess natural radioactivities. Uranium is a relatively abundant element (about as abundant as tin) that occurs naturally in Earth’s crust. To resolve the shortage in nuclear workforce, the US Nuclear Regulatory Commission has created a curriculum education grant program as a multidisciplinary technical elective.

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Fuel Efficiency in Transportation Systems, by Jack Seiner The late Prof. Jack M. Seiner of mechanical engineering and National Center for Physical Acoustics gave a lecture entitled fuel efficiency in transportation systems. The lecture covered six topics: the motivation for transportation efficiency, carbon emissions by light-duty vehicles, alternative engine concepts, alternate fuels, alternate power sources, and roles of aerodynamic efficiency. The brief opening segment of his talk reiterated the major causes of climate change and the importance of improved energy conservation and enhanced fuel efficiency in transportation systems in climate change mitigation. The discussion of carbon emissions by light-duty vehicles (the second part of the lecture) covered the concept of passenger miles per gallon (PMPG) for various transportation vehicles, estimation of auto sector CO2 emissions, and global CO2 emissions by economic sectors. It then reviewed the thermodynamics and thermal efficiencies of the two conventional piston-based engine cycles: the gasoline engine cycles and diesel engine cycles. These fundamentals led to major conclusions about the features and recent emphasis on diesel engines: diesel fuel has higher heat content than gasoline, and diesel engine has a 30–35 % higher thermal efficiency than conventional engine. For instance, a diesel engine in a light-duty vehicle such as a 2,000 lb Volkswagen Jetta gets 50 miles per gallon on the highway. The discussion of alternate engines (the third part of the lecture) covered automotive gas turbines, rotary Wankel engine, Di Pietro rotary air engine, and other types of compressed-air cars. The history, design features, advantages, and technical issues of these technologies were discussed. The comparison of these engines considered the factors including pollutant emissions, efficiency, engine weight, fuel type, maintenance effort, life expectancy, number of parts, warm-up period, fuel flexibility, noise, and throttle lag. In the discussion of alternate fuels (the fourth part of the lecture), the characteristics of gasoline with various alternate energy sources were compared: diesel, liquefied natural gas (LNG), compressed natural gas (CNG), ethanol and blended ethanol, liquid hydrogen, hydrogen at 150 bar, lithium, nickel metal hydride, lead acid battery, and compressed air. The number of vehicles that use these alternate fuels is increasing. Hydrogen and diesel have energy density higher than that of gasoline. Hydrogen does not have emission problems, but its storage in an efficient, safe, and cost-effective system has emerged as a major research area. Energies required for compression of H2 to a gaseous state at high pressure and for liquefying H2 are cost concerns. Energy loss in delivery in pipeline is another factor. Independently, means to store hydrogen by other materials have been investigated. Most of these works focus on hydrides, i.e., chemically bond hydrogen in a solid metal or carbon materials. In addition to hydrogen-packing density, performance indices include reversibility of hydrogen uptake and release, weight of hydride, kinetics of uptake and release, and the temperature and pressure dependence of H2-hydride equilibrium. H2 generation from hydrolysis of complex hydrides was discussed. Due to the complexity of these requirements, the US Department of Energy has announced a set of specific technical targets for hydrogen storage. The second half

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of the discussion of alternate fuels was placed on biofuels. The historic development of “flexible fuel vehicles” was discussed first. He then discussed the feedstock, conversion technologies, emissions, policies, and challenges of various biofuels, with the emphases on the bioethanol and biodiesel. The serious challenges in the production of bioethanol include energy consumptions in the conversion of grain to ethanol (hydrolysis, distillation, drying, and emission control), water consumption, fertilizer use, and decrease in food supply. Biodiesel has a higher thermal efficiency than gasoline; the various sources of biodiesels, emissions prospective, and costs were then covered. The alternate power sources for vehicles include hydrogen fuel cells, battery, and hybrids. This portion of the lecture covered the basic principles, comparison of various hydrogen storage systems, hybrid features and their prospective and their efficiencies in each of the energy conversion steps. The last segment of this lecture covers the aerodynamic efficiency. It included the discussions of the factors influencing airplane ticket price per the nautical mile and nautical mile per gallon of gas. Recent development of blended wing body (BWB) for airplane design has shown advantages in weight of aircraft, fuel efficiency, and, therefore, the direct operating cost. The propulsion/airframe integration, aerostructure integration aerodynamics, and controls remain as major design challenges.

Photochemical Reduction of CO2 and Water Splitting, by Nathan I. Hammer Chemistry professor Nathan Hammer, a spectroscopist, gave a lecture on photochemical reduction of CO2 and splitting of water. Solar energy is not only renewable, but also abundant. Indeed, more energy from sunlight strikes the Earth in 1 h (4.3  1020 J) than all the energy consumed on the planet in a year (4.1  1020 J). There is a high incentive to efficiently convert and store solar energy to reduce our reliance on fossil fuel. Photo- and electrochemical conversion of CO2 and H2O have been identified as one of the top five research areas in catalysis that require urgent attentions by the DOE’s Basic Energy Science (Bell et al. 2007). Photocatalytic conversion of CO2 to formic acid, formaldehyde, methanol, Co, and methane on catalyst surface has been demonstrated, and it is one of these potentially attractive approaches that brings CO2 to a higher energy state by using solar energy. While CO2 and H2O react with photochemically excited electrons, water splitting takes place at electron holes. Water splitting can also be achieved by photolysis of water alone where O2 forms on the photoanode and H2 forms on cathode. The lecture covered the importance of these technologies, their fundamental reaction mechanisms, the role of band gap, and the characteristics and selection of catalysts in these photochemical reactions. It also includes several prominent works that demonstrate photochemical fixation of CO2 on organic compounds, including the catalysts, reaction mechanisms, products, and secondary reactions.

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Carbon Sequestration, by Robert Holt Geology and geological engineering professor Robert Holt gave a lecture about his experiences in geologic carbon sequestration. He first explained the six known geologic sequestration options: • • • • • •

Depleted oil and gas reservoirs Use of CO2 in enhanced oil recovery Deep unused saline water-saturated reservoir rocks Deep unmineable coal seams Use of CO2 in enhanced coal bed methane recovery Other suggested options including basalts, oil shales, and cavities

There are four CO2 trapping mechanisms: structure and stratigraphic trapping, residual saturation trapping in large pores, solubility trapping by in situ water, and mineral trapping through chemical reactions. Mineral trapping is the most attractive process since it could immobilize CO2 for a long time. However, it is comparatively slow because it depends on dissolution of silicate minerals. Security of trapped CO2 (immobility) increases with time since the solubility and mineral trapping are slow. The annual CO2 consumption by the global chemical industries is only about 115 million metric tons, or less than 1 % of its production. At the same time, both natural and industrial analogues have provided evidences that geologic sequestration could be successful before other massive CO2 utilization and storage technologies are developed. Distribution of natural analogues in the world, such as oil and gas reservoirs and CO2 accumulation sites, is presented. Similarly, the distribution of industrial analogues in the world including natural gas storage, liquid waste disposal, and CO2 injection for enhanced oil and gas recovery were presented. The lecture covered the CO2 injection technology for enhanced recovery of hydrocarbons, the worldwide geologic storage potential, potential release pathways after injection, storage cost estimates, and monitoring technologies. Deep saline formation and sequestration in oil and gas fields have the highest capacities. The last segment of his lecture covered the development of monitoring technologies at the University of Mississippi. The technology is based on a conceptual model for CO2 transport in a saturated zone that involves buoyancy-driven CO2 fingering with pulsation through coarse layers. It is visualized that pools of CO2 are trapped beneath aquifer-confining layers; fingering and breakthrough of the trapped CO2 occur when CO2 pressure exceeds the non-wetting phase entry pressure. For phreatic aquifers, CO2 moves into the unsaturated zone and pooling above the capillary fringe. Holt’s research team has set up bench-scale apparatus and has been conducting field tests to answer the following basic scientific questions: 1. 2. 3. 4.

What controls CO2 partitioning and dissolution into the aqueous phase? What chemical reactions will occur and what are their rates? What are the sizes of zones of detectable CO2 and by-products? What type of monitoring design will be required to insure detection?

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Introduction to Climate Change: Solutions, by Wei-Yin Chen This lecture was intended to give an overview on the solutions to climate change. It was originally arranged as session #12, the opening session on climate change mitigation, but scheduling issues left us few options except for this arrangement. The lecture included four major segments: energy conservation and efficiency, alternative energy sources, advanced combustion and gasification for efficient carbon utilization and enabling carbon capture and sequestration, and other advanced technologies. The first segment on energy conservation and efficiency started with the IPCC’s comparison (Intergovernmental Panel on Climate Change 2007c) of sectoral economical potential for global mitigation as a function of carbon price in 2030. The residential and commercial buildings sector leads the six other sectors in sectoral economical potential for global mitigation, which reflects the important role of energy conservation. Both building design and personal behaviors, such as the replacement of standard incandescent bulbs by compact fluorescent light bulb and shutting off lights and personal computers after work, could make notable contributions to carbon reduction. Energy supply sector ranks second in sectoral economical potential for global mitigation. Thus, the impact factors of various emerging technologies for power generation were discussed. According to IPCC’s AR4, nuclear power, natural gas combined cycle, wind power, integrated coal gasification combined cycle (IGCC), pulverized coal combustion with oxygen (oxy-combustion) and carbon capture and sequestration (CCS), and pulverized coal combustion CCS are leading technologies that have the highest impact factors. The segment on alternative energy sources covered the technical principles of nuclear energy, biofuels, wind and tide, geothermal energy, and solar energy. The rationale, scientific principles, and technologies are discussed. For the biofuel production and power generation, it covered biodiesel from vegetable oil and fat, ethanol from sugar cane and corn, ethanol from lignocellulosics, and thermal conversion of biomass. The segment on advanced combustion and gasification for efficient carbon utilization and enabling carbon capture and sequestration covered the need for carbon capture and sequestration, the present sequestration technologies, and the post- and precombustion carbon capture technologies. Topics also included in the sequent discussion are basic design principles of oxy-fuel combustion, IGCC, chemical looping combustion, and integrated oxygen transport membrane for combustion. The segment on other advanced technologies covered the fundamental principles of photocatalytic reduction of CO2, electrochemical splitting of H2O, and geoengineering approaches. The four geoengineering approaches include the use of stratospheric aerosols, cloud albedo enhancement, ocean iron fertilization, and sunshade geoengineering.

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Integrated Gasification Combined Cycle (IGCC), by Robert Dahlin Dr. Robert Dahlin, director of the Power Systems and Environmental Research of the Southern Research Institute, gave a lecture on IGCC. The lecture started with the presentation of the rationales behind the widespread use of coal in the USA: coal’s abundance, wide availability, and more than 250 years’ reserve (comparing to limited natural gas supply). IGCC flow sheets were used to discuss its major unit operations and the process features. These features include: • Higher thermal efficiency than pulverized coal combustion • Lower emissions • Higher feedstock flexibility (coal, oil, natural gas, biomass, petroleum coke, and waste) • Higher product versatility (chemicals, liquid fuels, power, and gas fuel) • More economic means for CO2 capture than pulverized-coal combustion (due to the higher CO2 concentration from a gasifier) Coal gasification was first used for streetlight in 1792. The USA had 1,200 gas plants in 1920s, but the discovery of natural gas led to demise of these plants. Increased energy demand, high natural gas prices, and stringent environmental regulations focused interests on IGCC. There are 117 operating plants and 385 gasifiers worldwide. The lecture then covered the scientific reasons of the IGCC advantages over pulverized coal combustion mentioned above. IGCC removes the pollutants from synthesis gas before they are burned. High pressure and low gas volume provide favorable economics of pollutant removal; these operating characteristics also allow flexibility in pollutant concentration in feedstock. IGCC also produces less waste and consumes less water. IGCC uses two power cycles in series: gas turbine where power is generated from burning the syngas and steam turbine where power is generated from steam expansion. Syngas can also be used to produce chemicals and liquid fuels. Hydrogen can be used as a transportation fuel and fuel cell for generating electricity. These unit operations reveal not only the versatility of the IGCC process, but also a higher IGCC efficiency higher than that of pulverized coal combustion. Some features of the 513 MW IGCC demonstration plant in Kemper County, Mississippi, were then discussed. Lignite will be its primary fuel and natural gas its backup. It has an air-blown rather than an O2-blown gasifier. This modification eliminates the need of an air separation unit and reduces the capital and operating costs and cost of electricity. Moreover, it significantly reduces the emissions of SO2, NO2, CO, volatile organic compounds, and particulates. It is anticipated that about 50 % of the CO2 will be captured. The last segment of his lecture covered some of the research activities of Southern Company’s IGCC Power Systems Development Facility (PSDF) at Wilsonville,

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Alabama. These activities include the particulate removal by hot-gas filtration, hightemperature high-pressure particulate sampling system, development of drag correlations for the feeding system, tar cracking, gas clean up, and CO2 capture. CO2 capture for the high-pressure syngas in an IGCC plant will be less costly than a conventional pulverized coal combustion process. Southern Research is testing a wide spectrum of solvents and additives for capturing CO2; representative data were presented.

Oxy-firing and Chemical Looping, by Thomas K. Gale Dr. Thomas Gale, Power Systems Research Manager of the Southern Research Institute, presented his efforts on oxy-firing and chemical looping. Both are emerging carbon-capture-enabling technologies. The objective of Southern Research’s oxygen-fired CO2 recycle combustion project is to investigate, develop, optimize, and model O2-fired utility boilers by: • Retrofitting the existing Southern Company/Southern Research’s 1 MW pilotscale test facility • Utilizing an advanced oxy-fired coal burner • Measuring the operating and output responses to adjustable parameters • Comparing these responses with CFD modeling results The project has multiple participants. Coal is burnt by O2 and recycled CO2 in an oxy-fired boiler so that the flue gas contains mainly CO2, not N2 as the conventional pulverized coal combustion process. About 75 % of the CO2 is recycled to avoid excessive flame temperature and maintain flow and heat transfer requirements. Thus, advanced burner for oxy-firing will be carefully signed to allow flame shape and heat release to be controlled and to provide a stable attached flame without natural gas assist. Since N2 is not in the flue gas, the flue gas from an oxy-fired boiler has a 25 % volume of that from a conventional air-fired boiler, purification and compression are much less expensive for carbon sequestration. Air separation prior to combustion, however, creates sizable (about 25 %) energy penalty and notable electricity cost. Additional energy penalty comes from purification of CO2 and compression and sequestration. These concepts were introduced in this lecture. Moreover, Southern Research’s unique efforts were discussed that include Maxon oxy-fired burner, oxygen skid and piping system, distributed control system, gas flow control system, recycle system, safety system, conversion of facilities, axial temperature distribution and NO emissions from tests of two coals, computational fluid dynamics modeling conducted by Reaction Engineering International, and plans for the future tests. Parameter study for the future will be devoted to coal type, amounts of O2 in primary flow, burner quarl tip, staging through the recycle-gas tip on the sides of the burner, and staging through the over-fired ports, and percentage of recycle. Flue gas composition, carbon burnout, inleakage, temperature profile, heat transfer, stability

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of the test, acid-gas buildup, and apparent corrosion will be monitored during the tests. In the second segment of the lecture, the basic concepts of the emerging chemical looping technology and Southern Research’s research activities were introduced. An oxygen carrier, usually an oxidized metal, shuttles between two vessels in a cyclic chemical looping process. The oxide oxidizes (or gasifies) the fuel, such as coal and natural gas, in one reactor, while the reduced oxygen carrier is oxidized by air in a second reactor. Since the oxidant for burning fuel does not have N2, the CO2 concentration is high in the flue gas. Separation of CO2 from the fuel oxidation reactor of chemical looping process is much less expensive than separating CO2 from the flue gas of a pulverized coal combustor. Chemical looping is versatile, as it can be applied to both combustion and gasification. Finally, Dr. Gale predicts the overall future of coal-fired power generation in the face of CO2 emission regulation. Existing plants will have three choices as a result of immediate regulations: adding CO2 scrubbers, retrofitting the boiler by installing oxy-firing with flue-gas recycle, or closing the plant. New plants may include oxy-fired furnace without much if any recycle and advanced thermodynamic cycles to offset the energy penalty or other advanced power systems such as oxy-fired IGCC. In the long term, chemical looping and IGCC look promising.

Fuel Cells, by Amala Dass The lecture of chemistry professor Amala Dass included five arguments: fuel cell basics, fuel cell stacks and bipolar plates, types of fuel cells, proton exchange membrane fuel cells, and current status. A schematic is used to illustrate the major components and their functions in a hydrogen fuel cell (proton exchange membrane or PEM cell) at the outset. Slow reaction rate and hydrogen availability remain as challenges. To gain high power output, multiple fuel cells are arranged in series, and bipolar plates are developed. PEM fuel cell uses relatively low temperature and can start quickly. It has been adopted in cars and buses. Five other major types of fuel cells have been developed: phosphoric acid, direct methanol (DMFC), alkaline (AFC), molten carbonate (MCFC), and solid oxide (SOFC). Hydrogen is the fuel for all of these fuel cells. The operating temperature ranges, electrolytes, catalysts, and operating characteristics of these fuel cells were discussed. Schematics were presented to illustrate the chemical structure and characteristics of the most popular PEM, Nafion. The strong C-F bond resists chemical attacks. Nafion’s unique ionic properties are a result of incorporating perfluorovinyl ether groups terminated with sulfonate groups onto a tetrafluoroethylene (i.e., Teflon) backbone. The polymer is hydrophobic; the sulfonate side chains, SO3
, however, are hydrophilic. This leads to the desirable hydrophilic/hydrophobic micro-phase separated morphology. Advancement in nanotechnology has significantly enhanced efficiency of carbon-supported platinum catalysts.

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Hydrogen is the common fuel for several types of the fuel cells mentioned above. The issues facing the infrastructure of hydrogen economy include H2 production, delivery, storage, safety, and end-use materials. For fuel cell, the emerging technology faces challenges in the development of PEM stock, ancillary devices, fuel processors, fuel storage, fuel supply, and electric components. The industry for H2-powered fuel cell (H2FC) vehicles will have to overcome several critical technological barriers that include the hydrogen cost, H2 storage capacity at reduced cost, and fuel cell cost with higher durability. It also has to overcome the economic and institutional barriers that include safety, codes and standard development, H2 delivery infrastructure, domestic manufacturing and supply base, and public awareness and acceptance.

Computational Chemistry, by Steven Davis Professor Steven Davis of the chemistry department gave an overview of computational chemistry techniques and their applications to reaction energetics and dynamics. The Hartree-Fock method was discussed along with its failure to include an accurate description of dynamic electron correlation. Characterization of chemical structures along potential energy surfaces was presented using the harmonic oscillator approximation to calculate vibrational frequencies to determine minima (stable structures) and maxima (transition states). Accurate potential energy surfaces were presented as determined using both single and multiconfigurational wave functions. Examples of highly strained structures with potential for solar energy storage were presented and their thermal isomerizations discussed. One such example, tricyclo[3.1.0.02,6]hexane (Davis et al. 2003), illustrated the necessity of using a multiconfigurational wave function plus Moller-Plesset perturbation theory to achieve accurate energies and correct electronic descriptions of transition states. The use of trans double bonds in small hydrocarbon rings as a way to store potential energy was discussed and the advantages of using computational chemistry to determine relevant reaction pathways and energetics presented. The activation barriers were shown to be somewhat tunable by the substitution of heteroatoms for carbon atoms in the ring moiety (Davis et al. 2009). Multireferenced second-order Moller-Plesset perturbation theory (MRMP2) and coupled-cluster singles, doubles, non-iterative triplets [CCSD(T)] accuracies were compared for systems in which a single determinant was valid to provide a basis for accepting the MRMP2 energies for wave functions with strong multiconfigurational character. A brief overview of how to choose the correct theoretical model to accurately determine chemical properties using computational chemistry was discussed. It was hoped that the students would gain an appreciation for the powerful tool computational chemistry has become as a companion to the experimentalist.

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Table 2 Student presentations in 2008 and 2009 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Student Damon Webster Crystal Warren Joey Parkerson Michael McClure Eddie Smith Archer Davis Josh Sage Leanna Smith Brett Vescovo Grady Cutrer Sarah Mixon Alison Kinnaman Eric Williams Shaolong Wan Benson Gathitu Guang Shi Michael Brandes Whitney Hauslein Katherine Osborne Jonathan Jones Ifejesu Eni-olorunda Elizabeth Spence Ray Nalty

Research title Nuclear energy Implementation of solar panels on commercial properties and the costbased incentives Atmospheric carbon dioxide capture technologies Solar energy Home energy efficiency Ice cores Hydroelectric energy Green roofs US vs. global policy changes Green community Algae-based biofuels Microremediation Biomass utilization Oxy-coal combustion Integrated gasification combined cycle Chemical looping combustion Renewable wind energy Ocean power Heat island infrastructure effects on climate change The hydrogen economy, hydrogen fuel cells, and implementation in Oxford, Mississippi The hydrogen economy – harnessing wind energy How to go green Weather control

Activities of the Students Students were asked to choose a research topic at the beginning of the semester. They were asked to give a short oral report about their research status, questions, and difficulties in the middle of the semester. They were asked to give a term paper and an oral presentation at the end of the semester. A list of the students’ presentations is given in Table 2. The topics range from offering tips in everyday life to modern technologies. Their presentations and papers were evaluated by a panel formed by a

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group of faculties. Two outstanding works selected for the two awards were “Implementation of Solar Panels on Commercial Properties and the Cost-Based Incentives” by Crystal Warren and “Atmospheric Carbon Dioxide Capture Technologies” by Joey Keith Parkerson. They were given the title Ole Miss Idols of Climate Change Mitigation. In addition, each one of them received a $250 cash award. Their slides have been uploaded to the course Web site at http://home.olemiss.edu/~cmchengs/ Global%20Warming/ along with the formal lectures. Joey introduced the technology of capturing atmospheric CO2 by using NaOH in a process that includes two chemical looping cycles: one involves NaOH/Na2CO3 and the other Ca(OH)2/CaCO3/CaO. In the sodium loop, NaOH is converted to Na2CO3 in an air/CO2 contactor, and Na2CO3 is converted back to NaOH by Ca (OH)2 in a causticizer. In addition to the causticizer, the calcium loop includes calciner and a slacker. CaCO3 decomposes to CaO in the calciner, and CaO is hydrolyzed to Ca(OH)2 in the slacker. Joey presented the capture technology as well as the cost evaluation, about $240 per ton of carbon. He argued that it would be competitive if compared to the cost for capturing carbon emitted from vehicles since no mobile device has to be carried. Crystal proposed the widespread use of solar panels for commercial properties, legislative incentives for such installation, and mandatory installation by law. She presented the principles of solar panels, the rationales, cost estimate, and recommendations. Success stories of Wal-Mart, FedEx, and Google were discussed. She interviewed local business owners, including her mother and Wal-Mart, during her course of research. German government pays solar panel users 20 cents per kWh received from grid and receives 50 cents per kWh for energy sent back to grid. Crystal, on the other hand, proposed that federal, state, and local government each pays one third of the installation cost. She also proposed fixed energy prices for 15 years at 25 cents per kWh purchased from the grid and 50 cents per kWh for energy sent back to grid. The Chancellor of the University of Mississippi launched the campus Green Initiative in the spring of 2008 when the course was offered for the first time. The students were excited about the initiatives; they felt that they can share their enthusiasms by transforming what they learned in the semester into actions. The Green Initiative, however, was in its infancy, and the administrators in charge had just started to organize a committee, which will eventually layout the tasks. The students decided to examine the current policies and facilities of the University and explore if there were rooms for improvement. They spent a few evenings together and deliberated their thoughts. The product of their discussions is a list of recommendations, which can be found at: http://home.olemiss.edu/~cmchengs/Global% 20Warming/. An oral presentation was also made to the University administrators. The newly inaugurated provost, the retiring provost, and the university architect were among the participants for the presentation and its subsequent discussions. The two parts of the recommendations, policy and facility, were presented by the two students who were selected to be the idols of the climate change mitigation only a

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couple of days earlier. In the last years, knowledge about climate change, sustainable energy, and environment has indeed been gradually incorporated into the curriculum. Research collaborations and outreach activities in these areas have increased. The University and City of Oxford, Mississippi, have established a public transportation. This course has notably induced public awareness.

Future Directions Climate change affects the life of every living species on Earth. Only contributions from all concerned citizens could generate a monumental impact. Thus, climate change literacy must reach grassroot level that has several unprecedentedly largescale characteristics. Disseminating climate change knowledge secures the immediate need of a strong workforce in the battle against climate change, which is gravely lacking. It raises public awareness and promotes actions of world citizens. More importantly, it is expected to catalyze innovations. In his State of the Union address of 2011 (Obama 2011), President Obama stated the philosophy of his science and technology: “This is our generation’s Sputnik moment.” The Russian Sputnik space satellite program in 1958 has stimulated the space race that, in turn, promoted innovations in many areas of science and technology. President Obama also characterized the nature of the new race in the same address: “We’ll invest in biomedical research, information technology, and especially clean energy technology - an investment that will strengthen our security, protect our planet, and create countless new jobs for our people.” The clean energy activities are expected to grow rapidly in the near future. Mitigating GHG concentrations is closely related to the growths in energy demand, economy, and population. The adaption, impacts, and mitigation of GHG require knowledge in many different (if not all) fields and actions related to different sectors (if not all) of the civilization. Most notably, as this Handbook is organized, collaborations of political, legislative, educational, scientific, technological, and news media sectors will be necessary. For completeness, climate change literacy must cover all of these areas. Science and technology will be in the core of these efforts. In the next few decades, there will be a wide range of research and development investments on the establishment of an alternative energy infrastructure, especially in the areas of biomass conversion, solar panel and concentrator, nuclear energy, wind turbine, hydropower, fuel cell, and geothermal energy. Fossil fuels, particularly coal, are abundant and widespread, and fossil fuel-based power generation is expected to remain a major driving force of the economy in the near future. CO2 production, however, is much higher than its current utilization. Therefore, carbon capture and sequestration and large-scale utilization of CO2 will be of great interests. Moreover, much attention will also be placed on technologies that enable carbon capture including chemical looping combustion, oxy-fuel combustion, and integrated

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oxygen-transport membrane. Integrated coal gasification combined cycle (IGCC) is versatile and efficient. A hydrogen economy will depend on the development of technologies in several industrial sectors. Energy conservation and energy efficiency will be two major approaches to optimize the limited sources for power generation, transportation, buildings, and industrial sectors. High-risk and high-impact innovations are not only required for clean energy research, but also desirable for science, technology, engineering, and mathematics (STEM) educations with emphasis on climate change literacy. Government investments on these topics are expected to increase worldwide. Efforts of the National Science Foundation (2011) and NASA (2011) are just two major sources for literacy funding in the USA. Synergistic collaborative alliances are welcome for generating projects with unique objectives and broad impacts. Creative use of information technologies, such as global seminars, could facilitate communication network. At the time of writing this chapter, the author has jointly offered a video, online global seminar class on sustainability with a colleague at the National Pingtung University of Science and Technology in Taiwan. The objectives of this course are to introduce modern issues to graduate students around the globe and to induce healthy and constructive debates representing the students in different regions of the world and different sectors of the society. In addition to the speed of the Internet, there is plenty of information available on the World Wide Web; therefore, Web-based teaching is expected to be more versatile and creative in the future.

Conclusions Climate literacy can be offered with a group of faculties from different fields in various fashions. The broad nature of the subject renders it possible to cover only selected topics for the organized lectures and other topics for students’ research. This course has generated a set of useful slides public dissemination. However, the Web sites mentioned in section “Lectures Presented by Faculty and Scholars” are also available. Alternatively, some of the organized lectures can be replaced by students’ deliberations on subjects such as “Should we promote the production of bioethanol as an alternative fuel?” or “Should we promote the growth of genetically altered plants for increased photosynthesis?” These discussions can certainly promote critical thinking about important issues and absorbing knowledge in related fields. Activities of climate change literacy are expected to increase in the next decade. There will be more formal and short courses, workshops, summer camps, and outreach projects in other formats. Sustainability will be a central theme of these activities. With the adoption of modern information technology, climate change literacy is likely to accelerate President Obama’s prediction that “This is our generation’s Sputnik moment” (Obama 2011).

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References Beckman EJ (2004) Supercritical and near-critical CO2 in green chemical synthesis and processing. J Supercrit Fluids 28:121–191 Bell AT, Gates BC, Ray D (2007) Basic research needs: catalysis for energy. Office of Basic Energy Science, US Department of Energy, Washington, DC California’s Climate Action Team (2007) Climate action team proposed early actions to mitigate climate change in California, California Protection Agency. http://www.climatechange.ca.gov/ climate_action_team/reports/2007-04-20_CAT_REPORT.PDF Davis SR, Nguyen KA, Lammertsma K, Mattern DL, Walker JE (2003) Ab initio study of the thermal isomerization of tricyclo[3.1.0.02,6]hexane to (Z, Z)-1,3-cyclohexadiene through the (E, Z)-1,3-cyclohexadiene intermediate. J Phys Chem A 107:198–203 Davis SR, Veals JD, Scardino DJ, Zhao Z (2009) Isomerization barriers and strain energies of selected dihydropyridines and pyrans with trans double bonds. J Phys Chem A 113:8724–8730 Dessler AE, Parson EA (2010) The science and politics of climate change: a guide to the debate, 2nd edn. Cambridge University Press, Cambridge Energy Information Administration (EIA) (2008) Emissions of greenhouse gases in the United States 2007. Office of Integrated Analysis and Forecasting, U.S. Department of Energy, Washington, DC. http://www.eia.doe.gov/oiaf/1605/archive/gg08rpt/pdf/0573(2007).pdf Energy Information Agency (EIA) (2007) Annual energy outlook, with projections to 2030. US Department of Energy, Washington, DC. http://ftp.eia.doe.gov/forecasting/0383(2007).pdf. Accessed 16 Sept 2011 Gerrard MB (2007) Global climate change and U.S. law. American Bar Association, Chicago, pp 17–25, 32–58, 61–85 Intergovernmental Panel on Climate Change (2007a) Climate change 2007 – the physical science basis: working group I contribution to the fourth assessment of the IPCC. Cambridge University Press, Cambridge. www.ipcc.ch Intergovernmental Panel on Climate Change (2007b) Climate change 2007 – impact, adaptation and vulnerability: working group II contribution to the fourth assessment of the IPCC. Cambridge University Press, Cambridge. www.ipcc.ch Intergovernmental Panel on Climate Change (2007c) Climate change 2007 – mitigation of climate change: working group III contribution to the fourth assessment of the IPCC. Cambridge University Press, Cambridge. www.ipcc.ch Jacob DJ (1999) Atmospheric chemistry. Princeton University Press, Princeton Manson N (2002) Formulating the precautionary principle. Environ Ethics 4(3):263–274 National Aeronautics and Space Administration (2011) Global climate change education project. Langley Research Center, Hampton. http://www.nasa.gov/offices/education/programs/descrip tions/Global_Climate_Change_Education_Project.html National Science Foundation (2011) FY 2012 budget request to congress, Washington, DC. http:// www.nsf.gov/about/budget/fy2012/pdf/fy2012_rollup.pdf Obama B (2011) State of unions address. US Capital, Washington, DC. http://www.whitehouse. gov/the-press-office/2011/01/25/remarks-president-state-union-address Posner R (2003) Economic analysis of law. Aspen, New York Seinfeld JH, Pandis SN (1998) Atmospheric chemistry and physics: from air pollution to climate change. Wiley, New York Sunstein CR (2005) Cost-benefit analysis and the environment. Ethics 115:351–385 Tester JW, Drake EM, Driscoll MJ, Golay MW, Peters WA (2005) Sustainable energy choosing among options. MIT Press, Cambridge, MA Vanek FM, Albright LD (2008) Energy systems engineering: evaluation and implementation. McGraw-Hill, New York Wayne RP (1985) Chemistry of atmospheres. Clarendon, Oxford World Health Organization (2003) Climate change and human health – risks and responses. Summary. World Health Organization, Geneva. ISBN 9241590815

Reducing Personal Mobility for Climate Change Mitigation Patrick Moriarty and Damon Honnery

Contents Introduction: Travel Reductions for Climate Mitigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Surface Transport Patterns in Four Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Present Transport Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Predicted Future Transport Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Creating Environmentally Sustainable Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . General Principles for Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Changing Travel Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Voluntary Travel Reductions: An Australian Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reducing Travel: Changing Vehicle Occupancy Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reducing Travel: Changing Urban Land Use Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reducing Travel: Raising the Overall Level of Motoring Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reducing Travel: Lowering the Convenience of Car Travel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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In the high-mobility countries of the Organisation for Economic Cooperation and Development (OECD), many governments are seeking to reduce personal mobility, particularly car travel, for a variety of reasons. Reductions can be justified in general by concerns about global climate change, oil depletion and supply security, and traffic casualties. In urban areas, additional concerns are air pollution, traffic congestion, take-up of land by transport infrastructure, and quality of P. Moriarty (*) Department of Design, Monash University, Melbourne, VIC, Australia e-mail: [email protected] D. Honnery Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, VIC, Australia e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_51

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urban life. Similarly, a variety of technological approaches are possible for addressing these problems in the context of global warming mitigation. This chapter examines policies for mobility reduction, as these can have a significant impact on climate change mitigation. It mainly restricts itself to the high-mobility countries of the OECD and uses four such countries (Australia, Japan, the UK, and the US) as case studies. The approaches considered here include: • Using modern Information Technology (IT) advances to promote travel substitution • Car pooling, especially in urban areas • Land use planning, particularly increased urban densities • Encouraging the use of more environmentally friendly travel modes • Raising the overall level (and perhaps also changing the structure) of motoring costs • Reducing the convenience of car travel. It is found that the use of IT, car pooling, and land use planning, whether voluntary or legislated, cannot be expected to produce much reduction in either car passenger-km or vehicle-km. Nor will reliance on voluntary approaches for car travel reduction by encouraging more use of environmentally friendly travel modes. Only the last two approaches can produce large and sustained reductions in travel greenhouse gas emissions, but heavy reliance on market forces such as very large increases in motoring costs is inequitable in OECD countries. The only equitable approach is to reduce the convenience of car travel, for example, by large travel speed reductions and by a reversal of the usual present ranking of travel modes: car, public transport, and active modes. Abbreviations

ABS BITRE bp-k BTS DfT EFMs EIA GDP GHG HOV IEA IPCC IT OECD OPEC

Australian Bureau of Statistics Bureau of Infrastructure, Transport, and Regional Economics (Australia) billion passenger-km Bureau of Transportation Statistics (US) Department for Transport (UK) Environmentally friendly modes Energy Information Administration (US) Gross Domestic Product Greenhouse gas High occupancy vehicle International Energy Agency Intergovernmental Panel on Climate Change Information Technology Organisation for Economic Cooperation and Development Organization of the Petroleum Exporting Countries

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PEB SBJ TDM UN WBCSD

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Pro-environmental behavior Statistics Bureau Japan Travel demand management United Nations World Business Council for Sustainable Development

Introduction: Travel Reductions for Climate Mitigation In the high-mobility countries of the Organisation for Economic Cooperation and Development (OECD), many governments are seeking to reduce personal mobility, particularly car travel, for a variety of reasons. Reductions can be justified in general by concerns about global climate change, oil depletion and supply security, traffic casualties, and even personal fitness (Moriarty and Kennedy 2004; Sallis et al. 2004). In urban areas, additional concerns are air pollution, traffic congestion, take-up of land by transport infrastructure, and quality of urban life. A variety of technological approaches are possible for addressing the problems listed, including improving vehicular fuel efficiency and developing alternative fuels and power systems. This chapter examines policies for mobility reduction, as these can have a significant impact on climate change mitigation. Nevertheless, the other arguments given above for the desirability of travel reductions can help acceptance of such policies. Although this study is mainly restricted to examining travel in only four OECD countries (Australia, Japan, the UK, and the US), the conclusions should have more general application, at least to other high-mobility OECD countries. The approaches considered here include: • Using modern Information Technology (IT) advances to promote travel substitution • Car pooling, especially in urban areas • Land use planning, particularly increased urban densities • Encouraging the use of more environmentally friendly travel modes • Raising the overall level (and perhaps also changing the structure) of motoring costs • Reducing the convenience of car travel. What level of greenhouse gas (GHG) reduction in passenger transport might be needed to avoid serious anthropogenic climate change? It is here assumed that reductions in the transport sector, including surface passenger transport, will need to match those in the world economy overall. The 2013 Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway 2.6 (RCP2.6) has used models showing that CO2 emissions from fossil fuels may have to be cut by the year 2050 to as little as 30.5 % of the year 2013 values, and fall to zero by 2070, if global temperature rises are to be limited to 2  C (Stocker et al. 2013).

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(The European Union regards a rise of 2  C since the industrial revolution as representing a prudent limit for avoiding dangerous climatic change.) Others believe that CO2 atmospheric concentration levels are already too high, and emissions thus need to be cut to zero before 2050 (Moriarty and Honnery 2011). In 2010, travel by all modes accounted for seven billion tonnes of CO2-equivalent emissions, with about 72 % coming from road transport (Sims et al. 2014). For overall CO2 reductions, transport cannot be ignored. Assume that global energy-related CO2 emissions have to follow the RCP2.6 limits and that by 2050 need to be cut to 2.9 billion tonnes of carbon (2.9 GtC) annual levels (Stocker et al. 2013). By 2050, passenger transport emission levels would also have to fall proportionally, if emission reductions are shared equally across sectors. But emission levels in the OECD countries are far higher than the world average. For example in 2013, the US emissions of CO2 from fossil fuel combustion was 3.8 times the world average (BP 2014). If equal per capita emissions for the entire world’s population are assumed by 2050, then (provided US share of world population remains at its present level) US surface passenger transport emissions would need to fall to around 8 % of their 2013 value. What this simple calculation shows is that reduction of a few percent in transport emissions will not suffice: a drastic reduction is needed. Overall, this study finds that the use of IT, car pooling, and land use planning, whether voluntary or legislated, cannot be expected to produce much reduction in either car passenger-km or vehicle-km. Nor will reliance on voluntary approaches for car travel reduction by encouraging more use of environmentally friendly modes (EFMs) of travel. Only the last two approaches can produce large and sustained reductions in travel greenhouse gas emissions, but heavy reliance on market forces, such as very large increases in motoring costs, is inequitable, at least in highly motorized countries. The only equitable approach is to reduce the convenience of car travel, perhaps by large travel speed reductions and by a reversal of the usual present ranking of travel modes: car, public transport, and active modes.

Surface Transport Patterns in Four OECD Countries Before attempting to discuss any specific policies for personal mobility reductions in any country, it is necessary to look at both the present transport situation and the path surface transport took in that country to reach the present position. Four OECD countries (Australia, Japan, UK, US), representing all four continents from which the OECD has members, were chosen as case studies. Together these countries span the range of transport-relevant parameters (for example, public transport share, gasoline costs, urban densities, car occupancy rates) found in OECD countries overall (The one exception is for non-motorized transport, so the experience of other OECD countries will be briefly considered for these modes.). These four countries also have good travel statistics available in English. It is also important to look at possible future patterns of surface travel. Accordingly, both the forecasts of global and regional travel from the latest IPCC Report

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(Sims et al. 2014) and official travel energy forecasts for the US have been included. In addition, the findings of researchers who have used the existence of travel time and money budgets to project travel in each of the various regions of the globe have been discussed. Levels of surface travel both much higher and much lower than at present have been predicted by various authorities. Studying past, present, and projected future travel patterns are important for several reasons. Comparison of present travel in the four countries can reveal insights into where policy levers should be applied for climate mitigation. Understanding is needed, for instance, as to why surface travel per capita in Japan is so much lower than in the other countries studied. Discussion of projected travel by official organizations in, say, the year 2040 is also important. If travel reductions are going to occur anyhow because of over-riding changes in technology, the economy, or lifestyles, the remaining task would then be to merely guide these changes.

Present Transport Patterns Vehicular Travel Table 1 shows the composition of vehicular surface travel in passenger-km per capita in the four countries considered. It is evident from the table that in 1960, car travel was well-established as the dominant mode in the US, but was still negligible in Japan. Australia and the UK were in an intermediate position, with Australia closer to the US in car ownership and use. Both personal travel by motorcycles and light trucks have been included with car travel. Motorcycle travel is negligible today in each country (less than 1 %), except in Japan. Even in Japan, the share of motor cycle travel appears to have peaked in the 1980s and today is only a few percent of total passenger travel (Statistics Bureau Japan (SBJ) 2014). Table 1 also shows that combined public transport patronage is today lower in the UK and the US than it was in 1960, but has grown slightly in Australia, and strongly in Japan, with most of the growth on rail. In fact, bus transport per capita peaked in Japan in the early 1970s at around 1,000 passenger-km/capita and has steadily fallen since. In contrast, train travel is resuming the strong growth that temporarily reversed in the mid-1990s. Figure 1 demonstrates that per capita private car travel over the past 10–20 years appears to have leveled out in Australia, Japan, and the UK. Even in the US, car travel per capita has since 2004 flattened out as well, before the recent global financial crisis actually reduced per capita travel levels. In Great Britain, even total car, van and taxi travel, fell from 674 billion passenger-km (bp-k) in 2007 to 643 bp-k in 2012 (DfT 2013). It is evident that the very high levels attained in the US are unlikely to be reached by the other three countries – or by any other country, in or out of the OECD. And perhaps not even again in the US: the total number of vehicles registered per 1,000 population may have peaked in 2007 (Davis et al. 2013). Another feature of the graph is that the later the country began its push to mass car ownership, the lower the peak level of travel per capita.

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Table 1 Per capita surface passenger-km of travel by mode and country, 1960 and 2011 Country Australia Australia Japan Japan UKa UKa US US

Year 1960 2011 1960 2011 1960 2011 1960 2011

Bus/tramb 390 870 495 705d 1,550 685 650 1,510

Train 875 670 1,955 3,090 785 1,110 200 195

Carc 6,500 13,620 130 6,350d 2,950 10,530 11,100 20,310

Total 7,765 15,155 2,580 10,145 5,285 12,325 11,950 22,015

Car % 83.7 89.9 5.0 62.6 55.8 85.4 92.9 92.3

a

Averages are for Great Britain only, i.e., excluding Northern Ireland Includes a small amount of coastal sea transport c Includes all private road vehicle travel d 2009 values Sources: US Department of Transportation (DoT) (2011), Department for Transport (DfT) (2012), Bureau of Infrastructure, Transport, and Regional Economics (BITRE) (2013), Davis et al. (2013), DfT (2013), Bureau of Transportation Statistics (BTS) (2014), SBJ (2014) b

Fig. 1 Surface travel per capita versus year for Australia, Japan, the UK, and the US, 1960–2011 (Sources: As for Table 1)

In Australia, at least, males have been over-represented in car travel and underrepresented in public transport travel compared with females. Further, females have been traditionally over-represented as car passengers, not drivers. This situation is changing, and today, the differences, although persisting, are small (Moriarty and Mees 2006). In all four countries, young female car driver licence-holding rates are approaching those for males. In a number of US states, there are now more female than male licence holders.

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Non-Motorized Travel So far, only vehicular surface travel has been considered. But non-motorized travel – walking and cycling – will, it is argued, be an important component of vehicular travel reductions for mitigating climate change. Non-motorized travel is better recorded for the journey to work trip, so most of the data presented here is for this trip type. For Melbourne, Australia, the available data span more than 50 years from 1951 to 2006, the date of the last national census. In Melbourne in 1951, about 11 % of work trips were by walking, with another 10 % on bicycle. By 2011, their share had fallen to 3.6 % and 1.3 %, respectively. Most of the drop in cycling had occurred by the late 1960s, although the fall in the share for walking was more uniform over time (Moriarty and Mees 2006). For Australia overall in 2011, the share of these modes was similar, with 4.5 % walking and 1.3 % cycling for the journey to work (BITRE 2013). As with motorized travel, females in the past had higher rates of non-motorized travel overall than males, but much greater rates of walking and lower rates of cycling for the work trip. Today their rate is similar to that for males. For Great Britain overall, journey to work mode of travel data go back to 1890. In the 1890s decade, 59.4 % walked and 2.0 % cycled to work. Cycling peaked in the 1940s decade at 19.6 %, with a further 17.2 % walking (Pooley and Turnbull 2000). By 2008, the figures had fallen to 3 % for cycle and and 11 % on foot. In terms of travel distance, for all trip types cycling fell from 23 bp-k to about 4 bp-k between 1952 and 2007, although bicycle travel has been almost constant at between 4 and 5 bp-k for the past two decades (DfT 2012, 2013). It is difficult to get data on the early use of non-motorized travel in Japan, but given the negligible vehicle ownership until the 1970s (ownership was only 5 per 1,000 population in 1960 (SBJ 2014)), the use of non-motorized modes was presumably high. In Tokyo, non-motorized trips were 25.8 % of the total in 1970 and still 21.7 % in 1990 for the journey to work (Newman and Kenworthy 1989, 1999). In the US, these modes were even less used than in Australia, with 2.8 % walking for the work trip in the US overall in 2009 (BTS 2014). In 1983, the figure for walking was a little higher at 4.3 %. The highest level of walking to work was found in small cities and towns, with both large metropolitan areas and rural areas having somewhat lower levels (US Census Bureau 2012). Ausubel et al. (1998) presented a graph showing that daily walking per capita by Americans was around 4 km in 1880 and did not fall below 3 km until 1960, after which it fell rapidly to well below 1 km today. These low values for non-motorized travel in the four countries today can be contrasted with several other OECD countries in Europe. Pucher and Dijkstra (2003) examined bicycle and walking trip-making in the urban areas in a number of OECD countries. Table 2 shows the results for selected countries for the year 1995. The authors caution that the definition of a trip varies from country to country, but even so, the results are startling, and shows what is possible even today, given the right conditions. Climate seems to have a very little effect on the level of non-motorized trip-making. Sweden, part of which lies above the Arctic Circle, has far higher levels than several countries with more benign climates, such as

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Table 2 Proportion of all urban trips by walking and cycling, various OECD countries, 1995 Country US Canada England and Wales France Italy Germany Sweden Denmark Netherlands

All nonmotorized trips (%) 7 12 16 28 28 34 39 41 46

Walking (%) 6 10 12 24 24 22 29 21 18

Cycling (%) 1 2 4 4 4 12 10 20 28

Source: Pucher and Dijkstra (2003)

France and Italy. And as shown for 46 world cities by Newman and Kenworthy (1999) for 1990, the average for walking and cycling combined for the work trip was 5.1 % for six Australian cities, 4.6 % for 13 US cities, but 18.4 % for 11 European cities.

Predicted Future Transport Patterns Vehicular Travel Schafer and Victor (2000), following earlier work, argued that in all countries, both rich and poor, people have a fixed travel time budget per day. They therefore concluded that a shift from slower modes (public transport and non-motorized modes) to car travel is needed for people to travel further for a given daily time outlay. It is certainly the case that the observed decline in the share of these slower modes has been accompanied by a rise in car – and air – travel. They also postulated that in high-income countries, households spend a fixed share of their income on travel. Personal travel levels themselves (including air travel, both domestic and international) were not anticipated to decline – indeed they saw large increases even in the high-mobility OECD countries. But to keep within their postulated daily travel time budget, they projected absolute declines in the level of car travel for present car-oriented countries, particularly the US, and large increases in high-speed travel (air and very fast train travel). Continued economic growth was seen as the method by which households could pay for this increased travel, while continuing to spend a constant share of household personal disposal income on travel. A variant of this approach has seen magnetically levitated (maglev) trains traveling at very high speeds in evacuated tunnels (to lower air friction) displacing car travel, presumably mainly for longer-distance trips (Ausubel et al. 1998; Moriarty and Honnery 2005). Clearly, air travel within urban areas is not an option. But medium length trips are also unlikely to be made by high speed modes, even by high speed rail. Trips can only be at high speed if stops are very far apart, as there are definite limits to the rates

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of acceleration and deceleration that humans can comfortably tolerate, which reduces average travel speed. Waiting at stops further reduces overall speeds. Although the surface travel reductions of Schafer and Victor do not translate into overall travel reductions (because of rising high speed travel) they do imply a reduction in future surface travel levels, including travel by car, in OECD countries. But it is doubtful that people do in fact have constant travel time budgets, even when aggregated at the city-wide or even national level. And the empirical evidence also suggests that the share of disposable household income spent on travel has risen over time in the four countries studied here (Moriarty 2002b). Further, different sub-groups of the general population have very different average travel time outlays, as shown by the more than twofold travel time difference between female pensioners and full-time working males found in a 1986 Australian travel survey (Moriarty and Honnery 2005). Further, as U.K. researchers Lyons and Urry (2005) have stressed the increasing ability to use travel time for other activities, such as using a laptop on public transport trips, argues against individuals having fixed travel time budgets. Other researchers, impressed by advances in the new IT, have also seen future reductions in surface travel. They have argued that not only surface travel, but all travel, urban and non-urban, surface and air travel, will decline because of substitution by IT. This view has been argued in some detail by MIT planner William Mitchell (2003). He used the term “demobilization” as a general term for the substitution of work, shopping, and other trips by networked computers. Others who have similarly envisaged a controlling role for IT as a means of travel substitution are Frances Cairncross (2001) and Joseph Pelton (2004). As Tal (2008) has documented, the argument that IT will radically reduce travel has now been made for almost three decades. Actual results in the form of travel reductions that can be ascribed to teleworking or teleshopping so far have been disappointing (Moriarty and Kennedy 2000). There are two separate points that need to be examined when evaluating the “telework will reduce travel” argument: • What is the present extent of teleworking and what is its likely growth in future? • What impact does a given level of telework have on overall travel? The numbers who telework for some or all of the time have not risen to anywhere near the levels forecast. Although Raiborn and Butler (2009) reported that in 2008, 11 % of the US workforce teleworked at least 1 day per month, up from 8 % in 2006, the percentage of “full-time equivalent” teleworkers will evidently be low. Even more important, teleworking households may not even reduce their travel overall. First, most households in OECD countries have more vehicle licence-holders than available personal vehicles. So even if a household car is not used for work travel on any given day, it may be used for other purposes by other household members – or by the teleworker for non-work trips. Second, teleworking could affect the location decisions of households. If the commute trip by one or more household members is reduced through telework, the household may locate further away from the city center, where land prices are lower. At least for Australian cities, outer suburban (and non-urban) households travel

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much further per capita than inner urban households (Moriarty 2002a). And for travel overall, including air travel, Smith (2008) has remarked that it is now so easy to plan travel by sitting at one’s desk that IT could well have increased travel. Similarly, teleshopping, or e-commerce, has also not fulfilled its early predictions; after more than a decade, e-commerce still only accounts for a 4 % share of all retail sales (US Census Bureau 2012), although for the category of computer hardware and software the share is much higher. With such a low overall share (and even at a much higher share, say 20 %), the effect on shopping trip frequency will probably be negligible, since a large variety of purchases are usually made on each shopping trip, even if only one shop (for example a super-market) is visited. It may also be true that much on-line shopping is additional to traditional shopping, and not a substitute. None of these proposals for travel substitution is really new – all have low-tech precedents. A small proportion of the workforce has always worked from home. Mail order catalogues enabled remote shopping more than a century ago. Today, a telephone and a mailbox are still all that is needed for teleshopping. But whether a letter, telephone, or networked computer is used for ordering merchandise, it still needs to be physically delivered to the householder – with the exception of software. Any saving in private travel will thus be partly offset by a rise in freight vehicle travel. “Cyber universities” are less discussed today than they were a decade ago, but they are really just a new version of the old correspondence courses. In all, greater change probably came from the introduction of instantaneous communication with the telephone and the radio, than from the later introduction of modern IT. Even if reductions in surface travel will not naturally occur by either the operation of travel time budgets or IT substituting for travel, there are other, more recent, arguments for future travel reductions. William Rees (2009) is a researcher who has a very pesimistic view on the likelihood of anything approaching “business-as–usual” in future cities. But his doubts are based on the need for very large reductions in both greenhouse gas emissions and oil consumption, and the limited ability of technical solutions like alternative fuels or efficiency gains to deliver in the limited time frame available. All these views are in sharp contrast to the travel forecasts for OECD countries offered by various international and national authorities. The US Energy Information Administration (EIA) (2014), in its Annual Energy Outlook 2014, saw a gradual fall in US transport energy use, from 2012 to 2040, with transport energy in 2040 being 4.3 % below that in 2012 in the base case scenario. Nevertheless, vehicle-km by light vehicles was forecast to grow steadily from 2012 out to 2040 in the base case, even though it fell in the aftermath of the Global Financial Crisis. The IPCC (Sims et al. 2014) warns that “Without policy interventions, a continuation of current travel demand trends could lead to a more than doubling of transport-related CO2 emissions by 2050 and more than a tripling by 2100 in the highest scenario projections.” The Organization of the Petroleum Exporting Countries (OPEC) (2013) gave an estimate of 897 million private transport vehicles in the world in 2010 and projected that this figure would rise to 1875 million in 2035. Although about two-thirds of all cars are presently in the OECD, the future annual growth in private vehicles in the OECD was forecast to be under 1 %. For China,

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OPEC forecast car ownership to grow from 58 million in 2010 to a massive 442 million in 2035. This optimistic forecast assumes, of course, that neither oil availability nor concerns about global climate change impose limits.

Non-Motorized Travel Most official future travel projections simply ignore non-motorized travel. If discussed at all, it is in the context of future travel in low-income countries. Schafer and Victor (2000) assumed that non-motorized forms of travel would be too slow for their time-constrained, high mobility future. Both the reports of the World Business Council for Sustainable Development (WBCSD) (2004) and the earlier IPCC reports devoted little space to non-motorized travel, with the WBCSD report assuming that it will gradually disappear as low-mobility societies move up the “ladder of mobility improvement,” by which is meant that motorized travel will supplant it. Non-motorized travel was thus regarded as an inferior travel mode, and technical solutions (alternative fuels, vehicle efficiency improvements, etc.) were seen as the most important means of tackling climate change. The very few available projections are thus usually only from advocates of these travel modes. Geurs and van Wee (2000) used backcasting to examine what changes were needed for a reduction in Dutch transport GHG emissions of 80–90 %. They concluded that compared to their “business as usual” scenario for 2030 transport, bicycle use, already high in the Netherlands (as shown in section “Non-Motorized Travel”), would need to double in terms of passenger-km in their major emissions reduction scenario. Given that car travel and motorbike/moped travel would need to be reduced by 50 % and 75 %, respectively, it is clear that cycling would become a major travel mode. The present role of walking and cycling in the Netherlands demonstrates what is politically possible, even today. Income levels in the Netherlands are higher than most countries in the OECD, so that, unlike the situation in low-income countries, the popularity of these modes is not based on economic necessity. And at 51–54 N, the climate is less benign for walking/cycling that most other OECD countries. Nevertheless, its flat terrain and high population density are advantageous. In all OECD countries, however, there is increased concern about obesity and personal fitness (Pucher and Dijkstra 2003; Sallis et al. 2004). Non-motorized travel modes are well-placed to benefit from this concern.

Creating Environmentally Sustainable Behavior Changing behavior as a means of achieving environmentally sustainable ends such as household travel and energy reductions is attractive because in principle it can be introduced rapidly. In fact, during gasoline shortages, changes in travel behavior can happen overnight, as motorists car pool, walk or use public transport to get to work. (However, after the emergency is over, very little permanent change in travel patterns has been observed.) These measures can also be very cheap to implement, compared with most other alternatives, and if voluntary, carry few political costs. The

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important questions to ask of psychology are the following: How much change can be expected? Which approaches work best? Do voluntary approaches work better than more coercive approaches? Which demographic groups are most likely to change? In this section an attempt will be made to answer these questions, first for general environmental change and then for transport change.

General Principles for Change Linda Steg (2008) has discussed three factors she considered important in promoting more environmentally sustainable behavior at the individual or household level: knowledge, motivation, and ability to make the necessary changes. Below, these three points are discussed in turn, then the significance of the findings for promoting pro-environment behavior (PEB) in general is discussed. Knowledge is a necessary condition for adopting PEB. People have to be aware of the consequences of their consumption, such as their household domestic electricity use or private car use, on the physical environment. But consequences are not always easy to determine. For instance, the public’s knowledge of the facts on climate change, and the reasons why nearly all climate scientists regard climate change as a serious problem, is generally poor, even among the educated populations of the OECD countries. The immense complexity of the climate change problem, with its multiple feedbacks operating at varying time scales, is one cause. Others include the significant natural variability of climate, making unambiguous attribution of cause difficult, and the stress on this uncertainty by industry groups with a strong interest in continued inaction on climate change. Second, not only is knowledge important, but the public must be motivated to change their behavior in a more environmentally appropriate direction. When surveyed, most people in OECD countries profess to be concerned about the environment in general, but such concern does not always translate into action, as is shown by the continued rise in household energy consumption in many OECD countries, for example. Further, in the case of climate change mitigation, the link between individual reductions in GHG emissions and environmental benefit, particularly local, is tenuous. Other factors important for success or otherwise in achieving behavioral change include any extra costs and effort incurred, or any reduction in personal convenience. Policies will thus be more effective if they simply involve purchase of more energy-efficient equipment and do not restrict perceived freedom of choice (Steg 2008). Recycling involves no monetary costs and has been made convenient by the provision of recycling bins at households and businesses, and so has been widely adopted. Unfortunately, much household recycling may be only of marginal benefit in achieving ecological sustainability (Wikipedia 2014). De Groot and Steg (2009) have further argued that ethical arguments (altruistic and biospheric considerations) for change in household practices are more effective than other approaches, such as those that stress cost savings. As they put it, it is better to get people to “act green” than to “act mean.” Cost saving arguments can come undone when, for example, energy costs fall or household circumstances change. An

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illustration of the former is the steep decline in sales of more energy-efficient hybrid electric vehicles in the US, following the fall of gasoline prices after mid-2008. Nevertheless, countries with higher costs for gasoline and domestic electricity and natural gas, in general use less energy. Third, people must also be in a position to make the necessary changes. Money is often a barrier. Many households may not have the financial means to buy the new, more energy-efficient equipment, or to pay for retro-fitting their house to cut heating energy. They may find it easier to continue paying higher monthly or quarterly bills than to find the money for an energy efficiency improvement. It is not only physical or financial impossibility that matters; even cultural norms may make an action perceived as impossible. Given these conditions needed for change, some suggestions for general strategies to promote environmental changes follow. Promoting the purchase of more energy-efficient appliances (such as compact fluorescent globes in place of incandescent ones) can be a succesful strategy, especially if, as in this case, not only are the purchase costs low, but households suffer little inconvenience from the change. In the case of compact fluorescent globes, both costs and inconvenience were so minor that several governments have been able to mandate the phasing out of the less-efficient incandescent globes (Brown 2009). Changing the costs of energy, for example through a carbon tax, can also help reduce energy consumption, as can increasing the costs of travel. The road pricing schemes in London, and particularly Singapore, have had some success in reducing travel levels and marked success in changing travel patterns. Researchers have found that higher income groups respond best to interventions for improving PEB. Studies in the US has shown that such groups are more likely to participate in “green energy” programs. For Australian capital cities, high income and high education households were also found to be more likely to have a strong environment commitment (Moriarty and Kennedy 2004). Torgler and GarcíaValiñas (2007) also reported that both better-educated and higher income individuals usually had stronger pro-environmental attitudes. They reasoned that “Wealthier citizens may have a higher demand for a clean environment and less environmental damages.” On the other hand, in the US, sports utility vehicle ownership is much higher among the more affluent, and air travel in all countries is similarly concentrated among the well-off. Clearly, the issue of environmental support is a complicated one, where actions may not coincide with attitudes (Kennedy et al. 2009). Thus the relationship between PEB and socioeconomic status is much more complex than revealed by surveys. Lower income households in OECD countries can be regarded as “involuntary environmentalists,” because their per capita use of public transport is greater, while their use of domestic energy or water, is usually lower than that for higher income households. Similarly the higher levels of environmental concern usually (but not always) found for females (Torgler and GarcíaValiñas 2007) could have a similar basis. In any case, as shown in section “Present Transport Patterns,” female use of more environmentally friendly transport modes is today not much better that that for males. These comments on involuntary environmentalism apply with even greater force to low income households of the

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industrializing world. Nevertheless, higher income households, despite their greater resource use, are more likely to respond to campaigns for increased PEB (Gifford and Nilsson 2014).

Changing Travel Behavior It is widely agreed that changing travel behavior is far harder than changing behavior for recycling or even general domestic energy conservation (e.g., Garling and Schuitema 2007; Dietz et al. 2009; Gifford and Nilsson 2014). In general, external constraints, whether real or perceived, on changing travel mode are usually severe in the car-oriented countries of the OECD. An important constraint is that alternatives to the car for any given trip usually involve longer travel times. It follows that bringing about voluntary change can be expected to be much more difficult than promoting other forms of pro-environmental behavior such as recycling. In addition, there are strong psychological benefits of car travel which other modes cannot match. Clearly, transport GHG emission reductions would be easy if a carbon-neutral fuel was readily available at about the same price as existing petroleum-based transport fuels and could be used in existing vehicles. Proenvironment behavior would then be as easy as shifting to another brand of gasoline. But such a convenient solution to transport’s GHG emissions will not be available for decades, if ever. Other approaches, such as travel demand management (TDM), are needed. Dietz et al. (2009) have examined ways in which US households can voluntarily cut their carbon emissions. From behavioral research, they estimated that, nationally, the “reasonably achievable emissions reduction” potential in the household sector overall is 20 %. This reduction can be achieved in a decade, they argued, if “the most effective nonregulatory interventions are used.” Although about 45 % of the estimated savings came from reductions in private vehicle fuel use, only about 11 % of this transport total came from travel reduction measures, namely from car pooling and trip chaining. Overall then, only 1 % (20 %  0.45  0.11) of all household sector emissions could be reduced by voluntary TDMs. The authors assumed that only 15 % of households that were not currently car pooling or trip chaining would in fact voluntarily do so, if the most effective interventions were employed. In contrast, 90 % of households were anticipated to weatherize their houses. Another US study (Greene and Schafer 2003) surveyed a large number of potential TDMs, both voluntary and legislated, to reduce vehicle-km of travel, including car pooling, congestion pricing, use of telecommuting, and land use planning. They estimated that combining all these approaches might reduce vehicular travel by around 10 %. Even this low figure – relative to what section “Introduction: Travel Reductions for Climate Mitigation” showed might be needed – they saw as representing an enormous challenge. Garling et al. (2000) investigated the potential for voluntary reduction in car use by interviewing a number of randomly selected households in Goteborg, Sweden.

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Respondents had reported beforehand they could eliminate at most 10 % of their car trips over the 8 days of the survey, but their actual reduction achieved over these 8 days was even less, because of unforeseen car trips. Stated intentions to reduce car travel were thus very different from actual behavioral changes. The authors concluded that a 10 % reduction, the same value as found for the US, was the most that could be expected from noncoercive measures. Also in Goteborg, Hagman (2003) interviewed motorists about what they perceived as the advantages and disadvantages of car use. Interviewees were found to present the advantages in terms of their personal experience, for example, time savings. But only some disadvantages were based on personal experience; most were based on abstract arguments about adverse environmental effects. These arguments were derived from the media. Hagman thus concluded that “knowledge about advantages becomes absolute while knowledge about safety and environmental risks becomes relative and negotiable.” He speculated that this difference could explain why presenting motorists with information on car travel’s environmental costs has been unsuccessful in reducing driving. It was reported above in section “General Principles for Change” that knowledge of the effects of consumption are considered important for promoting PEB in general. Tertoolen et al. (1998) used a field experiment in 1992 in the Netherlands to explore motorists’ resistance to travel mode change. They found that providing information to car drivers on the monetary and environmental costs of car travel produced no measured reduction in driving, in line with other research. But Tertoolen and colleagues went further and claimed that information campaigns to reduce car use could have undesirable side effects. Their explanation was in terms of cognitive dissonance. If motorists cannot reconcile their general proenvironmental attitudes with information that their car use is damaging the environment, the dilemma can be resolved in two ways. The societally preferred way is of course to change behavior, but another way is by revising or even discarding their original proenvironmental attitudes. The authors show that the latter approach was common among their respondents. Motorists seem to react negatively to being branded as polluters, so that such an approach may not be at all effective in persuading them to use their cars less (Moriarty and Kennedy 2004). Not all researchers would agree with De Groot and Steg (2009) that it is better to get people to “act green” rather than “act mean,” at least for changing transport behavior. Wardman et al. (2007) used both revealed preference and stated preference surveys and modeling to find the most effective policies for reversing the steep decline in cycling noted in section “Non-Motorized Travel” in Great Britain. They argued that the best policy was a financial incentive for cycling to work. Payment of UK ₤2 daily to cyclists was found to double the level of cycling to work, whereas complete provision of segregated cycleways, an expensive undertaking, would only raise cycling by 55 %. Whether such modeled increases would actually occur is of course uncertain, but in any case, even a doubling of cycling commuter share would do little to reduce overall GHG emissions. In an another recent study on factors affecting the success of programs to increase the use of cycling, Pucher et al. (2010) wrote:

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The current level of bicycling in a community also affects bicycling safety and the potential to further increase bicycling. Several studies have demonstrated the principle of “safety in numbers.” Using both time-series and cross-sectional data, the studies find that bicycling safety is greater in countries and cities with higher levels of bicycling, and that bicycling injury rates fall as levels of bicycling increase. As the number of cyclists grows, they become more visible to motorists, which is a crucial factor in bicycling safety.

They added that as cycling use increases, “a higher percentage of motorists are likely to be bicyclists themselves, and thus more sensitive to the needs and rights of bicyclists.” They also showed the complexity of responses to policy initiatives to encourage cycling. Noncyclists in bicycle-oriented cities may respond much more positively to a given set of programs or infrastructure provision than noncyclists in cities with few cyclists. Context is very important. (Their findings are supported by the experience of cycling in Melbourne, discussed in section “Non-Motorized Travel,” where it was shown that cycling to work collapsed in the 1950s – at precisely the time that car travel was growing rapidly.) Similar conclusions probably apply to policies to encourage walking – and even public transport. Thus the overall empirical findings of behavior change psychologists and other researchers suggest that the prospects for voluntary travel reductions, at least, as a means of cutting energy use or GHG emissions, are not promising. Even using the most effective campaigns, only modest changes can be expected from voluntary transport change programs and even less from general media campaigns. These projected changes in travel behavior are small and reflect only the likely reductions in a “business as usual” transport future. As will be shown later, the context in which the changes are to take place matter a great deal. Even noncoercive measures could be effective if it becomes clear to the general populace that continuation of present practices is no longer an option. Unfortunately, in the context of adverse climate change, it was shown in section “General Principles for Change” that this is presently not the case. Table 3 provides a list of TDMs under four categories, along with the percent savings considered possible by Greene and Schafer (2003) for individual measures. Both voluntary measures and what were seen as politically possible coercive interventions are included. In the next sub-section, a major voluntary trave change program in Australia is examined, and it is concluded that the findings of the psychologists are largely vindicated.

Voluntary Travel Reductions: An Australian Case Study To evaluate the effectiveness of voluntary schemes, a case study from Australia is provided. In Australia, voluntary approaches to car travel reduction have mainly taken the form of TravelSmart interventions to encourage more use of environmentally friendly modes (EFMs) of travel – public transport, walking, and cycling. In contrast to other major Australian cities, where interventions have been small or nonexistent, the intervention in Perth, a city of about 1.7 million, was both far more

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Table 3 Summary of travel demand reduction methods General TDM category Physical change measures

Legal policies

Economic policies

Information and education measures

Travel reduction method Area-wide ridesharing Bicycle/pedestrian travel improvements Land-use planning to reduce trip distances e.g., mixed land use, “smart growth” Park-and-ride lots Public transport improvements e.g., improved intermodal interchanges High-occupancy vehicle (HOV) lanes Prohibiting traffic in city centers Decreasing speed limits Compressed work week Parking control Telecommuting Parking pricing: work Parking pricing: nonwork Congestion pricing Tax on emissions per vehicle-km Decreasing costs for public transport Individualized marketing Public information e.g., advertizing campaigns for public transport Giving feedback about consequences of behavior Social modeling e.g., role model endorsement of public transport

Greene and Schafer (2003) vehicle-km savings estimates (%) 0.1–2.0 Less than 0.1 0.0–5.2

0.1–0.5 0.0–2.6 0.2–1.4 NA NA 0.0–0.6 NA 0.0–3.4 0.5–4.0 3.1–4.2 0.2–5.7 0.2–0.6 NA NA NA NA NA

Sources: Greene and Schafer (2003), Rajan (2006), Garling and Schuitema (2007)

extensive and also earlier than in other cities, enabling an evaluation of the program. The main idea was to target the less-committed motorists in a selected municipality, in recognition of the fact that while some of their trips have to be made by car, for many other trips presently made by car, EFMs are a real option, and the change could be made with only marginal loss of convenience. By providing information on these EFMs, the TravelSmart programs tried to shift some car trips to these modes. The information was tailored to the needs of the individual household, with local timetables for buses provided. Such programs in Perth have now been in operation for more than a decade, and most of the city’s total population have been targeted, so that reductions should appear at the city-wide level. As will be discussed later in section “Reducing Travel: Changing Urban Land Use Patterns” (see Table 5), levels of car passenger-km per capita, or car ownership, are today no lower than the

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Table 4 Central Metropolitan Perth, Victoria Park, and South Perth journey to work, 1996 and 2001

Year Population Light vehicle travel (%) Car occupancy rate Public transport (%) Walk/cycle (%) All EFMs EFM % rise 1996–2001

Central Metropolitan region 1996 2001 117,700 121,950 78.2 75.5 1.09 1.08 11.9 13.2 8.1 9.5 20.0 22.7 13.5

Victoria Park municipality 1996 2001 26,720 27,690 76.1 75.9 1.12 1.10 15.8 16.8 5.9 5.6 21.7 22.4 3.2

South Perth municipality 1996 2001 36,450 37,520 83.7 81.9 1.10 1.09 10.7 11.2 3.9 4.8 14.6 16.0 9.6

Source: Moriarty and Kennedy (2004)

average for Brisbane and Adelaide, cities closest in size and urban density. The initial municipality for comprehensive TravelSmart intervention was South Perth, which had blanket intervention in 2000. It is therefore useful to compare South Perth with the adjacent areas of Victoria Park and the Central Metropolitan region as controls, both at the 1996 Australian census, before the South Perth intervention, and 1 year later at the year 2001 census. As evidenced by the journey to work data in Table 4, no shift to a higher share of EFMs, or to a higher occupancy rate for the work trip was found as a result of the intervention 1 year earlier. Any gains that were initially made thus do not appear to have persisted, although a 2006 evaluative report on all the Australian TravelSmart programs (Australian Greenhouse Office 2006) suggested that there is some “evidence that changes appear to be sustained for at least 5 years without maintenance or further intervention.” And from the government TravelSmart website, it is evident that activities have ceased in recent years (TravelSmart Australia 2008). In fact, the website has not been updated since October 2008. But governments are willing to try these programs because it puts the responsibility on individuals to make the changes rather than on politicians facing re-election. European experience with voluntary schemes has been similar. Garling and Schuitema (2007), after surveying the use of voluntary measures for TDM, summarized their findings thus: The conclusion is that non-coercive TDM measures alone are unlikely to be effective in reducing car use. Therefore, coercive TDM measures such as increasing cost for or prohibiting car use may be necessary but are difficult to implement because of public opposition and political infeasibility.

In summary, whatever the importance of voluntary approaches for promoting general conservation practices, they have not worked for private travel. The remainder of this chapter thus mainly looks at non-voluntary measures for reducing travel demand.

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Reducing Travel: Changing Vehicle Occupancy Rates Increasing the occupancy rate for cars appears to be an attractive greenhouse reduction method, for several reasons. First, it can be implemented with the existing vehicle fleet. Second, the costs are low compared with other approaches. Third, the potential is large: occupancy rates in OECD countries today are typically about 1.5 persons per car, or 30 % occupancy for a five-seater car. What is more, they were historically much higher, at around two persons per car in Australia and the US in the 1960s (Moriarty and Honnery 2008b). Policies for increasing occupancy rates for personal vehicles can be voluntary or mandated. Neither approach has enjoyed much success. An important reason is that in all OECD countries, average household sizes have fallen in step with completed family size. In Japan, persons per private household have fallen from 3.28 in 1975 to 2.42 in 2010 (SBJ 2014). Fewer family members are then available to fill the car for weekend social trips. Figure 2 shows how US car occupancy rate (sports utility vehicles not included) has fallen in step with average US household size. The occupancy rates for cars appear to be tied very closely to the occupancy rates for houses. In addition, cars per 1,000 population have risen in all four countries. As an example, in Melbourne, Australia, the car occupancy rate for the journey to work correlates almost perfectly (R2 = 0.99) with persons per light vehicle available (Moriarty and Mees 2006). This suggests that occupancy rates for cars will be hard put to even maintain their present level if either car ownership continues to rise or household sizes continue their fall in OECD countries. But even if a law was passed (and adhered to by motorists) requiring that average occupancy rates be doubled, it is doubtful that the net GHG reductions would be very significant. In order that roads do not choke up, a car-based passenger transport system requires trip origins and destinations, and so traffic, to be dispersed in both space and time. Only for commuting, with its low occupancy rates (less than 1.1 persons per car for Australian cities today), and travel concentrated in morning and evening peaks, would (say) a doubling of occupancy rates be feasible. But whether GHG reductions would follow is uncertain: in California, Greene and Schafer (2003) reported that a car-pooling scheme did raise commuter car occupancy rates while in operation, but only at the expense of public transport patronage. Overall, they saw “area-wide ridesharing” as having the potential to reduce total US vehicle-km by 0.1–2.0 % and HOV lanes by 0.2–1.4 % (see Table 3). Car pooling can also conflict with attempts by motorists to combine different trip purposes, another method of reducing car travel (i.e., vehicle-km traveled). To the extent that a car-pooling scheme was successful, it would radically change the meaning of private travel, replacing the perceived tyranny of public transport timetables with the new tyranny of dependency on the punctuality of others, often nonfamily members. Further, the circuitry of such chauffered trips will increase the total vehicle-km traveled, partly offsetting any GHG reductions. Since much of the easily arranged car pooling is already being done, it can be expected that major rises in car pooling would greatly increase this circuitry factor.

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Fig. 2 Average household size versus car occupancy rate, US, 1960–2005 (Sources: US Census Bureau 2012; BTS 2014)

For public transport, the position is very different. As public transport loses patronage, the occupancy rates of public transport vehicles decrease. For the case of electric tramsin Melbourne, Australia, the occupancy rate fell from 24.6 in 1960, with overall patronage 783 million pass-km, to only 18.3 in 1980, 442 million passkm (Newman and Kenworthy 1989). As patronage has grown strongly in recent years, occupancy is once again rising. Similar changes have been observed in Great Britain. Bus occupancy was 19 passengers per bus for 61.4 bp-k in 1974, fell to 8 passengers in 2000 at 46.2 bp-k, and has since risen to 10 passengers in 2007 at 50.8 bp-k (DfT 2013). Unlike car occupancy rates, public transport occupancies are independent of household size. What this suggests is that public transport systems are often capable of much higher occupancy rates (but not often at peak hour, when many services are already at capacity loadings). Hence a shift to public transport from car can give a double boost to GHG reduction: one from the higher energy efficiency per seat-km that public transport enjoys over car travel, and second, from the higher occupancy rates possible from higher loadings (Moriarty and Honnery 2007, 2008b). The reason for these occupancy rate changes is that when patronage falls, operators try to maintain service levels to prevent further passenger desertion. Conversely, as patronage rises, as is happening on many public transport systems in the OECD today, the rising patronage is initially accomodated on existing services, with additional services provided as required. In effect, if public transport patronage rises because of higher fuel prices, or rising congestion, seat occupancy increases naturally without any specific policy needed, either voluntary or nonvoluntary, for its increase.

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In summary, public transport occupancy rates can be expected to rise, but the prospects for higher levels of car pooling are poor. Car pooling goes against several of the perceived advantages of the car, including privacy, direct travel between origin and destination, and no waiting (time of travel solely at the discretion of the driver). Instead, car pooling involves the need to negotiate with others, required levels of puntuality, choice of on-board music, and degree of driving caution. And even if car pooling could be politically mandated, the rise in occupacy rates would be partly illusory. In purely serve-passenger trips, the driver should not be counted as an occupant; public transport drivers are not counted. Increasing occupancy rates are not useful unless total transport GHG emissions are thereby reduced as well.

Reducing Travel: Changing Urban Land Use Patterns Changing land use patterns is really only a mobility reduction option for urbanized areas, but in the OECD countries, 80 % or more of the total population live in urban areas. Many urban researchers have proposed such changes in existing cities as a means of both reducing vehicular travel overall, while increasing the share of public transport (e.g., Newman and Kenworthy 1999, 2006; Handy et al. 2006). The most discussed urban land use changes are policies to encourage (or mandate) increases in urban density. After allowing for differences in the definition of urban density for different cities – particularly if the cities are in different countries – urban densities can still vary by more than two orders of magnitude for different cities of the world (Newman and Kenworthy 1999). Figure 3 shows the exponential relationship for private travel versus urban density for 46 cities in Asia, Australia, Western Europe, and North America. Not only car travel, but all vehicular travel per capita, and transport energy consumption per capita, show similar curves. While the density-private travel relationship is indeed strong, some caveats are in order. Australian and US cities, nearly all with densities of 1,000–2,000 persons/ km2, form a distinct group along the upper left-hand axis. For them, travel variations seem unrelated to density; all US cities had higher levels of car travel than any Australian city, even though the urban densities for the two countries fully overlapped. At the other extreme of the graph, in the bottom right-hand corner, lie six Asian cities, with very high urban densities and low levels of car travel. However, several also have much lower income levels than the other cities shown, and lower incomes will reduce both car ownership and travel. The second problem relates to the definition of each city. The older cities of Europe often have boundaries that are much more restricted than those of Australian or North American cities, so that many of what would be called outer suburbs in the latter regions are excluded. Outer suburban residents typically travel much more than those living closer in and travel more by private transport (Moriarty 2002a). The result is lower recorded overall per capita urban travel levels in Europe’s cities that would be the case if more extensive urban boundaries were used. Travel per capita by residents in higher density areas of cities is usually lower than in areas of low density. A US example of this is found in the analysis by Fan and

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Fig. 3 Private vehicular travel per capita versus urban density, 46 world cities, 1990 (Source: Newman and Kenworthy 1999)

Khattak (2008) of the results of the 2006 Greater Triangle Region Travel Study in North Carolina. They concluded that travel overall in the region could be reduced by densification. But urban density tends to decrease with distance from the city center, and, as has just been shown, outer suburban residents travel more than inner city residents. An alternative explanation for their result might be that per capita travel rises with distance from the city center, as found for Melbourne, Australia (Moriarty 2002a). The different areas of a city together form an interdependent urban system. If the inner city contains a surplus of workplaces over resident workers, as is true for many major cities, then workers from other areas must travel to fill these jobs. Similarly, the inner areas of major cities contain a variety of institutions and venues that are meant to serve the city as a whole, or even the entire region, many of them housed in or adjacent to the CBD. Examples include specialized shops and services, theatres, art galleries, and sports stadiums. Travel needs for inner area residents to these locations are minimized, but are of course higher for other urban residents. Overall, of course, this arrangement of activities is efficient, minimizing total metropolitan-wide travel for (say) a major sporting event. Also helping reduce inner area car travel is the radial nature of many fixed rail urban networks, which results in denser and more frequent services there, and hence much greater public transport use per capita. Higher traffic congestion also discourages inner city residents from using cars for travel. Looking at the four countries chosen, the urban densities of the three major Japanese cities – Tokyo, Osaka, and Nagoya – are far larger than those of the largest cities in Australia, the US, or even the UK. Indeed, the total annual number of motorized trips within a 50 km radius of central Tokyo was only slightly higher in 2009 than in 1995, and for street travel only (public and private), was lower in 2009

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than in 1995. In a 50 km radius of central Osaka, vehicular trips also declined, with the total again lower in 2009 than in 1995 (SBJ 2014). The very high job and population densities in these Japanese cities seem to have led to a saturation level for per capita vehicular travel at low levels compared with US or Australian cities. Further, only one-third of Tokyo trips, and about two-fifths of Osaka trips, are by private car. In Japan overall, the “car ownership intensity” (cars owned – which reflects car use – per unit of Prefectural Gross Income), correlates strongly (R2 = 0.8) with the share of each prefecture living at high density (Moriarty 2007). A strong case can thus be made that very high urban densities, at least, lead to higher public transport patronage and far lower car travel levels. Higher urban densities can potentially influence urban mobility levels (and mode choice) in two ways. First, for a given income level, a higher density city can support a higher density of shops and services of all kinds, simply because, for example, the total retail expenditure per km2 will be higher. The distance to the nearest shopping center should therefore be lower in denser cities. The problem is that urban residents today don’t necessarily use their nearest shopping center. A shopping survey from the 1990s in the city of Canberra, Australia’s capital city with a population of around one-third of a million, illustrates this point (ABS 1998). Canberra, unlike other major Australian cities, was consciously planned to have a defined hierarchy of shopping centers. In order of increasing size they are local centers, group centers, and town centers. In the survey, a local center was the nearest shopping center for 69 % of the city’s population, a group center for 27 %, and for a town center, only 4 %. Yet only 19 % of households overall usually did their major food and grocery shopping at their nearest center. For the majority living nearest to a local center, nearly all of which have supermarkets, the figure fell to 5 %. (Nearest centers were, however, more popular for convenience items.) These findings can only be partly explained by the fact that the larger shopping centers were often closer to their workplaces, and sometimes presumably accessed from there. These results can probably be extended to trip types of all kinds, as well as to other cities where, like Canberra, car travel is still perceived as both convenient and cheap. In support of this point, Moriarty and Beed (1988) compared the 1981 actual average trip length (airline) for the journey to work in Australia’s major cities with the minimum average trip distance possible if all residences and workplaces were fixed, but workers could freely change workplaces. They found that such a change could halve work travel. Again, proximity to workplaces is not a sufficient condition for travel reduction. By how much could urban density increases reduce vehicular travel and thus GHG emissions? Australia’s five cities of one million-plus population provide a useful case study, particularly since the data are all collected using a common format. These cities – all state capitals – vary by over a factor of two in urban density from Brisbane to Sydney (see Table 5). Yet the two densest (Sydney and Melbourne) had a slightly higher level of vehicular passenger-km per capita than the three lower density cities (Brisbane, Perth, Adelaide). However, per capita public transport travel was much higher in these denser cities.

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Table 5 Personal mobility, population, urban densities, five largest Australian cities, 2011

City Sydney Melbourne Brisbane Perth Adelaide

Population (millions) 4.637 4.208 2.169 1.865 1.270

Car (b-pk) 50.23 49.40 24.94 21.40 12.97

Public transport (b-pk) 7.95 6.02 2.25 1.64 0.83

Vehicular travel per capita (pass-km) 12,545 13,170 12,540 12,355 10,865

Densitya (persons/ km2) 2,058 1,532 918 1,090 1,295

a

2006 values Sources: Moriarty and Mees (2006), BITRE (2013)

For low density cities, advances in traffic engineering techniques, together with the spread of traffic to off-peak times, may be able to accommodate some rise in urban density without making congestion much worse, which could explain the lack of response in Australian cities. For the US, Greene and Schafer (2003) reported that a doubling of local population and employment densities would only give a 5 % reduction in vehicle-km traveled (Table 3). So, at best, even doubling the urban density of the smaller, lower density cities would achieve little in the way of travel reductions. It might be objected that for low-density Australian and US cities, all the above example shows that a mere doubling of urban density is not enough. But it is one thing to have the historically very high densities of many Asian cities – up to ten times Australian and US levels – but another to try to convert historically low density cities to very high density. It would also be enormously unpopular, and would in effect replace the political resistance to policies that directly reduce car travel (discussed below) with equally unpopular policies that might indirectly reduce travel. Urban infrastructure has a lifetime of many decades – up to 70 years for houses, and even longer for transport right-of-ways. Even if the very large density changes were possible, it would take many decades to achieve. The world may not have that long for responding effectively to the challenge of global climate change. A final argument against such large density increases concerns GHG emission reductions overall in the economy. Transport is an important, but not the only source of, emissions. All sections of the economy, not just the transport sector, will need to undergo drastic cuts in GHG emissions. An environmentally sustainable city might need somewhat lower density living to allow for households to supply much of their water needs from rainwater tanks, at least some food (mainly fruit and vegetables) from gardens, and part of their energy from rooftop photovoltaic cells and solar water heaters (Moriarty 2002a). Neither the patterns found for Japan’s largest three cities, nor those for the 13 US major cities analysed by Newman and Kenworthy (1999) fits this Australian pattern of vehicular travel per capita being independent of city size and density. In Japan, vehicular trips per capita in 2005 still showed a small increase with city size and population density (SBJ 2014), perhaps reflecting the continuing importance of public transport in these cities. This trend would fit in with the Australian experience,

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where in 1947, when public transport dominated vehicular travel in Australian cities, vehicular travel per capita was higher in the higher density cities (which were also larger in size). In the US, there is a weak trend for cities with higher densities to have lower per capita vehicular travel – the opposite of Japan’s experience, but more in line with the general world trend of per capita travel falling as urban density increases. In summary, the very high historical urban densities achieved by the cities of Japan (and other Asian countries such as South Korea and China) do form an important constraint on the level of vehicular travel possible. At the low densities of many Australian and US cities, however, politically achievable density increases might not have much effect on total travel levels, although some shift to public transport should occur. But the short time frame the world has for climate change amelioration means that policy makers will have to work with cities largely as they presently exist. Further, as will be seen in section “Reducing Travel: Lowering the Convenience of Car Travel,” for many cities the changes are unnecessary; the same result can be achieved by much more rapidly implemented changes to legislation.

Reducing Travel: Raising the Overall Level of Motoring Costs Another possible approach is to increase significantly the costs of motoring, by adding further taxes on motoring fuels, and perhaps also increasing urban parking charges. Taxing motoring fuels has the advantage of reducing both urban and nonurban travel. Already, fuel taxes differ widely in the various OECD countries. Indicative gasoline and diesel prices for the year 2013 for various OECD countries, including those with the highest and lowest prices, are shown in Table 6. Since neither feedstock costs not refining costs vary much from country to country, most of the difference is due to different fuel taxes. Within the OECD countries, both gasoline and diesel prices vary by a factor of three. Combining this data with that for recent car travel from Fig. 1 suggests that the higher fuel prices found elsewhere in the OECD compared with the US is mainly responsible for the much higher levels of per capita travel in the US. However, comparison of Japan and the UK shows the importance of factors other than fuel prices. Recent UK per capita car travel is 66 % higher than that in Japan, despite the higher gasoline prices in the UK. Less road space per vehicle in Japan, resulting in low travel speeds, is an important factor. Car travel in Australia is in turn higher than the UK, and petrol prices are lower. But when the higher urban densities of UK cities are also considered, and the lower national road space per vehicle, it seems that unacceptably high fuel price rises would be needed in Australia to ensure sufficient mobility reductions. Nevertheless, by raising fuel taxes to a very high level, it would be possible to reduce car travel to any desired low level, both in urban and non-urban areas – assuming political feasibility – just as it was concluded that raising urban densities to very high levels would. It would also be very inequitable, particularly in Australia and the US, as suggested by the analysis above. In both these countries, households

1096 Table 6 Indicative 2013 gasoline and diesel prices

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Country Australia Germany Italy Japan Mexico Norway Turkey UK US

Gasoline (super) ($/l) 1.61 2.11 2.34 1.66 0.91 2.59 2.68 2.09 0.98

Diesel ($/l) NA 1.60 1.85 1.30 0.78 1.86 2.40 1.84 1.06

Source: IEA (2013)

having access to at least one car are fairly uniformly spread over all income groups, and only around 10 % of households are noncar owning. In Australia, at least, outer suburban households have, on average, a much lower income on a per capita basis compared with inner suburban households, but higher car ownership levels. They also have greater travel needs and have inferior public transport services (Moriarty 2002a). (In lower-income countries, on the other hand, where car ownership is often under 20 per 1,000 persons (OPEC 2013), raising fuel taxes would present much less of an equity problem.) Surveys of motorists generally show that the respondents think that raising car travel costs will not be very effective in reducing travel (Steg 2008). But the actual responses to fuel cost rises tell a different story. (However, it may be that what the respondents really mean is that they do not likefuel costs rises and would prefer to see other measures adopted, such as cheaper, or more extensive, public transport provision.) Evidence for the efficacy of raised fuel prices comes from the effect of price rises on gasoline sales in the years before the global financial crisis. In Australia, per capita sales of fuel for light road vehicles peaked locally in 2004, and in 2012 were still below their 2004 level (ABS 2013). Similar effects seem to have occurred in a number of other OECD countries. The fixed costs of car travel (including depreciation, registration, and insurance costs) presently dominate the annual costs of owning and running a car. For the US, Greene and Schafer (2003) found that for a 2001 model year car, gasoline costs were only 10.2 % of the total annual costs. However, this gives a misleading impression of their actual significance to motorists. Since fuel and parking costs are usually all that motorists perceive as the costs of car travel on a day-to-day basis, altering the structure of motoring costs could also reduce car travel. At present, motorists can significantly reduce their unit costs by traveling more kilometers annually. Insurance and registration fees could be recovered by raising fuel taxes and could even be done so that the overall costs of motoring did not change for the average motorist. High annual travel motorists, however, would find themselves paying more per kilometer traveled, so that, once again, lower income outer suburban households might be disadvantaged.

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Road pricing is an alternative market-based approach. Road space worldwide is still largely publicly provided, and freely available to all road users, regardless of the resulting congestion. Although toll roads, many of them privately owned, are centuries old, road pricing as a means of controlling traffic levels really began with the successful scheme in Singapore in 1975. The comprehensive and successful London scheme introduced in 2003 has led to renewed interest in road pricing in many other cities. Supporters can argue that since electronic road pricing is now technically feasible, rationing road space by electronic road pricing could be an important means for keeping urban congestion to tolerable limits. But road pricing, with its emphasis on road space scarcity, can only indirectly reduce vehicular travel and emissions. It can induce motorists to shift to public transport, but its main effect is probably to redirect traffic to other times and other untolled routes or destinations. In summary, raising motoring costs can be an effective means of reducing car travel, but in OECD countries has adverse equity considerations. With less traffic on roads, average car speeds could (and probably would) be raised, resulting in a widening gulf between the high and low mobility sections of the population. Also, given that high-income households are more time-constrained than incomeconstrained, their car travel would rise, with an attendant rise in GHG emissions. In effect, the burden of reducing transport emissions would fall mainly on lowerincome households. As discussed in section “General Principles for Change,” they would become involuntary environmentalists. Major reductions in GHGs will not occur unless all sections of the population are engaged. Nevertheless, it is likely that fuel cost rises – perhaps large ones – are unavoidable. Following record high costs for crude oil in the first half of 2008, prices slumped to under $40/barrel, but soon recovered and since 2011 annual prices have once again averaged over US$ 100/barrel (OPEC 2014). The age of cheap oil is over – unless the global economy collapses to such an extent that oil demand is greatly lowered. Higher motoring costs thus seem inevitable, and unlike measures such as reduced speed limits, will not be seen as the fault of governments of oil-importing countries.

Reducing Travel: Lowering the Convenience of Car Travel Section “Reducing Travel: Changing Urban Land Use Patterns” has already discussed how high urban densities potentially allow trip distances to be shortened, although for low density cities, this potential is only very partially realized. But for very high densities of residents and workplaces, as in Japanese cities, another important effect occurs: because urban congestion is inevitably at high levels, the average speed of private car travel is much reduced, which tends to both lower car travel levels and raise the relative speed and economic viability of public transport, especially rail, with its own right-of-way. This is shown by Fig. 4, which plots for 1990, per capita car travel against the average car travel speed for the same sample of world cities as in Fig. 3, most of them (37) in OECD countries. The cities with low travel speeds and annual car travel are all in Asia. Although other factors are

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Fig. 4 Average per capita car travel versus average car speed for 46 world cities, 1990 (Source: Newman and Kenworthy 1999)

important, annual per capita car travel is clearly sensitive to average vehicle speed at least in cities. As Table 1 showed, car travel is the overwhelming choice for surface travel not only for Australia and the US but also for the more densely populated UK. This perceived advantage of car travel over other modes arises from several causes. First, car travel, especially driving, produces psychological benefits such as mastery of the vehicle and the thrill of acceleration (Moriarty and Honnery 2005). Second, car travel allows much greater flexibility of travel: door-to-door travel at any time of the day or night, and so freedom from public transport timetables (even assuming public transport is an option). It also affords protection from the weather, greater perceived personal security, privacy from strangers, and the ability to transport much luggage. This last advantage is important for shopping and explains much of the popularity of drive-in shopping centers. The third advantage concerns travel times. Because the extensive network of roads in most OECD cities is designed to provide vehicular access from origin to destination for almost every conceivable trip, distances by car are often shorter than by public transport (particularly fixed rail transport) for a given trip. Overall average trip travel times are also shorter by car because of higher average travel speeds; public transport has to make frequent stops to set down and pick up passengers. In general, car travel will always have an advantage over public transport modes on the first two factors discussed – it is inherent in the nature of private travel. But the third present advantage is not inherent in car travel: it results from the privileges granted to the car, such as speeding through residential areas, access to all areas of the city (usually including even the city center with its dense pedestrian traffic), and ability to park (even if a charge is made) at most locations (Moriarty and Honnery 2013).

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As has been shown, in major Japanese cities where this third advantage is largely lacking, travel speeds by car are very low. The result is low vehicular travel levels overall, with rail replacing the car as the major travel mode. In Japan, such an effect has arisen “naturally”; its cities were largely formed before car travel was significant (Table 1). But given the political will, the privileges that have been given the car can be removed. Many cities in the OECD have taken tentative steps in this direction, with traffic-free central business districts, and priority for alternative travel modes, and “traffic calming” measures in residential districts. But the city of Graz, Austria, with a population of 240,000 in the city proper, and 360,000 in the Greater Graz region, has gone furthest. In 1992, after a 2-year test period, the city imposed a 30/50 km/h speed limit on the entire road network. The 30 km/h limit was imposed on all side-roads and near centers such as schools and hospitals. These areas accounted for 80 % of the total city area. On all other roads, a 50 km/h limit was applied (European Local Transport Information Service 2008). The main purpose of the speed reductions was to improve road safety for all, but particularly pedestrians and cyclists, and to improve urban amenity. A modest reduction in the share of car travel has resulted and significant increase in cycling’s share (Commission for Integrated Transport 2009). The overall aim of policy would be to reverse the present transport priorities in OECD countries, so that non-motorized travel would be regarded as the default solution for urban trip-making, with public transport for back-up for necessary longer trips. Private vehicular travel would still be used in the transition to a low travel future, mainly in nonurban areas for longer trips difficult to service by public transport. The emphasis would be on “transport efficiency” (getting more access from each passenger-km) and less on mobility as an end in itself.

Future Directions In this final section, the various arguments made in this chapter will be drawn together, in order to assess what policies for travel reductions would work in future in the various countries. Policies that work in cities will not always be effective in nonurban areas. Nor will policies that are successful in highly motorized countries necessarily be relevant in presently low-mobility countries. Further, the scope for vehicular travel reductions may be much smaller in congested cities like Tokyo, compared with many major cities in the US or Australia, with their far lower population and job densities. First, an important concern when future mobility reduction policies are considered: Should the policies be voluntary, or mandated by governments? As discussed earlier, voluntary measures are easier to introduce and do not have the political costs to governments of more coercive measures. However, voluntary approaches to travel reduction have had little success. This conclusion should come as no surprise. After all, the decisive improvements in transport, from safety measures such as the installation of seat-belts and air bags, speed limits, and blood alcohol content limits, to technical environmental measures such as three-way catalytic converters, have all

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been mandatory. So, of course, have been adherence to the highway code, proficiency tests and age limits for drivers, the requirement that vehicles have functioning brakes and turn indicator lights, tires with adequate tread, and so forth. If measures are to be compulsory, what form should they take? They could involve very large changes to the monetary costs of motoring, as discussed in section “Reducing Travel: Raising the Overall Level of Motoring Costs.” There, it was stressed that in highly motorized OECD countries it would prove inequitable, as reductions in motoring would mainly come from lower-income groups. Garling and Schuitema (2007) have also stressed that perceived fairness is important for public acceptability of TDM measures in general. In section “Reducing Travel: Lowering the Convenience of Car Travel,” an alternative set of compulsory policies were explored. The main benefit of these approaches is that they target all travelers, because they change the relative travel speeds of the different modes. For many trips, EFMs would now become faster than car travel, particularly in areas closer to the city center. This loss of relative speed advantage for car travel could offset many of its inherent advantages, as already discussed. An example from outside transport, from the authors’ home city, Melbourne, illustrates these points well. Stream inflow volumes to Melbourne’s water reservoirs have fallen over the past decade, while Melbourne’s population has been growing rapidly (Melbourne Water 2014). Fortunately, when it became clear that reservoir levels were in sharp decline (together, they held less than 26 % of their design capacity in mid-2009), the problem was easily communicated to the public, and understood and accepted by all. So the state government was able to act fast and introduce policies to cut water use (although with recovery of reservoir levels since mid-2010, restrictions have been eased). Of course, they were many exhortations for residents to do the “right thing” and conserve water. But ultimately the success of the program rested on the outright banning of certain categories of water use, such as car washing, for all residents – not by using market measures. Because the measures applied to all, their acceptance was much greater. One crucial reason why this policy could be successfully introduced can be seen by contrasting public perceptions of water shortages with that for global climate change. Unlike the disarray in opinions (at least by the public and the media) over the latter topic, which have still not abated, there were no media-promoted “Melbourne reservoir water level skeptics” to tell us that there really was plenty of water in the reservoirs or that alternatives to water would soon be available. But what are the chances for success in introducing mandatory measures that could bring about very significant changes to travel behavior? World transport faces the twin problems of global climate change and depletion of conventional oil reserves. Climate change can be denied/avoided for a while longer – indeed, despite all the talk, international meetings, and the recently released IPCC report, this is the world’s implicit response – but such a response is not an option for global oil depletion. The global annual available supply of conventional oil has likely peaked, and nonconventional supplies will be costly in both monetary and environmental terms and slow to develop. Oil use per capita peaked in 1978, and again in per capita terms has been constant from the early 1980s to the mid 2000s, but is now in slow

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decline (BP 2014; UN 2014). If countries like China and India wish to increase their per capita use, it must fall in other countries if output is not raised. And given that most oil use is still in OECD countries, it is there that oil use must fall the most. Climate scientists use the term external “external forcing” to refer to the way increased greenhouse gas concentrations are driving the planetary climate from thermal equilibrium. Given not only the strong attachment motorists presently have to their cars, but the lack of readily available and convenient alternatives to private travel, especially in the nonurban areas, it is likely that the “car culture” found in OECD countries will, in a similar manner, only change in a major way under “external forcing” of transport systems. Oil supply security issues and price rises will likely provide the initial external forcing in the future. The Australian experience again provides a historical example of such external forcing. The only time when the fledgling car culture was seriously challenged was in 1929. Car ownership rose rapidly in the 1920s, but the Great Depression, followed by World War II and with it, gasoline rationing and the very low levels of car imports, stalled the rise of the car for two decades. Public transport patronage rose to record levels. Since then car travel has steadily increased its dominance of surface transport systems, both urban and nonurban. In recent years, however, driven by the crude oil price rises that began in the early 2000s (ABS 2013), Australia has seen not only sharp rises in public transport patronage but also a small reversal in market share (BITRE 2013). Similar gains have been recently reported for many other OECD countries, including the UK and Japan (DfT 2013; SBJ 2014). Such rises in public transport patronage provide a benefit that can go far beyond that gained by substituting a given amount of passenger car travel by alternative (EFM) modes. In earlier papers (Moriarty and Honnery 2007, 2008a, b, 2013), the authors have advanced the idea that the dominant transport mode determines not only the modal share but also the total level of per capita vehicular travel and even the patterns of trip making. Australian historical experience suggests that the levels of vehicular travel are much lower when public transport dominates travel, as it did until the late 1940s. Consider the case of Melbourne. In 1947, public transport accounted for 80 % of vehicular travel and car travel 20 %. Yet within only 15 years, these percentages were reversed. Further, per capita travel levels today, with the car the dominant mode, are about four times those of 1947. What this demonstrates is that, under the right conditions, major transport changes can happen very fast. Another important change was the shift in urban travel patterns. In 1947, vehicular travel in major Australian cities was strongly oriented toward the city center, since most workplaces, shopping expenditures and major centers for sports and entertainment were in the inner city area. Although many trips were local, such as visiting local shops and friends, most of these short trips were by nonmotorized means. Today, vehicular travel destinations are far more uniformly dispersed over the urban area (Moriarty and Honnery 2011). In each area of the city there is now a far better balance between workplaces and workers, shops and shoppers. Levels of personal travel could have been reduced, given this better balance. Instead, per capita levels rose several-fold in each of Australia’s major cities. Most of this rise was for

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discretionary trips such as shopping or social trips, rather than for nondiscretionary work or education trips. Overall, the suburbanization of many activities means that nonmotorized travel can now take over a large share of trips. In urban areas of OECD countries, localization of activities will be increasingly needed. Residents will need to work, shop, recreate, and socialize more and more at the local level. This localization will in turn require both local areas to be more attractive, and residents to develop a “sense of place” and a sense of belonging. Urban planners will have to start thinking creatively about how to design areas for humans, rather than focusing mainly on traffic flow, the current preoccupation; urban planning is not reducible to traffic planning. The changes will also need to be implemented very quickly, as time is important if countries are to greatly cut not only transport’s contribution to climate change but also oil consumption. As already mentioned, it is likely that impending oil shortages could act as a catalyst for necessary changes, forcing the public to realize that change is unavoidable and making their acceptance more likely. Transport GHG reductions through personal travel reduction are different from other resource-using sectors in that synergistic effects come into play to a far greater extent than is possible elsewhere. Individuals can readily reduce their use of domestic energy or water use, even if their neighbours don’t. Conversely, if the entire neighbourhood cuts its water use, it doesn’t much help an individual household in the neighborhood reduce its own water use (except through peer pressure). But if, as advocated here, local shopping centers are used more intensively, the range of goods and services offered for sale will improve, most likely at the expense of the presently popular, drive-in centers. If public transport patronage rises greatly, service frequency will also rise and probably also service coverage. The latter could initially occur using buses, but in the longer term could be replaced by fixed-rail transport, if patronage justified it. For transport, government intervention will be crucial for success in changing to a new transport “logic.” How crises such as global climate change or oil depletion get interpreted is important for policy responses. However, while many people recognize as severe the challenges posed by oil depletion and global climate change, there are many others who don’t see a problem, or if they do, think that one or more of a variety of tech fixes will solve these twin problems, without the need to resort to potentially unpopular measures such as mobility reductions. Policies promoting tech fixes are thus more likely to be tried first, and only when acknowledged to be inadequate, will the more fundamental changes advocated here be adopted. This finally gives rise to another important question: whether incremental changes (such as the ongoing research and development of “green cars”) will really help the move to an environmentally sustainable transport system. In section “Introduction: Travel Reductions for Climate Mitigation,” it was shown how far reaching are the changes needed for OECD passenger transport. An analogy can help here: to get a couple of meters closer to the Moon, leaning a ladder against the back shed will suffice, but it is a dead-end approach for much closer approaches to the Moon. For that, a rocket must be built. However, other incremental approaches provide a very good fit to deeper change, including efforts to to make urban destinations more

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accessible by active modes or to move people onto public transport. It is here that policy makers should focus their efforts in the interim period before more coercive policies must inevitably be introduced. Acknowledgments Patrick Moriarty acknowledges the financial support of the Australasian Center for the Governance and Management of Urban Transport (GAMUT) for the research which underpins this book chapter. GAMUT is in turn funded by the Volvo Research and Education Foundations. He would also like to thank the Maintenance Technology Institute in the Department of Mechanical and Aerospace Engineering and the Department of Design, both at Monash University, for providing him with accomodation during the writing of this book chapter.

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Nontechnical Aspects of Household Energy Reductions Patrick Moriarty and Damon Honnery

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Factors Affecting Domestic Energy Consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Strategies for Household Energy Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Social Psychology and Pro-environmental Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Role of Information Provision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Role of Monetary Approaches and Carbon Taxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Context for Domestic Energy Conservation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Domestic energy forms a significant part of total energy use in OECD countries, accounting for 22 % in the USA in 2011. Together with private travel, domestic energy reductions are one of the few ways that households can directly reduce their greenhouse gas emissions. Although domestic energy costs form a minor part of average household expenditure, the unit costs for domestic electricity and natural gas vary by a factor of 4 and 5, respectively, among OECD countries, and per capita use is strongly influenced by these costs. Other influences on domestic energy use are household income, household size, residence type (apartment/flat vs. detached house), and regional climate. Numerous campaigns have been carried out in various countries to reduce household energy use. A large literature P. Moriarty (*) Department of Design, Monash University, Melbourne, VIC, Australia e-mail: [email protected] D. Honnery Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, VIC, Australia e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_71

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has analyzed both the results of these studies and the general psychology of pro-environmental behavior, yet the findings often seem to conflict with the national statistical data. The authors argue that the rising frequency of extreme weather events (especially heat waves, storms, and floods), together with sea level rises, is likely to be a key factors in getting both the public and policy makers to treat global climate change as a matter of urgency. Costs of domestic energy are likely to rise in the future, possibly because of carbon taxes. But such taxes will need to be supplemented by other policies that not only encourage the use of more efficient energy-consuming appliances but also unambiguously support energy and emission reductions in all sectors. Abbreviations

ABS EIA EJ EPR EU GHG GJ GNI Gt IEA IPCC IT MWh NG OECD ONS PCT PEB RCP SBJ SCC UHI UN

Australian Bureau of Statistics Energy Information Administration (US) Exajoule (1018 J) Energy performance rating European Union Greenhouse gas Gigajoule (109 J) Gross national income Gigatonne (109 tonne) International Energy Agency Intergovernmental Panel on Climate Change Information technology Megawatt-hour (106 W-hour) Natural gas Organisation for Economic Co-operation and Development Office for National Statistics (UK) Personal carbon trading Pro-environmental behavior Representative Concentration Pathway Statistics Bureau Japan Social cost of carbon Urban heat island United Nations

Introduction In 2011, world CO2 emissions from energy and industry totalled 33.74 gigatonnes (Gt) (BP 2014). (A gigatonne = 1018 tonnes.) For the USA alone in 2011, total emissions were 5.5 Gt of CO2, resulting from total energy use of 102.5 EJ (EJ = exajoule = 1018 J).

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Of this total US energy, household energy use accounted for 22.6 EJ or 22.0 %, compared with 18.6 %, 31.4 %, and 28.0 % for the commercial, industry, and transportation sectors, respectively. The US Energy Information Administration (EIA) projects that domestic energy use in the USA will grow only slowly over the period 2012–2040, at an average of only 0.2 % per year (EIA 2014). Along with private transport, cutting energy use at the household level is an important way for individuals to directly reduce their carbon footprint. (In this chapter, the terms “household energy use” and “domestic energy use” are used interchangeably.) Two possible approaches for reducing domestic energy consumption are, first, to encourage the purchase and use of domestic energy-using devices (see also chapter “▶ Energy Efficiency: Comparison of Different Systems and Technologies” in this handbook) and, second, by reducing the use of such devices. This could involve having fewer appliances (e.g., dispensing with second refrigerators in the household), running energy devices for fewer hours (e.g., turning off lights), or running at a lower setting (e.g., lowering thermostat settings in winter). This second approach to energy reductions is more important for household energy use than for either commercial buildings or industry, because for both of these sectors, energy costs are likely to be monitored more closely and policies for energy reduction, both technical and nontechnical, more readily implemented for purely economic reasons. Nevertheless, considerable scope still remains for both industry and commercial buildings to adopt these practices. There is a further reason for a focus on domestic energy use. In many Organisation for Economic Co-operation and Development (OECD) countries in recent years, total primary energy use per capita, or even total primary energy use, has fallen (BP 2014). In the UK, for instance, total energy use has not risen for four decades, and total CO2 emissions from fossil fuels peaked in 1970 and are now 26.5 % lower than the peak value. The problem is that recent decades have also seen the rise in imports to the OECD of energy- and CO2-intensive manufactured products from Asia. As Davis and Caldeira (2010) show, such embodied CO2 and energy can make a big difference to national emissions and energy statistics and render problematic the interpretation of energy time series data. Because domestic energy statistics only measure energy used by household equipment and not the embodied energy in the equipment, this problem is avoided. This chapter is structured as follows. Section “Factors Affecting Domestic Energy Consumption” looks at patterns of domestic energy use in various selected OECD countries. Domestic energy prices, household income, household size, and climate were all found to be important for present domestic energy use. (In this chapter, the terms energy reductions and CO2 reductions are used interchangeably, since, at the household level, energy reductions are – apart from rooftop solar devices and switching to gas from electricity for space and water heating – the only means available to reduce CO2 emissions.) In section “Strategies for Household Energy Reductions,” the numerous studies and field trials on reducing household energy use are reviewed. Researchers have looked at the effect of parameters such as income level, gender, age, and ethnicity on responsiveness to campaigns for energy reductions. The latest studies have concluded that significant energy reductions are

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possible, but stressed that households face many barriers to reductions, including lack of relevant information. Building on the energy cost data in the previous section, the authors stress the importance of future carbon taxes for motivating energy reductions. In section “Future Directions,” the possibility for conflicts between household energy savings and overall global climate change mitigation (or adaptation) is examined.

Factors Affecting Domestic Energy Consumption Table 1 shows domestic energy consumption by end use for the USA for year 2011. Over half the energy use is for space heating and cooling (with the UK having a similar proportion (Steg 2008)), with almost one-fifth for water heating and refrigeration/freezers. Since 1993, the share for space heating has fallen, and the shares for both space cooling and appliances have risen (EIA 2013). Energy for space heating in the USA overall is expected to fall out to the year 2040, for space cooling to continue to increase (EIA 2014). Although space heating presently uses almost six times as much energy as space cooling in the USA overall, this ratio varies with regional climate. Households in colder climates spend a higher share of their total expenditure on fuel because of high winter fuel bills, which more than compensates for lower need for space cooling in the warmer months. In Australia, for example, in subtropical Brisbane (27
300 S), the figure is 2.1 %, compared with 3.5 % for temperate Hobart (43
S) (Australian Bureau of Statistics (ABS) 2012). In OECD countries, nearly all of this domestic energy is supplied by reticulated electricity and natural gas. Table 2 shows the unit prices of these two domestic energy sources for 2012 for a number of OECD countries, including both the major economies and those with either very high or very low energy costs. The unit costs for domestic electricity and natural gas vary by a factor of 4 and 5, respectively, among OECD countries, with Mexico, one of the lowest-income OECD countries, Table 1 Domestic energy use by function for the USA, 2011

Delivered energy consumption by end use Space heating Space cooling Water heating Refrigeration and freezers Cooking Clothes washers and dryers Lighting Dishwashers Televisions and related equipment Computers and related equipment Other uses Delivered energy Source: EIA (2014)

Share (%) 43.03 7.54 15.70 4.07 3.06 2.48 5.67 0.88 2.97 1.14 13.47 100.00

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having the lowest unit costs. The different costs have a large impact on domestic energy use. Comparing the USA and Japan, the much higher costs for domestic energy in Japan (2.3 times that of US electricity costs; see Table 2) coincide with a 3.5-fold reduction in domestic energy per capita (EIA 2014; Statistics Bureau Japan (SBJ) 2014). Only a small part of this difference can be explained by the 9.3 % higher gross national income (GNI)/capita reported for the USA (Table 2). Further, the slightly larger average household size in the USA compared with Japan (about 2.5 and 2.4 occupants, respectively) should, if anything, lower per capita domestic energy use. Similarly, the high-income, high-energy cost European countries (Denmark, Germany, and Sweden in Table 2) have much lower per capita domestic energy use than the USA. Further, the increase in domestic energy prices in the UK was seen as a partial explanation for the decrease in domestic energy use between 2005 and 2011 in England and Wales (Office for National Statistics (ONS) 2013). The burden of domestic energy costs depends not only on unit prices but also on income level. As expected, the share of household expenditure spent on domestic energy declines for the higher-income quintiles (Table 3). However, higher-income Table 2 Unit cost of domestic electricity and gas and per capita GNI for various OECD countries in 2012 Country Denmark Germany Japan Mexico Netherlands Sweden UK USA

Gas $/MWha 123.09 90.32 NA 30.36 98.7 156.89 73.65 35.22

Electricity $/MWh 383.43 338.75 276.76 90.20 238.24 223.96 220.74 118.83

GNI/capitab 59,870 45,170 47,870 9,640 48,110 56,120 38,500 52,340

Sources: International Energy Agency (IEA) (2013b), World Bank (2014) Gross heating value b Atlas method (US$ 2012) a

Table 3 Domestic energy expenditure vs. household income quintile, Australia and Japan Country Australiaa Australiab Japanc,d Japane

Lowest 4.0 % 1,147 7.0 % 162.6

Second 3.4 % 1,460 6.3 % 178.7

Third 2.7 % 1,616 5.8 % 187.8

Sources: ABS (2012), SBJ (2014) 2009–2010 survey data b $Aust (2009–2010) per year c 2012 survey data d Only households with two or more persons are included e In 1000 yen (2012) per year a

Fourth 2.5 % 1,929 5.2 % 197.8

Highest 2.0 % 2,294 4.5 % 224.7

Average 2.6 % 1,721 5.5 % 190.5

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households also have more persons per household (ABS 2012; ONS 2013; EIA 2014; SBJ 2014), so it may be that the greater energy efficiency possible with larger households explains some or all of the decrease. The UK statistics also measure domestic energy costs for quintiles ranked on an “equivalised disposable income,” which adjusts for the number of persons per household (with, e.g., two adults counting as one unit, but two adults plus two children counting for 1.4 units) (ONS 2014). This 2012 UK data shows that, after such adjustment for size, the poorest fifth of households spent 10.9 % of their disposable income on domestic fuel, compared with only 2.8 % for the wealthiest quintile – nearly a fourfold difference. For both quintiles, the share of disposable household income spent on domestic fuel had risen since 2002 (from 8.0 % for lowest and from 1.7 % for highest), even though average domestic energy use in the UK had fallen by 17 % over the decade. Nevertheless, in absolute terms, the highest-income quintile spent more on domestic energy (and produced more CO2 emissions) than the lowest-income quintile, and the same was true for gross expenditure on domestic energy in Japan and Australia (see Table 3). Energy use in households also varies with housing type. A 2008 UK study (Druckman and Jackson 2008) found that those living mainly in flats (“city living”) had a much lower share of weekly expenditure on energy than “countryside” residents, mainly living in detached houses. An earlier study in Australia (Moriarty 2002) found that inner-city residents of Melbourne and Sydney, with a high share of residents living in flats, spent a lower share of disposable income on household fuel than outer suburban residents or nonurban residents, both groups mainly living in detached houses. Along the same lines, a Canadian study (Larivière and Lafrance 1999) measured the residential electricity consumption of Québec’s 45 most populous cities and towns and found that the per capita energy rose as the share of single dwellings increased. This result would be expected if electric power was an important form of heating in a cold climate. The size of the residence (in square meters (m2)) is also an important factor, particularly for domestic heating and cooling. It helps explain some of the large difference between US and Japanese energy use. In the USA in 2011, average residence size was 154.5 m2, compared with only 94.1 m2 for Japan overall and as low as 63.9 m2 for Tokyo prefecture (2008 values, the latest available) (EIA 2014; SBJ 2014). The high population density of Japan and the resulting high land prices explain much of this difference. Other important differences are in both ownership and average size of appliances. For example, in Japan in 2009, only 27 % of households of two persons or more owned dishwashers; in the USA in 2009, the corresponding figure was 64 %. Also, both the number of refrigerators per 1,000 households and their average capacity were larger in the USA (EIA 2013; SBJ 2014). The behavior of the occupants has also been found to be crucial. A British study (Pilkington et al. 2011) examined space heating demands in “a terrace of six similar, passive solar dwellings with sunspaces.” Space heating demand per occupant was found to vary by a factor of 14. This finding clearly indicates both that behavioral factors are important for domestic energy use and also that considerable potential

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exists for energy reductions. Further evidence comes from a study of 3,400 German homes: Sunikka-Blank and Galvin (2012) again found that dwellings with the same energy performance rating (EPR) varied widely in space heating energy use. (The EPR, measured in kWh/m2 per year, assesses the overall energy efficiency of a building, either using actual or modeled energy use data (Corrado and Mechri 2009).) But they also found that (energy inefficient) dwellings with high EPR ratings consumed much less energy than calculated, while the reverse was true for low EPR (energy efficient) dwellings. Similar results appeared to hold for several other EU countries. They concluded that the potential energy savings from changes to occupant behavior may be far greater than assumed. Section “Strategies for Household Energy Reductions” looks further at this potential.

Strategies for Household Energy Reductions Domestic energy reductions rely on far fewer policy options than are available for reducing household private travel energy. In addition to legislation on vehicular fuel efficiency (see also chapter “▶ Reducing Personal Mobility for Climate Change Mitigation”), authorities can also influence the levels of private travel (in vehiclekm) by measures such as street closures in the inner city, speed limit reductions, priority for public transport and nonmotorized modes, limits on availability of parking spaces, road pricing as in London and Singapore, reduced arterial road construction in urban areas, provision of improved public transport, as well as increased charges for parking and taxes on transport fuels. Authorities can implement these measures because most of the road systems, and often the public transport systems, are publicly owned. A further limit on the capacity of regulations to drive change is the much longer lifetimes of housing stock relative to road vehicles. Apart from increasing fuel costs, these policy levers are not available for reducing domestic energy use. As with road vehicle efficiency, governments can legislate the use of energy-efficient light globes and establish energy ratings for domestic appliances and minimum insulation standards for new buildings. But too much intervention in the domestic sphere would meet strong popular resistance. Because of this, authorities must rely far more on voluntary behavior change (and domestic energy cost increases) for reducing domestic energy use than in other areas of energy use. Nevertheless, domestic energy conservation has at least one important advantage over travel energy conservation. It is very difficult for individual households to reduce car travel if other households do not, particularly for countries like the USA, where car travel accounts for over 90 % of all surface vehicular travel. Even if car travel is reduced as a result of a campaign, households will usually soon relapse back to former practices, since car travel is usually faster than other modes. On the other hand, individual households can make domestic energy reductions even if others do not. This section first reviews the extensive social psychology literature (see section “Social Psychology and Pro-environmental Behavior”) on pro-environmental behavior (PEB), particularly the importance of information provision (see section

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“The Role of Information Provision”) before examining the role of carbon taxes (see section “The Role of Monetary Approaches and Carbon Taxes”) and, finally, the context for energy conservation (see section “The Context for Domestic Energy Conservation”).

Social Psychology and Pro-environmental Behavior A vast literature is now available on the application of social psychology to energy conservation, and pro-environmental behavior in general, together with policy recommendations. According to Dietz (2014), “modest policies” aimed at raising the efficiency of US household energy consumption (presently 22 % of total energy) could reduce overall CO2 emissions in the USA by 7 %. Surveys in OECD countries have consistently found that the public regard protecting the environment and saving energy as important (Steg 2008; Booth 2009). Obviously, it is not how people respond to surveys about PEB (i.e., their stated attitudes toward the environment and energy conservation) that is important but whether or not households do in fact reduce their energy use and whether any such reductions continue in the long term. For as Dietz (2014) has also stressed, few studies with a social psychology approach are able to study actual environmental behavior, as distinct from stated intentions. A 2010 survey of energy use in Hungarian households has shown how stated intentions and actual behavior can differ. The survey of over 1,000 people found that those who “consciously act in a pro-environmental way” did not necessarily use less residential energy than respondents who did not exhibit PEB (Tabi 2013). Much of the social psychology literature on PEB has concentrated on individual attributes. Jagers et al. (2014) found that 21 % of the respondents in a Swedish survey met the requirements for “ecological citizenship.” Their conclusions found support for a strong relationship between ecological citizenship and PEB: “Our results suggest that individuals who think along the lines of ecological citizenship are more likely than others to behave in an environmentally friendly way in their daily lives.” Yet PEB was measured by response to items such as “try to save household electricity” rather than comparing actual household electricity use with other householders; hence, pro-environmental attitudes rather than actual pro-environmental behavior were being measured. Gifford and Nilsson (2014) have recently reviewed the various “personal and social factors that influence pro-environmental concern and behavior.” We discuss here some of their findings relevant to methods for reducing household energy use. In general, survey respondents with more knowledge about environmental problems indicated greater overall environmental concern. (The role of information is discussed in more detail in section “The Role of Information Provision.) Interestingly, older people generally reported higher pro-environmental behavior than younger people and women more than men. Not only did the authors report that environmentalists “tend to be middle- or upper-middle-class individuals” but, at the national level, “environmental concern has a clear positive relation with gross domestic product (GDP) per capita.”

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Yet, as we have seen in section “Factors Affecting Domestic Energy Consumption,” the higher-income quintiles in OECD countries have higher domestic energy use per household, and, globally, the OECD and other high-income countries have much higher primary energy use and CO2 emissions per capita than low-income countries (IEA 2013b). Residents of low-income households and countries could thus be regarded as “involuntary environmentalists” (see Moriarty and Honnery 2012): their low incomes constrain their energy use and carbon emissions. Further, survey results are usually only given as percentage reductions, ignoring the fact that low-income households already use much less energy than the average. But in the USA, a recent study (Bohr 2014) found that income effects on belief about the reality of climate change were mediated by political beliefs. Briefly, lower-income Republicans regarded climate change as a more serious issue than higher-income Republicans, but the reverse was found true for Democrats. Clearly, one needs to be careful in evaluating the transfer of social psychology findings to the national energy policy domain. A related point is the choice of incentives for promoting PEB. One fairly consistent result in the published literature is the apparent superiority of nonmonetary over monetary rewards. Steg (2008) has argued that domestic energy conservation is best served by appealing to normative and environmental values, because they provide a more enduring basis for change than ones which maximize personal interests, such as cost savings. If, for example, cost reductions disappear, then so will the conservation behavior, if formed on that basis. Overall, this view can be summed up by arguing that “green” reasons for change are superior to “mean” reasons (de Groot and Steg 2009). Dietz (2014) simply stated that “self-interest is only one of several values that underpin environmental decision making.” Turaga et al. (2010) reached similar conclusions and stated that the empirical evidence suggested that PEB was more likely for people whose “core values” could be described as “social altruistic” and/or “biospheric”. Of course, this still leaves the problem of how to promote PEB in householders whose behavior is more in line with homo economicus. These researchers also warned that government policies might crowd out motivations for altruistic behavior. They thus stress the need to create “carefully structured institutions.” The question of monetary incentives in the real world is, however, not so simple and is discussed in greater detail in section “The Role of Monetary Approaches and Carbon Taxes”. Steg (2008), looking specifically at domestic energy conservation, reported three barriers to conservation. The first barrier was that many households do not have sufficient knowledge of means to effectively reduce their energy consumption, as discussed in section “The Role of Information Provision.” The second was the low-priority households attach to reducing energy use. As discussed in section “Factors Affecting Domestic Energy Consumption,” domestic energy is typically only of the order of 5 % of household expenditure, although a higher proportion for low-income households. The third barrier was the high costs for some energy-saving strategies, particularly if it involved the purchase of more energy-efficient appliances. She reported that two general strategies can be used to reduce household energy use. First, use psychological insights to change householders’ “knowledge,

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perceptions, motivation, cognitions, and norms related to energy use and conservation.” Second, alter the context in which energy use decisions are made; this important topic is treated in detail in section “The Context for Domestic Energy Conservation.” “Social marketing” has become popular as a means of changing people’s attitudes and behavior on environmental issues. As defined by Corner and Randall (2011), social marketing “is the systematic application of marketing concepts and techniques to achieve specific behavioural goals relevant to the social good.” Their study is a critique of the application of social marketing techniques in the UK to engage the public more fully on climate change. The study showed that the approach may in some circumstances be effective, particularly for encouraging PEB that needs only minor lifestyle changes, such as recycling household waste. However, given the scope of overall CO2 reductions needed by the UK and other high-emitting countries, social marketing for carbon reductions appeared to be less effective, and some of the approaches tried were even counterproductive. One particular problem was that attempting to tailor messages to individual groups may lead to compromises that negatively impact PEB in the longer term and in other domains. In other words, it is risky to consider the various environmental problems (and even non-environmental problems) in isolation. A complication of this type arises from what social psychologists term “moral licensing.” According to Merritt et al. (2011), moral licensing “occurs when past moral behavior makes people more likely to do potentially immoral things without worrying about feeling or appearing immoral.” Tiefenbeck et al. (2013) carried out a field experiment in 154 households of a 200-apartment complex in Greater Boston in the USA. The study examined the effect of a household water conservation program on electricity consumption. “The results show that residents who received weekly feedback on their water consumption lowered their water use (6.0 % on average), but at the same time increased their electricity consumption by 5.6 % compared with control subjects.” They concluded that such moral licensing “can more than offset the benefits of focused energy efficiency campaigns, at least in the short-term.” In some ways, this effect is similar to the well-known concept of “energy rebound,” where improving energy efficiency makes the operation of energy-using devices cheaper, thus leading either to some increased use of such devices or using the money saved for other (energy-using) goods and services.

The Role of Information Provision It seems intuitive that households need accurate information on both energy costs and energy use of specific household equipment. Studies have shown that there is indeed an information gap. Attari et al. (2010) conducted a nationwide US survey on estimated energy savings from such actions as turning off lights or replacing existing lights by more efficient ones. They concluded that “For a sample of 15 activities, participants underestimated energy use and savings by a factor of 2.8 on average, with small overestimates for low-energy activities and large underestimates for high-

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energy activities.” Householders may simply think that the unit energy consumption of an appliance is simply related to its size (Steg 2008). Correcting this bias would seem essential for domestic energy decision-making. At least one government agency (the Office for National Statistics in the UK) saw better information as partly responsible for the observed declines in UK household energy use in recent years. The list of possible explanatory factors for household natural gas and electricity reductions included technical efficiency measures such as better cavity wall insulation and “improved efficiency of gas boilers and condensing boilers to supply properties with both hot water and central heating,” as well as continuous rises in the price of domestic gas and electricity after the mid-2000s (ONS 2013). But they also saw the provision of better information to households as important, specifically the “introduction of energy rating scales for properties and household appliances, allowing consumers to make informed decisions about their purchases” and “generally increasing public awareness of energy consumption and environmental issues.” But as the following discussion documents, simply providing more information can have unexpected effects on energy use. The rise of the new information technology (IT) has greatly enlarged the scope for providing data on domestic energy use to households. There is now a growing literature on intelligent or smart cities and smart houses. Cook (2012) has described possible future houses equipped with a vast number of sensors (“ambient intelligence”) to automatically adjust temperature and lighting levels, for example. A barrier to the realization of such smart houses is the privacy issue. But even if the privacy issue could be overcome, there are doubts about the extent of energy savings possible with such information provision alone. An Irish study (McCoy and Lyons 2014) reported the results of a controlled trial of 2,500 electricity consumers. Householders were supplied with smart meters which gave them detailed information on usage. They found that electricity use fell as expected, but compared to the control group, these householders invested less on energy-saving equipment. The authors speculated that householders might realize that conservation measures can be an alternative to energy efficiency investments. In other words, energy conservation and energy efficiency measures may not always be complementary measures, as is often assumed. Delmas et al. (2013) performed a meta-analysis on 156 published “informationbased energy conservation experiments” conducted over the period 1975–2012. The studies focused on household electricity savings. The type of information provided in the various experiments included items such as tips on how to save energy and the provision of detailed data on own energy use or that of peers. From these experiments, they found average measured savings in electricity use of 7.4 %. However, the savings found depended greatly on the type of information provided. The authors concluded that “strategies providing individualized audits and consulting are comparatively more effective for conservation behavior than strategies that provide historical, peer comparison energy feedback.” They also reported potential problems with information campaigns, in that feedback on costs and monetary incentives led to relative increases in household electricity use.

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Another recent study from the USA (Gromet et al. 2013) provided further evidence that simply giving more information will not necessarily encourage PEB in householders. In one study, they compared responses of self-identified political liberals with self-identified political conservatives. They showed that conservatives were less likely to buy more expensive but also more energy-efficient light bulbs if they were labeled as being good for the environment than if they were not so labeled. Responses were reversed for liberals. The researchers believed that “the political polarization surrounding environmental issues” in the USA was the explanation for their unexpected findings. This finding may not therefore be applicable to other OECD countries: in the EU, several conservative governments support deep cuts to CO2 emissions.

The Role of Monetary Approaches and Carbon Taxes One government policy often mentioned as both an important and necessary part of any carbon reduction strategy in all sectors of the economy is carbon taxes (Van Vuuren et al. 2011a). The European Union (EU) already has an emissions trading scheme (ETS), although the prices in 2013 were at historically low levels. Given that every tonne of CO2 emitted, regardless of location, has the same climate effect, a global carbon market would be preferable. At present, though, apart from the multinational regional EU market, existing carbon markets are either national or even subnational (Newell et al. 2014). But reliance on market-based incentives can be criticized because it can (and has) led to abuses, particularly the “reducing emissions from deforestation and forest degradation” (REDD) scheme of the UN Framework Convention on Climate Change (Moriarty and Honnery 2011). Nevertheless, such carbon taxes are sometimes regarded as providing motivation for domestic energy use reductions. Certainly, the cross-country evidence presented in section “Factors Affecting Domestic Energy Consumption” on domestic energy costs suggests that monetary considerations are important for energy use. The IPCC estimated that after 2050, carbon taxes required to meet Representative Concentration Pathway 2.6 (RCP2.6) target would need to be as high as $250 per tonne CO2 (Van Vuuren et al. 2011b). Here, we provide a rough estimate of the effect such a tax would have on lower end OECD domestic electricity prices. In recent years, electricity generation in OECD countries overall has led to emissions of 0.434 tonne CO2/MWh (IEA 2013a). At $250 per tonne CO2, this works out as $108.5/ MWh. From Table 2, this value would roughly double domestic electricity prices in Mexico and the USA. An important question is whether such carbon taxes would be regressive. Dissou and Siddiqu (2014) have argued that they need not be, if seen in the context of a comprehensive analysis. They argued that “Most studies have assessed the distributional impact of carbon taxes through their effects on commodity prices alone, while ignoring their impact on individual welfare brought about by changes in factor prices.” They found a U-shaped curve for income inequality (as measured by the Gini coefficient) when plotted against the level of carbon tax. Although maximum

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income equity was found at a tax of about $50, a zero tax had about the same equity effect as one of over $100 per tonne CO2. Nevertheless, a tax rate of $250 per tonne CO2 would substantially increase inequality. However, a carbon tax is not the only way of reducing emissions by monetary means. Starkey (2012) examined the equity effects of “personal carbon trading” (PCT). In this UK proposal, every adult would receive for free an equal carbon quota, with the sum of these quotas amounting to perhaps 40 % of total allowable national emissions. The author compared this proposal with other emission reduction schemes, including a carbon tax, and showed that these other schemes can be designed to be as equitable as any PCT one. Another possible approach is to alter the structure of domestic energy costs, with lower fixed costs on energy bills and higher unit costs for energy use. This change could be revenue neutral overall, but, again, its equity implications would need to be evaluated for each country. Future price rises for fossil fuels are likely inevitable; policies will have to be designed to ensure that lower-income households, who already pay a higher share of household income for domestic energy, are not be further disadvantaged. The level of carbon tax necessary will depend on the costs of either replacing fossil fuels by nonfossil alternatives (renewable and nuclear energy) or the costs of various carbon sequestration methods. The latter include biological sequestration in plants (especially forests) and in soils and also mechanical sequestration techniques such as capturing CO2 from the flue stacks of fossil fuel electricity plants, followed by compression, transport, and geological burial (Van Vuuren et al. 2011b; Moriarty and Honnery 2011). For details, see also chapter “▶ Reducing Greenhouse Gas Emissions with CO2 Capture and Geological Storage” in this handbook. A recent study (Marshall 2013) found an extremely broad range of both the unit costs of various carbon sequestration methods – from $10 to $2,000/tonne CO2 sequestered – and global potential (in Gt CO2). Of course, imposing such high carbon taxes would be unwarranted if it could be shown that the costs of climate adaptation (again, measured in $ per tonne of CO2 or equivalent) were much smaller. Some economists have argued that the global economic costs of a 2
C temperature rise will be small, and an official US estimate was that the “social cost of carbon” (SCC) was $37 per tonne of CO2 emitted. However, these and similar results derived from economic models have been heavily criticized (Revesz et al. 2014). In any case, integrated climate models show that climate costs will rise in a nonlinear fashion as temperature rises beyond the nominal 2
C “safe limit.” Ackerman and Stanton (2012) have thus argued that the SCC could easily be an order of magnitude higher or, given certain assumptions, even infinite.

The Context for Domestic Energy Conservation What will induce households, as well as policy makers, to take climate mitigation seriously? At present, despite the high profile of the climate change problem over the past two to three decades in both the press and scholarly publications, there has been

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no real progress in mitigation: in 2013, emissions from fossil fuels were 2.1 % higher than in 2012 (BP 2014). Possible reasons for such climate inaction could include pressure from fossil fuel-based industries and energy-exporting countries, skepticism about the reality of global warming, and belief in the efficacy of future technical fixes such as aerosol geoengineering to painlessly solve the problem (see also chapter “▶ Geoengineering for Climate Stabilization” in this handbook). Interestingly, the Asian OECD countries (Japan and South Korea) both report very high levels of belief in the reality of global warming (Wikipedia 2014) and have insignificant fossil fuel reserves (BP 2014). The Intergovernmental Panel on Climate Change (IPCC) (Stocker et al. 2013), in its latest report (Fifth Assessment Report (AR5)), warned that the world will increasingly face greater extremes in climate, particularly in the form of heat waves and high-intensity precipitation. Over the past century, global mean temperature has risen less than 1.0
C, yet in temperate climates, daily variation can be 20
C or more. Such variation makes it difficult for laypersons to feel the urgency that climate scientists feel. But already, recent heat waves in Europe and elsewhere have led to tens of thousands of excess deaths (Moriarty and Honnery 2014). Climate scientists speak of climate forcing (or radiative forcing, in watts per square meter) from GHGs. Analogously, it can be expected that the spread of extreme weather events, both in intensity and frequency, will provide the forcing for both the public and their policy makers in all countries to take decisive action on climate mitigation, although intense arguments will continue regarding the sharing of emission reductions between countries. On the other hand, there is a disconnection between national costs for climate mitigation and benefits accruing to the same nation (Moriarty and Honnery 2014). Climate mitigation is an example of a global public good; these tend to be undersupplied by market economies. In contrast, most of the health benefits from reducing local air pollution in a city will accrue to that city. The problem would have been less serious when the OECD countries both had the highest per capita emissions of CO2 and accounted for most of the global emissions. In 1965, the OECD produced 68.3 % of fossil fuel CO2; in 2012, even a much enlarged OECD accounted for only 40.3 % (BP 2014). The urgent need for countries like China and India, still with relatively low emissions per capita, but large total emissions, to reduce their emission levels, will complicate popular acceptance of deep emission reductions in the OECD. Another factor that must impact ordinary citizens’ perception of both the need for reducing fossil fuel use and acceptance of high domestic fossil fuel energy prices is national fossil fuel reserve estimates. One set of reserve estimates, those of BP (2014), is shown in Table 4. Countries like Denmark, Japan, South Korea, and Sweden have negligible amounts of fossil fuels. German reserves are almost all low-quality lignite, which produces high CO2 emissions per unit of delivered energy – an embarrassment for a country striving for “green” credibility. Even the UK, once the world leader in coal production, and, until recently, an important natural gas (NG) and oil producer, finds itself today with only a few years’ reserves of all three fuels at their current production rates.

Nontechnical Aspects of Household Energy Reductions Table 4 Fossil fuel reserve estimates at the end of 2012 for various OECD countries, in EJ

Country Australia Canada Denmark Germany Japan Mexico South Korea Sweden UK USA World

Oil 22.3 993.2 4.0 1.5 0.3 65.1 0.0 0.0 17.7 199.9 9531.3

1121 NG 143.2 75.4 1.5 2.3 0.0 15.1 0.2 0.0 7.5 320.3 7058.0

Coal 1584.0 141.0 2.6a 569.4 9.7 28.9 1.8 0.0 6.4 4825.9 17665.0

All fossil fuels 1749.4 1209.5 8.1 573.2 10.0 109.1 2.0 0.0 31.7 5346.0 34254.3

Source: BP 2014 In Greenland

a

Most fossil fuels used in these countries are thus imported, and so these importing countries are increasingly dependent on the continued goodwill of both oil- and NG-exporting countries. Restrictions on both oil and gas exports have been used for political purposes. In the USA, in contrast, the public is being led to believe that shale gas (and even shale oil) will lead once again to oil and gas independence for the USA. The context in which appeals to the public to conserve energy are made in OECD Europe or Asia, compared with fossil fuel-rich North America or Australia, is thus very different.

Future Directions One important consideration for both future climate change mitigation and adaptation is to ensure that actions taken at the local level (such as an urban area) do not conflict with actions needed at the global level. Similarly, local actions for climate mitigation or adaptation must not conflict with policies needed for ecological sustainability in general. One proposal for climate change mitigation is to paint urban building roofs (and even roads) with reflecting paint, in order to increase their albedo – the share of insolation that is reflected directly back into space (Royal Society 2009). Unlike most other geoengineering proposals, such roof whitening should meet with little international opposition, since the actions involved are clearly on national territory. It would also represent a means for households to directly mitigate climate change without reducing domestic energy use. And unlike most climate mitigation measures, most of the temperature reduction benefits would accrue to the urban area concerned (see also chapter “▶ Geoengineering for Climate Stabilization” in this handbook). However, a recent study (Jacobsen and ten Hoeve 2012) modeled both local and global climate effects. The study found that although local temperature reductions

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would indeed occur, the global effect would be a modest temperature increase. Even if different climate models were to give different results, the study illustrates the importance of such potential conflicts. A further problem is that “cool roofs” will reduce winter as well as summer temperatures, both inside and outside buildings. In temperate climates, domestic heating energy needs will therefore rise. Another study of reflective pavements (Yang et al. 2013) also found a similar unintended consequence: “reflected radiation from high-albedo pavements can increase the temperature of nearby walls and buildings, increasing the cooling load of the surrounding built environment and increasing the heat discomfort of pedestrians.” In section “Factors Affecting Domestic Energy Consumption,” it was found that residents of apartment blocks, and higher urban density living in general, reduced household energy consumption. Increasing the residential density of cities might therefore appear as a way to lower energy use and carbon emissions. Further, increased urban density has also been promoted as a means of reducing urban car travel and their associated emissions (Moriarty and Honnery 2013). However, several possible conflicts arise. First, higher-density living might interfere with the ability to use passive solar energy for temperature control and natural lighting (Steemers 2003). Second, it might reduce the potential for individual households to use PV (photovoltaic) roof panels or solar hot water systems or, in low rainfall regions, tanks for rainwater storage. One also needs to consider the effect of urban density on the urban heat island (UHI) effect. Of course, reduction in household energy use will reduce urban waste heat, which is one component of the UHI effect. But according to Kleerekoper et al. (2012), a more important cause is the “urban canyon” effect, which prevents escape of radiant heat, and impervious surfaces, which prevent evaporative cooling. Both are likely to be more important in densely built-up urban areas. This chapter has shown that deep reductions in household energy and thus CO2 emissions will require a variety of compatible policies. The national statistical data presented in sections “Factors Affecting Domestic Energy Consumption” and “Strategies for Household Energy Reductions” showed that household domestic energy use is lowest in countries with low fossil fuel reserves; these countries also usually have higher prices for domestic energy use. Public support for decisive action on climate change varies from country to country and even in one country from month to month. However, the rise in frequency of extreme weather events – heat waves, storms, and floods – together with rising sea levels, is likely to increase support for action in all countries. The review of domestic energy conservation campaigns discussed in section “Social Psychology and Pro-environmental Behavior” found only limited permanent measured energy reductions. But it could be that this disappointing result occurs because respondents presently do not really feel that energy security and fossil fuel depletion and climate change are serious problems that will necessarily involve major lifestyle changes. In future, it is likely that, for both fossil fuel depletion and climate change reasons, the context in which domestic energy decisions are made will change. Past research on domestic energy conservation may then be of little relevance. But new research will also have to take a more comprehensive view of

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energy savings than in the past, to ensure that neither conflicts between energy efficiency and energy conservation do not occur nor conflicts between energy savings in different sectors.

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Bringing Global Climate Change Education to Middle School Classrooms: An Example from Alabama Ming-Kuo Lee, Chandana Mitra, Amy Thomas, Tyaunnaka Lucy, Elizabeth Hickman, Jennifer Cox, and Chris Rodger

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Program Development and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alabama Science in Motion Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Educational Modules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Earth and Space Science Module: Effects of Volcanic Activities on Atmosphere and Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hydrology and Environmental Science Module: Groundwater Resource and Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Physical Sciences Module: Urban Heating Island Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Program Dissemination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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M.-K. Lee (*) • C. Mitra Department of Geology and Geography, Auburn University, Auburn, AL, USA e-mail: [email protected]; [email protected] A. Thomas Outreach Program, College of Sciences and Mathematics, Auburn University, Auburn, AL, USA e-mail: [email protected] T. Lucy • E. Hickman Alabama Mathematics and Science Technology Initiative, Auburn University, Auburn, AL, USA e-mail: [email protected]; [email protected] J. Cox Alabama Science in Motion Program, Alabama State University, Montgomery, AL, USA e-mail: [email protected] C. Rodger Department of Mathematics and Statistics, Auburn University, Auburn, AL, USA e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_97

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Abstract

A NASA-funded Innovations in Climate Education (NICE) Program has been launched in Alabama to improve high school and middle school education in climate change science. The overarching goal is to generate a better informed public that understands the consequences of climate change and can contribute to sound decision making on related issues. Inquiry-based NICE modules have been incorporated into the existing course of study for 9–12 grade biology, chemistry, and physics classes. New modules in three major content areas (earth and space science, environmental science, physical science) have been introduced to selected 6–8 grade science teachers in the summer of 2013 and 2014. The environmental science module allows students to explore the relationship between extreme climate events, water resources, and water pollution. In the earth science module, students investigate the effects of volcanic eruptions on Earth’s atmospheric composition, global climate, and local landscape and water resources. The physical science module introduces students to the concept of urban climate and heating island effects. The NICE modules employ Roger Bybee’s five E’s of the learning cycle: engage, explore, explain, extend, and evaluate. Module learning activities include field data collection, laboratory measurements, and data visualization and interpretation. K-12 teachers are trained in the use of these modules for their classroom through unique partnership with Alabama Science in Motion (ASIM) and the Alabama Math Science Technology Initiative (AMSTI). Certified AMSTI teachers attend summer professional development workshops taught by ASIM and AMSTI specialists to learn to use NICE modules. Scientists are partnered with learning and teaching specialists and lead teachers to implement and test efficacy of instructional materials and models. This chapter serves as an example of how climate change education can be brought into K-12 schools.

Introduction There is growing concern over the change that is occurring to Earth’s climate and the impact it will have on the people, water resources, and ecosystems. Although the magnitude of climate change in the future is difficult to predict, there are likely to be effects on ecosystems and human systems such as agricultural, transportation, water supply, and health infrastructure – in ways people are only beginning to understand (International Panel on Climate Change 2007; National Academies 2008). These rapid changes make it less likely that human and natural systems will adapt. In order to deal with climate change impacts, greater efforts are needed toward educating the public about the science of climate change. The overarching goal is to improve the teaching and learning about global climate change through secondary education in a majority of high and middle schools in the state of Alabama, employing resources and data provided by NASA Innovations in Climate Education (NICE) Program.

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In order to achieve this goal, new educational modules containing laboratory, field, and computer activities in targeted areas of global climate change education are developed. The main objective is to create modules that can be incorporated into the existing course of study for 6–12 grade science classes. Education modules used in high school classrooms were presented in the first edition of Handbook of Climate Change Mitigation (Lee et al. 2012). This paper presents the contents of new education modules developed for middle schools. High school and middle teachers are trained in the use of these modules for their classroom through partnership with Alabama Science in Motion (ASIM) and the Alabama Math Science Technology Initiative (AMSTI), respectively; both are administered by the Alabama State Department of Education. Specifically, the Alabama NICE program is designed to (1) improve understanding of climate change, enhance problem solving skills, generate greater interest in science, develop better informed persons capable of making decisions, and promote more interest in science, technology, engineering, and mathematics (STEM) careers among students; (2) enhance teachers’ content knowledge of climate change and their ability to direct inquiry-based instruction and use of scientific data in the classroom; and (3) generate climate literacy, support for STEM education, climate conscious communities, and reduction in the carbon footprint among the diverse citizens of the state of Alabama.

Program Development and Implementation Alabama Science in Motion Program The NICE program is sustained through unique partnership with the Alabama Science in Motion (ASIM) and Alabama Math Science Technology Initiative (AMSTI) programs, which are funded by the Alabama State Department of Education. The program is free and allows all Alabama high and middle schools, no matter the size and location, to utilize the same high-tech, state-of-the-art laboratory and field equipment. In 1994 the governor of Alabama signed the Alabama Science in Motion program into legislation, and Alabama became the first state in the nation to institute a state-wide Science in Motion program. ASIM is administered by the Alabama Math Science Technology Initiative (AMSTI). In order for a school to be serviced by ASIM, they must be designated as an AMSTI school. This designation is given if all mathematics and science teachers and administrators come to 4 weeks of professional development training. At present over 40 % of the schools in the state are AMSTI schools. Of the current AMSTI schools, 80 % of the teachers attend a summer 2-week institute in biology, chemistry, or physics for years 1 and 2 of the program. The high school NICE modules are delivered in a separate four-day summer professional development workshop for teachers that have already received years 1 and 2 training. The NICE high school modules become the focal point for the professional development for all AMSTI teachers in grades 9–12 for ASIM year 3 and beyond training. The new NICE middle school modules were developed and delivered in the 2013 and 2014 professional development workshops for about

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30 selected middle school teachers. The professional development workshops are delivered by ASIM and AMSTI specialists who are certified biology, chemistry, physics, and earth science teachers that serve their respective disciplines. This unique arrangement provides an equal opportunity for hands-on experimentation that many Alabama students would never experience. The program better prepares students for postsecondary education and recruitment into STEM disciplines.

Educational Modules The NICE middle school education modules are developed by scientists in various content areas (e.g., earth and space science, environmental science, physical science) in conjunction with AMSTI specialists and lead teachers (Table 1). The modules employ Roger Bybee’s (Bybee 1997) five E’s of the learning cycle: engage, explore, explain, extend, and evaluate. The modules are aligned with the Alabama Course of Study, Alabama Graduation Examination, and National Learning Standards in Science, Geography, Technology, and Environmental Education (American Geographical Society 1994). Modules’ learning activities include field data collection and laboratory measurements. Students employ remote sensing imagery and conduct Table 1 Overview of NICE middle school educational modules Science content areas 2.1. Earth and space science

Main themes Effects of volcanic activities on atmosphere and climate

2.2 Hydrology–environmental science

Groundwater resource and climate change

2.3 Physical science

Urban heating island effects

Module activities 2.1.1 Build a baking soda and vinegar volcano 2.1.2 Assess the reduction in light to Earth’s surface using simple tools 2.1.3 Use graphic methods to explore impacts of volcanic eruption on climate 2.2.1 Build an aquifer 2.2.2 Use the aquifer model to learn the basic vocabulary of groundwater and its hosting aquifers 2.2.3 Use the aquifer model to explore Earth’s hydrologic cycle and impacts of climate change 2.3.1 Understand impacts of urbanization on local environment 2.3.2 Measure temperature and humidity to learn about pervious and impervious urban surfaces 2.3.3 Use remotely sensed images compare and contrast global cities 2.3.4 Watch a movie on renewable energy and analyze the pros and cons of adaptation and mitigation techniques for global climate change

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hands-on laboratory experiments to investigate effects of global climate changes on physical environments and humans. NICE instructional materials include background content information (including an introductory Climate 101 Podcast), a detailed description of the specific exercise, pre-laboratory PowerPoint notes for teachers and students, pre- and post-laboratory test questions, and detailed procedures that utilizes the five E’s of the learning cycle for each module. Climate 101 Podcast introduces teachers and students the basic key concepts and fundamental issues of global climate change. Students will leave the classroom with an understanding of the sources and impacts of climate change, the key national and international policies, and potential impact of climate change on human activity for many years to come. Currently, this climate change podcast is distributed as a DVD digital media file (including video and audio) via ASIM. The standards alignment (National Science Education Standards 1996) is articulated, and an equipment/ materials list is generated, along with specific references. The modules enable students to gain hands-on experience in collecting and analyzing data, as well as to empower students and teachers to become more engaged in issues related to global climate change.

Earth and Space Science Module: Effects of Volcanic Activities on Atmosphere and Climate Leading scientists: Ming-Kuo Lee AMSTI specialist: Tyaunnaka Lucy, Jennifer Cox Background. More than 50 volcanoes erupt each year worldwide and some of the catastrophic eruptions may change climate. For example, the 1991 eruption of Mt. Pinatubo in the Philippines blasted millions of tons of gases (e.g., sulfur dioxide) and solids (e.g., ash particles) into the atmosphere which circled the globe for weeks. These airborne-erupted materials (known as aerosols) may linger in the atmosphere for years before being flushed out by fluid motions (e.g., precipitation) in the atmosphere. These lingering aerosols can scatter the incoming solar radiation that reaches Earth’s surface, resulting in lower temperature in the atmosphere. The sources of aerosols can be either natural (e.g., volcanic eruption) or anthropogenic (e.g., combustion of fossil fuels and biomass). A natural catastrophic volcanic eruption may cause a “measurable” change in Earth’s climate on the timescale of several years (Russell et al. 1996). In addition to their effects on Earth’s atmospheric composition and global climate, volcanic eruptions have effects in modifying the local landscape, weather, and water resources. Learning goals and activities. Students learn (1) climate change can result from natural catastrophic events such as volcanic eruption and (2) understand the massive outpouring of gases and solids from volcanoes may increase the amount of aerosols in the atmosphere. In this activity students (1) build a baking soda and vinegar volcano, (2) assess the reduction in light to Earth’s surface using simple tools, and (3) use simple graphing activities to illustrate climate impacts of volcanic eruption. This module is modified from a climate discovery educational module prepared by

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the National Center for Atmospheric Research (NCAR) (http://eo.ucar.edu/educa tors/ClimateDiscovery/LIA_lesson8_9.28.05.pdf). Engage. Students asked to read the following quote describing the conditions in Olongapo City, close to Mt. Pinatubo before and during its eruption in 1991. I was only 14 when it happened. But I remember that there was no sun for several days. The sky was either red or black. The ground was shaking all the time for days from the aftershocks. It was raining ashes and we had to wear a mask when we went outside. We also stayed inside the base for three days.

An image of the massive eruption of Mt. Pinatubo was provided (Fig. 1). Students brainstorm the changes in (1) the landscape near a volcano during and after an eruption and (2) in the atmosphere during and after an eruption. Students may be asked: What happens during a volcanic eruption and what materials are ejected from the volcano? What effects will the ejected materials have upon Earth’s atmosphere? Students also make a list of potential changes for the landscape and water resources over time after a volcanic eruption. Teachers explain the eruption processes, materials ejected from volcanoes, and potential eruption impacts: (a) The very hot magma (known as lava) leaves the magma chamber, forcing its way through the volcano and reaching Earth’s surface. The lava flows down the sides of the volcano, cooling and solidifying over time, forming layers of ash and cinder along the cone. Some eruptions can be explosive, and ejected materials may include rock fragments (known as pyroclastic debris), ash (particles < 2 mm in diameter), and gas (H2O, SO2, and CO2). Fig. 1 An image of the massive eruption of Mt. Pinatubo on June 15, 1991 (From http:// volcanoes.usgs.gov/hazards/ gas/climate.php)

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(b) The airborne-erupted materials (known as aerosols) may linger in the atmosphere for years before being flushed out by fluid motions like rain (e.g., precipitation) in the atmosphere. These lingering aerosols can scatter the incoming solar radiation that reaches Earth’s surface, resulting in a lower temperature in the atmosphere. On the other hand, volcanic carbon dioxide, a known greenhouse gas, has the potential to promote global warming. (c) Quick-moving lava (basaltic) with speeds up to 30 km/h can cover the land and create new rocks. The eruption of slow-moving lava (andesitic) forms a large mound (known as lava dome) above the vent. Explosive eruptions and accompanying earthquakes may trigger landslides. In cases where volcanoes are covered with snow and ice, water can mix with ash to form a mudflow called a lahar, which moves down the slope very quickly at speeds up to 50 km/h. The most common type of water contamination results from ash fall and causes a change in turbidity, acidity (pH), and toxic metals. Ash can clog streams and cause the turbidity (cloudiness of water caused by suspended solids) of water to rise and the pH of water to fall. Finer ash is able to carry more toxic metals and contaminate local water supply. Explore 1. Students build a baking soda and vinegar volcano using the following steps: (a) First make the “cone” of volcano using model clay or dough. Make their own dough by mixing flour, cooking oil, and water. The dough should be smooth and firm. Mold the dough around the soda bottle into a volcano shape. Do not cover the hole or drop dough into it. (b) Mix vinegar (or warm water) with a pack of powdered drink mix. (c) Fill the bottle to about ¾ of its capacity with warm water. (d) Add 6–7 drops of detergent to the bottle contents. The detergent helps trap the bubbles produced by the reaction. (e) Add three tablespoons of baking soda to the liquid. (f) Slowly pour vinegar into the bottle until it starts to bubble and watch for the eruption (Fig. 2). (g) Recharge the volcano by adding more baking soda and vinegar. 2. Students assess the reduction of solar energy reaching Earth’s surface following a volcanic eruption. Students use an infrared digital thermometer (i.e., an IR gun) to measure the temperature of a white surface exposed to direct sunlight. They then measure the temperature of a white surface in the shadow of Sun. Students compare and note the change in surface temperature. The white surface represents the surface of the Earth and sunlight obstruction represents the dust layer produced by a volcanic eruption that blocks incoming light. 3. Students explore the effects of a large eruption on the atmosphere and Earth’s surface temperature. The illustrations of the Sun with different brightness (known as illumination) shown below reflect the amount of ashes and debris in the atmosphere. Students use a pocket light meter to measure how much illumination is spread over a given area in the illustration with maximum light (before

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Fig. 2 AMSTI teachers built a baking soda and vinegar volcano

Before eruption During eruption Measured illumination (in lux) Measured illumination (in fc)

Fig. 3 Difference in the illustration with maximum light (before eruption) and minimum light (during eruption)

eruption) and minimum light (during eruption) (Fig. 3). The unit for illumination can be expressed either as lux (lumen per square meter) or foot-candle (fc, in lumen per square foot) (1 fc = 10.764 lx). Students draw two curves (amount of debris vs. time and temperature vs. time) in a diagram (Fig. 4) that demonstrates the impacts of volcanic eruption on atmosphere and Earth’s surface temperature. Explain. Students are asked to answer the following questions after the experiments: (a) What type of gas is produced by mixing baking soda and vinegar? Will this gas be produced in real volcanoes? Is this gas considered a greenhouse gas? (b) What are the temperatures of the white surface exposed to direct sunlight and those in the shadow of Sun? After a massive volcanic eruption, the airborneerupted materials (known as aerosols) may linger in the atmosphere for years.

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More Debris

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TIMELINE

Amount of volcanic debris in atmosphere

Less Debris Time

Warmer

Temperature at the Earth surface

Cooler Time

Fig. 4 The illustration of Sun before, during, and after a volcanic eruption

How do aerosols affect the incoming solar energy? How would Earth’s surface temperature change (cooling or warming) in the years after a massive volcanic eruption? (c) Use the illustrations of the Sun to answer the following questions: • How does the relative amount of ash in the atmosphere change over time before, during, and after eruption? • How will the amount of volcanic ash (and the change in ash through time) affect temperature on Earth’s surface? • Explain the correlation between the amount of ash and atmosphere temperature. Extend. Students investigate what Earth’s (geological) tectonic processes may cause volcanic eruption and where the active volcanoes are often located on Earth’s surface. Students conduct research on selected supervolcanoes (e.g., Yellowstone) whose eruption in the past or modern time might dramatically affect Earth’s atmosphere and climate.

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Evaluation. Evaluations of student performance are based on (1) students’ answers to pre-lab questions, (2) students’ graphs (debris vs. time and temperature vs. time), (3) students’ explanations on results, and (4) students’ report on extension activities. Equipment/materials needed. An infrared digital thermometer, an Extech light meter, man-made volcano ingredients (warm water, liquid dishwashing detergent, baking soda, vinegar, food coloring, or powdered drink mix).

Hydrology and Environmental Science Module: Groundwater Resource and Climate Change Lead scientist: Ming-Kuo Lee AMSTI specialists: Jennifer Cox, Tyaunnaka Lucy Background. There is growing concern over the impacts of climate change on people and their water resources (Shat 2005; Foster 2006).Because of climate change, extremes in climate such as droughts and floods are likely to become more severe and more common (IPCC 2007, 2012; Karl et al. 2008). An increase in precipitation would lead to increases in surface runoff, sediment yields, nutrient loading, and release of human pollutants. An extended period of drought will lead to shortages of water and food supplies. Climate change can affect every component of our global freshwater budget, including precipitation, evaporation, groundwater, and surface stream flow and runoff (Chang and Jung 2010; Lee et al. 2013). Among various water resources, groundwater is the world’s largest storage of clean freshwater. Groundwater is also the primary source of drinking water to nearly half of the world’s population (Moench 2005) and the dominant source of water for irrigation and industrial activities. Future changes in climate and precipitation patterns will intensify pressure upon groundwater resources to meet the rapidly growing, global demand for freshwater. Learning goals and activities. This module introduces students to the basic vocabulary used to describe groundwater and its hosting aquifers. Key terms (italicized) include precipitation, surface runoff, water table, unsaturated zone, saturated zone, well casing, and well screen. Students will build an aquifer to learn the fundamentals of Earth’s hydrologic cycle, such as recharge and discharge, and the effects of rain, drought, and pumping on water table. After these activities students will better understand aquifers and the relationship between climate, water resources, and water pollution. Engage. PowerPoint notes on basic groundwater and aquifer vocabulary, hydrologic cycles, and effects of climate change on water resources are presented to students by the teacher. Students then fill in the word boxes in the groundwater chart (Fig. 5), which show various components of the hydrologic cycle and a groundwater aquifer. After learning the basic vocabulary and concepts, students build their own aquifer models (Fig. 6) using an aquifer kit provided by the NICE project team. Students follow the following steps: (1) Insert rubber stop into the drainage hole of the 1.5-gal

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Fig. 5 A chart showing groundwater aquifer and hydrologic cycle

Fig. 6 ASMTI teachers built an aquifer tank model to demonstrate groundwater flow and contamination. Water can be added to simulate recharge or pumped out to simulate drought and overuse

tank; (2) slope a layer of gravel in the tank, with the lowest ground near the drainage hole; (3) insert a 1-in diameter well (a PVC pipe with holes drilled to serve as well screen) near the higher ground close to the side of the tank, with screen tapping the bottom gravel layer; (4) create a river by placing a clear plastic liner (with holes punched in the bottom) near the low ground; (5) lower a spray pump with plastic tubing to the screen interval in the PVC pipe; and (6) create a lake near high ground by patting down a thin layer of clay on a small circular depression.

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Exploration (a) Students simulate a precipitation event by slowly pouring water on ground surface using a cup with holes punched in the bottom. Some of the rain runs off on the surface into the river. Some of the rain moves down through the sediments and begins to fill up the aquifer (a process known as recharge). Students can see a river in the depression (discharge area) is fed directly by surface runoff and also by groundwater moving through the aquifer (a process known as discharge). (b) Students mark the initial water table, saturated zone, and unsaturated zone (before the water table reaches the riverbed) using a water-soluble marker. They add more water and observe how the water table responds to rainfall. Students then use a spray pump (represents a municipal well) to withdraw groundwater from the aquifer. They observe how the water table declines in response to pumping. Groundwater cannot be withdrawn when the water table drops below the well screen interval. (c) Students will slowly pour water into the lake underlain by clay, sand, and gravel. Students will compare the permeability of gravel, sand, and clay. (d) Students simulate groundwater contamination by slowing pouring colored water (use food coloring or dye) on the ground near the water well, or students can spread colored powder (Kool-Aid) on the ground surface and then slowly pour water on the powder. Students observe how the contaminant reaches the groundwater and water well. Students will withdraw contaminated groundwater from the well using the pump. Explain. Students are asked to answer the following questions after the experiments: (a) Why some rainwater does not simply disappear on the surface while other rainwater quickly percolates through the ground? Are all the rock layers equally permeable? (b) What happens to an aquifer when it rains? What happens to an aquifer when its groundwater is continuously withdrawn during a drought? (c) Explain the concept of groundwater safety yield. What happens when the water table drops below the well screen? (d) Explain why the safety and effectiveness of a water well depends upon its siting. (e) Explain why a well needs to be properly sealed (known as well closure) when it is. (f) List potential groundwater contaminants. Extend. Students explore the concepts of the porosity of different geologic materials (i.e., clay, sand, and gravel) using the fluid saturation methods*. Students will find out which material is very porous (with pore spaces to store water) and permeable (allow fast water movement) and can make a productive aquifer for water supply. Contaminants must be removed from groundwater before it reaches

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municipal water systems. Students will search and write a report on state-of-the-art groundwater remediation methods (i.e., remove contaminants by physical, chemical, and biological methods such as pump-and-treat, oxidation/reduction, and bioremediation). Information on specific groundwater cleanup technologies organized by type and contaminants can be found on the US Environmental Protection Agency (USEPA) website: http://www.epa.gov/superfund/remedytech/remed.htm. *Fluid saturation method can be used to measure the porosity. A clean and dried sample is weighted, saturated with a liquid of known density, and then reweighed. The weight change divided by the density of the fluid results is the pore volume. The volume of dried sample can be estimated using a beaker. Porosity is calculated as the ratio of fluid pore volume and volume of bulk sample. Example. The following procedure can be run to obtain pore and bulk volume of a sample and porosity using water with a density of 1 gm/cc. (1 cc = 1 mL): 1. 2. 3. 4.

Weight of clean, dry sand: Wdry = 115 gms. Bulk volume of clean, dry sand: Vb = 100 cc (cc = cubic centimeters). Weight of sand saturated with liquid Wsat = 135 gms (ρw = 1 gm/cc). W W Calculate the pore volume of fluid V p ¼ satρ dry ¼ 13S11S ¼ 20 cc. 1

5. Porosity =

Vp Vb

w

20 ¼ 100 ¼ 20 %.

Evaluation. Evaluations of student performance are based on (1) students’ aquifer model, (2) students’ explanations of key terms and demonstration on aquifer model, and (3) students’ report on extension activities. Teachers use the following score sheet to evaluate students’ work: Aquifer Score Sheet Students’ Names: ____________________________________________ Concept Groundwater recharge from precipitation Groundwater recharge from surface water Groundwater discharge to river Water table Saturated zone Unsaturated zone Permeability Impact of a well has on groundwater Groundwater contamination

Explain/ define 1 2 1 1 1 1 1 2 1

Demo/point out 1. Recharge to groundwater

Total

1. Existence of surface water 2. Recharge to groundwater 1. Water flow in river 1. Point out the water table 1. Point out the saturated zone 1. Point out the unsaturated zone 1. Show permeability in 2 different materials 1. Water is withdrawn from well 2. Water level is lowered 1. Contamination is shown in groundwater (continued)

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Concept Importance of well siting (location) Importance of well closure Groundwater as part of hydrologic cycle

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Explain/ define 1 1 1

Demo/point out 1. Location of wells to source of pollution 1. Place cap on well 1. Connection among reservoirs

Total

Equipment/materials needed. 1.5-gal aquarium tank, gravels, sands, clays, one PVC pipe (1 in in diameter and 8 in long) with holes drilled to serve as the screen interval, PVC pipe cap, spray pump with plastic tubing, water-soluble marker, rain maker (plastic cup with holes in bottom), clear plastic liner (river), flashlight (to look down the well), food coloring, beakers, rubber stop, syringe (to drain water).

Physical Sciences Module: Urban Heating Island Effects Lead Scientist: Chandana Mitra AMSTI Specialist: Tyaunnaka Lucy Background. Rapid urbanization has led to an increase in built-up area and impervious surfaces, increased greenhouse gas emissions, and more anthropogenic activities which are detrimental to the delicate yet complex environmental climate system of the Earth (IPCC 2007, 2012). Considered to be a cumulative effect of all these impacts is the urban heat island (UHI), defined as the difference of temperature between urban and surrounding rural areas. The urban heat island is a distinct “warm island” among the “cool sea” (Pérez and Peña 2010) which is graphically shown in Fig. 7. In countries like the USA, heat is the primary weather-related cause of death, and therefore, promotion of strategies for mitigating the UHI is a big concern for government agencies. There are two main UHI reduction strategies: first, to replace the black asphalt roofs with white-colored roofs and, second, to transform the concrete roofs to green roofs by planting grass and plants on them (Solecki et al. 2005). Overall the UHI can be mitigated by growing urban forests and parks and using more of renewable energy like solar and wind power instead of energy produced by fossil fuels. This would make the cities more sustainable and livable in future. Learning goals and activities. This module introduces the basic knowledge about urbanization and what the impacts of rapid urbanization are on our environment. At the end of this activity, the students will understand how changing local environmental conditions like population increase, the materials you use on buildings, cars you drive, and the lifestyle you lead can affect city temperatures and create an urban heat bubble, also known as urban heat island. The students will be using infrared thermometers and hygrometers to measure the differences in temperature and moisture for different materials. They will also watch a movie that will give them an insight into the various renewable forms of energy which could be a solution to future climate change.

Bringing Global Climate Change Education to Middle School Classrooms: An. . . Fig. 7 Urban heat island source: http://www.nctcog. org/trans/sustdev/SDGreen/ UrbHeatIsl.asp

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Little vegetation or evaporation causes cities to remain warmer than the surrounding countryside

Fig. 8 Growth of Riyadh, Saudi Arabia (Source: USGS)

Engage. PowerPoint notes on urbanization, urbanization impact on climate change, permeable and impermeable surfaces, albedo, urban heat island, adaptation and mitigation techniques, and renewable energy will be provided. To further engage the students, they will use tracing papers and the given Google and USGS images (http://earthshots.usgs.gov/earthshots/about#ad-image-0). With the help of the tracing papers, they will try to determine and see for themselves how cities are growing worldwide. A number of images downloaded from Earthshots–USGS will be provided, for example, Riyadh in Saudi Arabia (Fig. 8), Sydney in Australia (international), and Atlanta in the USA. This will give them an idea of the impact of uncontrollable city growth over short period of time and relate to the discussion earlier on impacts of population increase on environment.

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The students will also be asked questions to engage them in a discussion involving their visit to Atlanta GA, did they see parks in Atlanta downtown, how much of Atlanta downtown is green, and what happens when a lot of people come and settle in a city. Besides these they will also be asked about the surface (green grass or concrete) they would like to walk on a hot afternoon, why people living in deserts wear white long robes, what happens when you burn coal, and whether they have heard about wind and Sun’s energy usage. In this module Atlanta is the city of focus but the teacher can choose any big city which the students are familiar with. That will give the students a sense of involvement. After learning the basic concepts and discussing the urbanization issues, students will use the instruments to measure temperature and humidity of various surfaces provided in the “urban heat island” kit by the NICE project team. Exploration (a) Option 1: Students will use infrared thermometers and hygrometers to measure the temperature of black and white surfaces and moisture level over a cemented concrete surface and a grass surface (Fig. 9). They will write their readings in the table provided below (can increase the rows if they feel like measuring more surfaces made of various materials). The students will calculate the differences and then discuss the reason why there is a difference in the temperatures. They will then relate the surface measurement differences to an urban environment. The teacher will help the students here by citing examples of heat absorption by black cars, white cars, desert people wearing long white robes, and black solar panels (example will be provided in the PowerPoint). IR thermometer reading White surface (roof if possible/white board) exposed to direct sunlight Dark black surface (roof if possible/black board) in direct sunlight Surface of black car Surface of white car Grass surface Concrete surface Hygrometer reading

Temperature ( C)

Temperature ( F)

Relative humidity (%)

Concrete surface in direct sunlight Grass space in direct sunlight Concrete surface under shade of tree Green space under shade of tree

Option 2: If the teacher wants, then he/she can make the students do a day-long study taking measurements every hour or every 2 h, documenting the temperature for different materials. They can prepare trend lines using graph papers (temperature and humidity variations vs. type of surface) to show how the

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Fig. 9 AMSTI middle school teachers using IR thermometers to measure temperature of black cars and hygrometer to measure humidity of green grass

temperature varies depending on material in an urban environment. The teacher will help the students to relate the trend lines with urbanization and discuss the benefits of having white roof over black roofs and green space and urban parks over all impervious surfaces. (b) The teacher will show in class the movie “Carbon Nation” (a movie on renewable energy) as a part of exploration. This movie is 84 min long which is one of the best climate change solution movies. The movie does not directly deal with the subject of climate change but focused mainly on using renewable energy which will help mitigate some of the effects of climate change and make our Earth a better place to live in. Explain (a) Why do you think dark roofs are hotter than white roofs? How does albedo help in reducing white roof temperatures? (b) What are the problems of having dark roof? (c) Do you think having green parks, green roofs, and green walls will help lessen the effect of UHI? (d) The more concrete we have in our cities, the chances of having more urban flooding will increase – is this true? (The teacher will ask the students to relate this to the “Aquifer module” and make them relate urban flooding with impermeable surface and surface runoff.) (e) Students will take notes while watching the movie “Carbon Nation” on the different types of renewable energy and what the benefits of each are. Is it possible to replace nonrenewable energy with renewable energy? Students will discuss the long-term and short-term benefits of using renewable energy. Extend (a) The students will use various methods (pictures and articles from magazines, journals, newspapers, Internet sources) to prepare charts and collages on the

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things they learned during lab. They can work in groups. They will learn about each renewable energy, their limitations and examples from different parts of the world; try to find out if anywhere in their area solar power is harnessed; learn about electric cars and if they are better; and the gases that cause global warming and why they are increasing in the atmosphere. (b) Students will investigate what would happen if there is an increase in heat in urban areas, discuss in class about ways in which population can be attracted away from cities to suburban areas, and conduct research on the growth of various cities in the USA and worldwide to see how cities are growing and at what rate. (c) Another extension would be to talk to their neighbors and educate them on roof color and material and write a report on what feedback they received. The students can work in groups for this. (d) Ask the students to find out if the city nearby or the city in which they live has a Climate Action Plan. They should search on the net cities which have implemented the maximum UHI mitigation techniques (Portland, Chicago, New York City, State of California). Evaluation. Evaluations of student performance are based on (a) students’ answers to questions based on PowerPoint notes, (b) their understanding of temperature and humidity differences and their effects on urban–rural climate patterns based on responses in class, (c) students’ graphs (temperature and humidity variations vs. type of surface), (d) students’ explanations of results and answer to the explain section, and (e) students’ report on extension activities. Equipment/materials needed. Overhead projector, an infrared digital thermometer, hygrometer, Google and USGS images showing growth of cities, tracing paper, reading material (urban heat island, city growth over time, adaptation and mitigation techniques to reduce urban heat island effect, renewable energy), two cardboard sheets (black and white) to represent different colored roofs.

Program Dissemination Several methods of dissemination have been employed. Results of outreach activities and education materials were divulged through publications, conferences, and education symposium. Education modules used in high school classrooms and their evaluations were presented in the first edition of Handbook of Climate Change Mitigation (Lee et al. 2012). This paper presents the contents of new education modules developed for middle schools. Moreover, more than 10 papers have been presented at national conferences hosted by the American Geophysical Union, Geological Society of America, America View Fall technical meeting, and American Meteorological Society. Last, the College of Sciences and Mathematics hosted a climate change education symposium to educate faculty, graduate students, and undergraduate students on the interdisciplinary interface of sciences and mathematics. A forum “Frontiers in Global Climate Change” was held in the spring semester

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of 2012. The leadership team served as the coordinating committee for the symposium. The keynote address was delivered in a fashion so that individuals not engaged in specifics of climate change research can become more informed. This forum enabled the leadership team to continue to meet and to refine background understanding regarding NICE education. In addition, it provided the leadership team with specific training in topics relevant to NICE. The symposium was advertised on-campus and to neighboring institutions in the region, which includes two historically Black colleges and universities: Alabama State and Tuskegee University. Media coverage was requested as well through Auburn University Office of Marketing and Communications.

Conclusions Successful implementation of NICE education modules should enable significant advances in high school climate change science education. New resources including instruction materials for teachers and students have been developed in forms of laboratory handouts, database, laboratory kits, and multimedia products (podcast, movie, and PowerPoint files). The modules use new technology or innovative tools including computer software, web-based data search and visualization, and scientific data collections using sensors. The instruction materials are aligned with state and national academic standards, and teacher professional development program is implemented through partnership with ASIM and AMSTI programs. The overall teacher satisfaction from the teacher training was 4.88/5.00. The overall conclusion from the pre–post attitude assessment was the teachers came to the workshop interested in learning more about global climate change and were aware that it is an environmental concern that needs more public attention. While they also believe the government should be involved and NICE should be a national priority, they are not sure how at this point in time. After completing the module teacher training, the teachers reported a strong agreement that the content developed in the modules of this project for teaching global climate change concepts should be included in the Alabama secondary curriculum. At the culmination of the project, the team and AMSTI director will convene a final project meeting to disseminate the final evaluation results and plan for sustained delivery of NICE modules by AMSTI personnel. A preliminary conclusion of this project is that high and middle schools can effectively partner with universities to offer students a meaningful and enriching science experience that increases their understanding of the concepts of Earth’s system and climate change, and underscores the need to take action. Such a project can give these students access to expertise and equipment, thereby strengthening the connections between the universities, state education administrators, and the community. This project can serve as an example for improving K-12 school education in climate change science around the world to raise public awareness and perception.

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Acknowledgments This project was supported by a grant from NASA NICE Program (NN09AL73G; Principal Investigator: Chris Rodger) and funding from the Alabama Science in Motion (ASIM) and Alabama Math Science Technology Initiative (AMSTI). We thank Mr. Matthew Williams (Office of Sustainability, Auburn University) for preparing a global climate change podcast as part of the instructional materials. We also thank America View, consortium of remote sensing scientists to expertise on satellite images.

References American Geographical Society, Association of American Geographers, National Council for Geography Education, and National Geographic Society (1994) Geography for life national geography standards. National Geographic Research and Exploration, Washington, DC Bybee RW (1997) Achieving scientific literacy: from purposes to practices. Heinemann Publisher, Portsmouth Chang H, Jung I-W (2010) Spatial and temporal changes in runoff caused by climate change in a complex large river basin in Oregon. J Hydrol 388:186–207 Foster S (2006) Groundwater; sustainability issues and governance needs. Episodes 29:238–243 International Panel on Climate Change (2007) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK/New York IPCC (2007) Climate change 2007: the physical science basis. In: Solomon SD, Qin M, Manning M, Marquis K, Averyt MMB, Tignor HL, Miller HL Jr, Chen Z (eds) Contribution of working group 1 to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, New York IPCC (2012) In: Field CB, Barros V, Stocker TF, Qin D, Dokken DJ, Ebi KL, Mastrandrea MD, Mach KJ, Plattner GK, Allen SK, Tignor M, Midgley PM (eds) Managing the risks of extreme events and disasters to advance climate change adaptation. A special report of working groups I and II of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK/New York, 582 pp Karl RT, Meehl GA, Miller CD, Hassol SJ, Waple AM, Murray WL (eds) (2008) Weather and climate extremes in a changing climate. Regions of focus: North America, Hawaii, Caribbean, and U.S. Pacific Islands. U.S. Climate Change Science Program Synthesis and Assessment Product 3.3, 180 pp Lee M-K, Marllin S, Fielman K, Marzen L, Lin Y, Birkhead R, Miller C, Norgaard P, Obley M, Cox J, Steltenpohl L, Wheeles E, Wooten M, Rodger C (2012) Bring global climate change education to Alabama Classroom. In: Handbook for climate change mitigation. Springer, New York, pp 1983–2028 Lee M-K, Natter M, Keevan J, Guerra K, Saunders JA, Uddin A, Humayun M, Wang Y, Keimowitz AR (2013) Assessing effects of climate change on biogeochemical cycling of trace metals in alluvial and coastal watersheds. Br J Environ Clim Change 3:44–66 Moench M (2005) Groundwater; the challenge of monitoring and management. In: World’s Water, 2004–2005, P. Gleick, ed., Island Press, Washington DC, pp. 79–100 National Academies Report (2008) Understanding and responding to climate change. Highlights of the National Academies Reports. the National Academies, Washington, DC National Science Education Standards (1996) National Research Council. National Academy Press, Washington, DC Pérez AC, Peña MA (2010) The urban heat islands (UHI). http://www.urbanheatislands.com/. Last accessed on 16 Oct 2014

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Russell PB, Livingston JM, Pueschel RF, Bauman JJ, Pollack JB, Brooks SL, Hamill P, Thomason LW, Stowe LL, Deshler T, Dutton EG, Bergstrom RW (1996) Global to microscale evolution of the Pinatubo volcanic aerosol derived from diverse measurements and analyses. J Geophys Res 101:18745–18763 Shat T (2005) Groundwater and human development; challenges and opportunities in livelihoods and environment. Water Sci Technol 51:27–37 Solecki WD, Rosenzweig C, Parshall L, Pope G, Clark M, Cox J, Wiencke M (2005) Mitigation of the heat island effect in urban New Jersey. Global Environ Change B Environ Hazards 6:39–49

Climate Change: Outreaching to School Students and Teachers Dudley E. Shallcross, Timothy G. Harrison, Alison C. Rivett, and Jauyah Tuah

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Need for Education in Climate Science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Granny Model: Basic Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Granny Model: The Underpinning Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A One-Layer Atmosphere Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A One-Layer Atmosphere Model Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A One-Layer Atmosphere Model: Taking the Investigation Much Further . . . . . . . . . . . . . . . Surface Temperatures on Other Planets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Snowball Earth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Global Dimming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stratospheric Ozone Depletion and Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Milankovitch Cycles and Ice Ages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Milankovitch Cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Present-Day Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A Simple Mathematical Model That Can Be Used to Predict the Atmospheric Level of Greenhouse Chemicals Given Their Lifetime and Emission Rate . . . . . . . . . . . . . . . . . . . . . . Simple Mathematical Climate Model to Investigate the Role of the Oceans in Slowing Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climateprediction.net: Taking Part in Climate Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Writing Articles for School Students and Their Teachers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Practical and Hands-on Activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A Climate Change Lecture Demonstration: A Pollutant’s Tale . . . . . . . . . . . . . . . . . . . . . . . . . . . . Demonstrations and Experiments That Can Be Done in School to Augment Climate Change Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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D.E. Shallcross (*) • T.G. Harrison • A.C. Rivett Bristol ChemLabS, School of Chemistry, University of Bristol, Bristol, UK e-mail: [email protected]; [email protected]; [email protected] J. Tuah Secretariat of Brunei Darussalam Technical and Vocational Education Council, Permanent Secretary Office (Higher Education), Ministry of Education, Bandar Seri Begawan, Brunei Darussalam e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_53

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Soot/Particulate Carbon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Solubility of CO2 in Water/Precipitation of Calcium Carbonate . . . . . . . . . . . . . . . . . . . . . . . . . . Methanol Whoosh Bottle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hydrogen-Filled Balloons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Reduction of Iron Oxide on a Match Head . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alcohol Burners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fuel Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Grätzel Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Production of Biofuels from Vegetable Oils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nitrogen Dioxide Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Detection of Atmospheric Carbon Dioxide Levels Using IR Sensors . . . . . . . . . . . . . . . . . . . . . Impact and Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Generic Learning Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Suggested Questions to Discern Different Learning Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . Some Misconceptions Concerning Climate Change and Greenhouse Gases . . . . . . . . . . . . . . . . . Datasets That Can Be Used in a Class Setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . AGAGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Global Warming Potentials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methods Used to Monitor Greenhouse Gases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Outreach: Impact on Providers and Others . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . What Is the Impact on Postgraduates and Researchers Who Engage with Schools, Teachers, and the General Public? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Impact on Recipients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Is Climate Change All Gloom and Doom? Introducing Stabilization Wedges . . . . . . . . . . . . What Activities May Achieve This Effect? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Even More Contemporary Atmospheric Chemistry: Criegee Biradicals . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

This chapter will describe some simple models that have been used to explain the basic principles of the Earth’s climate to primary school students (aged 4–11), secondary school students (aged 11–16), post-16 students (16–19), and the general public (all ages) including those with disabilities. It will then describe a range of hands-on practical activities that demonstrate aspects of the climate system at the appropriate level. Assessment and impact of these activities on the learner’s level of cognition are then presented showing that the hands-on approach is a most effective way of communicating such concepts irrespective of the age of the learner. Furthermore, the varied impacts of a “lecture demonstration,” that is, a talk where points are illustrated by exemplar experiments that visually portray the science concept, are presented. The many misconceptions that surround the understanding of the Earth’s climate system and how teachers and other science communicators can deal with such issues in a classroom setting are discussed. The sourcing and use of the myriad datasets linked with the Earth’s climate that are freely available for schools’ projects are discussed with illustrations drawn from projects undertaken already.

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Often the impact of such engagement activities on the provider themselves is ignored; here the tangible benefits to all providers involved are discussed with some case studies as illustrations. Finally, the future prospect for the Earth’s climate is nearly always portrayed as negative. In this chapter, the idea of stabilization wedges and ways that the worstcase scenarios for climate change can be averted is discussed. Using a variety of metrics, it is possible for a wide range of learners to appreciate the impact of any mitigation strategy, that is, literally “speaking in a language they can understand.”

Introduction The Need for Education in Climate Science It is essential that teachers are armed with the correct (factual) information about the Earth’s climate system, so that they can educate the next generation of students. It goes without saying that such education is essential so that these students can make informed decisions about their response to potential climate change. In the UK, climate chemistry is now included in many science courses that are taken by 16-yearold students, toward the end of compulsory education. Further work on climate change is part of advanced-level (A-level) chemistry and other courses that are taken by preuniversity students. Many of these courses have associated textbooks which do not go into sufficient depth to answer some of the questions that arise. More confusion results from incorrect information from a number of sources including the press, the Internet, and teachers that are not sufficiently knowledgeable about the topic (see section “Some Misconceptions Concerning Climate Change and Greenhouse Gases”). A fundamental problem is that a basic explanation of the Earth system and the need for naturally occurring greenhouse gases and their impact is often muddled. The Research Councils UK (RCUK) (2002) was anxious that high-quality teacher training on the Earth’s climate, and several other topics, was put in place by the creation of a daylong course to be hosted by the Science Learning Centres and run by experts in the field (Science Learning Centres 2004). The RCUK is split into seven sub-councils (arts and humanities, biosciences, engineering and physical science, economics and social science, medical, natural environment, and the science and technology facilities) and administers funding for research in the UK of around £2 billion a year in these areas. The Science Learning Centres were originally a network of nine regional centers and one national center, which provide continuing professional development for both primary and secondary teachers in the UK. These have recently contracted to five regional centers and the National Science Learning Centre in York. Therefore, in the UK, such a partnership was very potent in terms of its ability to bring expert researcher and teacher together. These courses are not compulsory for teachers to attend, and although feedback is very good, it will take a long time for the material to be disseminated from teacher to teacher. It is hoped

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that one consequence of this chapter would be that it is of assistance to teachers and other educators looking to improve their understanding of climate science.

The Granny Model: Basic Concepts Figure 1 introduces the Granny model; it consists of a heater and a very sensible Granny (grandmother). She wants to keep warm but knows that if she sits too far away from the heater, she will be cold and if she sits too close to the heater, she will be too warm. So she places her seat a sensible distance away from the heater so that she is neither too hot nor too cold, but just the right temperature (sometimes this is known as the Goldilocks hypothesis). The Granny represents the Earth and the heater is the Sun. It turns out that the Earth is just the right distance away from the Sun for the average surface temperature to be about 10
C, based on simple heat flux arguments (see section “The Granny Model: The Underpinning Mathematics”), and this qualitative explanation works well at KS3 (Key Stage 3, 11–14-year-olds in the UK). There is a problem with this simple model, in terms of the Earth system, illustrated by Fig. 2. Clouds in the sky and ice at the Earth’s surface act as mirrors and reflect back to space about 30 % of the energy arriving from the Sun. It turns out that about 6 % is reflected by ice at the surface and 24 % from the atmosphere (mostly by clouds), and this reflectivity (30 %) is known as the Earth’s albedo, A (where A = 0.3). Other surfaces on the Earth are reflective but nowhere near as much as ice (see Table 1). Figure 3 shows how this new feature can be incorporated into our Granny model. If it is imagined that Granny’s pet dog has sat in front of the fire, it will block some of the heat from the heater reaching Granny. In the Earth system, the presence of clouds

Fig. 1 The Granny model, part 1. Mean temperature of the Earth is around 10
C

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A big problem: clouds and ice From the Sun (100%) Scattered away by clouds (24%)

Scattered away by (ice) surface (6%)

Land surface

Ice

Water

30% of incoming solar radiation reflected back out to space without being absorbed (Earth’s Albedo A = 0.3)

Fig. 2 A problem with the Granny model, part 1

The Earth

“Clouds and ice”

The Sun

Fig. 3 The Granny model, part 2 (with clouds and ice). With clouds and ice mean temperature of the Earth 18
C

Table 1 Reflectivity of different types of surface with respect to incoming solar radiation

Surface type Fresh snow Dry sand Grass-type vegetation Needleleaf coniferous forest Broadleaf deciduous forest

Reflectivity (%) 90–95 35–45 15–25 10–20 5–10

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and ice would reduce the average surface temperature of the Earth to 18
C, very cold indeed, making the Earth uninhabitable. The average surface temperature of the Earth is much hotter, so there must be a compensatory mechanism. What could the Granny do? She could move the pet out of the way (water is essential to the Earth, and one would not want to remove clouds and ice – even if they could be removed). She could move closer to the heater (although the Earth’s orbit fluctuates, it cannot move close enough to the Sun to compensate; in any case, there are issues to do with evaporation of water and the formation of more cloud!). Finally, she could stay where she was and put on a blanket. The final option is what the Earth does; it puts on a blanket (greenhouse gases) to compensate for the loss of heat caused by clouds and ice. For Fig. 4, the audience is asked to imagine that they are in space looking at the Earth and observing the heat being released from the surface of the Earth (in the infrared region). The figure clearly shows that not all of that heat escapes to space but that some is trapped by greenhouse gases in the atmosphere, such as carbon dioxide, ozone, and methane (CO2, O3, and CH4), and that these act as a blanket around the Earth (or around the Granny). Figure 5 now completes the Granny model where she has a blanket to offset the heat lost. The combination of these two effects (the Earth’s albedo leading to cooling and the greenhouse gases leading to a warming) cancels out, ending up with an average surface temperature of about 16
C. Hence, greenhouse gases are essential to

Wavelength (µm) 25

20

15

10

9

8

7

Radia CE (mW m−2 sr−1 cm)

320 K 150

H2O

IRIS Spectrum (Sahara)

300 K Atmospheric Window

100

CO2

280 K

O3

260 K 50

240 K

CH4

220 K

0 400

H2O

1,000

1,500

Wave number (cm −1)

Fig. 4 Spectrum showing the outgoing infrared radiation from the Earth and the parts of the spectrum that are absorbed by greenhouse gases in the Earth’s atmosphere

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Fig. 5 Granny model, part 3 (clouds, ice, and greenhouse gases). With clouds and ice and greenhouse gases, the mean temperature of the Earth 16
C

the Earth system. A PowerPoint of this model is available for download from the Bristol ChemLabS outreach website at http://www.chemlabs.bristol.ac.uk/outreach/ resources/Atmos.html.

The Granny Model: The Underpinning Mathematics A First Attempt to Model the Climate The simplest model of the climate is one where incoming solar energy and outgoing terrestrial energy emitted from the planet are equal, that is, an “energy in equals energy out” model or a balanced flux model. Throughout this section, it refers to energy; however, tacitly this means energy flux, that is, energy per second. It is known from measurements that the energy from the Sun reaching the top of the atmosphere, termed the solar constant S, is 1,370 W m2. If it is assumed that the radius of a perfectly spherical Earth is RE, it can be seen that the Earth absorbs solar radiation over an area πR2E (i.e., a flat disk of atmosphere) but emits energy from an area 4πR2E (i.e., from the entire surface), as illustrated in Fig. 6a, b. If an energy analysis is now carried out and it is assumed that energy in and energy out are the same, it is possible to arrive at the following: Energy in ¼ Eneregy out

(1)

Energy per unit area per unit time  total area ðdiscÞ ¼ Energy per unit area  total surface area ðsphereÞ

(2)

1370  πR2E ¼ σT 4E  4πR2E

(3)

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a

Area of Earth normal to Solar radiation S = pRE2

Surface area of Earth = 4pRE2

Solar flux, per unit area, S

b

1370 W m−2 Cross-section = pR 2

Surface area = 4pR 2

Fig. 6 (a) A schematic of a balanced flux model for the Earth. (b) A simplified version of the schematic of a balanced flux model for the Earth

Rearranging Eq. 3 yields an expression for the surface temperature of the Earth: T 2E ¼

1370 4  5:67  108

T E ¼ 279 Kð6
CÞ

(4) (5)

First, it should be noted that the σTE4 comes from the Stefan-Boltzmann law. All bodies radiate energy as electromagnetic radiation. A blackbody absorbs all radiation falling on it and emits that radiation as a function of its surface temperature, where that flux of energy radiated is equal to σT4; here σ is the Stefan-Boltzmann constant, 5.67  108 W m2 K4, and T is the surface temperature of the body in Kelvin. Second, a first glance at the result in Eq. 5 looks like a sensible figure for the average surface temperature of the Earth, maybe a little too cold. The problem with this very simple model is that some energy is reflected back out to space by clouds and ice without being absorbed. Approximately 24 % of the incoming energy is reflected by clouds, and another 6 % is reflected by the surface, for example, ice. This gives a total albedo (A) for the Earth of 30 % or 0.3. Therefore, the left-hand side of Eq. 4 must now be rewritten as 0.7  1,370  πRE2, and the calculation of TE becomes

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1370  0:7 4  5:67  108

(6)

T E ¼ 255 Kð18
CÞ

(7)

T 4E ¼

This new value for the average surface temperature in Eq. 8 is obviously far too low and leads naturally to the question: “Why is the Earth so warm?” In order to answer this question, a slightly more complex model is needed.

A One-Layer Atmosphere Model If it is assumed that the atmosphere is made up of a single layer of miscible gases, a more accurate model can be constructed that can be used by students using a spreadsheet. In this model, allowances are made for absorption by the atmosphere of the incoming visible light from the Sun and absorption of the outgoing infrared light emitted from the Earth. Figure 7 summarizes the elements of the model. FS is the solar constant divided by 4; hence, the incoming energy from the Sun is FS(1  A), where A is the albedo, that is, removing that portion reflected back to space. This incoming energy is in the UV and visible region. τVIS is the fraction of this incoming energy that is transmitted through the atmosphere, that is, if the atmosphere absorbs it, all τVIS is zero, if the atmosphere absorbs none of it, τVIS is equal to 1. Hence, the energy reaching the surface of the planet is FS(1  A)  τVIS. The Earth will act as a blackbody and will emit the energy denoted as Fg, from the surface of the Earth. This terrestrial radiation is centered in the infrared region of the spectrum. τIR is the fraction of infrared energy transmitted through the atmosphere, being zero if the atmosphere absorbs all of it and unity if the atmosphere absorbs none of it. Certain gases in the atmosphere do indeed absorb the infrared energy (greenhouse gases), and so outgoing energy is Fg  τIR. Fg × t IR

Fs(1−A) Fa Atmosphere t VIS

Fs(1−A) × t VIS

Ground

Fig. 7 Schematic of a one-layer atmosphere

t IR

Fa

Fg

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Assuming that the energy from the atmosphere is denoted as Fa and that the energy in and out at the surface of the Earth and the top of the atmosphere are both balanced, then: At the surface of the Earth, FS ð1  AÞτVIS þ Fa ¼ Fg

(8)

And at the top of the atmosphere, Fg τIR þ Fa ¼ FS ð1  AÞ

(9)

Combining Eqs. 8 and 9, Fg ¼

FS ð1  AÞð1 þ τVISÞ ð1 þ τIRÞ

(10)

Finally, noting the Stefan-Boltzmann law once again, Fg can be expressed as Fg ¼ σT 4E ¼

FS ð1  AÞð1 þ τVISÞ ð1 þ τIRÞ

(11)

Equation 11 can be rearranged to make TE the subject:  TE ¼

 FS ð1  AÞð1 þ τVISÞ 0:25 σð1 þ τIRÞ

(12)

Assuming that FS = 342.5 W m2 (solar constant divided by 4) and that τVIS = 0.8 and τIR = 0.1, then TE = 288.5 K (15.5
C). It is Eq. 12 that can be put into a package such as Microsoft Excel so that students may see the effects of changes in global temperature when parameters are changed.

A One-Layer Atmosphere Model Simulation Further example output is shown in Table 2. In experiment 1, it is assumed that the atmosphere does not absorb any of the incoming or outgoing energy fluxes and the albedo is 0.3, giving a temperature of 254 K. If there are no clouds or ice (A = 0.0), the Earth then warms up in experiment 2–278 K, showing the importance of albedo. From experiment 2–3, the atmosphere now absorbs all the outgoing infrared radiation, and the Earth warms to 330 K. If clouds and ice are now introduced in experiment 4, the temperature drops to 302 K. These four factors, FS, A, τVIS, and τIR, play a vital role in determining the surface temperature of the Earth, and students can investigate this for themselves. These models have been very popular with teachers and their students at secondary school in the UK and are beginning to be used in other countries.

Climate Change: Outreaching to School Students and Teachers Table 2 Output from the one-layer atmosphere model

Experiment Variables FS/W m2 A τVIS τIR TE/K TE/
C

1 342.5 0.3 1.0 1.0 254 19

2 342.5 0.0 1.0 1.0 278 5

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3 342.5 0.0 1.0 0.0 330 57

4 342.5 0.3 1.0 0.0 302 29

Typical questions that could be asked that would require the students to use this model are: 1. Which of the variables has the greatest effect on average global temperature? This is a somewhat open-ended question; one would first assume that the solar constant is the most important. However, if A approaches 1, that is, the Earth’s surface becomes very reflective, covered in ice like the snowball Earth (see section “A One-Layer Atmosphere Model: Taking the Investigation Much Further”), then the temperature plummets. 2. What would happen to the surface temperature if the ice caps melted? This question is asking the student to reduce A by approximately 6 %. It is quite surprising how much the temperature rises with modest reductions to the Earth’s albedo. 3. If the average distance from the Earth to the Sun was increased by 1 % of the current value, what would the temperature be assuming albedo is 0.3, τIR = 0.3, and τVIS = 0.6? This question opens up the importance of the solar constant and how small fluctuations in the Sun’s energy (e.g., solar flares or sunspots) can affect surface temperature. Indeed, students can explore what would happen to the Earth’s surface temperature if the Earth moved closer to the Sun or further away from it. As a simple approximation, one can assume that the Sun’s energy is evenly spread over the surface of a sphere. Therefore, for simplicity it can be stated that the solar constant scales with 1/R2, so the solar constant S = 1,370/R2, where R = 1 is defined as the distance from the Sun to the Earth at present. Therefore, if the distance from the Sun to the Earth is halved (just a bit further than Mercury is from the Sun), the solar constant increases by a factor of 4, and if the distance from the Sun to the Earth is quintupled (increased by a factor of 5 bringing the Earth slightly closer to the Sun than Jupiter), then S is reduced by a factor of 25 (see section “A One-Layer Atmosphere Model: Taking the Investigation Much Further”).

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Of course, far more challenging questions could be asked, for example: 1. The sand in the Sahara desert can be made into a glass mirror. If a perfectly reflecting mirror is put at the Earth’s surface in the Sahara desert, it could reflect back incoming solar radiation and cool the planet. 2. How big would the mirror have to be in order to cool the planet by 1
C? 3. What fraction of the Sahara desert would that be?

A One-Layer Atmosphere Model: Taking the Investigation Much Further The one-layer atmosphere model opens us the possibility to investigate a myriad of interesting and more complex systems, and some of these are given here and tie in very well with current topics being presented at school level.

Surface Temperatures on Other Planets The one-layer atmosphere model can be used to estimate the surface temperature on other planets. For simplicity, in the first instance, it can be assumed that the planet’s atmosphere does not interact with energy entering or leaving the planet (τVIS and τIR are equal to 1) and that the planet’s albedo is zero (nonreflecting). Using the approximation developed in question 3 from the previous section, S(R) = 1,370/R2, it is then possible to work out the temperatures. Data for the relative distances are collected in Table 3, and from this an estimate of the surface temperature of each planet is then given and compared with actual measurements. It should be noted that these actual measurements are averages and should not be taken as the exact number. Table 3 Estimates of the surface temperature of other planets in the solar system using the one-layer atmosphere model

Planet Mercury Venus Earth Mars Jupiter Saturn Uranus Neptune a

D, Distance to Sun/millions of miles 36 67 93 142 484 891 1,790 2,800

D/ DEarth 0.4 0.7 1.0 1.5 5.2 9.6 19.2 30.1

S W m2 8,562 2,796 1,370 609 51 15 4 1.5

T K 441 333 278 228 122 90 65 51

T
C 168 60 5 45 151 183 208 222

T actuala
C 167 457 10 46 153 184 197 223

Actual temperatures are taken fromhttp://wiki.answers.com/Q/What_is_the_surface_temperature_ on_the_planets and http://theanswermachine.tripod.com/id2.html. Accessed 31 Aug 2010). Note that S = 1,370/(D/D Earth)2 and T = {S/(4σ)}0.25 (in Kelvin)

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However, the first point is that the agreement is stunning apart from one planet, Venus. The surface temperature of Venus is much hotter than predicted. Why is this? It turns out that a runaway greenhouse effect has taken place and not even decreasing τIR to zero can reproduce the very hot temperature experienced (further modifications are required). The atmosphere of Venus is around 96 % CO2, and the subsequent trapping of infrared radiation has caused the planet to experience much higher surface temperatures than predicted simply by its distance from the Sun.

Snowball Earth Through geological evidence, it has been proposed that some 650 million years ago, the Earth was nearly completely covered in ice (see Hoffman et al. 1998). Such a snowball Earth is believed to have preceded the Cambrian explosion of life on Earth. Evidence for this comes from the fact that there are glacial deposits near the equator, and magnetic measurements also support this. In order for there to be glacial deposits in the tropics, there needs to be ice. Using the one-layer model, it is possible to investigate what would happen to surface temperature as the albedo (or amount of ice) increases. Taking τVIS and τIR to be equal to 1 for simplicity, it is then possible to calculate the effect on temperature as A is increased, that is, A = 0, T = 278 K, A = 0.5, T = 234 K, A = 0.75, T = 197 K, A = 0.9, and T = 156 K. It soon emerges that the model diverges from linearity and as A approaches zero the temperature plummets. To raise the temperature again, it is believed that greenhouse gases (CO2 and CH4) eventually rose to a level where the temperature started to rise again and ice melted causing a feedback on warming.

Global Dimming It is a well-known phenomenon that one of the reasons that the Earth’s surface temperature has not increased over the last 50 years as dramatically as originally predicted, even though greenhouse gas levels have increased significantly, is because of a process known as global dimming. In the process of burning fossil fuels, particulate matter is also released as well as water. It has been shown that the energy from the Sun reaching the Earth’s surface has decreased since the 1950s by around 5 % (see Wild et al. 2005) and is believed to be caused by the addition of particles that increase the albedo of the Earth. The one-layer model can be used to investigate this impact by increasing the albedo (similar to snowball Earth in fact) of the Earth, where increasing A from 0.3 to 0.31, for example, cools the surface temperature by 1
C, in keeping with the global dimming hypothesis. Indeed, the role of aerosols and volcanic eruptions (which inject sulfur-rich species into the atmosphere and lead to more cloud cover) can all be investigated using this model, all leading to a cooling.

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Stratospheric Ozone Depletion and Climate Change A topic that is often confused is the relationship between stratospheric ozone and climate. Ozone (O3) is formed in the stratosphere, a region of the atmosphere between about 10 and 50 km in altitude. Its location arises because of the balance between the need for high-energy photons of light (UVC radiation) found in greater abundance the higher in altitude one goes and high pressures which decrease dramatically with increasing altitude. The reactions governing the formation of ozone are those derived by Chapman in the 1930s and are known as the Chapman mechanism and are summarized in reactions (Eqs. 13, 14, 15, and 16). O2 þ hν ! O þ O  200 nm

(13)

O þ O2 þ M ! O3 þ M

(14)

O3 þ hν ! O þ O2  250 nm

(15)

O þ O3 ! O2 þ O2

(16)

O2 absorbs a photon of vacuum UV light (around 200 nm) and dissociates to form two O atoms in reaction (Eq. 13). The O atoms can add to O2 in the atmosphere to form O3, ozone, but need to have a relatively high pressure, denoted by M, so that the newly formed molecule can be stabilized. Since Eq. 13 is most efficient at the top of the atmosphere and Eq. 14 is most efficient at the bottom of the atmosphere, it is not surprising that somewhere in the middle the amount of ozone made is at a maximum, hence the location of the stratosphere. Ozone itself absorbs high-energy vacuum UV (around 250 nm), shown in reaction (Eq. 15). There are two important consequences of the ozone layer in the stratosphere. First, between O2 and O3, they filter out all the UVC radiation (200–280 nm) from the atmosphere which would cause life on the surface of the Earth to be severely compromised if it were not removed. Second, reaction (Eq. 15) gives out a lot of heat; hence, the stratosphere is a warm layer relative to the top of the troposphere (the layer of the atmosphere from 0 to 10 km approximately). This warm layer moderates the weather in the layer below and has other beneficial dynamical effects. The τVIS term relates directly to the absorption of the Sun’s energy by O3 and O2. The one-layer model shows what would happen to the surface temperature if there was no ozone layer (e.g., A = 0, τVIS = 1, and τIR = 1) returning a value for T = 278 K, with an ozone layer (A = 0, τVIS = 0.8, and τIR = 1) T = 271 K, that is, a cooling of about 7 K or 7
C. Taking this further, it was discovered by Nobel Prize winner Paul Crutzen and others in the 1970s that the natural catalytic cycles reduce the amount of ozone in the stratosphere. These cycles arise from H2O, CH4, and N2O being present in the atmosphere through natural cycles. If there was more ozone, that is, no natural removal processes, then τVIS = 0.7 may be a more reasonable number (T = 267 K), and the drop in surface temperature would be an additional 4
C. Some may suggest that such a warming caused by gases released by biological processes occurring at the Earth’s surface proposes a Gaia-type link, yet another interesting avenue for class discussion.

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The destruction of stratospheric ozone will, of course, increase τVIS from 0.8 toward 1.0 and will lead to a warming of the surface. However, ozone is itself a greenhouse gas, and so by removing it, the amount of τIR transmitted would increase, that is, a cooling. So there is now an interesting balance to investigate, but this is not the end of the story. The species that have been responsible for polar stratospheric ozone depletion, the chlorofluorocarbons (CFCs) such as CFCl3 and CF2Cl2, are also greenhouse gases (reducing τIR). So ozone is removed, which both cools and warms the planet, and in addition, the CFCs also warm the planet. These CFCs are in fact very potent greenhouse gases and absorb IR in the region known as the atmospheric window (see Fig. 4), a region of the spectrum where IR largely escapes to space.

Milankovitch Cycles and Ice Ages Over the last 450,000 years, the Earth’s climate has undergone four ice ages (glacial periods) where temperatures have been about 10
C colder than they are today. During the ice age, large parts of the Earth were covered in ice. At the end of every ice age, there is a sudden rise in temperature (scientists are still trying to understand exactly why), and the Earth goes into a period known as an interglacial. This cycle of glacial and interglacial occurs on a timescale of about 100,000 years. Figure 8 shows this variation in temperature and comes from ice core data taken from Antarctica. What causes ice ages? 800 CH4(g)

400 Temperature deviation (°C)

CO2(g) 200

5 88 kyr

85 kyr

108 kyr

122 kyr

0 0

CH4(g) (ppbv) and CO2(g) (ppmv)

600

−5 −10

Temperature 450

375

300 225 150 Thousands of years before present

75

0

Fig. 8 Data taken from the Vostok ice core showing the changes in surface temperature and levels of CO2 and CH4 over the last 450,000 years

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Milankovitch Cycles Climate shifts correspond to three cycles related to Earth’s orbit around the Sun that affect the intensity of solar heating (heat from the Sun). The discovery of these cycles is attributed to Milutin Milankovitch. These shifts are caused by gravitational attraction between the planets (mainly Jupiter) and Earth. Eccentricity of Earth’s orbit (see Fig. 9a) varies from nearly circular to elliptical. At low-eccentricity orbits, the average Earth-Sun distance is less, but when the Earth is in a more elliptical phase, the Earth-Sun distance is greater, and the heat from the Sun per unit area is less and leads to the onset of an ice age. This can be modeled by reducing S as the Earth-Sun distance increases. The timescale of this is about 100,000 years. Axial tilt or obliquity of the Earth’s axis of rotation (see Fig. 9b) changes from about 22
(currently 23.5
) to 24.5
and has a timescale of about 41,000 years. As the tilt increases, it changes the heat that reaches various parts of the Earth’s surface. Precession (wobble) changes the quantity of incident radiation (heating) arriving at each latitude during a season and has a timescale of about 22,000 years. These orbital cycles explain qualitatively why the Earth experiences ice ages (glacials) and interglacials. In Fig. 8, it can also be seen that two important greenhouse gases in the atmosphere, CO2 and CH4, also rise and fall with temperature. The reason for their fall as the Earth enters an ice age is because the surface of the Earth is being covered in more ice and this reduces the flux of CH4 to the atmosphere from natural systems such as wetlands and animals and CO2 from respiration. Using the one-layer model and increasing A (more ice) and increasing τIR (decreasing levels of greenhouse gases) from a base case will lead to a cooling, in agreement with observations. Therefore, past climates can also be investigated and explained by this model.

Present-Day Climate There are many diagrams on the Internet and elsewhere that show how the surface temperature of the Earth has changed over the last 200 years. One thing is clear: Figure 8 shows that over the last 450,000 years, the level of CO2 varied between about 170 and 280 ppm; today the level is around 400 ppm. Also during this period, CH4 varied between about 350 and 700 ppb and is now around 1,750 ppb. Such a rise over the last 200 years has been conclusively shown to be due to the burning of fossil fuels. Evidence for this is interpreted from the carbon isotope ratio present in the sample. The one-layer model would suggest that such a rise in greenhouse gas levels should lead to a rise of about 1–3
C in temperature. Part of the reason why the rise has not been on the high side is due to global dimming, mentioned earlier (see section “Stratospheric Ozone Depletion and Climate Change”). The point is that there should be no debate about warming due to increased levels of greenhouse gases; the debate should be how large the increase will be and how quickly it takes place. Data from present-day studies will be discussed in section “Impact and Assessment.”

Climate Change: Outreaching to School Students and Teachers

a

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Eccentricity Less elliptical

More elliptical

Orbit Periodicity: 100,000 YEARS Axial tilt Axis

Axis

b

21.5

24.5

Equator

Equator

Radiation

Periodicity: 41,000 Years

c

Precession 1.Now 23.5 Summer

Winter

2. In c. 5,250 years

Summer

Equator

3. In c. 10,500 years Periodicity: c. 23,000 Years

Summer

Winter

Winter

Fig. 9 (a) Eccentricity of the Earth’s orbit around the Sun has a period of ca. 100,000 years. (b) Axial tilt of the Earth relative to the Sun has a period of ca. 41,000 years. (c) Precession of the Earth has a period of ca. 23,000 years

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A Simple Mathematical Model That Can Be Used to Predict the Atmospheric Level of Greenhouse Chemicals Given Their Lifetime and Emission Rate The following mathematical model should allow more able students and their teachers to make some more advanced predictions on the levels of greenhouse chemicals as a function of time given their emission rate and lifetime. Many scenarios can be explored to determine emission levels required to achieve a variety of equilibrium concentrations. There is myriad of “greenhouse gases” in the Earth’s atmosphere, i.e., many species can absorb infrared radiation over the wavelengths being emitted by the Earth. The most well known are CO2, CH4, and N2O, but chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs), and in particular the hydrofluorocarbons (HFCs) also play a role. A fundamental concept in atmospheric science that is required is the budget of a compound. Put simply we consider the sources of the compound and the loss processes (“sinks”) for the compound. If the sources and sinks of a compound balance, it will lead to a constant concentration being observed in the atmosphere. If sources are greater than sinks, then the concentration of that compound in the atmosphere will increase with time and vice versa. However, can we be more quantitative? If the budget is balanced, what will the constant concentration be and what controls this parameter? It turns out (see appendix for derivation) that the concentration of a compound A at time t, [A]t, is ½At ¼ E=R 1  expðRtÞ

(17)

where E is the source or emission rate and R is the loss rate (units s1). We can use the concept of lifetime τ, which is simply the reciprocal of R (1/R), to rewrite Eq. 17: ½At ¼ τEð1  expðt=τÞÞ

(18)

When sufficient time has elapsed, i.e., when an equilibrium has been established, a constant concentration of A, [A]constant, is reached and is equal to E/R or τE. If the emission rate E increases, a new [A]constant is established which is bigger than before; if the emission rate decreases, the new [A]constant is now smaller. If R, the loss rate, increases, [A]constant decreases. If the loss rate decreases, [A]constant increases. Hence, the concentration of any compound, whether it is carbon dioxide, ozone, methane, nitrogen oxides, chlorofluorocarbons, etc., in the atmosphere is determined simply by E and R or E and τ. The overall impact will be a sum of the individual compound impacts. Using the main greenhouse gas carbon dioxide (CO2) as an example, we can imagine that there are natural processes, not involving human (anthropogenic) activity, releasing carbon dioxide (CO2) into the atmosphere (respiration, aerobic decomposition of organic materials, natural forest fires, volcanic activity) and that

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that CO2 is taken up by plants via photosynthesis and in the oceans first as dissolution and then into the lengthier precipitation processes to form carbonate rock. This natural system leads to an equilibrium, and at that point the level of CO2 is equal to a baseline concentration, [CO2]baseline. If there is now a constant emission of CO2 arising from human activity (Ehuman), it will lead eventually to a new, higherlevel [CO2]perturbed which is larger than the baseline. This new-level [CO2]perturbed is equal to ½CO2 perturbed ¼ ½CO2 baseline þ Eτ

(19)

Current data, based on measurements in ice cores of trapped air deposited with preindustrial levels (before 1800) of CO2, show that [CO2]baseline 280 ppm and that human activity is releasing about 8 ppm per year of CO2 into the atmosphere (6.5 ppm due to fossil fuel combustion and cement production, etc., and 1.5 ppm through deforestation) and that about half of this stays in the atmosphere (the rest taken up by natural sinks within the lowest part of the troposphere by surface contact processes such as photosynthesis), so the annual emission of CO2, Ehuman, is about 4 ppm per year. If we assume a lifetime of CO2 in the whole of the atmosphere of ~100 years, the new CO2 level will be ½CO2 perturbed ¼ ½CO2 baseline þ Ehuman τ ¼ 280 þ 4  100 ¼ 680 ppm It should be noted that the natural sinks for carbon dioxide are within the boundary layer within the troposphere. If carbon dioxide were to be contained into the bottom 1–2 km of the troposphere, the lifetime of the CO2 would be in the order of 4 years. Apart from a small reduction in carbon dioxide due to being dissolved out in rainfall at higher altitudes within the troposphere, there are no sinks for carbon dioxide above the boundary layer (approximately lowest 2 km). The carbon dioxide at high levels needs to be circulated through the boundary layer to be removed. This explains the difference in lifetime. How long will it take to achieve the new equilibrium level? ½CO2 t ¼ ½CO2 baseline þ τEhuman ð1  expðt=τÞÞ

(20)

We can plot Eq. 20 as a function of time (Fig. 10) which shows that the time taken is between 200 and 300 years. However, the emission rate, E, of CO2 is predicted to increase over the next 50 years if no action is taken, and hence the level of 680 ppm would be reached more quickly as a result. It should be noted that CO2 is the dominant greenhouse gas (not including H2O) at the time of writing; although gases such as methane (21 times more potent) and nitrous oxide (290 times more potent) are much better at absorbing infrared radiation than CO2 on a molecule per molecule basis, their rise in concentration is 2.5  104 that of CO2, and so their contribution is small but not insignificant to infrared radiation trapping.

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800 Concentration of CO2 /ppm

700 600 500 400 300 200 100 0

0

200

400

600 Time /years

800

1000

1200

Fig. 10 Graph of concentration of carbon dioxide (ppm) against time (years)

What would emissions have to change by to reduce [CO2]perturbed to 500 ppm? ½CO2 perturbed ¼ 500 ppm ¼ ½CO2 baseline þ Ehuman τ ¼ 280 þ E  100 220 ¼ 100Ehuman 2:2 ¼ Ehuman This amounts to a 45 % reduction in current emission rates.

Simple Mathematical Climate Model to Investigate the Role of the Oceans in Slowing Climate Change The question of the impact of the oceans in taking up excess carbon dioxide from the atmosphere and the timescales involved is often queried. This simple model will allow exploration of these ideas. Mass of ocean ¼ 1:3  1021 kg Heat capacity of water  4 Jg1 K1 Heat capacity of the ocean ¼ 5:2  1024 JK1 The heat capacity of the ocean is approximately 1,000 times that of the atmosphere, and so it can absorb excess thermal energy from the atmosphere. If we imagine that since the year 1800 the increase in greenhouse gases has caused a rise in heating of ~1 Wm2 (so-called radiative forcing) (http://www.ipcc. ch/), the total energy flux increase ΔEf is

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ΔEf ¼ 1½Wm2   4πR2E ðsurface area of the Earth where RE is the radiusÞ
2 ΔEf ¼ 4π 6:3781  106 W ΔEf  5  1014 W The time taken for this energy flux to cause a rise in temperature of 1 K in the atmosphere can now be calculated since energy (J) over power (watts) is time (seconds): Timeatmosphere ¼ 5  1021 =5  1014 ¼ 1  107 s  116 days However, the time taken for this energy flux to cause a rise in temperature of 1 K in the ocean is Timeocean ¼ 5:2  1024 =5  1014 ¼ 1:04  1010 s  330 years Hence, the timescales for climate change are driven by the ocean’s thermal mass. It should be noted that this does not mean that temperature will not rise, but does mean that the timescale will be longer.

Climateprediction.net: Taking Part in Climate Simulations Climateprediction.net is self-billed as “the world’s largest climate forecasting experiment for the twenty-first century.” It does this by recruiting help from people around the world who can offer time on their computers when their computers are switched on but are not being used to their full capacity. This is an example of citizen science that school students may wish to engage with. The full climate model has many parameters that can be adjusted; to explore all of these parameters, an extremely large number of simulations must be performed. Even with the computer resources available to the climateprediction.net team, such an ensemble of simulations would take a very long time. The idea behind climateprediction.net is that anyone can download a version of the model that will explore one of these particular parameters from a group of preset scenarios. The model will take about 3 months to run in the background while one works, without compromising the speed of the computer. Calculations are performed in three parts. The first part runs calculations using data from the years 1850 to 1900, checking the resulting predictions against temperature records: this is known as the calibration run. The second part runs a simulation from 1901 to 2000. The third stage then runs a simulation of the future climate (2000–2100) with one parameter changed, for example, the sensitivity of climate to uncertainties in the sulfur cycle. Once the calculations are complete, the data is automatically uploaded to the UK’s Meteorological (Met) Office the next time the computer is online. The interface software which is provided free of charge with the simulation gives the computer user a graph of the changes to the climate, as they are calculated. Temperature variations by season with latitude, longitude, and

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altitude are just some of the variables that can be visualized. Such features can enable a cross-curricular school project linking geography and the physical sciences. The climateprediction.net web site also offers information and resources specifically for schools (http://www.climateprediction.net/education/). By August 2010, the project has run 74,842,477 model years and has 43,691 active hosts running the different simulations. In 2014, alone volunteers donated nearly 7,500 years of computing time completing half a million successful simulations. A set of current experiments may be found at the project web site as will details of how to get involved. How does the simple model compare with more sophisticated models such as the Hadley Centre climate model used by the UK’s Met Office? In fact, the two models are very similar, except that the Hadley Centre model does not consider the atmosphere as one layer but splits it into a number of boxes based on altitude, latitude, and longitude. For each box, the model directly calculates the amount of incoming UV/visible radiation transmitted and scattered within that box and the amount of outgoing infrared radiation transmitted by that box, based on the concentrations of key greenhouse gases and the surface area of cloud and ice. The most sophisticated versions of the Hadley Centre model also consider the heat flux into and out of the ocean and the uptake of CO2 by vegetation. If the principles of the one-layer model are understood, comprehending the more complicated climate models is possible.

Writing Articles for School Students and Their Teachers There are many publications, specialists, or otherwise that report new science to the general public, for example, New Scientist. There are also many publications that are aimed specifically at school students and their teachers. In Europe, examples include Science in School (http://www.scienceinschool.org/ last accessed February 21, 2015), Physics Education run by the Institute of Physics (http://iopscience.iop. org/0031-9120/ last accessed February 21, 2015), and Chemistry Review (http:// www.york.ac.uk/chemistry/schools/chemrev/ last accessed February 21, 2015). In Brazil, the Ciência para Todos/ Science for All blogsite (http://www.ccell11.com/ last accessed February 21, 2015) aims to do this in Portuguese, Spanish, and English. Ideally, one would want cutting-edge research reported in a way that can be understood by the school community and indeed the general public. To do this effectively, articles should take into consideration the language and terminology that students are familiar with (Tuah et al. 2009); ideally then, the articles should be written by an expert in the field with the help of a practicing school teacher (Harrison et al. 2006; Shallcross and Harrison 2009). In 2005, at the School of Chemistry at the University of Bristol, the first ever full-time School Teacher Fellow (Shallcross and Harrison 2007a, b) position was established. Here an experienced secondary school science teacher was permanently seconded to work with the School of Chemistry, and one of the many things that took place was a rapid increase in the production of articles for a school audience. In concert with the School Teacher Fellow, researchers in the department have been encouraged to write such articles, and a number of

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articles on aspects of climate change have also been written (Shallcross and Harrison 2007c, 2008a, b; Shallcross et al. 2009a, b). Elements of these articles focusing on practical and hands-on tools for education in climate science are given in the next section.

Practical and Hands-on Activities A Climate Change Lecture Demonstration: A Pollutant’s Tale One method of effectively engaging with large numbers of the public on aspects of atmospheric chemistry and climate change is through a lecture demonstration. A lecture demonstration is different to a “chemistry magic show” because the experimental demonstrations chosen are used to illustrate the chemistry being discussed and are not just there for the “wow” factor. The “wow factor” is there in that some of the demonstrations are spectacular, but their use in telling the climate story is their primary value. The secondary aims are tied up with the promotion of chemistry and the “edutainment” value of the talk. One such portfolio of talks was created by the authors entitled “A Pollutant’s Tale” together with its version aimed at primary school students “Gases in the Air.” These have been performed in excess of 1,400 times in an 8-year period to a total audience of over 225,000 in twenty countries from China to New Zealand to South Africa to the USA and Europe (2006–2014). The several versions of the talk aimed at secondary school students and the wider public all contain the same experiments but the depth to which the explanations are given are age/prior knowledge appropriate. Some of the demonstrations used double-up to reinforce areas of knowledge required by the school curriculum. The talk is best given by two people but can be given by a suitably dexterous and informed individual. It needs 30 min setting up time and 20 min clear-up and can last from 50 to 80 min depending on the audience. The basic lecture demonstration is also now being given by other groups. The lecture demonstration begins with a comparison of the Earth’s atmosphere with the atmospheres of other planets in our solar system (Table 4). The gas giants being predominantly composed of hydrogen and helium give the excuse to set fire to balloons of these gases to reinforce knowledge of the chemistry of these gases and to start the lecture off with a bang. The chemistry of the gases in the Earth’s atmosphere is next with experiments looking at liquid nitrogen and the production of oxygen via Table 4 Three most abundant gases in each planetary atmosphere

Neptune Uranus Saturn Jupiter Mars Venus Earth

H2 (80 %) H2 (82 %) H2 (96 %) H2 (93 %) CO2 (95 %) CO2 (96 %) N2 (78 %)

He (19 %) He (15 %) He (3 %) He (7 %) N2 (2.7 %) N2 (3.5 %) O2 (21 %)

CH4 (1–2 %) CH4 (2.3 %) CH4 (0.45 %) CH4 (0.3 %) Ar (1.6 %) SO2 (0.015 %) Ar (0.93 %)

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the elephant’s toothpaste experiment (catalytic decomposition of hydrogen peroxide using potassium iodide). From here the audience is introduced to volatile organic compounds (VOCs), a term for which most audiences have no knowledge. The audience is invited to analyze several examples of VOCs, that is, samples of plant origin VOCs such as lime, coconut, vanillin, and lavender are given to the audience to smell, by dipping thick blotting paper strips into a solution of these fragrances. These “smell sticks” are color-coded with food dye so that several samples may be given out at the same time. Synthetic versions of historically animal-derived fragrances of “whale vomit” (ambergris) and civet (originally extracted from the anal gland of the civet cat and still smelling like it) are also used. The question is raised “Where do all these smells go?” This question leads onto the subject of combustion, incomplete combustion being demonstrated by the production and ignition of acetylene and complete combustion of methanol vapor in the “whoosh bottle experiment” (see section “Methanol Whoosh Bottle”). The true demise of the VOCs via free radical mechanisms is then given to appropriately experienced audiences. From here the talk goes onto other pollutants starting with nitrogen dioxide (see section “Nitrogen Dioxide Preparation”). The audience is taken through some research data on the nitrogen dioxide concentration in a city across a day, and its connectivity with photochemical smog is developed with audiences whose background knowledge is suitable. A major section of the talk then targets carbon dioxide with inspection of Bristol CO2 levels over a year’s data capture and then to the “Keeling CO2 curve” from Mauna Loa. A moment is taken to look at why Hawaii and also to get the audience to consider that studying science could get them to some very pleasant places to work! Two very basic demonstrations with dry ice (solid CO2) are performed, the inflation of rubber gloves showing that dry ice sublimes and also that carbon dioxide is soluble in water and will neutralize an alkaline solution becoming weakly acidic (see section “Solubility of CO2 in Water/Precipitation of Calcium Carbonate”). Three to five minutes are then taken to explain climate using the Granny model (see sections “The Granny Model: Basic Concepts” and “The Granny Model: The Underpinning Mathematics”). A graph of temperature data for the past 150 years is shown which then leads onto the computer modeling of the climate. This is done showing both natural forcings and human contributions and finally the sum of the two. The use of computer modeling to first be able to match the past events before it can be used to make predictions is discussed. The predictions on temperature and rainfall for the area of the world that the lecture demonstration is being delivered are then highlighted. The question “What can be done about it?” is then posed. A graph showing the carbon emissions by year from 1955 to 2055 is put up. The wedge of carbon needed to be removed to avoid the “business as usual” situation is highlighted, and the Pacala and Socolow (2004) stabilization wedge idea is explained. The take-home message then becomes that no one has to wait around for someone to invent ways of removing carbon. In fact, there are already 11 technologies that currently exist. If the social and political willpower were present employing these technologies, it would not only remove the projected carbon load but even reduce it below the current levels. It is very important to leave younger students with a positive message rather than one of

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“gloom and doom.” The final demonstrations, to end on a bang, are a reminder of the chemistry of helium and hydrogen (a fossil fuel replacement). One version of the PowerPoint of “A Pollutant’s Tale” may be downloaded from http://www.chemlabs. bristol.ac.uk/outreach/A-Pollutant-Tale.html, and Spanish and German translations are available from the same webpage.

Demonstrations and Experiments That Can Be Done in School to Augment Climate Change Education There are a number of chemicals that are important to consider for climate change, either as contributors to climate (soot and carbon dioxide formation), as alternative fuels (methanol and hydrogen), or as alternative energy sources. In this section, several classroom demonstrations and experiments to introduce these materials and describe how they can be used to enliven climate change lessons or lectures are presented. Safety note: Local rules and regulations on health and safety should be applied before trying these out. Always practice the experiments before presenting them in front of students, and the environment that the experiments are to be performed in should be taken into account.

Soot/Particulate Carbon Soot fits into the category of airborne particulate matter. Particles are considered hazardous when they are less than 5 μm in diameter, as they are not filtered out by the upper respiratory tract before entering the lungs. Black carbon will enhance global warming, but not all particles in the atmosphere do. It all depends on their optical properties: if the particles are very reflective, like a mirror (e.g., sea-salt particles), they can reflect incoming solar radiation back to space and decrease the radiation that reaches the Earth, causing a reduction in surface temperature. If they are dark, such as soot, they will absorb incoming and even outgoing radiation and enhance warming. Soot is a product of incomplete combustion of carbonaceous fuels, for example, in car motors, central heating, or power stations. There are a number of reactions that can produce soot. The simplest teacher demonstration is to burn small pieces of expanded polystyrene packaging, holding them with tongs over a heatproof mat. The yellow flame produced is very smoky, and the smoke contains black specks of carbon. However, this is not a suitable reaction for students to perform, as the polystyrene drips molten droplets of burning material; instead, the teacher should demonstrate this. Another teacher demonstration, that is a little more spectacular, is the combustion of glucose with an oxidizer. If 5 g of glucose powder is mixed with 5 g of potassium chlorate on a heatproof surface, it can be ignited by a few drops of concentrated sulfuric acid. The eruption of flame also produces a lot of gray smoke which can be discussed in terms of incomplete combustion (safety note: this experiment must not be made by students, as it is dangerous).

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Fig. 11 Addition of calcium carbide to water (with some washing-up liquid added) and then ignition of the resulting foam

If a class experiment to produce soot is needed, the combustion of freshly prepared acetylene (ethyne, C2H2) gas is an entertaining reaction (see Fig. 11). Take a 250 ml glass beaker, place it on a heatproof mat, and half fill the beaker with water. Add a good squirt of washing-up liquid (to trap the acetylene gas produced as a foam) to the water and also a few pieces of calcium carbide (CaC2). The reaction is immediate, liberating bubbles of acetylene. The teacher or student can then use a lit splint, taper, or match to ignite the foam. This burns dramatically with a yellow flame with smuts of carbon. CaC2 þ 2H2 O ! CaðOHÞ2 þ C2 H2

(21)

Solubility of CO2 in Water/Precipitation of Calcium Carbonate If dry ice is available, an interesting experiment can be performed to demonstrate the solubility of carbon dioxide in water. This can be used to introduce a discussion about the uptake of carbon dioxide (CO2) by the oceans as a possible mechanism for removing carbon dioxide from the atmosphere. For this very visually impressive reaction (see Fig. 12), add a handful of dry ice (take care to avoid cold temperature burns) to a large (1 l) beaker of water that has been made alkaline (pH = 12) with sodium hydroxide solution and to which a small volume of universal (pH) indicator has been added. Apart from the impressive condensation of water vapor, forming a cloud above the beaker, the formation of carbonic acid (a weak acid) causes a series of color changes to the indicator from purple through to orange (see Fig. 12). For a more impressive cloud, use hot water, as there is more water vapor to condense. The condensation is caused by very cold carbon dioxide gas produced when the dry ice

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Fig. 12 Tim Harrison and Dudley Shallcross with dry ice reacting in alkaline water

sublimes, using energy from the much hotter water. Some of the carbon dioxide dissolves in the water. A small piece of dry ice placed in limewater (calcium hydroxide solution, Ca(OH)2 ) (aq) can also be used to show the precipitation of carbon dioxide as calcium carbonate. The oceans of the world dissolve carbon dioxide gas and can precipitate calcium carbonate, which is used in shell construction by numerous creatures. The rate of dissolution is too slow to compensate for the increase in atmospheric carbon dioxide: If no dry ice is available, then a 2 l drink bottle could be filled with carbon dioxide gas, and about 30 cm3 of 2 mol dm3 sodium hydroxide can be added. Place the cap on the bottle and shake. The bottle should start to collapse as the carbon dioxide gas reacts with the sodium hydroxide, thus reducing the pressure inside the bottle. The solution forms exothermically so that it gets warm. This shows that carbon dioxide gas is acidic. This has implications for the change in the ocean’s pH as the high concentrations dissolve over time.

Methanol Whoosh Bottle Methanol is a biofuel, an alternative to fossil or nuclear fuels, and this experiment can be used to demonstrate its combustion. In addition to being a renewable fuel, methanol has the advantage over fossil fuels of not releasing “stored” carbon dioxide into the atmosphere; instead, it recycles carbon dioxide that is in the environment anyway.

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Fig. 13 Igniting the methanol “whoosh” bottle experiment

Methanol vapor (which is toxic) can be ignited inside an 18–20 l plastic water bottle of the type used in water dispensers. Note that after the experiment, the container will no longer be fit for its original purpose! Be warned some polymers used to make these containers may melt! Also the water bottle must be dry, as the tops of wet bottles tend to melt during the combustion! Pour around 20 ml of methanol (methyl alcohol, CH3OH) into a dry 20 l water bottle and shake to vaporize. The pressure of the vapor can be sensed by the hand held over the bottle’s mouth if the room is warm. Pour out the surplus liquid methanol. Put the bottle behind a transparent safety screen on the floor and away from any overhead heat, flame, flash sensors, or curtains. Put a lighted taper or long match to the mouth of the water bottle, holding it at arm’s length with fingers outstretched. A blue flame will erupt with a loud roar as the methanol vapor completely combusts (see Fig. 13). The experiment should not be repeated with the same container until it is dry again otherwise the methanol burns more slowly and the top of the container begins to melt! Using ethanol or methylated spirits is not recommended as more heat is generated and the container gets very hot. Some demonstrators use propan-2-ol as the fuel. Ethanol burns too hot to do this safely. Another dramatic demonstration of combustion uses 5 g of glucose mixed with 5 g of potassium chlorate on a heatproof mat. A few drops of concentrated sulfuric acid initiate the reaction between the powders which produces flame and smoke, as also mentioned above. This is a variant on the more well-known “screaming jelly baby” demonstration where a soft jelly sweet is quickly inserted into a clean boiling

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tube a quarter full of potassium chlorate which has been heated strongly until molten. In both cases, the potassium chlorate being an oxidizer can be thought of as releasing oxygen to allow the sugar to burn releasing energy as heat and light from the fuel/air mixture.

Hydrogen-Filled Balloons This teacher demonstration could be used to introduce hydrogen as an alternative fuel to replace fossil fuels and especially to raise the question of whether the combustion product is a greenhouse gas. One way to demonstrate that hydrogen is a fuel is to fill a balloon with hydrogen (from a cylinder) and tether it to a chair placed away from sensors and flammable materials (such as posters, blinds, or curtains) using a piece of thin string. Ignite the balloon using a lit taper or match, fastened to the end of a meter ruler or a long pole at arm’s length. Students should remain several meters away, as during the resultant explosion bits of the rubber balloon tend to fly in all directions. Those with sensitive hearing should place their hands over their ears. The flame and heat energy liberated are spectacular (see Fig. 14) and should lead to discussion of hydrogen’s suitability as a fuel. Fig. 14 Igniting a hydrogenfilled balloon

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The Reduction of Iron Oxide on a Match Head The use of blast furnaces in the iron and steel industries contributes to the atmospheric concentration of carbon dioxide. The crucial reaction, which reduces iron oxide to pure iron by means of carbon monoxide, is Fe2 O3ðsÞ þ 3COðgÞ ! 2 FeðsÞ þ 3CO2 ðgÞ

(22)

Students can mimic this reaction on the head of a match! Moisten an unlit match with water and roll into sodium carbonate (Na2CO3) powder, and then in iron oxide powder (Fe2O3), so that both stick to the match head. Use a second match to ignite the first and let it burn for a moment or two. Crunch the first match head onto a watch glass or Petri dish. Drag a magnet against the underside of the watch glass; the small particles of iron formed will be visible as they follow the magnet’s pull. Try this with the starting materials to show that no magnetic materials were initially present. The match provides both the energy for the reaction and the carbon monoxide as a reducing agent. The sodium carbonate acts as a flux material.

Alcohol Burners Unburned hydrocarbons enter the atmosphere and are oxidized by the hydroxyl radical (●OH) to form predominantly alcohols and carbonyls. Therefore, starting with an alcohol reduces the number of oxidation steps that must take place. Computer model simulations show that the concentration of ●OH in the atmosphere is increased when hydrocarbons are swapped for alcohols and carbonyls. Increasing the concentration of ●OH will increase the removal rate of greenhouse gases containing a C–H bond. It is also well known that the oxidation of alcohols leads to smaller production of secondary pollutants such as tropospheric ozone. Therefore, using alcohols has a positive effect on both air quality and the removal of greenhouse gases. Moreover, the smaller alcohols can be removed, to a small extent, by physical processes such as dry (taken up by a surface) and wet (rain, fogs, and aerosols) deposition, whereas their hydrocarbon counterparts cannot. Alcohol burners are the small burners made of glass (see Fig. 15), complete with a wick, which traditionally come with children’s chemistry sets and are readily available from school equipment companies. They can be used to determine the energy released in the combustion of shorter primary alcohols such as methanol, ethanol, propan-1-ol, butan-1-ol, and pentan-1-ol. The production of such fuels is a topic in its own right. Note it is too dangerous to use petrol or diesel in these burners.

Fuel Cells Fuel cells produce electricity from a reaction between a fuel such as an alcohol or hydrogen at the anode and an oxidizing agent such as oxygen or chlorine at the

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Fig. 15 Alcohol burner setup under a beaker to which a known volume of water is to be added

cathode. The fuel and the oxidizing agent react in the presence of an electrolyte. A fuel cell is different from a chemical battery because in fuel cells reactants can be replenished, whereas the chemicals being consumed in batteries are not, as they are sealed. A fuel cell will continue to work as long as its reactants are replaced. There are several demonstration fuel cells available for purchase to show the principle to students. In an alcohol/air fuel cell (see Fig. 16), the cell consists of two parts: an adapted plastic beaker with a conductive pad connected to a terminal (the anode) and an insert containing the catalyst. A defined volume of a source of alcohol (such as antifreeze) or of an alcohol itself (such as propan-1-ol) is mixed with 55 ml of alkali (such as sodium hydroxide) and put into the plastic beaker. The insert (colored red in the image) is put into the beaker to complete the cell. Air can pass through the insert into the alkaline alcohol mixture. The voltage produced by the fuel cell can easily be measured using a cheap multimeter/voltmeter.

Grätzel Cells Grätzel cells, also called “nanocrystalline dye solar cells” or “organic solar cells,” convert sunlight into electricity directly. Named after their inventor, Michael Grätzel, a Swiss engineer, the function of Grätzel cells is based on artificial photosynthesis using natural dyes found in cherries, blackberries, raspberries, and blackcurrants, among others. These purple-red dyes, known as anthocyanins, are very easy for school students to extract from fruits and leaves by simply boiling them up in a small volume of water and filtering.

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Fig. 16 Fuel cell using gin to generate electricity

These cells are very promising because they are made of low-cost materials and do not need elaborate apparatuses to manufacture. Although their conversion efficiency is less than that of the best thin-film cells, their price/performance ratio (kWh m2 annum1) is high enough to allow them to compete with fossil fuel electrical generation. Commercial applications, which were held up due to chemical stability problems, are now forecast in the European Union Photovoltaic Roadmap to be a potentially significant contributor to renewable electricity generation by 2020. Grätzel cells separate the two functions provided by silicon in a traditional cell design: normally, the silicon both acts as the source of photoelectrons and provides the electric field to separate the charges and create a current. In the Grätzel cell, the bulk of the semiconductor is used solely for charge transport, while the photoelectrons are provided from a separate photosensitive dye (the anthocyanin). Charge separation occurs at the surfaces between the dye, semiconductor, and electrolyte. The dye molecules are quite small (nanometer sized), so in order to capture a reasonable amount of the incoming light, the layer of dye molecules needs to be made fairly thick, much thicker than the molecules themselves. To address this problem, a nanomaterial is used as a scaffold to hold large numbers of the dye molecules in a 3D matrix, increasing the number of molecules for any given surface area of cell. In existing designs, this scaffolding is provided by the semiconductor material (titanium oxide), which serves double duty.

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Production of Biofuels from Vegetable Oils There are a number of ways of making biofuels from a range of vegetable oils, but the reaction is essentially the same. A biofuel is made by alkaline hydrolysis of the triglycerides in a vegetable oil and the following reesterification of the triglycerides to the methyl ester (a transesterification is done to obtain a less viscous fuel, which is termed biodiesel). In practice, both steps can take place in the same preparation, provided a mixture of methanol in alkali is used. This mixture contains the methoxide ion. During hydrolysis, a fatty acid is liberated from the triglyceride. Together with the methoxide ion, the methyl ester of the fatty acid is then formed. Glycerol (propan-1,2,3-triol) is a waste product of this last reaction. The disposal or use of the glycerol is one of the challenges for this growing industry. One can either use a large tube or a reflux method involving QuickfitTM laboratory glassware. If using a reflux for the reaction, the biofuel can be separated from the glycerol by solvent extraction. If the experiment is being performed by students in a well-equipped laboratory, the products formed from several different starting vegetable oils can be compared using GCMS (gas chromatography-mass spectrometry). In the simpler preparation, 12–13 ml of a vegetable oil of choice is put into a boiling tube with 2 ml of potassium hydroxide in methanol (5 % w/w). The liquids are mixed without shaking to prevent trapping air and foaming. The mixture is left to stand in a water bath at 60
C. The reaction rate can be followed by measuring the viscosity: one can time how long it takes for a small ball bearing to drop through a defined depth of the mixture in the tube every 5 min at regular intervals for up to 2 h. Furthermore, you can leave a sample for a whole day in these conditions to observe the extent of hydrolysis. Note, if previously used vegetable oil is utilized, please remember to strain out any food residues first!

Nitrogen Dioxide Preparation Few students make or even see the gas nitrogen dioxide (NO2) as it is poisonous, and science teachers are put off by the necessary risk assessment. Nitrogen dioxide can be made in small volumes very simply using a source of copper and concentrated nitric acid. In the UK, it is permissible to use copper coinage as a source of copper and as such adds to the interest of the demonstration. If coinage use is not possible, then a spatula of copper turnings – not bulk copper metal or copper powder – should be used. The copper is placed in a wide-necked conical flask or 400 ml beaker placed on a white tile against a white background to make the color change more easily seen. After a short while, orange-brown fumes of nitrogen dioxide can be seen. The reaction increases speed after a few moments. Provided there are no drafts, the density of the gas may be seen by pouring out the gas from the reaction vessel. The acidity of the gas may be demonstrated using damp universal indicator paper or blue litmus. Some closer members of the audience may get to smell the chlorine-like odor,

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and it may remind them of the smell that is sometimes detected near busy roads or outside of central heating boiler ducts. The reaction may be stopped by diluting the acid in the reaction vessel with water. The blue color of hydrated copper (II) can be seen. The color of the gas is important, indicating that it absorbs light at around 400 nm. The NO2 is easily broken down to NO and O atoms by this photolysis process. The O atom produced can add to O2 as shown in reaction (Eq. 14) and gives rise to the production of ozone near the surface. Such production of ozone near the surface is bad for animal and plant health and is associated with photochemical smog. As the oxidizing properties of nitric acid are concentration dependent, this reaction has a number of other teaching uses.

Detection of Atmospheric Carbon Dioxide Levels Using IR Sensors Carbon dioxide (CO2) is the most commonly known greenhouse gas. One might well ask how levels of CO2 are measured in air samples, particularly as their concentrations are so low. A lot of people will remember from their own school science lessons that carbon dioxide can be detected through the use of limewater (saturated calcium hydroxide solution) where the clear and colorless solution turns chalky, misty, and milky or forms a white precipitate depending on interpretation. All these descriptions refer to the formation of a suspension of calcium carbonate (CaCO3). Few have any understanding of how the concentration of carbon dioxide in the atmosphere can be known. Few will have any understanding of infrared spectroscopy and its link with molecular bonding. How Do Infrared (IR) Sensors Work? Two types of carbon dioxide sensors have been used with school students and teachers (Harrison et al. 2006): one which allows gas to diffuse into the sensor and one which is pumped. They both work in similar ways. Carbon dioxide molecules absorb energy at specific frequencies of infrared radiation and use the corresponding energies to stretch or bend the covalent bonds between the carbon and oxygen atoms accordingly. Low energies cause a bondbending motion, and high energies cause bond stretching. The frequencies at which this occurs are within the infrared part of the electromagnetic spectrum (between 4,000 and 650 wavenumbers, corresponding to 2.5–15 μm). A wavenumber is the unit commonly used in spectroscopy to relate wavelength to energy. A wavenumber (1/λ) is the reciprocal of wavelength (λ) and is directly proportional to energy. This absorbance at this wavelength can be used to determine the CO2 concentration in the air. There are two main types of carbon dioxide sensors (Harrison et al. 2006). The more expensive research sensors pump air through the sensor, while the cheaper devices rely on diffusion. For either type of detector, air passes into the absorption cell. This is effectively a small darkened cylinder within the sensor. At one end of the

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absorption cell, there is an infrared light source coupled to a fixed wavelength filter, which provides a narrow band source of infrared light, for CO2 at around 2,350 cm1 (wavenumbers, i.e., 4.3 μm). At the other end of the tube, there is an infrared detector or photon counter that measures the infrared light intensity. The more CO2 molecules are in the air sample, the more infrared radiation is absorbed in the cell, and the less infrared radiation reaches the detector. For small absorptions, the Beer-Lambert law shows that Concentration ¼

ð1  ðI=I 0 ÞÞ σl

(23)

where l is the path length (length of the cell). σ is the absorption cross section for CO2 at the wavelength being used and is known to a high accuracy. (I/I0) is the ratio of infrared radiation arriving at the detector when the cell is empty (I0) to when it has an air sample in it (I). I0 is not measured for each reading, but will be measured frequently to check that there are no appreciable fluctuations in the instrument infrared light intensity. Students who have used such sensors (see Fig. 17a, b), on loan from the University of Bristol, have been surprised that the carbon dioxide reading inside an empty classroom is much greater than that outside, the latter being well above 0.037 % (370 ppm) as reported for the CO2 atmospheric concentration in some textbooks. New school buildings in the UK appear to have windows that are not designed to be opened! Simple experiments in a lecture theater with 200 students show that the CO2 concentration will reach 1,400 ppm after 50 min. The CO2 sensors that have been used with students are tuned to the CO2 ν3 asymmetric bond stretch at 2,349 wavenumbers (Harrison et al. 2006). An asymmetric stretch is where the carbon-oxygen double bonds (C=O) absorb energy and one of the two bonds lengthens, while the other one contracts. For CO2, there can only be one asymmetric stretch. This particular bond stretch is important because carbon dioxide is the only molecule present in high quantities in the atmosphere to absorb at 2,439 wavenumbers. Therefore, only absorption by CO2 can cause a change in infrared light intensity at this wavelength. It is common for an optical sensor to be tuned to a specific frequency where the molecule absorbs. Usually it is the most intense absorption that is chosen to be detected because there will be the greatest sensitivity. Using the method with other gases, this is not always possible as there may be others that also absorb in that region. In that case, a different absorption is chosen free from interferences. Examples of simple investigations that can be made with such sensors without logging include measuring the levels inside a classroom before and after it is in use, measuring roadside levels of carbon dioxide and the differences that are there in moving away from the road (wind direction, season, time of day also play a part),

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a

100 mm

160 mm

b

Inlet: Constant air flow IR detector

IR lamp

CO2 molecule

Exhaust

Other molecules InfraRed filter (2,439 cm−1)

Fig. 17 (a) Internal circuitry of the CO2 detector. (b) A schematic of the CO2 cell within the sensor 2,439 cm1 = 4.1 μm

and measuring levels above and below trees and other vegetation. With a logging device, simple investigations of the change in concentration in a classroom during the lesson, with and without windows and doors open, are easy to do. Roadside data measurements over a period of time provide a rich source of information not only about emissions from cars but also about the dynamics of the atmosphere. Fourier transform analysis (Harrison et al. 2006) of these data has revealed cycles of minutes (corresponding to traffic light signal cycles), 8 h (rush hour peaks), 12, and 24 h revealing the rising and falling of the Earth’s boundary layer. Very-long-term measurements, of course, provide seasonal cycles that a student can investigate and reveal, even in urban measurements, a winter peak and summer trough caused by photosynthesis.

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Impact and Assessment “How does one know that what one does in terms of climate change outreach is doing any good?” is often a question asked of work with primary and secondary school students or indeed with the wider public. It is often a question asked of prospective funders either directly or by implication on grant applications when the use of evaluators is required. In this section, some feedback methods are discussed that may be useful for employment in outreach activities. A major current issue in the field of science communication is evaluating the impact of activities designed to engage people with science and technology. Evaluation is widely seen as the primary tool to identify best practice and provide empirical evidence of the positive impact of such activities. However, there is no standard method for doing this or for comparing the results. The majority of published evaluations involve the use of quantitative data generated through written questionnaires. Using such methods to evaluate the impact of short-duration activities is often inappropriate or impractical. Are there alternatives to the traditional questionnaire for obtaining feedback about the impact of some types of science communication activity? What are the effects, if any, of the activities on participants?

Generic Learning Outcomes In a recent research exercise, Rivett (2009) investigated a number of physical science outreach events, including the use of lecture demonstrations at primary and secondary level on atmospheric chemistry and climate change. These activities were evaluated using a variety of unconventional techniques. The events were evaluated using postcard writing, children’s drawings, comments boards and walls, observation, and unsolicited and teacher feedback. An interactive voting system and some written questionnaires developed and administered by third parties were also utilized. These largely focused on identifying the immediate to short-term impact of the activities. They generated largely qualitative data but included a quantitative component. These data were analyzed using the Generic Learning Outcome [GLO] (Generic Learning and Archives Council 2008) framework, which is becoming a common evaluative tool across the Museum and Science Centre sector. GLOs are a way to look at different types and levels of impact using one tool. The model stems from a view of learning as a personal and individual experience, which is context dependent. Five categories are used to code participants’ responses: knowledge and understanding; skills; attitudes and values; enjoyment, inspiration, and creativity; and activity, behavior, and progression. The alternative evaluation techniques tested resulted in the production of a large amount of useful data and a greater range and depth of information on impact than might be expected. The qualitative nature of the tools is more appropriate for small

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sample sizes (which might lack statistical significance). They were generally uncomplicated to use and simple to analyze using the GLO framework. • Write a postcard feedback revealing the greatest range and depth of learning outcomes, comparable with an externally designed written questionnaire. • Observations were a rich source of data, but did not necessarily capture the impact on all participants. Teacher feedback provided information about a range of learning outcomes, but not from the pupils’ own perspective. Children’s drawings gave some useful information about a limited range of learning outcomes. • Comments boards provided a deeper insight into participants’ experiences than initially expected, but generally only about a subset of learning outcomes. To generate meaningful data about impact, questions must be carefully worded to guide responses. • Unsolicited feedback does not give reliable evidence of learning outcomes, but can be analyzed to provide limited information about impacts. • Interactive voting provided the least information about impact in this study, because the questions asked generally did not focus on learning outcomes. • The major category of learning outcome reported by participants is enjoyment, but evidence for knowledge gained, changes in attitudes, and behavior is also strong. It is the questions asked which hold the key to elucidating different learning outcomes.

Suggested Questions to Discern Different Learning Outcomes The evaluation techniques differed in their level of convenience. Data collection tools such as the postcard feedback and Post-it note comments were cheapest and simplest to administer and could be analyzed rapidly using the GLO method. The majority of these techniques can only evaluate the immediate impact of the activity. This is due to when they are administered, which could be instantly after the event or at the most up to 1 or 2 weeks afterward. Asking participants to complete these styles of evaluation, a significant amount of time afterward is impractical and becomes more a test of memory than anything else. Teacher feedback was shown to provide an indication of longer-term impact, although this may be rather subjective. The GLO framework is a useful coding device which allows wider comparisons with other studies. It enables outcomes beyond immediate “reaction” level to be investigated in a meaningful way. The GLO approach reveals that impact is not a neat, linear process but occurs at many levels and over a multiplicity of timescales. The learning outcomes themselves are extremely varied. There may be no or even a negative impact, a transient effect, or something deep and long lasting. The level of impact is impossible to predict and is not the same for all participants. Discovering the medium- to long-term impact of any of these activities is beyond the scope of the techniques tested.

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Fig. 18 A postcard from a primary school student, providing feedback on an activity

However, a learner’s enthusiasm for a subject is usually retained much longer than memory of facts or content. There is evidence that memorable activities which provide positive experiences of science can affect future behavior. Given the right support, situational interest may become sustained and so increase motivation and satisfaction with a subject. Science communication activities like those investigated are just one part of the many and varied experiences in people’s lives. A single event cannot be expected to have a significant impact on the life choices of the majority of participants. What can make a difference is ensuring, through thorough and reliable evaluation, that there are a range of high-quality opportunities for people of all ages to experience different aspects of science, meet role models, and develop their interest and abilities.

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Table 5 Suggested questions that can be used for evaluation of activities What was your favorite part of the day Was there anything you did not like Please tell me anything you learned today How did today make you feel about science Did you find out how to do anything new or do anything better Do you think you will do any science activities following this event

Formative/process/ enjoyment Formative/process/attitudes Knowledge/skills Attitude/enjoyment Skills/knowledge Behavior/attitudes

The study identified a number of techniques which provide a range and depth of information about the learning outcomes experienced by respondents. They can easily be embedded into science communication activities and do not require timeconsuming analysis. The impact of the physics and chemistry activities studied was found to be very positive for the majority of participants and was similar to those found in other studies. A myriad of effects are seen at a variety of levels and over a range of timescales. This postcard (Fig. 18) sums up how a simple evaluation method can pay dividends in terms of the level of information gathered and show true evidence of the potential impact of science communication activities. A list of suggested questions for a GLO analysis is provided in Table 5.

Some Misconceptions Concerning Climate Change and Greenhouse Gases The following are the main misconceptions that workshops with students or with teachers have unearthed. It is important for all educators working in climate change to realize that ideas and models that are commonly used with peers are not general knowledge and the “obvious” needs to be spelled out. One such example with a group of experienced teachers was the term “aerosol,” which was only considered to be a spray can! All greenhouse gases are synthetic/man made. No, several natural processes release gases which can absorb outgoing infrared radiation (i.e., they are greenhouse gases), for example, CO2 is produced during respiration and natural combustion, N2O is produced by denitrifying bacteria in soil, and CH4 is generated by termites and cows. Global warming means that the entire planet will warm up evenly everywhere. No, warming will be quickest at the North Pole and slowest in the southern ocean. All pollution in the atmosphere causes global warming. No, for example, air pollution that leads to aerosol formation can cool the planet down (global dimming), e.g., SO2 emissions.

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All greenhouse gases are bad for the planet. No, a natural background level is essential for the average surface temperature to be habitable (see sections “The Granny Model: Basic Concepts” and “The Granny Model: The Underpinning Mathematics”). If more carbon dioxide means a warmer temperature, surely faster photosynthesis at the higher temperatures will remove the excess CO2. Photosynthesis is controlled by enzymes, so at some temperature this process will stop. Also, at higher CO2 levels, stomatal conductance drops (the plant does not have to work so hard to obtain CO2), and there is evidence that its physiology changes significantly. If burning waste materials produces CO2, then why not simply not burn organic waste instead of letting it rot. This is a contentious issue; during rotting, a myriad of gases are released into the atmosphere, and many will be greenhouse gases that will eventually be converted to CO2 in the atmosphere. So there is a strong argument to burn the waste, harness the energy, and capture the CO2 produced. CO2 is worse than methane. Figure 4 shows us that CO2 already absorbs a significant fraction of outgoing infrared radiation around 660 cm1 (25.2 μm), and therefore to absorb more would require a bigger jump in concentration than that for CH4. It turns out that CH4 is 21 times more potent than CO2 over long timescales. Carbon dioxide is always heavier than air. Below 100 km, gases are all well mixed in the Earth’s atmosphere, and even though CO2 is heavier than air, it is well mixed. It is only burning fossil fuels that causes emissions of CO2. Respiration also produces CO2 as do a number of key industrial processes such as iron and steel, aluminum, and cement production.

Datasets That Can Be Used in a Class Setting There are many datasets that are freely available, such as the UK National Air Quality Archive (NETCEN) (1996), that are a fantastic resource for students and teachers who want to have more hands-on activities concerned with air quality and climate change. However, the main problem is finding out about these archives, being able to access them and, of course, being able to comprehend what these data are and how to use them. A very profitable way forward is to provide background material for teachers and to run master classes in how to use these data. Through these classes, it has been possible to refine the notes provided and extend the scope of the class. There are also datasets that are well documented such as the Advanced Global Atmospheric Gases Experiment (AGAGE) dataset. One such use of a dataset was research into how fireworks affected air quality during the UK’s Bonfire Night. Students from several year groups from three schools were instructed on how to handle data from the UK-AIR website (http://uk-air.defra. gov.uk), and their research was published (Harrison and Shallcross 2011).

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AGAGE AGAGE (1978) is a project that has run since 1978 (then called the Atmospheric Lifetime Experiment, ALE) and consisted originally of five surface stations that were spread across the Northern and Southern Hemisphere, away from major pollution sources. These sites were in Ireland, the USA, Barbados, American Samoa, and Australia (see Fig. 19) and use gas chromatography coupled with a variety of detectors to measure CFCs (chlorofluorocarbons), compounds that were responsible for depleting stratospheric ozone and their replacements the HCFCs and HFCs (hydrochlorofluorocarbons and hydrofluorocarbons). In addition to these gases, measurements of key species such as CO2, CH4, and N2O are made. Extensive information is available, and clear notes on data are provided. Using data such as that from AGAGE can transform classroom teaching and cognition on the subject of climate.

Global Warming Potentials It is useful to define a concept called the global warming potential or GWP. In the “Introduction” section, it was explained why greenhouse gases are so important to the Earth’s climate system and that to be a greenhouse gas, it needs to absorb infrared radiation corresponding to the wavelengths shown in Fig. 4. The most important of these greenhouse gases is CO2, and the GWP is defined relative to CO2. The GWP is calculated using a computer model and allows greenhouse gases to be “ranked” in

Fig. 19 Original surface sites for the AGAGE project

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Table 6 Some global warming potentials for a range of trace gases over a 20-year and 100-year time horizon Trace gas CO2 CH4 N2O CFCl3 CF2HCl CF2Cl2

Lifetime (years) 120 10 150 60 15 130

GWP time horizon 20 years 1 63 270 4,500 4,100 7,100

GWP time horizon 100 years 1 21 290 3,500 1,500 7,300

terms of their potency. It is not too difficult to see that the two factors that determine a GWP are how strongly does the gas absorb infrared radiation emitted by the Earth (effectively the size of the absorption cross section of the gas) and how much of the gas (determined by its source strength and lifetime) is present. In a GWP computer model, one would typically release a unit mass of CO2 and a unit mass of the gas whose GWP is to be determined. After 20 model years, the radiative forcing or heat trapped by CO2 is calculated and scaled so that it equals 1. Using this scaling factor, the radiative forcing of the gas under inspection is also calculated. The model is run for 100 model years, and the radiative forcing is calculated again and scaled to CO2. Some data from key greenhouse gases are collected in Table 6. The table reports the GWP on a 20-year and 100-year time horizon and, because of the definition, CO2 in unity always. Interestingly, for all other gases, the GWP either increases from a 20-year time horizon to a 100-year one or decreases. Further inspection shows that those gases that have a shorter lifetime than CO2, that is, CH4, CFCl3, and CF2HCl, all decrease, while the remaining two, N2O and CF2Cl2, whose lifetimes are longer than CO2 increase. This change in GWP with time (hence the need to stipulate the time horizon) arises because if the gas is removed more quickly than CO2, relative to the year 20, the ratio of X/CO2 in the year 100 will have decreased, that is, far more of X will have been removed than CO2. Hence, with time the effectiveness of the gas will decrease, that is why the GWP of CH4 drops from 63 to 21, for example. In a similar vein, N2O is longer lived than CO2, and so with time the CO2 will decay more rapidly, and the N2O becomes even more effective with time. Regardless of lifetime, it is clear that species containing C–F and C–Cl bonds have very high GWPs. This was explained in section “Stratospheric Ozone Depletion and Climate Change,” that is, that these gases absorb in the region known as the atmospheric window and have high absorption cross sections, coupled with their lifetime, leading to the high GWP. Compounds of particular concern are the PFCs (perfluorocarbons), fully fluorinated saturated hydrocarbons (e.g., CF4 and C2F6). These molecules have incredibly long lifetimes (sometimes known as immortal molecules) and very large absorption cross sections and can therefore have a GWP of many thousands. It has been speculated that if man colonizes another planet such as Mars, PFCs would be needed in the terraforming process to flood the atmosphere with high GWP gases and raise the surface temperature.

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Methods Used to Monitor Greenhouse Gases It is instructive to know how the levels of greenhouse gases in the atmosphere are determined. First, the site of the monitoring station is important; it needs to be away from major pollution sources, so that changes to the background concentration can be determined. This criterion dictated where the AGAGE stations would be located (see Fig. 19), and it also then requires that the stations are in remote locations. Hence, the monitoring systems need to be robust, reliable, and low maintenance. For the majority of gases, gas chromatography (Fig. 20) with either an ECD (electron capture detector) or an FID (flame ionization detector) or a mass spectrometer is used. Since many of these gases are present in trace quantities, the air mass must first be pre-concentrated, and to achieve this, a cooled microtrap (50
C) containing some solid adsorbent is used to trap the gases of interest (ADS in the figure). Many liters of air can be trapped in this way, and once collected this slug of air can be driven off the trap in 1–2 s by ballistic heating. This slug of concentrated air is then separated into its components by passing it through a GC (gas chromatography) column. As the gases pass over a solid or liquid phase (an adsorbent), some bond to the surface more efficiently than others, and so separation takes place. For gases such as CFCs, HCFCs, and N2O, which have electronegative elements such as F, O, and Cl, an ECD is a good detector. An ECD consists of a beta (electrons) emitter that provides a baseline current. As the molecule passes through the beam, it absorbs electrons and a dip in current is observed. This invention of Lovelock is incredibly sensitive. For other species, they can either be burned in a flame, where ions are produced and detected, or “weighed” using a mass spectrometer.

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Fig. 20 Schematic of a gas chromatography system used in the AGAGE project

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Outreach: Impact on Providers and Others What Is the Impact on Postgraduates and Researchers Who Engage with Schools, Teachers, and the General Public? There are several reasons why researchers such as postgraduates should get involved with outreach in topics such as climate change excluding the most important one, which is that taking part in well-organized and well-thought-through activities is great fun!

Communication Skills Working with school students causes researchers to evaluate the language that they use to communicate their work. Researchers who only used to communicating their science to peers do not always realize that their language is very specific and has acceptance of mutually understood models. They forget that this language and use of models are not widely understood by others. Working with school students directly, or writing articles for them, brings this home. The advantage for the researcher is being able to communicate their work to wider audiences including to those less expert. There are many instances when it may be vital to be able to explain to someone what research you are doing, for example, a potential funder. To younger researchers, the opportunity to give presentations to groups of school students increases their confidence and makes the delivery of talks at seminars and conferences of their peers a less daunting task than it would otherwise be. For younger researchers, it also forces them to really understand the background to their material, as they will almost certainly be asked that obvious but not trivial question about their subject, by an enthusiastic teacher or student. Role Models School students still see stereotypes of scientists as being male, middle-aged with long white hair. Putting young researchers, perhaps with colored hair and studs through their noses, in front of school students makes a big difference. Bristol ChemLabS outreach often has requests for outreach teams to be composed of specific gender and racial types to act as role models in particular places. For example, in areas in certain countries of social deprivation with a high proportion of immigrant descendents, to have teachers that are from that group can have an amazing impact on the student’s enthusiasm. In another instance, a totally female team was requested to work with primary aged girls who had become disillusioned with science and mathematics. The feedback from both implied that these targeted role models had the desired effect. Supervisors Many supervisors may be reluctant to let their postgraduates engage in outreach activities as this removes them from the research laboratory environment. Students report that they really value short periods spent away from their labs engaged in outreach. Students give as examples, coming back into the labs afresh, the ability to

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look at their work with renewed enthusiasm as they treat outreach engagements as “periods of tranquility” in an otherwise chaotic work program. Indeed, some students have only managed to complete their PhDs because of this outlet. In other cases, the climate change science being presented to school students has suddenly clarified the point of a piece of PhD research and then has led to it moving on in a new direction.

Increased Employment Prospects Students can access many more potential careers such as those directly involved in science communication and teaching. Working for an outreach team also gives them additional referees that can comment on their skills for these and other positions. Increasingly, employers value the soft skills, such as communication and team work skills, over technical expertise of graduate chemists. Outreach work can develop these.

Impact on Recipients Well-focused activities with supporting resources can have a lasting (Harrison and Shallcross 2010; Tuah et al. 2009) impact on teachers and their students, in terms of cognition in this subject area. Through schools one can also interact with whole families, for example, parents. A combination of lecture demonstrations, model workshops, and hands-on practical sessions has been found to be a powerful portfolio for a wide range of learner types and ages. Such approaches have also worked well for those with disabilities, for example, visually impaired.

Is Climate Change All Gloom and Doom? Introducing Stabilization Wedges When learning about climate change, the students can become despondent easily. They can feel that warming of the Earth and the resultant consequences are inevitable. Both to give some hope to the students and to demonstrate to them the potential of scientific research, ideas presented in a recent paper by two leading climate scientists (Pacala and Socolow 2004) can be introduced into lessons. Their paper discusses how CO2 levels can be stabilized and other carbon-based greenhouse gas emissions into the atmosphere using technologies that already exist. Stephen Pacala and Robert Socolow devised the concept of stabilization wedges as a way to reduce carbon emissions over the next 50 years. Figure 21 shows how carbon emissions have increased over the last 50 years and how they are predicted to change in the next 50 years largely based on changes in population. By 2055, it is predicted that there will be 14 gigatons (billion tons) of carbon (GtC) emitted per year if nothing is done now. This will lead to a level of CO2 in the atmosphere that is around three times the CO2 level before the industrial revolution started and is predicted to cause a rise in the Earth’s average surface temperature of 1–5
C.

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Fig. 21 Carbon emissions, past, present, and future, and the concept of stabilization wedges

Pacala and Socolow suggest that the objective is to maintain carbon emissions at their present levels of 7 GtC per year. As there is no one method to remove this carbon burden, they devised the idea of stabilization wedges. A wedge represents an activity that reduces emissions to the atmosphere that starts at zero today and increases linearly until it accounts for 1 GtC per year of reduced carbon emissions in 50 years. The cumulative total is therefore 25 GtC of reduced emissions over 50 years.

What Activities May Achieve This Effect? Improved Fuel Economy A typical car emits a ton of carbon into the air each year. There are one billion cars in use today, and the figure will grow to two billion. Two wedges could be saved if their fuel economy were improved from 30 miles per gallon (mpg) of fuel to 60 mpg. Reduced Use of Cars Assuming an increase by 2055 to two billion cars and assuming that no improvement in fuel economy was achieved, a wedge could be saved if the number of miles traveled was reduced from 10,000 miles per year to 5,000 miles per year. Both of these options could save more than one wedge if there is an overprediction regarding the increase in the number of cars in use by 2055. More use of telecommunication and mass transit will reduce the use of cars further.

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More Efficient Buildings Many savings can be made in terms of energy efficiency in buildings, for example, replacing all the world’s incandescent light bulbs with compact fluorescent lights would provide a saving of one fourth of one wedge. However, to save one wedge of carbon requires a cut in carbon emissions from buildings of 25 % by 2055. This can be achieved using known and established approaches to energy efficiency. The largest savings are in space heating and cooling, water heating, lighting, and electric appliances. Improved Power Plant Efficiency Currently, coal-powered plants operate at about 32 % efficiency and are responsible for about 25 % of all carbon emissions. Improving plant efficiency to 60 % through use of better turbines, fuel cells, etc., would save half a wedge if the quantity of coal-based electricity is unchanged. Emissions from power plants can be reduced both by changing the fuel and by converting the fuel to electricity more efficiently at the power plant. Decarbonization of Electricity and Fuels For example, per unit of electricity, carbon emissions are half as large from natural gas power plants as from coal-based power plants. A wedge would be achieved by displacing 1,400 GW of baseload coal with baseload gas by 2055. However, a wedge would require an amount of natural gas equal to that used for all purposes today. A wedge worth of gas would require 50 LNG (liquefied natural gas) tanker deliveries every day or the equivalent of 50 Alaska gas pipelines. This scenario also assumes that no losses of CH4 (which has a higher GWP than CO2, see above) would occur during exploration and distribution. Carbon Capture and Storage One wedge of carbon can be saved by providing carbon capture and storage at 800 GW of baseload coal plants of 1,600 GW of natural gas plants. A wedge will require injecting a volume of CO2 equal to the amount of oil extracted every year back into subsurface locations. There are currently less than ten CO2 storage (pilot) projects that each injects one million tons of CO2 per year. By 2055, 3,500 will be needed. Decarbonization of Electricity and Fuels: Nuclear Fission The rate of installation of nuclear power plants required to save one wedge of carbon from electricity is equal to the global rate of nuclear expansion from 1975 to 1990. Phasing out of nuclear electric power would create the need for another half wedge of emission cuts. There are of course continuing issues concerning removal and storage of nuclear waste, natural catastrophes (compare Fukushima), and the threat of terrorism. Increased Use of Renewable, Nonfossil, Energy Sources, Including Wind, Electricity, Photovoltaic Electricity, and Biofuels Installed wind capacity has been growing at about 30 % per year for more than 10 years. It is around 50 GW peak at present, and therefore a wedge of carbon would require 40 times the current deployment. The wind turbines would occupy about 30 million hectares (about 3 % of the area of the USA), some on land and some out to

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sea. However, since the windmills would be widely spaced, it is possible to use the land for other purposes as well. A wind electricity wedge would require a combined land area the size of Germany. The current global deployment of photovoltaics is about 3 GW peak, with a growth factor of about 30 % per year. Therefore, to save 1 GtC per year would require an increase in the deployment by a factor of 700 by 2055 giving 2,000 GW peak. This would be equivalent to an area of about 2 million hectares, assuming an output of 1,000 W peak per m2 or 2–3 m2 per person. A photovoltaic electricity wedge would require an array of photovoltaic panels with a combined area about 12 times that of metropolitan London. Biofuels such as ethanol can replace fossil fuels, but a wedge of first-generation biofuels (e.g., ethanol from sugar cane or biodiesel from rapeseed or soy bean) could be achieved by the production of 34 million barrels per day of ethanol to replace gasoline by 2055. This assumes that the ethanol is from fossil-free carbon and is 50 times larger than the current production rate. This would require 250 million hectares of high-yield plantations equivalent to one sixth of the world’s cropland. One wedge from biofuels (first generation) would require planting an area the size of India with biofuel crops. For details, see the respective chapter on biofuels in this handbook. The pros and cons of implementing each of these technologies would make both interesting projects and the subjects for class debates whether in science or in social studies. The approaches – as well as the problems they are designed to reduce – will impinge more on the lives of the young rather than on their teachers or the authors of this chapter. All options are based on current technologies, and therefore some of these options may well provide more savings as technology improves. The consequences of these do generate comment particularly from younger audiences.

Deforestation If the current rate of clear-cutting of primary tropical forest were reduced to zero, over the next 50 years that would save half a wedge. A further half wedge would be saved if reforestation of 250 million hectares of tropical land (currently 1,500 million hectares) or 400 million hectares of temperate forest (currently 700 million hectares) took place over the next 50 years. One wedge of saving would require new forests over an area the size of the continental USA. Soil Management Conversion of forest or natural grassland to cropland leads to aeration of the soil through annual tilling. This practice accelerates the decomposition of stored carbon and releases it back into the atmosphere. It is believed that 55 GtC has been lost from soils (two wedges worth) historically. Currently, 110 million hectares out of a total of 1,600 million hectares of cropland worldwide undergo conservation tilling. Conservation tilling will involve nondisruption to the soil, for example, drilling of seeds without plowing, soil erosion control, and planting of cover crops. It is feasible that a half to one wedge can be saved through conservation tilling of all croplands. Currently, conservation tillage is practiced on less than 10 % of global cropland.

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Conclusions and Summary The need to make the public more aware of climate change and the potential consequences of it, not only on planet Earth as a whole but also on the individual, is going to increase. Frequently aired radio and television programs, whether for an educated public or school-aged students, need to be made. Articles in popular magazines and not just science-specific journals need to be written for a range of audiences. If possible, access to scientists well versed in public communication at venues that do not intimidate such as bars and social centers, rather than university lecture theaters, for café scientifique experiences is going to be needed. Naturally, all these will be pointless if the level of communication is not appropriate to the audience. In schools in the UK, there has been a major move to promote “science literacy” so that students can make educated decisions about information they receive on a great number of issues from nuclear power to alternative fuels and to evaluate adverts and newspaper articles. These students also look at “how science works,” so they are also taught about how research is funded and now can have opinions as to whether research in some areas should be funded. These are of course not just future major consumers and tax payers but are also the voters of tomorrow. Whether this education trend will develop more widely or not, scientists need to communicate their findings as widely and in an accessible way as possible. The models developed in this chapter and associated practical experiments have enhanced the cognition of teachers and students with respect to the Earth’s climate system. It provides these learners with tools to carry out their own investigations and projects and does not require expensive equipment or facilities. The Earth’s climate system can be distilled to something that can be understood by the vast majority of people, and it is a great shame that at present there is still considerable misunderstanding that persists. The notion of stabilization wedges is a very powerful one and provides learners with some light at the end of the tunnel. Using the models developed, it is possible to carry out simple calculations and arrive at the estimates provided in terms of land area required, for example. The ability to make such “back of the envelope” calculations not only is a very useful life skill but allows the learner to critically assess the viability of each option presented. There is clearly much still to do in terms of providing the tools to allow new learners to understand the underpinning science of this important topic. However, the material described in this chapter makes a start at least on this road.

Even More Contemporary Atmospheric Chemistry: Criegee Biradicals Many school science curricula may expect examples of contemporary science. One recent case in atmospheric chemistry concerns the Criegee biradical. It involves elements of preuniversity chemistry such as free radicals, alkenes, and ozonolysis. In 1949, Criegee and Wenner first proposed that ozonolysis of alkenes such as ethene proceeds through carbonyl oxide intermediates, such as the •CH2OO• biradical.

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First, an adduct is formed, and this cyclic structure decomposes rapidly to form a carbonyl and a Criegee intermediate (the details can be found elsewhere in this reference work). Such biradicals had not been detected until recently when a group of British and American researchers succeeded using the Advanced Light Source at the University of California (Berkeley, USA) and photoionization mass spectrometry (PIMS). The importance: free radicals regulate ozone levels in the stratosphere and oxidation rates throughout the lower atmosphere, and some of the accepted atmospheric chemistry is now being rethought through. An outline of the fundamental science for teachers has been published (Shallcross and Harrison 2013).

Future Directions The Bristol ChemLabS outreach project, the range of activities being described here, is a sustainable program. While the activities such as lecture demonstrations; writing of articles suitable for teachers, school students, and members of the public; and teacher training will continue, their scope will expand. Already, requests for inclusion of climate change sessions for the Prince’s Teaching Trust which supports newly qualified (chemistry) teachers and teacher training sessions in Perth, Australia, are being planned. The Royal Society of Chemistry has recently awarded a grant to the ChemLabS team to deliver lecture demonstration training to postgraduate chemists in other universities, several of whom it is hoped will adopt “A Pollutant’s Tale” for their own delivery, as has been done in South Africa. Last, an interactive climate change book, suitable for navigation by members of the public of all ages and prior knowledge, is being considered. The climate change challenges are not going away in the short term, and so the outreach needs to educate will not either.

References AGAGE (1978) http://agage.eas.gatech.edu/. Accessed 29 Oct 2014 Generic Learning Outcomes, Museums Libraries and Archives Council (2008) www.inspiringlear ningforall.gov.uk/toolstemplates/genericlearning. Accessed 27 Oct 2014 Harrison TG, Shallcross DE (2010) What should be expected of successful engagement between schools, colleges and universities? Sch Sci Rev 91(335):97–102 Harrison T, Shallcross D (2011) Smoke is in the air: how fireworks affect air quality. Science in School 21:47–5 Harrison T, Shallcross D, Henshaw S (2006) Detecting CO2 – the hunt for greenhouse-gas emissions. Chem Rev 15(3):27–30 Hoffman PF, Kaufman AJ, Halverson GP, Schrag DP (1998) A Neoproterozoic snowball earth. Science 281(5381):1342–1346. doi:10.1126/science.281.5381.1342 NETCEN (1996) UK National Airquality Archive. http://www.airquality.co.uk/. Accessed 27 Oct 2014 Pacala S, Socolow R (2004) Stabilization wedges: solving the climate problem for the next 50 years with current technologies. Science 305:968–972 RCUK (2002) www.rcuk.ac.uk. Accessed 29 Oct 2014

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Rivett AC (2009) A study into the feasibility and validity of using alternatives to questionnaires to evaluate the impact of a selection of physics & chemistry science communication activities. Thesis (M.Sc.), University of Bristol Science Learning Centres (2004) https://www.sciencelearningcentres.org.uk/. Accessed 21 Feb 2015 Shallcross DE, Harrison TG (2007a) A secondary school teacher fellow within a University chemistry department: the answer to problems of recruitment and transition from secondary school to University and subsequent retention? Chem Educ Res Pract 8:101–104 Shallcross DE, Harrison TG (2007b) The impact of School Teacher Fellows on teaching and assessment at tertiary level. New Dir 3:77–78 Shallcross DE, Harrison TG (2007c) Climate change made simple. Phys Educ 42:592–597 Shallcross DE, Harrison TG (2008a) Climate change modelling in the classroom. Sci Sch 9:28–33. www.scienceinschool.org/2008/issue9/climate. Accessed 21 Feb 2015 Shallcross DE, Harrison TG (2008b) Practical demonstrations to augment climate change lessons. Sci Sch 10:46–50. www.scienceinschool.org/2008/issue10/climate. Accessed 21 Feb 2015 Shallcross DE, Harrison TG (2009) Hydrogen in the earth’s atmosphere. Chem Rev 19(2):2–6 Shallcross D, Harrison T (2013) Radical changes in our atmosphere. Education in Chemistry, Royal Society of Chemistry, 22–25 Sept Shallcross DE, Harrison TG, Henshaw SJ, Sellou L (2009a) Fuelling interest: climate change experiments. Sci Sch 11:38–43. www.scienceinschool.org/2009/issue11/climate. Accessed 27 Oct 2014 Shallcross DE, Harrison TG, Henshaw SJ, Sellou L (2009b) Looking to the heavens: climate change experiments. Sci Sch 12:38–43. www.scienceinschool.org/2009/issue12/climate. Accessed 27 Oct 2014 Tuah J, Harrison TG, Shallcross DE (2009) The advantages perceived by schoolteachers in engaging their students in university-based chemistry outreach activities. Acta Didactica Napocensia 2(3):31–44 Wild M, Gilgen H, Roesch A, Ohmura A, Long CN, Dutton EG, Forgan B, Kallis A, Russak V, Tsvetkov A (2005) From dimming to brightening: decadal changes in solar radiation at Earth's surface. Science 308(5723):847–850. doi:10.1126/science.1103215

Geoengineering for Climate Stabilization Maximilian Lackner

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Safe Limits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climate Engineering Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Radiation Balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Global Carbon Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Impacts of Climate Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Legal, Moral, and Social Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Legal Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Moral and Social Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Preliminary Climate Engineering Field Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Proposed Strategies for Climate Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Carbon Dioxide Removal (CDR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Solar Radiation Management (SRM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Other Greenhouse Gas Remediation Ideas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ERM and Energy Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climate Engineering in the Context of Climate Change Mitigation and Adaptation . . . . . . . . . Is It Geoengineering or Not? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Engineering the climate by means of carbon dioxide removal (CDR), Earth radiation management (ERM), and/or solar radiation management (SRM) approaches has recaptured the attention of scientists, policy makers, and the M. Lackner (*) Institute of Advanced Engineering Technologies, University of Applied Sciences FH Technikum Wien, Vienna, Austria e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_72

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public. Climate engineering is being assessed as a set of tools to deliberately, and on a large scale, moderate or retard global warming. There are several concepts available, like injecting aerosol-forming SO2 into the stratosphere or placing huge objects in orbit to partly shade Earth from incoming radiation or fertilizing the ocean with iron for increased algae growth and creation of carbon sinks. Such concepts are highly speculative, and irrespective of whether they would work, they bear huge risks, from adversely affecting the complex climate system on a regional or global scale to potentially triggering droughts, famine, or wars. More research is needed to better understand promising concepts and to work them out in depth, so that options are made available in case they should become necessary in the future, when climate change mitigation and adaptation measures do not suffice and fast action becomes imperative. Apart from the technological hurdles, which are anyhow mostly far beyond today’s engineering capabilities, huge social, moral, and political issues would have to be overcome. The purpose of this chapter is to highlight a few common concepts of CDR, ERM, and SRM for climate engineering to mitigate climate change.

Introduction Climate engineering (also dubbed geo-engineering, geoengineering) is defined as “the deliberate large-scale intervention in the Earth’s climate system, in order to moderate global warming” (Shepherd 2009). Another, more positive term found in the literature is “climate remediation” or “climate intervention.” It can be considered a variant of macroengineering (the implementation of extremely large-scale design projects such as the Panama Canal) and similar in type to terraforming (planetary engineering, i.e., altering the environment of an extraterrestrial world). The expression is not to be confused with geological engineering (likewise termed geoengineering or geotechnical engineering, which is concerned with the design and construction of earthworks, including excavations, hydraulic fracturing (fracking), drilling, and underground infrastructure). Climate engineering can be seen as the most desperate, bizarre climate change mitigation measure. Yet, due to slow progress with conventional and incremental measures, it has recaptured widespread attention among scientists, politicians, and the public. Climate engineering or “hacking the planet” (Kintisch 2010) is hyped as “quick fix” and “only solution” on the one hand and bedeviled and rejected as wacky idea, simply gambling, being impossible, and very dangerous on the other hand. Some see it as a metaphoric “Faustian bargain” or man’s attempt to “play God.” Finally, one needs to acknowledge that climate engineering concepts mostly “treat the symptoms rather than cure the illness” of climate change. It is not so easy to find one’s position toward climate engineering, and according to Heyward and Rayner (2013), some “scientists involved in geoengineering discourse convey mixed messages about the need for technocratic management of the

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anthropocene at the same time as expressing strong commitments to the importance of public participation in decision making about geoengineering.” The Intergovernmental Panel on Climate Change (IPCC) states that every option has to be considered, yet it expresses a critical attitude toward climate engineering due to the inherent, unknown risks and assesses it in its 2007 report as “largely speculative and unproven and with the risk of unknown side-effects.” It was around the year 2008 (Ming et al. 2014) to 2009 that a critical discourse of geoengineering started to emerge, mainly in American magazines (Biello 2009; Kunzig 2008) and German newspapers (Anshelm and Hansson 2014). Kennedy et al. (2013) write that “No study of coping with climate change is complete without considering geoengineering.” Social science teaches that transformation dynamics evolve from hope-inspired alternative choices rather than fear-driven technical constraints (Stirling 2014). With a lot of disappointment from commitment and implementation of climate change mitigation measures over the last years, and continued GHG emissions, many scientists feel certain despair, giving an inclination toward options provided by climate engineering. Climate engineering can be considered a complementary approach to conventional measures: Preserving the climate (quick fix) while CO2 is gradually brought under control by natural and/or artificial processes. In this scenario, climate engineering would “buy time” for mankind and the globe. The major issue, even with reversible actions of climate engineering, is that the climate system is very complex. Identifying unintended consequences is not a trivial – if at all possible – task. Such consequences could be most severe and irreversible, like droughts or wars. In this context, it is worthwhile to think about the theory of chaos, which is rooted in the pioneering work of MIT meteorologist and mathematician Edward N. Lorenz (1963). Moreover, a slight drifting of the continents or a minor shifting of ocean currents may bring ice to one land and desert sands to another; see Lorenz (1972).

Safe Limits The concept of Earth as a self-regulatory system was developed in the late 1960s by J. E. Lovelock and became popular under the name “Gaia hypothesis” and “Daisyworld” model (it is a parable on the biological homeostasis of the global environment. “Daisyworld” contains white and black flowers. When temperatures rise, more white daisies grow, increasing reflection. Sinking temperatures are counteracted by a growth of black daisies: They absorb more sunlight. Hence the balance of white to black daisies controls the temperature and stabilizes it. The simplistic Daisyworld model intuitively describes the coupling between climate and the biosphere). Lovelock’s concept is being discussed controversially (Weaver and Dyke 2012; Boston 2008). For sure nature can buffer anthropogenic impact to some extent, but not endlessly, and climate change is testimony for this finite buffering capacity.

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In their seminal paper “A safe operating space for humanity” (compare The Limits to Growth work by the Club of Rome in 1972), Rockström et al. write that “Although Earth has undergone many periods of significant environmental change, the planet’s environment has been unusually stable for the past 10,000 years. This period of stability — known to geologists as the Holocene — has seen human civilizations arise, develop and thrive” (Rockström et al. 2009). They define nine interlinked planetary boundaries, three of which have already been overstepped. For instance, the estimated safe threshold identified for atmospheric CO2 is 350 ppm or a total increased warming of 1 W/m2 (current warming is approx. 1.9 W/m2 radiative forcing from 400 ppm of CO2 (Butler and Montzka 2013), not considering the additional radiative forcing by other greenhouse gases such as CH4).

Climate Engineering Approaches Climate engineering is still in its infancy, at a theoretical stage, where ideas are being generated, discussed, and elaborated. The Secretariat of the Convention on Biological Diversity concluded that “There is no single geoengineering approach that currently meets all three basic criteria for effectiveness, safety and affordability. Different techniques are at different stages of development, mostly theoretical, and many are of doubtful effectiveness” (Secretariat of the Convention on Biological Diversity 2012). Global climate engineering is untested and mostly untestable (MacMynowski et al. 2011). Its roots go back to 1965, when advisors to US President Lyndon B. Johnson suggested spreading reflective particles over 13 million km2 of ocean in order to reflect an extra 1 % of sunlight away from Earth (Kintisch 2010). This was one of the first high-level acknowledgements of climate change. Interestingly, no suggestions to cut down CO2 emissions were reported to have been made. The president did not follow these early geoengineering suggestions. Even prior to that, in 1955, John von Neumann foresaw “forms of climatic warfare as yet unimagined” in Fortune magazine (von Neumann 1955). In 1974, the Russian researcher Mikhail Budyko suggested that cooling down the planet could be achieved by burning sulfur in the stratosphere, which would create a haze from the resulting aerosols (higher albedo) (Teller et al. 1997). This and other concepts will be touched upon below. Space-based geoengineering concepts build upon Tsiolkovsky’s and Tsander’s 1920s idea of utilizing mirrors for space propulsion (Kennedy et al. 2013). As these examples show, ideas to engineer the climate came up quite early. Small-scale weather modification can already be achieved today, e.g., by cloud seeding to induce rainfall. The historical Project “Stormfury” (1962–1983) attempted to weaken tropical cyclones with silver iodide (Willoughby et al. 1985). For a brief review on “rainmaking attempts” and “weather warfare,” which is outside the scope of this chapter, see Chossudovsky (2007) and Climate Modification Schemes, American Institute of Physics (AIP) (2011). Weather modification action has been limited by the international community, e.g., during war by the 1977 UN

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Environmental Modification Convention. Another regulation in this respect is the London Convention (1972) and its 1996 Protocol, which are global agreements regulating dumping of wastes at sea. Article 6 prohibits exports of wastes for dumping in the marine environment, which includes, e.g., CO2 in CCS (carbon capture and storage) schemes (Dixon et al. 2014). Examples where man has modified local climate (impacts) include artificial snow in skiing resorts or irrigation for crop yield amelioration. Previous environmental interventions by man have sometimes brought about unwanted – and unexpected – effects, also in the near past, e.g., streamlining riverbeds leading to local floods or the creation of urban heat islands. Joe Romm, founding editor of the blog Climate Progress, has linked “geoengineering to a dangerous course of chemotherapy and radiation to treat a condition curable through diet and exercise — or, in this case, emissions reduction” (McGrath 2014). Al Gore, former vice president of the USA, was quoted on climate engineering to be “utterly mad and delusional in the extreme.” He said that searches for an instant solution were born out of desperation, were misguided, and could lead to an even bigger catastrophe (Goldenberg 2014). “The idea that we can put a different form of pollution into the atmosphere to cancel out the effects of global warming pollution is utterly insane” (Goldenberg 2014). In fact, the idea of “engineering” the Earth’s climate is a shocking one. There is yet little information available, and “technically feasible” concepts are totally vague on costs, effectiveness, reversibility, risks, and side effects. However, serious scientists have started to investigate options for climate engineering more deeply, since swift remedial action might be needed once the Earth’s climate system reaches a “tipping point” (positive feedback, thermal runaway, e.g., thawing of permafrost releases CH4, which further increases temperatures). It seems necessary to study climate engineering, to be prepared. There is also the threat of unilateral action by another country (Dean 2011), should a local benefit from such action be expected. Tipping point rhetoric is challenged in Heyward and Rayner (2013). Climate engineering ideas and concepts fall into two broad groups: carbon dioxide removal (CDR) and solar radiation management (SRM). Several researchers discern Earth radiation management (ERM) from SRM, where ERM techniques focus on atmospheric convection enhancement (building of thermal bridges) and increasing outgoing IR heat radiation (i.e., long wavelength). The focus of SRM is on (short wavelength) incoming radiation. The term ERM was introduced by David L. Mitchell et al. (2011). He includes CRD and cirrus cloud reduction into SRM (Mitchell and Finnegan 2009). CRD techniques are remediation, whereas SRM are intervention. CDR techniques are generally not considered that controversial, and they do not seem to introduce global risks, as they work on the local scale. Costs and technical feasibility have been limiting CDR deployment, e.g., reforestation or CCS. CRD attacks the root cause of climate change. However, the effects work slowly to bring down temperatures again. SRM targets an increase in the amount of solar energy radiated back into space, effectively dimming the Sun. The necessary albedo enhancement is envisioned for

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deserts, oceans, mountains, clouds, and also manmade objects like roofs or roads. Prominent concept examples include deployment of giant orbiting sunshields in space, emission of huge amounts of SO2 (Crutzen 2006) and particles into the stratosphere to mimic the action of volcanoes, increase of the Earth’s albedo by “painting” deserts white, spraying sea water into the atmosphere to produce and whiten clouds, redirecting ocean streams and changing their salinity (Could a massive dam 2010), or pumping seawater into pole regions and creating ice. Such techniques bear the risk of upsetting the Earth’s natural rhythms. SRM approaches act quickly. However, they do not remove the root cause of climate change, mainly CO2 levels in the atmosphere, so other aspects like ocean acidification are not tackled. Raymond Pierrehumbert, professor in Geophysical Sciences at University of Chicago, said “The term ‘solar radiation management’ is positively Orwellian. It’s a way to increase comfort levels with this crazy idea” (Rotman 2013). According to Shepherd (2009), CDR methods should be regarded as preferable to SRM methods. SRM methods are expected to be cheaper, though. The Royal Society wrote in a 2009 report (Shepherd 2009): “Solar Radiation Management methods could be used to augment conventional mitigation. However, the large-scale adoption of Solar Radiation Management methods would create an artificial, approximate, and potentially delicate balance between increased greenhouse gas concentrations and reduced solar radiation, which would have to be maintained, potentially for many centuries. It is doubtful that such a balance would really be sustainable for such long periods of time, particularly if emissions of greenhouse gases were allowed to continue or even increase.” Although technological hurdles exist, it is expected that devising working technologies (i.e., installations that cool the atmosphere) are easier than understanding their effects or how governance (Shepherd 2009) should be applied. The focus of this chapter lies on SRM, which directly modify the Earth’s radiation balance; compare Fig. 1. It also covers CDR, which influences the global carbon cycle (see Fig. 2), and ERM, as well as touching upon governance and other related aspects of climate engineering.

Radiation Balance Energy on Earth mainly comes from the Sun. The solar constant is approx. 1,361 W/m2, which translates into a power of 1.730  1017 W for the entire Earth. The average incoming solar radiation is approx. ¼ of the solar constant (342 W/m2). The radiation balance of the Earth is shown in Fig. 1 in a simplified version. Climate engineering aims at modifying this radiation balance to achieve a lower net heating effect. In climate science, radiative forcing or climate forcing is defined as the difference of insolation (sunlight) absorbed by the Earth and energy radiated back to space. Currently, it is 2.916 W/m2, which corresponds to 479 CO2-eq. 1.88 W/m2 thereof is due to CO2 and 0.51 W/m2 due to CH4 (Butler and Montzka 2013).

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Fig. 1 Schematic showing the global average energy budget of the Earth’s atmosphere. Yellow indicates solar radiation; red indicates heat radiation; and green indicates transfer of heat by evaporation/condensation of water vapor and other surface processes. The width of the arrow indicates the magnitude of the flux of radiation and the numbers indicate annual average values. At the top of the atmosphere, the net absorbed solar radiation is balanced by the heat emitted to space (Source: Shepherd 2009)

Global Carbon Cycle Figure 2 shows the simplified global carbon cycle in Gt of carbon per year (1 Gt = 1 Pg = 1015 g). One can see that the ocean is the largest sink. The various carbon sinks present opportunities for geoengineering. Subsets of special techniques are biogeoengineering and Arctic geoengineering. In biogeoengineering, plants or other living organisms are used or modified to beneficially influence the climate on Earth, e.g., by creating carbon sinks. An example is iron fertilization of the oceans. Iron is a growth-limiting factor, so fertilization would be expected to produce more algae, taking up CO2, like land-based biomass. “Global dimming” is an aspect that could be exploited for climate engineering. Monoterpenes from boreal forests (Rinnan et al. 2011; Aaltonen et al. 2011) were found to contribute to global dimming (cooling), apart from being a CO2 sink, so tree planting would be a working biogeoengineering approach. Global dimming, generally, is caused by an increase in particulates such as sulfate aerosols in the atmosphere due to human action. The effect of anthropogenic global dimming has interfered with the hydrological cycle by reducing evaporation and so may have reduced rainfall in some areas. Global dimming also creates a cooling effect that may

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Fig. 2 Simplified representation of the global carbon cycle. The values inside the boxes are standing stocks (in Pg C); the arrows represent annual fluxes (Pg C/y). The black arrows and numbers show the preindustrial values of standing stocks and fluxes; the red arrows and numbers indicate the changes due to anthropogenic activity (Source: Cole 2013)

have partially counteracted the effect of greenhouse gases on global warming. With sulfur levels in fuels being further reduced, e.g., for ships, the global warming contribution of combustion emissions will increase in the future. Arctic geoengineering focuses geographically on the Arctic, which plays a key role in maintaining current climate due to its albedo and stored methane. The Arctic ice is disappearing quickly, though, and concepts have been envisioned to support ice buildup.

Impacts of Climate Engineering The targeted impact of climate engineering is to bring down global air and surface temperatures. Undesired side effects might also occur, though, particularly in SRM schemes. Several researchers have run computer models to investigate the effect of blocking part of the solar radiation. Shading the Sun would, according to the models,

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reduce the global temperatures, but also lead to profound changes to precipitation patterns including disrupting the Indian Monsoon (Shepherd 2009). Anthropogenic SO2 in the stratosphere at a level necessary to counteract the radiative forcing of human CO2 and CH4 could cut rainfall in the tropics by 30 % (Ferraro et al. 2014). Also, it would lead to acid rain. There is further concern that SO2 in the troposphere can harm the ozone layer; see also section “Stratospheric Sulfate Aerosols.” Evidence that such action would in fact result in a net cooling was provided by the eruption of the volcano Mt. Pinatubo in the Philippines in June 1991. It resulted in a 0.5  C variation in the Earth surface temperature, due to the effect of sulfate aerosol-induced albedo enhancement. However, already by the year 1995, the effect had vanished, and the temperature returned to the former value (Gomes and de Araújo 2011). Note: Another volcanic event with transient, global impact on the climate was the 1815 eruption of Mount Tambora in Indonesia, which led to a “year without summer” and famine due to reduced crop yields (Stilgoe et al. 2013a). Sticking with this geoengineering example, potential side effects of SO2 injected into the stratosphere by, e.g., balloons, artillery, or jet planes, are: • • • • • • •

CO2 emissions from the missions Litter, e.g., from returning balloon shells Noise, e.g., from the artillery Depletion of ozone Regional droughts, e.g., in Africa and Asia from weaker monsoon activity Impact on cloud formation, particularly cirrus clouds, with unpredicted effects Acidic rain, leading to further ocean acidification, and other effects on the ecosystem • Whitening of the sky due to aerosols, more diffuse radiation • Less yield from solar energy collectors, impacting renewable energy production • Temperature changes in the stratosphere, influencing atmospheric circulations in the troposphere with unknown effects The Geoengineering Model Intercomparison Project (GeoMIP) around Ben Kravitz assesses the projected impacts of geoengineering by different climate models, focusing on SRM (http://climate.envsci.rutgers.edu/GeoMIP/publications. html). In 2013, 12 climate models simulating quadrupled atmospheric carbon dioxide levels and a corresponding reduction in solar radiation were compared (Kravitz 2013). In Fig. 3, an overview by the Convention on Biological Diversity (http:// www.cbd.int/convention/) shows which intended and unintended effects might result from geoengineering. It is expected that both SRM and SDR would affect biodiversity and ecosystems, which finally have a significant impact on human well-being. As stated above, quantification of intended and also identification of unintended consequences of SRM and to a lesser extent ERM and CDR techniques are difficult to achieve. On the benefits, risks, and costs of stratospheric geoengineering, see e.g., Robock et al. (2009).

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Anthropogenic emissions 3

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Fig. 3 Conceptual overview of how greenhouse gas emission reductions and the two main groups of geoengineering techniques may affect the climate system, ocean acidification, biodiversity, ecosystem services, and human well-being (Numbers refer to the chapters in the cited source, from which reproduction with permission was made (Secretariat of the Convention on Biological Diversity 2012))

Legal, Moral, and Social Issues “Whose hand will be on the planetary thermostat?”(Robock 2014). Action by one nation would impact climate globally, but who is entitled to enact and control climate engineering? Would the target of climate engineering be to reduce future global warming, i.e., to maintain current temperatures; to limit global warming to, e.g., 2 K; or to bring back temperatures to preindustrial levels? Who would set the target? These questions cannot be answered at this point in time, as outlined in this section of this chapter.

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Legal Issues Signed by 150 government leaders at the 1992 Rio Earth Summit, the Convention on Biological Diversity is dedicated to promoting sustainable development. Conceived as a practical tool for translating the principles of Agenda 21 (a voluntarily implemented action plan of the United Nations with regard to sustainable development), it states “that no climate-related geo-engineering activities that may affect biodiversity take place, until there is an adequate scientific basis on which to justify such activities and appropriate consideration of the associated risks for the environment and biodiversity and associated social, economic and cultural impacts, with the exception of small-scale scientific research studies” (http://www.cbd.int/convention/). Thereby, private or public experimentation and adventurism are avoided, yet research is possible. R&D in climate engineering is justified so that man understands his options once a said environmental tipping point has been surpassed (contingency planning to have “something on the shelves” when needed). Research priorities in this respect are worked out in Shepherd (2009).

Moral and Social Issues While anthropogenic greenhouse gas emissions are an unwanted side effect, climate engineering constitutes a large-scale, intentional effort to alter the climate. Responsibilities and global political governance are not clear. It is conceivable that different governments have different targets for global temperatures. Some areas of the world show higher crop yield in an elevated temperature scenario, for instance. So actions by one country to alter the climate, motivated by expected local benefits, might result in war. Multilateral commitments and agreements over time periods of several 100 years would be necessary, as this is the time that, e.g., SO2 from climate engineering would have to remain in the stratosphere in a delicate balance with anthropogenic CO2 emissions it is offsetting, so there would also have to be imperative controls over CO2 levels at the same time. The governance of emerging science and innovation is discussed in Stilgoe et al. (2013b), citing canceling the geoengineering project “SPICE” (see below) as an example. For public perception of geoengineering, see Corner et al. (2013) and Sikka (2012). Governance principles concerning climate engineering were also elaborated in the 2010 Asilomar International Conference on Climate Intervention Technologies (http://climate.org/resources/climate-archives/conferences/asilomar/report.html).

Preliminary Climate Engineering Field Experiments Climate engineering has a global scale, and documented field trials to date are very limited. Some concepts can hardly be tested at all.

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Fig. 4 Whitening the mountain Chalon Sombrero in Peru in a geoengineering pilot project (Source: Collyns 2010)

One of the largest experiments, known as LOHAFEX, was an Indo-German fertilization experiment in 2009, in which six tonnes of iron as iron sulfate solution was spread over an area of 300 km2 (Ebersbach et al. 2014) in the South Atlantic. It was expected to trigger an algal bloom, resulting in CO2 update and some of the algae ending up in the ocean bed as carbon sink. A much disputed, similar experiment was carried out in July 2012 by entrepreneur Russ George, who put approx. 100 t of iron sulfate into the Pacific Ocean several hundred miles west of the islands of Haida Gwaii/Canada. The intention was to increase the production rate of phytoplankton for salmon fishing (Sweeney 2014). In 2005, a pilot project in Switzerland to cover a glacier with a reflective foil was carried out. On the Gurschen glacier, it was found that the blanket reduced the melding by 80 % (Pacella 2007). More trials on an area of more than 28,000 m2 were done on the Vorab glacier (Pacella 2007). Painting the Andes: In 2009, the World Bank has awarded a seed grant to 26 innovative climate adaptation projects, selected from 1,700 proposals (World Bank). Among them was one idea from Peruvian inventor Eduardo Gold to whiten the Chalon Sombrero peak in the Andes (Collyns 2010). This pilot project (see Fig. 4) has received positive media attention. In the UK SPICE project (Stratospheric Particle Injection for Climate Engineering, 2015), a trial balloon flight was planned; see Fig. 5. The idea was to send a balloon 1 km into the sky and to eject water droplets. These droplets should create clouds, increasing the albedo. The experiment had to be canceled due to opposition from environmental groups (Shukman 2014; Zhang et al. 2015). Tree planting (reforestation, afforestation) (Zomer et al. 2008; Schirmer and Bull 2014; Trabucco et al. 2008) and peatland restoration (Bonn et al. 2014) activities are

Geoengineering for Climate Stabilization Fig. 5 Concept of the SPICE experiment (Source: Vidal 2011)

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Tethered boom delivery system Balloon

Fine spray of water droplets

1km Pipe

Pipe tethered to a ship

being considered in several parts of the world. According to the IPCC, reforestation refers to establishment of forest on land that had recent tree cover, whereas afforestation refers to land that has been without forest for longer time periods (IPCC 2015). Cool roof experiments: In cities, the temperature is typically 1–3  C higher than in the surrounding countryside, due to, e.g., heat-absorbing infrastructure such as dark asphalt parking lots and dark roofs (Oke 1997). By increasing the reflectivity, more radiation is sent back into space, and energy costs (air conditioning) can be reduced. Pilot projects are, e.g., the “White Roof Project” (http://www. whiteroofproject.org/) and New York’s “NYC  CoolRoofs” (http://www.nyc.gov/ html/coolroofs/html/home/home.shtml). Keeping groundwater level and salinity low. In Australia, rising levels of salty groundwater pose a problem for farmers. By pumping that groundwater into shallow evaporation ponds, crops are protected, with a positive side benefit of increased albedo (Edmonds and Smith 2011); see Fig. 6 (note that “geoengineering” is a side effect here). Edmonds and Smith (2011) also describe reflective covers on water bodies to prevent evaporation losses. According to Ming et al. (2014), 40–50 % of the water stored in small farm dams of “hot” countries may be lost due to evaporation. Such covers, as a side effect, increase the albedo and thereby contribute to climate change mitigation; compare Fig. 7.

Proposed Strategies for Climate Engineering Potential approaches are surface based (e.g., albedo modification of land or ocean), troposphere based (e.g., cloud whitening), stratosphere based (e.g., injection of SO2 or Al2O3), and space based (e.g., gigantic space-based mirrors, lenses, or sunshades). Below, several selected concepts are briefly introduced.

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Fig. 6 Image of a 700  900 m2 wheat field in Western Australia in which a 66 m diameter evaporation pond was created (Source: Edmonds and Smith 2011)

Fig. 7 Reflective evaporation covers on a mine reservoir at Parkes in Australia (Edmonds and Smith 2011)

Carbon Dioxide Removal (CDR) As mentioned above, the first set of concepts can be summarized as CO2 removal schemes (CDR) as visually summarized in Fig. 8.

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Fig. 8 Depiction of some popular CDR concepts. See text for details (Source: Climate 2010)

Carbon capture and storage (CSS) and carbon sequestration projects are out of the scope of this chapter; see elsewhere in this handbook and in the DOE/NETL CO2 capture and storage roadmap (2010). Other CDR concepts include (Shepherd 2009): • • • •

Use of biomass as carbon sink. Protection of and (re)creation of terrestrial carbon sinks such as grasslands. Enhanced weathering to remove CO2 from the atmosphere. Direct capturing of CO2 from the ambient air (concepts to wash CO2 out of the atmosphere include “artificial trees” and scrubbing towers), known as industrial air scrubbing (IAS) or direct air capture (DAC) (de_Richter et al. 2013). Costs are expected to be prohibitively high (House et al. 2011). • Enhancement of oceanic uptake of CO2, for example, by fertilization of the oceans with naturally scarce nutrients such as iron or by changing ocean currents. • Biochar (when biomass is pyrolyzed, char (biochar) remains. It can be mixed with soil to create terra preta, a carbon sink (Hyland and Sarmah 2014)).

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There are numerous other concepts, such as removing (dark) vegetation from the mountain tops or changing the composition of ship and aircraft exhaust. The interested reader will find a collection of ideas in various internet sources such as Wikipedia. Out of the concepts presented from (Shepherd 2009) above, two are described briefly as an example.

Enhanced Weathering In enhanced weathering, inorganic matter is used to take up CO2, a process that occurs in nature, but slowly. For instance, if carbonates are formed, CO2 is stored long term. This chemical approach to geoengineering involves land- or oceanbased techniques. Examples of land-based enhanced weathering techniques are in situ carbonation of silicates such as ultramafic rocks (ultrabasic rocks, which are igneous and metaigneous rocks with a very low silica content and a high magnesium and iron content). Ocean-based techniques involve alkalinity enhancement of the sea, e.g., by grinding, dispersing, and dissolving olivine, limestone, silicates, or calcium hydroxide against ocean acidification and for CO2 sequestration. Enhanced weathering is considered as one of the most cost-effective options. CarbFix (2015) is a feasibility project of enhanced weathering in Iceland. For details on mineral carbonation/mineral sequestration, see, e.g., Herzog (2002) and Goldberg et al. (1998). Bioenergy with Carbon Sequestration (BECS), Biochar, and Wood Burning BECS is a hybrid approach in which bioenergy crops are grown and used as fuel, and the CO2 emissions are captured and stored (see CCS elsewhere in this handbook). Biochar and BECS could together contribute a carbon sink of 14 GtC/year by 2100 (Edenhofer et al. 2012). The concept of burying wood in anoxic environments (e.g., deep in the soil) is that decomposition would be much slower, providing a long-term carbon sink; compare Fig. 9. According to Zeng (2008), the long-term carbon sequestration potential for wood burial is 10  5 GtC per year, and currently about 65 GtC is available on the world’s forest floors in the form of coarse woody debris suitable for burial. The cost for wood burial is estimated to be lower than the typical cost for power plant CCS. Approx. 100 tC are bound as coarse wood carbon from a typical mid-latitude forest area of 1 km2 in 1 year (Zeng 2008). However, there is the potential for counterproductive emissions of methane from anaerobic decomposition of the buried wood. It is estimated that, by storing carbon in deep sediments, deep ocean sequestration can capture up to 15 % of the current global CO2 annual increase. It was hence suggested to dump crop residues in the deep ocean (Strand and Benford 2009).

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Fig. 9 Schematic diagram of forest wood burial and storage (Source: Zeng 2008)

1 Space Stratosphere

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1. Space-based reflective mirrors 2. Stratospheric aerosol injection 3. Cloud-brightening 4. Painting roofs white 5. Planting more reflective crops 6. Covering desert surfaces with reflective material

Fig. 10 Depiction of solar radiation management (Source: Climate 2010)

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Solar Radiation Management (SRM) The second set of techniques for climate engineering is the SRM category. SRM stands for “solar radiation management” or “sunlight reflection methods;” compare Fig. 10. Four of such SRM concepts are explained below.

Cloud Reflectivity Modification This approach considers altering the reflectivity of clouds in two ways: thinning of cirrus clouds and brightening (low) marine clouds. High, cold cirrus clouds let sunlight penetrate but capture infrared radiation. Hence, thinning or removing cirrus would have a net cooling effect on Earth. By contrast, low, warm clouds (stratocumulus, which cover approx. 1/3 of the ocean’s surface) reflect sunlight efficiently. This “cloud whitening” or “marine cloud brightening” could be achieved with cloud condensation nuclei (CCN) such as fine seawater droplets. The effect is considered to be more pronounced on the sea than on the land, as clouds over the landmass have more (natural and anthropogenic) CCN available. Proposed schemes include seawater sprays produced by unmanned ship, ocean foams (Evans et al. 2010) from air bubble bursting, ultrasonic excitation (Barreras et al. 2002), and electrostatic atomization. Stratospheric Sulfate Aerosols SO2 is known to cause global dimming, as it leads to aerosol formation, and the aerosols reflect sunlight. The mechanism is that SO2 is oxidized to sulfuric acid, which is hygroscopic, has a low vapor pressure, and hence forms aerosols (Robock 2014). It was suggested to inject sulfur into the stratosphere as SO2, sulfuric acid, or hydrogen sulfide by artillery, aircraft, and balloons (Rasch et al. 2008). According to estimates by the Council on Foreign Relations, “one kilogram of well placed sulfur in the stratosphere would roughly offset the warming effect of several hundred thousand kilograms of carbon dioxide” (Victor et al. 2009). This approach was estimated to be over 100 times cheaper than producing the same temperature change by reducing CO2 emissions (Keith et al. 2010). The SO2 injection would have to be maintained, as tropospheric sulfur aerosols have a comparatively short atmospheric lifetime. Also, other particles have been considered, e.g., Al2O3. Space Lenses, Space Mirrors, and “Dyson Dots” Space-based concepts aim at transforming the solar constant into a controlled solar variable (Kennedy et al. 2013). They envision large space-based objects, which might be manufactured on the moon, mining local materials, or using material from asteroids. Concepts of giant lenses (Early 1989), dust rings (Bewick et al. 2013), and sunshades (Kosugi 2010) to block part of the Sun’s incoming radiation using the effects of reflection, absorption, and diffraction were worked out. A convex lens with 1,000 km in diameter is considered sufficient, and in a Fresnel embodiment, it would only be a few millimeters thick (Early 1989). Shading the Sun by approx. 55,000 orbiting mirrors with 100 km2 size, made from wire mesh, or by trillions of smaller mirrors (comparable to a DVD), was suggested (Ming et al. 2014); however, such

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Fig. 11 Dyson dot concept with “self-funding” master energy delivery to the Earth (Reproduced with permission from Kennedy et al. 2013)

concepts are widely viewed as unrealistic. Current engineering capabilities are far from being able to realize such science-fiction-like concepts, not speaking about the costs, which are estimated at a century worth of global domestic product of all nations combined (Ming et al. 2014). The “mirrors and smoke in space” concept was refined and coined “Dyson dots” (Kennedy et al. 2013). The concept is to place one or more large lightsail(s) in a radiation-levitated position sunward of the Lagrange point 1 (L1, SEL1). In this point, the gravitational forces on an object exerted by Earth and the Sun are equal. L1 is approx. 1.5 million km from Earth. A 700,000 km2 parasol in L1 would reduce insolation on Earth by at least 0.25 %. A photovoltaic power station on the sunny side of the parasol could “beam” energy to Earth via a maser (microwave laser) on the order of global demand, hence essentially funding the entire project. The “Dyson dot” concept is shown in Fig. 11. The expression “Dyson dot” is based on the concept of a “Dyson sphere,” a hypothetical megastructure imagined by Freeman Dyson in 1960, who speculated in a science article entitled “Search for Artificial Stellar Sources of Infrared Radiation” that advanced extraterrestrial civilizations could have housed in their star with a megastructure, maximizing energy capturing. A 0.25 % reduction in the Sun’s energy output was observed in the period of mid-sixteenth to mid-seventeenth century dubbed “sunspot cycle shutdown time,”

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Fig. 12 Impression of an L1 positioned dust cloud for space-based geoengineering (Source: Bewick et al. 2012)

“Maunder Minimum,” or “Little Ice Age,” so this order of magnitude is what space geoengineers are aiming at.

Dust Clouds Clouds of extraterrestrial dust placed in the vicinity of the L1 point are an alternative concept to thin-film reflectors, aiming at significantly reducing the manufacturing efforts. The material should be mined from captured asteroids, being moved by solar collectors or mass drivers (Bewick et al. 2012); see Fig. 12. For details on such a dust concept, see, e.g., Bewick et al. (2012). Dust for sunlight blocking might also be mined on the moon.

Other Greenhouse Gas Remediation Ideas There are many other geoengineering concepts than those introduced above, some of which are mentioned here:

CFC Destruction by Lasers Chlorofluorocarbons (CFC) are persistent in the atmosphere, having huge GWP, yet they are accessible via their photochemistry (Stix 1993). Extremely powerful lasers might be used to break up tropospheric CFC.

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Ocean Heat Transport Ocean heat transport (downwelling of ocean currents) is outlined in Zhou and Flynn (2005). This concept aims at changing oceanic currents to shovel heat energy to deeper regions of the ocean. Also, solar-driven heat pumps might be used to this end. Methane Remediation Since methane is also a GHG of big concern, other geoengineering concepts target reducing CH4 emission, e.g., by soil oxidation into CO2 (Tate 2015).

ERM and Energy Production Earth radiation management (ERM) aims at increasing the long wavelength radiation sent into space, which today is being trapped by GHG. ERM can be combined with energy production in so-called meteorological reactors (Ming et al. 2014). The term “meteorological reactor” stands for a climate engineering installation that fulfills two purposes: reduction of radiative forcing and energy production. Possible embodiments are: • • • • •

Solar updraft tower Solar downdraft energy tower Atmospheric vortex engine Heat pipes Radiative cooling, emissive energy harvesters (EEH) Figure 13 shows an overview of such ERM schemes.

Fig. 13 Principal longwave radiation targets of meteorological reactors (Source: Ming et al. 2014)

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Fig. 14 Two possible EEH designs. (a) In a thermal EEH, a heat engine operates between the ambient temperature and a radiatively cooled plate. (b) In an infrared rectenna EEH, the whole panel is at ambient temperature, but the circuit’s electrical noise is coupled to the cold radiation field via antennas (Source: Byrnes et al. 2014)

The “chimney effect” is used to create air motion, which can drive a generator. The hot air is moved into higher layers of the atmosphere, where it can radiate off heat energy. In Fig. 14, emissive energy harvesters (EEH) designs are depicted. For details on “meteorological reactors” in ERM mode, see Ming et al. (2014) and http://www.solar-tower.org.uk/meteorological-reactors.php.

Climate Engineering in the Context of Climate Change Mitigation and Adaptation Figure 15 is an illustration of the conceptual relationship between SRM and CDR with climate change adaptation and mitigation, in the context of the interdependent human and climatic systems. The Kaya identity (O’Mahony 2013) mentioned in the caption of Fig. 15 is based on Japanese scientist Kaya and can mathematically be expressed as F = pop * (GDP/pop) * (E/GDP) * (F/E), with F being global anthropogenic CO2 emissions, pop being global population growth, G the world GDP, and E the global energy consumption. Carbon emissions F can be estimated as the product of growth (pop), economic expansion (GDP/pop), energy intensity (E/GDP), and carbon efficiency (F/E).

Is It Geoengineering or Not? The term geoengineering expresses, as stated initially, deliberate large-scale intervention in the Earth’s climate system. CDR methods with a local to regional and/or low global impact are hence not real geoengineering approaches. The delineation is not exactly clear-cut. An attempt was made by the 2011 IPCC Expert Meeting on Geoengineering; see Fig. 16.

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Fig. 15 Illustration of mitigation, adaptation, solar radiation management (SRM), and carbon dioxide removal (CDR) methods in relation to the interconnected human, socioeconomic, and climatic systems and with respect to mitigation and adaptation. The top part of the figure represents the Kaya identity. REDD stands for Reducing Emissions from Deforestation and Forest Degradation (Source: Edenhofer et al. 2012)

As Fig. 16 shows, ocean fertilization and ocean alkalinization are seen as geoengineering-type projects, as can be large afforestation/reforestation.

Discussion Having presented some geoengineering concepts, a discussion about their targeted effectiveness and commercial viability has to be carried out. Geoengineering appraisals in their context frames were studied in Bellamy et al. (2012), where “climate emergency,” “insufficient mitigation,” and “climate change impacts” were cited most often. The appraisals were found to be mostly expert analytic, involving calculations/computer modeling, expert reviews and opinions, economic assessments, and MCA (multi-criteria analysis) (Bellamy et al. 2012). This study also investigated the frequency of different geoengineering proposals; see Fig. 17. Stratospheric aerosols and space reflectors were investigated most often. There was a balance between solar- and carbon-based concepts. A qualitative ranking of storage potentials and local vs. global impact is shown in Fig. 18.

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Fig. 16 Scale and impact are important determinants of whether a particular CDR method and specific application should be considered as geoengineering or not. Note that the specific positioning of the different methods is only illustrative and does not constitute a consensus view of the experts participating in the 2011 IPCC Expert Meeting on Geoengineering that produced this chart (Source: Edenhofer et al. 2012)

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n o o n n g n n o o n g o o o n g er g e ls rs so to ag tio ed tio ed tio ed tio itio ed itio ed ed llin llin tio ed rin rin th ro flec stor ilisa alb sta alb duc alb stra dd alb dd alb alb we we ilisa alb the the O e a rt a d t p rt n a a a re d o e re n d d d rt fe lou ffo rba r pr lan qu ate se rus lan en dow e u fe lou we we ric ce an A U a op se on De ho ss lem e nc gen al c ed ed he pa re Iron al c h t a r a p c c c n t p b c C o r h r S ptu s ic oos G Se han En itro ogic han han to rb Ca a an Bi N ol ra n n Ph ca rc ch En i St e h Bi ial e n e A it M w tr cea s gy rre O er Te en o Bi Geoengineering proposals

Fig. 17 Relative abundance of geoengineering concepts in the scientific literature. “Others” were cited no more than once (Source: Bellamy et al. 2012)

Fig. 18 The relative estimated total storage potential for emission reduction and sink creation projects at different scales (Source: Edenhofer et al. 2012)

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Fig. 19 Preliminary overall evaluation of the geoengineering technique (Shepherd 2009)

As Fig. 18 shows, concepts with a large estimated global potential are carbon sinks, with the ocean being particularly important. For these, transboundary issues arise. Blue carbon is the carbon captured by the world’s oceans and coastal ecosystems (Blue Carbon Initiative 2015). An overall evaluation in terms of affordability and effectiveness, reproduced from Shepherd (2009), is shown in Fig. 19. The color of the bullets in Fig. 19 indicates the level of system safety (red = low; yellow = medium; green = high), whereas the size of the bullets relates to the timeliness of the techniques (large = quick; small = slow). One can see from Fig. 19 that urban surface albedo enhancements like “white roofs” are safe, but lack effectiveness technically and financially. Afforestation, also a safe technique, is affordable, but has a lower effectiveness potential than stratospheric aerosols, which are more risky, are more costly, and take more time. Such comparison charts can help define research priorities. Results from another, similar study are depicted in Figs. 20 and 21. Lenton and Vaughan (2009) concludes “only stratospheric aerosol injections, albedo enhancement of marine stratocumulus clouds, or sunshades in space have the potential to cool the climate back toward its pre-industrial state. Strong mitigation, combined with global-scale air capture and storage, afforestation, and bio-char production, i.e., enhanced CO2 sinks, might be able to bring CO2 back to its pre-industrial level by 2100, thus removing the need for other geoengineering.” A third study (Goes et al. 2010) which is being presented here has compared four scenarios: BAU (business as usual), CO2 abatement, intermediate geoengineering (next 50 years), and continuous geoengineering from the present until 2150; see

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Fig. 20 Schematic overview of the climate geoengineering proposals considered. Black arrowheads indicate shortwave radiation; white arrowheads indicate enhancement of natural flows of carbon; gray downward arrow indicates engineered flow of carbon; gray upward arrow indicates engineered flow of water; dotted vertical arrows illustrate sources of cloud condensation nuclei; and dashed boxes indicate carbon stores (Source: Lenton and Vaughan 2009)

Figs. 22 and 23. The two geoengineering scenarios deploy stratospheric aerosol injection. CO2 emissions are assumed to be equally increasing in all scenarios except the abatement one. Two key observations from this study (Goes et al. 2010) are: • Radiative forcing in the “intermediate geoengineering” scenario would reach the same levels as that in the BAU scenario soon after the geoengineering was stopped. • Compared to the BAU scenario, a temperature rise of up to 1.5 K per decade, as opposed to less than 0.5 K per decade, would result. Such a strong change might finally be even worse for flora and fauna – and humans than a steady increase. Figure 23 gives projections on the costs of the four scenarios. As one can deduct from Fig. 23, damage and total costs of the BAU and intermediate geoengineering scenarios are highest, whereas the continuous geoengineering scenario presents itself as the economically most favorable one. As the authors conclude, aerosol geoengineering for CO2 abatement can be an economically ineffective strategy. Failure to sustain the aerosol forcing can lead to huge and abrupt changes to the climate: “Substituting aerosol geoengineering for greenhouse gas emissions abatements constitutes a conscious risk transfer to future generations, in violation of principles of intergenerational justice which demands that present

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Fig. 21 Summary of estimates of the radiative forcing potential of different climate geoengineering options from Lenton and Vaughan (2009). The potential of longwave (CO2 removal) options is given on three different time horizons, assuming a baseline strong mitigation scenario. The rightward pointing arrows, which refer to mirrors in space, stratospheric aerosols, and air capture and storage on the year 3,000 timescale, indicate that their potential could be greater than suggested by the diamonds (which in these cases represent a target radiative forcing to be counteracted: 3.71 W/m2 due to 2  CO2 = 556 ppm for the shortwave options and 1.43 W/m2 due to 363 ppm CO2 in the year 3000 under a strong mitigation scenario) (Source: Lenton and Vaughan 2009)

generations should not create benefits for themselves in exchange for burdens on future generations” (Goes et al. 2010).

Conclusions As this brief, introductory chapter to geoengineering has shown, several concepts that at first sight look tempting to “quickly fix global warming” have been developed. Ideas range from more tree planting to huge constructions in space, they include techniques to substantially alter the albedo of manmade objects, deserts, or mountains, and they consider injecting vast amounts of chemicals into the ocean and/or the stratosphere. At the present time, the consequences of such measures, and even the magnitude of their very effect, are hard if not impossible to predict, possibly generating huge risks from irreversibly messing up the complex climate system of our Earth for centuries, altering rainfall patterns, and provoking severe military activities, to name but a few possible side effects. Yet, climate engineering poses an option to deal with the impending aggravation of climate change, and once scientists know more about the various options, one or the other of them might in fact become a viable support in global climate change mitigation and adaptation

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Fig. 22 Radiative forcing (panel a), global mean atmospheric CO2 (panel b), global mean surface temperature change (panel c), and the rate of global mean surface temperature change (panel d) for BAU (circles), abatement (dashed line), intermittent geoengineering (crosses), and continuous geoengineering (solid line). Note that these results neglect potential economic damages due to aerosol geoengineering forcing. BAU business as usual, GWP gross world product (Source: Goes et al. 2010)

Fig. 23 Economic damage of climate change (panel a), total costs (i.e., CO2 abatement costs and climate change damages cost), abatement, (panel b), fraction of CO2 abatement (panel c), and per capita consumption (panel d) for BAU (circles), optimal abatement (black dashed line), intermittent geoengineering (crosses), and continuous geoengineering (solid line). Note that these results neglect potential economic damages due to aerosol geoengineering forcing. BAU business as usual, GWP gross world product (Source: Goes et al. 2010)

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measures to bring the anthropogenic impacts back under control. On the question of geoengineering ethics, Alan Robock concludes that “in light of continuing global warming and dangerous impacts on humanity, indoor geoengineering research is ethical and is needed to provide information to policymakers and society so that we can make informed decisions in the future to deal with climate change. This research needs to be not just on the technical aspects, such as climate change and impacts on agriculture and water resources, but also on historical precedents, governance, and equity issues. Outdoor geoengineering research, however, is not ethical unless subject to governance that protects society from potential environmental dangers. . .Perhaps, in the future the benefits of geoengineering will outweigh the risks, considering the risks of doing nothing. Only with geoengineering research will we be able to make those judgments” (Robock 2012). So to conclude, one can say that climate engineering is an interesting topic of research, and CDR techniques that are less risky than SRM techniques might complement conventional climate change mitigation actions. For approaches with global impact, clear governance rules need to be established and enforced.

Outlook Research of geoengineering should be enhanced, as recommended, e.g., by the UK Royal Society, the American Meteorological Society, the American Geophysical Union, the US Government Accountability Office, and prominent scientists (Robock 2014). Unrealistic and potentially dangerous concepts will be abandoned, and new, innovative ones emerge, possibly providing new options for climate change mitigation and adaptation.

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Social Efficiency in Energy Conservation Patrick Moriarty and Damon Honnery

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Social Efficiency: Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Passenger Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Freight Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Social Efficiency: Buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Social Efficiency: Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Global energy use, fossil fuel carbon dioxide (CO2) emissions, and atmospheric CO2 levels continue to rise, despite some progress in mitigation efforts. Improving energy efficiency is seen as an important means of reducing emissions, but absolute reductions in global energy use remain elusive because of continued growth in the numbers of important energy-using devices such as transport vehicles, and energy rebound. Limiting the rise in average surface temperature above preindustrial to 2  C is widely regarded as the limit for avoiding dangerous anthropogenic climate change. Given the magnitude of CO2 emission reductions necessary for this limit to be met, other approaches are needed for reducing energy use and its resultant emissions. This chapter discusses social efficiency (nontechnical means for reducing energy use) and stresses the social P. Moriarty (*) Department of Design, Monash University, Melbourne, VIC, Australia e-mail: [email protected] D. Honnery Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, VIC, Australia e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_73

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and environmental context in which energy consumption occurs in various sectors. Three important sectors for energy use, transport, buildings, and agriculture, are used to illustrate the potential for social efficiency in energy reductions. We argue that by focusing more clearly on the human needs energy use is meant to satisfy, it is possible to find new, less energy-intensive ways of meeting these needs. Abbreviations

ABS CO2-eq EIA EJ GHG GJ Gt IEA IPCC IT MJ OECD p-km SBJ t-km UK v-km

Australian Bureau of Statistics Carbon dioxide equivalent Energy Information Administration (US) Exajoule (1018 joule) Greenhouse gas Gigajoule (109 joule) Gigatonne (109 tonne) International Energy Agency Intergovernmental Panel on Climate Change Information technology Megajoule Organisation for Economic Co-operation and Development Passenger-km Statistics Bureau Japan Tonne-km United Kingdom Vehicle-km

Introduction Most studies on energy efficiency focus on technical efficiency measures such as megawatt-hour output of electricity per megajoule (MJ) of primary energy input for a power station, or vehicle-km per MJ of fuel input for a car. While the potential for technical efficiency improvements in energy-consuming devices is large (Cullen et al. 2011) and efficiency gains are expected to be a major factor in future carbon mitigation scenarios (Van Vuuren et al. 2011a, b), the results to date have been disappointing. Many barriers, both technical and socioeconomic, hinder the implementation of energy efficiency policies. Global energy use and fossil fuel CO2 emissions continue to grow (BP 2015), resulting in a steady climb in atmospheric CO2 levels. Further, energy efficiency is subject to the well-known rebound effect. Rebound occurs because efficiency improvements (e.g., in light bulbs or passenger cars) lower the cost of operation, either encouraging more use of the energy-using device or allowing the money so saved to be spent on other energy-using goods or services (Druckman et al. 2011; Moriarty and Honnery 2015). A related concept is the demonstration effect of present lifestyles in high-income countries on the

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expectations of residents of industrializing countries. If their ownership of energyintensive goods such as private vehicles or air conditioners rises to levels near those prevailing in high-income countries, any efficiency gains will be swamped by rising global use. Technical energy efficiency is important for carbon mitigation, but needs to be supplemented by nontechnical measures for deep carbon reductions. Energy efficiency measures are discussed in detail in the chapter “▶ Energy Efficiency: Comparison of Different Systems and Technologies”. It is not enough that the energy (or carbon) intensity of economies – primary energy (or carbon) consumed per unit of gross national income – be reduced; absolute levels of fossil fuel energy must also be greatly cut. As used here in the context of energy conservation, the term social efficiency refers to a system-based approach that stresses the social and environmental context in which energy consumption occurs in various sectors. As Haas et al. (2008) have stressed, households and organizations do not use energy for its own sake; they use it to enjoy the energy services it provides. Put simply, social efficiency will refer to nontechnical means for reducing energy use. As discussed, technical efficiency improvements are made by getting more output from a given energy input, such as electric output per unit of fossil fuel input energy; social efficiency improvements, on the other hand, are made by getting more social “value” from each unit of the output of an energy-using device (Moriarty and Honnery 1996, 2014). It is instructive to compare approaches in climate change modeling and energy efficiency studies. Climate scientists have utilized general circulation models for decades and, more recently, coupled carbon-climate models. Such modes have been used to show, for example, that afforestation could exacerbate climate change (Keller et al. 2014). The newly grown forests would decrease the albedo (the fraction of the insolation reflected directly back into space), offsetting the carbon sequestration in the trees. With the exception of the rebound literature, energy efficiency research, in contrast, mostly does not look at effects on other energy sectors. To illustrate both the approaches used and the potential for social energy efficiency, this chapter focuses on three important energy-using sectors as case studies: transport, both passenger and freight; energy use in buildings, both household dwellings and commercial buildings; and agriculture, particularly for food production. These case studies were chosen not only for their importance for global energy use and greenhouse gas (GHG) emissions but also because they illustrate different aspects of social efficiency. By examining social efficiency in these three sectors, we hope to point to new ways at looking at energy and GHG emissions reductions. In particular, we stress the need to examine more closely what energy is used for (Shove and Walker 2014). As energy researcher Benjamin Sovacool (2014) put it: “Academic researchers frequently obsess over technical fixes rather than ways to alter lifestyles and social norms.” The usual, technical approach is to find ways of performing existing tasks more efficiently; instead we ask whether the tasks should be done in the first place and whether the human needs underpinning energy use can be met in a different, less energy-intensive way.

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Social Efficiency: Transport In 2012, the fuel for all modes of vehicular transport, including both passenger and freight, accounted for 27.9 % of global final demand for energy, up from 23.1 % in 1973 (International Energy Agency (IEA) 2014). Transport is heavily reliant on fossil fuels (96.6 % in 2012) and global road vehicle numbers are still rising rapidly. GHG emissions from this sector are thus rising, and it will be very difficult for technical solutions alone to stop further rises, let alone greatly reduce them.

Passenger Transport The conventional measure of the passenger transport task is passenger-km (p-km). For example, 10 p-km is generated if one passenger travels 10 km or ten passengers each travel for 1 km. Transport efficiency in turn is measured as p-km per MJ of primary fuel. Measures such as miles per gallon and liters per 100 km are still widely used for vehicle efficiency, but suffer from two drawbacks. First, the useful output of passenger travel is p-km rather than vehicle-km (v-km); in other words, the occupancy rate is important. With this measure of output, buses can now be compared with car travel. Second, although liters per 100 km is useful for comparing the efficiency of various petrol or diesel-fueled vehicles, it is not useful for comparing electric-powered vehicles, whether for private or public transport, with vehicles that run on liquid fuels. But p-km/MJ of primary enables fair comparison of all passenger transport modes, regardless of energy source or vehicle carrying capacity (Moriarty and Honnery 2012). However, even though p-km is a more useful measure than v-km, transport is still mainly a derived demand. Although some travel, especially by car, is undertaken for its own sake, in most cases travelers undergo the monetary and time costs required in order to access out-of-home activities such as working, education, or shopping. Access to activities, not mobility, is the real purpose of transport; hence one measure of the social efficiency of passenger transport would be access per primary MJ of transport fuel. Obviously, all else being equal, doubling the occupancy rate of all vehicular transport should double the access achieved per primary MJ. Occupancy rates are covered in more detail in the chapter “▶ Reducing Personal Mobility for Climate Change Mitigation”. Of course, it is much easier to measure p-km than it is to measure access, which has a subjective component. As Halden (2011) has stated: “accessibility is an attribute of people and goods rather than transport modes or service provision.” Mobility may be easy to measure, but given that travel is mainly a derived demand, he further argued that it is difficult to say whether more travel is better than less. How can access be improved? The journey to work trip will be used to illustrate the possibilities. First, we need to define two terms, minimum average work trip length and actual average work trip length. For convenience, we will use the example of cities and assume that all workplaces within the city boundaries are filled by resident workers. The minimum average work trip length for any city will

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then be the average distance traveled to work if workplaces are fixed, but workers can change residences such that total travel to work for all city residents is minimized. The actual average work trip length is that calculated from origindestination studies of citywide work trip patterns. Clearly, total work travel will be less if the actual average distance is close to the minimum. Studies have shown that, in real cities, there is a large amount of “excess” work travel. For a range of US and Australian cities, actual work travel was found to be roughly twice the minimum. On the other hand, for a sample of Japanese and South Korean cities, actual work travel was much closer to the minimum (Moriarty and Honnery 2013). The much higher densities of the latter cities compared with US and Australian cities, and the accompanying traffic congestion, are important explanatory factors. However, even if excess work travel is very low, overall work travel could still be reduced in some cities. This happens if there is a mismatch between residences and workplaces – if, for example, workplaces are largely located in one area of a city and residents (and thus workers) in other areas. With the rise of the service sector (and the decline in manufacturing jobs) in Organisation for Economic Co-operation and Development (OECD) cities, this potential mismatch is disappearing. Jobs such as those in the education, health, retail shopping, and other service sectors serve a local area and so are found intermingled with residential areas. With manufacturing, in contrast, the intended market for the products is far wider, often national or even international in scope, and so did not need to be close to residential areas. The result of the rising share of service jobs is improvement in the balance of workplaces and resident workers at the local level (Australian Bureau of Statistics (ABS) 2013; Cervero 1996). For other trip types, access is more difficult to define. For shopping, access is not only a function of distance to the nearest shopping center but also the range of shops available. Authorities can and do improve resident access to services by strategic location of schools, parks, local government offices, and health centers, for example. As discussed in the chapter “▶ Reducing Personal Mobility for Climate Change Mitigation” (Section 7), if we lower the convenience of car travel in an attempt to reduce its external costs (e.g., air and noise pollution, GHG emissions, community disruption, traffic casualties), the balance between private travel and other modes will be fundamentally altered. In particular, nonmotorized modes will now be relatively more convenient, as well as faster and safer. Vehicular trips for different purposes will be combined more often, and preferred destinations for discretionary trips will change. In brief, if we remove the priority accorded to vehicular travel, especially by car, overall vehicular travel will fall. But access levels need not decline with reduced (vehicular) travel, since travel patterns and the intensity of use of various local services can be expected to change over time to maintain access levels. As Gabrielli and von Karman (1950) showed many decades ago, there is a tradeoff between speed and energy efficiency. Slower modes of transport are usually more energy efficient. So an important way of lowering the convenience of car travel is by speed reductions. This will not only reduce transport energy use but also traffic-related air and noise pollution. It will also reduce the frequency and severity

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of traffic accidents, both for vehicle occupants and for nonmotorized travelers. For the latter group, research has found that at “impact speeds of 32 km/h, only about 5 % of pedestrians are killed and injuries are minor. At 48 km/h, 50 % are killed and many are seriously injured, while at 80 km/h most do not survive the impact” (Moriarty and Honnery 1999, 2008). Similarly, vehicle impacts with other vehicles or roadside objects are reduced in both number and severity. These benefits can be used to justify lower speed levels. Even before the global financial crisis, land passenger travel per capita had started decreasing in a number of OECD countries (Millard-Ball and Schipper 2011). However, air travel continues its strong growth, except for Japan, where it has been falling since the year 2000 (Statistics Bureau Japan (SBJ) 2014). Globally, Airbus projects air travel to grow at an average rate of 4.7 % over the years 2014–2033, with international tourism a key driver (Airbus 2014). Hence, an important approach to reducing fuel use and GHG emissions in air transport is the substitution of more local for international tourist destinations. Why do so many people feel the need for international holidays and distant travel in general? One reason is the large and rising number of people, often from lower-income countries, working in wealthier countries (OECD 2014), who visit their families or friends in their home country. Another possible reason is the stress of modern industrial life and work, which impels people to take their vacations in distant locations to get away from this situation (Chen and Petrick 2013). What these examples do show is that global social and economic conditions form part of the explanation of the present high levels of travel. Finally, we need to explore the ways in which the new information technology (IT) affects travel behavior. Although this question has been explored for nearly four decades, no definitive answer has emerged. Dal Fiore et al. (2014) concluded, as others have, that the new IT, especially mobile technology, has the potential to both increase and decrease levels of passenger travel. Given that per capita vehicular travel levels are falling in many OECD nations, it is possible that either IT is now actively decreasing travel levels or that it is at least enabling people to cope with less travel.

Freight Transport In a similar manner to passenger transport, technical freight transport efficiency can be measured by tonne-km (t-km) of payload freight per MJ of primary fuel. Even more so than for passenger travel, the efficiency of the various freight modes varies by two to three orders of magnitude (Edenhofer et al. 2014), with air transport being by far the least energy efficient (but the fastest) form of freight transport. Although freight trucks in all weight classes have shown technical efficiency gains in recent years (in terms of t-km/primary MJ), there has also been a trend toward increased use of smaller freight vehicles for delivery. In Australia overall, but especially in urban areas, light commercial vehicles are carrying a rising share of total t-km (ABS 2013). In London, the same trend has been found and is expected

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to continue out to the year 2050 (Zanni and Bristow 2010). Such trends undo some of the efficiency gains in truck freight transport. “Just-in-time” logistics is intended to keep parts inventory in manufacturing to a minimum. One consequence is that delivery frequencies have risen, and average loads have decreased. In effect, the private costs of inventory have fallen, but at the expense of increased external costs for highway freight. The list of external costs for road freight vehicles is similar to those already discussed for road passenger travel. The “occupancy rate,” or payload to tare weight ratio, for freight vehicles is just as important as for passenger travel. For specialized transport vehicles, such as oil or liquefied natural gas tankers, return loads are not feasible. For general goods carriers, two-way loadings can often be improved by better logistics planning, resulting in overall energy reductions (Edenhofer et al. 2014). But a prior question should be: is this particular freight transport needed at all? Most tonne-km of freight globally is moved by international ocean vessels. In most OECD countries, large volumes of products are either imported from other countries or from a different region of the same country. Yet similar products are often also made in the importing country or region. Consumer choice may be important; the point that is often overlooked is that the external costs of the necessary freight transport are unpaid, leading to underpricing of the imported goods. However, social changes already underway could move freight in a more sustainable direction. Recently much attention has been given to “food miles” and a general preference for locally produced goods, such as that sold at farmers’ markets. Food miles represent the distance between the point of food production and the point of consumption. Van Passel (2013) has shown that the concept needs to be modified to meet the charge of oversimplification. He argued for its extension to include freight transport externalities and even added that “all relevant economic, social, and ecological aspects should be taken into account.” Many existing food products are endorsed as variously being “fair trade,” “organically grown,” or “dolphin safe” and often have detailed nutritional information on their packets. In the future we could well see information such as the energy costs, kilometers of transport, and transport mode added to labels. Just as many countries worry about energy security, food security could also become more important for consumer preferences. This point is discussed further in the section “Social Efficiency: Agriculture.” As an example of the kind of systems thinking needed about freight, Schewel and Schipper (2012) have examined in detail “retail goods movement” in the USA, which in 2009 accounted for 6.6 % of US energy demand. They start with the point of import or of manufacture, followed by transport of these goods to a central warehouse, then distribution to individual shops, and finally transport, usually by car, of the purchased goods to the consumer’s final destination. They point out the conflict that can arise between freight transport energy costs and the final consumer’s energy costs. The trend toward fewer, larger stores has improved freight energy efficiency by allowing use of higher capacity trucks, but on the other hand, shoppers have had to drive further to the more widely spaced retail outlets. This retail case study shows that it is not always possible to separate passenger travel energy from freight transport energy.

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Social Efficiency: Buildings According to the Intergovernmental Panel on Climate Change (IPCC), in 2010 “buildings accounted for 32 % of total global final energy use” (Edenhofer et al. 2014). They were also responsible for 19 % of energy-related GHG emissions, or 9.18 Gt CO2-eq., when electricity-related emissions were included. Further, according to the IPCC, this “energy use and related emissions may double or potentially even triple by mid-century.” Although building energy is growing strongly in industrializing countries, in the core OECD countries, and the economies in transition, total building energy, both direct and indirect, has peaked (Edenhofer et al. 2014). But, as pointed out in the chapter “▶ Nontechnical Aspects of Household Energy Reductions” (Section 2)”, research has shown that occupant behavior can make a huge difference in domestic energy use and presumably for commercial buildings as well. Thus, it is becoming increasingly acknowledged that the social context in which building energy use occurs is crucial. Energy use in buildings is different from energy use in passenger transport in that it can and does occur without a human presence. In many cases, this raises few problems: refrigerators, freezers, and electric clocks are best left running continuously. But lighting and space heating/cooling in buildings, as well as computers, televisions, radios, and other appliances, are often left running, whether or not humans are there to enjoy the energy services provided. Even when not running, their standby energy use can be collectively important. Rather than measuring the power consumption of, for example, a television set, a possible measure of social efficiency might be the number of person-hours of actual viewing per hour the set is operating or per MJ of energy the device consumes. In OECD countries, by far the most important energy use in buildings is for space heating and cooling. Yet temperature controls for both heating and cooling could be set much closer to ambient levels, if clothing more appropriate to outside temperatures were worn indoors. For offices, it would mean that dress codes would need to change to allow more appropriate clothing for the season. One problem with fixed temperature settings is that it weakens the possibility of acclimatization to seasonal temperatures. For example, in hot regions of the world, Auliciems (2009) has reported that inhabitants preferred temperatures of “34  C or even higher.” This seasonal or regional acclimatization can be lost where air-conditioning of buildings is common. Passive solar energy is in some ways a misnomer, since its use requires a far more active participation by building occupants for space heating or cooling, for example, than does mechanical air-conditioning, which merely requires a thermostat setting. Passive solar can be used for lighting as well as thermal conditioning of buildings. For residences, use of passive solar involves the judicious opening and shutting of windows and blinds for temperature control and lighting and even varying the timing and use of cooking stoves and ovens, depending on whether the heat will add or subtract from thermal comfort. In some situations, it may be worthwhile investigating a change to hours of employment as a means of improving occupant comfort. Passive solar (in the form of wind energy) can also be used for

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clothes drying, but in many communities the use of outdoor clothes drying is still banned (Lee 2009), because of the claim that clothes lines are unsightly. The case study by Pilkington et al. (2011) in the UK showed the importance of occupant behavior for making the most of energy savings from passive solar design. The six terrace houses studied were of identical design, with superefficient insulation and “sunspaces.” They found that space heating use per occupant varied by a factor of 14. The main reason for the variation was that the higher energy users kept the internal doors open on winter days. Overall, the approach we advocate here can be contrasted with the “smart buildings” approach. Instead of predetermined settings, even if set by the occupants, we advocate that the building occupants actively respond to changing ambient conditions and adjust openings and shading accordingly. Just as for passenger transport, the occupancy rate of buildings is important in determining energy use. For residences, the occupancy rate has generally fallen in recent decades in most OECD countries, a consequence of both declining family size and rising incomes (e.g., ABS 2012; SBJ 2014; US Census Bureau 2012). The result is that dwelling space (in m2) per occupant has also risen, which tends to raise the energy for heating or cooling and lighting energy per occupant. If the trend toward declining household size could be reversed, not only would domestic energy efficiency rise but the occupancy rate for cars, and thus their energy efficiency, would also rise. Possibilities for increase include young adults staying at home longer and multi-family and group households. Both the latter groups are already common in many OECD countries, forming an increasing share of total households (e.g., ABS 2012). However, they have not been able to stem the overall fall in household sizes.

Social Efficiency: Agriculture Modern industrial agriculture is not only heavily reliant on energy, especially petroleum-based fuels, but is also a major producer of the GHGs methane and nitrous oxide, as well as CO2. Over the years 2000–2100, the IPCC estimated that average annual emissions of all GHGs from agriculture were in the range 5.0–5.8 Gt CO2-eq., compared with all-sector global 2010 emissions of 49 Gt CO2-eq. (Edenhofer et al. 2014). For these reasons alone, a change is needed in the way the world produces its food and fiber. But present agricultural methods also produce a host of other serious environmental problems and costs, including air and water pollution, loss of biodiversity, soil erosion, and soil salinity. The emphasis in industrial agriculture is on cost minimization per unit of output, given that its products must compete in the marketplace. However, these costs are usually viewed in a narrow accounting sense; the external costs (including GHG emissions and the other costs listed above) can often be ignored (Weis 2010), just as they often are for transport. These environmental costs, such as surface water pollution, will incur energy costs for their remediation (Moriarty and Honnery 2011).

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Ho and Ulanowicz (2005) investigated the energy return (in terms of food kilojoules) to energy input ratio for three types of agricultural systems: preindustrial, semi-industrial, and full-industrial. They found that the range of energy return ratios for the first two systems was 6.9–11.5 and 2.1–9.7, respectively. For the full-industrial agricultural systems, the ratio was little better than unity. It appears that trying to coax more output per hectare in industrial agriculture is subject to diminishing returns on the largely fossil fuel energy invested (Bos et al. 2013). While it may save land (and for industrial agriculture, land rent, real or imputed, is an important part of production costs), such systems carry higher energy costs, as well as higher general environmental costs. A narrow technical approach to GHG emissions from agriculture can also lead to conflicts for overall climate mitigation. Emphasis on CO2 emissions reduction may lead to nitrous oxide emissions from fertilizer being overlooked. And the projected use of corn stover for conversion to liquid fuels runs the risk of increased soil erosion and loss of soil carbon. Using corn stover (and other agricultural wastes) for bioenergy will enable some fossil fuel carbon to be left in the ground, but soil carbon losses could partly or wholly offset this benefit. Nevertheless, for agriculture, we have to look wider than these biophysical environmental impacts. McMichael (2011), in his article on multi-functionalism in agriculture and the “food sovereignty” movement, stressed that farming is not simply about food production, vital though this is. It is valued also for “its contribution to ecosystem management, landscape protection, rural employment, fostering farming knowledge, rural life, cuisine maintenance, and regional heritage.” The recognition of the importance of multi-functionalism means that agriculture has diverse impacts on overall energy use; agriculture’s energy use implications go far beyond that involved in food and fiber production, even after the energy costs of environmental damages are taken into account. Whether or not these energy costs incurred in other sectors are greater or less for alternative than for industrial agricultural practices is presently unknown; the important point is that they should be considered in the analysis of the total energy costs of agriculture. Farming is a social activity. When discussing passenger transport in section “Passenger Transport,” we emphasized the importance of the question: What is the purpose of transport? Similarly, we need to ask: What is the purpose of agricultural production? What are the products used for? The answer might seem obvious, since food is a basic human necessity, with no substitutes. However, according to the Food and Agriculture Organization (OECD/FAO 2014), in 2014, 34.4 % of the global grain harvest (estimated at 2.461 Gt) was fed to livestock, with a further 6.8 % used for liquid fuel production. The FAO expects the share of these nonfood uses to rise modestly in the future, together reaching 42.3 % of the grain harvest by 2023. Grain provides the bulk of the human diet. Other important agricultural foodstuffs used for feedstock for animals or for fuels include soybeans, oilseeds, and sugarcane. It is true that feedstocks are used to produce meat and dairy produce. However, in many OECD countries, including the USA and Australia, meat and dairy produce consumption is well in excess of the level regarded as producing a healthy diet. Further,

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one billion people still suffer dietary deficiencies of various kinds (Conway 2012). If the world shifted to a more vegetarian diet, this deficiency could be remedied. A related issue is food waste: much of the food that is produced and intended for direct human consumption is not eaten but wasted. For industrializing countries, food losses are greatest in the immediate post-harvest part of the food supply chain. In contrast, for OECD countries, the greatest overall food losses resulted at the food retailer, food services industry, and household levels (Parfitt et al. 2010). Atkinson (2014) has even claimed that half the food supplied in high-income countries is thrown away uneaten. As a solution, Parfitt et al. have called for “[C]ultural shifts in the ways consumers value food” and educating the public on the environmental costs of such food waste. Urban agriculture could also be an important means for reducing food production energy use. Teng et al. (2011) have estimated that, worldwide, around 800 million nominally urban residents are involved in food production, many of them full time, especially in low-income cities. But food production is also growing in popularity in OECD cities. Growing food in cities for the household’s own use reduces the relevant “food miles” discussed in section “Freight Transport” to zero, thus cutting freight energy use. According to Ackerman et al. (2014), urban farms can also potentially produce a range of social and economic similar to rural farms: “Urban agriculture not only provides a source of healthful sustenance that might otherwise be lacking, it can also contribute to a household’s income, offset food expenditures, and create jobs.” It also helps the environmental sustainability of the city, and larger urban farms can provide job training for underserved populations. Varying diets to match the growing seasons of locally produced fruit and vegetables can also reduce agricultural transport costs.

Future Directions If efforts at mitigating climate change in the coming decades are no better than those in recent decades, the world could be heading to a 4  C rise in average surface temperature above preindustrial values by the century’s end. Although some adaptative measures will be clearly needed, since further climate change is unavoidable given climate (and social) inertia, adaptation cannot be expected to cope with such a temperature rise. At a 4  C rise, the broadly linear response so far observed in various climate subsystems may break down (New et al. 2011), resulting in changes difficult to predict. Adaptation efforts would then be continuously aiming at a moving target. Hence, mitigation is the only long-term solution to climate change, and the later it is postponed, the more drastic will be the changes needed. There are encouraging signs that the world’s leaders are starting to appreciate how serious the climate change problem is. The European Union now binds its member states to reduce their GHG emissions by at least 40 % from 1990 levels by 2030, mainly through improved energy efficiency and more renewable energy. The world’s largest carbon emitter, China, has recently pledged to stabilize its GHG emissions by 2030, and the

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second largest, the USA, has promised that by 2025, its emissions will be 14–16 % less than those in 1990 (Anon 2014; Malakoff 2014). Although technical solutions will doubtless be the preferred approach to meet these targets, the latest IPCC report on mitigation (Edenhofer et al. 2014) has placed far more emphasis on nontechnical approaches than did the earlier IPCC reports. A key advantage of technical energy efficiency improvements is that they are a much better fit to the existing growth-oriented market economies than the social efficiency approaches discussed here. At present, most of these social efficiency measures are not politically feasible. But, in addition to the GHG reduction targets just discussed, changes are under way which will ensure that, in future, social efficiency is less “unthinkable” than it is today. Rockstro¨m et al. (2009) have discussed nine “planetary limits” which Earth is approaching, including climate change, ocean acidification, and the rate of biodiversity loss. To this list must be added the global depletion of fossil fuels, particularly oil, and of key minerals essential for industrial economies. The official position is still that reserves of fossil fuels are more than enough to sustain rising production for decades to come (BP 2015; Energy Information Administration (EIA) 2014). The IPCC (Stocker et al. 2013) projects that natural gas will be an important component of future energy use, being seen as especially valuable as a transition fuel to a low carbon future, because of its low CO2 emissions per unit of energy compared with coal or oil. In contrast to this optimistic position, recent research (Inman 2014) has cast doubt on the long-term future for shale gas, which was thought to have large reserves, particularly in the USA. A fine-grained analysis of US shale formations has found that the “sweet spots” where production is presently occurring are not typical of the formations as a whole. Overall, US natural gas production could peak within a decade and then fall sharply. If the US example serves as a model for shale gas production globally, the decarbonization of the energy supply could even be reversed. More generally, Schindler (2014) and others (e.g., Hӧӧk and Tang 2013) have stressed that oil, both conventional and unconventional, will peak soon, and natural gas and even coal will peak within a very few decades as well. If the potential for renewable energy to reduce GHG emissions is also less than anticipated, energy reductions will have to be the main approach for GHG reductions. In the future, then, we can expect to see greatly increased attention to system approaches to energy use, as well as more research that combines both technical and social approaches to energy, for the following reasons: • Rising energy costs for producing energy partly offset any gains in device energy efficiency. • Energy rebound significantly offsets any gains in energy efficiency. • As evidenced by the continued rise in atmospheric concentrations of CO2 and GHGs overall, the current emphasis on technical solutions is not working. • Many of the easily made technical energy efficiency measures have already been implemented; those remaining will be progressively more difficult to implement. In contrast, social efficiency potential has barely been tapped.

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This chapter has shown that it is usually very difficult to neatly compartmentalize the various energy sectors. Improving freight energy efficiency may negatively impact on passenger transport efficiency, for example. A large range of social practices impact on energy uses, as shown in this chapter. The efficiency of providing thermal comfort in buildings can be greatly improved by changes to the lifestyles of the occupants, including their clothing choices, and by the active use of passive solar energy. Agricultural practices can affect both transport energy costs and the energy costs of ecosystem maintenance. Choosing a diet with less meat and dairy products can greatly improve the overall energy efficiency of national and global food systems. If the world is to produce the carbon mitigation effort needed to avoid disruptive climate change, the question that will increasingly need to be asked is: What is the energy for? What we have termed social efficiency is an attempt to address this vital question.

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Measuring Household Vulnerability to Climate Change Sofie Waage Skjeflo

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climate Change Impacts on Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Taking into Account Adaptation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Household Heterogeneity and Market Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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This chapter summarizes research on the potential impacts of climate change on households, with a particular focus on contributions from different methodological approaches to understanding impacts for households in developing countries. Agriculture has been a central focus of this literature, both because of the sensitivity of the agricultural sector to a changing climate and also because of the importance of agriculture for the livelihoods of the poor. The literature review shows that developing countries are largely expected to be disproportionally hurt by projected changes in temperature, precipitation, and extreme events. On the other hand, the actual household level response to these changes is not well understood, and there are still gaps in the methodological approaches to understanding these issues. The recent literature reveals promising approaches that may complement and improve existing methods as more data becomes available.

S.W. Skjeflo (*) UMB School of Economics and Business, Norwegian University of Life Sciences, Ås, Norway e-mail: sofie.skjefl[email protected]; sofieskjefl[email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_74

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Introduction Despite remarkable achievements in improving standards of living and reducing the proportion of the world’s population living in poverty over the past century (Easterlin 2000; Chen and Ravallion 2010), securing basic needs remains a challenge for a large share of the global population. In 2010, the estimated share of the world’s population living in extreme poverty, defined as less than $1.25 per day measured in purchasing power parity terms, was about 20 % (World Bank 2014). In sub-Saharan Africa, the estimated share is almost 50 % (World Bank 2014). The majority of the world’s poor live in rural areas and rely on agriculture as their main livelihood (World Bank 2014). In the face of a changing climate, the challenge of improving the livelihoods of the poor may be even greater (IPCC 2014). The physical characteristics of agriculture create a strong link between the climate, agriculture, and poverty (Porter et al. 2014). Understanding the potential impacts of climate change therefore requires knowledge of how the rural poor might be affected, through which channels and how policies to improve livelihoods interact with these impacts. This chapter aims to give an overview of the literature on climate change impacts in developing countries, with a particular emphasis on agriculture in sub-Saharan Africa. The focus is on the contributions of different methodological approaches to understanding climate change in rural developing countries, as well as empirical findings. After discussing the direct impacts of changing temperature and precipitation trends, the household level response to these impacts is discussed. This requires an understanding of household characteristics and the context in which rural households interact, which is discussed in section Household Heterogeneity and Market Characteristics. The final section concludes with some challenges for future research.

Climate Change Impacts on Agriculture The most recent report from the Intergovernmental Panel on Climate Change (IPCC) concludes that the climate system is warming and that it is very likely that weather extremes have become more frequent and severe due to climate change (IPCC 2013). Projections show that continued greenhouse gas emissions will cause average temperatures to increase further, and there is high confidence that the near-term increase will be larger in tropical and subtropical regions than midlatitude regions. Projections for average precipitation are less clear. It is likely that precipitation variability will increase, but the projections are uncertain and vary considerably across regions in sub-Saharan Africa (IPCC 2013). Figure 1 shows the trends and projected trends in temperature and precipitation for Africa. The top left panel of the figure shows the trend in temperature from 1901 to 2012, where white areas are areas where there is insufficient data to conclude on any trend. The top right panel shows the projected difference in annual mean temperature between mid- and late twenty-first century and 1986–2005. The projections for the RCP8.5, or the

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Fig. 1 Observed and projected changes in annual average temperature and precipitation (top panel, left). Map of observed annual average temperature change from 1901 to 2012, derived from a linear trend [WGI AR5 Figures SPM.1 and 2.21] (bottom panel, left). Map of observed annual precipitation change from 1951 to 2010, derived from a linear trend [WGI AR5 Figures SPM.2 and 2.29]. For observed temperature and precipitation, trends have been calculated where sufficient data permit a robust estimate (i.e., only for grid boxes with greater than 70 % complete records and more than 20 % data availability in the first and last 10 % of the time period). Other areas are white. Solid colors indicate areas where trends are significant at the 10 % level. Diagonal lines indicate areas where trends are not significant (top and bottom panel, right). CMIP5 multi-model mean projections of annual average temperature changes and average percent changes in annual mean precipitation for 2046–2065 and 2081–2100 under RCP2.6 and 8.5, relative to 1986–2005. Solid colors indicate areas with very strong agreement, where the multi-model mean change is greater than twice the baseline variability (natural internal variability in 20-year means) and >90 % of models agree on sign of change. Colors with white dots indicate areas with strong agreement, where >66 % of models show change greater than the baseline variability and >66 % of models agree on sign of change. Gray indicates areas with divergent changes, where >66 % of models show change

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“business-as-usual” scenario, show up to 6 warming by the end of the twenty-first century in some areas of Africa. The RCP2.6 scenario, which is a scenario with aggressive mitigation efforts where emissions are near zero by the end of the century, also shows warming in Africa, highlighting that adaptation efforts may be needed even if emissions are cut dramatically. The bottom two figures show that observed trends and projected changes in precipitation are much less clear, with missing data preventing clear insights on past trends. Studies of impacts of climate change in developing countries have to a large extent focused on impacts through agriculture, both because of the importance of the agricultural sector in terms of production and employment and because of the sensitivity of this sector to climate change (Arndt et al. 2012). Early studies of quantitative impacts of climate change on agriculture relied on crop simulation models to simulate the impact of changing temperature, precipitation, and concentration of CO2 in the atmosphere on crop growth (Kurukulasuriya and Rosenthal 2003). These models capture the effect of genetic factors; climate variables such as solar radiation, maximum and minimum temperatures, and precipitation; as well as soil characteristics and farm management practices on yields (Parry et al. 1999). The models can also take into account the fertilization effect of increased CO2 concentration in the atmosphere, as explained by Darwin and Kennedy (2000), and different adaptation options can be simulated by exogenously changing planting dates, fertilization, irrigation, and so forth. Since these models require detailed input and are constructed for separate crops, the applications of crop models for country- or region-level studies of Africa are scarce (Hertel and Rosch 2010; Thurlow et al. 2012). Thurlow et al. (2012) therefore use a less detailed hydro-crop model in their study of impacts of climate variability on Zambian agriculture. Based on climatic and agronomic statistics from the past three decades, their hydro-crop model predicts 14–77 % maize yield losses in the most drought-prone agroecological zone during a severe drought event and up to 48 % yield losses during more moderate drought events. An application at a more aggregated scale is provided by Jones and Thornton (2003) who use global circulation model (GCM) output to generate weather scenarios for surfaces in Africa and Latin America up to 2055. The authors do not state which emission scenarios the simulations are based on. The GCM output is used to produce daily weather data that is used in the CERES-Maize crop model. The model simulations are run under the assumption of current varieties and farm practices, i.e., without adaptation. The results show that three quarters of the countries in Africa and

ä Fig. 1 (continued) greater than the baseline variability, but 0.3) to cause adverse ecological impacts. Oldenburg and Unger (2004) coupled subsurface and surface-layer transport models to further evaluate subsurface-atmospheric interactions. The above-ground surface layers were established in a numerical code by setting a porosity equal to unity and permeability values to mimic a logarithmic wind velocity profile. Simulation results were consistent with earlier simulations in that relatively large CO2 concentrations were observed in vadose-zone air (i.e., a CO2 mole fraction approaching unity); however, CO2 concentrations in the surface layers were orders of magnitude smaller than in the subsurface due to dilution in wind. Lower CO2 concentrations in the surface air were observed in simulations with greater wind speeds. Simulations also suggested that some CO2 would reenter the subsurface in the direction downwind of surface release due to dissolution in infiltrating water. In the event that significant leakage occurs from the injection zone, remediation may be required in groundwater and the vadose zone. Vadose-zone remediation strategies for gaseous CO2 would probably be similar to those currently used for volatile organic compound contaminated sites, which are primarily based on soil vapor extraction (SVE) systems. Zhang et al. (2004) evaluated several design strategies for SVE-based remediation of CO2. Two-dimensional radial simulations demonstrated that the use of a vertical well SVE system provided modest improvements to remediation efficiency when compared with natural attenuation or passive strategies. The use of an impermeable cover did not improve remediation removal rates. Three-dimensional simulations suggested that the use of complementary vertical and horizontal wells in the SVE system may improve remediation efficiency compared with strictly vertical or horizontal well cases.

Existing Codes Several codes have been developed for multiphase flow and transport problems (Schnaar and Digiulio 2009). Codes reported in the literature used for the modeling of CO2 sequestration can also be applied or modified to simulate CO2 migration after sequestrating in the coal seams. The codes include those developed primarily

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for petroleum reservoir engineering (STARS, Law and Bachu 1996; ECLIPSE, Zhou et al. 2004; Juanes et al. 2006; CHEARS, Flett et al. 2007; and CMG-GEM and CMG-IMEX) and codes developed at the US Dep. of Energy national labs for a range of multiphase flow and transport problems (CRUNCH, Knauss et al. 2005; TOUGH series, Finsterle 2004; Xu et al. 2006; Doughty and Pruess 2004; Doughty 2007). These codes vary not only in the physical processes and governing equations but also in numerical techniques such as the spatial discretization methods, iteration approaches, and gridding routines.

Measurements Measurements of chemical and physical properties include collecting site information and monitoring the migration of CO2 after sequestration. X-ray CT and SEM were used to observe the gas storage and transport in a coal sample from Zonguldak Basin (Turkey) (Karacan and Okandan 2001; Karacan and Mitchell 2003). In these studies, a coal sample was placed in an X-ray transparent core holder that enables applying confining pressure and gas pressure separately. Images were processed and quantified to calculate the porosity and gas adsorption rate at different local positions. These data, together with SEM pictures at the same local points, revealed that different lithotypes show different rate behaviors in consolidated sample. These data were also used to study the equilibrium isotherm parameters and to investigate the kinetics of the adsorption process for calculating the diffusivity of CO2 in different microlithotypes. Monitoring of geologically sequestered CO2 is required to protect the environment as well as the health and safety of the public. White et al. (2005) reviewed the monitoring and verification of geologically sequestered CO2. Migration of CO2 can be monitored using a variety of techniques. The simplest monitoring method is to measure the pressure (White et al. 2005). To monitor the possible leakage of CO2 and CH4 to the surface, it is necessary to determine the flux of these gases emanating from the earth above the coalbed on a seasonal basis before CO2 is sequestered (Klusman 2003). A monitoring technique that allows determination of a slow and/or intermittent leak of CO2 to the surface is required. This can be done using a tracer. A tracer is an extraneous substance that is added to the CO2. White et al. (2005) summarized the use of tracer to determinate such kind of leakages. Geophysical methods represent another major category of monitoring tools that will be applied to monitor the fate and integrity of geologically sequestered CO2. Interested readers can refer to the literature review by White et al. (2005).

Summary Gas transport through porous media is a very important topic in CO2 sequestration and migration. Storage of CO2 in the coalbed has been proposed as a promising strategy because of high gas storage capacity of coal. However, mathematical

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modeling studies in this subject are very limited though much more experimental work was reported in the literature. Since modeling and simulation can be used to evaluate and optimize the performance and design of these systems, researchers could put more effort in modeling CO2 injection and migration for the sequestration process in the coal seams.

CO2-Oxygen Transport in Oxy-Combustion Introduction Oxy-fuel combustion is currently considered to be one of the major technologies for carbon dioxide capture. A book (Zheng 2011) has focused on the development of oxy-fuel combustion technologies using coal as fuel. Coal plays a very important role in our day-to-day lives. In a comprehensive report published in 2008, the International Energy Agency (IEA) predicted that the demand for coal will surpass oil in absolute terms between 2030 and 2050 and will become the predominant fuel for the world (IEA, 2008–1). Coal as an energy source has a number of negative environmental impacts, including (but not limited to) the release of particle matter, oxides of sulfur and nitrogen, carbon monoxide (CO), and trace metals such as mercury. Therefore, it is necessary to develop clean coal technology. Currently, there are three major CO2 capture technologies that have reached the level of industrial-scale demonstration: post-combustion capture, precombustion capture, and oxy-fuel combustion (Shaddix 2012). Oxy-fuel combustion is a very elegant approach for CO2 capture that uses oxygen instead of air for combustion. By eliminating nitrogen from the oxidant gas stream, it is possible to produce a CO2-enriched flue gas ready for sequestration after water has been condensed and other impurities have been separated out. Oxy-fuel combustion for CO2 capture incorporates three main components: the air separation unit that provides oxygen for combustion, the furnace and heat exchangers where combustion and heat exchange take place, and the CO2 capture and compression unit. The heat transfer characteristics and its impacts on boiler design were studied for furnaces of various sizes under oxy-fuel operation, and it is concluded that an oxy-fuel-fired furnace can have the same heat transfer rate as an air-fired one with lower furnace exit temperature and higher gas emissivity. Therefore, current boiler design principles and operational practice can be easily adopted for oxy-fuel combustion (Tan et al. 2006; Wall et al. 2005). Research into oxy-fuel combustion of coal has involved a diverse set of experiments and modeling studies, from the most fundamental aspects to pilot-scale experimental testing and full-scale boiler CFD modeling (Shaddix 2012). Pulverized coal combustion represents the vast majority of the installed power plant capacity, and most of the oxy-fuel combustion research to date has focused on applications of diluting the oxygen to produce similar radiant and convective heat transfer profiles as existing in conventional air-fired coal boilers. Since CO2 has higher volumetric heat capacity than N2, the average mixture of oxygen and

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recycled flue gas (predominately CO2, with high concentrations of moisture, in some cases) must be composed of approximately 28 % O2. Consequently, coal particles in the oxy-fuel boilers are igniting and burning in vastly different chemical and thermal environments than in conventional air-fed boilers. This has motivated a revisit of fundamental studies of coal particle ignition and char combustion phenomena in a CO2 bath gas, which provide key information for CFD modeling and oxy-fuel burner design. This section of the chapter focuses on the transport phenomena through the porous coal particles in the oxygen-fed boilers during the oxy-combustion.

Modeling and Simulation For oxy-combustion with flue gas recirculation, elevated levels of CO2 and steam affect the heat capacity of the gas, radiant transport, and other gas transport properties. A topic of widespread speculation has concerned the effect of gasification reactions of coal char on the char burning rate. To assess the impact of these reactions on the oxy-fuel combustion of pulverized coal char, Hecht et al. (2012) computed the char consumption characteristics for a range of CO2 and H2O reaction rate coefficients for a 100 μm coal char particle reacting in environments of varying O2, H2O, and CO2 concentrations using the kinetics code SKIPPY (Surface Kinetics in Porous Particles). Their results indicate that gasification reactions reduce the char particle temperature significantly (because of the reaction endothermicity) and thereby reduce the rate of char oxidation and the radiant emission from burning char particles. However, the overall effect of the combined steam and CO2 gasification reactions is to increase the carbon consumption rate by approximately 10 % in typical oxy-fuel combustion environments. In addition, the gasification reactions have increasing influence as the gas temperature increases (for a given O2 concentration) and as the particle size increases. Gasification reactions account for roughly 20 % of the carbon consumption in low-oxygen conditions and for about 30 % under oxygen-enriched conditions. Chen et al. (2012) reviewed the oxy-fuel combustion of pulverized coal in the aspects of characterization, fundamentals, stabilization, and CFD modeling. The technical review of oxy-coal combustion covered the most recent experimental and simulation studies. Numerical models for subprocesses were used to examine the differences between combustion in an oxidizing stream diluted by nitrogen and carbon dioxide. The review introduced the evolution of this technology from its original inception for high temperature processes to its current form for carbon capture, followed by a discussion of various oxy-fuel systems proposed for carbon capture. The review also discussed the characteristics of oxy-fuel combustion in the context of heat and mass transfer, fuel delivery and injection, coal particle heating and moisture evaporation, devolatilization and ignition, char oxidation and gasification, as well as pollutants formation. Further, the review included advances in sub-models for turbulent flow, heat transfer and reactions in oxy-coal combustion

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simulations, and the results obtained using the CFD modeling. It was summarized that distinct characteristics in oxy-coal combustion necessitate modifications of CFD sub-models because the approximations and assumptions for air-fuel combustion may no longer be valid. Based on the review, research needs in this combustion technology were suggested. Geier et al. (2012) reported on the development and application of an extended single-film reaction model that includes both oxidation and gasification reactions. The traditional single-film nth-order Arrhenius char oxidation model was extended by including additional heterogeneous reactions of char with CO2 and H2O, as is required to accurately predict char particle temperatures and char consumption rates in both conventional and oxy-combustion environments. The performance of the model has been systematically interrogated in comparison to experimental data for two US coals (a Powder River Basin subbituminous coal and a low-sulfur, high-volatile bituminous coal) for a variety of model assumptions. The analysis with the extended single-film model showed that incorporation of both steam and CO2 gasification reactions is required to maintained reasonable values for activation energy of the reactions. The modification of the traditional single-film char burnout model achieved the goal of improving CFD predictions of oxy-fuel combustion of pulverized coal char particles by focusing on the model performance in predicting experimentally observable data (particle temperature) of char particles burning in N2 and CO2 baths with different contents of O2. Kim et al. (2014) used burnout simulations of coal char particles with apparent char reactivity and a single-film model that includes the Stefan flow effect on mass and energy transfer, to study the impact of CO2 gasification on the oxy-combustion of pulverized coal chars. The simulations revealed that gasification reaction by CO2 improves the char burnout time and carbon consumption and decreases the char particle temperature. Also, the simulations indicate the gasification reaction has a greater influence on the char burnout time and the relative contribution to carbon consumption in an oxygen-deficient environment and a greater influence on the particle temperature in an oxygen-enriched environment. However, this tendency according to oxygen level is also influenced by the gas temperature. In addition, the influence of the gasification reaction on char combustion increases as the gas temperature increases and as the particle size increases. Although more reliable rate parameters and insight of the influence of boundary layer heat release are needed, the simulation study shows that it is important to include gasification reaction by CO2 when simulating char combustion in the oxy-fuel combustion environments.

Measurements In order to fully understand the results of pilot-scale tests and to accurately predict scale-up performance through CFD modeling, Murphy and Shaddix (2006) have measured the combustion rates of two pulverized coal chars in both conventional

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and oxygen-enriched atmospheres. The study used a combustion-driven entrained flow reactor equipped with an optical particle-sizing pyrometry diagnostic and a rapid-quench sampling probe. Oxygen-enriched combustion was found to significantly increase the char combustion temperature and to reduce the char burnout time, as expected. The optical kinetic data, interpreted with a single-film oxidation model, demonstrate increasing kinetic control in enriched-oxygen combustion, despite the faster particle combustion rates. Char burnout rates and char particle temperatures are predicted reasonably well when applying a char burnout model with the derived kinetics. Gonzalo-Tirado et al. (2013) determined the kinetics of CO2 gasification for coals of different ranks under oxy-combustion conditions. Combustion reactions were performed in a flow reactor consisting of a cylindrical, externally heated tube (1.6 m long, 78 mm inner diameter), in which the fuel particles are pneumatically injected by means of an insulated gun. Samples of partially burnt particles were collected at increasing distances from the injection point with an isokinetic probe. Higher activation energies and lower char reaction rates (in the conditions explored) were found for char gasification than for oxidation, and the coal rank influenced both sets of kinetics. Kim et al. (2014) applied a new experimental approach to directly measure the CO2 gasification rate of a subbituminous coal char at high temperatures and atmospheric pressure. Sandia National Laboratories’ laminar entrained flow reactor facility was employed for this study, and char particle size-temperature statistics were measured using a particle-sizing pyrometer, i.e., the velocity, diameter, and temperature of individual burning char particles. A water-cooled sampling probe with helium-quench gas dilution was used to collect char samples at selected heights for determination of char burnout.

Summary Computational fluid dynamic (CFD) simulations traditionally rely on the computational efficiency of single-film global kinetic oxidation models to predict char particle temperatures and char conversion rates in pulverized coal boilers. In oxy-fuel combustion with flue gas recirculation, char combustion occurs in the presence of elevated CO2 levels and, frequently, elevated water vapor levels (when employing wet flue gas recirculation). Also, local oxygen concentrations can be quite high in the vicinity of oxygen injection lances. The suitability of existing approaches to modeling char combustion under these conditions has been unclear. In particular, previous work has shown that both boundary layer conversion of CO and gasification reactions of steam and CO2 need to be included to give reasonable agreement with the experimental measurements, for particles over 60 μm in size. Large physical domain sizes and high computational complexity dictate the use of fairly coarse meshes for the spatial domain and application of simplified coal combustion models, which inevitably reduces the range of process conditions for which the simulation software produces reliable results.

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Oxygen Transport in Membrane at High Temperatures Introduction It was introduced in section “CO2-Oxygen Transport in Oxy-Combustion” that oxy-fuel combustion for CO2 capture incorporates three main components: the air separation unit that provides oxygen for combustion, the furnace and heat exchangers where combustion and heat exchange take place, and the CO2 capture and compression unit. This section of the book chapter focused on the technology of oxygen separation using membrane at high temperatures. The use of selective membranes to separate certain components from a gas stream, for example, separating oxygen from nitrogen in the oxy-fuel combustion system is a relatively novel capture concept (Mondal et al. 2012). Membranes are semipermeable barriers able to separate substances by various mechanisms (solution/diffusion, adsorption/ diffusion, molecular sieve, and ionic transport). These are available in different material types, which can be either organic (polymeric) or inorganic (carbon, zeolite, ceramic, or metallic) and can be either porous or nonporous. Oxygen separation technologies currently include polymer membranes, pressure swing adsorption (PSA), vacuum swing adsorption (VSA), cryogenics, chemical looping combustion (CLC), and ceramic autothermal recovery (CAR) (den Exter et al. 2009). Polymeric membranes are used for oxygen enrichment or depletion of air, and the polymers are commonly based on among others polyphenyloxide (Parker Gas Separation) and polyimides (air products). The separation is based on preferred dissolution and diffusion of oxygen over nitrogen in these materials, but the operating temperature is limited by the thermal stability of the polymers used. The PSA and VSA technologies are based on the preferred absorption of nitrogen in, for example, zeolite beds. Cryogenics is currently the most developed mature large-scale oxygen production technology, and this technology can also be used to produce nitrogen and argon. In CLC, a metal or metal oxide is oxidized by air in one reactor and transferred to a reduction reactor that is fed with, for example, syngas. The CAR concept uses a set of two or more batch reactors alternating between oxidation and reduction cycles, containing a perovskite material that is cycled between two oxygen contents. High-temperature oxygen transport membranes (OTMs) have been proposed for plants using high purity O2 for fuel conversion. These include both plants that partially oxidize feedstocks to produce syngas and power plants with CO2 capture based on oxy-fuel combustion (Chiesa et al. 2013). The optimal OTM operating temperature is between 800  C and 900  C when integrating as a permeator in a gas turbine of an integrated gasification combined cycle (IGCC) plant and is between 700  C and 900  C for heavy fuel oxy-combustion. All these applications require high operation temperatures of the OTMs. den Exter et al. (2009) clearly identified that the high-temperature ceramic membranes that selectively transport oxygen are the high-temperature oxygen transport membranes (OTMs). They are referred to with several acronyms of

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Fig. 2 Schematic representation of the transport of oxygen through an ion transport membrane consisting of a dense (left) and porous (right) part. The sweep can be either “inert,” for example, CO2 or H2O, or “fuel,” for example, CH4 (den Exter et al. 2009)

which OTM (oxygen transport membranes), ITM (ion transport membranes), and MIEC (mixed ionic electronic conducting) membranes prevail. They also pointed out the two main applications of high-temperature membrane technology are the production of high purity oxygen as a valuable chemical and as a reactant for various (partial) oxidation processes such as methane conversion. Most OTM materials are only permeable to oxygen at temperatures above 700  C (975 K) (Foy and McGovern 2005). OTM technology integrates O2 separation and combustion in one unit. A schematic representation of the air separation process using OTM as a whole is presented in Fig. 2 (den Exter et al. 2009). The driving force for the transport of oxygen is a difference in partial oxygen pressure (pO2) between the feed and permeate side of the membrane. Figure 2 also demonstrates that the OTM consists of an inert porous support (right) coated with a dense gas separation layer (left). There are three main types of ceramics with ion transport capabilities: perovskite, fluorite, and mixed (Foy and McGovern 2005). OTM reactors supply pure oxygen through the membrane to the sweep side where a fuel is introduced and oxidized. Examining the fundamentals of catalytic fuel conversion and how they couple with oxygen permeation and gas-phase reactions requires detailed and complex models (Hong et al. 2013a, b). Due to the coupling between catalytic fuel conversion and oxygen permeation, and the high operation temperature,

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a detailed analysis is needed to account for the coupling of oxygen permeation, gas-phase flow and transport, and homogeneous and heterogeneous chemistry in terms of the local thermodynamic state on both sides of the membrane surface. The modeling of the flow process considers a numerical solution of the conservation equations of mass, momentum, energy, and species in the axisymmetric flow domain (Ben-Mansour et al. 2012). The oxygen permeation across the membrane depends upon the prevailing temperatures and the oxygen partial pressure at both sides of the membrane. In the following section, modeling and simulation studies of the flow process were summarized.

Modeling and Simulation Understanding the theory of the OTM is very important for the modeling and simulation studies. Foy and McGovern (2005) provided a summary of the theory. There are a number of factors that affect the passing of oxygen through the membrane. Firstly the oxygen must reach the membrane. It is possible that due to transport in the flow of gas on the feed side of the membrane, the flux could be limited. After the oxygen reaches the membrane, it is adsorbed onto the surface. Surface exchange effects can be identified by a difference in the normalized values for different thicknesses of the same material. Once the oxygen has reached the surface and been adsorbed onto it, it is transported through the ceramic by bulk transport through the ceramic lattice, which contains oxygen ion vacancies. The oxygen flux across the membrane is given by the Nernst-Einstein equation above 700  C (975 K) where the flux is directly proportional to the absolute temperature and inversely proportional to the thickness of the membrane. The flux is also proportional to the natural log of the ratio of oxygen partial pressures across the membrane. This explains why the flux can be much higher when an oxygen-consuming reaction occurs on one side of the membrane. Modeling studies conducted so far have rarely related the heterogeneous chemistry for perovskite oxygen transport membranes to the local thermodynamic state and have not resolved its coupling with the oxygen permeation and gas-phase transport and reactions in detail (Hong et al. 2013a, b). Akin and Lin (2004) assumed different permeation mechanisms and two limiting oxidation kinetics: either extremely fast reaction or no conversion. Using a simple reactor model such as a continuously stirred tank reactor (CSTR), they examined how the oxidation reaction rates, the reducing gas flow rate, and the feed-side oxygen partial pressure influence the oxygen permeation rate. Based on the same CSTR model, Rui et al. (2009) investigated the effect of the finite chemical kinetic rates on the oxygen permeation rate. Results from these studies have shown that chemical reactions and their kinetic rates have substantial influence on the oxygen permeation. These models considered a CSTR and assumed arbitrary reaction rates. Wang and Lin (1995) estimated catalytic kinetic parameters assuming that perovskite membranes behave catalytically in a way similar to Li/MgO membranes and

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applied them to the CSTR model, while Tan et al. (2008) used the kinetic parameters of perovskite membranes with a plug flow reactor (PFR) model. Hong et al. (2013a, b) developed a physical model that resolves spatially the gas-phase flow, incorporates detailed homogeneous chemistry, and accounts for oxygen permeation. Hong et al. (2013a, b) further revised this model to incorporate heterogeneous chemistry on the membrane surface. The surface and bulk species and their reactions are coupled with the local thermodynamic state near the membrane in the gas phase. Using spatially averaged, i.e., reactor level, measurements available in the literature, numerical simulations have been used to develop the heterogeneous chemistry that resolves both oxygen surface exchange and catalytic fuel conversion. Computational fluid dynamics was also applied to model the oxygen transport in a lab-scale experimental setup for permeation testing of oxygen transport membranes using finite element analysis (Gozálvez-Zafrilla et al. 2011). The modeling considered gas hydrodynamics and oxygen diffusion in the gas phase and vacancy diffusion of oxygen in a perovskite disk-shaped membrane at 1273 K. In a first step, the model was set to obtain the diffusion coefficient of oxygen. The parametric study showed that the setup geometry and flow rate in the air compartment did not have major influence in the oxygen transport. However, very important polarization effects in the sweep-gas (argon) compartment were identified. The highest oxygen permeation flux and the lowest oxygen concentration on the membrane surface were obtained for the following conditions (in increasing order of importance): (1) a large gas inlet radius, (2) a short gas inlet distance, and (3) a high gas flow rate. The computational fluid dynamics method has also been applied by Habib et al. (2013a, b), and the solver of the Fluent software was used with a series of user-defined functions (UDFs) in a Cartesian coordinate system. To summarize, the modeling of the flow process considers a numerical solution of the conservation equations of mass, momentum, energy, and species in the axisymmetric flow domain. A representative OTM flow schematic for modeling study has been given by Hong et al. (2013a, b) and was reproduced in Fig. 3. The flow process couples the gas-phase flow, transport and chemical reactions, and oxygen permeation flux and heat flux across the membrane.

Conservation of Mass According to the configuration in Fig. 3, Hong et al. (2012) used the following as the continuity equation: N @ρ @V ρ @T X ρW @Y k @V þ þ ρU ¼   þ ρU ¼ 0 þ @t @y T @t k¼1 W k @t @y

(14)

where ρ is the density, V is the normal velocity, U is the transverse velocity, W is the mixture molecular weight, Wk is the molecular weight of species k, and N is the number of gas-phase species.

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Fig. 3 Planar, finite-gap stagnation flow configuration of the OTM flow schematic for modeling study (Hong et al. 2013)

Conservation of Momentum According to the configuration in Fig. 3, Hong et al. (2012) proposed the conservation of momentum in the x-direction and used the following equation: ρ

  @U @U @ @U þV þ ρU 2 þ Λx  μ ¼0 @t @y @y @y

(15)

where ρ is the density, V is the normal velocity, U is the transverse velocity, Λx ¼ 1x dp dx and is the scaled transverse pressure gradient (kg/m3/s2), and μ is the dynamic viscosity.

Conservation of Energy Hong et al. (2013) coupled the thermal energy balance of the membrane in their mathematical models and considered the conductive, convective, and diffusive heat transfer with the gaseous domain and the heat release from the surface reactions as well as the thermal radiation between the membrane and the reactor walls. According to the configuration in Fig. 3, Hong et al. (2012) used the following as the conservation of energy equation: "  # N N X @T @T 1 X @T @ @T þV þ  λ ρ jk cp, k h^k ω_ k þ ¼0 @t @y cp k¼1 @y @y @y k¼1

(16)

where ρ is the density, V is the normal velocity, ω_ k is the molar production rate of species k, cp is the mixture specific heat, cp,k is the specific heat of species k, h^k is the molar enthalpy of species k, λ is the mixture thermal conductivity, N is the number of gas-phase species, and jk is the flux of species k in the y direction.

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Conservation of Species Hong et al. (2013) distinguished three domains for the conservation of species with heterogeneous chemistry. The three domains were illustrated in Fig. 4 as gaseous, surface, and bulk domains. The gaseous and bulk domains are volumetric domains, whereas the surface domain is an interface domain between these two volumetric domains. The transport-chemistry interaction in each domain is modeled using the appropriate form of the differential equations, and the surface reactions are used to connect them. The bulk species concentration in the direction of the membrane thickness is governed by bulk diffusion, and the control volume approach is used to relate the volumetric bulk domain with the interface domain. The species conservation within the surface domain is accounted for by surface reaction without species transport or mass fluxes. When coupling the heterogeneous kinetic mechanism, the species concentration at and immediately below the surface domain is used. Ben-Mansour et al. (2012) specified the binary mass diffusion coefficient of the component i in the component j to determine the diffusion coefficient. The corresponding diffusion coefficient in the mixture is computed by

Fig. 4 Three domains (i.e., gaseous, surface, and bulk domains) and the species belonging to each domain (i.e., Yk = gas-phase species in the gaseous domain, Zk = surface species in the surface domain, and Ck = bulk species in the bulk domain). The gaseous and bulk domains are volumetric domains, whereas the surface domain is an interface domain between these two volumetric domains (Hong et al. 2013)

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1  Xi   Xi j, j6¼i D i, j

Di, m ¼ X

(17)

Gozálvez-Zafrilla et al. (2011) modeled the transport of oxygen in the membrane by a Fickian diffusion mechanism of oxygen vacancies in the structure. The transport depends on the concentration gradient of oxygen vacancies and a diffusion coefficient which is a material property.

Measurements Chemical and Physical Properties Zeng et al. (2009) applied the Archimedes method using mercury to obtain the relative density of the ceramic membrane. They also analyzed the phase composition of the membrane intermediate material by X-ray diffraction (XRD), measured the O1s XPS spectra of the powders with VG ESCALAB MKII, and analyzed with the Gaussian peak software. Park et al. (2008) applied SEM to measure the morphologies of the calcined powder and membrane. They painted the rectangular specimens with silver paste to measure the electrical conductivity with a dc four-probe method as a function of temperature (100–900  C) in 80 % N2-20 % O2 and in 1 % O2/N2 atmosphere at a flow rate 100 mL  min1. Transport Properties Oxygen permeation tests were performed by numerous researchers (Zeng et al. 2009; Park et al. 2008; Tan et al. 2012; Sunarso et al. 2009; Wang et al. 2014). Gas phase chemistry detection was involved in all these studies. In this section of the book chapter, we only representatively listed two studies. Zeng et al. (2009) measured the oxygen permeation through the membranes using the experimental setup: one side of a disk-shaped membrane was exposed to atmospheric air and the other side was swept with flowing helium or pure CO2 to carry away the permeated oxygen. The total flow rate on the feed side of the membranes was set to be 100 mL  min1 and the flow rate on the permeate side to 50 mL  min1. To verify the O2/CO2 production concept, a one-end closed membrane tube was sealed in an alumina tube by silver to form a permeation cell. The shell side of the tube was exposed to a pressurized air (3 bar), and the core side was swept with a flowing CO2 injected through an alumina tube. The effluent from the permeated (lower pO2) side of the membrane was analyzed with online gas chromatography. Park et al. (2008) measured the oxygen permeation using the setup shown in Fig. 5. The membrane permeation cell was assembled with the membrane, alumina tube, and sealant. Prior to oxygen permeation test, the cell part was purged with He gas to remove the air in permeation cell tube and to confirm

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Fig. 5 The schematic diagram of a permeation test cell (Park et al. 2008)

sealing of the assembly consisted of alumina tubes, membrane, and sealant for 20 h. The leakage through membrane during oxygen permeation test was also measured for all runs at each temperature, and the oxygen permeation fluxes were corrected on the basis of the measured leakage. Permeation study was performed within the temperature range of 750–950  C. The oxygen content in the permeate stream was measured with a gas chromatograph, and the oxygen flux was determined by: J O2 ½mL=min cm2 ðSTPÞ Ftotal ½mL=min yO2 ½v%  leakage correction ¼ A ½cm2 

(18)

where Ftotal is corresponding with the total flow rate of the permeation stream in which the oxygen concentration is yO2, A is the effective membrane surface area, and leakage correction means the calculating oxygen flux from leakage.

Thermal Properties Thermogravimetric analysis (TA) was carried out for the OTM materials. Tan et al. (2012) reported to use TA with 500 mg of the crashed hollow fiber sample in a sample holder. The sample was heated 25–950  C at a rate of 10  C  min1 in CO2 or nitrogen (flow rate = 50 mL  min1).

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Summary Numerous reports have been on the study of the oxygen transport membrane, and the OTM technology has been proved a popular topic. However, due to the complexity of the flow process through the membrane system, much further effort is still required to understand the fundamentals and to improve the performance of the OTM at high temperatures.

Future Directions In this book chapter, the author first listed the general mechanism to briefly explain transport through porous media. Then, a general review was given of the different processes, models, and experimental methods of the gas transport in the porous media associated with the three applications of CO2 migration after sequestration, CO2-oxygen transport in oxy-combustion, and oxygen transport in membrane at high temperatures. Due to the broadness of the topic, the author suggested readers to further refer to the listed references of each topic if interested. The topic of oxygen transport at high temperatures is popular recently. Many efforts have been put in exploring new materials for OTM, while less efforts have been made in understanding the transport mechanism. Due to the high working temperature, the OTM requires materials having strict properties so that it is very popular for researchers to study materials with high performance. It is very important to understand the transport mechanism in order to develop the new materials.

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Part III Climate Change Mitigation: Energy Conversation, Efficiency, and Sustainable Energies

Energy Efficiency: Comparison of Different Systems and Technologies Maximilian Lackner

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . What Is Energy Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Significance of Energy Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Benefits of Energy Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Downside of Energy Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Energy Efficiency Versus Energy Demand: The Rebound Effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Energy Intensity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emission Intensity (Carbon Intensity) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Historical Development of Energy Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Assessing Energy Efficiency Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Innovation and New Technologies for Energy Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Typical Energy Efficiencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Benchmarking of Energy Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Energy Efficiency World Records . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Some Not-So-Energy-Efficient Inventions and Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Barriers to Energy Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Levels of Energy Efficiency: From Process to Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Energy Efficiency Investments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introducing Energy Efficiency Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combustion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Power Plants and Electricity Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Energy Transmission and Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Energy Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Life Cycle Assessment (LCA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Total Cost of Ownership (TCO) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Energy Efficiency in Various Sectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Agriculture and Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Transportation and Logistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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M. Lackner (*) Institute of Advanced Engineering Technologies, University of Applied Sciences FH Technikum Wien, Vienna, Austria e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_24

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Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Public Sector and Community Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appliances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lighting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Consumers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Initiatives for Energy Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Other Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Energy Conservation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Further Study and Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The efficient use of energy, or energy efficiency, has been widely recognized as an ample and cost-efficient means to save energy and to reduce greenhouse gas emissions. Up to 1/3 of the worldwide energy demand in 2050 can be saved by energy efficiency measures. In this chapter, several important aspects of energy efficiency are addressed. After an introduction and definition of energy efficiency, historic development and state-of-the-art and future trends of energy efficiency are presented in the light of life cycle assessment and total cost of ownership considerations. Energy efficiency in the sectors energy production, energy transmission and storage, transportation, industry, buildings, and appliances is reviewed. Concurrent measures such as recycling or novel materials are also discussed and touched upon. Energy conservation is covered in the final section of this chapter. References for deeper study are provided with an emphasis on guidelines on how to improve energy efficiency. Given the breadth of the subject, only exemplary coverage can be aimed for. The purpose of this chapter is to highlight the significance of energy efficiency and to provide cross-learnings from achievements in different sectors so that energy efficiency in the readers’ own facilities and installations can be assessed and improved with cost-effective means as a contribution to climate change mitigation, cost savings, and improved economic competitiveness.

Introduction Energy in the everyday world is a range of commodities, for instance, thermal or electrical. It is a scalar physical quantity that is defined by the amount of work that can be done by a force. Energy comes in different forms: Classical mechanics distinguishes between kinetic and potential energy. In the everyday world, one can see chemical, thermal, gravitational, light, and electrical energy, to name but a few. These forms of energy can be transformed into each other. The SI unit of energy is joule [J], with other common units being kilowatt hour [kWh], tonne of oil equivalent [toe], and British thermal unit [btu, BTU]:

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1 J = 1 kg m2 s
2 = 1Ws 1 kWh = 3.6*106 J 1 toe = 41.868 GJ = 11,630 kWh 1 btu = 1.060 kJ; 1 quad = 1015 (1 quadrillion) btu = 1.06  1018 J The worldwide energy consumption is on the order of 500 exajoules (5  1020 J) per year, which corresponds to an average consumption rate of 15 terawatts (1.5  1013 W). Energy efficiency, i.e., the efficient use of energy, describes the use of less energy to achieve the same level of energy service. Energy efficiency is a universally applicable concept relevant for consumers and industry alike. It can be achieved by a more efficient technology, an improved process, or a change of individual behavior. Energy efficiency can, according to the IEA’s World Energy Outlook 2014, “close the competitiveness gap caused by differences in regional energy prices” (IEA 2014a). The International Energy Agency (IEA) promotes energy security amongst its 29 member countries through collective response to physical disruptions in oil supply and provides research and analysis on energy. The annual World Energy Outlook is the IEA’s “flagship” publication, which is widely recognized as an authoritative source for global energy projections and analyses. It provides mediumto long-term energy market projections, ample statistics, and recommendations for governments and the energy business. Obstacles toward the introduction of energy efficiency are often not imposed by technical or economic reasons but rather by the habits, norms, and mindset of our social institutions, often termed “market barriers.” Therefore, apart from increasing research and development (R&D) to create and improve energyefficient technologies and appliances, one has to address the issue from other angles such as policy-making (Blok et al. 2004), too. The proliferation of energyefficient technologies requires stimuli outside the scope of technical, and economic, logic arguments. Also, it has to be noted that the proliferation of technically and economically superior technology is a gradual one (Jaffe and Stavins 1994). Subsidies can have an important effect on the penetration rate of new energy technologies (Lund 2006), as can industry agreements (Grossman and Krueger 1991). In its most current World Energy Outlook (IEA 2014a), released in November 2014, the International Energy Association (IEA) has compared the “central scenario,” a kind of baseline or BAU (business as usual or reference) scenario, to its suggested course of action to control climate change, which is termed “for 2  C target” scenario. In the WEO 2009, it was called “450 scenario”, as a limit of 450 ppm of CO2-eq in the atmosphere would limit temperature increase to 2  C. In the reference scenario, worked out for the period to 2040, the world is set for a rise in temperature of up to 6  C, leading to severe global challenges in terms of irreversible environmental damage and energy security. The notion that energy security can be an issue has existed since the OPEC oil embargo of 1973 (otherwise known as the oil crisis), followed by the second energy crisis 6 years later. It was recently revived in

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Fig. 1 In the central scenario of WEO’s Energy Outlook 2014, the entire global budget of CO2-eq to 2100 is used up by 2040 (left). Investments to achieve the 2  C target are ~2/3 in the energy efficiency domain (right) (Source: IEA 2014b)

Central Europe in the winters of 2006 and 2009 (Gow 2009; Hollinger 2014) due to natural gas supply cuts. Globally, crude oil prices exceeding for the first time 100 USD per barrel in the same year have also led to concerns about energy security in terms of affordability and sustainability. There is no straightforward definition for energy security. In Kruyt et al. (2009), indicators based on availability, accessibility, affordability, and acceptability were created. With depleting fossil fuel sources and concentration of these in fewer regions, not all of which are considered politically stable, it can be anticipated that fossil fuel prices will go up and will fluctuate more strongly, partly driven by speculation. Today, the world relies to approx. 80 % on fossil fuels for primary energy production. The IEA “450 scenario” demands for fossil fuel consumption to peak by 2020 and for energy-related CO2 emissions to be cut from 28.8 Gt in 2007 to 26.4 Gt in 2030 (IEA 2009). In the “for 2  C target,” the world’s CO2 budget is given as 2,300 Gt, of which more than 50 % was emitted from 1900 to 2012; see Fig. 1. As it can be seen in Fig. 1, the largest contribution to CO2 abatement – approx. 2/3 – can be made by energy efficiency measures. Another strong contribution comes from changes in the mix of power generation technologies. Table 1, based on IEA (2009), shows the worldwide energy-related CO2 emissions. Similar results, focused on the USA, were found in Granade et al. (2009). As a conclusion, one can say that energy efficiency has a huge potential. In this chapter, several aspects of energy efficiency for climate change mitigation are highlighted. Complete coverage of the topic cannot be provided within the scope of this chapter, so a selection has been made to present some of the most relevant areas related to energy efficiency.

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Table 1 Global CO2 emissions in the “reference scenario” and the “450 scenario” in the 2009 World Energy Outlook of the IEA, compare Fig. 1 (Source: IEA 2009) CO2 emissions Total Per capita Power generation Transport Industry Buildings Others

1990 20.9 Gt 4.0 t 36 % 22 % 19 % 14 % 10 %

2007 28.8 Gt 4.4 t 41 % 23 % 17 % 10 % 10 %

2030, reference scenario 40.2 Gt 4.9 t 44 % 23 % 15 % 8% 9%

2030, 450 scenario 26.4 Gt 3.2 t 32 % 29 % 17 % 10 % 11 %

What Is Energy Efficiency Energy efficiency is, as the term implies, the efficient use of energy, i.e., using a lower amount of energy to achieve the same level of energy service (Patterson 1996). It can be achieved by improved behavior or by more efficient technology. Thermodynamics teach that energy can only be transformed. According to the first law, energy can neither be created nor destroyed. A change in the internal energy of a system, U, can be achieved by adding heat Q or work W: dU ¼ dQ
dW

(1)

where dQ and dW are incremental changes in heat and work, respectively (the minus denotes that positive work is being done by the system). Equation 1 can be rewritten as dU ¼ TdS
pdV

(2)

where the work done by the system during expansion is pdV. The amount of heat added to the system can be described by dQ = TdS with T being the temperature and S the entropy. In a heat engine, thermal energy is converted to mechanical energy by exploiting a temperature gradient between a hot and a cold reservoir for an energy transfer. The efficiency of such a heat engine is given by the ratio of useful power to heat energy input. It can be derived as follows: dW ¼ dQc
ð
dQh Þ

(3)

dW =
pdV, i.e., the work done by the engine. dQh = ThdSh, i.e., the heat energy taken from the high-temperature reservoir. dQc = TcdSc, i.e., the heat energy delivered to the cold-temperature reservoir. In the reversible Carnot heat engine cycle (dSc = dSh, i.e., no net change in the entropy), the maximum efficiency is

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Table 2 Efficiencies of power plants (Source: Curzon and Ahlborn (1975), Callen (1985)) Power plant A B C

Technology Coal fired Nuclear power Geothermal power

Tc ( C) 25 25 80

ηmax ¼ 1


Th ( C) 565 300 250

η (Carnot) 0.64 0.48 0.33

η (endoreversible) 0.40 0.28 0.178

dQc ðT c dSh Þ Tc ¼1
¼1
dQh ð
T h dSh Þ Th

η (observed) 0.36 0.30 0.16

(4)

The Carnot efficiency is a theoretical one, because it considers an infinitesimally small temperature change. As for “real” heat engines such as internal combustion engines or power plants, one is typically after a sizeable power output, which is an irreversible process. Therefore, the ideal, reversible Carnot process does not well describe the efficiency of a technical system. Taking the concept of endoreversible thermodynamics (Hoffmann et al. 1997) into consideration, the efficiency of a heat engine operating in irreversible mode can be obtained as rffiffiffiffiffi Tc η¼1
Th

(5)

This expression is known as the endoreversible efficiency or Chambadal-Novikov efficiency (Chambadal 1957; Novikov 1958). It allows a more realistic estimation of the efficiency of a heat engine, which can be termed semi-ideal. The endoreversible efficiency takes the destruction of exergy in an irreversible process into consideration. Exergy is the highest possible useful work during a process that brings the system into equilibrium with a heat reservoir (Perrot 1998; Dewulf et al. 2008; Demirbas et al. 2000; Wall et al. 1994; Prins et al. 2004). It was introduced by Gibbs as a special form of the Gibbs available energy. Exergy is the work potential of a system. It can be potential (gravitational or magnetic force field), kinetic (velocity), physical (pressure, temperature), or chemical (composition) (Dewulf et al. 2008). Exergy analysis can be used to determine inefficiencies. Table 2, compiled from Curzon and Ahlborn (1975) and Callen (1985), shows the comparison of the Carnot and Chambadal-Novikov efficiencies of three power plants to their actual ones. From the above table, it can be seen that the endoreversible efficiency predicts the observed one well. In Cullen and Allwood (2010), theoretical efficiency limits for energy conversion devices are reviewed. The combination of energy efficiency and renewable energy is often referred to as sustainable energy. Sustainability was defined in 1983 by the UN World Commission on Environment and Development as follows: “Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs.”

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Energy productivity, similar to energy efficiency, has a narrower scope. It is defined as ratio of output divided by energy consumption, e.g., GDP/energy consumption in terms of liter oil equivalent of that economy from its energy balance table (GDP = gross domestic product). Another aspect related to energy efficiency in the context of climate change mitigation is the concept of greenhouse gas emission factors. Apart from CO2, other greenhouse-active gases can be emitted, such as CH4, N2O, or halocarbons. Office of Energy Efficiency, Natural Resources Canada (2002), provides an overview. There is a huge potential for energy efficiency improvements. Three recent studies on this topic are Electric Power Research Institute (EPRI) (2015) and Granade et al. (2009), making projections until 2020, and IEA (2009), which extends its forecasts to 2030. It needs to be stressed that such impressive potentials can only be turned into reality if significant initiatives are launched. Program costs have to be catered for, too. Different approaches to measure energy efficiency in industry are shown in Phylipsen et al. (1997). Indicators of energy efficiency are discussed in Bor (2008) and Ang (2006). Another important consideration in energy efficiency is the entire life cycle of a product. Life cycle energy efficiency (Malça and Freire 2006) not only considers actual use of a piece of equipment but also its production and disposal (see section “Life Cycle Assessment (LCA)” later). Energy efficiency trading can only be mentioned here. It is discussed in Mundaca (2009). A detailed overview on energy efficiency is provided in McLean-Conner (2009).

Significance of Energy Efficiency There is – unfortunately – no such thing as a perpetuum mobile. As a consequence, energy can only be transformed from one form into another one, which happens under certain losses (see also above). Users of mobile phones, notebooks, and any other mobile device will naturally and subconsciously appreciate energy efficiency – because energy is obviously a scarce resource in these applications. Service life and hence usefulness will depend on the efficiency and energy density of the gadget (Mitsos et al. 2007). However, energy efficiency is a much broader topic. Energy is the leading source of anthropogenic greenhouse gas emissions, approx. 65 % (IEA 2009), and hence needs to be at the core of climate change mitigation actions. In the IEA’s reference scenario, the global energy demand is set to increase by 40 % from 2007 to 2030, reaching 16.8 billion toe (IEA 2009). 90 % of this increase is predicted to happen in non-OECD countries, with India and China accounting for half (IEA 2009). Global electricity demand is projected to grow by even 76 % from 2007 to 2030, requiring 4,800 GW of additional capacity. This is five times the existing US capacity (IEA 2009). In the proposed course of action, the “450 scenario,” more than 50 % of all (necessary) energy savings are realized by energy efficiency measures. The target is an energy-efficient and low-carbon economy. By 2050, energy efficiency measures could cut the total worldwide energy consumption by as much as 1/3 (IEA 2009).

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Energy efficiency has a large-scale effect. Apart from addressing global warming, energy security and fossil fuel depletion are tackled, alongside solid savings for individuals, enterprises, and nations at large. Air quality, particularly in urban areas and in developing countries, can also be improved by energy efficiency measures. There are other environmental co-benefits, too, from implementing energy efficiency measures. By focusing on energy efficiency rather than on increasing energy production, a cost-effective, “soft” energy path is followed. The term “negawatt” was coined two decades ago to describe electricity that “wasn’t created due to energy efficiency” (Joskow and Marron 1993). Energy efficiency has been widely recognized as a vast, low-cost energy source (Granade et al. 2009). The reason why this unused potential is so large stems from the multitude of barriers that impede energy efficiency today (Granade et al. 2009; Schleich 2009; Jaffe and Stavins 1994). Unlike the production factors of labor and capital, which have been seen impressive optimization since the industrial revolution, energy is far from being at the lowest possible level. Energy efficiency has become part of the political agenda in many countries (Al-Mansour et al. 2003). Monitoring energy intensity is common practice since the 1973 oil crisis. How policies can increase energy efficiency is shown in Geller et al. (2006) for the OECD countries (OECD = Organization for Economic Co-operation and Development; 34 member countries, which are considered highly developed) and in Vine (2002) for the state of California, a leading region for energy efficiency as will be referred to in this chapter of the handbook. For corporations, energy efficiency is an important pillar for the “triple bottom line,” i.e., their performance in economic, social, and environmental aspects. Businesses and consumers alike start taking energy considerations into account for decision making. It is estimated that energy is a strategic factor for 40 % of all global revenue (McKinsey & Company, Inc. 2009). Unpredictable volatility in fuel prices, driven by depletion of crude oil and speculation, places a burden on companies and economies as a whole, which they feel needs to be controlled. Stern (2007) provides an overview on the economic aspects of climate change. With energy efficiency being the easiest way to save energy, it is highly relevant to mitigate climate change effects and their detrimental consequences.

Benefits of Energy Efficiency Energy efficiency offers several direct and indirect benefits, some of which are obvious. The reduction of pollution and greenhouse gas emissions aids the environment. For businesses, reduced energy bills will translate into competitive advantages. Also, energy efficiency measures can lead to higher worker productivity and reduced sick leave rate (Granade et al. 2009) as concurrent benefits. Consumers can enjoy increased comfort levels (Jaffe and Stavins 1994), particularly those living in low-income households. Indirect benefits, as an example, also related to health (less drafty and damp rooms after the implementation of energy efficiency measures in

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private homes such as insulation upgrading). As a nation, a key benefit is an improvement in energy security, another one that reduced exposure to volatility in energy prices. There has also been a wide discussion on job creation by the quest for energy efficiency. While it is true that energy-intensive production processes are shifted toward developing countries, leading to job losses in countries of the European Union and the USA, for instance, there should be a net positive effect from the job market stimuli provided by energy efficiency. For instance, the market for building insulation is estimated at 10–12 billion USD for the USA alone (Granade et al. 2009). An overview on the market size for energy efficiency in the USA is provided by Ehrhardt-Martinez and Laitner (2008). Some considerations on actual and potential job creation by energy efficiency improvement programs are provided by Granade et al. (2009), where the potential for the USA is estimated to lie between 600,000 and 900,000 jobs over the next decade in direct, indirect, and induced jobs. Energy efficiency will not be the sole solution. There will still be a need for new, additional power plants, partly to meet increased demand, partly to replace old ones. Also, there might be additional demand that is now unaccounted for, e.g., to power electric vehicles (Granade et al. 2009) that are likely to replace traditional cars to some extent. A national commitment to green buildings has the potential to generate 2.5 million and to support 8 million American jobs (US Green Building Council 2015), with similar prospects being offered in other countries. The job market potential of clean energy is reviewed in Wei et al. (2010).

Downside of Energy Efficiency While energy efficiency as such is indisputably a good thing, there are several aspects that have to be considered to avoid detrimental overdoing. First, the economics have to be considered. In a competitive landscape, corporations will only implement energy efficiency measures that “pay for themselves” (see also later). High upfront investments are one of the barriers toward better energy efficiency. Apart from costs, complexity is another aspect to consider. In order to improve the efficiency of a plant or an engine, advanced control systems are required, which need to be maintained. Capable technicians and additional resources have to be provided to that end. The most economic process might not be the most reliable one. As operability of technical equipment, particularly in the capital-intensive process industry, is of utmost importance, some concessions to energy efficiency are sometimes well accepted from a process point of view. For many production plants, 1 day of additional, unplanned shutdown per year will mean the difference between profit and loss. Also, plant personnel might focus on other aspects than energy efficiency when operating a unit or equipment (Moore 2005) to safeguard “trouble-free” operation or simply be too busy to concentrate on continuously optimizing energy usage. Another extreme, hypothetic example of an inefficient energy saving attempt

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would be a person having an accident at home because of not turning on the light when fetching something from the cellar or during the night. For these reasons, it might happen and even be advisable not to squeeze out the last bit of energy efficiency from a given system, but rather to act with commonsense.

Energy Efficiency Versus Energy Demand: The Rebound Effect The effect that energy efficiency improvements on the microlevel (i.e., machines and individual plants in industry) do not fully translate into the expected energy savings on the aggregate level (such as the economy) is termed rebound effect or Jevons paradox. It is also called the Khazzoom-Brookes postulate. The rebound effect can be direct or indirect. If it is >100 %, it is called “backfire” (Sorrell 2009). Simply put, energy efficiency makes energy services cheaper, so demand tends to increase. This concept is called “elasticity of demand.” A more economic car might tempt its owner to drive faster and further, thus partially offsetting potential energy savings. A car producer can decide to install more electronic devices for increased driver comfort in a car that has been made more fuel efficient, thanks to the use of lightweight construction materials and a better engine. The extent of the rebound effect depends on the elasticity of demand, which tends to be stronger with consumers than with industrial plants (Sorrell 2009). William Stanley Jevons studied the rebound effect during the industrial revolution (Sorrell 2009). In his 1865 book The Coal Question (Jevons 2008), he was pondering over the question whether efficiency measures would really lower actual coal consumption, based on empirical evidence that after efficiency improvements with steam engines and in steel production, the actual energy consumption had soared. For more information, see Saunders (1992) and Herring and Sorrell (2009).

Energy Intensity Intensity is an ambiguous term. In physics, it is power per unit area [W/m2], a timeaveraged energy flux. In heat transfer, intensity commonly denotes the radiant heat flux per unit area per unit solid angle [W  m
2  sr
1]. Here, energy intensity is an economic concept as a measure of the energy efficiency of a nation’s economy. It is calculated as units of primary energy consumption per unit of GDP or value added, measured in [MJ/$] or [toe/$]. The energy intensity of a country is influenced by many factors, for instance, the climate. Economic productivity and standards of living contribute as well as the energy efficiency of buildings and appliances, traffic patterns (public transportation vs. individual cars), and the way energy is being produced (EIA 2015). Energy intensity can hence be used as a surrogate for aggregate energy efficiency. Countries differ strongly by energy intensity, and within countries, there are marked differences amongst regions. In the USA, a state with superior energy efficiency

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performance is California, which has established leadership in, e.g., per capita energy consumption (Rosenfeld 2008; Vine et al. 2006). The energy efficiency of different countries is assessed in Utlu and Hepbasli (2007). The term “energy intensity” can also be applied to a production process as a synonymous expression for specific energy consumption, based on quantity [kg] or value added [$] or [€]; see also section “Energy-Intensive Industries.”

Emission Intensity (Carbon Intensity) Another concept is the emission intensity. It is the average emission rate of a given pollutant from a given source related to the intensity of a specific activity, e.g., grams of CO2 per MJ of energy produced [g/MJ]. The term emission intensity is often used interchangeably with “carbon intensity” and “emission factor” in the climate change discussion. Other greenhouse gases and pollutants can be considered, too, by calculating CO2 equivalents (CO2-eq). Table 3 provides an overview on emission intensities, compiled from Bilek et al. (2008). The subscripts in Table 3 stand for “thermal” and “electric.” In combined heat and power (CHP, cogeneration), both heat and power are produced from a combustion process, boosting overall efficiency (see later).

Historical Development of Energy Efficiency A proverb says “Things that cost nothing have little value.” In this sense, as long as easy access to energy is available, there are few incentives to use it wisely. History tells several lessons here. Visitors to Greek islands will witness testimony of one such unsustainable practice exercised centuries ago, i.e., chopping down trees to build ships without reforestation. There are countless other examples of unsustainable acts related to resource and energy efficiency in the past, some of which have even led to the extinction of a local human population (Bologna and Flores 2008). The global oil crises in the 1970s were an event that has triggered several measures for energy efficiency on a large scale, e.g., the creation of the DoE (Department of Energy) in the USA. In the following decade, when crude oil prices Table 3 Emission intensities (Source: Bilek et al. 2008). The ratio of H/C is 4 in natural gas, which is higher than in oil and especially coal, leading to lower CO2 emissions per kWh

Fuel/resource Coal Oil Natural gas Nuclear power (U) Hydroelectricity Photovoltaics Wind power

Electric g(CO2-eq)/kWhe 863–1,175 893 587–751 60–65 15 106 21

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went down again, there was reduced motivation to focus attention on energy efficiency in many areas. The industrial sector has improved its energy efficiency continuously over the last 30 years, partly in order to reduce variable production costs and to improve competitive advantage (one also has to take into account that a significant part of energy-intensive production facilities was transferred to lowlabor-cost countries in, e.g., Asia). Economic growth, a trend toward increased personal mobility and toward larger homes and the use of more and more appliances, amongst others, has led to a steady increase of absolute energy demand in most industrialized countries. As a result, the overall energy intensities in the USA have declined as follows between 1980 and 2005 (Granade et al. 2009): Residential sector Commercial sector Industrial sector


11 %
21 %
42 %

While the national per capita energy consumption in the USA has grown by 1.3 % per year from 1977 to 2007, which means a doubling, it remained almost constant in California. In the EU, the average efficiency of gas-fired power plants has increased from 34 % in 1990 to 50 % in 2005 and is expected to increase to 54 % by 2015 (Graus and Worrell 2009). For coal-fired power plants, the efficiency, also based on the lower heating value, went up from 34 % in 1990 to 38 % in 2005 and is expected to increase to 40 % by 2015. These trends are visualized in Fig. 2. As the developed world has built its industry, specific energy consumption was constantly improved. Yet the largest share of historic and current global emissions comes from developed countries. Many people now fear that while other countries race through their development, they might expel “their share,” i.e., high amounts of pollutants, into the atmosphere. China, for instance, has been able to maintain economic growth of greater than 9 % from 1980 to 2000, while the energy demand only increased by 3.9 % per year (Lin 2007). This shows that energy demand does not necessarily have to outpace economic growth during the early stages of industrialization and development (Lin 2007). A word of caution: Many scientific publications, as well as the public opinion, believe in decreasing energy intensity over time. This hypothesis is often only an assumption, which needs to be proven. In Le Pen and Sévi (2010), the authors conclude that many energy efficiency trends on a national level follow a stochastic nature; see Fig. 3. In Schipper et al. (2005), historic developments and future trends of energy efficiency are discussed. Megatrends (Naisbitt 1985) will also have an impact on energy efficiency. How they are perceived can differ strongly (Atilla Oner et al. 2007). In general, there have been strong improvements in certain areas with respect to energy efficiency, some of which were countered, though, by rebound effects.

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Fig. 2 Energy efficiency trends of fossil fuel combustion in the EU27 (Reprinted with permission from Elsevier from Graus and Worrell (2009))

Assessing Energy Efficiency Improvements Energy efficiency improvements can be achieved by technological progress or by changes in behavior. They can be measured. However, for a correct assessment, the following factors have to be taken into account: • Erosion of part of the improvements by the rebound effect (see above) • Comparability of data (same year, same boundary conditions) • Selection of a proper baseline The baseline for measuring energy efficiency is of utmost importance to avoid wrong conclusions. This is elaborated with an example from the transportation industries below, viz., the fuel consumption of aircraft over time. Figure 4 shows a data compilation of how fuel efficiency of commercial aircraft was improved over the last decades. Taking the Comet 4 as a baseline, fuel consumption was reduced by 70 % in modern aircraft. Approx. 40 % of the improvements are attributed to engine efficiency improvements, and 30 % to airframe efficiency improvements (IPCC 2000). The de Havilland Comet was the world’s first commercial jet airliner (Davies and Birtles 1999). Figure 4 was taken from an IPPC report. The IPCC (Intergovernmental Panel on Climate Change) is a renowned, scientific intergovernmental body established to evaluate the risk of climate change caused by human activity (Intergovernmental

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–6

x10 2

Oil consumption (bl.) / GDP

1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 1965 1970 1975 1980 1985 1990 1995 2000 2005 4.5

x10

–6

Oil consumption (bl.) / GDP

4 3.5 3 2.5 2 1.5 1 0.5 0 1965 1970 1975 1980 1985 1990 1995 2000 2005 Fig. 3 Stochastic movement of energy consumption. Left: oil consumption per unit of GDP for OECD countries from 1965 to 2005. Right: same data for non-OECD countries (Reprinted with permission from Elsevier from Le Pen and Sévi (2010))

Panel on Climate Change (IPCC) 2015). It was awarded the 2007 Nobel Peace prize together with Al Gore. In Peeters et al. (2005), the authors argue that the pre-jet era was ignored in the above IPCC discussion and that the Comet 4 is an unsuitable baseline. From the conclusions of that report (Peeters et al. 2005):

1950

20

30

40

50

60

70

80

90

B707-320 DC8-30

1960

DC8-61 B707-320B

B707-120B

B747-100B

1970 1980 Year of Model Introduction

B747-200

B747-200B

B747-100B

B747SP

B747SP

DC10-30

DC10-30

B747-200

B747-100

DC8-63

SVC10

B747-100

B707-120 SVC10 DC8-30 B707-320 DC8-63 B707-120B B707-320B DC8-61

B707-120

Comet 4

B747-300 A310-300

B747-200B

A310-300

1990

B747-400

A330-300

A340-300

A300-600R

Aircraft Fuel Burn per Seat

A340-300

A330-300

B747-400

A300-600R

B747-300

Engine Fuel Consumption

Fig. 4 Fuel efficiency of commercial aircraft over the last 50 years. See text for details. Reprinted with permission (Source: IPCC 2000)

% of Base (Comet 4)

100

2000

B777-200

B777-200

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Fig. 5 IPCC graph with additional data (Reprinted with permission from Peeters et al. (2005)) The later piston-powered airliners were at least twice as fuel-efficient as the first jet-powered airliners; If, for example, the last piston-engine aircraft of the mid-fifties are compared with a typical turbojet aircraft of today, the conclusion is that the fuel efficiency per available seatkilometre has not improved. . .. The last piston-powered aircraft appear to have had the same energy efficiency per available seat-kilometre as average modern jet aircraft. The most modern jet aircraft (such as the B777-200 or B737-800) are slightly more efficient per available seat-kilometre.

The findings from this study are depicted in Fig. 5. As it can be seen in Fig. 5, slight changes in the assumptions will lead to strong deviations in the results. This has to be borne in mind when assessing and comparing energy efficiency studies presented by various interest groups.

Innovation and New Technologies for Energy Efficiency In order to increase energy efficiency, innovation (Christensen et al. 2001) is needed. By innovation, either of the following energy efficiency improvements can be achieved: • Carrying out the same task or process with less energy • Utilizing the same amount of energy to produce more output or higher value • Redefining the task or process so that the new way consumes less energy

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Innovation can take place in incremental steps or in a disruptive way, when a new technology is developed, for instance. The electric light bulb, being condemned as energy inefficient today, was one such disruptive innovation, which has been around for more than a century. So in order to innovate, engineers and researchers might be tempted to search and build more knowledge in their own area of expertise and to innovate as much as possible in their very own fields. This strategy has proven successful – take the famous Bell Labs (Gehani 2003) as an example. Fifty years ago, the Bell Labs were generating every new technology that the telephone business needed, and the telephone business, in turn, was using all of Bell Labs’ innovations. Bell Labs were virtually unbeatable. However, the rules of innovation have changed somehow over time. The Bell Labs invented the transistor, which clearly is one of their greatest discoveries. However, Bell Labs did not recognize the value of the transistor, and they gave it away for little money. The transistor, hence after, was extremely successful, but with the main use not being in the telecommunications industry. On the other hand, the very innovation that revolutionized the telecommunications industry – the fiberglass cable – was developed outside that industry. This phenomenon has been observed in many industries over the last 50 years (Drucker 2003) – the major innovations with the biggest impact for an industry are not likely to come out of the industry itself but will rather be “born” in a different area. The significance of this development for the realm of energy efficiency is as follows: Energy efficiency can be improved in many ways. In a passenger car, for instance, an advanced engine, lightweight plastics components instead of steel or tires causing less rolling friction will all serve the same final purpose of energy efficiency. Innovation takes time until its full potential is being realized, though. In Lund (2006) the market penetration rates of new energy technologies were studied. It is concluded there that the time for a takeover of market share from 1 % to 50 % varies from less than 10 years to 70 years, with takeover times below 25 years being associated with end-use technologies. Long investment cycles render the energy production industry inert to change.

Typical Energy Efficiencies The energy of photosynthesis is on the order of 1 %, with a fraction of approx. 0.2 % being stored as biomass. Sugarcane exhibits peak storage efficiencies of up to 8 % (Hall and Rao 1999). The first steam engines, designed as external combustion engines, had efficiencies on the same order of magnitude. To visualize the energy balance, i.e., the energy efficiency, of a process or machine, a Sankey diagram can be used. For exergy, Grassmann diagrams (Hinderink et al. 1999) are deployed (though both terms are sometimes used interchangeably in the literature). An example for a Grassmann diagram for nitric acid production is shown in Fig. 6 (Hinderink et al. 1999).

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Fig. 6 Simplified Grassmann diagram for the production of nitric acid (Hinderink et al. 1999) (Reproduced by permission of the Royal Chemical Society (RCS))

The Grassmann diagram can be seen as an energy flow diagram, visually explaining which fraction of the total, initial energy ends up in the final product. In order to obtain typical energy efficiencies, or reference energy efficiencies, a benchmark is deployed. The benchmark in energy efficiency is given by the state-ofthe-art and so-called BAT (best available technology) values. However, BAT values are often difficult to obtain, as corporations tend to keep them secret and patents do not always provide full disclosure. The energy efficiency and carbon intensity of a given process depend on the system boundaries that are considered and on the energy path. For instance, whether electricity for a hybrid car has been produced in a coal-fired power plant or by solar cells will heavily impact the overall efficiency (see also section “Life Cycle Assessment (LCA)”). Actual efficiencies will depend on a large number of factors such as the condition of a given system or appliance. Examples are the load of an engine, maintenance on motors, and usage patterns. This is obvious for every car owner who wants to reach the “official” fuel consumption of his/her car. When energy efficiency potentials are presented in the literature, one has to be careful not to overestimate or mix up the various potentials, which are: • Technical potential • Economic potential • Maximum achievable potential (considering factors such as demographics, market conditions, and regulatory factors) • Realistic achievable potential (taking historic data into account) People adapt to change at different rates. Take popular technologies as an example. Even for microwave ovens and mobile phones, it took 10–15 years for market penetration. Therefore, the realistically achievable potential is never equal to

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the full technical potential. Also, the effort to obtain a large part of any potential saving will increase along the way. For energy efficiencies of various technologies, processes, and appliances, the reader is referred to the respective chapters of this handbook and to the specialized, referenced literature.

Benchmarking of Energy Efficiency There are no useful reference data for absolute energy efficiency from a thermodynamic or theoretical point of view. Rather, one can only compare a given process or technology route, device, or method to other solutions in the lab or in the field, so that the best available technology (BAT) or state of the art can be determined empirically. Such a benchmarking exercise focused on energy efficiency will yield interesting results. In Phylipsen et al. (2002), for instance, it was found that the energy consumption of the steelmaking plants in several countries was 25–70 % above the best plant. In the cement industry, the average consumption was 2–50 % higher than the very best plant energy efficiency. Benchmarking can be used by operators of industrial plants to compare their energy efficiency, and ultimately their competitiveness, to that of their contenders. Consumers can use relative indications of energy efficiency, such as the Energy Star ® label, to easily spot energy-efficient appliances as a guide for purchase decisions. It needs to be mentioned that comparing like with like is crucial. If, for instance, steelmaking plants in two countries are to be compared, sectoral differences must be taken into account (Phylipsen et al. 2002) (if, e.g., there is plenty of secondary steel available, energy efficiency will “automatically” be higher). Also, regional differences in feedstock quality (Worrell et al. 2000a) or climatic conditions will affect the energy efficiency of a given plant. More information of reliable reference data for energy efficiency comparisons on a national level can be found in Doukas et al. (2008). In mature industries, energy efficiency differences from plant to plant are not expected to be very large, because improvements tend to be incremental. Generally, there is a lack of energy efficiency benchmark standards for industry at large and factories in various sectors (Yang 2010), secrecy and antitrust legislation being important impeding factors. There exist corporate benchmarks in some companies that operate multiple plants or sites. Several consultants carry out benchmarking studies in various industries, e.g., Solomon Associates for steam crackers, Phillip Townsend Associates for polymerization plants, Plant Services International for ammonia and urea plants, and PDC (Process Design Center) for more than 50 petrochemical processing plants (The International Energy Association in Collaboration with CEFIC 2007), to cite a few examples. These benchmarks present generalized and anonymized data with which the energy efficiency and the competiveness of one’s own plant can be compared to the industry average.

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Energy Efficiency World Records A world record in energy efficiency of a car was set in 2005 as 5,134 km per liter of gasoline equivalent, operating on a hydrogen-powered PEMFC (polymer electrolyte membrane fuel cell) (Santin 2005) during the Shell Eco-Marathon. It challenges students around the world to design, build, and drive the most energy-efficient car and has three annual events in Asia, America, and Europe. On the website of the competition (Shell Eco Marathon 2015), additional records on energy efficiency are highlighted, e.g., an equivalent of 3,771 km with 1 l of fuel with a combustion engine-powered car in 2009 (5 years earlier, the record was 3,410 km). These figures, equally impressive and irrelevant for current practical road transportation, show that there is plenty of potential left to increase energy efficiency, even beyond current imagination.

Some Not-So-Energy-Efficient Inventions and Practices Here are some examples of low-energy-efficient appliances and habits, most of which might soon astonish people that they even existed in our times: • • • • • • •

Incandescent light bulbs Huge private cars such as SUV with single occupancy Standby function on electrical appliances in households Patio heaters to warm open areas outside the house Melting snow in cities such as New York City to dispose of it Flaring of hydrocarbons in petroleum refineries Room temperature regulation by opening and closing a window, while keeping the heater switched on • Water ring pumps to produce an industrial vacuum In a typical household, appliances on standby use up 10 % of the total amount of electricity consumed. This is equivalent to 400–500 kWh annually, virtually wasted with no energy service rendered.

Barriers to Energy Efficiency There is no doubt about the fact that energy efficiency offers cost-effective energy savings. However, the full potential has barely been tapped into. There are several barriers, associated with financial limitations, uncertainty, or others. They can also be classified as structural and behavioral and related to availability (Granade et al. 2009). Though businesses and households are responsible for implementing most energy efficiency investments, it is their governments to provide the right bordering conditions to catalyze investments in energy efficiency by offering tax incentives,

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Table 4 Estimated persistence of energy efficiency measures (Source: Climate Action 2015) Years following implementation (installation) 1 2 3 4 5 6 7 8 9 10

Remaining energy efficiency impact Electricity-related measures Fuel-related measures (%) (%) 99.69 100 95.97 99.46 89.59 98.51 85.14 97.84 84.02 97.11 78.32 89.75 78.22 89.75 78.22 89.75 74.58 89.70 66.73 87.45

education, or other facilitation. One reason why the potential for energy efficiency has not yet been realized to its full extent is the fact that high upfront investments are often necessary, whereas the savings accrue incrementally over the subsequent years (Granade et al. 2009). Also, the energy efficiency improvement potentials are highly fragmented (Granade et al. 2009). Apart from low awareness, the difficulty to measure energy efficiency improvements in several areas contributes to slow progress. Barriers to energy efficiency are discussed in Granade et al. (2009), alongside the following potential actions to break down these barriers: • Information and education • Incentives and financing • Codes and standards Experience shows that consumers are particularly hostile toward funding of energy efficiency measures, compared to businesses, even if the economics are reasonable. They apply hyperbolic discounting, meaning that immediate value is regarded significantly higher than future one. Barriers toward energy efficiency improvements in industrial settings are reviewed in Schleich (2009). Another interesting question is the durability of energy efficiency measures, which was studied in Climate Action Team (2015), the results of which are given in Table 4. The percentages in Table 4 reflect the portion of the first year energy savings that remain throughout the full lifetime of the studied energy efficiency measures. A distinction was made between measures focused on saving electrical energy and measures to save fuel. It can be seen that already after a few years, considerable losses from the initial gains are encountered, which can be explained by various factors depending on the efficiency measure. “Hard-wired” energy efficiency initiatives will generally be lasting longer than those based on behavioral changes (see also below).

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An example on how energy efficiency can stagnate if the economic and organizational conditions are not in favor of it, such as prevailing low electricity prices, is shown for the Swedish building industry in Nässén and Holmberg (2005) and Nässén et al. (2008). Aspects of financing energy efficiency, another prominent barrier, are outlined in Taylor et al. (2008), Lee et al. (2003), Jechoutek and Lamech (1995), and Clark (2001). Barriers to energy efficiency in general are reviewed in Sorrell et al. (2004).

Levels of Energy Efficiency: From Process to Behavior Energy efficiency can be achieved by various means. A product can be manufactured in a way that energy is used efficiently, either during its production or during its use. A process can be energy efficient by itself, or it can produce energy-efficient outcomes. The same applies for services. Here are some examples of more and less efficient products and processes: • Office lighting by compact fluorescent lights/LED versus traditional incandescent light bulbs • Modern compact passenger car versus older, mid-sized model • Cement production by the dry process versus the wet process • Air separation by pressure swing adsorption versus air separation by cryogenic air cooling and fractionated distillation • Steel manufacture from scrap metal versus ore It is desirable to have efficient equipment and processes in place. However, these can be operated in very inefficient ways. The magnitude of loss in energy efficiency by “bad” operation can be as large as the difference between competing processes and equipment items (Moore 2005). Some examples of these “bad” operation aspects are: • • • • •

Excessive speeding with a car, which strongly increases fuel consumption/km Neglected maintenance on insulation of window frames in a private home Keeping office lights on overnight when they are not needed Operating plant utilities at full capacity during idle production times Not repairing leakages on compressed air pipelines

In contrast to the installation of new, more energy-efficient equipment, or the design of a more energy-efficient process, operation thereof requires constant attention (compare also the table above, showing the stunning erosion of energy efficiency gains over a few years’ time). By continuously working on a mindset toward energy efficiency, for instance, by having employees turn off idle equipment and by fostering continuous improvement, also small, individual savings can add up. In Moore (2005), some aspects of why operators in control rooms do not always give utmost importance to energy efficiency are listed:

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• Lack of urgency, little incentives to value long-term performance versus the short term • Preference of steady-state operation versus short-term optimization efforts • Comfort, trading economy against less effort • Individual work history and anecdotes making risk perception highly personal • Different levels of skills and knowledge • Instinct to preserve assets rather than maximize their utilization • Little effect of administrative control measures alone • Focus drift due to distraction The most economic mode of operation of a plant in the process industries, for instance, is not always the most convenient one (Moore 2005). This will lead operators to at least partly refrain from energy efficiency optimization. Such “human factors” can be improved by considering the usability of processes and equipment. Whereas the usefulness of a man-made tool or installation is related to user satisfaction, the term us(e)ability denotes the ease with which it can be deployed. In general, usability can be defined as a measure of the ease with which a system can be learned or used; its safety, effectiveness, and efficiency; and attitude of its users toward it (Jordan et al. 1996). In Nachreiner et al. (2006) and Nishitani et al. (2000), two examples of the successful application of usability and usability engineering in process control systems and industrial plants are given.

Energy Efficiency Investments As energy-efficient technologies often have higher initial investment costs than older, less advanced ones, economic considerations will determine the extent to which energy efficiency is considered for new investments and for retrofits alike. The TCO (total cost of ownership) approach will clearly recommend energy efficient, but typically more expensive installations, in many cases. Investing in “the right technology,” if it is not supported by a sound business case of yearly energy bill savings, will be easier during the construction of a new building or factory than when one wants to apply for funds, corporate and federal alike, later on. In industry, one can distinguish between: • Pure capacity investments • Pure energy efficiency investments • Hybrid capacity and energy efficiency investments Common appraisal methods for investment projects in industry are: • Payback period • Net present value (NPV)

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• Internal rate of return (IRR): discount rate where NPV = 0 • Strategic fit Approval can be based on an evaluation of several of these parameters, by a ranking or by fulfilling a certain cutoff criterion. To test the validity of the profitability calculation of such a project, a sensitivity analysis can be carried out by varying the most important parameters. Monte Carlo simulation enhances the quality of such simulations (Lackner 2007). Real options (Rugman and Li 2005) can also be used. While debottlenecking investments, which increase production capacities, usually have short payback periods and high IRRs, often exceeding 50 %, energy efficiency investments sometimes cannot make it over the 10 % hurdle. If the funds for investment projects are limited, naturally those with higher IRR will be preferred. Energy efficiency investments can be carried out at a lower IRR than a corporation’s normal hurdle rate (IRR), because the associated risk is generally lower than for a capacity investment (energy savings can be predicted more reliably). Often, when “selling” an energy efficiency project in a corporation, one had to better avoid the term “energy” and describe potential projects as “efficiency” or “productivity” improvement projects when presenting them to decision makers. Energy has a different importance for various sectors. Those industries which are energy intensive will suffer more from high and volatile energy prices than the ones incurring only a small percentage of their costs from energy bills. It is estimated that out of the total global economic activity (according to the International Monetary Fund (IMF) US$77.609 trillion (GDP) or US$106.998 trillion (purchasing power parity, PPP) for 2014), 40 % comes from companies where energy plays a strategic role (McKinsey & Company, Inc. 2009). The sectors concerned are transportation, building and construction, energy-intensive industries, engineering, IT (information technology), and the energy industry. For companies in these sectors, energy can have a direct or indirect effect, i.e., on their own production costs or on the acceptance of their products. On the other side, there are industries, such as education, retail, insurance, and healthcare, which do not depend as much on energy competitiveness.

Introducing Energy Efficiency Programs It is estimated that most organizations have a potential for 10–20 % energy efficiency improvement, which will materialize in the bottom line. In order to improve energy efficiency in a company or another larger institution, an energy survey or an energy audit can be a first step to map out the saving potential. More information on such energy audits can be found in Sustainable Energy Ireland (SEI) (2015) and Carbon Trust (2015). They consist of data collection (“hard facts” such as electricity consumption and interviews on common practices) and internal and external benchmarking. There is currently a lack of qualified energy auditing staff (Yang 2010). Checklists can help to uncover inefficiencies in processes and equipment.

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In the EU, Directive 2012/27/EU of 25 October 2012 on energy efficiency has introduced compulsory energy audits for large corporations in an attempt to foster energy consumption reduction. Using off-peak hour electricity is an option to shrink the electricity bill. How to manage energy efficiency in a corporation is described in Russell (2009). To which extent agreements foster energy efficiency is analyzed in Rietbergen et al. (2002).

Combustion Combustion plays a critical role in energy efficiency considerations, as approx. 80 % of global primary energy is produced by combustion processes. Combustion processes have the single largest human influence on climate with 80 % of anthropogenic greenhouse gas emissions (Quadrelli and Peterson 2007). Fuels can be fossil or renewable (biomass). They are gaseous, liquid, and solid. Combustion is used in power plants for electricity and heat production, transportation, and other areas (see sections below for details). Figure 7 shows the global trend in CO2 emissions over the last 140 years (source: Quadrelli and Peterson 2007). As it can be inferred in Fig. 7, the increase in anthropogenic, combustion-derived CO2 emissions has almost been an exponential one. For the impact on climate change, not only the efficiency of a combustion process itself but also emissions generated during fuel production and transportation have to be considered. For instance, for every kg of mined coal, 1.2–16.5 g of the greenhouse gas methane (GWP = 21) are emitted (Office of Energy Efficiency, Natural Resources Canada 2002). Combustion can be carried out in furnaces (see section “Power Plants and Electricity Production” below) and boilers, in internal and external combustion engines, and in gas turbines (Pilavachi 2000; Boyce 2006; Farzaneh-Gord and Deymi-Dashtebayaz 2009). Fig. 7 Trend in CO2 emissions from fossil fuel combustion (Source: Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, TN, USA). Units: Gigatons of CO2 (Reprinted with permission from International Energy Agency (2014))

GtCO2 35 30 25 20 15 10 5 0 1870

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Pyrolysis and gasification are special cases of combustion. These processes can be used to obtain gaseous or liquid fuels from biomass or coal in conjunction with a Fischer-Tropsch (van Vliet et al. 2009; Prins et al. 2004) or other synthesis processes. Due to the removal of moisture and ash and the effect of deoxygenation, liquid hydrocarbons derived from biomass have a threefold energy density and are hence more advantageous for transportation and storage (Demirbas et al. 2000). See also chapter “▶ Gasification Technology” in this handbook. Heat recovery from flue gases is a particularly energy-efficient measure. For steam systems, for instance, 1 % of fuel can be saved for every 25  C reduction in exhaust gas temperature (Galitsky 2008). In Quadrelli and Peterson (2007), recent trends on CO2 emissions from fuel combustion are reviewed. For combustion in general, see Lackner et al. (2010) and Lackner et al. (2013).

Power Plants and Electricity Production 12 % of man’s total energy is made up by electricity, a fraction that is expected to rise to 34 % until 2025 (Ibrahim et al. 2008). Energy efficiency in electricity production can be defined as the energy content of the produced electricity divided by the primary energy input, with reference to the lower heating value (Graus and Worrell 2009). The lower heating value (LHV, or net calorific value) assumes that the water formed in combustion remains as vapor. In cogeneration, the overall efficiency can be increased, because the (by-product and formerly waste) heat is used. Cogeneration is also dubbed CHP (combined heat and power). Power production is carried out by (large) public power and CHP plants and by so-called autoproducers. These are users such as chemical factories which produce their own power and heat. In the EU, autoproducers account for 8 % of the total power generation (Graus and Worrell 2009). Electricity production plants have an efficiency of around 30–40 %, whereas combined heat and power (CHP, cogeneration) yields up to 90 % (Office of Energy Efficiency, Natural Resources Canada 2002). For the installed base of CHP, see CHP Installation Database (2015). In the EU, the energy efficiencies for coal-fired power production range from 28 % (Slovak Republic) to 43 % (Denmark). On a global scale, the spread for oil-fired power plants is an efficiency of 23 % for the Czech Republic and 46 % for Japan (Graus and Worrell 2009). The efficiency of a given power plant is dependent on its age. The younger a plant, the higher its energy efficiency was (intuitively) found to be (Graus and Worrell 2009). These findings are in line with another study (Phylipsen et al. 2002), which revealed that the least energy-efficient plants are not always located in developing countries. Apart from the age of a plant, its fuel mix, size, and load account for the big differences in efficiencies mentioned above (see also section “Cross-Cutting Technologies” below).

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State-of-the-art power plants based on coal and gas have energy efficiencies of 46 % and 60 %, respectively (Graus and Worrell 2009). It is estimated that the replacement of inefficient coal-fired power plants by more efficient coal- or gas-fired ones, particularly in China and in the USA, can reduce global CO2 emissions by 5 % (IEA 2009). In Canada in 1988, according to the Canadian Industry Program for Energy Conservation (CIPEC), the average CO2 emissions in electricity production were 0.22 t/MWh, with a spread of 0.01 in Quebec to 0.91 in Alberta (Office of Energy Efficiency, Natural Resources Canada 2002). Demand side management (DMS) can help to level peak electricity demand (Loughran and Kulick 2004). This will be even more important as more renewable energy plants (wind, solar) are installed, where electricity production and consumption hardly coincide. Energy is increasingly being produced from waste. Methane can be extracted from landfills for power production in gas engines. Waste incineration uses the energy content of waste and converts it to a low-volume, inert residue. While previously the focus of waste incineration plants was on low-emission combustion to get rid of the waste, today the energy efficiency of these plants has become important, too. In Bujak (2009), an incineration plant for medical waste is presented. It is equipped with a heat recovery system and can extract 660–800 kW of usable energy from 100 kg/h of medical waste with an energy efficiency between 47 % and 62 %. New and innovative pyrolysis and gasification technologies for energyefficient waste incineration are presented in Malkov (2004). In Dijkgraaf and Vollebergh (2004), waste incineration is compared to landfilling, and in Cherubini et al. (2009), a life cycle assessment (LCA) (Guineé 2002) of waste management strategies is performed.

Energy Transmission and Distribution Today, electricity production is centralized, with large power plants being coupled to a complex distribution network. Energy transmission and distribution cannot be performed in a totally loss-free way (leaving apart superconductivity, where electrical resistance is exactly zero). In Europe, they typically amount to 4–10 % and hence reduce the overall efficiency of power supply by several percent points (Graus and Worrell 2009). For the USA, EIA estimates that national electricity transmission and distribution losses are approx. 6 % (FAQ and US Energy Information Administration). In India, losses are estimated at 32 %, which is significantly above the global average of 15 % (Joshi and Pathak 2014). Transporting the fuel to end users is more cost effective yet also consumes substantial amounts of energy (see sections below). Natural gas, for instance, is being pumped across long distances, because placing a gas power station next to the gas field and transmitting the electricity and heat would result in a considerably lower overall efficiency than compressing and moving the gas through pipelines.

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Globally, Russia is the largest producer and transporter of natural gas. Methane emissions from the Russian natural gas long distance network are estimated at approximately 0.6 % of the natural gas delivered (Lechtenböhmer et al. 2007).

Energy Storage The need for more and cleaner energy leads to an increase in distributed generation (DG) and renewable energy sources (RES) (Hadjipaschalis et al. 2009). Since such sources like wind power are not as reliable and as simple to adjust to demand fluctuations as conventional power plants, they could be coupled with energy storage systems. Power demand by (end) users fluctuates strongly. Typically the lowest consumption during a 24-h period is nearly half the peak demand (compare Fig. 8). Today, with a mainly centralized electricity production scheme, there is only a small storage capacity available, amounting to approx. 90 GW or 2.6 % of the total production of 3,400 GW (Ibrahim et al. 2008). With DG and RES on the increase, it is expected that energy storage, more specifically electrical energy storage, will gain significance on a local (small) and regional (large) level. Energy can be stored in various ways, for instance, as: Potential energy Kinetic energy Chemical energy Thermal energy

Pumped hydro storage (PHS, i.e., pumping water up into a reservoir, so that it can later drive a turbine) or compressed air energy storage systems (CAES, i.e., compressing gas in a cylinder) Accelerating a flywheel Batteries (Rydh and Sandén 2005), fuel cells (H2) Use of sensible or latent heat (Ibrahim et al. 2008), e.g., of NaOH

Lead batteries are well known for the storage of energy; however, they are heavy and inapt for high cycling rates. Rydh and Sandén (2005) discuss the energy efficiency of batteries. In Ibrahim et al. (2008) and Hadjipaschalis et al. (2009), an overview on current and future energy storage technologies is given. They differ in their maturity, target use (e.g., portable or fixed, long- or short-term storage), specific power (power density) [W/kg] and specific energy (energy density) [Wh/kg], the lifetime (number of cycles), the self-discharge rate, and the costs per installed kWh. Hydrogen storage options are reviewed in Hirscher and Hirose (2010). In Ibrahim et al. (2008), the energy efficiencies of various energy storage technologies are compared. An interesting option for electrical energy storage is power to gas (P2G, PtG) (Gahleitner 2013). Energy storage (and conversion) is always associated with losses.

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Reduced consumption

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Fig. 8 Average daily power consumption in France (Reprinted with permission from Elsevier from Ibrahim et al. (2008)). Peak demand happens in the morning and afternoon, with the lowest demand being met in the early morning hours

Life Cycle Assessment (LCA) Life cycle assessment (LCA) (Guineé 2002), also called life cycle analysis, is a holistic view on a product or service. As the name implies, all steps from its raw material production, manufacturing, transportation, distribution, use, and disposal are considered to determine the overall effect that a given product has on the environment. LCA is rooted in the ISO14001 environmental management system standard, more specifically in ISO 14040, 14041, 14042, and 14043 (ISO 2015). The ISO standard for energy management is ISO 50001. Variants of life cycle analysis are: Cradle-to-grave analysis Cradle-to-cradle analysis Cradle-to-gate analysis Gate-to-gate analysis Well-to-wheel analysis Wire-to-water efficiency

(Full life span) (Including recycling) (Partial process) (One step) (Used in the automotive industry; see below) (Used for pumps; see later)

Eco-balance is a synonymous expression for LCA. An illustrative example for the value of LCA is the use of plastic materials for insulation purposes. Within 4 months of use, the energy savings can equal the energy needed for production, with a service life of up to over 50 years (The International Energy Association in Collaboration with CEFIC 2007). In transportation, LCA is typically done as well-to-wheel (WtW) analysis, which is an overall fuel efficiency calculation (there are also the standard LCA studies for cars, ranging from production to use and disposal). WtW efficiency, detailed in Braungart et al. (2007), van Vliet et al. (2009), Svensson et al. (2007), and Hekkert et al. (2005), is a similar concept as life cycle energy efficiency (Malça and Freire 2006). Both concepts can be understood as overall efficiencies of a process chain, calculated as the product of the individual efficiencies.

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Fig. 9 Well-to-wheel efficiencies under hot starting conditions (Reprinted with permission from the Society of Automotive Engineers (SAE) from Ellinger et al. (2001)); ICE internal combustion engine, NG natural gas, CNG compressed natural gas, AFC alkaline fuel cell, SOFC solid oxide fuel cell, PEMFC polymer electrolyte membrane fuel cell

WtW efficiencies allow meaningful comparisons between different technologies, for instance, internal combustion engines (ICEs) versus fuel cell (FC) vehicle technologies. They provide for a fair comparison. Figure 9, taken with permission from Ellinger et al. (2001), shows the efficiency chain for different automotive propulsion systems under hot start conditions. In Fig. 9, the WtW efficiency is calculated as the product of conversion efficiency ηc, distribution efficiency ηt, and propulsion system efficiency ηp as shown in equation 6: η ¼ ηc ηt ηp

(6)

The conversion efficiency ηc for gasoline and diesel production in a refinery is quoted as 88 % in Heitland et al. (1990) and as 63 % for their production from methanol according to the Lurgi process (20 years ago), and the distribution efficiency ηt as 97–98 % in The International Energy Association in Collaboration with CEFIC (2007). In Fig. 9, it can be seen that the CNG-SOFC (compressed natural gas-solid oxide fuel cell) combination achieved the best overall efficiency of around 35 %, with the best internal combustion engine performance being 29 % for diesel from crude oil (the International Energy Association in Collaboration with CEFIC 2007).

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The eco-balance of biodiesel, for instance, has to consider the consumption of fossil fuels and materials for its production, e.g., the use of lubrication oil. Another important term is that of the energy path. The production process will strongly impact energy consumption. Methanol, for instance, can be produced via a path starting from sugarcane (1st-generation biofuel), from lignocellulosis (2nd-generation biofuel), or from natural gas (traditional), which will yield different eco-balances. An interesting website on LCA is run by the US Environmental Protection Agency (EPA) (http://www.epa.gov/nrmrl/std/lca/lca.html 2015). A related concept to LCA is the embodied energy (Venkatarama Reddy and Jagadish 2003). It is often used for buildings (see later). Also in other industries, significant amounts of energy are “stored” in the final product. In the case of the petrochemical and chemical industries, which consume 30 % of global industrial energy, more than half of the energy is locked up in the final products (the International Energy Association in Collaboration with CEFIC 2007) and can be recaptured at the end of their lifetime. The total life cycle of a product can not only be assessed with regard to energy use and environmental aspects but also from an economic point of view – in terms of costs. In this case, one speaks about life cycle costs (LCC) or total cost of ownership (TCO). Recycling is an important aspect of life cycle assessment. The primary energy demand for “new” materials is often considerably higher than that needed to recycle them from waste. For instance, if aluminum cans are recycled, the energy consumption will only be 5 % of the energy needed to make them from virgin bauxite ore. Scrap metal, glass, paper, and plastics should be recycled to make best use of their “energy content,” as primary production tends to consume more energy than secondary one. In the case of plastics, “thermal recycling” is an advantageous, final use if other types of recycling are not feasible. The 3Rs (reduction, reuse, recycling) are approaches to limit the quantity of primary raw material demand, hence contributing to sustainability.

Total Cost of Ownership (TCO) The total cost of ownership (TCO) concept acknowledges the fact that the use of any equipment has two types of costs associated with it: • Initial investment costs • Running costs over the entire useful lifetime (energy, maintenance, disposal, etc.) For industrial pumps, for instance, which are typically in service for 15–20 years, the initial investment cost is often less than 5 % of total incurred costs (Tutterow et al. 2002). For a majority of industrial assets and facilities, the lifetime energy will dominate the life cycle costs, which is also the case for many equipment items in private homes. More information on TCO can be found in Braun and Leiber (2007),

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US Department of Energy (2005), and Sorrell et al. (2004), with the latter two providing ample coverage of economic evaluation of energy efficiency.

Energy Efficiency in Various Sectors In the following sections, energy efficiency in various areas is discussed. As is shown in Fig. 1 and Table 1, major consumers of energy are end users, power plants, transportation, industry, buildings, and others, each of which showing potential for cost-effective energy efficiency improvements.

Agriculture and Food Agricultural activities make a strong contribution to anthropogenic climate change. Greenhouse gas emissions from this sector account for 22 % of global total emissions, which is similar to the contribution level of industry and greater than that of transportation. Livestock production (including transport of livestock and its feeding) accounts for nearly 80 % of the sector’s emissions (McMichael et al. 2007). The two strong greenhouse gases (GHG), methane and nitrous oxide (which are closely linked with livestock production), contribute much more to this sector’s warming effect than does carbon dioxide (McMichael et al. 2007). Emission factors of CO2 and CH4 for livestock are estimated at 36–3,960 and 0.01–120 kg per head and year, respectively (Office of Energy Efficiency, Natural Resources Canada 2002). Agricultural operations not only put strain on global climate by CH4 emissions from cattle but also by energy consumption, which is concentrated in the areas of irrigation, process heat applications, and refrigeration. Irrigation pumps, refrigerated warehouses, greenhouses, and postharvest processing offer various potentials for energy efficiency improvements. A nice example is provided by some Dutch greenhouses, which are heated by gas engines, the CO2 from which is fed into the greenhouses to fertilize the plants and to boost their growth (Lugt et al. 1996). In Oude Lansink and Bezlepkin (2003), different heating methods for greenhouses are compared. In Ramírez et al. (2006a), the energy efficiency of the Dutch food industry is reviewed, and in Ramírez et al. (2006b) that of the European dairy industry. Additional case studies of recent improvements in energy efficiency in the agricultural industry are discussed in Swanton et al. (1996). The energy use for the production of various agrichemicals, such as herbicides, growth regulators, and fungicides, ranges from 120 to 550 MJ/kg of active ingredient (Saunders et al. 2006), taking production, packaging, and transportation into account (Saunders et al. 2006). The application rate of these chemicals further determines the total energy consumption per kg of agricultural product. Food miles are a very simplistic concept relating to the distance food travels as a measure of its impact on the environment (Saunders et al. 2006). While a lower number of “food miles” will generally render a product more energy efficient, because transportation ways are shorter, a food commodity that is produced with

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high energy efficiency, e.g., by low use of fertilizers, and that has a long mileage to the consumer can still have a lower environmental impact that foodstuff manufactured close to the end customer in an otherwise inefficient way. This simple example shows that energy efficiency aspects are closely interwoven and often difficult to compare, not only in the agricultural industry. Globalization affects the food industry as much as it does high-tech goods. Ecuador is the world’s largest banana exporter. The carbon footprint of Ecuadorian export bananas was found to range from 0.45 to 1.04 kg CO2-equivalent/kg banana (Iriarte et al. 2014). In Wang (2008), energy efficiency in the food industry is treated in detail.

Transportation and Logistics Our world has become global, so that people and goods are being transported between countries and continents on a large scale. The IEA predicts significant improvements in energy efficiency in transportation; however, these will be more than offset by increased travel (IEA 2009) and further globalization. Fuel efficiency in transportation ranges from a few megajoules per kilometer and passenger for a bicycle to several 100 MJ for a helicopter. Approx. 1/3 of the energy consumption in transportation is used for freight movement (Sorrell et al. 2009), which accounts for 8 % of total anthropogenic CO2 emissions. Most of these emissions stem from trucks (heavy goods vehicles, HGV), which account for most freight activities in most countries, e.g., 68 % of all tonne kilometers in the UK (Sorrell et al. 2009). Ample road networks make cargo distribution by HGV convenient and efficient in terms of time and costs. Externalities are the costs or benefits that affect parties who did not choose to incur that cost or benefit (Buchanan and Stubblebine 1962). An example for such a negative externality is air pollution or climate change by transportation: The costs are born neither by car producers nor by motorists. For a discussion of freight and transportation externalities, see Ranaiefar and Amelia (2011). For details on transportation and climate change, see the subsections below and also chapter “▶ Fuel Efficiency in Transportation Systems” in this handbook.

Road Transportation and Internal Combustion Engines Although rail and ship transportations are more efficient and environmentally benign than road transportation, trucking is still heavily used for reasons of flexibility, costs, and timeliness, not only in weakly developed areas, to move goods and people. Most vehicles on the road today are powered by internal combustion engines (ICE). Engine and propulsion system selection for cars is based on various criteria such as driving performance, range, and safety. ICE burn gasoline and diesel, the latter being primarily for trucks. In some countries, cars and trucks with natural gas-, ethanol-, and hydrogen-propelled engines constitute a fleet fraction next to those

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with alternative systems such as electrical batteries or air buffer tanks. In Brazil, ethanol fuel has become popular. It is mostly produced from sugarcane, whereas the USA use corn as feedstock. For biodiesel, the Americas use soybean, whereas Europe mainly deploys rapeseed (1st generation biofuels). Hydrogen is chiefly obtained by water electrolysis. Internal combustion engines have become more efficient over the last decades. The largest losses in gasoline engines are encountered by throttling the engine (Ellinger et al. 2001). Taylor (2008) estimates that over the next decade, an efficiency improvement of another 6–15 % is feasible. Various optimizations such as direct fuel injection, variable valve timing, supercharging, downsizing, exhaust gas recirculation, onboard fuel reforming, and powertrain improvements, e.g., on the gearbox, are being tested and implemented (Ellinger et al. 2001). The reuse of losses also offers significant potentials, for instance, recuperative braking or the extraction of heat from exhaust gases, as it is a state of the art in power plants (economizers). Stationary engines, such as large gas engines for power backup or landfill gas use, can be operated in steady mode at optimum efficiency. Combustion engines in mobile machines have to perform well over a wide range of load, which yields poorer overall efficiency. A novel, promising combustion technology for engines is HCCI (homogeneous charge compression ignition) (Zhao 2007). HCCI is a hybrid between an autoignited diesel engine and a spark-ignited Otto engine in that it deploys auto-ignition of a homogeneous fuel-air mixture. Alternative ignition systems (Lackner 2009) such as laser ignition are also expected to improve fuel economy. For a discussion on internal combustion engines for future cars, see Lackner et al. (2005).

Passenger Cars It is estimated that by 2030, 60 % of all new cars sold will be hybrids, plug-in hybrids, and electric vehicles, as opposed to 1 % today (IEA 2009). Hybrid cars combine an electric engine and an internal combustion engine. Dual fuel concepts (natural gas and diesel, for instance) are also feasible. The CO2 intensity of the passenger car fleet in 2030 is estimated to be 90 g of CO2/km, compared to 205 g/km in 2007, as a worldwide average. In OECD countries, it should reach 80 g, in the EU 70 g, and in India and China 110 and 90 g, respectively, in 2030, the latter ones down from 225 and 235 g, respectively, in 2007 (IEA 2009). On the other hand, a large increase in the global number of cars is anticipated, particularly in developing nations such as China and India. Hybrids use regenerative breaking to recapture energy that would otherwise dissipate. The effect on fuel economy of such cars is particularly pronounced in stop-and-go city traffic. Fuel economy of private cars is governed by the following aspects: • Technology advances of the car, e.g., weight reduction or better engine • Driving habits (use of air-condition, cruising speed, payload in the car, etc.)

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Fig. 10 Energy losses in passenger cars (Reproduced with permission from Elsevier from Holmberg et al. (2012))

• Maintenance (no clogged air filters, correct tire pressure, etc.) • Weight (lightweight construction materials can save fuel over the entire lifetime) Figure 10 shows the breakdown of passenger car energy consumption (Holmberg et al. 2012). In passenger cars, one-third of the fuel energy is used to overcome friction in the engine, transmission, tires, and brakes. The direct frictional losses, without braking friction, are 28 % of the fuel energy. In total, only 21.5 % of the fuel energy is used to move the car. Potential solutions to reduce friction in passenger cars include the use of advanced coatings and surface texturing technology on engine and transmission components, new low-viscosity and low-shear lubricants and additives, and tire designs with reduced rolling friction (Holmberg et al. 2012). There is plenty of information available for consumers who want to pick an energy-efficient car, e.g., one website run by the US EPA (http://www.fueleconomy. gov/ 2015). In California, partial zero emission vehicles (PZEVs) were introduced to satisfy part of the state’s zero emission vehicle (ZEV) program (Collantes and Sperling 2008). In Johansson and Åhman (2002), options for carbon-neutral passenger transport are reviewed. Thomas (2009) compares fuel cell and battery electric vehicles. The primary energy efficiencies of alternative powertrains in vehicles are discussed in Åhman (2001)). In Ellinger et al. (2001), the energy efficiency of internal combustion engines and fuel cells for automotive use with different fuels is assessed. It is concluded there that fuel cells have an advantage during hot start conditions, but suffer from efficiency losses during cold starts (Ellinger et al. 2001).

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Although the energy efficiency of a fuel cell-powered car is not the best, the environmental performance of a vehicle burning hydrogen from solar generation in a low-noise, virtually emission-free fuel cell is outstanding. It is expected that the fraction of fuel cell cars will increase over the next decade, with an accompanying growth of the necessary infrastructure.

Ships Nifty percent of the world’s trade is carried by the international shipping industry, supported by 50,000 merchant ships (http://www.ics-shipping.org/publications/ 2015). Over the last four decades, total seaborne trade is estimated to have quadrupled, from just over 8,000 billion tonnes-miles in 1968 to over 32,000 billion tonnesmiles in 2008 (http://www.ics-shipping.org/publications/ 2015). In 2011, figures were 42.8 billion tonnes-miles or 8.7 billion tonnes according to UNCTAD (United Nations Conference on Trade and Development) and the ITF (International Transport Forum 2013). Seaborne shipping is one of the most energy-efficient means of transportation, especially for large, bulky goods. Here is a comparison of energy efficiency of different transportation modes, taken from a study by the Swedish Network for Transport and the Environment (Table 5) (http://www.ics-shipping.org/publications/ 2015). It has to be noted that the table above is slightly biased in favor of sea transportation, as the aircraft mentioned is an outdated one used on a short-haul flight. Ships can be driven by different technologies (Schneekluth and Bertram 1998) with diesel engines being most common. The resistance of the ship’s hull, the design or the propeller, and the tonnage are important factors for its energy efficiency as well. The impact of shipping on the atmosphere and on the climate is discussed in Eyring et al. (2010). The auxiliary powering of ships by kitelike devices is discussed in Burgin and Wilson (1985) and Kim and Park (2010). Spinning vertical rotors installed on a ship to convert wind power into thrust based on the Magnus effect, so-called Flettner rotors, are another option to increase energy efficiency. Microbubbles as a means of reducing skin friction on ships are studied in Kodama et al. (2000). Different propulsion systems for LNG carriers are discussed in Chang et al. (2008). LNG (liquefied natural gas) is expected to gain an increasing importance. Table 5 Energy consumption in different transportation modes (dwt is the deadweight tonnage (also known as deadweight, DW or dwt), a measure of how much weight a ship can safely carry. It is the sum of the weights of cargo, fuel, ballast water, crew, etc.) (Source: http://www.ics-shipping.org/ publications/ 2015) Mode Comment Energy consumption

Air B727-200 (1,200 km flight) 4.07 kWh/(ton*km)

Road Medium-sized truck 0.49 kWh/(ton*km)

Sea Cargo ship, 2,000–8,000 dwt 0.08 kWh/(ton*km)

Sea Cargo ship, >8,000 dwt 0.06 kWh/(ton*km)

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Rail Transportation Intuitively, rail transportation of people and cargo is amongst the most environmentally friendly modes of movement. Technological progress has increased energy efficiency in rail transportation, too. According to Kemp (1997), aerodynamic drag per seat at 150 km/h was cut by half over 30 years. Train speed determines energy efficiency. The energy consumption for a high-speed train from London to Edinburgh increases from 30 to almost 60 kWh/seat as the speed goes up from 225 to 350 km/h (Kemp 1994). The American railway corporation Amtrak reported an energy use of 2,935 BTU per passenger-mile (1.9 MJ/passenger-km) in 2005 (Amtrak 2015). A critical factor in energy efficiency of trains is the occupancy. If a train is only 25 % loaded, the fuel consumption per passenger and seat can be worse than with economic cars and modern aircraft as shown in Kemp (2004). For a discussion on the potential role of high-speed trains in future sustainable transportation, see Kamga and Yazici (2014). Air Transportation Aviation has helped shape our current business dealings and lifestyles significantly. Virtually any point on the globe has got into easy reach within 24 h. Air transportation is used for cargo and people. It has contributed approx. 3.5 % to global greenhouse gas emissions in 1990 with a projection of 15 % or more in the future (Penner et al. 1999). The impact of aviation on climate change is not only driven by CO2 emissions but also by H2O emissions at high altitude (Williams et al. 2002). Due to the long residence time of water vapor at aircraft cruising altitude, it can disproportionally contribute to global warming by reflecting and retaining infrared radiation (compare the effect of natural clouds). Biofuels for aviation (Marsh 2008) were already tested in a proof-of-concept study (BBC 2008), provoking mixed feelings amongst critics. Winglets (Marks 2009) and lightweight materials (Marsh 2007) are two commonly known concepts to increase fuel efficiency of aircraft, hence increasing energy efficiency. See also Figs. 4 and 5. The impact of service network topology on air transportation efficiency is discussed in Kotegawa et al. (2014). In a recent study on the impact of airline mergers and hub reorganization on aviation fuel consumption, it was found that a typical airline merger in the USA has a fuel saving potential of 25–28 % (Ryerson and Kim 2014). Renewable fuels in aviation are discussed in Winchester et al. (2013). Pipeline Transportation Pipelines (Ellenberger 2010), i.e., conduits of pipe, can be used to transport liquids, gases, and slurries. The Romans built aqueducts for water transportation some 2,000 years ago. An early industrial pipeline was installed in Austria in 1595 to transport brine from Hallstatt to Ebensee for salt production (Bedford and Pitcher 2005). Today, pipelines are commonly used to transport petroleum, natural gas, and other commodities over large distances. A comparison of natural gas transportation by

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LNG tankers and pipelines is made in Elvers (2007). LNG compression and regasification consume 7–13 % of the original amount of natural gas, as well as roughly 0.15 % per day of marine transport, which adds about another 1 % to overall energy losses. Pipeline transportation of natural gas results in energy losses of approx. 1 % per 1,000 km. Therefore, an intercontinental 8,000 km pipeline would involve energy losses of roughly 10 %, which is approx. half the amount of transportation by LNG tankers over the same distance (Elvers 2007). The transportation of liquids in pipelines versus onboard of trucks is compared in Pootakham and Kumar (2010) and (Ghafoori et al. (2007). The conveying of coal as slurry in pipelines is assessed in Kania (1984). In industrial plants, pneumatic conveying (dense phase or dilute phase conveying of a solid in air) and hydraulic conveying (solids in liquid carrier media) are used to transport materials between various processing sections. Variable speed drives (VSD) for pneumatic conveying blowers are a means of enhancing energy efficiency versus blowing off excess air at low conveying capacities for the transportation of solids in the gas phase. Kumar et al. (2007) review the transportation of biomass in pipelines. It is concluded that long distances and high throughput rates make such systems economic, as is generally the case with pipeline transportation.

Industry Industry accounts for a high fraction of the global energy consumption; see Table 1. The energy intensity varies strongly from 52.3 end-use BTUs per USD of value added in cement production to 0.4 end-use BTUs per USD in computer assembly (Granade et al. 2009). Ten end-use BTUs per USD can be set as limit for energyintensive industries as done in Granade et al. (2009). There is a huge potential for energy savings in industry, yet the biggest opportunities for optimization are not easily known to the people involved (Yang 2010). Approximately 2/3 of the energy saving potential can be found in specific process steps of energy-intensive industries, whereas 1/3 resides in various areas of nonenergy-intensive ones. Savings can be realized by more efficient processes or by more efficient equipment.

Crosscutting Technologies Equipment which is used in different sectors of industry, such as lighting, motors, boilers, and pumps, is subsumed as crosscutting technologies. For these, best practices (see, e.g., US Department of Energy 2010) and general recommendations can be formulated that are valid for several branches and sectors of industry. Generally, there exist untapped-into saving potentials in: • • • •

Waste heat recovery Steam systems Motor systems Pumps (Tutterow et al. 2002)

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• Lighting • Buildings • Utilities For quantifying energy efficiency potentials, there are various methods (Phylipsen et al. 1997). Here are some aspects of energy efficiency that are relevant for many industries: Process design: The largest contribution to energy efficiency is made during the design of a process. If a product, for instance, has to be heated up and cooled down several times, chances are high that the process is not energy efficient. Also, an implemented production process is difficult to change. Overcapacity: Design capacity should meet the needs for a process in terms of vessel size, engine power, etc. Overdesign always costs money – not only in the investment phase but most likely also later on, when energy consumption is higher than necessary. Overcapacities of process equipment should normally not exceed 10 % of the overall design capacity. Debottlenecking: If a plant can be deblottlenecked, i.e., the output can be increased by making some small modifications, one typically has a highly profitable project. Also from an energy efficiency perspective, debottleneckings frequently lower the specific energy consumption of a product, thus making it more energy efficient. Measuring, monitoring: In order to be able to track energy efficiency measures, it is necessary to measure accurately and regularly actual consumption values of electricity and other utilities such as compressed air or cooling water. Only by monitoring them actively will deviations be spotted. Automatic controls: Automatic process control is generally faster and more accurate than a manual one and also less prone to errors. Therefore, a production process can be carried out in the most energy-efficient way if it is automatically controlled (Szentennai and Lackner 2014). Automation will be more economic for large processing plants where the investment costs can be diluted over the volume. Compressed air: Leaks of air from pipes can easily lead to 20–50 % efficiency loss of a compressed air system. Preventive maintenance and the timely repair of leaks will help to minimize running costs. A pressure reduction of the entire system can often be considered, as instrument air (plant air) typically only needs to have ~6 bar pressure, which is less than the design pressure of many compressor systems. If the operating pressure is reduced by just 1 bar, energy savings of over 5 % can result. Maintenance: If industrial assets are not properly being taken care of, their energy consumption tends to increase. Advanced maintenance techniques such as riskbased maintenance, preventive maintenance, thermography, and others will help to keep energy efficiency up. Cutting costs on maintenance can bring short-term gains at the expense of increased risk and deferred costs. A typical yearly maintenance budget for industrial plants would be 2 % of the investment value, depending of course on the process.

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Cogeneration: Production sites that produce their own electricity should seriously consider combined heat and power (CHP). If there is no need for heat in the installation itself, there might be an opportunity to sell the heat, e.g., for district heating purposes. Cogeneration will use the heat which would otherwise be wasted, thereby increasing the energy efficiency. For details, see Raj et al. (2011) and Çakir et al. (2012). Motors and drives: It is estimated that 2/3 of all electricity consumption in industry is used to drive various motors (US Department of Energy 2010), so there is a huge optimization potential. The “motor challenge” is a recent program to improve motor efficiency (Energy Efficient Motor Driven 2010). Typical energy efficiencies of motors are 80–90 %, with advanced models reaching 97 % (Office of Energy Efficiency, Natural Resources Canada 2002). Variable speed drives: An engine’s energy consumption can be matched to the load by using a variable speed drive (VSD). VSDs can be realized with a frequency converter coupled to an engine. Up to 50 % of energy can be saved. Today, only an estimated 10 % of all engines in industry are equipped with VSD. A large number of motors are still controlled by throttling valves in pump systems or vanes in fan applications. By throttling, a part of the produced output immediately goes to waste. Speed control with intermediate transmission such as belt drives, gearboxes, and hydraulic couplings adds to the inefficiency of the system and requires the motor to run at full speed. Another drawback is that such systems typically require more maintenance. They can be noisy, too. Pumps: It is estimated that pumps consume 25 % of the electricity in US manufacturing facilities (Galitsky 2008). Industrial pumps have a lifetime of 20 years and longer. Pump efficiency is defined as the pump’s fluid power divided by the input shaft power and is influenced by hydraulic effects, mechanical losses, and internal leakages. Pump manufacturers have devised many ways to improve pump efficiencies. For example, the pump surface finish can be made smoother by polishing to reduce hydraulic losses. A “good” efficiency for a pump will vary depending on the type of the pump. A more useful efficiency term is the wire-to-water efficiency, which is the product of the pump and motor efficiency. An even better measure of efficiency for analysis purposes is the system efficiency, which is defined as the combined efficiency of the pump, motor, and distribution system. See also Tutterow et al. (2002) and “Life Cycle Assessment (LCA)” above. Blowers and fans: Fans move air as pumps move liquids. They can often be optimized for energy efficiency, e.g., by adding a VSD. For details, see, e.g., Gunner et al. (2014). Energy management system: An energy management system (EMS) is the energy equivalent of an environmental management system. Generally, industrial sites or units that consume more than 1,000 toe/day should have a dedicated energy manager, who will “pay himself/herself” by economizing on energy bills. A guideline for energy management is provided by Office of Energy Efficiency, Natural Resources Canada (2002). The standard ISO 50001 can serve as guidance.

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Several smaller units instead of large one: Instead of one large pump which is controlled with a bypass, several smaller pumps might be more energy efficient, matching power consumption to the process needs. The same consideration might work for air compressors, etc. Energy audit and energy survey: These tools were mentioned already earlier in this chapter in the context of the EU Directive 2012/27/EU of 25 October 2012 on energy efficiency. Energy audits and energy surveys can be administered by internal or external staff. Generally speaking, it is vital for the success of an energy efficiency program in a corporation to have the support of a senior, recognized executive and to make the effort lasting by introducing energy performance indicators, which can be linked to employee’s targets and performance management. Load shifting (using off-peak electricity) (Favre and Peuportier 2014): If energyintensive production processes can be concentrated in off-peak hours, the energy bill will be lower. This will also have positive effects on the environment, as peak electricity demand often needs to be produced in a not-so-efficient way. For details, see, e.g., demand side management in smart grid operation in López et al. (2015). Load shedding (Kanimozhi et al. 2014): By reducing peak electricity consumption, energy costs can also be reduced. Insulation: Process insulation can be optimized for energy efficiency. A waterlogged insulation transfers heat 15–20 times faster than a dry one, and one filled with ice even 50 times faster (Office of Energy Efficiency, Natural Resources Canada 2002)! Using waste heat: Heat losses are a major sink for energy. Process heat in general can be upgraded using absorption heat pumps (AHP) (Wei et al. 2014). Heat losses in flue gases are a particularly large term: If flue gases exist and the chimney too hot, significant amounts of heat are wasted (up to 1 % of fuel savings for 25  C colder flue gas temperature (Galitsky 2008)); see also cogeneration. As for heat exchangers, cleaning and optimization can bring additional energy efficiency gains (Wang et al. 2009). An overview on energy efficiency improvement potentials in industry is given in Rajan (2002) and Bannister (2010), the latter focusing on mechanical systems. Industrial energy efficiency in Asia, where a large part of global energy-intensive industry has settled, is treated in United Nations (2006).

Steam and Boilers Steam engines are gone; however, still 37 % of the fossil fuel burned in the US industry is used to produce steam (Einstein et al. 2001). Steam is the working fluid in steam turbines for electricity production. It is used in various industries to transfer and to store heat, as it is a capacious reservoir for thermal energy because of the high heat of vaporization of water. The chemical industry uses significant amounts of steam as process heat, one reason being that steam is generated as a by-product in some processes in integrated

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chemical production sites. Steam in general can be produced efficiently in cogeneration plants. In contrast to district heating networks to heat private homes, cogeneration plants in industry can be operated at full capacity all year round. Steam is produced in boilers. Energy efficiency measures for boilers include: • • • • • • •

Improved process control Reduced excess air Improved insulation Maintenance Recovery of heat from flue gas Recovery of steam from blowdown Optimization of fuel mix For steam distribution systems, the following measures are effective:

• • • • •

Improved insulation Improved steam traps Steam trap monitoring Leak repairs Condensate return

In Einstein et al. (2001), information on steam systems in industry and their energy use and energy efficiency improvement potentials are outlined. Detailed information on boilers is given in Heselton (2004).

Energy-Intensive Industries There are certain “heavy industries” that consume a large fraction of total energy output. In China, for instance, the top 1,000 energy-intensive enterprises consumed 30 % of China’s total energy and 50 % of the total industrial energy in 2007 (NDRC 2007). Energy intensity is a specific quantity, expressed as kWh/kg of product or as kWh/monetary unit (value added, often in USD). Above an arbitrary threshold of ten end-use BTUs per USD, one can speak about energy-intensive industries (Granade et al. 2009). This classification is valid for the production of: Cement Steel Aluminum Ores Pulp and paper

(Calcination process, clinker production) (Coke consumption) (Primary metal production by electrolysis) (Mining operations) (Mechanical pulping)

These industries have a strong effect on global energy consumption, because they are not only energy intensive as such but because they produce high amounts of materials per year. The global steel production, for instance, is in excess of one million tonnes (Lackner 2010). The IEA predicts big improvements in energy efficiency in industry, which are expected to be more than offset by higher output

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Fig. 11 China’s industrial energy consumption and intensity from 1996 to 2010 (Reproduced with permission from Ke et al. (2012))

of steel and cement (IEA 2009), especially in the developing world, to which countries like Brazil, Russia, India, China (BRIC), Mexico, and South Korea belong. Figure 11 shows the trend in China’s industrial energy consumption and intensity from 1996 to 2010 (Ke et al. 2012). The industrial energy consumption of China increased significantly from 1996 to 2010, especially after 2002. By 2010, China’s industrial energy intensity had decreased 46 % below the 1996 level (Ke et al. 2012). Energy production in China is largely based on coal combustion, with efficiencies being approx. 10 % lower than in Europe or the USA (Nuo and Gaoshang 2008). The CO2 emissions from coal combustion are naturally higher than those from other fuels with a lower C/H ratio. Several technology options to reduce energy consumption and CO2 emissions in energy-intensive industries are reported in Yudken and Bassi (2009); see also below.

Iron and Steel In the iron and steel industry, as the name implies, iron production and steel production are the main processes (Berns et al. 2008). Iron can be produced along different routes. The classic path is the production of pig iron from ore and coke in the blast furnace, which is then further processed into steel in the basic oxygen furnace (BOF) or the open hearth furnace (OHF), the first one being more energy efficient. Smelt reduction and direct reduction (DR) are two other, advanced routes to iron. The electric arc furnace (EAF) is used to produce secondary steel from scrap.

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Table 6 Potential technologies to make energy-intensive production processes more efficient (Source: Yudken and Bassi (2009) from IEA, DOE, AISI, Aluminum Association, Korean Energy Institute) Technology option Pulverized coal and plastic waste injection New reactor designs Paired straight hearth furnace Molten oxide electrolysis Hydrogen flash melting Geological sequestration and steelmaking

Description Pulverized coal is already used by more than 50 % of all US BOFs Uses coal and ore fines (COREX™, FINEX™) Substitutes coal for coke in blast furnaces, lower costs, uses 2/3 energy Produces iron and oxygen, no CO2 Uses hydrogen in shaft furnaces, no CO2

Time frame ST-MT MT MT-LT LT MT MT-LT

ST short term (2010–2015), MT medium term (2015–2030), LT long term (2030–2050)

In China, the energy consumption per tonne of steel has declined from 1.43 to 0.52 toe between 1980 and 2005 (Wei et al. 2007). Integrated steel plants have a specific primary energy consumption ranging from 19 to 40 GJ/t of steel (Gale and Freund 2014), with minimills that use scrap steel being more efficient. Technology options for reducing energy use and CO2 emissions in the iron and steel industry are tabulated in Table 6, reproduced from Yudken and Bassi (2009).

Aluminum Worldwide primary aluminum production is projected to increase from 23 to 38 million tonnes by 2020 (Gale and Freund 2014). The primary aluminum (Moors 2006) production, starting from bauxite via electrolysis (Hall-Héroult process), is a very energy-intensive process, contributing 1 % of total anthropogenic greenhouse gas emissions in 1995 with about 364 million tonnes/year CO2-equivalent (Gale and Freund 2014). Secondary aluminum production (Li et al. 2006) consumes approx. 5 % of the energy needed for primary production. Existing and potential future processes for bauxite processing are reviewed in Smith (2009). Technology options for reducing energy use and CO2 emissions in primary aluminum are summarized in Table 7, reproduced from Yudken and Bassi (2009). Other Primary Metals Generally, one can distinguish between pyrometallurgical and hydrometallurgical processes. The ore content of a deposit influences energy efficiency as the chosen process does. The energy demand for comminution is described in Tromans (2008). Energy efficiency of a lead smelter is discussed in Morris et al. (1983), and energy efficiency of copper and magnesium production in Alvarado et al. (2002) and Cherubini et al. (2008), respectively. Processes for the production of steel, aluminum, copper, lead, and zinc are reviewed from an energy perspective in Stepanov

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Table 7 Potential technologies to make energy-intensive production processes more efficient (Source: Yudken and Bassi (2009) from IEA, DOE, AISI, Aluminum Association, Korean Energy Institute) Technology option Wetted, drained cathode technology Alternative cell concepts Carbothermic and kaolinite reduction process on commercial scale

Description Combines inert anode, drained cathodes Alternatives to the HallHéroult process

Time frame MT-LT LT LT

ST short term (2010–2015), MT medium term (2015–2030), LT long term (2030–2050)

and Stepanov (1998). Sintering processes and their energy efficiencies are discussed in Musa et al. (2009) for one system, and scale-up in metallurgy in general in Lackner (2010).

Pulp and Paper The pulp and paper (P&P) industry is a very energy-intensive one. Pulp is being produced from wood by the kraft process, with electricity as additional input and output, plus steam as an output. An efficient kraft pulp mill can be a net exporter of heat and electricity (Jönsson and Algehed 2010). Industry practice shows that in the past, most energy-efficient measures were limited to low-investment, high-return projects, with typically 5 % energy savings with a 1-year payback time (Costa et al. 2007), with a lot of potential still untapped into. In current paper mills, steam savings of up to 30 % are deemed feasible (Kilponen et al. 2001; Costa et al. 2009; Axelsson et al. 2008; Nordman and Berntsson 2009; Lutz 2008). Energy efficiency savings can be obtained from the use of different fuels, which are typically wood, bunker oil, and black liquor (Costa et al. 2007), the latter being a by-product of the transformation of wood chips into pulp. Typical energy efficiencies in the industry for bark combustion are 67 % (based on the higher heating value) and 80 % for bunker oil combustion, respectively (Costa et al. 2007). In Jönsson and Algehed (2010), the utilization options for excess steam and heat at kraft pulp mills are studied. Traditional ways are increased electricity production and district heating, whereas increased sales of biomass as bark and/or extracted lignin and carbon capture and storage (CCS) are new pathways. There is a trend toward additional products, complementing the traditional pulp and paper output, by biofuels, pellets, lignin, carbon fibers, and other specialty chemicals (Jönsson and Algehed 2010) from pulp and paper plants. In Costa et al. (2007), the economics of trigeneration in a kraft pulp mill are discussed. In trigeneration, pulp production, waste heat upgrading, and power production are simultaneously carried out (compare polygeneration). Absorption heat pumps (AHP) can be used to cool waste heat streams and to extract energy from them.

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Table 8 Potential technologies to make energy-intensive production processes more efficient (Source: Yudken and Bassi (2009) from IEA, DOE, AISI, Aluminum Association, Korean Energy Institute) Technology option Black liquor gasification Efficient drying technology

Description In demonstration, R&D; commercially available 2030; 15–23 % gain R&D now; commercial demo, 2015–2030; commercial, 2030 onward

Time frame MT-LT MT-LT

ST short term (2010–2015), MT medium term (2015–2030), LT long term (2030–2050)

Technology options for reducing energy use and CO2 emissions in the paper and paperboard industry, reprinted from Yudken and Bassi (2009), are summarized here in Table 8. Recycling is another option to increase energy efficiency of paper products. For details on energy efficiency options in the pulp and paper industry, see Worrell et al. (2001).

Cement The cement industry, already 15 years ago, exceeded 1.5 billion tonnes of annual output, making it a huge consumer of energy. For cement production, first clinker has to be made, which is then blended with approx. 5–70 % additives such as gypsum and fly ash to yield cement. This first step is the most energy-intensive one. Limestone (CaCO3) is burnt with silicon oxides, aluminum oxides, and iron oxides. There is a wet process and a dry process, the latter one being more energy efficient. As cement plants (Deolalkar 2009) consume significant amounts of energy, approx. 4 GJ/t of cement produced (Khurana et al. 2002), energy efficiency programs have been extensively applied to various plants (da Graça Carvalho and Nogueira 1997; Utlu et al. 2006; Mandal and Madheswaran 2010; Worrell et al. 2000a; Doheim et al. 1987). For each t of cement, approx. 0.5 t of CO2 are generated (Office of Energy Efficiency, Natural Resources Canada 2002). In Worrell et al. (2000a), potentials for energy efficiency improvements in the US cement industry are discussed, and in Liu et al. (1995) those for China. CO2 and energy intensity reductions in cement production can be achieved by: • • • • •

Modification of the product composition (less clinker) Use of alternative cements (e.g., mineral polymers) Improving the energy efficiency of the process and process equipment Introduction of a different process (e.g., change from wet to dry process) Replacement of high-carbon fossil fuels by low-carbon fossil fuels

A trend in the cement industry is the use of waste fuels such as tires. Recommendations on energy efficiency and cost saving opportunities for the cement industry can be found in Worrell and Galitsky (2008).

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Glass Production Glass is a ubiquitous material that comes as sheet glass (produced in the float glass process), hollow glass (for glass containers), automotive glass, optical glass, and other glasses such as glass fiber and glass wool. Its production is an energy-intensive process. According to Sheredeka et al. (2001), 74 % of production costs are typically raw materials, fuels, and electricity. Recycling of glass offers a good way of increasing energy efficiency. One recycled bottle can save approx. 0.1 kWh (Glass Manufacturing Industry Council (GMIC) 2015). In http://www.osti.gov/glass/ bestpractices.html (2015), best practices for energy efficiency improvements in the glass industry are provided. A detailed treatise of energy efficiency potentials in the American glass industry can be found in Worrell et al. (2008). Petroleum Refining In a petroleum refinery (oil refinery) (Fahim et al. 2009), crude oil is processed into various petroleum products such as naphtha, gasoline, diesel, and liquefied petroleum gas (LPG). Refineries are complex, chemical plants that are usually highly integrated. Crackers, for instance, can produce lightweight hydrocarbons as basic feedstock for the petrochemical industry (see also below). Energy efficiency in a petroleum refinery can be tackled from various angles. Like in industry in general, there is usually optimization potential in cogeneration, steam systems, heat transfer systems, and motors; see also Coletti and Macchietto (2009a, b), Bevilacqua and Braglia (2002), Wenkai et al. (2003), Fath and Hashem (1988), Najjar and Habeebullah (1991), and McKay and Holland (1981) for details reported in the literature. Worrell et al. (1994a) estimated the energy saving potential for refineries to be around 15 %. The determination of the energy efficiency of a certain process is a somewhat tricky task, as it depends on boundary limits to be drawn. Alireza Tehrani Nejad (2007) attempts to allocate CO2 emissions in petroleum refineries to various petroleum products. One aspect of the petrochemical and chemical industry in general that has to be noted here with respect to energy efficiency is that the energy contained in the feedstock is partly converted to heat and power but also remains in the final products to some extent, providing potentials for recycling at the end of the various materials’ lifetimes (feedstock recycling or thermal recycling). Recommendations on energy efficiency and cost saving opportunities in refineries can be found in Worrell and Galitsky (2005). Petrochemicals Petrochemicals are products derived from petroleum (Meyers 2004) other than fuels for combustion. The petrochemical industry consumes approx. 8 % of total oil production for the manufacture of various products (The International Energy Association in Collaboration with CEFIC 2007) ranging from plastics, rubbers, and solvents to various fine chemicals. Two important upstream processes are cracking (fluid catalytic cracking, steam cracking) for the production of olefins such as ethylene and propylene and reforming (catalytic reforming) for the production of aromatics.

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Table 9 Potential technologies to make energy-intensive production processes more efficient (Source: Yudken and Bassi (2009) from IEA, DOE, AISI, Aluminum Association, Korean Energy Institute) Technology option High-temperature furnaces Gas turbine integration Advanced distillation columns Combined refrigeration plants Biomass-based system options

Description Able to withstand more than 1,100  C Higher-temperature CHP for cracking furnace

Feedstock substitution

Time frame MT-LT MT-LT MT-LT MT-LT LT

ST short term (2010–2015), MT medium term (2015–2030), LT long term (2030–2050)

Worldwide, more than 107 t of propylene, 6.5*106 t of ethylene, and 7*106 t of aromatics are produced per year. From these primary petrochemicals, to which also synthesis gas can be counted, a wide range of chemical products is made. Energy efficiencies of a steam cracker are reported in Tuomaala et al. (2010) and Ren et al. (2008). Naphtha crackers are estimated to consume 31.5 GJ/t of energy (Worrell et al. 2000b). The gross energy requirement (GER) for major petrochemical products such as ethylene, propylene, butadiene, and benzene is reviewed in Worrell et al. (1994a). Technology options for reducing energy use and CO2 emissions for petrochemicals are shown here in Table 9, from Yudken and Bassi (2009). Below, details on some petrochemical products with respect to energy efficiency are reviewed.

Polymers The polymer industry has ramped up plastic production between 1950 and 2007 from 1.5 to 260 million tonnes (Johansson 2015) worldwide, which corresponds to an annual growth rate of more than 9 %, making plastics ubiquitous and versatile construction materials. Today, plastic production has reached 300 million tonnes per year (http://www.essentialchemicalindustry.org/processes/recycling-in-the-chemi cal-industry.html 2015). Polyolefins are the most common plastics, with polyethylene (PE) and polypropylene (PP) accounting for the largest fraction, followed by polyvinylchloride (PVC), polystyrene (PS) and expanded polystyrene (EPS), polyethylene terephthalate (PET), polyurethane (PUR), and others, e.g., engineering plastics such as polycarbonate (PC). Polymers can be produced with different technologies, ranging from radical reactions (high-temperature and high-pressure processes such as for high-density polyethylene (HDPE)) to catalytic processes (at more moderate conditions), which show varying energy efficiencies. The gross energy requirements for the production of low-density polyethylene (LDPE), PP, PS, and PVC are 69.8, 61.6, 81.5, and 55.7 GJ/t, respectively (Worrell et al. 1994a). Plastic production uses 8 % of the world’s oil production, 4 % as feedstock and 4 % during manufacture (University of York 2010). Cogeneration and heat recovery in polymerization processes are discussed in Budin et al. (2006).

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In Europe, the recycling rate of plastics has reached 51.3 % (21.3 % recycling and 30.0 % energy recovery, i.e., combustion) (Johansson 2015). Worrell et al. (1994a) investigated potential energy savings in the production of plastics. That study found that the technical potential for energy efficiency savings varies from 12 % for PE to 25 % for PVC. Further information on energy use in plastic production can be found in Patel and Mutha (2004). Alternative feedstocks, biopolymers, and feedstock recycling (Scheirs 2006) are emerging trends in the industry with impact on energy efficiency.

Chemical Industry The chemical industry uses crude oil, natural gas, and coal, apart from electricity, both as raw materials and as fuels to produce more than 50,000 different products. More than half of the energy used by the chemical industry is processed as feedstock, which means that it is transformed into various products such as chemicals or polymers. Most energy is consumed by the production of a few small, intermediate compounds. In the chemical industry, energy costs account for 10–15 % of total manufacturing costs (Bieling 2007). For some processes such as electrolysis, energy costs can exceed 50 % of production costs. The DOE estimates potential energy savings within the chemical industry to be approximately 20 %. Strategies to improve energy efficiency in the chemical industry are process improvements, cogeneration, integration, and the introduction of energy management systems (EMS). Integration means that rather than producing a single chemical, a production location should strive to use its feedstock to make the desired final product, while utilizing by-products as well. If several production steps, such as crude oil distillation, cracking, and polymerization, can be done in one location, costly and wasteful transportation and storage steps can be avoided (compare the German concept of an integrated chemical complex, the “Verbund.” At the largest chemical Verbund site, BASFs, Ludwigshafen, synergies amount to 500 million € per year, 150 million € out of which are attributed to energy savings (The International Energy Association in Collaboration with CEFIC 2007)). Process design is also an important consideration for energy efficiency, as different unit operations (McCabe et al. 2004) have varying energy demands. In Worrell et al. (2000b), energy use and energy intensity of the US chemical industry are analyzed. A general review on sustainability and energy efficiency in the chemical industry is provided by de Swaan Arons (2010). Below, some details on various products of the chemical and process industries with respect to energy efficiency are compiled. Actual energy consumption values for the production of chemicals are significantly higher than the theoretical demand stipulated by thermodynamics. A “clean-sheet redesign,” not considering cost-effectiveness, would offer a potential for energy savings in chemical production of up to 95 % (Granade et al. 2009; Hinderink et al. 1999). Catalysts, as they lower the activation energy, can generally increase energy efficiency, particularly enzymatic catalysts for several particular reactions.

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Process intensification and polygeneration are two emerging technologies that could reduce energy demand in the chemical industry. By process intensification (Etchells 2005), more compact and efficient plants can be designed. Polygeneration using natural resources is detailed in Serra et al. (2009). An overview on energy efficiency in the chemical industry is provided in Worrell and Blok (1994) and Worrell et al. (1994a, b, 2000c). Green chemistry is discussed in Poliakoff et al. (2002) and Anastas and Warner (2000). Ammonia Ammonia is one of the inorganic chemicals with the highest yearly production volume. Its global consumption is in excess of 107 t. NH3 is the precursor to most industrially produced nitrogen-containing compounds. More than 80 % of ammonia is processed to fertilizers. Ammonia production consumes more than 1 % of all man-made power (Max Appl 2006). CO2 emissions in ammonia production are estimated to be 1.58 t for each t of the product (Office of Energy Efficiency, Natural Resources Canada 2002). Energy consumption is quoted as 39.3 GJ/t for feedstock (natural gas) plus 140 kWh/t electricity, totaling to 40.9 GJ/t (based on higher heating value, corresponding to 37.1 GJ/t based on lower heating value) (Worrell et al. 2000b). Without considering the natural gas, the primary energy consumption for ammonia production is 16.7 GJ/t (Worrell et al. 2000b). For energy efficiency studies and improvement potentials in ammonia production, see Panjeshahi et al. (2008) and Rafiqul et al. (2005). The use of ammonia as a fuel is described in Zamfirescu and Dincer (2009). The specific energy consumption for the production of urea is estimated at 2.8 GJ/t (1994) (Worrell et al. 2000b). Fertilizers Nitrogen-bearing fertilizer production is a very energy-intensive industry. Ammonia is the most important intermediate chemical compound here (see also above). Table 10 shows the energy use and emission intensity for the production of various fertilizer components, reprinted from Wells (2001): An early review on energy efficiency in fertilizer production is provided by Mudahar and Hignett (1985). Energy efficiency in the fertilizer industry is reviewed in Ladha et al. (2005), Abdul Quader (2003), Kumar (2002), Mudahar and Hignett (1985), and Fadare et al. (2010). Nitrogen fertilizer production has an additional impact on climate change, mainly via N2O emissions (Stuart et al. 2014). Table 10 Energy requirements to manufacture fertilizer components plus associated CO2 emissions (Source: Wells 2001)

Component N P K S Lime

Energy use [MJ/kg] 65 15 10 5 0.6

Emissions [kg CO2/MJ] 0.05 0.06 0.06 0.06 0.72

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Methanol Methanol can be produced by steam reforming from methane (Rosen and Scott 1988). It can also be obtained from coal (Li et al. 2010) and various biomass products (Hamelinck and Faaij 2002) such as sugarcane. Methanol has seen increased interest for its use in: • Direct methanol fuel cells (Jiang et al. 2004) • Fuel for combustion engines (Agarwal 2007) • Feedstock for chemical industry (Olah et al. 2009) In 1994, the specific energy consumption for the production of methanol was 38.4 GJ/t (based on higher heating value) (Worrell et al. 2000b). Best practice in 2013 was 9.0–10.0 GJ/t. Figure 12 shows today’s energy losses in the chemical industry for the major chemicals, amongst them methanol. Catalysis bears a great potential for further energy reduction (DECHEMA 2013).

Industrial Gases A wide variety of gases is industrially produced and sold in compressed or liquid state. Apart from air, oxygen and nitrogen are amongst the most commonly used industrial gases (Häring et al. 2007), others being argon (welding), carbon dioxide, and methane. Oxygen and nitrogen have traditionally been produced through cryogenic air separation where air is cooled and pressurized until it becomes a liquid with

Fig. 12 Cumulated theoretical total energy loss for major chemical processes based on 2010 production volumes (Source: DECHEMA 2013). TPA terephthalic acid, PP polypropylene, EO ethylene oxide, VCM vinyl chloride monomer, PX paraxylene, BTX benzene, toluene, xylene, pygas pyrolysis gasoline, PO propylene oxide

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the various gases being extracted through fractionated distillation. The associated energy consumption is estimated to be 1.8–2.0 GJ/t of oxygen or nitrogen (Worrell et al. 2000b). Other energy-efficient technologies such as pressure swing adsorption (PSA) (Sharma 2009) and membrane separation (Koros and Fleming 1993) are increasingly used. For a comparison of cryogeny versus membranes for oxygen-enriched air (OEA) production, see Belaissaoui et al. (2014). Methane can be produced through anaerobic fermentation (biogas) and methanogenesis (through bacteria). Also, hydrogen can be produced by bacteria (Xia et al. 2014); see also below. An article on energy efficiency gains in gas production (thermal gasification) is given by Kumar et al. (2010). Chlorine Chlorine is produced through electrolysis of a salt solution (brine), which is an energy-intensive process requiring between 3,065 and 3,960 kWh/t (Worrell et al. 2000b). The coproducts caustic soda (sodium hydroxide, NaOH) and hydrogen gas (H2) are obtained, with the major markets for chlorine being PVC (polyvinylchloride) manufacturing, inorganic chemicals, propylene oxide, water treatment, and organic chemicals. The chlorine industry is reviewed in Johnston and Stringer (2001). Technology options for reducing energy use and CO2 emissions in chlor-alkali manufacturing are summarized from Yudken and Bassi (2009) in Table 11. Hydrogen Hydrogen is regarded as an interesting option, as transportation fuel, and as storage medium for electricity, being produced from renewable resources. The “hydrogen economy” (Ball and Wietschel 2009) is often seen as a straightforward solution to many issues around pollution and global warming. Despite all the potential that lies in the technical exploitation of hydrogen, it needs to be borne in mind that the hydrogen – as clean as it is as such – has to be produced. Hydrogen from nuclear power is treated in Hori (2008) and Yildiz and Kazimi (2006). It is the overall energy efficiency (system efficiency) that will determine whether hydrogen will be used on a large scale as energy carrier. For details, see Page and Krumdieck (2009). Table 11 Potential technologies to make energy-intensive production processes more efficient (Source: Yudken and Bassi (2009) from IEA, DOE, AISI, Aluminum Association, Korean Energy Institute) Technology option Convert mercury process and diaphragm process plants to membrane technology

Description Combined electrolytic cell with a fuel cell, using hydrogen by-product

ST short term (2010–2015), MT medium term (2015–2030), LT long term (2030–2050)

Time frame MT-LT

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A comparison of thermochemical, electrolytic, photoelectrolytic, and photochemical solar-to-hydrogen production technologies is made in Wang et al. (2012).

Pharmaceutical Industry The US pharmaceutical industry has energy expenses of approx. one billion USD per year (Galitsky 2008), which, being only a small fraction of total production costs, is still significant, given the fact that energy savings will translate into direct and predictable earnings. In the pharmaceutical industry, there are three overall stages: • R&D • Production of bulk pharmaceutical substances • Formulation of the final products Table 12 shows the distribution of energy use (Galitsky 2008) in this sector. Twenty-five percent of the total energy is used for plug loads and processes, 10 % for lighting, and 65 % for HVAC (heating, ventilation, and air-conditioning). The biggest potential can hence be found in R&D and bulk manufacturing.

Public Sector and Community Infrastructure The public sector is another area where energy efficiency potential exists. Awareness of energy efficiency and conservation is a major topic. In a typical office, nearly 40 % of the electricity consumption occurs after closing hours (Danish Ministry of Transport und Energy 2005). In China, the energy consumption in the building sector is 25 % of total energy consumption. The energy use in urban buildings in megacities like Beijing and Shanghai are about 90 % of the whole energy consumption in buildings (Jiang 2011). It was found that amongst these urban buildings, the energy use in public buildings is higher than in other building sectors (Jiang 2011). China’s Ministry of Construction has issued six energy efficiency design standards to the building sector since 1995, where the latest one is the design standard for energy efficiency in public buildings, aiming at a 50 % reduction of energy consumption in new and refurbished public buildings. Beijing and

Table 12 Pharmaceutical industry and energy use (Source: Galitsky 2008) Area R&D Offices Production of bulk pharmaceutical substances Formulation, packaging, and filling Warehouse Miscellaneous Total

Distribution of energy use (%) 30 10 35 15 5 5 100

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Shanghai governments have also issued their local energy saving standards for public buildings with 65 % and 50 % of energy saving, respectively (Jiang 2011). Government institutions can apply energy-efficient procurement and create awareness for energy savings. Public buildings (see also next section) offer energy efficiency increase potential, as does, for instance, the lighting infrastructure of public roads. For enhancing energy efficiency in public buildings, local energy audit programs were found to be successful (Annunziata et al. 2014). Energy efficiency in public lighting is discussed in Radulovic et al. (2011). Desalination plants are important in several parts of the world. Their energy efficiencies for different technologies are assessed in Mesa et al. (1997), Tay et al. (1996), Al-Kharabsheh (2006), Gomri (2009), and Charcosset (2009). Another important infrastructure is data centers. Their energy efficiency is discussed, e.g., in Todorovic and Kim (2014).

Buildings Buildings have a strong and long-lasting impact on global energy consumption, because they are constructed for typically 50–100 years. In 2005, 39 % of the total energy consumption in the USA stemmed from commercial and residential buildings (US Green Building Council 2015). They accounted for as much as 70 % of total electricity consumption (US Green Building Council 2015). There is hence a huge potential for what is known as green buildings. The residential sector in the USA is expected to account for 29 % of the US energy consumption in 2020 (Granade et al. 2009), driven by population growth, larger homes, and more electric and electronic gadgets in private households. The specific energy use for heating of buildings, a major parameter for their energy efficiency, is given in kWh/(m2*year). Key determinants for energy efficiency of buildings are: • Location and surroundings • Insulation • Heating technology Sealing of ducts, basement insulation, and improved heating equipment are seen as major efficiency opportunities in private homes in the USA (Granade et al. 2009). Heat pumps are particularly energy efficient. There are three types of heat pumps: air to air, water source, and ground source. Ground source heat pumps typically use four times less electrical energy than direct electrical heaters. Deviations in energy efficiency from the design requirements to actual performance may come from: • Errors in the design • Errors in the construction

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• Incorrect operation • Lack of maintenance • Changed use of the building Various tools, such as an energy survey or an energy audit, can help uncover efficiency potentials. On average, heating and cooling account for almost half of a typical utility bill. Drafty rooms can be improved by checking windows and doors. The HVAC (heating, ventilation, air-conditioning) system often offers potential for improvement and so does the lighting. Compact fluorescent lights (CFL) are more efficient than electric bulbs. Passive buildings (Miller et al. 2009) and zero net energy (ZNE) buildings (Hernandez and Kenny 2010; Elkinton et al. 2009) are more energy efficient than traditional ones. For ZNE buildings, embodied energy (Venkatarama Reddy and Jagadish 2003) can be considered. This is the quantity of energy required to manufacture and transport the materials utilized for their construction. According to Venkatarama Reddy and Jagadish (2003), the total embodied energy of load-bearing masonry buildings can be reduced by 50 % when energyefficient/alternative building materials are used. Landscaping around private homes can also bring measurable energy savings. Carefully positioned trees can save up to 25 % of a household’s energy consumption for heating and cooling. They can, apart from giving a nice appearance, provide shade and shelter from wind. Payback times for such planting measures can be as low as several years (DOE 1995). Microgeneration for individual houses is another interesting technology option for the energy savvy. A small combined heat and power (CHP) system to produce electricity and heat for a community or a single household is known as microgeneration (Entchev et al. 2004). The most promising technologies are Stirling engines and fuel cells in a size range of approx. 1–10 kWe. Total efficiencies can be typically 80–88 % (Entchev et al. 2004). It is estimated that in US buildings, 1/3 of the total energy consumption can be saved at a cost of 2.7 $c/kWh (Brown 2008); see also for natural gas savings there. Figure 13 shows the electricity saving potential for the residential area, and Fig. 14 the same scenario for the commercial sector. It can be seen in Fig. 13 that in the residential area, a huge potential exists for TV sets, lighting, and space cooling, with freezers already being rather optimized. Figure 14 takes a look at the commercial sector. In the commercial sector, space cooling and lighting offer large potential, with the most cost-effective opportunities residing in space heating and ventilation. Energy efficiency in the residential area is covered in International Energy Agency (2008). A guide on energy efficiency for home owners can be found in Krigger and Dorsi (2008). Smart metering has been suggested for enhancing residential energy efficiency (Anda and Temmen 2014).

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Cost of Conserved Energy (2007$/kWh)

2007 Residential Retail Electricity Price 0.10

1. Color television 2. Lighting 3. Other uses 4. Water heating 5. Clothes washer 6. Space heating 7. Furnace fan 8. Personal computer 9. Refrigeration 10. Space cooling 11. Dishwasher 12. Freezer

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Fig. 13 Residential electricity saving potential in the year 2030 (Reprinted with permission from Brown (2008))

Cost of Conserved Energy (2007$/kWh)

0.10 2007 Commercial Retail Electricity Price

0.09 1. Space heating 2. Ventilation 3. Water heating 4. Refrigeration 5. Other uses 6. Space cooling 7. Office Equip. – non-PC 8. Office Equip. – PC 9. Lighting 10. Cooking

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Fig. 14 Commercial electricity saving potential in the year 2030 (Reprinted with permission from Brown (2008))

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Appliances Appliances are a collection of electrically powered devices, which can be found in nearly every household. They account for approx. 20 % of a typical household’s energy consumption, with refrigerators, washing machines, and dryers at the top of the consumption list. A “cheap” device can become very costly over its entire lifetime of up to 10 or 20 years (see TCO concept above). In 1978, California took a leading national role in the USA by establishing the first building and appliance standards in the country. Nearly 85 % of all dishwashers in California are Energy Star™ compliant (see later), and 50 % of refrigerators and washing machines conform to these standards, too. What is even more impressive, however, is that this increase in market share occurred within no more than 7 years; see Fig. 15, reprinted with permission from Next 10’s California Green Innovation Index (2010). Typical renewal cycles of appliances in industrialized countries, here the USA, are shown in Fig. 16, reprinted from Okura et al. (2006). Modern appliances consume significantly less energy than older ones.

Lighting Lighting has played a large part in the public discussion on energy efficiency. As traditional incandescent bulbs, which have an efficiency on the order of 1 % to produce light, are being phased out in many countries, mild panic-buying could be observed in 2009 (Jamieson 2009). Some consumers oppose the compact fluorescent lights (CFL), which typically cost four times as much as traditional bulbs. The fact that their energy consumption is one-fifth and that payback times are typically short has not convinced all consumers (yet). There are reservations against the hue of the 100% 80% 60% 40% 20% 0% 1998

1999 Dishwashers

2000

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2002

Refrigerators

2003

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Clothes Washers

Fig. 15 Market share of Energy Star™ appliances in California (Reprinted with permission from Next 10’s California Green Innovation Index (2010))

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Fig. 16 Appliance renewal cycles (Reprinted with permission from Okura et al. (2006)) Table 13 Number luminous flux emitted by common light sources (Reproduced with permission from Gan et al. (2013)). Lumen is the SI unit of luminous flux, a measure of the total quantity of visible light emitted by a source Lamp Incandescent lamp Compact fluorescent lamp Fluorescent lamp LED

Lamp wattage 75 W 15 W 36 W 18 W

Lumens 950 810 2,400 1,600

CFL’s light. CFL that work in dimmers tend to cost more than standard CFL. In Techato et al. (2009), a life cycle analysis of CFL is made. An alternative to CFL is light-emitting diodes (LED) (Principi and Fioretti 2014; Gan et al. 2013). For a comparison of typical light sources, see Table 13.

Consumers Up to 2/3 of household energy use is for space heating, water heating, and refrigeration (Granade et al. 2009) with lighting playing a lesser role. Another significant share is held by the “plug load”. “Plug load” is a collective term for electrical devices and small appliances. These are virtually hundreds of small devices in private homes, consuming electricity. The biggest shares are held by TV sets (22 %), DVD players (5 %), PCs (5 %), and microwave ovens (3 %) (Granade et al. 2009). Standby power consumption is a huge energy waster. In Japan, the annual per household standby electricity consumption could be reduced from 437 to 308 kWh from 2002 to 2005 (Granade et al. 2009). Figure 17 shows typical energy expenditures for Swedish households, reproduced from Nässén et al. (2008). It is assumed that with a tripling of energy prices, energy use of private households would decrease by 30 % (Nässén et al. 2008). Energy consciousness of consumers has increased over the last years, partly induced by various initiatives such as Energy Star™; see also below.

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Fig. 17 Annual average of expenditures of households on energy for heating and electricity (Reprinted with permission from Elsevier from Nässén et al. (2008))

Tips and Tricks for Consumers There are plenty of tips and tricks in various organizations’ and authorities’ brochures and Internet pages for consumers on how to lower their utility bills. Most of them are commonsense, but it is worthwhile to take a look at them to capture some fast savings. Here are a few examples of often unused potential in private homes: • • • •

The temperature of the refrigerator is too low. The refrigerator is positioned in a confined space. The washing machine is operated half empty with too warm water temperature. Open food is stored in refrigerators (liquids need to be covered, and food should be wrapped to avoid moisture release). • Untight windows. • Time is not considered (peak electricity is most costly). Ample advice on how to save energy (energy conservation and energy efficiency) in the household can be found in the internet, e.g., from governmental sites such as (http://energy.gov/energysaver/articles/energy-saver-guide-tips-saving-money-andenergy-home 2015) or organizations like the OECD (http://www.oecd.org/ greengrowth/40317373.pdf 2015).

Initiatives for Energy Efficiency Energy efficiency improvements do not come “naturally”, at least not at the desired speed. In order to overcome the known barriers toward energy efficiency, which were outlined above in this chapter, government action can help. Numerous programs and initiatives to educate people about and to promote energy efficiency have

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been started by governments, NGOs (nongovernmental organizations), NPOs (nonprofit organizations), for-profit entities, and visionary individuals such as business owners and public celebrities. One such initiative is Energy Star™. The Energy Star ® label is used to identify energy-efficient appliances. It was initiated by the DOE (US Department of Energy) and the EPA (US Environmental Protection Agency). Products with the Energy Star™ label usually exceed minimum efficiency standards by a substantial amount. More information on Energy Star ® can be found at (http://www.energystar.gov/ 2015) and (http://www.eu-energystar.org/ 2015). The impact of agreements on energy efficiency is reviewed in Grossman and Krueger (1991).

Other Aspects There are countless areas for hidden or for indirect energy efficiency improvements, some of which are being touched upon here. Advanced packaging, for instance, can save substantial amounts of materials to achieve the same level of good protection. Lightweight packaging will make transportation over long distances more energy efficient. One example is the replacement of bulky glass bottles by composite containers of (recycled) cardboard and plastics. In information technology (IT), there is often an untapped potential for energy savings and efficiency improvements. Anyone who has witnessed the large air-conditioning systems for server rooms will immediately see the potential offered by what has become known as green computing. More details can be found in Minas and Ellison (2009) and Namboodiri (2009). The service sector can also contribute to more energy efficiency. Electronic banking, video telephony, and teleconferencing (Liang et al. 2007), telecommuting (Nelson et al. 2007; Rhee 2008), and fleet management (D’Agosto and Ribeiro 2004) are just a few examples where energy for traveling can be economized. In general, shifting employment and economic activity from manufacturing to the service sector saves energy and cuts greenhouse gas emissions, because the service sector is much lower in energy intensity. Energy efficiency potentials in hospitals are discussed in Sloan et al. (2009). Energy efficiency under extreme conditions is reviewed in Tin et al. (2010).

Energy Conservation Being a broader term than energy efficiency, energy conservation is about using less energy, with a lower energy service being delivered. Sometimes, it is used synonymously with energy efficiency. Energy saving is without doubt the quickest, most effective, and most cost-efficient way for reducing greenhouse gas emissions, as well as improving air quality, especially in developing countries and in densely populated areas. An example of energy conservation on a private level is, for instance, driving

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less with one’s car. An organization can study its office lighting setup to remove costly over-illumination, for example. For more information on energy conservation, see Thumann and Dunning (2008), Patrick et al. (2007), Chirarattananon and Taweekun (2003), Jin et al. (2009), Markis and Paravantis (2007), Lin (2007), and Al-Mofleh et al. (2009).

Further Study and Reading In this section, a few terms that are related to energy efficiency were compiled as a starting point for further exploration by the interested reader. Dematerialization: By this expression, one can understand the decline of weight and “embedded energy” (cf. embodied energy) of materials in industrial end products over time or, more broadly speaking, the absolute or relative reduction in the quantity of materials required to serve economic functions (Wernick et al. 1996; Tapio et al. 2007). On the one hand, one can observe a decline in weight of certain good such as PCs; on the other hand, people tend to use more materials as their comfort level increases (e.g., larger homes, larger cars). Trends of dematerialization are reviewed in Wernick et al. (1996). A similar term is ephemeralization, which was coined by R. Buckminster Fuller. It is the ability of technological advancement to do “more and more with less and less until eventually you can do everything with nothing” (Buckminster Fuller 1973). Industrial Ecology: Being defined as a “systems-based, multidisciplinary discourse that seeks to understand emergent behaviour of complex integrated human/ natural systems” (Allenby 2006), industrial ecology strives at sustainability and eco-efficiency. More information on the topic can be found in Frosch and Gallopoulos (1989). Eco-efficiency: According to the World Business Council for Sustainable Development (WBCSD), it is expressed as: • • • • • • •

Reduction in the material intensity of goods or services Reduction in the energy intensity of goods or services Reduced dispersion of toxic materials Improved recyclability Maximum use of renewable resources Greater durability of products Increased service intensity of goods and services

More information can be found in World Business Council for Sustainable Development (WBCSD) (2000). Water efficiency: Water efficiency is closely linked to water conservation. It can be defined as the accomplishment of a function, task, process, or result with the minimal amount of water feasible. Effluent reuse is one important means of achieving water efficiency (White and Howe 1998). It is estimated that each m3 of water utilized in the industrial and service sectors generates at least 200 times more wealth

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than it does in the agricultural sector (Beaumont 2000). This suggests that waterintensive production will be shifted from arid regions to those with more water (compare the shift of CO2-intensive production to certain areas). Here, the concept of virtual water (Allan 2005; Chapagain 2006) steps into place. Virtual water, also called embedded water, embodied water, or hidden water, refers to the water needed to manufacture a good or service. Yearly individual water consumption is on the order of 1 m3 for drinking, 100 m3 for domestic use, and 1,000 m3 embedded in food. This shows that the concept of virtual water is closely linked to water efficiency and ultimately to energy efficiency. Other burning topics related to energy are the affordability of energy and access to energy, which are both not secured for a high number of people.

Conclusions This chapter has taken a look at energy efficiency in industry, transportation, the private sector, and other areas, exploring a topic of high relevance for climate change mitigation. Energy use efficiency is the cheapest and easiest source of energy, with a huge unused potential. It is estimated that up to 1/3 of the worldwide energy demand in 2050 can be saved by energy efficiency measures. In its “International Energy Outlook 2014,” the EIA (US Energy Information Administration) mentions a growing energy efficiency in the transportation sector, which, in OECD Europe, already induced a decline in consumption of liquid fuels (EIA (US Energy Information Administration) 2014). Energy efficiency has started to proliferate, and there is still a lot of potential. In this chapter, aspects of energy efficiency from various sectors were presented, spanning historic data, current levels, and future trends. An emphasis is placed on providing brief information and references on how energy efficiency improvements can be realized.

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White SB, Howe C (1998) Water efficiency and reuse: a least cost planning approach. In: Proceedings of the 6th NSW recycled water seminar, Sydney Williams V, Noland RB, Toumi R (2002) Reducing the climate change impacts of aviation by restricting cruise altitudes. Transp Res Part D: Transp Environ 7(6):451–464 Winchester N, McConnachie D, Wollersheim C, Waitz IA (2013) Economic and emissions impacts of renewable fuel goals for aviation in the US. Transp Res A Policy Pract 58:116–128 World Business Council for Sustainable Development (WBCSD) (2000) Eco-efficiency: creating more value with less impact. World Business Council for Sustainable Development, Geneva. ISBN 2-94-024017-5 Worrell E, Blok K (1994) Energy savings in the nitrogen fertilizer industry in the Netherlands. Energy 19(2):195–209 Worrell E, Galitsky C (2005) Energy efficiency improvement and cost saving opportunities for petroleum refineries. Lawrence Berkeley National Laboratory, LBNL paper LBNL-56183. Retrieved from http://www.escholarship.org/uc/item/96m8d8gm. Accessed 1 Jan 2015 Worrell E, Galitsky C (2008) Energy efficiency improvement and cost saving opportunities for cement making, an ENERGY STAR ® guide for energy and plant managers. Ernest Orlando Lawrence Berkeley National Laboratory, LBNL-54036-Revision Worrell E, De Beer JG, Faaij APC, Blok K (1994a) Potential energy savings in the production route for plastics. Energy Convers Manag 35(12):1073–1085 Worrell E, Cuelenaere FA, Blok K, Turkenburg WC (1994b) Energy consumption of industrial processes in the European union. Energy 11(19):1113–1129 Worrell E, Martin N, Price L (2000a) Potentials for energy efficiency improvement in the US cement industry. Energy 25(12):1189–1214 Worrell E, Phylipsen D, Einstein D, Martin N (2000b) Energy use and energy intensity of the U.S. chemical industry. Lawrence Berkeley National Laboratory, LBNL paper LBNL-44314. Retrieved from http://www.escholarship.org/uc/item/2925w8g6. Accessed 1 Jan 2015 Worrell E, Phylipsen D, Einstein D, Martin N (2000c) Energy use and energy intensity of the U.S. chemical industry, LBNL-44314. Lawrence Berkeley National Laboratory, Berkeley Worrell E, Martin N, Anglani N, Einstein D, Khrushch M, Price L (2001) Opportunities to improve energy efficiency in the U.S. pulp and paper industry. Lawrence Berkeley National Laboratory. LBNL paper LBNL-48354. Retrieved from http://www.escholarship.org/uc/item/7sv597fv. Accessed 1 Jan 2015 Worrell E, Galitsky C, Masanet E, Graus W (2008) Energy efficiency improvement and cost saving opportunities for the glass industry: an energy star guide for energy and plant managers. Lawrence Berkeley National Laboratory, Publication no LBNL-57335-Revision Xia A, Cheng J, Ding L, Lin R, Song W, Zhou J, Cen K (2014) Enhancement of energy production efficiency from mixed biomass of Chlorella pyrenoidosa and cassava starch through combined hydrogen fermentation and methanogenesis. Appl Energy 120:23–30 Yang M (2010) Energy efficiency improving opportunities in a large Chinese shoe-making enterprise. Energy Policy 38:452–462 Yildiz B, Kazimi MS (2006) Efficiency of hydrogen production systems using alternative nuclear energy technologies. Int J Hydrog Energy 31(1):77–92 Yudken JS, Bassi AM (2009) Climate policy and energy-intensive manufacturing impacts and options. Millenium Institute, 2111 Wilson Boulevard, Suite 700, Arlington 22201. http://www. globalurban.org/Climate_Policy_and_Energy-Intensive_Manufacturing.pdf. Accessed 1 Jan 2015 Zamfirescu C, Dincer I (2009) Ammonia as a green fuel and hydrogen source for vehicular applications. Fuel Process Technol 90(5):729–737 Zhao H (2007) HCCI and CAI engines for the automotive industry. Woodhead Publishing, Cambridge. ISBN 978-1845691288

Fuel Efficiency in Transportation Systems Maximilian Lackner, John M. Seiner, and Wei-Yin Chen

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Carbon Emissions by Light Duty Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Carbon Generated by Combustion with Air . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alternative Fuels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alternative Power Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Air Transportation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cargo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Means of Energy Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Comparison of Different Transportation Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Transportation of people and of goods plays an important role in modern life. It is a major source of anthropogenic CO2. This chapter, after introducing some fundamentals of natural climate fluctuations as described by Milankovitch cycles,

John M. Seiner: deceased M. Lackner (*) Institute of Advanced Engineering Technologies, University of Applied Sciences FH Technikum Wien, Vienna, Austria e-mail: [email protected] J.M. Seiner W.-Y. Chen Department of Chemical Engineering, The University of Mississippi, Oxford, MS, USA e-mail: [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_18

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describes the causes and consequences of man-made climate change and the motivation for increased fuel efficiency in transportation systems. To this end, contemporary and future ground-based and air-based transportation technologies are discussed. It is shown that concepts that were already given up, such as turbine-driven cars, might be worthwhile for further studies. Alternative fuels such as hydrogen, ethanol and biofuels, and alternative power sources, e.g., compressed air engines and fuel cells, are presented from various perspectives. The chapter also addresses the contribution of CO2 emissions of the supply chain and over the entire life cycle for different transportation technologies.

Introduction The purpose of this chapter is to introduce current concepts being examined to increase fuel efficiency in transportation systems in order to reduce their impact on unfavorable climate change. This is a daunting task that will take the cooperation and sacrifice of most of the entire human population to avoid a premature catastrophic event. Now, other chapters of this handbook reveal the salient scientific reasons for climate change, and the reader is encouraged to consult these chapters. However, here it is only necessary to establish that global warming or cooling has continually occurred by natural causes since Earth’s formation. This can be deduced from examining the so-called Milankovitch cycles (Kukla and Gavin 2004). Transportation of people (passengers) and goods (freight, cargo) can be done on the land, the sea, and the air. Approx. 50 % of all transportation emissions are from passenger transport (Lipscy and Schipper 2013). One can distinguish between individual transportation (e.g., cars, bikes) and mass transportation (e.g., trains, planes, buses). Land-based transportation is achieved on highways and on railroads. Travel intensity and choice of transportation mode depend on personal preference, income, and country (Lipscy and Schipper 2013). Trip distance, e.g., to work for commuters, is also an important driver (Muratori et al. 2013). Goods can also be moved in pipelines. With the globalization of the economy and shifts in lifestyle habits, transportation has become more and more important over the last 100 years, both in the industrial and the developing world. Figure 1 below, in an exemplary fashion, shows the increase in energy consumption for transportation in China. According to Zhang et al. (2011a), highways have become the dominant mode of transportation in China. The energy consumption in this mode increased from 1980 to 2006 from 36.4 % to 61.5 %. Other economies have seen similar developments. As Fig. 1 shows, other transportation systems have seen more and more usage as well. Transportation systems are mainly driven by fossil fuels, predominantly those made from crude oil. The reason is that liquid fuels such as gasoline and diesel have high energy content that are safe and convenient to handle at low costs. Energy efficiency of transportation systems can be defined as the amount of energy needed for a certain task, e.g., the transportation of one passenger or one unit of cargo over a certain distance. Transportation and energy is reviewed in

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Highways

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Fig. 1 Chinese transportation sectors and their energy consumption from 1980 to 2009 (Reproduced with permission from Zhang et al. 2011b)

Greene (2004). Energy efficiency is the most economic way for climate change mitigation (Kamal 1997). Therefore, efforts need to be taken to improve energy efficiency of transportation systems. Since the year 2000, the world production of gasoline (petrol) has matched consumption of this product. This has led to sporadic shortfalls of gasoline at the pumps along with elevated costs. Beyond the uncertainty of future fuel costs, the predictions for effects of global warming on the planet are very severe, and it is important that mankind addresses the issue of how transportation systems contribute to this problem. Today there are over one billion vehicles in the world, and within 20 years, the number will double (Sperling et al. 2010), largely a consequence of China's and India's explosive growth. Figure 2 takes a look at the projected number of cars in China. An impressive increase is expected over the next years (Hao et al. 2011). Figures 1 and 2 depict the situation in China, which was chosen as a showcase example here, as China is currently one of the world’s major emitters of anthropogenic CO2. At the present time, as shown in this chapter, there are only partial solutions to reduce the impact of transportation systems on global warming. Energy conservation by avoiding travel is one option. Technical improvements to transportation systems are another approach. Readers will note that the production of CO2, a by-product from the combustion of carbonaceous fuels such as gasoline with air, has been linked to a global increase in temperature. With an increase in the Earth’s temperature comes melting of the ice caps and a rise of sea level on coastal cities. Of most concern is an accompanying change in composition of the Earth’s fragile atmosphere. Millions of years ago the Earth had a very different atmosphere than it does today, where ice caps were melted and instead had lush forests. The percentage of O2 was over 30 %, a level that would support large mammals, as it did, but not the present human population. Therefore, it is imperative that economical methods be found to reduce the emission of CO2 if mankind is to have a sustainable future. Tim Flannery (2006) (http://www.

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Fig. 2 Projection of China’s vehicle population through 2050 (Reproduced with permission from Hao et al. 2011)

theweathermakers.org/) pointed out in his book that to stay below the threshold for melting of the ice sheets in Greenland and West Antarctica, it would be needed to reduce CO2 emissions by 80 % from today’s levels. This corresponds to no more than 30 lb of CO2 per person per day. Further, Flannery predicts that if progress in reaching the above goal is not enough, only 20 % of the present world population will reach the year 2050. Professor Tim Flannery is an Australian mammalogist, paleontologist, environmentalist, and global warming activist. In this chapter, the case for the reduction of CO2 emissions from transportation systems is made. Solutions to efficient reductions are an evolutionary process where incremental change may represent mankind’s only solution. With this viewpoint prior automotive designs that were introduced years ago and that failed to gain acceptance but may deserve another evaluation will be discussed. Presentday automotive engines utilize fuel injection systems instead of carburetors and represent the main reason for increased fuel mileage. Consequently, this chapter will also examine various engine cycles. Other measures such as lightweight construction materials, car pooling, and traffic management can also reduce fuel consumption. There is also a need to consider alternate fuels not only for emissions, but also reduction of the dependence on oil. Thus, the use of biofuels and hydrogen as substitutes for oil will be discussed. This is such a broad effort that this chapter will only be able to introduce a few concepts for automotive applications. Concepts for other landborne plus air- and seaborne transportation will be touched upon. The authors will also briefly discuss fuel cells, hybrid vehicles, and electric vehicles. Aircraft with respect to fuel efficiency will shortly be addressed. There is no question that aircraft play an important role in contemporary lifestyle, but they require significant energy to perform their mission. Thus it will be necessary to introduce radical designs that would substantially reduce the fuel burn rate.

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The Issue Since Earth’s formation, the atmosphere’s composition and temperature has changed dramatically due to the Earth’s cooling. However, there is another factor that affects the temperature of the atmosphere that is related to gravitational attraction between the planets and the sun. This gravitational attraction produces an eccentricity of the Earth’s orbit, obliquity of the Earth’s axis, and precession of the Earth’s axis of rotation. These effects have various periods as was first noted by Milankovitch who observed the following periods of the Earth’s axis: Wobble cycles of 19,000 and 23,000 years, tilt cycle of 41,000 years, and cycles of 100,000 and 400,000 years to the Earth orbit around the sun (Kukla and Gavin 2004). The Earth’s orbit transitions periodically between a circular and an elliptical orbit. When on an elliptical orbit, the Earth’s distance to the Sun has periods where it is the greatest, and the Earth’s atmosphere is cold (i.e., ice age). Currently, the Earth is in a more circular orbit, and the Earth’s temperature is warmer. These Milankovitch cycles are of course natural events that mankind cannot interfere with. During previous periods the ice caps were melted, and in the USA, alligators extended as far north as Denver. Data gathered from the Antarctica ice shelf allow researchers to infer the air temperature of the Earth at that location going back 400,000 years from analysis of cores drilled into the ice. Further analysis of these cores also permits one to estimate the percentage of CO2 in the atmosphere during this period of time. One can also deduce that during nearly circular orbits, the Earth’s temperature is the warmest, and during elliptical orbits, the Earth’s temperature is the coldest. The temperature spikes around 320,000, 210,000 and 130,000 years before today’s time and now have elevated contents of CO2 in the atmosphere. The warming periods that occurred beyond present day were controlled by natural events. However, during the present cycle that includes the Industrial Revolution, there appears to be a large increase in the percentage of CO2 that is significantly higher than recorded for previous cycles: the CO2 concentration in the atmosphere is elevated by 100 ppm due to human action. During the warm periods where the Earth’s orbit is nearly circular, the peak concentration of CO2 has been in the order of 275 ppm CO2. Today (January 2015) it has spiked to just under 400 ppm (The Keeling Curve et al. 2015), about 40 % higher than in preindustrial times and higher than in any other period in at least 800,000 years. The level of atmospheric CO2 is rising at a rate of approximately 2 ppm/year. This increase can be attributed to the presence of humans on Earth and their rapid consumption of energy, i.e., by the combustion of fossil fuels. A fair question to ask is what are the major contributors to CO2 production and how the CO2 concentration is related to Earth’s average temperature. From Fig. 3, one can see that there are three main contributors to the production and emission of CO2 in the atmosphere from burning fossil fuels, cement production, and land use change. The figure, reproduced from the 5th IPCC Assessment Report (2013), also shows the CO2 sinks. These represent the areas where technology developments to reduce CO2 are needed. The question then is how this increase in concentration of CO2 modifies the average temperature of the planet.

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Fig. 3 Leading contributors to production of CO2 and sinks (Reproduced from IPCC 2013)

Note that CO2 is not the only anthropogenic greenhouse gas, but also the most important one. Most of the natural greenhouse effect is caused by water vapor. Other important greenhouse gases are CH4, N2O, and SF6. CH4 emissions are also produced by the transportation sector, e.g., as losses from natural gas (and biogas) production and distribution and as unburnt hydrocarbon emission from the combustion process.

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It is very surprising how small an increase in CO2 concentration contributes to the average temperature around the globe. Now, the atmosphere has reached a level of said ~400 ppm. This means that the world has seen a nearly 2
C increase in temperature over that of preindustrial times. Even with this small increase in average temperature, many today can recall changes that have occurred and are noteworthy (for more information on narrative research in climate change, see, e.g., (Paschen and Ison 2014). In the early 1900s, people would drive their cars across Lake Ontario to Toronto, Canada, on the frozen ice sheet. This lake has not frozen over for more than 50 years. In Southern Virginia, James River used to freeze over as late as the 1950s, but no longer. Predictions by Flannery are that if an atmospheric CO2 concentration between 900 and 1,000 ppm is reached, in the future only one in five people would survive. Now, aside from observations that have occurred with an increase in global temperature, one can observe that the ice sheets have already begun to melt. Figure 4 shows the extent of the Arctic sea ice averaged over the period 1979 to 2007 for the months May to September. Following Fig. 5, one can see that the ice shelf does not restore itself until September. In a typical year the ice sheet would begin to grow again in August, but now in August it is still melting. With melted ice sheets, the Earth’s thermal energy balance is changed since more heat from the Sun is absorbed by the Earth rather than being reflected back into space. Thus, the cycle is intensified. Figure 5 below shows the thickness of the ice sheet north of Greenland in the 1950s and the prediction by NOAA (National Oceanic and Atmospheric Administration) for the year 2050, which shows the ice sheet is predicted to be reduced to half its previous size. Therefore, there is a strong motivation to increase the fuel efficiency of transportation systems for people and freight to mitigate anthropogenic climate change. Several aspects will be discussed below.

Carbon Emissions by Light Duty Vehicles It can be seen that since the beginning of the Industrial Revolution, the planet’s atmosphere has increased in temperature by almost 2
C. Not a large increase, but big enough to start significant melting of the ice caps. One can see that the temperature increase can be linked to a large increase in CO2 in the atmosphere. Combustion of solid (coal), liquid (gasoline, diesel), or gaseous (natural gas) fuels, to a significant fraction for transportation purposes, is the major contributor to the production of anthropogenic CO2. Natural gas has a higher H/C ratio than diesel or gasoline. Therefore, it is more climatically benign when being burnt in engines (note that the greenhouse warming potential [GWP] of CH4 is ~20 times that of CO2, so CH4 emissions are to be avoided). A natural question to ask at this point is what percentage of CO2 production is due to transportation and which countries are the major contributors. DeCicco et al. provide a graphic illustration of each sector’s contribution in Fig. 6. The estimates shown in this figure only include the use of fossil fuel. As can be seen,

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Fig. 4 Annual cycle of the Arctic sea ice extent for 2012 (red), 2007 (orange), 2011 (green), and 2008 (blue). Dashed lines show decadal means for the 2000s (black dashes), 1990s (gray dashes), and 1980s (light-gray dashes) (Source: IARC/JAXA Sea Ice Monitor, http://www.ijis.iarc.uaf.edu/ en/home/seaice_extent.htm) (Walsh 2014)

over 40 % of the CO2 emissions are from the production of home electricity and heat. Light-duty vehicles only account for 10 % of the production, and almost half of that is produced in the USA with a significant nearly a quarter from Europe. One observes that only a little over 2 % occurs in China and India. In the next 20 years, China and India are expected to grow and consume an amount equal to the USA (compare also Figs. 1 and 2). A substantial growth in CO2 production by light-duty vehicles would require additional refineries throughout the world, or extreme shortages at the pump would

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Sea Ice Thickness (10-year average) 1950’s

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Fig. 5 Melting of the polar ice cap (Reprinted with permission from the National Snow and Ice Data Center 2015)

Other sectors 9% Residential 8%

Electricity and heat production 41%

OECD Pacific Former Soviet Union 9% and Eastern Europe 6% China 2% Other Asia 2% India 1% Middle East 1% Latin America 5% Africa 2% United States 45%

OECD Europe 21%

Industry 18%

Canada Light duty and Mexico 7% vehicles 10%

Other transportation 14%

Fig. 6 Estimates for CO2 production by sector and light-duty vehicles. Left: Global carbon emissions by sector (6,814 *106 t). Right: Light-duty vehicle carbon emissions by region (680*106 t). (Reprinted with permission from DeCicco et al. 2015)

occur. Energy conservation will play a more realistic role in the future to avoid the problem of fuel shortage, but this cannot be expected to take effect until existing vehicles are replaced with ones using new technology. DeCicco also addressed this issue, and in Fig. 7a, one can see that old SUVs dominate the carbon burden share

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a Small cars SUVs Pickups Midsize cars On-road stock New fleet

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Fig. 7 Carbon emissions by new versus old vehicles and electric producers. (a) CO2 pollution as % of new & old vehicles. (b) Carbon emissions: auto & electric producers DeCicco et al., Global Warming on the Road (DeCicco et al. 2015)

and that both new and old midsize cars contribute equally. Carbon emissions by cars dominate those associated with electric producers, see Fig. 7b. These statistics indicate that there is a need to adopt a policy to retire existing vehicles as soon as possible and, in particular, SUVs. DeCicco et al. point out that there are three factors that govern the production of carbon dioxide in the transportation sector. The first is related to travel demand, the second to automotive efficiency, and the third to carbon content per gallon of fuel. Aside from reducing the distance travelled per year by car or light-duty truck, it is of interest to know how alternate means for ground transportation compare to decide which mode to emphasize. Table 1 shows a compilation of results by the US

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Table 1 Efficiency of various transportation systems 1 gal (~3.7854 l) of gasoline contains approximately 114,000 BTU (120 MJ) of energy. MPGe = miles per gallon gasoline equivalent. This measure of the average distance travelled per unit of energy consumed compares the energy consumption of alternative fuel vehicles. 1 MPGe  0.0182 km/kW  h  0.005 km/MJ Transport mode Vanpool Motorcycles

Average passengers per vehicle 6.1 1.2

Rail (Amtrak)

20.5

Rail (transit light and heavy) Rail (commuter)

22.5 31.3

Air

96.2

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1.57

Personal trucks

1.72

Buses (transit)

8.8

Efficiency per passenger 1,322 2.7 l/100 km BTU/mi (87 MPGe) 1,855 3.8 l/100 km BTU/mi (62 MPGe) 2,650 5.4 l/100 km BTU/mi (43 MPGe) 2,784 5.7 l/100 km BTU/mi (41 MPGe) 2,996 6.1 l/100 km BTU/mi (38 MPGe) 3,261 6.7 l/100 km BTU/mi (35 MPGe) 3,512 7.2 l/100 km BTU/mi (33 MPGe) 3,944 8.1 l/100 km BTU/mi (29 MPGe) 4,235 8.7 l/100 km BTU/mi (27 MPGe)

Department of Energy (DOE) for the efficiency of various transportation systems in terms of energy expended per passenger with an estimate of an equivalent number of liters per 100 km. The efficiency in Table 1 is estimated in terms of BTU/mile and also in miles per gallon. Table 1, from the US Department of Energy in 2008, clearly indicates the value of carpooling with a van that would carry six passengers. On a per passenger basis, the vanpool achieves 87 MPGeUS, an efficiency that would be hard to match by an automobile with a single passenger. Only motorcycles nearly match the vanpool. Personnel trucks are listed as one of the most inefficient modes of transportation with cars, only slightly better. Transit buses are the worst form primarily due to the constant stopping and starting needed to pick-up and let off passengers.

Carbon Generated by Combustion with Air Each barrel contains 42 gal (159 l) of crude oil and consists of various petroleum products as shown in Fig. 8. As one can observe, only about half a barrel of crude can be refined into gasoline (after fractionated distillation, several processes in a refinery such as cracking can shift the product mix).

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Fig. 8 Products obtained from refining a crude barrel of oil (Reproduced with permission from Gibson Consulting 2015). API American Petroleum Institute

what’s in a barrel of oil

other 0.3 gal. Kerosene 0.2 gal. lubricants 0.5 gal. feedstocks* 1.2 gal. asphalt/raod oil 1.3 gal. petroleum coke 1.8 gal. still gas 1.9 gal. liquefied gases 1.9 gal. residual fuel oil 2.3 gal. jet fuel 4.1 gallons distillate fuel oil 9.2 gallons

Source: API. Totals more than 44 gals. because of “processing gain”

gasoline 19.5 gallons

The amount of CO2 emitted per gallon is governed by the Code of Federal Regulations (40CFR600.113) (Title 40 2015). The carbon content of gasoline per gallon is 2,421 g, whereas the carbon content of diesel fuel per gallon is 2,778 g. Recall the words of Tim Flannery who said that to prevent the ice sheets from melting, every human had to be on a diet of 30 lb or less of carbon a day. So each person could only use about a gallon and a half of gasoline each day. The ability to use only a gallon and a half each day strongly suggests an elusive goal. While one may not be able to meet this goal, earnest conservation steps can ease the way into the inevitable. One of the first conservation steps one can take is to consider engine thermodynamic cycles to see if there is any advantage. Toward this purpose, the bare essentials associated with the spark and compression ignition engines are discussed. The four-stroke engine cycle was first patented by Eugenio Barsanti and Felice Matteucci in 1854. An illustration of the four-stroke cycle, reproduced from Obert (1973), is shown in Fig. 9. There, one sees the position of the cylinder head, intake valve, exhaust valve, and spark ignition for one entire cycle. Figure 10a, b show that the thermodynamic model for either SI (spark ignition) or CI (compression ignition) during intake and exhaust is considered to be an isentropic process (=constant entropy). During cycles of heat in or out, the thermodynamic model is far from isentropic. Note that for compression ignition engines, during combustion, the process takes place at constant pressure. For the ideal combustion, the efficiencies associated with the stoichiometric combustion of these fuels with air are illustrated in Fig. 10. For gasoline, this is given by 1=

C8 H18 þ 12 2 O2 þ 47N2 ! 8CO2 þ 9H2 O þ 47N2

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THE FOUR STROKE CYCLE

INTAKE

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IGNITION

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Fig. 9 Graphic illustration of four-stroke compression ignition engine (Reproduced from Obert 1973)

a

b 3

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i se

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isen tropic

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ropic

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Fig. 10 Idealized four stroke for SI and CI combustion models. (a) Otto cycle Pv Diagram. (b) Diesel cycle Pv Diagram(Reproduced from Obert 1973). P, pressure; v, volume; W, work; Q, heat; SI, spark ignition; and CI, compression ignition

where following Fig. 10a one can note QArev ¼ cv ðT3  T2 Þ QRrev ¼ cv ðT1  T4 Þ

ηt ¼

QA þ QR T1 1 ¼1 ¼ 1  γ1 QA T2 rv

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where rv is the engine compression ratio. As an example, consider the following: engine compression ratio, rv = 8; ambient temperature, Ta = 540
R (300 K); ambient pressure, Pa = 14.7 psia (101.3 kPa = 1.014 bar); and then one has that ηt ¼ 1 

1 rvγ1

¼1

1 ¼ 0:565 ¼ 56:5% 80:4

Factoring in transmission and drive train, the overall gasoline-powered automobile efficiency is approx. 17 % (Obert 1973). Quite remarkable, about 83 % of the available energy is wasted on the gasoline-powered internal combustion engine. Even the thermal efficiency of the four-stroke ideal diesel engine cycle appears more attractive. Consider the Pv diagram shown in Fig. 10b, which shows air coming into the system at constant pressure and air being discharged from the system at constant pressure. Based on this cycle one can derive that the reversible heat added and discharged is given by  γ   QArev ¼ cv ðT3  T2 Þ , and since TT32 ¼ TT41 , the thermal efficiency is given by QRrev ¼ cv ðT1  T4 Þ ηt ¼

   γ   QA þ QR 1 T4  T1 1 r 1 ¼1 ¼ 1  γ1 γ T3  T2 γðr  1Þ QA rv

Typical values for the diesel cycle are compression ratios near 25 to ensure auto ignition. A diesel engine takes in just air, compresses it, and then injects fuel into the compressed air. The heat of the compressed air lights the fuel spontaneously. A typical thermal efficiency computed from the above equation using a compression ratio of 25 is a value ηt ¼ 0:264. Note: Diesel engines are in general 30–35 % more efficient than gasoline-powered vehicles; however, efficiency strongly depends on the vehicle load. The energy efficiency of alternative power trains in vehicles is discussed in Åhman (2001). Otto and diesel engines are most commonly used in transportation. The Wankel engine is another concept with less proliferation. It operates without pistons. The Mazda RX-8 is one example of a car that deploys a Wankel engine. Table 2 shows some aspects of Wankel engines. Experiments with turbine-powered cars were carried out in the USA around 1960. The following pros and cons were identified (Table 3). Gas turbines are very efficient at high speeds and constant load. They need time to reach optimum operating conditions, and they produce thrust rather than torque. The problem with vehicles is that they are operated in several load conditions and often only for short distances. Although the concept of turbine cars was abandoned soon after their appearance, they might still offer an interesting route to future efficient cars, so new research is carried out in this area, for instance, on micro-gas turbines (MGT) to recharge battery packs, in particular, for electric vehicles (EVs) (Sim et al. 2013).

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Table 2 Assessment of the Wankel engine (Reproduced with permission from Hege 2006) Pros High power output/unit weight Good fuel/air mixing Even combustion

Cons Rotating seals reduce engine compression ratio Large fraction of unburned fuel lowers the efficiency Excessive noise due to rotating seals

Table 3 Assessment of turbine-powered automobiles (Reproduced from Hege 2006) Pros Low maintenance Long engine life expectancy Reduction of number of parts by 80 % No warm-up period, easy low-temperature start No stall at sudden overload Hot but clean exhaust gases Low oil consumption Operation on wide fuel variety

Fig. 11 Air-fuelled engines (Reproduced with permission from Chen et al. 2011)

Cons High fuel consumption at idle due to high rpm throttle lag from idle as the engine spools up. High temperature of exhaust gases, low efficiency High noise emissions Expensive

a Compressed Air Tank

Expander Compressed air engine

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Another technology is the “air fuelled engine.” It can be operated by compressed air (Miller et al. 2010) or by liquid air, yielding zero tailpipe emissions (Chen et al. 2011), compare Fig. 11. Due to the high energy consumption of air liquefaction plants, the compressed air-powered engines have a better energy efficiency than the liquid air ones (28.3 % to 36.0 % vs. 12.8 % to 17.0 % for the setups studied in Chen et al. 2011). Compared to liquid hydrocarbon fuels, compressed air has a lower energy density. A novel concept for internal combustion engines is HCCI (homogeneous charge compression ignition) (Zhao 2007). It is a kind of hybrid between a compression ignition and a spark ignition engine, in that a homogeneous fuel/air mixture is brought to autoignition. This combustion mode resembles the typical “knocking” in gasoline engines. It is fast and hard to control. However, HCCI offers the potential of low-pollution and high-efficiency automotive engines.

Alternative Fuels With depleting fossil fuel resources, costs go up and supply shortages might occur, apart from the emission of CO2 into the atmosphere from the burning of these fuels. Alternative fuels can be unconventional fossil fuels (such as those derived from shale gas (Mallapragada et al. 2014), methane hydrate, fracking, etc.) and “renewable” fuels. This section focuses on renewable fuels, which are produced directly or indirectly from sunlight, without the need to turn to fossil fuels. The following energy carriers have been envisaged as fuels for combustion engines and/or fuel cells: • • • • •

Hydrogen Ethanol Ammonia (Zamfirescu and Dincer 2009) Methane Methanol

These fuels can be produced via various routes, both from fossil and renewable resources. Methane is also the main constituent of biogas. There are so-called flexible-fuel (flex fuel) vehicles that can run on several fuels, e.g., ethanol. A blend of gasoline and 85 % ethanol is called E85. Flex-fuel vehicles (FFV) have been produced since the 1980s. Ethanol (von Blottnitz and Ann Curran 2007) and biodiesel (Ticker 2003) are two common “biofuels.” Fischer Tropsch synthesis and biomass gasification are important processes to obtain fuels from biomass, apart from anaerobic digestion and fermentation. Fuels from waste are also considered biofuels. Oil crops yield fuels from extraction and pressing of suitable plants (Tickell 2000). Also, aquatic biomass such as certain algae can be used, e.g., for biodiesel production. There is also some controversy around biofuels. Two issues associated with biofuels are

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• Potential competition over farmland with food crops • Water consumption associated with their production (see concept of virtual water, Allan 2011) One can distinguish between 1st, 2nd, and 3rd generation of biofuels. First-generation biofuels are made from foodstuff (ethanol from corn, biodiesel from soybean, or rapeseed via transesterification). They are mature and available on the market. Second-generation biofuels are produced from lignocellulose. There are thermal and enzymatic processes to break of the biopolymers into smaller units. There are also “1.5 G” biofuels, which utilize the full plant of 1G fuels. The first 1.5G and 2G biofuel commercial production plants are on stream. Their advantage is that no competition over arable land with food crops exists. Also, 2G biofuels can be grown on marginal land. Third-generation biofuels target algae for “green” fuel production, as they are expected to yield more biomass per area than land-based fuels. They could use sewage as nutrient, and avoid land usage (land use change, e.g., through deforestation to produce cropland), which also contributes to climate change. Energy produced from biomass was initially considered carbon neutral because biomass is renewable through photosynthesis. Controversies, however, have emerged about the various impacts of promoting the use of first-generation biofuels. Major concerns about using bioethanol as fuel include the following issues: • Corn is a food source, and corn ethanol production will reduce food availability. Developing countries that depend on the corn donation from the west have already experienced food shortages. • Fertilizer is required in corn production; both cost and energy consumption are incurred during fertilizer production. Moreover, unprecedentedly large scale use of fertilizer alters the natural nitrogen cycle and induces other ecological/environmental problems that have already been identified as threats. • About 5 gal of water are needed in the production of each gallon of ethanol in a plant; this does not consider the amount of water it takes to grow the corn. So potable water shortages might result from excessive bioethanol production. • Bioethanol production requires energy input. Ethanol purification by distillation is energy intensive and usually involves consumption of natural gas, which, in turn, produces CO2 from fossil fuel. As a result, while bioethanol utilization reduces fossil fuel dependence, it is not a completely carbon neutral process. Widespread adoption of bioethanol will cause redistribution of the world’s natural resources and wealth. The actual environmental and societal costs of bioethanol are likely to be much higher. A good starting point for a healthy debate on this issue can be found at (Schulz 2007). The transportation of energy carriers also consumes, naturally, energy. In Hamelinck et al. (2003), the energy consumption of biofuel transportation from production site to point of use is discussed, so that biofuels are not entirely carbon

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Table 4 Energy density of various fuels Fuel Diesel Gasoline LPG (liquefied petroleum gas) Propane Ethanol Methanol Liquid hydrogen Hydrogen (150 bar) Nickel-metal hydride Lead acid battery Compressed air

Volumetric (Wh/l) 10,942 9,700 7,216 6,600 6,100 4,600 2,600 405 100 40 17

Gravimetric (Wh/kg) 13,762 12,200 12,100 13,900 7,850 6,400 39,000 39,000 60 25 34

neutral or even carbon negative. The carbon balance of several biofuels is even worse than that of gasoline or diesel. A detailed life cycle assessment is necessary. When assessing biofuels, next to climate change, abiotic depletion, acidification, eutrophication, and human toxicity (Petersen et al. 2015) need to be considered. Second- and third-generation biofuels hold promise for CO2 emission savings. The share of biofuels is expected to increase significantly over the next decade. An important aspect of alternative fuels, apart from their specific costs, is the energy density (see Table 4). From the above Table 4, one can see that compressed air has a low energy density both in terms of volume and weight. The energy density is important for the range of a vehicle. Gases can be stored in compressed form, as hydrides or as a liquid in cryogenic conditions. Liquefaction can consume a considerable amount of energy. For hydrogen, one can define the gravimetric storage density. It is the weight of hydrogen being stored divided by the weight of the storage and delivery system. A typical value is 2–4 %. Storage has to be achieved in a safe, cost-effective, and efficient way. Alanates are a promising material class for hydrogen storage (Gross et al. 2002). Hydrides, this is chemically bond hydrogen in a solid material. This storage approach should have the highest hydrogen-packing density. However, storage media have to meet several requirements: • • • •

Reversible hydrogen uptake/release Lightweight with high capacity for hydrogen Rapid kinetic properties Equilibrium properties (p, T) consistent with near-ambient conditions There are two solid-state approaches:

• Hydrogen absorption (bulk hydrogen) • Hydrogen adsorption (surface hydrogen)

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H3BH3 Thermal decomp

LiAIH4 + NH4CI Thermal decomp.

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0

2000 0 Steel cylinder

Theoretical capacity (wt %)

Excluding ancillaries

Theoretical capacity (wh/kg)

Fuel Efficiency in Transportation Systems

Fig. 12 Graphic illustration of hydrogen storage methods. Red color indicates that the technologies have not reached maturity yet (Reproduced from Obert 1973)

For details on hydride storage, see Agresti (2010). Figure 12 compares several storage methods for hydrogen. Hydrogen can be produced, e.g., by electrolysis (solar power) or gasification. Renewable energies for sustainable development are discussed in Lund (2007).

Alternative Power Sources Electric cars come as battery-powered and fuel-cell-powered models. For a comparison on “well-to-wheel” energy pathways, see, e.g., (Eaves and Eaves 2004). So-called hybrid vehicles use a combination of an internal combustion engine (ICE) plus an electric motor (van Vliet et al. 2010).

Air Transportation According to Chèze et al. (2011), world air traffic should increase by about 100 % between 2008 and 2025. The world jet fuel demand is expected to increase by about 38 % during the same period (Chèze et al. 2011). Aircraft manufacturers have reduced the specific fuel consumption of their equipment over the last decades, e. g., by using more efficient turbines, lightweight construction materials, and improved design. More radical concepts might help lower specific fuel consumptions further. Blended-wing-body (BWB) aircraft are promising constructions currently being studied. Their benefits are 10–15 % less weight and 20–25 % less fuel

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consumption. Challenges today are the integration of the propulsion system into the airframe, aerodynamics, and control. An important aspect for the fuel efficiency of aircraft is the so-called aerodynamic efficiency. It determines its range with all other parameters kept constant. For details, see Qin et al. (2004). CO2 emissions and energy efficiency of aircraft are treated in Lee (2010), Babikian et al. (2002), Lee et al. (2004), and Morrell (2009).

Cargo Freight transportation is a huge industry. Goods are moved by sea, air, and land, where seaborne transportation has the highest share with over 30,000 billion tonnemiles per year. Sea transportation aboard large container ships has a particularly advantageous energy efficiency compared to other modes. Because of concerns for the air quality in harbors and port cities, the emissions from ships have recently received more attention. For details on CO2 emissions from shipping activities and their mitigation, see Fitzgerald et al. (2011), Villalba and Gemechu (2011), Cadarso et al. (2010), Geerlings and van Duin (2011), Heitmann and Khalilian (2011), Schrooten et al. (2009).

Means of Energy Efficiency Energy efficiency improvements can be achieved in various ways. By training staff, an “energy saving mindset” can be created. It can yield fuel savings directly, without the need for significant investment costs. However, the impact will not be as long lasting as technical improvements. Building upon the above idea of different means to achieve energy efficiency gains, the following Fig. 13 below highlights four energy conservation strategies for road transportation and their monetary impact, reproduced with permission from Litman (2005). In Parry et al. (2014), an analytical framework for comparing the welfare effects of energy efficiency standards and pricing policies for reducing gasoline, electricity, and carbon emissions is discussed.

Comparison of Different Transportation Technologies A key question related to energy efficiency in transportation is how various modes compare to each other. This is shown in an exemplary way for the greenhouse gas emissions (g CO2 equivalents) per PKT (PKT = passenger kilometer travelled). In that paper (Chester and Horvath 2009), it is concluded that the total life cycle energy inputs and greenhouse gas emissions for road, rail, and aircraft transportation on top of the tailpipe emissions are 63 %, 155 %, and 31 %, respectively. This means that in the case of rail transportation, the major part of CO2 emissions does not occur during the use of the vessel for a journey, but rather in related areas such as infrastructure

Change in Per Vehicle Annual Costs

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$400 $300 $200 $100

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Noise Pollution Barrier Effect Traffic Services Roadway Costs Crash Externalities Local Air Pollution Traffic Congestion Parking Externalities Energy Conservation Consumer Surplus

$0 −$100 −$200

Alternative Fuels

Fuel Efficiency Standards

Fuel Taxes

Mobility Management

Fig. 13 Cost impact of four different strategies for energy conservation. Above the 0 line, benefits are shown, and below costs. The barrier effect refers to delays that motorized traffic causes to other modes of transportation. In Litman (2005), it is valued at 0.7 cent per vehicle kilometer. For more details, the reader is referred to Litman (2005)

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Small Aircraft Midsize Aircraft Large Aircraft Vehicle Active Operation Vehicle Insurance Infrastructure Parking

Greenhouse Gas Emissions (g CO2e/PKT)

98 92 Vehicle Inactive Operation Infrastructure Construction Infrastructure Insurance

Vehicle Manufacturing Infrastructure Operation Fuel Production

Vehicle Maintenance Infrastructure Maintenance

Fig. 14 Total GHG (greenhouse gas) emissions per PKT (passenger kilometer travelled). The components of vehicle operation are depicted in grey, while other vehicle components are shown in blue shades. Infrastructure components are shown in red and orange. Fuel production components carry green color. All components appear in the order of the legend (Reproduced with permission from Chester and Horvath 2009)

construction and infrastructure operation. The infrastructure for railways is more complex than that of large aircraft, for instance. As can be seen from Fig. 14 above, it is important to consider infrastructure and supply chain aspects when comparing different transportation modes for their energy efficiency. The (assumed) passenger occupancy is one parameter that strongly affects the results of such studies.

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Energy efficiency of rail transportation is detailed in Miller (2009); of buses in Ally and Pryor (2007); and of aircraft in Lee (2010), Babikian et al. (2002), Lee et al. (2004) and Morrell (2009).

Future Directions Over the last years, a “green” development has emerged, and sustainability has become a buzzword also among consumers and in the transportation industries. In Utlu and Hepbasli (2007), the energy efficiencies of different sectors in several countries are compared (see Fig. 15 below). One can spot that they range from 35 % to 70 %. There is a big potential for savings in all sectors, and it is largest in the transportation area, followed by utilities, residential/commercial, and industrial sectors. The efficiency of vehicles on US roads from 1923 to 2006 is discussed in Sivak and Tsimhoni (2009). In Romm (2006), Joseph Romm ponders on the car and fuel of the future, and in Azar et al. (2003), global energy scenarios in transportation until 2100 are developed. By looking at Fig. 15, one can assume that the transportation sector offers plenty of potential for energy efficiency improvements. An interesting study (Åkerman and Höjer 2006), which is partly reproduced below, has attempted to quantify these potentials, see Tables 5 and 6. For cargo transportation, airships might be an energy-efficient means of transportation in future (Liao and Pasternak 2009).

Energy efficiencies (%)

90 80 70 60 50 40 30 20 10 0 Countries Utility

Industrial

Residential

Transportation

Agriculture

End-use

Power (End-use)

Fig. 15 Energy efficiencies of different countries by sector. In transportation, the potential for improvement seems biggest (Reproduced with permission from Utlu and Hepbasli (2007))

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Table 5 Potential to reduce the energy use per passenger-km in Sweden from 2000 to 2050. The occupancy and speed are kept constant (Reproduced with permission from Åkerman and Höjer 2006) (see there for details)

Car, combustion mode, 1,2 pass/car ( pyridinium > phosphonium > imidazolium (Yuan et al. 2013).

CO2 Storage Storing CO2 in the subsurface is technologically feasible but far from a trivial endeavor. A large effort of multidisciplinary research is needed before any largescale injection operation is started. Selection of a storage site is usually aided by a source-sink matching survey, which will limit the viable region for injection to those located close to large stationary CO2 sources. Geological criteria will then determine whether a given formation in the selected area is suitable for injection. These criteria are basically related to the reservoir storage capacity, the containment capability, and the injectivity of CO2. Geological characterization methods, such as those used in the oil industry, will be required for this evaluation, often being an expensive and time-consuming step. Even if a suitable site is found, environmental and regulation issues must be assessed as well to ensure that the storage complex will operate within local safety standards and legislation. Furthermore, site operations must have a positive public acceptance, especially by local communities in the vicinity of the storage complex. This section will review some of the technical aspects related to the injection of CO2 and the characteristics of the geological media for storage and containment.

Technical Aspects CO2 is injected in a reservoir through an injection well, which is in many aspects similar to oil and gas production wells. However, wellbore materials have to be carefully selected. Cement and steel commonly employed for completion of production wells may experience corrosion by wet CO2 (an acid media that reacts strongly with cement, leaching components resulting in structural damage) (Scherer et al. 2005). Steel casings may also be corroded by this media. CO2 needs to be compressed in the surface to reach the reservoir. Ideally, it should be stored underground in a supercritical phase – a state where CO2 has gas-like viscosity (therefore with high mobility) and high density, which is advantageous for maximizing storage per pore volume. This state is reached when both temperature and pressure of CO2 are both above 31.1  C and 73.9 bar, respectively. Since there is an increase in pressure and temperature with depth in the Earth’s crust (geothermal and hydrostatic gradients, averaging ca. 30  C and 100 bar per kilometer, respectively), at approximately 800 m depth, CO2 is likely to be found

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in a supercritical state. One ton of CO2 occupies 509 m3 at surface conditions, and the same amount occupies only 1.39 m3 at 1000 m depth (temperature of 35  C and pressure of 102 bar) (Bentham and Kirby 2005).

Description of the Geological Media The geological media used to store CO2 are similar in many ways to a petroleum system. A storage system is composed of a reservoir and a caprock and may or may not contain a trap (Holt et al. 1995). A geological reservoir is a porous and permeable rock (commonly a sedimentary rock) that contains fluids such as water, oil (liquid hydrocarbons) and natural gas (light hydrocarbons), CO2, or H2S, among others, and can be used to safely store CO2. Porosity is the space within rock matrix (e.g., in between sand grains) and/or rock fractures that contains fluids, which will be partly occupied by CO2 during storage. A reservoir is preferentially a sedimentary rock (e.g., sandstone, limestone, coal) or less commonly a fractured metamorphic or igneous rock (e.g., basalts). Other less known (in terms of operation and performance) target reservoirs include oil shales, gas hydrates within marine sediments, and engineered salt caverns (IPCC 2005). These options are less investigated and will not be discussed here. CO2 stored in common geological conditions is typically found in a gas or supercritical phase, with density lower than water (ca. 600–800 kg/m3) (Fig. 6), and therefore, it will tend to move upward in the reservoir and overburden sequence, until it seeps on the surface (Gunter et al. 2004). To ensure that the CO2 will be 100 0 20 11 0.5

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Fig. 6 Variation of CO2 density with depth, assuming hydrostatic pressure and a geothermal gradient of 25  C/km from 15  C at the surface (IPCC 2005)

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retained after injection, it is necessary that the reservoir be sealed with an overlying impermeable caprock (with permeability typically lower than 0.1 mD). This caprock will prevent migration of CO2 out of the reservoir and allow other trapping mechanisms starting to operate (see following sections). Impermeable caprocks are commonly sedimentary rocks such as mudstones, limestones, or evaporites.

Injectivity Injectivity is the ability of CO2 to flow from the well into the reservoir and is directly related to the reservoir permeability, which is a measure of the degree of connection between the rock pores. This property is not easily predicted, as different techniques can be employed to evaluate it (using core samples, interpretation of well log data, and well testing), often resulting in conflicting data. Also, it is susceptible to minimum heterogeneities of the reservoir and is highly anisotropic (it varies significantly with the direction of measurement). Ideally, a permeability higher than 100 mD is required to provide good injectivity. However, in some cases, the reservoir is not sufficiently permeable to allow high rates of CO2 inflow, and it may require an artificial enhancement through well stimulation (by injection of chemicals or induction of fractures) to improve injectivity. The number and array of wells is also important to optimize injection rates. In the next section, the most important geological reservoirs for CO2 storage will be described in more detail.

Reservoir Options As mentioned previously, there are three main groups of reservoirs that are more likely to be used in a CO2 storage operation: petroleum fields, saline aquifers, and coal deposits (Fig. 7). The first two are already in their commercial phase, and the

Enhanced Coalbed Methane Recovery (ECBM)

Storage in Depleted Oil & Gas Fields

Storage in Deep Saline Aquifers

Oil and Gas Injected CO2 Stored CO2

Enhanced Oil Recovery (EOR)

1 km

2 km

Fig. 7 Scheme of the possible reservoir options for CO2 storage

Storage in Deep Saline Aquifers

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latter, although proven in pilot scale, still needs to be demonstrated in larger scale (Van Bergen et al. 2004).

Oil and Gas Fields Petroleum reservoirs are appealing targets for CO2 storage, for several reasons. First, the trapping efficiency within these reservoirs is endorsed by the fact that they were capable of holding hydrocarbons for millions of years. Also, these formations are often well studied by oil companies, with plenty of data available. Finally, the injection of CO2 has been already carried out in many oil fields (especially in the USA) for several years, to increase the pressure in the reservoir and improve the oil/gas recovery rates (a method known as enhanced oil recovery – EOR) (Gozalpour et al. 2005). CO2 injection, often alternated with water, will mix with the residual oil forming a single phase (depending on reservoir pressure and temperature and oil properties) or, eventually, displace the petroleum and water phases to occupy pore space within the structural trap of the field. Mixing CO2 with oil within a reservoir typically reduces oil viscosity and increases oil recovery by 8–15 % of the residual oil left after primary and secondary (water injection) recovery (NETL 2010; Blunt et al. 1993). Immiscible EOR with CO2, i.e., related to the physical displacement of oil with CO2, is also possible, but in this case recovery factors are typically lower than miscible EOR (Taber et al. 1997a, b). Enhanced oil recovery using CO2 is a proven technique that has been carried out by the oil industry since the 1970s to maximize oil exploration in mature fields, with approximately 140 projects in operation in 2010, the majority located in the Permian Basin in west Texas (USA) (IEA 2013; Gozalpour et al. 2005). In 2013, the first offshore CO2-EOR project was started by the Brazilian oil company Petrobas, in the Lula field, one of the major ones in the Pre-Salt area in the south Atlantic Ocean (GC Institute 2014). Unfortunately, the net emission reductions associated with an EOR project most likely will not be quite significant, as more fossil fuels are produced in the process, which will be consumed, generating additional CO2. Furthermore, in many EOR projects currently running in the USA, CO2 is not captured from anthropogenic sources but instead extracted from natural accumulations in the Colorado and New Mexico states and transported through an extensive pipeline network. It is difficult to estimate how much CO2 will remain stored in EOR projects, as it depends on the field structure, the recovery rates and injection methods, and the operation strategy after CO2 breaks through in the production wells. To maximize CO2 storage in EOR projects, the CO2 produced together with oil must be separated and reinjected in the same or other reservoir. Until 2010, approximately 560 Mt of CO2 have been injected in petroleum fields by EOR projects in the USA only. Currently, ca. 60 Mt of CO2 are injected every year in that country (NETL 2010). Despite its arguable benefits for emission reductions, CO2 EOR is an activity with significant potential for CCS development. It is estimated that up to 80 % of oil reservoirs worldwide might be suitable for CO2

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injection based upon oil recovery criteria alone (Taber et al. 1997a, b), with an overall capacity between 675 and 900 Gt CO2 (IPCC 2005).

Saline Aquifers Saline aquifers are formations that are geologically similar to oil and gas fields, save for the fact that its pores are filled mostly with highly saline water (brine). Salinity of these formation waters should be above levels that make them unsuitable for human consumption, which usually means concentrations higher than 10 g/L. Usually, only aquifers with salinity higher than seawater (35 g/L) are considered suitable for storage projects. As already mentioned, an ideal reservoir should be deeper than ca. 800 m, for a higher likelihood of CO2 being in a supercritical phase, with a high density and gas-like viscosity, therefore maximizing pore-volume filling and mobility within the reservoir (Pruess and Garcia 2002). Both porosity and permeability of the reservoir should be sufficiently high so as to ensure constant injection of CO2 for the time duration of the project (usually a few years, at least). Since the CO2 injected will displace the original fluid, a low permeability may cause clogging and reservoir overpressures that may result in hydraulic fractures of the reservoir. Physicochemical interactions between CO2 and reservoir rock and fluids should not deteriorate reservoir quality close to injection wells during injection phase (this topic will be described in greater detail further in the chapter). To be eligible for CO2 storage, a saline aquifer must present an overlying caprock with low permeability, being continuous and with minimum amounts of faults and fractures over the range of the estimated storage area. Moreover, this formation must resist the hydraulic overpressure imposed during the injection phase. The great advantage of saline aquifers over other storage reservoirs is their enormous theoretical capacity and worldwide availability, with uniform distribution. On the other hand, there is much less information and data available for saline aquifers, since the economic incentive for their study is nearly absent. Therefore, global storage capacity estimations for deep saline formations have been roughly estimated thus far, between 1,000 and 10,000 Gt CO2 (IPCC 2005).

Coal Fields Coalbeds are able to trap CO2 by adsorption (see next section), and most of the world coal resources are unminable (usually because of high depths), therefore being potential targets for CO2 storage. Like in oil fields, storage in coalbeds may be economically interesting, as the injected CO2 can be adsorbed by the coal matrix, displacing the naturally occurring methane from coal, which can be produced through wells – a technique known as enhanced coalbed methane recovery (ECBM). A key issue for storage in coal is the identification of suitable coalbeds. A detailed characterization of the coal is necessary to evaluate composition, rank, nonorganic material

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content, permeability, and adsorption capacity, providing the necessary information for site selection. In addition, technical limitations related to coal permeability, which is typically lower than in common conventional reservoirs, have to be considered. The injection of CO2 is known to cause coal swelling, which further decreases permeability and, consequently, injectivity (Day et al. 2010). Reactivity of coal with CO2 and/or formation water is another issue that requires investigation, since the interactions of coal macerals (organic matter) with CO2 are largely unknown and may lead to alterations that modify the coal matrix and its adsorption behavior toward CO2, methane, and other gases (Reeves and Schoeling 2001). Due to these limitations, CO2 storage in coalbeds is still in the early stages of development, compared to the other reservoir options, with a few ECBM demonstration projects currently deployed. ECBM tests and demonstrations have been carried out in the USA, in the San Juan Basin (Colorado), where many commercial coalbed methane (CBM) operations are in place (Gale and Freund 2001; Stevens et al. 2001). An ECBM pilot project was started in 2009 in southern Brazil (Carbometano/Porto Batista project) to evaluate the potential for methane recovery and CO2 storage of the coal reserves in this country (Beck et al. 2011).

Trapping Mechanisms of CO2 in Geological Media There are at least six trapping mechanisms that can keep CO2 confined in a storage complex for long periods of time. These mechanisms, discussed in detail in this section and depicted in Fig. 8, may vary significantly with time and space within the reservoir (IPCC 2005).

Structural and Stratigraphic Trapping CO2 may fill “closed” structural or stratigraphic traps in a similar fashion that oil and gas do in petroleum fields. In this case, CO2 will be accommodated within the reservoir below the caprock, and after equilibrium, it will be stored as an immiscible and immobile plume underneath the caprock. CO2 may occupy the entire pore volume of the reservoir within the trap from the top until its spill point, minus the volume of irreducible water (and oil and gas). This is the most important mechanism in the early stages of an injection operation, as CO2 tends to migrate upward through the reservoir in only a few years, accumulating below the caprock.

Hydrodynamic and Residual Trapping CO2 injected in an “open” reservoir, i.e., a reservoir with a caprock without a closure or trap, may form an immiscible plume that will migrate upward and up dip, due to density differences between the CO2 and water (or oil) phases. Forces acting

Reservoir

CO2 CO2

Formation fluids (brine/oil/gas)

Mineral grains

Residual Saturation

Fig. 8 Trapping mechanisms of stored CO2 in geological reservoirs

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Adsorption

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against the displacement of CO2 will retard plume movement and trap CO2 within the reservoir for a certain period of time. The displacement of this plume will leave a CO2 “tail” behind, in which storage occurs in pore space as residual gas at irreducible gas saturation (i.e., the minimum saturation of a fluid to be displaced in water media). As with the structural trapping, these mechanisms will also operate soon after CO2 injection in a reservoir.

Dissolution and Mineralization Trapping After injection, CO2 will start to dissolve in formation water, and depending on factors like pH, a different proportion of dissolved species will form: H2CO3 (carbonic acid), HCO3 (bicarbonate), and CO32 (carbonate). Once dissolved, CO2 will be trapped within the reservoir aqueous phase as a dissolved species until geochemical conditions are changed (and proportion of dissolved species modified) or the fluids are displaced. Dissolved CO2 may change drastically geochemical conditions of the media, mostly by increasing acidification of the aqueous phase, which in general enhances drastically the rate of dissolution of minerals present in the reservoir and caprock. Furthermore, the aqueous phase tends to be dried out in the vicinity of the CO2-water interface, as the supercritical CO2 absorbs water, leading to a more saturated brine (Kaszuba et al. 2003). This may set off the precipitation of minerals in this region, such as halite (NaCl). Dissolved CO2 species and cations originated from dissolution of minerals or present in water may interact to form carbonates such as calcite (CaCO3), magnesite (MgCO3), and siderite (FeCO3), among others. The type of carbonate formed will depend on pressure, temperature, and pH conditions, particularly on the activity of the cations dissolved in water and kinetics of reactions. Once in a solid phase, CO2 will be stored within the reservoir until unlikely (in a period of 473 K). The sorbent treated with ammonia at 673 K showed the adsorption capacity of 1.73 mmol/g. This improvement was ascribed to the introduction of nitrogen-containing groups to carbon structure. Pevida and his group (Pevida et al. 2008) made a conclusion that the CO2 adsorption capacity is not directly related to the total nitrogen content of sorbents but rather to specific nitrogen functionalities that are responsible for increasing the CO2–adsorbent affinity. Alesi et al. (2010) studied CO2 adsorption and regeneration conditions of tertiary amidine derivatives supported on AC from 302 to 323 K. It was found that CO2 adsorption on the amidine-modified AC only occurred in the existence of moisture. Adsorption of water vapor on the hydrophilic AC support limits the CO2 capture capacities. Maroto-Valer et al. (2005; Tang et al. 2004; Zhang et al. 2004; Zhong et al. 2004) found that anthracite coal with 2 h of activation at 1163 K achieved a CO2 adsorption capacity of 1.49 mmol/g (Maroto-Valer et al. 2005). The feasibility of a high-surface-area sorbent from low-cost anthracites was also investigated (Zhong et al. 2004; Maroto-Valer et al. 2005). The adsorption capacity of polyethylenimine (PEI)-impregnated deashed anthracite sorbent was 2.13 mmol/g at 348 K (Zhong et al. 2004). In another study, they observed a decrease in adsorption capacity of activated anthracites impregnated with PEI with increasing adsorption temperature (Maroto-Valer et al. 2005).

Ammonia-treated AC Ammonia-treated char

2.79 1.98

0.831 0.28

1190 653

1617 954

0.48

SWNT AC Ammonia-treated AC

2

540

1300

Anthracite-based AC

0.6–0.8

Temperature T (K) 298

298 298

308 298 309.15

303

298 298

1.5–2.2

BET surface area (m2/g)

AC AC

Pore volume (cm3/g)

298 298

Pore size (nm)

AC AC

Sorbent AC

Table 5 CO2 adsorption capacity of carbonaceous solid sorbents

1 1

1 0.1 1

1

1 1

1 0.2

Pressure p (atm) 1

1.91 2.20

2.07 0.57 1.73

1.49

3.23 2.61

2.45 0.75

Capacity (mmol/g) 2.07

(continued)

References (Kikkinides et al. 1993) (Chue et al. 1995) (Do and Wang 1998) (Na et al. 2001) (Siriwardane et al. 2001) (Maroto-Valer et al. 2005) (Cinke et al. 2003) (Lu et al. 2008) (Przepiorski et al. 2004) (Pevida et al. 2008) (Plaza et al. 2009)

CO2 Capture Using Solid Sorbents 2361

APTES-grafted CNTs APTS-grafted CNTs TEPA-impregnated CNTs TEPA-impregnated CNTs

Sorbent Amine-enriched fly ash PEI-impregnated fly ash APTS-modified CNT PEI-functionalized SWCNTs Graphene CMS

Table 5 (continued)

0.91 0.056

0.108

25.47

0.603

0.70

8.9 19.04

Pore volume (cm3/g)

Pore size (nm)

17

198 8.9

1725

BET surface area (m2/g)

0.15/0.5 1 1 1

293 300 195 303

343

0.1

0.15 0.1 0.02

1

348

293 298 313

Pressure p (atm) 0.1

Temperature T (K) 298

1.32 0.93 3.56 3.87 (humid) 3.09

0.8 2.43

0.98/2.59 2.1

1.02

Capacity (mmol/g) 2.05

(Liu et al. 2014a)

(Ghosh et al. 2008) (Burchell et al. 1997) (Hsu et al. 2010) (Lu et al. 2008) (Ye et al. 2012)

(Arenillas et al. 2005) (Su et al. 2009) (Dillon et al. 2008)

References (Gray et al. 2004)

2362 Y. Shi et al.

CO2 Capture Using Solid Sorbents Fig. 2 Isotherm for adsorption of CO2 on activated carbon (Do and Wang 1998)

2363

Adsorbed (mmole/g)

0.8

298 K 323 K

0.6

373 K 0.4

0.2

0.0 0

5

10 Pressure (kPa)

15

20

Carbon-enriched fly ash concentrates treated with various amines were developed by Gray et al. (2004), Maroto-Valer et al. (2008; Zhang et al. 2004), and Arenillas et al. (2005). A typical comparison of CO2 adsorption capacities of activated fly ash carbon and its alkanolamine-modified counterparts at various temperatures was reported by Maroto-Valer and others (Maroto-Valer et al. 2008). It was found that activation by steam before impregnation could successfully increase the pore volume and surface area, consequently resulting in the increase of CO2 capture capacity (Zhang et al. 2004; Maroto-Valer et al. 2008). The impregnation with PEI could significantly enhance the adsorption capacity of this class of sorbents up to 2.13 mmol/g at 348 K, which is much higher than that without impregnation (0.22 mmol/g at 348 K) (Zhang et al. 2004). Arenillas et al. (2005) achieved the CO2 adsorption capacity of 1.02 mmol/g at 348 K using activated fly ash-derived sorbents impregnated with PEI (Zhang et al. 2004; Arenillas et al. 2005). Fly ash impregnated with PEI and its blend with poly (ethylene glycol) (PEG) was also investigated. The addition of PEG into the PEI-loaded sorbents improves the CO2 adsorption capacity and kinetics, which could be attributed to the bicarbonate formation reaction in the presence of PEG (attracts more water). CNT can act as a suitable candidate for CO2 capture by choosing the appropriate pore size and optimum conditions (Huang et al. 2007; Razavi et al. 2011). Considerable experimental research and theoretical modeling efforts are being devoted to investigate the adsorption of CO2 on CNTs. Cinke et al. (2003) reported CO2 adsorption on purified single-walled carbon nanotubes (SWCNTs) in the temperature range from 273 to 473 K (see Fig. 3). The CO2 adsorption capacity of SWCNTs was twice that of AC. Lu et al. (2008) reported CO2 capture by CNT and its modification. After functionalization, CNT showed a significant enhancement in

2364

Y. Shi et al.

Volume absorbed (cm3/g STP)

100

purified HiPco

90 activated carbon

80 70

raw HiPco

60 50 40 30 20 10 0 0

200

400

600

800

1000

Pressure (mmHg)

Fig. 3 Comparison of CO2 adsorption capacities of high-pressure CO conversion (HiPco) singlewalled nanotubes (SWNTs) and activated carbon (AC) at 308 K (Cinke et al. 2003)

CO2 adsorption capacity. CNTs modified by APTES were also tested for their CO2 adsorption potential at various temperatures by Su et al. (2009). The CO2 adsorption capacities of CNTs and CNTs (APTS) increased with water content, and decreased with temperature, indicating the exothermic nature of adsorption process. The CO2 adsorption capacity of CNT (APTS) was 2.59 mmol/g at 293 K. The potential application of CNT as the support for amine-impregnated sorbents has been studied by Fifield et al. (2004). In order to increase the affinity of the carbon structure, pyrene methyl picolinimide (PMP) was introduced as anchors. Dillon et al. (2008) synthesized and characterized PEI-functionalized SWNTs. A maximum adsorption of 2.1 mmol/g was reported for PEI (25000)-SWNT at 300 K. Hsu et al. (2010) proposed that a combination of thermal and vacuum desorption of CNT (APTES) at 393 K could reduce the regeneration time. The adsorption capacities and physicochemical properties were preserved after 20 cycles of adsorption/ regeneration. Industrial-grade multi-walled carbon nanotubes (IG-MWCNTs) impregnated with tetraethylenepentamine (TEPA) were systematically investigated for CO2 capture by Liu et al. (2014a, b). TEPA-impregnated IG-MWCNTs were shown to have high CO2 adsorption capacity comparable to that of TEPA-impregnated P-MWCNTs (Ye et al. 2012). The adsorption capacity of IG-MWCNT-based adsorbents was in the range of 2.145–3.088 mmol/g, depending on adsorption temperatures. The isosteric heat of adsorption for CO2 decreased with the increase in CO2 loading (Fig. 4). The high heat of adsorption in the lower loading region was due to the reaction of CO2 with the active sites of TEPA. The process of IG-MWCNTs-50 adsorption of CO2 was partly physical and partly chemical adsorption. The adsorption/desorption kinetics of CO2 on TEPA-impregnated

CO2 Capture Using Solid Sorbents

2365

60

50

Q (KJ/mol)

40

30

20

10 0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Adsorption Capacity (mmol/g)

Fig. 4 Isosteric heats of adsorption of CO2 for IG-MWCNTs-50 in a binary mixture of CO2 and N2 (Liu et al. 2014a)

IG-MWCNTs was investigated to obtain insight into the underlying mechanisms on the fixed bed. Avrami’s fractional-order kinetic model provided the best fitting for the adsorption behavior of CO2. In order to find the optimal regeneration method, three desorption methods were evaluated for the regeneration of solid sorbents. The activation energy Ea of CO2 adsorption/desorption was calculated to evaluate the performance of the adsorbent. The effect of gas contaminants on the adsorption behavior of adsorbents for CO2 was also studied. H2O and NO had a minimal impact on CO2 adsorption capacity, while the effect of SO2 on CO2 adsorption was influenced by adsorption temperature and SO2 concentration. Skoulidas et al. (2006) carried out simulations to analyze the adsorption and transport diffusion of CO2 and N2 in SWCNTs at room temperature. They reported that transport diffusivities for CO2 in nanotubes with diameters ranging from 1 to 5 nm are approximately independent of pressure. The observed diffusion mechanism is not Knudsen-like diffusion. Based on Monte Carlo simulations, Huang et al. (2007) showed that CO2 adsorption in the range of 4–9 mmol/g is an increasing function of the diameter of the CNTs. Additionally, CNTs demonstrated a higher selectivity toward CO2 than other sorbents, such as ACs, zeolite 13X, and MOFs. Razavi et al. (2011) also concluded that CNTs exhibited a higher selectivity of CO2 over N2, compared to other carbon-based materials, for the separation of CO2/N2 mixture. In summary, the impregnation of amines for carbonaceous materials is found to be effective to enhance CO2 adsorption capacity. However, the impregnation also caused a significant decrease of the surface areas and pore volume. Although the exact mechanism of these changes is still not well understood, it is believed that the size and molecular structure of amines play an important role.

2366

Y. Shi et al.

Polymer-Based Sorbents Polymeric amine sorbents have been used for years to capture CO2 in closed environments, such as aircraft, submarine, and space shuttles, under the concentrations of CO2 1000), was conducted by Harlick and Tezel (2004) for the capture of CO2 from flue gas. Adsorption capacities of the adsorbents increased in the following order (in the pressure range of 0–2 atm):13X (Si/Al = 2:2) > NaY (Si/Al = 5:1) > H-ZSM-530 (Si/Al = 30)> HiSiv3000 > HY-5 (Si/Al = 5) (Fig. 5). It might be on account of a low Si/Al ratio with cations (sodium) in the structure that show strong interactions with CO2. Zukal et al. (2010) investigated CO2 adsorption on six high-silica zeolites (SiO2/ Al2O3 > 60): TNU-9, IM-5, SSZ-74, ferrierite, ZSM-5, and ZSM-11. TNU-9 and IM-5 were found to have the highest CO2 adsorption capacity, attaining 2.61 and 2.42 mmol/g at the pressure of 100 kPa, respectively.

Sorbent Zeolite 13X NaY H-ZSM-5-30 HiSiv 3000 HY-5 Ferrierite ZSM-5 ZSM-11 TNU-9 IM-5 SSZ-74 NaY Cs-treated NaY Na-ZSM-5 13X MEA-modified 13X 13X MEA-modified 13X TEPA-modified Y-type zeolite TEPA-impregnated beta zeolite 811 483

0.118 0.163 0.131 0.165 0.134 0.123 0.46 0.21

0.34 0.059 0.34 0.059

1.54 1.58

11 11 11 11

680

615.5 9.15 615.5 9.15

BET surface area (m2/g)

Pore volume (cm3/g)

Pore size (nm)

Table 7 CO2 adsorption capacity of zeolites

0.15 0.15

393 333

0.1

1 0.15

303 303

303

1

0.1

Pressure p (atm) 1

473

293

Temperature T (K) 295

Capacity (mmol/g) 4.61 4.06 1.9 1.44 1.13 2.03 2.30 2.17 2.61 2.42 1.92 0.46 0.80 0.75 1.25 0.78 0.18 0.63 2.54 4.27 (water) 2.08

(Fisher et al. 2009)

(Katoh et al. 2000) (Jadhav et al. 2007) (Jadhav et al. 2007) (Su et al. 2010)

(Diaz et al. 2008)

(Zukal et al. 2010)

References (Harlick and Tezel 2004)

CO2 Capture Using Solid Sorbents 2369

2370

5

13X NaY

Amount Adsorbed (mol/kg)

Fig. 5 Comparison of CO2 adsorption isotherms for fresh zeolites at 295 K (Harlick and Tezel 2004). The filled symbols were obtained by regenerating the fresh adsorbent at 200  C for 12 h followed by the adsorption study. The open symbols were obtained as a repeat of 200  C regeneration for 12 h followed by adsorption without changing the adsorbent sample

Y. Shi et al.

4

3

HZSM-5-30 HiSiv 3000

2

HY-5 1

0 0.0

0.5

1.0 1.5 Pressure (atm.)

2.0

2.5

To enhance the adsorption capacity of CO2, the modification of zeolites via the introduction of electropositive and polyvalent cations was concentrated. Khelifa et al. (2004) concluded that NaX (Si/Al = 1.21) zeolite exchanged with Ni2+ and Cr3+ showed a decrease in CO2 adsorption capacity, compared to that of the parent NaX zeolite, due to a weak CO2–sorbent interaction. NaX and NaY and those resulting from ions exchanged with Cs, since it is the most electropositive metal of the periodic table, were tested regarding the adsorption of CO2 by Diaz et al. (2008). Cs-treated zeolites performed better and were more active for adsorption at higher temperatures (373 K). Zhang et al. (2008a) prepared chabazite (CHA) zeolites (Si/Al < 2.5) and exchanged them with alkali cations (e.g., Li, Na, and K) and alkaline-earth cations (e.g., Mg, Ca, Ba) to evaluate their potential for CO2 capture from flue gas by VSA below 393 K. From the adsorption isotherm, it was found that the NaX zeolite shows superior performance at relatively low temperatures, while NaCHA and CaCHA hold comparative advantages for high temperature (>273 K) CO2 separation. According to the research of the selectivity of ion-exchanged ZSM-5 zeolites by Katoh et al. (2000), M-ZSM-5 (M = Li, Na, K, Rb, and Cs) might be attributed to the fact that almost all CO2 molecules strongly adsorbed on the cation sites, while N2 interacted with the wall of the H-ZMS-5. There is a detrimental effect of water vapor on CO2 adsorption for zeolite, due to its preferential adsorption from the gas mixture (Brandani and Ruthven 2004; Li et al. 2008c). Trace amounts of water vapor could significantly decrease the CO2 adsorption capacity, because it gets competitively adsorbed on the zeolite surface and blocks the access for CO2 (Brandani and Ruthven 2004). It was demonstrated by another study that the adsorption of CO2 is considerably inhibited by H2O as CO2 and water vapor adsorption on zeolite 13X (Li et al. 2008c).

CO2 Capture Using Solid Sorbents

2371

Zeolites with large surface area and pore volume present a potential option for CO2 adsorption. However, CO2 adsorption capacity on zeolites decreases significantly as the temperature increases. The capacity will also be very low in the existence of moisture. Therefore, a few researches (Table 7) synthesized aminated zeolites as alternative sorbents. Zeolite 13X was modified with MEA by Jadhav et al. (2007) by impregnation method. Compared with unmodified zeolite, a higher capacity at 293 K was obtained with MEA loading of 50 wt%, despite reduced pore volume and lower surface area resulted from impregnation. The chemical interaction between CO2 and amine probably played a significant role in adsorption of CO2 at 293 K. Similarly, Su et al. (2010) dispersed TEPA into commercially available Y-type zeolite (Si/Al = 60). They obtained a CO2 adsorption capacity of 4.27 mmol/g at 333 K in the presence of 15 % CO2 and 7 % water vapor in gas stream. In another study, Fisher et al. (2009) employed β-zeolite as a solid support for TEPA impregnation and compared it with TEPA-impregnated silica and alumina. The TEPAmodified β-zeolite exhibited a CO2 adsorption capacity up to 2.08 mmol/g at 303 K under the 10 % CO2/90 % argon flow, outperforming TEPA/SiO2 and TEPA/Al2O3 sorbents. TEPA/β-zeolite maintains its CO2 capture capacity for more than 10 adsorption/regeneration cycles. Their study suggests that the higher capacity of TEPA/β-zeolite can be related to zeolite’s high surface area.

Silica-Based Sorbents Impregnated Silica-Supported Sorbents The first amine-impregnated silica used to capture CO2 was reported by Song and others (Xu et al. 2002), and they used wet impregnation of hydrothermally synthesized MCM-41 with PEI to create an adsorbent in terms of a “molecular basket” (Xu et al. 2002, 2003, 2005a, b). In their further study, Xu et al. (2003) reported the highest CO2 adsorption capacity of 3.02 mmol/g with MCM-41-PEI at a PEI loading of 75 wt% under a pure CO2 atmosphere and at 348 K. As expected, increased PEI loadings led to higher adsorption of CO2. Compared with the chemical adsorption for higher PEI loadings, the physical adsorption on the unmodified pore wall of MCM-41 (and the capillary condensation in the mesopore) is negligible. Additionally, a synergetic effect of MCM-41 and PEI for CO2 adsorption was hypothesized (Xu et al. 2003). When the mesoporous pores were loaded with 50 wt% PEI, the highest synergetic adsorption gain was obtained. MCM-41 impregnated with PEI exhibited an increase in adsorption capacity with increasing temperature, in comparison to ACs and zeolites. Xu et al. (2003) assumed that low adsorption rate caused by kinetic limitations results in the low adsorption capacity at low temperature. Therefore, the overall process is kinetically controlled. Song and his groups also studied a series of performance and stability using a MCM-41-PEI sorbent to capture CO2 from simulated flue gas, flue gas from a natural gas-fired boiler, and simulated humid flue gas using a packed-bed

2372

Y. Shi et al.

Fig. 6 Schematic representation of the synthesis of PME (Heydari-Gorji and Sayari 2011)

adsorption column (Xu et al. 2005a, b). The adsorbent showed a separation selectivity of 180 for CO2/O2 and >1000 for CO2/N2. The adsorbent was stable at 348 K after ten cycles of adsorption/desorption process, while it was not stable when the operation temperature was >373 K. The observation of NOx to be adsorbed simultaneously with CO2 indicates the need for preremoval of NOx from flue gas (Xu et al. 2005a, b). In addition, the CO2 adsorption capacity was enhanced when the moisture concentration is lower than that of the CO2, which could be due to the formation of bicarbonate ion (reaction 2) during the chemical interaction between PEI and CO2 in the presence of moisture. To enhance the CO2 adsorption capacity of MCM-41-PEI, PEI supported on pore-expanded (PE) MCM-41 was studied by Heydari-Gorji et al. (2011). The adsorption capacity exhibits as high as 4.68 mmol/g at 348 K for 55 wt% PEI loading due to the well-dispersed PEI inside the PE-MCM-41 pores (Heydari-Gorji and Sayari 2011) (Fig. 6). As an alternative strategy to further improve efficiency for CO2 adsorption, Yue et al. (2008a) impregnated TEPA into as-prepared MCM-41 that had been prepared with the ionic surfactant cetyltrimethylammonium bromide (CTAB). The as-prepared MCM-41 impregnated with 50 wt% TEPA exhibited a CO2 adsorption capacity of 4.16 mmol/g in 5 % CO2, probably owing to better amine distribution using ionic surfactant templates (Yue et al. 2008a). The type, amount, and distribution of the surfactant in the pores of MCM-41 all have significant influences on adsorption process. However, their studies showed that the adsorbent required only 1.5 min to reach the adsorption halftime but 140 min to reach close to equilibrium adsorption capacities. SBA-15-supported sorbent loaded with 50 wt% PEI was developed by Ma et al. (2009). The CO2 adsorption capacity of 3.18 mmol/g was obtained at 348 K under a CO2 partial pressure of 15 kPa. The CO2 adsorption capacity was 50 % higher than that of their previously reported MCM-41-PEI sorbent, probably due to the higher pore diameter and pore volume of SBA-15. This allows the PEI-modified

CO2 Capture Using Solid Sorbents

2373

sample prepared from SBA-15 to have a higher surface area for the same PEI loading. The significant role of the distribution of the amine groups impregnated in the porous materials has been confirmed by Zhu and his group (Yue et al. 2006). As-prepared mesoporous SBA-15 occluded with an organic template (Pluronic P123) was used to impregnate TEPA. The CO2 adsorption capacity of the modified SBA-15 with a TEPA loading of 50 wt% was higher than that of the calcined SBA-15. The presence of the template enhanced the accessibility of CO2 to TEPA because of a better dispersion and distribution of amines. Furthermore, Yue et al. (2008b) also synthesized as-prepared SBA-15-supported sorbents through dispersing amine blends of TEPA and DEA. The hydroxyl group in DEA is found to significantly improve the CO2 adsorption. Hydroxyl group facilitates the formation of the carbamate zwitterion; therefore, equilibrium CO2 loadings of amine can reach 2 mol CO2 (mol amine)1. Ahn and coworkers (Son et al. 2008) synthesized a series of PEI-loaded (50 wt%) ordered mesoporous silica supports, namely, MCM-41, MCM-48, SBA-15, SBA-16, and KIT-6, to evaluate their CO2 adsorption performance. All impregnated sorbents showed substantially higher CO2 sorption capacities and stability, as well as faster adsorption kinetics, than that of pure PEI. The CO2 adsorption capacities were in the following order: KIT-6 (dp = 6.5) > SBA-15 (dp = 5.5)  SBA-16 (dp = 4.1) > MCM-48 (dp = 3.1) > MCM-41 (dp = 2.1), where dp is the average pore diameter (nm). The adsorption performance was proposed to be influenced by the pore diameter and pore arrangement of mesoporous silica materials. Bulky PEI is assumed to be introduced to the pore easily as the pore size in the support increases. Goeppert et al. (2010) studied nanostructured fumed silica impregnated with various organoamines, namely, PEI, MEA, DEA, TEPA, and PEHA, as well as 2-amino-2-methyl-1-3-propanediol (AMPD), 2-(2-amino-ethylamino)ethanol (AEAE), etc. Simple amines such as MEA, DEA, AEAE, etc. are not suitable for impregnation, due to amine leaching problems at higher temperature. As shown in Table 8, amine-impregnated silica sorbents can effectively adsorb CO2 with relatively higher working capacity. The modification of pore size of silica support can further enhance the adsorption capacity. The adsorption capacity of amine-impregnated silica sorbents is not sensitive to the presence of moisture (in many cases, moisture helps to obtain higher capacity). However, the durability and regeneration kinetics of the amine-impregnated solid sorbents have not been tested adequately. Their desorption kinetics is still slow. In addition, considerable loss of amines is a major drawback for impregnated amine-functionalized sorbents.

Grafted Silica-Supported Sorbents The synthesis and characterization of amine-grafted mesoporous silica sorbents (Class 2 category) for CO2 capture were reported by many groups. In this case, amine, mainly aminosilane, is covalently tethered to the silica support (Choi et al. 2009). Three methods have been used for the grafting of amine onto a silica support: post-synthesis grafting, direct synthesis by co-condensation, and anionic template synthesis with the help of the interaction between the cation head in

PE-MCM-41 DEA(77 wt%)-impregnated PE-MCM-41 MCM-41 PEI(50 wt%)-impregnated MCM-41 MCM-48 PEI(50 wt%)-impregnated MCM-48 SBA-15 PEI(50 wt%)-impregnated SBA-15 SBA-16 PEI(50 wt%)-impregnated SBA-16 KIT-6 PEI(50 wt%)-impregnated KIT-6 PEI(65 wt%)-impregnated monolith TEPA(50 wt%)-impregnated MCM-41 MCM-41 PEI(50 wt%)-impregnated MCM-41 SBA-15 PEI(50 wt%)-impregnated SBA-15 TEPA(50 wt%)-impregnated SBA-15

Sorbent MCM-41 PEI(50 wt%)-impregnated MCM-41 PEI(50 wt%)-impregnated MCM-41

1.15 0.03 1.31 0.2 0.02

1229 11 950 80 7

16

0.03

2.7 – 6.6 6.1 –

1042 4 1162 26 753 13 736 23 895 86

0.85 0.01 1.17 0.10 0.94 0.04 0.75 0.02 1.22 0.18

2.8 – 3.1 – 5.5 – 4.1 – 6.0 5.3

917

BET surface area (m2/g) 1480 4.2

2.03

Pore volume (cm3/g) 1.0 0.011

2–3

Pore size (nm) 2.75 0.4

Table 8 CO2 adsorption capacity of silica solid sorbents

0.15 0.15 0.15 0.05 348 348 348

0.05 0.05

348 348 348

1

0.05

Pressure p (atm) 1 0.1 0.13

348

298

Temperature T (K) 348 348 348

0.14 2.02 0.11 3.18 3.23

3.75 4.54

2.52 2.89 2.93 2.70 3.07

2.93

Capacity (mmol/g) 0.195 2.05 3.08 (humid)

(Yue et al. 2006)

(Ma et al. 2009)

(Ma et al. 2009)

(Chen et al. 2009) (Yue et al. 2008a)

(Franchi et al. 2005) (Son et al. 2008)

(Xu et al. 2005a)

References (Xu et al. 2002)

2374 Y. Shi et al.

18.6

DAEAPTS-grafted HMS

9.6

DAEAPTS-grafted PE-MCM-41

Aziridine polymer-grafted SBA-15

2.21

10

APTES-grafted SBA-15 DAEAPTS-grafted PE-MCM-41 1.05

0.54 0.40 0.29

APTES-grafted SBA-15 AEAPS-grafted SBA-15 DAEAPTS-grafted SBA-15

0.46

0.67

19.0

429

950

374 250 183

926

1125

6.16

125

0.704 0.016

3.9

0.01

3.6

–

TEPA(30 wt%) + DEA(20 wt%)impregnated SBA-15 PEI(40 wt%)-impregnated mesoporous silica TEPA(83 wt%)-impregnated MC400/10 APTES-grafted silica gel APTS-grafted HMS

348 298

343

298 298

333

0.1

0.05

0.04 0.05

0.15

0.9

1 0.9

323 293 293

0.1

1

0.05

348

348

348

1.98 (humid) 3.11 (humid)

2.28

0.66, 0.65 (humid) 1.36, 1.51 (humid) 1.58, 1.80 (humid) 0.4 2.65

1.34

0.89 1.59

5.57

2.4

3.61

(continued)

(Gray et al. 2005) (Harlick and Sayari 2007) (Serna-Guerrero et al. 2010a) (Hicks et al. 2008)

(Leal et al. 1995) (Knowles et al. 2005) (Knowles et al. 2006) (Hiyoshi et al. 2005)

(Goeppert et al. 2010) (Qi et al. 2011)

(Yue et al. 2008b)

CO2 Capture Using Solid Sorbents 2375

APTES-grafted SBA-12 APTES-grafted MCM-41 APTES-grafted SBA-15

Sorbent AEAPTS-grafted SBA-16

Table 8 (continued)

37 9 52 38 55 28

Pore size (nm)

Pore volume (cm3/g) 0.54 1347 310 1506 239 687 134

BET surface area (m2/g) 715 298

Temperature T (K) 300 0.1

Pressure p (atm) 1

1.04 0.57 1.53

Capacity (mmol/g) 1.4

References (Knofel et al. 2007) (Zelenak et al. 2008)

2376 Y. Shi et al.

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Fig. 7 Modified hexagonal mesoporous silica (HMS) materials (Chaffee et al. 2002)

aminosilane and anionic surfactants (Chew et al. 2010). The mesoporous nature of the silica permits high diffusivity of organic amine into the pore structure and, following functionalization, easy diffusion for CO2 to enter and leave the pores. A wide variety of aminosilanes (see Table 8) have been grafted onto the surface of porous silica for the investigation of the impact of amine type and loadings on the CO2 adsorption capacity. Leal et al. (1995) first investigated the chemisorption of CO2 onto APTESgrafted surface of silica gel. However, the CO2 adsorption capacity of this sorbent was far below the requirement for industrial application of the sorbents. Afterward, a series of aminopropyl-grafted hexagonal mesoporous silica (HMS) compounds was prepared and characterized by Chaffee’s group to enhance CO2 adsorption. The grafted HMS materials, as shown in Fig. 7, were developed by Delaney et al. (Chaffee et al. 2002) using 3-aminopropyl-trimethoxysilane (APTS), aminoethyl-aminopropyl-trimethoxysilane (AEAPTS), and N-[3-(trimethoxysilyl) propyl) diethylenetriamine (DAEAPTS), ethylhydroxyl-aminopropyltrimethoxysilane (EHAPTS), and diethylhydroxyl-aminopropyl-trimethoxysilane (DEHAPTS) (see Table 8). The modified silica supports showed high surface area with varied concentrations of surface-bound amine and hydroxyl functional groups. The modified HMS sorbents were also shown to reversibly adsorb significantly more CO2 than modified silica gel, as reported by Leal et al. (1995). The ratio of CO2 molecules adsorbed per available N atom was 0.5 for HMS-APTS, HMS-AEAPTS, and HMS-DEAPTS, which is consistent with the carbamate formation mechanism, as presented by reaction 1. For HMS-DEHAPTS, the ratio was 1. Because tertiary amines cannot form stable carbamates, it was proposed that the hydroxyl groups may serve to stabilize carbamate-type zwitterions. Based on a systematic investigation on CO2 adsorption on different mesoporous silica substrates and their amine-functionalized hybrid product, Knowles et al. (2005, 2006; Chaffee 2005) also pointed out that the extent of surface functionalization is found to be dependent on substrate morphology (e.g., available surface area, pore geometry, and pore volume), diffusion of reagents to the surface, as well as the silanol concentration on the substrate surface. The higher nitrogen

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content of the tether caused a higher CO2 adsorption capacity. The CO2 adsorption performance of hybrid materials exhibited highest CO2 capacity of 1.66 mmol/g at 293 K in dry 90 % CO2/10 % argon mixture, and good adsorption kinetics, reaching equilibrium within 4 min. Hiyoshi et al. (2004, 2005) revealed the potential application of aminosilanemodified mesoporous silica for the separation of CO2 from gas streams in the presence of moisture. In their subsequent research (Hiyoshi et al. 2005), DAEAPTS-SBA-15 showed enhanced CO2 adsorption capacity after SBA-15 was treated with boiling water for 2 h, followed by the grafting of aminosilanes. The CO2 adsorption capacity reached 1.58 and 1.80 mmol/g in the absence and presence of moisture, respectively. The efficiencies of the aminosilanes at identical amine surface density were in the following order: APTES > AEAPTS > DAEAPTS. Gray and coworkers (Gray et al. 2005; Chang et al. 2003; Khatri et al. 2005, 2006) also prepared a series of amine-grafted SBA-15 sorbents for CO2 adsorption. Enhanced CO2 adsorption capacity was observed in the presence of H2O because of the formation of carbonate and bicarbonate (Chang et al. 2003) confirmed by Khatri et al. (2006). Khatri et al. (2006) and Zheng et al. (2004) studied the thermal stability of several grafted SBA-15 and found these to be stable up to 523 K. Furthermore, the SO2 adsorption on APTES-SBA-15 led to a sharply decrease of CO2 adsorption capacity, indicating the necessity of SO2 removal before aminebased CO2 adsorption (Khatri et al. 2006). Sayari and coworkers (Harlick and Sayari 2006, 2007; Sayari et al. 2005; SernaGuerrero et al. 2008, 2010a, b, c; Belmabkhout et al. 2010; Belmabkhout and Sayari 2010; Sayari and Belmabkhout 2010) developed pore-expanded MCM-41 mesoporous silica (PE-MCM-41) grafted with amine. The DAEAPTS-grafted PE-MCM-41 support with aminosilane loading of 5.98 mmol (N)/g showed an adsorption capacity of 2.05 mmol/g at 298 K and 1.0 atm for a dry 5 % CO2 in N2 feed mixture (Harlick and Sayari 2006). The amine surface density of the sorbent had a strong impact on the adsorption capacity. However, the existence of moisture did not significantly improve the performance of the amine-impregnated PE-MCM-41 sorbents. Subsequently, Harlick and Sayari (2007) found that, compared with dry grafting procedure, wet grafting via the co-addition of water at 358 K showed an increase in the total amine content, resulting in a 90 % overall improvement. The sorbent exhibited good stability over 100 cycles with an average working adsorption capacity of 2.28 mmol/g for pure CO2 through regeneration under a vacuum at 343 K (Serna-Guerrero et al. 2010a), while the temperature swing regeneration process was suitable only at >393 K (SernaGuerrero et al. 2010b). In addition to thermal stability, it also showed extremely high selectivity for CO2 over N2 and O2 (Serna-Guerrero et al. 2010b, c; Belmabkhout et al. 2010; Belmabkhout and Sayari 2010). It was also confirmed by Belmabkhout and Sayari (2010) that SO2 has an adverse effect for CO2 capture (Khatri et al. 2006). In addition, this group noted that their sorbent underwent over 700 cycles without any loss of capacity when adsorption and regeneration was carried out using a humid gas with 7.5 % relative humidity at 343 K. Furthermore, experimental data of CO2 uptake as a function of time at temperatures between 298 and 373 K were fit to a series of kinetic models, namely, Lagergren’s pseudo-first- and pseudo-second-order and

CO2 Capture Using Solid Sorbents

2379

Fig. 8 Hyperbranched amino silica (Drese et al. 2009)

Avrami’s kinetic models. The adsorption kinetics of CO2 on amine-functionalized PE-MCM-41 was successfully described using Avrami’s kinetic model with a reaction kinetic order of 1.4, which has been associated with the occurrence of multiple adsorption pathways (Serna-Guerrero and Sayari 2010). Jones and his coworkers developed a covalently tethered hyperbranched aminosilica (HAS) sorbent (Fig. 8) with high amine content capable of capturing CO2 reversibly from flue gas. They also compared it with other covalently supported solid sorbents (Hicks et al. 2008; Drese et al. 2009). HAS was synthesized via a one-step surface polymerization reaction of aziridine monomer inside SBA-15 pores (Drese et al. 2009). The HAS sorbent had an amine loading of 7.0 mmol N/g and CO2 adsorption capacity of 3.08 mmol/g when tested in a packed-bed reactor under a flow of 10 % CO2/90 % argon saturated with water at 298 K. It was stable over 12 cycles with regeneration temperature at 403 K. In another study, Drese et al. (2009) proposed modification of the HAS synthesis conditions, such as the aziridine-to-silica ratio and the solvent to further tune the sorbent’s composition, adsorbent capacity, and kinetics. They found that higher amine loadings contributed to a better adsorption capacity. The comparison of three APTES-grafted mesoporous silica materials, namely, MCM-41 (dp = 3.3), SBA-12 (dp = 3.8), and SBA-15 (dp = 7.1), was made by Zelenak et al. (2008). The sorbent capacity was consistent with the order of pore size and amine surface density, similar to that observed in the amine-impregnated mesoporous silica sorbents. Kim et al. (2008) developed and tested a series of amine-functionalized mesoporous silica sorbents via anionic surfactant-mediated synthesis method for CO2 adsorption at room temperature. As expected, higher amine loading on the mesoporous structure was the governing factor to achieve high CO2 adsorption.

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Table 8 lists the CO2 adsorption capacity of various amine-grafted adsorbents. Although the functionalization of mesoporous silicas with amine functional groups significantly enhances the CO2 adsorption capacity of silica substrate, the reported equilibrium CO2 adsorption capacities are not as high as those reported with amineimpregnated mesoporous silicas. Moreover, the low thermal stability of mesoporous silicas, in the presence of water vapor at elevated temperature, is still one of the major concerns.

Metal–Organic Frameworks MOFs are network solids composed of metal ion or metal cluster vertices and organic linkers. The ability to freely incorporate and vary organic linkers in MOFs translates to abundant options to control pore shape, pore size, and the chemical potential of the adsorbing surfaces and, consequently, their capacity, selectivity, and kinetics. MOFs have two important features: (i) their syntheses can be modular, and (ii) the solids are crystalline. Because the bonding (coordinate covalent) is weaker than those in metal oxides, solvated pores are not sure to necessarily exist if the solvent is removed. Indeed, these compounds can be classified into three generations due to this fact: first generation, those that collapse irreversibly and are not porous; second generation, those that retain their structures and show reversible gas sorption isotherms; third generation, a category where the material behaves more like a sponge and changes structure reversibly with guest sorption (Kitagawa et al. 2004). Many of the MOFs show large CO2 adsorption capacities at pressures at and above 1 bar, due to their high surface areas. However, the adsorption capacities at lower CO2 pressures are often not directly reported, and these have been carefully estimated for CO2 (0.15 bar) and N2 (0.75 bar) and are listed in Table 9. Table 9 also lists the calculated selectivity values for CO2 over N2 at 298 K for selected MOFs, using the molar ratio of the CO2 uptake at 0.15 bar and the N2 uptake at 0.75 bar. The direct measurement of multicomponent isotherms, which has not been performed for CO2/N2 mixtures, is necessary in order to evaluate the accuracy of selectivity factors predicted from single-component isotherms and ideal adsorbed solution theory (IAST).

Surface Functionalization of MOFs It is essential to tune the affinity of the framework functionalities toward CO2 for optimization of the adsorptive properties. The various kinds of functionalities to enhance CO2 capture performance are discussed in the following sections, including amines, strongly polarizing organic functionalities, and exposed metal cation sites. • Pores Functionalized by Nitrogen Bases. MOFs functionalized with basic nitrogen-containing organic groups have been widely investigated for the CO2 adsorption. The dispersion and electrostatic forces due to the interaction between

Al(OH)(2-amino-BDC)

Cu3(BTC)2 H3[(Cu4Cl)3(BTTri)8(mmen)12] Zn2(ox)(atz)2 Pd(μ-F-pymo-N1,N3)2 Cu3(TATB)2 Co2(adenine)2(CO2CH3)2 Fe3[(Fe4Cl)3(BTT)8(MeOH)4]2 Al(OH)(bpydc)• 0.97Cu(BF4)2 Zn(nbIm)(nIm)

Zn2(dobdc)

NH2-MIL-53 (Al), USO-1-AlA

ZIF-78

CuTATB-60 bio-MOF-11 Fe-BTT

Ni-MOF-74, CPO-27-Ni Co-MOF-74, CPO-27-Co Zn-MOF-74, CPO-27-Zn HKUST-1 mmen-Cu-BTTri

Ni2(dobdc)

Co2(dobdc)

Common names Mg-MOF-74, Mg-CPO-27

Material chemical formula Mg2(dobdc)

Table 9 CO2 and N2 uptake in selected MOFs

0.70

2.64 2.15 1.89 1.48 1.32 1.23 1.20 0.91 0.75

1.73

3.23

CO2 uptake at 0.15 bar (mmol/g) 4.68 4.30 3.80 3.30 3.84

0.29 0.1 0.34 0.12 0.13

0.15 0.07

N2 uptake at 0.75 bar (mmol/g) 0.65 0.5 0.39 0.31 0.76

24 65 18 39 30

101 165

Selectivity 44 52.3 58.8 61.1 30

298

293 298 293 293 298 298 298 298 298

296

298

Temperature (K) 303 313 323 333 298

(continued)

(Aprea et al. 2010) (McDonald et al. 2011) (Vaidhyanathan et al. 2009) (Navarro et al. 2007) (Kim et al. 2011) (An et al. 2010) (Sumida et al. 2010) (Bloch et al. 2010) (Phan et al. 2010; Banerjee et al. 2009) (Arstad et al. 2008b)

(Caskey et al. 2008)

(Dietzel et al. 2009; Yazaydin et al. 2009b) (Yazaydin et al. 2009b)

References (Mason et al. 2011)

CO2 Capture Using Solid Sorbents 2381

Co4(OH)2(doborDC)3

Zn4O(BTB)2 Zn4O(BDC)(BTB)4/3 Zn4O(BDC)3

Zn2(bmbdc)2(4,4’-bpy) Ni2(BDC)2(DABCO) V(IV)O(BDC) Al(OH)(bpydc) Zn20(cbIm)39(OH) Zn4O(NO2-BDC)1.19((C3H5O)2BDC)1.07-((C7H7O)2-BDC)0.74 Zn2(BTetB)(py-CF3)2 Zn(MeIM)2 Zn4O(BDC-NH2)3

MOF-177 UMCM-1 MOF-5, IRMOF-1

ZIF-8 IRMOF-3

USO-2-Ni MIL-47 MOF-253 ZIF-100 MTV-MOF-5EHI

MIL-53(Al), USO-1-A

UMCM-150

Cu3(BPT)2

Zn2(BTetB) Al(OH)(BDC)

USO-2-Ni-A UMC-150(N)2

Common names Cu-BTTri

Material chemical formula H3[(Cu4Cl)3(BTTri)8] Zn2(bpdc)2(bpee) Ni2(2-amino-BDC)2(DABCO) Cu3(BPT(N2))2

Table 9 (continued)

0.11

0.14 0.11 0.11

0.20 0.14 0.14

0.32 0.27 0.25 0.23 0.23 0.23

0.41 0.39

0.41

CO2 uptake at 0.15 bar (mmol/g) 0.66 0.48 0.48 0.43

0.03

0.14

0.02

0.13 0.05

0.11

N2 uptake at 0.75 bar (mmol/g) 0.06 0.01

18

4

50

9 22

19

Selectivity 19 44

298

298 298 298

298 298 298

298 298 298 298 298 298

298 298

298

Temperature (K) 298 298 298 298

(Bae et al. 2010)

(Bae et al. 2009) (Yazaydin et al. 2009b) (Millward and Yaghi 2005; Yazaydin et al. 2009b) (Mason et al. 2011) (Yazaydin et al. 2009b) (Yazaydin et al. 2009b)

(Henke and Fischer 2011) (Arstad et al. 2008b) (Yazaydin et al. 2009b) (Bloch et al. 2010) (Wang et al. 2008b) (Deng et al. 2010)

References (Demessence et al. 2009) (Demessence et al. 2009) (Wu et al. 2010) (Yazaydin et al. 2009b; Park et al. 2011) (Yazaydin et al. 2009b; Park et al. 2011) (Bae et al. 2009) (Arstad et al. 2008b)

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the quadrupole moment of CO2 and localized dipoles generated by heteroatom incorporation are typically responsible for the enhanced CO2 adsorption performance. In some cases, acid–base-type interactions of the lone pair of nitrogen with CO2 have also been observed. The degree to which nitrogen incorporation improves CO2 adsorption depends significantly on the properties of the functional group. Three major classes of nitrogen-functionalized MOFs have been synthesized: heterocycle (i.e., pyridine) derivatives (Stylianou et al. 2011; An and Rosi 2010; An et al. 2010), aromatic amine (i.e., aniline) derivatives (Millward and Yaghi 2005; Zhao et al. 2009a; Arstad et al. 2008a; Stavitski et al. 2011; Couck et al. 2009), and alkylamine (i.e., ethylenediamine) bearing frameworks (McDonald et al. 2011; Demessence et al. 2009; Hwang et al. 2008). • Other Strongly Polarizing Organic Functional Groups. In addition to the nitrogen-based functionalities, organic linkers with heteroatom functional groups (other than amines) have also been examined on the CO2 adsorption behavior (Phan et al. 2010; Banerjee et al. 2008, 2009; Deng et al. 2010). These functional groups contain hydroxy, nitro, cyano, thio, and halide groups, and the degree to which CO2 adsorption capacity is improved in these cases depends primary upon the extent of ligand functionalization and the polarizing strength of the functional group. Generally, strongly polarizing groups will influence CO2 adsorption favorably. • Exposed Metal Cation Sites. The generation of structure types bearing exposed metal cation sites on the pore surface is another way that has been used to enhance the affinity and selectivity of MOFs toward CO2 (Mason et al. 2011; Chui et al. 1999; Bordiga et al. 2007; Vishnyakov et al. 2003; Caskey et al. 2008; Bloch et al. 2010). Cu3(BTC)2 (HKUST-1) is one of the most studied materials featuring such binding sites (Chui et al. 1999). It shows a cubic, twisted boracite topology constructed from dinuclear Cu2+ paddlewheel units and triangular 1,3,5-benzenetricarboxylate linkers. The as-synthesized form of the framework has bound solvent molecules on the axial coordination sites of each Cu2+ metal center, which can be subsequently removed in vacuo at elevated temperatures to create open binding sites for guest molecules. The open metal cation sites serve as charge-dense binding sites for CO2, which is adsorbed more strongly at these sites due to its greater quadrupole moment and polarizability.

Application for MOFs in Harsh Environment Understanding the effects of the contaminants (water vapor, SO2, NOx, et al.) is critical to properly evaluate MOFs in a realistic CO2 capture process. Here, we discuss a number of researches that have aimed to study the performance of MOFs under more realistic conditions. • Stability to Water Vapor. Although partial dehydration of the effluent may be possible, it is costly and most likely not feasible on a large scale to dry the gas completely prior to adsorbing CO2 (Granite and Pennline 2002; Lee and Sircar 2008). In evaluating MOFs for applications in CO2 capture processes, it is significant to consider not only the stability of the framework to water vapor but also the effect of water vapor on the adsorption of CO2.

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Regarding water stability, the metal–ligand bond is typically the weakest point of a MOF, and hydrolysis can cause the displacement of bound ligands and collapse of the framework structure (Low et al. 2009). This was first observed in MOF-5, which is water sensitive and begins to lose crystallinity when exposed to small amounts of water vapor. It was found that the basic zinc acetate clusters characteristic of most zinc carboxylate MOFs, such as MOF-177 and the IRMOF series, are most susceptible to hydrolysis (Cychosz and Matzger 2010). The trinuclear chromium clusters found in many of the MIL series of frameworks are the most stable, while the copperpaddlewheel carboxylate clusters found in HKUST-1 exhibit intermediate stability. One way to increase the water stability of MOFs is to use azolate-based linkers rather than the typical carboxylate linkers (Demessence et al. 2009). The azolate linkers can bind metals with a similar geometry to carboxylate ligands, but their greater basicity typically results in stronger M–N bonds and greater thermal and chemical stability. The relative M–N bond strengths can be predicted based on the pKa values associated with the deprotonation of the free ligand. Therefore, stability typically decreases with the pKa: pyrazole (pKa = 14.4) linkers exhibit the greatest stability, imidazole (pKa = 10.0) and triazole (pKa = 9.3) are intermediate, and tetrazole (pKa = 4.6) linkers are the most labile (Fig. 9). An alternative strategy for increasing the metal–ligand bond strength in MOFs is through the use of trior tetravalent metal cations (Low et al. 2009). Generally, frameworks containing Cr3+, Al3+, Fe3+, and Zr4+ cations exhibit a high degree of stability in water. Specifically, MIL-53 (M(OH)(BDC), M = Cr3+, Fe3+, Al3+) is a flexible framework that expands or contracts based on the absence or presence of water (Serre et al. 2002; Whitfield et al. 2005; Loiseau et al. 2004). The overall framework scaffold remains intact upon repeated exposure to water, due to the reversibility of the structural transition. MIL-100 and MIL-101 are rigid trivalent frameworks built from trinuclear metallic clusters that have shown a high stability in both boiling water and steam. On the contrary, the zirconium(IV)-based UiO-66, which contains extremely robust Zr6O4(OH)4(CO2)12 cluster units (Fig. 10), exhibits their high solubility in water (Cavka et al. 2008). There have been several researches of MOF stability in liquid water, but few regarding different levels of humidity. HKUST-1 was initially focused on understanding the effect of water on CO2 capture in MOFs. The effect of water coordination on the CO2 adsorption performance of HKUST-1 was tested (Yazaydin et al. 2009a). Near 5 mmol/g of CO2 was adsorbed for the dehydrated form, compared with less than 1 mmol/g at 1 bar in the fully hydrated form. This is in agreement with a similar research, which found that HKUST-1 shows a decrease in CO2 uptake to about 75 % of its original value and a concurrent loss of some crystallinity after exposure to 30 % relative humidity (Liu et al. 2010). In a similar study, CO2 adsorption isotherms were measured at different water loadings for HKUST-1 and Ni2(dobdc) (Liu et al. 2010). Both MOFs retained some adsorption capacity for CO2 at low water loadings but exhibited essentially no capacity above 70 % relative humidity. Significantly, water adsorption caused a much faster decrease in CO2 adsorption for zeolites 5A and NaX than for either MOF.

CO2 Capture Using Solid Sorbents

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Fig. 9 The general trend of increasing pKa for ligands built from carboxylic acids, tetrazoles, triazoles, and pyrazoles. The metal–ligand bond is expected to be stronger as the pKa increases (Sumida et al. 2012)

Fig. 10 A portion of the crystal structure of the high-stability metal–organic framework UiO-66 (Cavka et al. 2008). Yellow, gray, and red spheres represent Zr, C, and O atoms, respectively. H atoms are omitted for clarity

In order to evaluate their CO2/N2 separation performance, the effects of water vapor on the performance of the M2(dobdc) (M = Zn, Ni, Co, and Mg) series of MOFs were studied (Fig. 11) (Kizzie et al. 2011). Although Mg2(dobdc) has the highest reported adsorption capacity for CO2 at low pressures, it performed the worst out of the series with a recovery of only 16 % of its initial capacity after regeneration. Ni2(dobdc) and Co2(dobdc) performed far better with recoveries of

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Fig. 11 Comparison of the flow-through CO2 capacities, as determined from breakthrough experiments using a 5:1 N2/CO2 mixture, for pristine M2(dobdc) and regenerated M2(dobdc) after exposure to 70 % RH (Kizzie et al. 2011)

61 % and 85 % of their initial CO2 capacity, respectively. This is in consistent with a similar study that found Ni2(dobdc) could maintain its CO2 capacity after steam conditioning and long-term storage, while Mg2(dobdc) suffers a significant loss in capacity (Liu et al. 2011). Some flexible MOFs exhibit promising CO2 adsorption properties in the existence of water vapor (Cheng et al. 2009). In one report, water induced structural changes in MIL-53 that promoted a higher selectivity for CO2 over CH4 (Llewellyn et al. 2006). The breakthrough CO2 adsorption of the flexible framework NH2-MIL53(Al) in the presence of 5 % water vapor was also investigated (Stavitski et al. 2011). Interestingly, CO2 is selectively retained by the framework even in the presence of water. While the abovementioned experiments are crucial for the initial assessment of MOFs for CO2 capture, multicomponent adsorption isotherms are of high priority for evaluating and understanding the performance under conditions likely to be encountered in an actual capture system (Keskin et al. 2010). • Other Minor Components. The exact amount of each species present in actual gas varies based on the specific configuration of a given plant. Particularly, in order to research the influence of flue gas contaminants, MIL-101(Cr) was selected as the focal point by Liu (Liu et al. 2013). CO2 adsorption capacity of MIL-101(Cr) was able to maintain a high level of performance in trace gas-contaminated environments as well as after multiple cycles of adsorption and mild-condition regeneration. The addition of H2O, SO2, and NO to a 10 vol. % CO2/N2 feed flow was found to have only a minor effect on adsorption capacity. Under feed flow conditions of 10 vol.% CO2, 100 ppm SO2, 100 ppm NO, and 10 % RH, MIL-101(Cr) preserved greater than 95 % of its adsorption capacity after 5 cycles of adsorption/desorption.

CO2 Capture Using Solid Sorbents

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Regenerable Alkali-Metal Carbonate-Based Sorbents Due to the low operating temperature ( AC > vermiculite > silica gel. To identify the best sorbent support system, some researchers (Lee et al. 2006a; Lee and Kim 2007) have prepared several K2CO3-based sorbents by impregnating it on various supports, such as AC, TiO2, Al2O3, MgO, SiO2, and zeolites. CO2 adsorption capacities of K2CO3/AC, K2CO3/TiO2, K2CO3/MgO, and K2CO3/Al2O3 (with an active phase loading of 30 wt%) were 2.0, 1.9, 2.7, and 1.9 mmol/g, respectively. However, the CO2 adsorption capacities of K2CO3/Al2O3 and K2CO3/ MgO decreased after regeneration at 473 K , because of the formation of KAl (CO3)2(OH)2, K2Mg(CO3)2, and K2Mg(CO3)2  4(H2O) phases during carbonation, which were not completely converted to the original K2CO3 phase. However, in the case of K2CO3/AC and K2CO3/TiO2 sorbent systems, regeneration was not a problem in the temperature range of 403–423 K. “KZrI30” (30 wt% K2CO3/ZrO2 sorbent system) was developed in 2009. The CO2 adsorption capacity of the sorbent was 96 % of the theoretical value in the presence of 1 % CO2 and 9 % H2O at 323 K, and it almost remained the same in multicycle operation (Lee et al. 2009). It is reported that the enhanced CO2 capture capacity can be obtained by converting the entire K2CO3  1.5H2O phase to the KHCO3 phase if the sorbents are fully activated with excess water (Lee et al. 2006b). Lee et al. (2011) reported a new regenerable modified Al2O3 support for K2CO3 sorbent for CO2 adsorption below 473 K. The CO2 adsorption capacity of the 48 wt% K2CO3-loaded sorbent was 2.9 mmol/g and did not decrease over five cycles. Zhao et al. (2009b, c) found that K2CO3 with hexagonal crystals has superior carbonation kinetics over monoclinic K2CO3, because of the crystal structure similarities between K2CO3 (hexagonal) and KHCO3. Table 10 summarizes the literature data on alkali carbonate sorbents for CO2 capture. In summary, the high CO2 capture capacity of Na2CO3 (9.43 mmol/g) and K2CO3 (7.23 mmol/g) and favorable carbonation/regeneration temperature between 333 K and 473 K suggest that they are potentially excellent adsorbents for CO2 capture. Moreover, they have the additional advantage of being relatively inexpensive. However, to be commercially viable, the long-term stability and persistence performance of these sorbents under real flue gas conditions of post-combustion applications have yet to be established. The above discussion clearly indicates that several chemisorbents, such as amine-functionalized sorbent (both impregnated and grafted), have shown promise to meet the desired working capacity target in simulated flue gas conditions. Mostly, chemisorbents are found to have higher CO2 selectivity. Aminefunctionalized polymer-based sorbents showed very high adsorption capacity, but

AC, TiO2, Al2O3, MgO, ZrO2, CaO, SiO2, and zeolites

“Sorb KX35” (proprietary recipe)

“Sorb A” (proprietary recipe)

AC, silica gel, activated Al2O3 Modified Al2O3 support KAl(CO3) (OH)2

K2CO3

K2CO3

K2CO3

K2CO3

K2CO3

Ceramic supported sorbents

Support AC, activated coke, and silica Ceramic supported sorbents Ceramic supported sorbents

Na2CO3

Na2CO3

Na2CO3

Active phase K2CO3

35 wt%

Ads.: 333 Reg.: 473 (in N2) Ads.: 343–363 Reg.: 403 (in N2)

Simulated flue gas: (dry basis)12 % CO2 and 88 % N2; 7–30 % moisture Slipstream coal-fired flue gas: 7–9 % CO2 (dry basis), 10–19 % H2O 15 % CO2, 15 % H2O, and N2 balance 1 % CO2, 9 % H2O, and N2 balance

30 wt%

Ads.: 333–373 Reg.: 403–673 (Moisture up to 9 % and balance N2) Ads.: 333–373 Reg.: 393–493 (in N2) Ads.: 343–363 Reg.: g150 (in N2)

~28–48 wt%

~25 wt%

35 wt%

Simulated flue gas: 14.4 % CO2, 5.4 % O2, 10 % H2O, and 70.2 % N2 1 % CO2, 0–11 % H2O, and N2 balance

Gas composition Simulated flue gas and actual flue gas in slipstream Simulated flue gas and actual flue gas 10 % CO2, 12.2 % H2O, and 77.8 % N2

20–50 wt%

35 wt%

wt% active phase 35 wt% in AC 10–40 wt%

Ads.: 323–343 Reg.: 393 (in N2)

Temperature of operation (K) Ads.: 373 Reg.: 423 Ads.: 333–343 Reg.: 393–413 Ads.: 323–343 Reg.: >408 (in N2)

Table 10 Alkali carbonate sorbents for CO2 capture

~2.9 (~48 wt% K2CO3 loading)

(Zhao et al. 2009d) (Lee et al. 2011)

(Park et al. 2009)

CO2 >85 % (capacity not available) ~0.34–1.7

(Yi et al. 2007)

(Lee et al. 2006a, b, 2009; Lee and Kim 2007)

(Lee et al. 2008b)

References (Hayashi et al. 1998) (Samanta et al. 2012) (Seo et al. 2007)

~2.1 (~96 % sorbent efficiency)

~2.6 (~80 % efficiency with a 35 % active phase) ~2.3 (>80 % sorbent efficiency with a 30 % active phase) ~1.1–2.7

Capacity (mmol/g) ~2.1 (Ads. efficiency ~80 %) ~0.5–3.2

CO2 Capture Using Solid Sorbents 2389

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there is not adequate information regarding other selection criteria. Impregnated mesoporous silica sorbents showed improved capacity in the presence of water vapor, whereas grafted silica showed good thermal stability at high temperature (90 % CO2 purity during tests with 200 standard l min1 of flue gas. In addition, the column operated for approximately 7000 adsorption/regeneration cycles with no signs of adsorbent degradation and no loss in process or adsorbent performance. The project partners are now looking at scaling up to pilot-scale testing. Due to the early stages of development, not much information is available currently on the pilot plants; the availability of data on these projects in the future will represent a crucial step toward the deployment of adsorption processes at commercial scale.

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Future Directions Compared to conventional liquid amine processes, solid sorbents for capture CO2 are advantageous in regeneration energy cutback, corrosion prevention, and cost reduction. However, as discussed previously, solid sorbents also have limitations and challenges to be addressed before they can be applied commercially. The following are three recommendations for further research: • Synthesis and modification of the potential solid sorbents to enhance the adsorption performance, such as working capacity, selectivity, and multicycle durability • Comparison of some of the most promising solid sorbents, based on technoeconomic assessment of the system including thermal integration • Performance study of the potential solid sorbents under actual gas conditions using various bed configurations, such as fixed bed, fluidized bed, moving bed, and circulating bed

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Xu XC, Song CS, Miller BG, Scaroni AW (2005a) Influence of moisture on CO2 separation from gas mixture by a nanoporous adsorbent based on polyethylenimine-modified molecular sieve MCM-41. Ind Eng Chem Res 44(21):8113–8119 Xu XC, Song CS, Miller BG, Scaroni AW (2005b) Adsorption separation of carbon dioxide from flue gas of natural gas-fired boiler by a novel nanoporous “molecular basket” adsorbent. Fuel Process Technol 86(14–15):1457–1472 Yang Y, Li H, Chen S, Zhao Y, Li Q (2010) Preparation and characterization of a solid amine adsorbent for capturing CO2 by grafting allylamine onto PAN fiber. Langmuir 26(17):13897–13902 Yazaydin AO, Benin AI, Faheem SA, Jakubczak P, Low JJ, Willis RR, Snurr RQ (2009a) Enhanced CO2 adsorption in metal-organic frameworks via occupation of open-metal sites by coordinated water molecules. Chem Mater 21(8):1425–1430 Yazaydin AO, Snurr RQ, Park TH, Koh K, Liu J, LeVan MD, Benin AI, Jakubczak P, Lanuza M, Galloway DB, Low JJ, Willis RR (2009b) Screening of metal-organic frameworks for carbon dioxide capture from flue gas using a combined experimental and modeling approach. J Am Chem Soc 131(51):18198–18199 Ye Q, Jiang JQ, Wang CX, Liu YM, Pan H, Shi Y (2012) Adsorption of low-concentration carbon dioxide on amine-modified carbon nanotubes at ambient temperature. Energy Fuel 26 (4):2497–2504 Yi CK, Jo SH, Seo Y, Lee JB, Ryu CK (2007) Continuous operation of the potassium-based dry sorbent CO2 capture process with two fluidized-bed reactors. Int J Greenhouse Gas Control 1 (1):31–36 Yong Z, Mata V, Rodrigues AE (2002) Adsorption of carbon dioxide at high temperature – a review. Sep Purif Technol 26(2–3):195–205 Yue MB, Chun Y, Cao Y, Dong X, Zhu JH (2006) CO2 capture by As-prepared SBA-15 with an occluded organic template. Adv Funct Mater 16(13):1717–1722 Yue MB, Sun LB, Cao Y, Wang Y, Wang ZJ, Zhu JH (2008a) Efficient CO2 capturer derived from as-synthesized MCM-41 modified with amine. Chem Eur J 14(11):3442–3451 Yue MB, Sun LB, Cao Y, Wang ZJ, Wang Y, Yu Q, Zhu JH (2008b) Promoting the CO2 adsorption in the amine-containing SBA-15 by hydroxyl group. Microporous Mesoporous Mater 114(1–3):74–81 Zelenak V, Badanicova M, Halamova D, Cejka J, Zukal A, Murafa N, Goerigk G (2008) Aminemodified ordered mesoporous silica: effect of pore size on carbon dioxide capture. Chem Eng J 144(2):336–342 Zhang YZ, Maroto-Valer MM, Zhong Z (2004) Microporous activated carbons produced from unburned carbon in fly ash and their application for CO2 capture. Abstr Pap Am Chem Soc 227: U1090 Zhang J, Singh R, Webley PA (2008a) Alkali and alkaline-earth cation exchanged chabazite zeolites for adsorption based CO2 capture. Microporous Mesoporous Mater 111(1–3):478–487 Zhang J, Webley PA, Xiao P (2008b) Effect of process parameters on power requirements of vacuum swing adsorption technology for CO2 capture from flue gas. Energy Convers Manage 49(2):346–356 Zhao ZX, Li Z, Lin YS (2009a) Adsorption and diffusion of carbon dioxide on metal-organic framework (MOF-5). Ind Eng Chem Res 48(22):10015–10020 Zhao CW, Chen XP, Zhao CS, Liu YK (2009b) Carbonation and hydration characteristics of dry potassium-based sorbents for CO(2) capture. Energy Fuel 23:1766–1769 Zhao CW, Chen XP, Zhao CS (2009c) Effect of crystal structure on CO2 capture characteristics of dry potassium-based sorbents. Chemosphere 75(10):1401–1404 Zhao CW, Chen XP, Zhao CS (2009d) CO2 absorption using dry potassium-based sorbents with different supports. Energy Fuel 23:4683–4687 Zhao A, Samanta A, Sarkar P, Gupta R (2013) Carbon dioxide adsorption on amine-impregnated mesoporous SBA-15 sorbents: experimental and kinetics study. Ind Eng Chem Res 52(19):6480–6491

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CO2 Capture by Membrane Teruhiko Kai and Shuhong Duan

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CO2-Separation Membrane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Principle of Membrane Gas Separation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . An Overview in the Development of CO2 Membrane Separation Material . . . . . . . . . . . . . . Membrane Module Design and Manufacturing for CO2 Membrane Separation . . . . . . . . . Demonstration (Field Test) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary and Future Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Among various CO2-capture technologies, membrane separation is considered as one of the promising solutions because of its energy efficiency and operation simplicity. Many research and development are conducted for the (1) CO2/N2 (CO2 separation from flue gas), (2) CO2/CH4 (CO2 separation from natural gas), and (3) CO2/H2 (CO2 separation from integrated gasification combined cycle (IGCC) processes). In this section, recent research and development of various types of membranes (polymeric membranes, inorganic membranes, ionic liquid membranes, facilitated transport membranes) for these applications are reviewed, as well as future prospects of membrane separation technologies.

T. Kai (*) • S. Duan Research Institute of Innovative Technology for the Earth (RITE), Kizugawa-shi, Kyoto, Japan e-mail: [email protected]; [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_84

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Introduction Carbon dioxide (CO2) capture and storage (CCS) is generally considered as an option for climate change mitigation. There are three principal pathways to capture CO2 from large emission sources: (1) CO2/N2 (CO2 separation from flue gas), (2) CO2/CH4 (CO2 separation from natural gas), and (3) CO2/H2 (CO2 separation from integrated gasification combined cycle (IGCC) processes). For practical application of the CCS technology, cost-effective methods for CO2 capture are required. Many studies have focused on the development of effective CO2-capture and CO2-separation technologies. Among them, membrane separation is one of the promising solutions because of its energy efficiency and operation simplicity. In the case of CO2 separation from flue gas, more than half of the cost of membrane separation goes toward powering the vacuum pump to evacuate the permeate side of the membrane. In addition, the costs of the membrane module and piping are high because the pressure ratio between the feed and the permeate side is low, and a large membrane area is needed. Therefore, high CO2 permeability is more important than high selectivity to reduce the cost of the membrane modules. On the other hand, in the case of CO2 separation in IGCC processes, a significant reduction in the CO2-capture cost is expected via the use of membrane technology, because a vacuum pump is not needed for high-pressure gas separations. In this case, both CO2 permeability and CO2/H2 selectivity are important to separate CO2 effectively. A schematic diagram of the IGCC process with membrane separation is shown in Fig. 1. Coal is gasified into synthesis gas and is then converted into H2 and CO2 via the water-gas shift reaction. Here, the gas composition is roughly 60 % H2 and 40 % CO2 at pressure of 2–4 MPa. Therefore, it is expected that membrane separation can reduce the cost of CO2 capture from IGCC. However, it is very difficult to separate CO2 from H2, which has a smaller molecular size. Therefore, it is very important to develop CO2-selective membranes with high CO2/H2 selectivity. In this section, research and development on CO2-selective membranes using various types of materials is reviewed.

CO2-Separation Membrane Principle of Membrane Gas Separation The early membrane separations were osmosis described by Nollet in 1748, electroosmosis described by Reuss in 1803, and dialysis described by Graham in 1861. These observations laid the scientific milestone of the beginning of membrane separation (Mulder 1996). Research on membrane gas separation using O2, N2, CO2, CH4, SO2, etc. started around 170 years ago. However, the application of membrane gas separation started relatively recently. In 1979, Monsanto Company in the United States developed membrane modules for O2/N2 separation

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Fig. 1 Schematic diagram of IGCC with CO2 capture

(Nakagama 1989). Membranes were known to have the potential to separate gas mixtures long before 1960, but the technology to fabricate high-performance membranes and modules economically was lacking. The development of high-flux asymmetric membranes and large-surface-area membrane modules for reverse osmosis applications occurred in the late 1960s and early 1970s. The innovative concept of high-flux asymmetric membranes was reported and prepared by Loeb and Sourirajan in 1961 initially for reverse osmosis and then adapted to gas separation, as shown in Fig. 2 (So et al. 1973). An acetone solution of 20 % (w/v) cellulose acetate was cast on a glass plate and dried for about 2 min for forming the surface dense layer and then immersed in water. Phase separation of water and acetone resulted in pore formation in the inner membrane. Hence, asymmetric membrane with porous layer and skin dense layer was prepared, and high flux was obtained. Milestones in the development of membrane gas separation are shown in Fig. 3 (Adapted from (Baker 2002; Li et al. 2006; Ismail and David 2001)). It is considered that the first plant with polysulfone hollow fiber membranes for gas separation was performed by Permea PRISM ® membranes in 1980 for H2/N2 separation. The first plant for CO2/CH4 separation with cellulose triacetate membranes was produced by Separex in 1982. The first commercial vapor separation plants were installed by MTR, GKSS, and Nitto Denko in 1988. The largest membrane plant for natural gas processing (CO2/CH4 separation) was installed in Pakistan in 1994 with spiral wound modules, which was a clear example of the easy scale-up of membrane technology. LTA zeolite membranes were commercialized by MES for dehydration in 1997. The development of membrane materials was investigated from conventional polymers to nanoporous materials (zeolite, carbon, silica, MOF, TR polymer, etc.). With the development of industry, separation of carbon dioxide from gas mixture has become very important. CO2 gas separation can be used for many industrial

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Fig. 2 Diagram of high-flux asymmetric membranes prepared by Loeb and Sourirajan (Preparation of asymmetric 1973). (a) Diagram of membrane preparation. (b) Loeb and Sourirajan anisotropic phase separation membrane

fields, such as natural gas or land fill gas recovery process, enhanced oil recovery (EOR), upgrading of methane (CO2/CH4 separation) generated by the decomposition of biological wastes, and integrated gasification combined cycle (IGCC) processes (CO2/H2). And, CO2 membrane separation will play an important role in CCS. The membrane can be considered as a permselective barrier or interface between two phases as shown in Fig. 4a. Phase 1 is usually considered as the feed or upstream side phase while phase 2 is considered as the permeate side or downstream side phase. The membrane has the ability to transport one component from

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2409 1850

1. Graham’s Law of diffusion

ª

1950

3. Loeb and Sourirajan make the first anisotropic membrane 1961

1960

2. van Amerongen, Barrer make first systematic permeability measurements 4. Spiral-wound and hollow-fiber modules developed for reverse osmosis

1970 1980 5. Permea PRISM® membranes Introduced 1980

6. Generon produces first N2/air separation system 1982 7. Dried CA membranes for CO2/CH4 natural gas separations Separex, Cynara, GMS

8. Advanced membrane materials for O2/N2; H2/N2 and H2/CH4 separation launched by Ube, Medal, Generon 1987 1990 10. Medal polyimide hollow-fiberf membrane for CO2/CH4 separation Installed 1994

9. First commercial vapor separation plants installed by MTR, GKSS, Nitto Denko 1988 11. First propylene/N2 separation plants installed 1996

2000 12. 1997 LTA zeolite membranes commercialized by MES for dehydration 2010

13. From polyimide to nano-porous membranes (Zeolite, Carbon, Silica, MOF, TR polymer etc.)

Fig. 3 Milestones in the development of membrane gas separation (Baker 2002; Li et al. 2006; Ismail and David 2001)

the feed mixture more readily than any other component or components because of differences in physical or chemical properties between the membrane and the permeating components. Transport through the membrane takes place as a result of a driving force acting on the components in the feed. In many cases, the permeation rate through the membrane is proportional to the driving force. The two phases divided by a membrane are different for various membrane separation processes as depicted in Fig. 4b. Driving force can be gradients in the pressure, concentration, and temperature. Membrane separation processes can be classified according to their driving force as in Table 1. Most of membranes used for gas separation have been nonporous polymer membranes, such as cellulose acetate (Yan 1996), silicone rubber polysulfone (Hao Jihao and Wang Shichang 1998; Ismail and Shilton 1998; Borisov et al. 1997), and polyimide (Li and Teo 1998; Thundyil et al. 1999; Staudt-Bickel and Koros 1999). Recently, microporous inorganic membranes, such as zeolite membranes (Wang et al. 1998; Poshusta et al. 1999; Aoki et al. 1998), nanoporous carbon membranes (Hernandez-Huesca et al. 1999), and ceramic membranes (Paranjape et al. 1998), have also been developed. Mechanism of membrane gas separation has been proposed depending on the properties of both the permeant and the membranes, as shown in Fig. 5. Different mechanisms may be involved in the transport of gases across a porous membrane included Poiseuille flow, Knudsen diffusion, and the molecular sieve effect as shown in Fig. 5(1). When membrane has pore sizes much larger than the dimension of gas molecules, Poiseuille flow takes place. Knudsen diffusion is the predominant transport mechanism in small pores at low pressures and high

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Fig. 4 Schematic drawings of membrane separation. (a) Two phases separated by a membrane with driving force such as ΔP, ΔC, ΔT, and ΔE. (b) Schematic representation of phases divided by a membrane. L liquid, G gas Table 1 Driving force for various membrane separation processes. L liquid, G gas Driving force 1. Pressure

Phase 1 L

Phase 2 L

2. Partial pressure

G G L L L L L

G G G L L L L

3. Concentration 4. Electrical potential

Membrane process Reverse osmosis Nanofiltration Ultrafiltration Microfiltration Gas separation Vapor permeation Pervaporation Dialysis Membrane extraction Electrodialysis Membrane Electrodialysis

temperatures. When membrane has pore sizes close to the dimension of gas molecules, the molecular sieve will be effective. In some cases, affinity between gas molecules (e.g., CO2) and membrane materials can play an important role in high separation performance.

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Fig. 5 Mechanism of membrane gas separation. (1) Mechanisms for gas flow though a microporous membrane. (2) Mechanisms for gas flow though a nonporous polymeric membrane

The solution–diffusion model is used for transport mechanism for the permeation of gases through nonporous polymeric membranes, as shown in Fig. 5(2). The solution–diffusion model describes the transport of gases through a membrane as a three-step process: (a) preferential sorption of the gas into the membrane at the feed side, (b) diffusion through the membrane due to an applied concentration gradient (e.g., partial pressure), and (c) desorption of the gas from the permeate side of the membrane.

Gas Transport Through Porous Membrane Up to now a lot of work has been done in modeling the gas transport through membranes including porous and nonporous membranes. The models of gas permeation through porous membrane began with a comparison of the mean free path of the gas molecules and the mean membrane pore size. If the mean free path of the gas molecules is very small relative to the pore

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diameter, gas transport takes place by viscous or Poiseuille flow, and no separation is achieved. The volume flux through these pores may be described by the Hagen–Poiseuille equation (Mulder 1996): J¼

er 2 ΔP 8ητl

(1)

where J is the volume flux through the pores, e is the porosity, r is pore radius, ΔP is pressure difference across a membrane of thickness l, η is viscosity, and τ is pore tortuosity. If the mean free path of the gas molecules is much greater than the pore diameter, gas transport takes place by Knudsen flow, and separation is achieved. Mass transfer may be expressed by the following equation (Mulder 1996): J¼

πnr 2 DK ΔP RTτl

(2)

where n is the number of pores and r is the pore radius. Dk, the Knudsen diffusion coefficient, is given by DK ¼ 0:66r

rffiffiffiffiffiffiffiffiffiffi 8RT πMW

(3)

T and Mw are the temperature and molecular weight, respectively. Equations 2 and 3 show that the flux is proportional to the driving force, i.e., the pressure difference (ΔP), across the membrane and inversely proportional to the ratio of the square root of the molecular weights of the gases. If the pore size of membrane used in separation is close to the mean free path of the gas molecules, the transport of gases and vapors falls in the transition between Knudsen and Poiseuille flow. Schofield et al. (1990) developed the transport model of gas and vapor for the transition region between Knudsen and Poiseuille flow in a simple and effective semiempirical relationship. The flux was expressed as follows: J ¼ aPb ΔP

(4)

where a is membrane permeation constant and b is 0 for Knudsen diffusion and 1 for Poiseuille flow.

Gas Transport Through Nonporous Polymeric Membrane The transport of gases through a dense, nonporous membrane is expressed in terms of a solution–diffusion model, as described above (Fig. 5b). The relationship between permeability, solubility, and diffusivity is expressed as follows: PermeabilityðPÞ ¼ SolubilityðSÞ  DiffusivityðDÞ

(5)

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The ability of a membrane to separate two molecules, A and B, is expressed as the ratio of their permeability (the selectivity, α): α ¼ PA =PB

(6)

For a binary gas mixture, the selectivity can also be determined from a molar concentration of the two gases in feed and permeate: α ¼ yð1  xÞ=xð1  yÞ

(7)

where y is the permeate concentration of the fast permeating gas and x is its feed concentration. The simplest way to describe the transport of gases and vapors through nonporous membrane is by Fick’s first law (Mulder 1996): J ¼ D

dc dx

(8)

The flux J of a component through a plane perpendicular to the direction of diffusion is proportional to the concentration gradient dc/dx. The proportionality constant D is called the diffusion coefficient. If it is assumed that the diffusion coefficient is constant, the change in concentration as a function of distance and time is given by Fick’s second law (Mulder 1996): @c @2c ¼ D 2 @t @x

(9)

Gas Transport Through Facilitated Transport Membrane Facilitated transport membranes, a type of liquid membranes, were developed for gas separation with high selectivity, especially at low gas partial pressure. Facilitated transport membranes selectively permeate specific gases (e.g., CO2) by means of a reversible reaction between the gases and the membrane. Other gases such as H2, N2, and CH4 do not react with the membrane and can only permeate by a solution–diffusion mechanism. The model of gas transport through a carrier membrane is described as follows. First, component A molecules form a complex AC with the carrier, and AC diffuses through the membrane. Second, dissolved gas A diffuses across the membrane with normal Fickian diffusion (shown in Fig. 6). The total flux of component A will then be the sum of the two contributions, i.e., JA ¼

 DAC   DA  CA, o  CA, l þ CAC, o  CAC, l l l

(10)

The first term on the right-hand side of Eq. 10 represents permeant diffusion according to Fick’s law, where DA is the diffusion coefficient of the uncomplexed

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Fig. 6 The mechanism of a facilitated transport membrane. (a) The scheme of a facilitated transport membrane. (b) The scheme of a facilitated transport membrane for CO2

component inside the liquid membrane, while CA,o is the concentration of component A just inside the liquid membrane at the feed side and is equal to the solubility of the liquid of A when thermodynamic equilibrium occurs at the interface. The second term represents carrier-mediated diffusion with the flux being proportional to the driving force, which in this case is the concentration difference of complex across the liquid membrane. DAC is the diffusion coefficient of the complex, and CAC,o is the concentration of the complex at the feed side. The following limiting cases can be observed:

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1. CA, o  CAC, o When the concentration of the complex AC is much lower than the concentration of A, the first term, i.e., Fickian diffusion, is rate determining. 2. CA, o  CAC, o When the concentration of the complex AC is much greater than the concentration of A, the second term, i.e., diffusion of the complex, is rate determining. 3. CA, o  CAC, o When the concentration of the complex AC is close to the concentration of A, both Fickian diffusion and the diffusion of the complex are rate determining. Facilitated transport membranes for CO2 separation were originally prepared by impregnating pores of microporous support membranes or polymer matrices with carrier solutions such as amines and alkali metal carbonates, which have chemical affinity to CO2. Figure 6b shows the conceptual diagram of CO2-facilitated transport membranes (Matsuyama et al. 1996). As shown in Fig. 6b, CO2 carrier incorporated membrane can react selectively and reversibly with CO2. The CO2 permeation rate can be facilitated because CO2 carrier of the reaction product can transport through the membrane, in addition to CO2 transport membrane of physical solution–diffusion mechanism. On the other hand, other gases, such as N2, CH4, and H2, transport through the membrane only by solution–diffusion mechanism. As a result, the CO2 selectivity of facilitated transport membranes can be extremely high at low CO2 partial pressures. If amine is used as CO2 carrier, the reaction of carrier and CO2 is expressed as follows:  2CO2 þ 2RNH2 þ H2 O Ð RHNCOOH þ RNHþ 3 þ HCO3

(11)

The weak basic amino group will initiate the reaction. However, considering that amino groups are not consumed during the reversible reactions, they are taking the role of catalysts for the reversible CO2 hydration reactions; the final reactions can therefore be demonstrated with Eq. 12: þNH2

þ  H2 O þ CO2  )*  H þ HCO3

(12)

It is suggested that the high CO2 selectivity and permeability can be obtained by the reversible reaction above.

An Overview in the Development of CO2 Membrane Separation Material Polymeric Membranes Many studies have reported CO2-selective polymer membranes for the separation of CO2/CH4 and CO2/N2 gas mixtures. On the other hand, there are comparatively few polymeric membranes that can be utilized for the selective recovery of CO2

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T. Kai and S. Duan F

F

2

F

F F F

O

O

N

N

O

O

]

O

]3]

F

F F F F F

O

N

N

O

O

]2 O

un-cross-linked polymer

OH

film or hollow-fiber formation

asymmetric hollow-fiber

dense film

Cross-linking

Δ, vacuum F

F

F

F F F

O

O

]N

N

O

O

O

]3]

F

F F F F F

O

N

N

O

O

]2 O

+ O

HO

byproduct O

O

]N

N

O

O F

F

F F F

O

O

H

cross-linked polymer

F

O

]3]

O

O

N

N

O

O

F

F F F F F

O

]2

Fig. 7 Illustration showing the cross-linked polyimide (propane-diol monoesterified) membrane formation (Omole et al. 2010)

over H2. Polymeric membranes made from glassy polymers such as cellulose acetate and polyimide have exhibited practical use in selective CO2 separation from CO2/CH4 gas mixtures. However, CO2/CH4 separation greatly decreases under high CO2 partial pressures due to CO2-induced plasticization. Koros et al. reported that cross-linked polyimide membranes exhibited enhanced resistance to CO2 plasticization, as shown in Figs. 7 and 8 (Omole et al. 2010).

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CO2/CH4 Separation Factor

50.0

40.0

30.0

20.0

un-cross-linked cross-linked (150 C)

10.0

cross-linked (200 C) cross-linked (250 C)

0.0 0

200

400

600

800

1000

Feed pressure (psia) Fig. 8 Effect of cross-linking temperature on CO2/CH4 separation factor (Omole et al. 2010)

The structure of polyimide consisted of the following three monomer units: (1) 4, 40 -(hexafluoroisopropylidene) diphthalic anhydride (6FDA), (2) 2,4,6-trimethyl1,3-diaminobenzene (DAM), and (3) 3,5-diaminobenzoic acid (DABA), in the ratio 5:3:2. The DABA groups were used as sites for cross-linking at 150, 200, and 250  C for 2 h under vacuum, as shown in Fig. 2. The effect of cross-linking temperature on CO2/CH4 separation factor using a mixed-gas feed with 50 % CO2 was shown in Fig. 3. 200 and 250  C cross-linked fibers showed higher selectivities than the un-cross-linked and 150  C cross-linked counterparts. Due to scale-up considerations for using lower cost conventional ovens, lower temperatures are referred commercially. Considering these aspects, 200  C cross-linking temperature would be useful to pursue. Robeson reported that there was a trade-off relationship between separation factor and the gas permeability for polymeric membranes. This upper-bound relationship for CO2/CH4 is shown in Fig. 9 (Robeson 2008). In recent years, the development of new membrane materials has been studied to produce both high permeability and high selectivity. Among of them, thermally rearranged polymers (TR polymers) are a novel polymer material in which the molecular sizes of the interchains are controlled by heat treatment. The outstanding performance of TR polymer membrane results from largely unique cavity formation with the size of angstrom order during thermal molecular rearrangement (Park et al. 2007). In the case of TR polymer, free-volume structure and distribution are suitable for gas transport (formation of cavity with size, distribution, and shape for a preferred CO2 transport) in contrast with conventional polymers. For comparative investigation, mixed-gas separation of CO2/CH4 by TR polymer and carbon molecular sieve

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T. Kai and S. Duan 104

Present Upper Bound

1000

ALPHA CO2/CH4

Prior Upper Bound

TR polymers

100

10

1 0.0001

0.01

1

100

104

P(CO2) Barrers

Fig. 9 Upper-bound correlation for CO2/CH4 separation (Robeson 2008)

membranes derived from a polyimide of intrinsic micro porosity was reported. High CO2/CH4 separations by TR polymer membranes were maintained under high pressures because of its high free volume and enhanced resistance to plasticization (Swaidan et al. 2013). Chung et al. reported that thickness, durability, and plasticization of membrane with TR polymer from ortho-functional polyimide based on 2,20 -bis-(3,4-dicarboxyphenyl) hexafluoropropane dianhydride (6FDA) and 3,3-dihydroxy-4,4-diamino-biphenyl (HAB) for CO2 permeability was studied. Long-term exposure of the TR films to CO2 showed that the CO2 permeability of the thick TR films (15–20 μm) did not show significant decline at 32 atm for over 500 h (Wang et al. 2014). Lee et al. reported on physical properties, cavity size, and transport behavior of TR-PBO membranes by precursor hydroxypolyimide (Calle et al. 2013). Freeman et al. investigated on TR poly(benzoxazole)/polyimideblended membranes for CO2/CH4 separation and showed that blending a-hydroxypolyimides with non-TR polyimides was a feasible strategy to produce films with improved mechanical strength that retain the high gas separation performance of the TR polymer alone (Scholes et al. 2014a, b). It was also reported that MOP (microporous organic polymer) membranes with high affinity to CO2 displayed excellent CO2 separation, the same as TR polymer (Du et al. 2011; Xu and Hedin 2014). In addition, the directions for new membrane material design have been investigated to obtain high CO2 gas selectivity and permeability. And more

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research and investigation are carried out actively to introduce the molecular sieve ability with angstrom order size (Gin and Noble 2011; Hudiono et al. 2011). Poly(ethylene glycol) (PEG) has a high physical affinity toward CO2 and was expected to be a viable CO2-separation membrane material. However, pure PEG exhibited very low CO2 permeability, owing to its crystallization. Freeman et al. developed cross-linked PEG membranes in order to prevent this crystallization. The cross-linked PEG membranes exhibited favorable interactions with CO2, which enhanced the solubility of CO2 over that of H2 and showed a CO2/H2 selectivity of about 10 at 35  C and 25 at 20  C (Lin et al. 2006). Wessling et al. developed a PEG block copolymer membrane and obtained a CO2/H2 selectivity of 10 at 35  C (Husken et al. 2010). Peinemann et al. also developed a PEG block copolymer with CO2 affinity and obtained a CO2/H2 selectivity of 10.8 at 30  C (Car et al. 2008). As stated in introduction, CO2 separation from flue gas using membranes is performed under low pressure ratio between the feed and the permeate side, and the improvement in CO2 permeability is important in terms of flowering the system cost and membrane area. It is also important to improve the separation process. Merkel et al. proposed a new system to obtain a CO2 partial pressure difference between the feed and the permeate side using air as a sweep gas to reduce the energy cost. In addition, a membrane module with high CO2 permeability (Polaris TM membrane) was developed (Merkel et al. 2010). Huang et al. investigated on pressure ratio between feed side and permeate side and its impact on membrane gas separation processes. They reported that the optimum membrane processes may not correlate with the highest selectivity because of limited pressure ratio (Huang et al. 2014). Ha¨gg et al. reported similarly that the optimization of the operating conditions is important for membrane gas separation process, by investigating the influences of the operating parameters such as temperature, pressure, and stage-cut using the carbon membrane (He and Hagg 2011).

Inorganic Membranes As for inorganic membranes, zeolite membranes and carbon membranes, among others, have been reported for CO2 separation. Inorganic membranes have appropriate-sized pores that can act as molecular sieves to separate gas molecules by their effective size. In addition, inorganic membranes with strong CO2 affinities show high CO2 selectivity over N2 and CH4. Noble et al. reported that zeolite SAPO-34 membrane showed a high CO2/CH4 separation performance (Zhang et al. 2010). Zhou et al. reported preparation for silica MFI membranes with a thickness of 0.5 μm on analumina support membrane. The membrane showed a separation selectivity of 109 for CO2/H2 mixtures and a CO2 permeance of 51  107 mol m2 s1 Pa1 at 35  C (Zhou et al. 2014). Sub-nanoporous carbon membranes are prepared through precursor polymer thermolysis and carbonization in several hundred degrees or more by heat treating. Polyimide, polyacrylonitrile, cellulose, phenolic resin, etc. are used as precursors. Carbon membranes prepared from a precursor polyimide based on 6FDA-mPDA/ DABA (3:2) by thermolysis under 550  C showed CO2 permeability as high as

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14750 Barrer with CO2/CH4 selectivity of approximately 52. Even 800  C pyrolyzed carbon membranes still showed high CO2 permeability of 2610 Barrer with high CO2/CH4 selectivity of approximately 118 (Qiu et al. 2014). Inorganic membranes show high gas separation performance and high stability and durability at high temperature. On the other hand, they have the disadvantages of high membrane cost, compared with polymeric ones. To combine the benefits of both polymeric and inorganic materials, mixed-matrix membranes (MMMs), a type of organic/inorganic composite membranes, have also been studied. Many studies have been reported on gas separation membranes using ZIF (zeolitic imidazolate frameworks), a type of MOF (metal-organic framework), as inorganic nanoparticles. Bae et al. reported that MMMs prepared by incorporating MOF (ZIF-90) into a polymeric matrix showed a high CO2/CH4 separation performance (Bae et al. 2010). MMMs prepared by incorporating ZIF-108 nanoparticles into polysulfone (PSf) matrix showed CO2/N2 selectivity of 227 (Ban et al. 2014). Ha¨gg et al. developed ZIF-8/PEBAX-2533 MMMs for CO2 capture. MMMs from PEBAX-2533/ZIF8 with 25 % ZIF-8 loading showed CO2 permeability of 1129 Barrer with CO2/N2 selectivity of 31 (Nafisi and Hagg 2014). Because CO2 separation by inorganic membranes is mainly carried out via molecular sieving, a high selectivity is obtained for CO2/CH4 and CO2/N2 separation but generally not for CO2/H2 separation.

Ionic Liquid Membranes Ionic liquid (IL) membranes have received increasing interest and have been studied in recent years because of their low vapor pressures and stability at high temperatures. Polymerized IL membranes were prepared for the separation of CO2/ N2, CO2/CH4, etc. by Noble et al. (Bara et al. 2007). Amino-containing ILs were investigated for the separation of CO2/H2 by Myers et al. (2008), and a CO2/H2 selectivity of 15 was obtained at 85  C. Matsuyama et al. reported aminocontaining IL membranes for the separation of CO2/CH4, and the membrane showed constant separation abilities for 260 days (αCO2/CH4 = ca. 60) (Hanioka et al. 2008). Nagai et al. reported impregnating IL and ZSM-5 into PI matrix for improvement of IL composite membrane stability. The resulting membrane exhibited CO2/CH4 selectivity of 31 with CO2 permeability of 4509 Barrer (Shindo et al. 2014). IL monomer was polymerized to improve pressure durability of IL membranes by Wessling et al. The resulting membrane showed CO2/CH4 selectivity of 22 with CO2 permeability of 18 Barrer at 40  C, CO2 (50 vol.%)/CH4 (50 vol.%) of feed mixed gas under 40 atm total pressure (Simons et al. 2010). Facilitated Transport Membranes Facilitated transport membranes for CO2 separation were originally prepared by impregnating pores of microporous support membranes or polymer matrices with carrier solutions such as amines and alkali metal carbonates, which have chemical affinity to CO2. Figure 10 shows the conceptual diagram of CO2-facilitated transport membranes (Zou and Ho 2006). As shown in Fig. 5, CO2 carrier incorporated membrane can react selectively and reversibly with CO2. The CO2 transport membrane rate can be facilitated because CO2 carrier of the reaction product can transport through the

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Fig. 10 The conceptual diagram of CO2-facilitated transport membrane (Zou and Ho 2006)

membrane, in addition to CO2 transport membrane of physical solution–diffusion mechanism. On the other hand, other gases, such as N2, H2, and CO, transport membrane only by solution–diffusion mechanism. As a result, the CO2 selectivity of facilitated transport membranes can be extremely high at low CO2 partial pressures. Facilitated transport membranes for CO2 separation have been studied since the 1960s. Ward and Robb immobilized an aqueous bicarbonate–carbonate solution into a porous support and obtained a CO2/O2 separation factor of 1500 (Ward and Robb 1967). Immobilized liquid membranes impregnated with carbonate and bicarbonate solutions were studied by Jung and Ihm (1984), Bhave and Sirkar (1986) and Yamaguchi et al. (1996). Apart from carbonate or bicarbonate ions as the reactive carrier, amines were other chemicals that can facilitate CO2 transport. Aqueous solution of diethanolamine (DEA) was used for facilitating CO2 transport (Guha et al. 1990) (Matsuyama et al. 1996). The transport of acid gases through an ion-exchange membrane was facilitated with a diamine carrier (Quinn et al. 1997). The membrane which acted as a fixed carrier membrane for CO2-facilitated transport was prepared by plasma grafting 2-(N, N-dimethyl) aminoethyl methacrylate (Matsuyama et al., 1996) (Neplembroek et al. 1992). The membranes based on the polyelectrolyte, poly(vinylbenzyl trimethyl ammonium fluoride), exhibited high permselective properties for CO2/CH4 (Quinn et al. 1997; Kemperman et al. 1997). Although the immobilized liquid membranes have quite high permselectivity, they have a shortcoming of instability. Some methods were proposed to improve membrane stability under a pressurized condition or in a vacuum. For example, polymer gel was used to retain CO2 carriers in membrane (Neplembroek et al. 1992; Kemperman et al. 1997; Matsumiya et al. 2004, 2005) or the surface of support membrane was treated by chemical method and liquid membrane layer was formed on the pretreated support membrane (Ito et al. 1997), etc. Ho et al. developed facilitated transport membranes by blending amines with poly(vinyl alcohol) (PVA) (Zou and Ho 2006). These membranes showed a CO2/H2 selectivity of 300 at 110  C and 100 at 150  C, as shown in Fig. 11. Matsuyama et al. reported facilitated transport membranes prepared by the immobilization of

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Fig. 11 CO2/H2-separation properties of facilitated transport membranes prepared by blending amines with poly(vinyl alcohol) (PVA) (Zou and Ho 2006)

2,3-diaminopropionic acid and cesium carbonate in a PVA/poly(acrylic acid) copolymer matrix, and the resulting membrane showed a CO2/H2 selectivity of 432 at 160  C, as shown in Fig. 12 (Yegani et al. 2007). Ha¨gg et al. developed a CO2/N2-separation membrane by blending PVA and poly(vinyl amine) (PVAm). The composite membrane with a selective layer thickness of 0.3 μm was prepared by casting a solution of PVA/PVAm on a polysulfone (PSf) support membrane (Sandru et al. 2010). A model of CO2-facilitated transport membrane mechanism was shown in Fig. 13. In this model, the bicarbonate ion is considered as CO2 carrier and plays an important role for CO2 permeation.

CO2 Capture by Membrane

CO2 flux (mol/m2 s)

10−2

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a

10−3 125°C 140°C

10−4 50wt% DAPA

160°C

CO2/N2 selectivity

N2 permeance (mol/m2 s kPa)

CO2 permeance (mol/m2 s kPa)

b 10−4

10−5 10−6

c

10−7

103

d

102

101 100

200

300

400

500

600

Feed gas pressure (kPa) Fig. 12 CO2/N2-separation properties of facilitated transport membranes prepared by the immobilization of 2,3-diaminopropionic acid and cesium carbonate in a PVA/poly(acrylic acid) copolymer matrix (Yegani et al. 2007)

Myers et al. reported that amino-containing IL membrane showed CO2-facilitated transport for dry CO2/H2 mixed-gas separation (Myers et al. 2008). Matsuyama et al. developed amino acid IL-based facilitated transport membranes for CO2 separation. A tetrabutylphosphonium proline as amino acid IL membrane showed

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Feed side N2

CO2carriers fixed on polymer backbone CO2 NH2

CO2 Only by diffusion

H2O Top skin layer of PVAm

Reversible reaction NH3+ H2O

HCO3− CO2

Porous support CO2

N2

Permeate side Fig. 13 CO2-facilitated transport membrane mechanism by bicarbonate (Sandru et al. 2010)

an excellent CO2 permeability of 14,000 Barrer with CO2/N2 selectivity of 100 at 373 K under dry conditions and 10 kPa CO2 partial pressure (Kasahara et al. 2012). CO2 partial pressure and temperature significantly influenced CO2 permeability and CO2/N2 selectivity (Kasahara et al. 2014a, b). Svec et al. developed polymer hybrid CO2-facilitated transport membrane by photopolymerization based on polyaniline and 2-hydroxyethylmethacrylate. The resulting hybrid membranes showed a CO2 permeability of 3460 Barrer with CO2/ CH4 selectivity of 540 under 8.3 kPa CO2 partial pressure (Blinova and Svec 2012). Sirkar et al. reported excellent CO2/N2 selectivity using a viscous and nonvolatile poly(amidoamine) (PAMAM) dendrimer as an immobilized liquid membrane under isobaric and saturated water vapor test conditions (Kovvali et al. 2000). In the integrated coal gasification combined cycles with CO2 capture and storage (IGCC-CCS), CO2-separation membranes will play an important role for reducing CO2-capture costs. In Japan, PAMAM dendrimer/polymer hybrid membranes were developed for CO2 separation from flue gas (CO2/N2) (Duan et al. 2006; Kai et al. 2008) and from IGCC process (CO2/H2) (Taniguchi et al. 2008; Duan et al. 2012; RITE today (annual report 2015).

Membrane Module Design and Manufacturing for CO2 Membrane Separation Industrial membrane plants for gas separation often require hundreds to thousands of square meters of membrane to perform the separation. It is very important to provide a large surface area to deal with large quantity of flue gas or fuel gas.

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Fig. 14 Modular constructions employed for gas separation processes (Sanders et al. 2013)

Hence, it is very important to design and produce membrane modules. There are several ways to economically and efficiently package membranes for high surface area and economical module for gas separation. These packages are called membrane modules. The examples of membrane modules are shown in Fig. 14 (Sanders et al. 2013). 1. Hollow Fiber Membrane Modules A typical hollow fiber bundle contains on the order of 105 hollow fibers which are tightly packed (packing fractions on the order of 50 % are common) with both ends embedded in a thermosetting epoxy polymer (Coker et al. 1998). A hollow fiber bundle would then be housed in a polymeric or metal pressure vessel, depending on the pressure that the system was expected to encounter during operation. Feed gas can be introduced into the bore side or the shell side of a hollow fiber module, depending on the application.

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Fig. 15 Hollow fiber membrane module. (a) Countercurrent flow. (b) Cocurrent flow

Fig. 16 Cross section constructions of spiral wound membrane module for gas separation

Two basic shapes of hollow fiber membrane module are shown in Fig. 15: (a) countercurrent flow and (b) cocurrent flow. Countercurrent shape module has the shell-side feed design with a loop of fibers contained in a pressure vessel. The system is pressurized from the shell side, and the permeate passes through the fiber wall and exits through the open fiber ends. It is easy to make very large membrane areas, thick wall, and small diameter to stand the pressure for used in-gas separation. In cocurrent shape module, fibers are open at both ends, and the feed fluid is circulated through the bore of the fibers. Large diameter is needed to minimize pressure drop (Δp) for in-gas separation at p Pc, penetration of the non-wetting phase occurs. In fact, there are pores (i.e., pore spaces with relatively large diameter forming between particles) and pore throats (i.e., the narrowest point of a tube connecting pores) of various sizes within the target porous medium. Therefore, even if PnwPw > Pc for a certain pore or pore throat diameter, penetration of CO2 (breakthrough) does not occur immediately, and the non-wetting phase is blocked by the next throat of the flow path with a smaller diameter. The first breakthrough occurs when the continuous flow path for the non-wetting phase is formed between both ends of the porous medium. The flow path of the non-wetting phase at this point occupies an insignificant fraction of total pore space (i.e., the water saturation Sw is high). A further increase in the difference of Pnw and Pw enables the penetration through pore throats with a smaller diameter, which results in the expansion of the flow path volume of the non-wetting phase. In contrast, a reduction of the difference between Pnw and Pw after the breakthrough of the non-wetting phase leads to re-imbibition of the wetting phase,

Residual gas saturation

Irreducible water saturation

Fig. 1 Relationship of each Pc term characterizing the sealing performance (Pcen, Pcdis, Pcth, and Pcres) with the Pc–Sw curve

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Capillary pressure, Pc

CO2 Geological Storage

Drainage

Pcres Pcth Pcdis Imbibition

0

Pcen 90

100

Water saturation, Sw (%)

starting with the smallest pores and proceeding successively to larger pores (Hildenbrand et al. 2002). As a result, the connected flow path becomes blocked; the permeability k of the non-wetting phase decreases. Ultimately, the flow path in the largest pore throats is shut off, and the penetration of the non-wetting phase stops. The drainage and imbibition process of the wetting phase within the porous medium presents a PcSw curve (Fig. 1). Generally, the Pc in the imbibition process is smaller than that of the drainage process on the equal Sw. Therefore, the PcSw curve between the two produces large hysteresis.

Definition of Pc On the PcSw curve, the Pc value changes with penetration of the non-wetting phase into the porous medium. However, depending on its processes, various terms are defined to characterize the sealing performance. These terms include the entry pressure Pcen, displacement pressure Pcdis, threshold pressure Pcth, and residual capillary pressure Pcres. Here, Fig. 1 presents their general definitions and relationships with PcSw curve. The Pcen is the pressure when the non-wetting phase first comes in contact with the target porous medium. It is an index of the diameter of pores or maximum pore throat exposed at the porous medium surface. In this case, however, the throat does not need to be connected to the opposite end of the porous medium. The Pcen is easy to identify experimentally, but the structures of pores and pore throats exposed on the surface are dependent on the effects of sample size and heterogeneity. Thus, the physical meaning of measured Pcen is not necessarily clear (Pittman 1992). Based on a breakthrough experiment of mercury in sandstone, limestone, and silty shale rocks, Schowalter (1979) defined the Pc at a mercury saturation of 10 % as the Pcdis. Although these samples had a wide pore throat diameter distribution,

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the non-wetting phase saturation necessary to build connected flow paths was limited to a narrow range of 4.5–17 %. Thus, it is concluded that breakthrough of non-wetting phase occurs in many rocks when Sw is approximately 90 %. The Pcth is a particularly ambiguous measure of sealing performance, and its definition has varied in past research. Generally, it refers to the difference of Pnw and Pw at both ends of porous medium, when building a connected flow path for the non-wetting phase in the porous medium. Experimentally, it is measured as the differential pressure when the non-wetting phase initially penetrates the porous sample. The magnitude of Pcth is defined by the Pc at the maximum pore throat diameter. Katz and Thompson (1986, 1987) considered that the pressure at which mercury forms a connected pathway within the sample is equivalent to the inflection point at which the PcSw curve becomes convex upward and defined this pressure as Pcth. In connection with this, Thomeer (1960) and Swanson (1981) both showed by numerical analysis and experiments, respectively, that a pore system with a good connectivity forms within rocks at the vertex of a hyperbola (i.e., a point where the slope of the tangent is 45 ) obtained when the PcSw curve is expressed in a double logarithmic diagram. Along with Pc in these drainage processes, the Pc in imbibition process is also defined. If the flow path of the non-wetting phase is completely blocked in the imbibition process of the wetting phase, residual pressure difference is generated at both ends of the porous medium and defined as the Pcres (Hildenbrand et al. 2002).

Measurement Methods for Pc Commonly, Pc is measured by mercury intrusion or gas sorption (mainly using nitrogen). The results are then converted to the Pc in the target system. In the former method, a throat diameter of several nm to several hundred μm is the target, while the throat diameter of approximately 0.1–100 nm is the target for the latter method. In either method, the principle of analysis is the same. For example, conversion to the CO2–water system using the mercury intrusion method is conducted as follows (Purcell 1949): ðPc Þcw ¼

σcw  cos θcw  ðPc Þma σma  cos θma

(2)

where subscripts cw represents the CO2–water system and ma represents the mercury–air system. Specifically, the relationship between the volume of injected mercury and pressure is measured, and (Pc)ma is obtained from the shape of the PcSw curve. At this point, σma (480 dynes/cm) and θma (40 ) are both known; thus by using σcw and θcw under the target condition as the input parameters, (Pc)cw is determined. There are several methods that use the actual target fluid to determine Pc. The most common is the step-by-step approach, where the pressure of the non-wetting phase is slowly increased in steps and the Pc is obtained based on the flow rate

CO2 Geological Storage

2439

changes of the injected non-wetting phase and effluent wetting phase. The step-bystep approach corresponds to the measurement under static conditions in conformity with the definition of the seal; thus, it is considered to be the optimum method. However, to eliminate the dynamic effect, injection of the non-wetting phase at an extremely slow flow rate is required. As a result, it takes a few days to up to several weeks or more to measure the breakthrough of non-wetting phase (e.g., Liu et al. 1998). In contrast with these drainage processes, the Pcres is measured for imbibition processes (Hildenbrand et al. 2002). In this method, under the condition of constant volume for the whole system, the non-wetting phase is injected instantaneously at the same or higher pressure than the predicted Pcth. Following this, the upstream pressure in the sample decreases, while the downstream pressure increases. By measuring pressure changes in the non-wetting phase at both ends of the sample, Pcres is obtained from the difference in the final residual pressure. However, the Pcres measured in experiments possibly becomes lower when re-imbibition of the wetting phase is prevented because the flow path volume is different between at drainage and imbibition process. In fact, Hildenbrand et al. (2002) confirmed that in samples with k > 100 nD, Pcres becomes smaller than the Pcth in drainage process. To replace above static or quasi-static measurement methods, Egermann et al. (2006) proposed a dynamic measurement method, in which the non-wetting phase is injected applying a constant overall pressure drop, above Pcth, across the sample. This method stands on the following mechanism. Before the non-wetting phase reaches to the sample surface, the drainage rate of the wetting phase depends on the pressure drop over the whole sample. However, once the non-wetting phase starts to penetrate within the sample, the generation of Pcth at its front decreases the drainage rate of the wetting phase. From the experiments with a brine–nitrogen system, they showed that for fine-grained sandstone, carbonates, and chalk rocks with k  1 μD, the dynamic measurement method has a similar accuracy as the stepby-step approach, and measurements can be conducted in the same time as the Pcres method (Egermann et al. 2006). However, it is noteworthy that the Pcth measured in this method is influenced by the flow. In other words, under dynamic conditions, the interface between the wetting and non-wetting phase takes a shape defined by the receding contact angle against the wetting phase; thus, for rocks with poor wettability (i.e., θ of the wetting phase > 0 ), there is a possibility that θ becomes different from the equilibrium contact angle corresponding to static conditions. In such a case, Pcth may be overestimated (Egermann et al. 2006).

Evaluation of Sealing Performance Under CGS Conditions Previous Works The sealing performance of systems for CGS is evaluated with two types of methods: a method that converts from mercury’s Pc (e.g., Dewhurst et al. 2002; Bachu and Bennion 2008) and the direct measurement using CO2 (Hildenbrand et al. 2004; Li et al. 2005; Plug and Bruining 2007; Wollenweber et al. 2010). As shown clearly in

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Eq. 1, Pc depends on the type of fluid; thus, the latter method is more desirable in order to reduce uncertainties. However, the number of studies is currently limited. As one example, Li et al. (2005) measured the Pcth of N2, CH4, and supercritical CO2 in anhydrite (CaSO4) (a simulated sample of the caprock) using the step-bystep approach. It was shown that the Pcth of CO2 is lower than those of CH4 and N2, which reflects the fact that Pcth is proportional to σ between gas and brine. In contrast, after injecting CO2 with a constant flow in unconsolidated sand samples under the condition of various temperatures and pressures, Plug and Bruining (2007) kept the CO2 pressure constant to cause the imbibition of water with a constant flow. As a result, they indicated that an increase of CO2 pressure, which causes a decrease of σ, decreases the Pc in both drainage and imbibition processes. Hildenbrand et al. (2004) measured the Pcres of N2, CH4, and CO2 in argillaceous rocks from changes in the differential pressure for imbibition. In addition to the derivation of the relational expression of k and Pcres, they also analyzed the pore size distribution based on Pc. In a similar manner, Wollenweber et al. (2010) conducted an experiment with limestone and marl as the target. By repeatedly injecting CO2, a decrease in Pcres was observed, which was attributed to the dissolution and re-precipitation of carbonates.

Modeling of the Correlation Between Pcth and k Generally, rocks in nature can differ greatly from their Pcth because penetration depends on the flow path structure in individual samples. Therefore, from the perspective of stable CO2 containment, it is necessary to ascertain the range of variation of caprock’s Pcth by measuring numerous samples instead of a single one. Moreover, the sealing performance over a widespread area must be evaluated especially for grand-scale CGS. However, the core samples that one can realistically obtain from a storage site are numerically restricted. Moreover, samples are not necessarily available over the whole site. Because of these problems, the authors have proposed a method to represent Pcth’s variation using artificial samples of which the internal structure is intergraded from a simple to a more complicated one (Sorai et al. 2014a). This methodology enables the prediction of the range of variation of rocks’ Pcth without repeated measurements of numerous rock samples. As a first step, the authors prepared sintered compacts of uniform spherical silica particles with diameters of 0.1–10 μm. Manufactured sintered compacts were made available for measurements of k and Pcth. Specifically, Pcth was measured in supercritical CO2–water system under conditions of 1,000 m depth (10 MPa and 40  C). The CO2 in this condition corresponds to the supercritical phase. The CO2 pressure at the sample bottom was increased to higher than 10 MPa in steps of 10 kPa, but the water pressure at the upper side of the sample was maintained 10 MPa. The authors determined Pcth of a sample based on differential pressure at the instant when the CO2 breakthrough was observed through a sample cell observation window. Figure 2 shows a breakthrough image of supercritical CO2 from the upper surface of the sample, taking the 0.1 μm particle sample, for example (Sorai et al. 2014a). Initially the CO2 was not able to penetrate into the sample because

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Fig. 2 Breakthrough image of supercritical CO2 from an upper surface of a sample (Modified after Sorai et al. 2014a): (a) immediately before breakthrough; (b) breakthrough started from a specific point; and (c) finally the entire surface was covered with numerous breakthrough points

of a capillary effect (Fig. 2a), but a further increase of differential pressure caused CO2 seepage from the upper surface. The breakthrough started from a specific point even though particles were packed homogeneously in the interior of a sample. The CO2 flow passing through this point increased with increasing differential pressure (Fig. 2b). An additional rise of the differential pressure gradually increased the number of breakthrough points. Finally, the entire surface was covered with numerous breakthrough points (Fig. 2c). Figure 3 presents the correlation between Pcth and k for sintered compacts. The closest-packing structure of uniform spherical particles is defined theoretically as a line on a double logarithmic plot. Here, it is noteworthy that sintered compacts scatter around the closest-packing line because of their random packing (Sorai et al. 2014a). This variation is enhanced on lower k. Moreover, results suggest that samples with inhomogeneous particle packing are above the line, but samples in which particles are packed homogeneously overall, with inhomogeneous structures such as cracks included locally, are below the line. Figure 3 also shows experimentally obtained results for various sedimentary rocks. The Pcth of rock samples, which is shifted downward further distant from the closest-packing line, seems to be lower than that of sintered compacts. This is due to the diverse sizes, shapes, and mineral compositions of the particles contained in rocks. In other words, the rock’s Pcth can vary greatly due to such factors.

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Fig. 3 Correlation between Pcth and k of sintered compacts and various sedimentary rocks. The straight line represents calculated values for a case in which the closest packing of spherical particles is assumed

To what extent does such variation of Pcth affect the predictions of the spread of CO2 plumes after injection? For this problem, the migration of a CO2 plume was numerically simulated for a case, where a 100 m thick alternating sandstone and mudstone layer was set as the site, and one million ton of CO2 was injected annually into a sandstone stratum at 950–1,050 m depth for 50 years (Sorai et al. 2014b). The simulation compared the experimentally obtained upper (1.2 MPa) and lower limit (150 kPa) for the Pcth of mudstone stratum, assuming the k of each stratum in the vertical direction to be 10 mD (millidarcy) and 0.1 mD respectively. The result revealed a significant impact on the spread of the CO2 plume, particularly during the period following the completion of the injection. When Pcth was increased, almost all of the CO2 remained within the injection stratum over a longer period of time (Fig. 4a). However, when Pcth decreased, CO2 moved upward through the mudstone stratum due to its buoyancy, even after the injection had completed and reached the sandstone stratum located one layer above after 1,000 years (Fig. 4b). The magnitude of Pcth, therefore, has a significant impact on the predictions of CO2 behavior after storage. Determining the variation range of rock’s Pcth will be an issue tackled in the future. As the next step, the authors are investigating the impact of particle configuration and mineral composition on Pcth, in addition to the effect of particle size distribution arising from mixtures of particles with various sizes.

Conclusion of This Section With respect to the sealing performance of rocks, fundamental theory, measurement and analytical methods, and the application of obtained data have been well studied, particularly in the field of petroleum exploration. The acquired knowledge is directly useful in evaluating the safety of CGS. However, some questions remain regarding CGS, which were not necessary for consideration in petroleum exploration, such as the interaction of the non-wetting phase (CO2) and wetting phase

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Fig. 4 Impact of difference in Pcth of mudstone stratum on CO2 plumes (After Sorai et al., 2014b). The solid line represents the upper edge of the sandstone stratum, while the dotted lines represent the upper edge of the mudstone stratum. The Pcth of the mudstone stratum corresponds to (a) 1.2 MPa and (b) 150 kPa, respectively

(formation water) and the phase change of non-wetting phase itself. Moreover, even for existing evaluation methods, many issues remain such as the development of an accurate and efficient measurement method and the establishment of a theory that can be applied to rocks with complex internal structures. Future work should hopefully involve new approaches, such as modeling of Pcth using artificial samples with controlled internal structures, which can further develop the methods for the evaluation of sealing performance for CGS.

Evaluation of Geochemical Processes Introduction Implementing the CGS requires the quantitative evaluation of the behavior and effects of the injected CO2. Regarding this, the focus is generally on physical processes, such as CO2 migration, starting immediately after CO2 injection. This leaves many unknowns in the long term (1,000 years) (IPCC 2005) such as the effect of geochemical interactions. For instance, in storage aquifers in which the highest storage potential is expected, active geochemical processes are expected to occur due to the acidification of formation water caused by dissolution of CO2. The time scale for this process is expected to be long term, e.g., ranging from several hundred years to several tens of thousands of years. However, some processes may start immediately after CO2 injection in areas near injection wells and in rocks containing highly reactive carbonate minerals.

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In this paper, the author presents the target processes and the methods for understanding geochemical processes related to CGS in aquifers. The author focuses on numerical simulations as the essential approach for the evaluation of long-term geochemical processes. To improve model reliability, the author examined conditions and issues to improve the accuracy of input parameters. The paper also includes an example of reaction rate measurements for carbonates at hot springs.

Approach to Evaluation of Geochemical Processes On CGS in aquifers, geochemical processes on various temporal and spatial scales are predicted to occur in components of the storage system, such as reservoirs, sealing layers, cracks, faults, wellbores, and upper aquifers. These processes include the dissolution of CO2 in formation water, reactions of acidified water with surrounding rocks, pore-filling materials, and cement, carbonation of CO2 through reaction with mafic or ultramafic rocks, evaporation of formation water (dry-out), formation of CO2 hydrate, groundwater pollution, etc. These processes are directly related to the evaluation of important issues associated with implementing CGS. These issues include: the storage potential (geochemical trapping) based on long-term mechanisms; CO2 injectivity in reservoirs; leakage risks from caprock, cracks, faults, and wellbores; and environmental effects on shallow groundwater. Four types of approaches are applied for the evaluation of the abovementioned issues: field tests, laboratory experiments, natural analogue studies, and simulation studies. Each method targets a different temporal and spatial scale. Laboratory experiments have significant constraints on the temporal and spatial scales, yet conditions can be strictly controlled. Thus, laboratory experiments are suitable for elucidating mechanisms and the acquisition of parameters for each fundamental process. In contrast, natural analogue studies make it possible to understand phenomena occurring on the geological time scale. However, the transitional history of the environmental conditions is not always clear; thus, these are not suitable for acquisition of quantitative data related to reaction kinetics. On the other hand, simulation studies can deal with phenomena of all scale and play a crucial role in complementing other approaches. Especially in recent years, a three-dimensional reactive transport simulation is becoming mainstream with drastic advances in computing power (e.g., Xu et al. 2003; Johnson et al. 2004; White et al. 2005). However, as will be later discussed, there are many issues regarding the reliability of calculation results. Field tests are quite efficient for conducting quantitative analysis of CO2 behavior in underground conditions. Starting with the Norwegian Sleipner Project in 1996 for the study of CGS in aquifers, demonstration projects of various scales are currently in progress around the world. However, geochemical approach mainly bases on ex situ analyses of brine and rock samples. In other words, there is no effective tool for in situ monitoring of geochemical processes.

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The Role and Directionality of Simulation Studies Geochemical processes are phenomena that occur on an extremely long time scale. Thus, the ultimate evaluation of these processes must rely on numerical simulations. However, as previous studies have indicated, current simulations are based on many assumptions with various uncertainties and unknown parameters. Thus, for the long-term evaluation of CGS, these uncertainties must be reduced in order to increase the accuracy of simulation results. Here, to improve the prediction accuracy of geochemical processes, the author examined the parameters that are especially important for simulation studies including contributions from each of the abovementioned approaches.

Equilibrium Parameters Equilibrium parameters include the density, solubility, and enthalpy in the CO2–water system and so forth (Gaus et al. 2008). For these parameters, it is necessary to formulate as a function not only of temperature, pressure, and salinity but also of the effect of impurities and acidic gases other than CO2. Interfacial tension and wettability that regulate capillary pressure of CO2 in rocks are also important parameters to which geochemical processes indirectly contribute. As for interfacial tension, a relatively large number of measurements have already been made for the CO2–water system (e.g., Bachu and Bennion 2009), and in part, expansion into multicomponent systems such as a mixed gas of CO2 and H2S is underway (Shah et al. 2008). Wettability is difficult to evaluate due to its complex behavior depending on the surface conditions; thus, subsurface minerals are often assumed as a condition of the surface being completely saturated with water (i.e., contact angle of 0 ). However, some of the recent studies showed that contact angles of mica and quartz change in the presence of CO2 (e.g., Chiquet et al. 2007). Therefore, additional data from laboratory experiments are desired. Kinetic Parameters Generally, the rate formula for the mineral reaction is expressed as the following Eq. 3 (e.g., Lasaga 1998): Rate ¼ kA expðE=RT Þ Πani i f ðΔGr Þ;

(3)

where k is the rate constant, A signifies the reactive surface area, E is the activation energy, R denotes the gas constant, T is the absolute temperature, ai is the activity of chemical species i, and ni stands for the reaction order for ai. The last term f(ΔGr) corresponds to a function related to the Gibbs free energy change, which is expressed as a function of the degree of saturation:
 ΔGr ¼ RTln Q=K eq ;

(4)

where Q signifies the activity product and Keq is the equilibrium constant. As shown clearly in Eq. 3, the reaction rate is calculated as the product of each parameter;

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thus, just one inaccurate parameter can reduce the overall reliability of the calculated results. The US Geological Survey (USGS) compiled the value of k, E, and n for H+, in acidic, neutral, and alkaline ranges, based on the dissolution rate data for all the important minerals (Palandri and Kharaka 2004). This is currently one of the most useful reaction rate database, but these values are not always measured under conditions consistent with those in CGS. As a result, reaction rates may change due to differences in reaction mechanisms. The A has long been discussed as the parameter with the highest uncertainty (e.g., Lasaga 1998). Especially when obtaining A, there is no agreement on whether the commonly used BET method – based on the amount of adsorbed inert gas – expresses the actual reactive surface areas. In addition, natural mineral surfaces are different from fresh cleavage planes often used in laboratory experiments and may be influenced by adhesion of clay minerals, coating of secondary products precipitated from leaching components, etc. (Blum and Stillings 1995; White and Brantley 2003). These effects of surface conditions also should be investigated further. The f(ΔGr) have mostly been overlooked in numerical simulations until now, as the knowledge of dissolution mechanism is especially limited. As a result, it was often approximated as a linear function of Q/Keq based on the transition state theory (e.g., Xu et al. 2005). However, based on dissolution experiments of feldspars in recent years, it has been shown that f(ΔGr) follows a sigmoidal curve, or an irregular shape is produced in response to the difference in dissolution mechanisms (Burch et al. 1993; L€uttge 2006; Hellmann and Tisserand 2006; Sorai and Sasaki 2010). On the other hand, the function form of the ΔGr in the precipitation should incorporate the nucleation process prior to the growth. Most simulations assume that secondary minerals precipitate immediately after the solution becomes supersaturated (i.e., Q/Keq > 1). In fact, however, nucleation first occurs when a certain critical supersaturation is achieved. In addition, rates differ in homogeneous nucleation in free space and heterogeneous nucleation on the wall. Especially the heterogeneous nucleation rate is predicted to change significantly depending on the property of the wall surface. A factor that has not been considered much in previous numerical simulations is the activity of various impurities other than H+, i.e., promotion and inhibition effects of the reaction. It is unrealistic to examine the effects of all chemical species dissolved in the formation water for each mineral in this regard. However, for example, in the precipitation of calcite – the most important CO2 fixing mineral – it has been known for a long time that divalent cations such as Mg2+ function as inhibitory factors (e.g., Morse et al. 2007). Therefore, given the fact that the formation water generally includes these ions, effects of impurities should be taken into account at least in such reactions that relate to the nature of geochemical processes.

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Setting Conditions Simulation results are strongly influenced by the setting of primary and secondary minerals. Primary minerals can reflect the analysis of the rock samples from the site, but generated secondary minerals cannot be determined based on thermodynamically stable relationships only. In other words, when conducting an analysis from a kinetics perspective, in addition to the setting of a metastable phase as an intermediate product, the deviation from the thermodynamically stable region caused by changes in environmental conditions must also be considered (Gaus et al. 2008). The simulation of CGS into sandstone aquifers often assumes that the CO2 is mineralized into dawsonite. However, both thermodynamic and kinetic properties of dawsonite are not fully understood yet, except for some thermodynamic parameters (Be´ne´zeth et al. 2007). Regarding this, the dawsonite dissolution rate measured at 80  C and pH range of 3–10 indicates that dawsonite is in a stable phase only under high CO2 pressure conditions; it dissolves rapidly as the CO2 pressure decreases and mainly precipitates as kaolinite (Hellevang et al. 2005). Therefore, to avoid the overestimation of mineral trapping, care should be taken when assuming dawsonite. Similar issues exist for dolomite and magnesite, for which the precipitation mechanism is still unknown.

Measurement of Reaction Rates of Carbonates at Hot Springs The CO2 stored in aquifers dissolves in formation water to become carbonic acid, which in turn dissolves mineral components in rocks over a long period of time. Reaction rates of minerals are ordinarily extremely slow, but carbonates such as calcite or aragonite (calcium carbonate in both cases) are exceptions as they have high reactivity. When carbonates dissolve within alternating sandstone and mudstone layers, particularly in cases where the thicknesses of respective strata are thin, it can potentially lead to the formation of a leakage path to upper strata. In contrast, precipitation of carbonates can also occur when cations reaching from minerals in a sandstone stratum combine with bicarbonate or carbonate ions. In such cases, sealing performance would be enhanced due to the clogging of the sandstone stratum. The reaction of carbonates is, therefore, one of the most important geochemical processes associated with CGS, and knowing its rate is essential for geochemical simulations of CGS. It has been pointed out that mineral reaction rates measured in laboratories are completely different from those in nature because of the effects of various factors, such as reaction time, surface area, surface conditions (defects and coatings), pore water compositions, mass transfers, and biological activities (Blum and Stillings 1995; White and Brantley 2003). For this problem, the authors attempt to obtain carbonate reaction rates at carbonated and bicarbonated springs in various regions of Japan, regarding these sites as the natural analogue field of CGS. Selected sites

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Fig. 5 Differential interference microscope images for reacted calcite surface: (a) growth experiment at Masutomi Hot Springs (30 min after the start of the reaction) and (b) dissolution experiment at Shichirida Hot Springs (336 h after the start of the reaction)

contain either undersaturated or supersaturated waters with respect to carbonates. At each site, cleaved single crystals of various carbonate species were immersed in the spring water for up to 1 month. Each sample was taken out at prescribed times for surface observations. A part of the sample surface was covered with a sputtered gold thin film or a silicon rubber for an inert reference area. Figure 5a shows the calcite cleavage plane reacted in the supersaturated water at Masutomi Hot Springs in Yamanashi, Japan, as viewed with a differential interference microscope. Numerous pyramidal-shaped pattern, referred to as growth hillocks, formed immediately after the start of experiment. These growth hillocks grew in size and repeatedly combined with the progress of reaction. It is noteworthy that calcite single crystals in the shape of rhombohedron formed on a gold coating plane. This signifies that the solute flux applied uniformly on the sample was directly incorporated on a non-coated bare calcite surface to form growth hillocks, but the heterogeneous nucleation of calcite occurred on a gold coating plane, since solutes were not incorporated into gold. In contrast, Fig. 5b corresponds to the sample

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Fig. 6 The temporal profile of the height difference between the reacted and reference surface (gold coating or original surface): (a) growth experiment at Masutomi Hot Springs and (b) dissolution experiment at Shichirida Hot Springs

reacted in the undersaturated water at Shichirida Hot Springs in Oita Prefecture. The length scale of the image is different from that of Fig. 5a, since the change of surface configuration was greater due to the long duration of the experiment. The undersaturated water produced numerous etch pits in the shape of inverted pyramids, a pattern of dissolution. These etch pits were expanded and combined with the progress of reaction. A phase shift interferometer with a nanoscale vertical resolution and a laser microscope were used to take measurements of the height difference Δh between coated and non-coated areas of these calcite cleavage planes (Sorai and Sasaki 2010). Figure 6 presents the time-course change of the Δh, corresponding to the experiments shown in Fig. 5 (Sorai et al. 2014b). The Δh for the former was expressed as a positive value, being growth from the reference plane, while the latter was expressed as a negative value, being regression from the reference plane. The growth and dissolution rates were estimated to be 3.3  105 and

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3.2  106 mol m2 s1, respectively, from the slope of a fitting line to the temporal profile. However, the growth and dissolution rates derived based on the USGS database described above were 4.5  105 mol m2 s1 and 2.9  106 mol m2 s1, respectively, under identical temperature and pH conditions (Palandri and Kharaka 2004), showing that the experimentally obtained values, particularly with regard to the growth rate, were smaller by almost 30 %. Regarding this, the USGS database defines the reaction rate as a function of temperature, pH, and the degree of saturation, with no consideration given to the effects of impurities contained in the solution. Therefore, it is possible that the growth rate was reduced by trace dissolved components, primarily magnesium ions, in the field experiment. On the other hand, the effect of impurities on the dissolution process of calcite is presumably small because the actually measured and calculated values are practically identical for the dissolution rate.

Conclusion of This Section Geochemical processes improve the safety of a reservoir by stabilizing and changing the form of CO2 on geological time scales; however, geochemical processes can also result in negative effects such as increased leakage risks near injection wells and lowered injectivity. Evaluation of these geochemical processes tends to rely on numerical simulations owing to the long time scales involved. However, the author highlights that many previous studies point out the lack of sufficient knowledge on reaction kinetics, especially compared to the equilibrium theory. Therefore, to improve the reliability of simulation studies, data with high uncertainties and assumptions should be examined on a case-specific basis while referencing appropriate monitoring results of demonstration tests, laboratory experiments, natural analogue studies, etc.

Geophysical Monitoring and Modeling Introduction In CO2 geological storage projects, monitoring is indispensable for verification of CO2 storage. Various techniques are used to monitor the location of CO2 injection and volumetric extent of CO2 migration and detect possible leaks of CO2 at faults and seals. Monitoring is required to implement for long time, beginning with the survey and development of a site, continuing throughout the CO2 injection period, and even after the site is closed. Therefore, it is essential to develop monitoring technology that is cost-effective. In order to make CO2 geological storage (CGS) projects acceptable to society, consideration of long-term cost is also very important. Monitoring technologies for CGS are divided into four main categories: (1) atmospheric monitoring tools, (2) near-surface monitoring tools, (3) subsurface

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monitoring tools, and (4) data integration and analysis technologies (Litynski et al. 2012). Here we describe geophysical monitoring and modeling technologies concerning the latter two categories.

Seismic Monitoring Geophysical exploration methods that detect the two- or three-dimensional distribution of physical properties from the ground surface/sea surface are used as effective monitoring methods that can supplement well data (which provide direct information of the deep underground, but consist only of linear or point measurements). Among them representative one is seismic monitoring using active seismic methods such as seismic reflection, vertical seismic profiling (VSP), and cross-hole seismic tomography. Seismic monitoring is considered to be the standard monitoring method in CGS worldwide (e.g., Eiken et al. 2011). In these methods, an elastic wave emitted from multiple source points by a moving artificial hypocenter is received by a multichannel seismometer array spread across the wellbores or on the ground surface/seabed and then analyzed to estimate the elastic properties of the medium (e.g., elastic wave velocity and attenuation) through which the elastic wave propagates. The underground structure and physical state are estimated based on the results. Since it is believed that the outline of the underground area where injected CO2 has spread (a CO2 plume) can be detected through this process, active seismic exploration method, especially seismic reflection, is considered to be an extremely useful method for CO2 monitoring. In active seismic exploration, a “snapshot” that captures the underground CO2 plume at a given time is obtained. This process of taking a snapshot is repeated over appropriate time intervals to detect temporal variations of the snapshots. In the seismic reflection, a method that obtains a “three-dimensional snapshot” using sources and geophones distributed on the ground surface is called three-dimensional (3D) reflection method. It is also called 4D reflection method since a time axis is added in monitoring. However, such seismic reflection surveys are expensive, in particularly expensive to conduct surveys in the ocean, where a ship is used for the deployment of sources and geophones. Since sources and geophones are spread over a wide area, negotiations with local people and officials in the survey area are also required, which can influence social receptivity to CGS. Therefore, it is desirable to decrease the number of 3D seismic reflection survey when monitoring needs to be conducted regularly. There are also the following fundamental limits: seismic waves can only detect elastic properties, and the detectable structures and resolution can change depending on the frequency, energy, and source location of the elastic wave. Considering these limitations, it is worthwhile to take into account the use of other geophysical methods, in particular passive exploration methods, which can supplement seismic methods and reduce overall monitoring cost.

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Fig. 7 Geophysical postprocessors. Various computational postprocessors permit the user to calculate temporal changes that are likely to be observed if geophysical surveys of an operating and/or closed CO2 injection site are repeated from time to time. Results may be used to supplement conventional reservoir engineering measurements in history-matching studies undertaken during reservoir model development

Geophysical Modeling To appraise the utility of geophysical techniques in monitoring of CO2 injected into deep aquifers, Ishido et al. (2011) carried out numerical simulations using the so-called geophysical postprocessors. The geophysical postprocessors calculate temporal changes in geophysical observables that result from changing underground conditions computed by reservoir simulations (e.g., Pritchett et al. 2000; Ishido et al. 2011, 2015). The purpose of the development is to enable us to use monitoring data from repeat and/or continuous geophysical measurements in history-matching studies (Fig. 7). The name, postprocessor, comes from the fact that there is no need to couple and solve governing equations for geophysical phenomena with governing equations for reservoir simulations to calculate changes in geophysical observables; rather, they can be solved using the results of a reservoir simulation (snapshots) “afterwards.” For example, electrokinetic phenomena handled by the self-potential postprocessor (Ishido and Pritchett 1999) are current flows coupled with fluid flow within the pores of rocks. It handles a phenomenon in which the potential difference (streaming potential) is created proportional to the pore pressure difference. The streaming potential leads to secondary pressure difference due to an electroosmotic effect at the same time, but the secondary pressure difference is extremely small and can be neglected.

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Thus, governing equations for electrokinetic phenomena do not need to be solved at the same time as the governing equations for reservoir simulations. A simulation that couples “G” (geophysical observables) to a reservoir simulation, which is a TH coupled simulation in which governing equations for the transport of T (heat) and H (fluid/chemical species) are coupled and solved simultaneously, is generally not required. However, when calculating underground stress changes and/or ground surface deformation due to pressure or temperature changes, a THM coupled simulation that includes M (mechanics) should be performed if changes in porosity and permeability due to stress changes are important. In the applications to CGS, the geophysical postprocessors can be used for the following purposes: 1. Planning of an appropriate monitoring system: Effective methods and way of monitoring can be chosen based upon prediction of changes in geophysical observables, which are calculated from underground flow models and potential risks associated with vertical faults, openings in the caprock, etc. 2. Quick understanding of the underground conditions: Whether or not injected CO2 is stored as predicted can be judged by comparing the monitoring data obtained from actual geophysical measurements with predicted changes. If the behavior that is different from the predictions possibly arises from potential risks, the selection and deployment of effective monitoring methods can be examined. 3. Verification of the storage model: If the measured changes in geophysical observables are different from the predictions, the underground flow model is improved so as to reproduce the measured changes (history matching). The calibrated flow model provides a basis for reliable long-term predictions.

Flow Simulation Based Upon Tokyo Bay Model Here, illustrative computations which have been carried out using various geophysical postprocessors are described, based upon the results of numerical simulations of CO2 injection into an aquifer system underlying a portion of the Boso Peninsula/ Tokyo Bay area and calculations of the temporal changes in geophysical observables caused by changing underground conditions as computed by the reservoir simulation. The Tokyo Bay area in the southern Kanto plain is a representative industrial area in Japan. A number of large-scale CO2 emission sources surround the Tokyo Bay. From a geological point of view, sedimentary strata underlying the Tokyo Bay area are believed to be suitable for open aquifer CO2 storage (e.g., Okuyama et al. 2009). Late Pliocene to Middle Pleistocene Kazusa Group sediments are found below several hundred meters depth, comprising an alternation of turbidite sandstone and pelagic to hemipelagic mudstone. The sandstone is poorly consolidated with high porosity and permeability. The mudstone, on the other hand, is well consolidated, having fairly high porosity but very low permeability. Below the Boso Peninsula, the Kazusa Group sediments are more than 2,000 m thick, almost undeformed, and dip to the west toward Tokyo Bay at very low angles (less than 10 ).

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20000

15000

10000

Meters North

5000

0 −5000 −10000

25000

20000

15000

10000

5000

0

−5000

−10000

−16000

−25000

−20000

−20000

−15000

Meters East

Fig. 8 Study area (in the Boso Peninsula, Japan) considered in the numerical simulation. Also shown is a top view of the computational grid blocks used for flow simulations. “Inj-base” and “Inj-ese” indicate the location of CO2 injection site for the base and the ESE injection scenarios, respectively

A three-dimensional model is covering a 25  15 km2 area (Fig. 8) and representing 2,500 m of alternating sandstone- and mudstone-dominated formations based broadly upon the geological structure underlying the Tokyo Bay area (Fig. 9). In the base-case model, the horizontal and vertical permeabilities are simply assumed as 50 and 10 mD (1 mD = 1015 m2), respectively, for the sandstone-dominated (aquifer) formations, and 10 and 1 mD, respectively, for the mudstone-dominated (seal) formations. In view of the relative thinness of individual mudstone layers compared to the vertical size of the computational grid blocks (=100 m), they assumed a relatively high average permeability for the mudstonedominated seal formations. The porosity is assumed to be 0.2 for all formations. Relative permeability models for CO2 gas and liquid water are represented by Corey-type curves (with 0.1 residual saturation) and van Genuchten-type curves (with 0.2 residual saturation), respectively (Fig. 10). Capillary pressure (gas or liquid CO2 phase vs. aqueous phase) is represented by a van Genuchten-type model, and the capillary pressure magnitude is 3.58 kPa when the water saturation is 0.8 in the base model (Fig. 11).

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Fig. 9 Distribution of rock formations in the WNW-ESE section (x-z plane) at j = 8. The Umegase formation is indicated by the dark blue color.

1.0

Carbon–Dioxide Water

Relative permeability

0.8

0.6

0.4

0.2

0.0 0.0

0.2

0.4 0.6 Water Saturation

0.8

1.0

Fig. 10 Relative permeabilities for the non-wetting (carbon-dioxide gas, liquid carbonate) and wetting (water) phases. Residual saturation for the wetting (non-wetting) phase is 0.2 (0.1)

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delp0 = 0.0358 bar delp0 = 0.62 bar delp0 = 5.0 bar

Capillary Pressure, MPa

10

1

10–1

10–2 0.0

0.2

0.4 0.6 Water Saturation

0.8

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Fig. 11 Van Genuchten capillary pressure curves parameterized by delp0 (capillary pressure magnitude when the water saturation is 0.8)

In the initial state, all of the pore space within the computational grid is full of motionless liquid H2O (with small amount of dissolved CO2). At the outer lateral boundaries, the fluid pressure distribution is maintained at the initial (hydrostatic) value. At the top boundary, the pressure and temperature are maintained at 1 bar and 15  C, respectively. The bottom boundary is impermeable, and its temperature varies between 40  C at x = 0 km and 60  C at x = 25 km. In the numerical simulations, the “STAR” reservoir simulation code (Pritchett 1995, 2002) was used with the “SQSCO2” fluid constitutive module (Pritchett 2008) which represents the thermodynamics and thermophysical properties of H2O–NaCl–CO2 mixtures over the range from liquid-CO2 to supercritical-CO2 conditions including the three-phase region. (For test problem #3 in a code intercomparison project (Pruess et al. 2002), the STAR/SQSCO2 gave almost the same results (dry-out region development, disolved CO2 mass fraction, etc.) as those given by the TOUGH2/ECO2N simulation (Pruess 2005). See Fig. 12) Similar to the TOUGH2/ECO2M (Pruess 2011), the STAR/SQSCO2 can describe all possible phase conditions for brine–CO2 mixtures, including transitions between super- and subcritical conditions and phase change between liquid and gaseous CO2. Simulations were carried out for 50 years of injection (at a rate of ten million tons of CO2 per year) into a sandstone-dominated layer at 1,400 m depth (the Umegase formation) at the grid blocks (i = 10, 11; j = 8, 9; k = 9; “Inj-base” shown in Fig. 8) followed by 1,000 years of shut-in. The internal energy of the injected

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Fig. 12 A result of the “STAR/SQSCO2” application to test problem #3 in a code intercomparison project (Pruess et al. 2002). Computed distribution of gaseous-phase saturation as a function of the similarity variable ξ (= r2/t) for freshwater (blue) and seawater (red) cases (after Pritchett 2008)

CO2 corresponds to a temperature and pressure of 34  C and 144 bars (same as in situ conditions prior to injection). Here the results for two variants of the base case model: “L-k” and “H-k” models are presented, in which the horizontal/vertical permeabilities of the Umegase formation are 50 mD/ 10 mD and 500 mD/ 100 mD, respectively. Figure 13 shows the distribution of pressure, temperature, and phase saturations at t = 50 years (when injection ceases) and 1,050 years (after 1,000 years of shut-in) for the “H-h” model. At t = 50 years, the injected CO2 remains as a supercritical free phase with the saturation 0.2 or more within the sandstonedominated layers (the Umegase and underlying Otadai formations). After injection ceases, the CO2 density decreases (and its volume increases) due to pressure release. The supercritical CO2 then gradually migrates upward for hundreds of

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Fig. 13 “H-k” model: pressure (cyan), temperature (red), liquid CO2 (green) and gas (black) saturation contours in x-z plane at j = 8 at t = 50 and 1050 years. Contour interval is 2 MPa for pressure and 5  C for temperature. Liquid CO2 and gas saturation contour labels are 0.005, 0.105, 0.205 and 0.305. The region shown in the figure extends 2500 m in the vertical (z) direction and 10,000 m (i = 3, . . ., 19) in the x-direction

years due to buoyancy and penetrates into the overlying seal layer (the Kokumoto formation). However, the rising gaseous CO2 is then densified at shallower levels as the temperature decreases below the critical temperature at sufficiently deep levels and becomes relatively immobile liquid CO2 condensate. As shown in Fig. 14, at t =1,050 years about 17 % of the CO2 is trapped as immobile CO2 condensate at near residual saturation, and the remaining CO2 is trapped as dissolved CO2 in the aqueous phase (41 %) and supercritical residual gas below the seal layer (42 %). Other similar calculations have shown that if a much lower permeability (i.e., 0.1 mD) or a larger capillary pressure is assumed for the seal layer than in the base-case model, CO2 intrusion into the seal layer in the postinjection period will become negligible.

Prediction of Changes in Geophysical Observables Next, various “geophysical postprocessors” were used to calculate time-dependent earth-surface distributions of seismic observables (from reflection, VSP, or tomography surveys), microgravity, electrical self-potential (SP), and apparent resistivity (from either DC or MT surveys). The temporal changes are caused by changing underground conditions (pressure, temperature, gas saturation, concentrations of dissolved species, flow rate, etc.), as computed by the reservoir simulations. Figures 15 and 16 show seismic sections calculated by applying the seismic (reflection survey) postprocessor (Stevens et al. 2003) to the reservoir simulation

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results. The reflected waves correspond to the upper and lower boundaries of regions containing CO2 gas around the injection wells. In this case, the seismic postprocessor calculated the seismic velocity and Q factor in the water/gas two-phase regions using a “patchy saturation” model (e.g., Mavko et al. 2009). In this model, the low-frequency and high-frequency limiting bulk moduli are given by Gassmann’s relation and by Hill’s relation, respectively. The “standard linear solid” is applied to predict the velocity dispersion and attenuation with the characteristic frequency, which is inversely proportional to the square of liquid cluster size which depends on the liquid-phase saturation. The reflection events for the “H-k” model (Fig. 15) corresponds to the CO2 gas region at t=50 year shown in Fig. 13. Compared with this, the seismic events for the “L-k” model (Fig. 16) remains in a narrower region, which corresponds to a less horizontal expansion of CO2 gas region due to lower permeabilities of the injection aquifer (the Umegase formation) assumed for the “L-k” model. Figure 17 shows “sounding results” calculated by using the magnetotelluric (MT) postprocessor for the “L-k” model. In this calculation the postprocessor assumes that the pore fluid salinity is homogeneous at 0.01 below the upper surface

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of the seal layer (the Kokumoto formation), which gives 2.5 S/m pore fluid conductivity around the injection level. Change in the pore fluid conductivity (σ) due to CO2 injection is given so as that σ is proportional to the square of the aqueous-phase saturation. In shallower levels than the seal layer, the bulk conductivity of rock–fluid mixture is fixed at 0.01 S/m to represent freshwater regions. As seen in Fig. 17, although the apparent resistivity of the CO2-saturated region does not change very rapidly, it has increased by 15 % or more after 50 years. Figure 18 shows changes in earth-surface gravity at t = 50 years for the “H-k” model. The maximum decrease, which appears just above the injection zone, is about 75 μGal. The gravity disturbance grows almost linearly with time during the 50 year of injection interval (Fig. 19). After shut-in, further gravity decrease takes place up to about t = 55 years arising from the upward buoyant migration of the

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CO2 (Fig. 19). However, the rate of further gravity change becomes very small after t = 60 years although the upward migration continues for hundreds of years after shut-in. This is because the supercritical CO2 entering the Kokumoto seal layer is densified by condensation as the temperature decreases below the critical temperature at sufficiently deep levels and the upward movement slows down. As for the “H-k” model, gravity increase and decrease continue at stations 1 and 2 respectively after t = 55 years. This slight change reflects CO2 gas movement from the injection location to peripheral regions. Figure 20 shows downhole borehole-gravity response at stations 1 and 2 (see Fig. 18 for the locations) for the “H-k” model. At the injection location (station 1), pronounced gravity changes appear even as early as t = 5 years, corresponding to the thickness of the CO2 plume. At station 2, the change in earth-surface gravity is

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small even at t = 50 years (Fig. 19), but the borehole response is very apparent particularly after 25 years or so when the expanding CO2 plume engulfs the borehole location. Figure 21 shows change in self-potential (SP) at t = 5 years for the “H-k” model; the maximum increase, which appears just above the injection zone, is more than 40 mV. The self-potential postprocessor calculates changes in subsurface electrical potential induced by pressure disturbances through electrokinetic coupling (Ishido and Pritchett 1999). Since the permeability of the seal layer (the Kokumoto formation) is relatively large in the present model, a pressure disturbance propagates to shallower levels where a transition zone between the shallower fresh and deeper saline water is assumed to be present as in the MT calculations. This transition zone acts as an interface between regions of different streaming potential coefficient. Pressure increases about 2 bars around this interface, which is located at a depth of 1,000 m at the injection location, bringing about a positive change of 40 mV at the earth surface (see the vertical section in Fig. 21). This obvious SP change develops rapidly with pressure increase for the first several years and persists until shut-in at t = 50 years. After shut-in, SP disturbance gradually declines as pressures return to their original levels. As seen in Fig. 22, more pronounced SP disturbance appears for the “L-k” model, which corresponds to larger pressure buildup (about 5 bars) due to CO2 injection into the lower permeability formation.

Summary Of course, the applicability of any particular method is likely to be highly site specific, but the calculations described here indicate that none of these techniques should be ruled out altogether. In addition to seismic methods (especially reflection surveys, e.g., Chadwick et al. 2009), microgravity surveys appear to be suitable for characterizing long-term changes, and SP measurements are quite responsive to short-term disturbances. The computed gravity changes suggest that microgravity monitoring can be used to characterize the subsurface flow of CO2 injected into underground aquifers. Gravity monitoring results are sensitive to the lateral migration of the CO2-rich phases (both liquid condensate and particularly gaseous CO2). Gravity monitoring may also be useful for assessing the suitability of particular disposal aquifers for CO2 sequestration. If the geothermal gradient is low as is observed in a portion of the Tokyo Bay area, the predicted decrease in gravity is quite small considering the relatively large injection rate. Even if the (supercritical) gaseous CO2 gradually migrates upward for hundreds of years after injection, the gaseous CO2 will be densified as the temperature decreases below the critical temperature at sufficiently deep levels and become relatively immobile liquid condensate, which is much less likely to escape the aquifer than highly buoyant, low-viscosity CO2 gas. When this occurs, the gravity change is very slight during the 1,000-year postinjection period. Considering the current advanced technology for field measurements (e.g., Nooner et al. 2007; Alnes et al. 2008; Sugihara and Ishido 2008; Sugihara et al. 2013), microgravity monitoring is thought to be a very promising technique for evaluating CO2 geological storage.

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Fig. 18 Distribution of gravity change between t = 0 and 50 years in the study area shown in Figure 8 (extending from 15 km to 5 km in the east-west direction and from 10 km to 10 km in the northsouth direction). Maximum decrease is 75 μGal near the injection site centered at 8 km east and 1 km north

The self-potential postprocessor calculates changes in subsurface electrical potential induced by pressure disturbances through electrokinetic coupling. If the permeability of the seal layer overlying the injection zone is not too small, substantial SP changes will appear at the earth surface during the first few years of injection. At least in coastal and estuarine environments, this large change is produced by a pressure increase of several bars at the interface between the shallower fresh and deeper saline water layers, which acts as an interface between regions of different streaming potential coefficient. If a discontinuity of streaming potential coefficient is present, SP monitoring can be an effective technique for monitoring pressure changes near the interface at depth.

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Fig. 19 Change in gravity from t = 0 to 100 years for the “H-k” and “L-k” models at two stations 1 and 2, the locations of which are shown in Fig. 18

Fig. 20 Borehole gravity response for the “H-k” model at selected times at stations 1 and 2, the locations of which are shown in Fig. 18

Geomechanical Modeling Introduction When any kind of fluid like CO2 is pressure injected into an underground reservoir as is done for geological CO2 storage, the pressure (pore pressure) of the fluids underground increases, and the stress distribution underground may change. Stress redistribution within and surrounding the reservoir and caprock system may lead to geophysical changes, microseismicity, and fault reactivation and may even trigger

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Fig. 22 Temporal variations of self-potential from t = 0 to 100 years for the “H-k” and “L-k” models at two stations 1 and 2, the locations of which are shown in Fig. 18

large earthquakes (Giammanco et al. 2008; Lei et al. 2008; Miller et al. 2004; Yamashita and Suzuki 2009). For example, at a gas field in In Salah, Algeria, where CO2 is pressure injected to enhance natural gas production, synthetic aperture radar observations from a satellite have indicated a ground uplift rate of about 1 cm/year around the CO2 pressure injection wells, along with a similar amount of subsidence around the gas production wells (Onuma and Ohkawa 2009). In some gas fields in the Sichuan Basin, China, following injection of unwanted water into depleted gas reservoirs, a number of seismic sequences have been observed with sizable earthquakes ranging up to M4  5 (Lei et al. 2008, 2013). In recent years, following the rapid increase of applications in which fluids are intensively pressed into the deep formations of the Earth’s crust, such as the enhanced geothermal system (EGS), fracking of shale gas, and geological sequestering of CO2, injection-induced earthquakes and other risks related to injection-induced rock deformation and failure have attracted growing attention (Ellsworth 2013; Lei et al. 2013; Zoback et al. 2013; Zoback and Gorelick 2012). Indeed, geophysical changes and microseismicity are useful in the monitoring and management required during and after a large-scale injection project. However, the risks related to fluid leakage and earthquakes that can be felt may give rise to strong social impacts. The issue of noticeable or damage-causing earthquakes induced by artificial operations is controversial and has been the cause of delays and threatened cancelation of some projections such as the EGS (enhanced geothermal system) project at Basel (Deichmann and Giardini 2009). To carry out geological CO2 storage safely and for this technology to be accepted not only by the

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inhabitants around the storage sites but also by the society as a whole, technological developments that address such public concerns are essential. In addition, there is a strong desire to be able to control or predict the occurrence of damaging earthquakes. In this regard, geophysical/geomechanical modeling is key in site selection, injection operation, and postinjection management. The purpose of the following subsections is to provide a general framework for geophysical/geomechanical modeling and microseismicity analysis. Section “A General Framework of Geophysical/Geomechanical Modeling” introduces a general framework for modeling. Then, section “Numerical Simulation for THM Coupling Analysis” introduces the numerical simulation technology used in the coupled THM (heat transferring, fluid flow, rock mechanics) analysis. Postprocessing for history matching and fault stability analysis is presented in section “Fault Stability Analysis: Coulomb Failure and Slip Tendency.” A case study of a natural analogue is introduced in section “An Example of a Natural Analogue: The Matsushiro Seismic Swarm Driven by CO2-Quality Fluid Activity.” Finally, section “Data Processing and Analysis of Injection-Induced Seismicity” introduces some key technologies for data processing and analyzing of injectioninduced seismicity.

A General Framework of Geophysical/Geomechanical Modeling Figure 23 shows a schematic flowchart of modeling with coupled THM simulation and history matching using a geophysical postprocessor (see section “Geophysical Monitoring and Modeling” for details). Firstly, existing geological and geophysical data should be integrated to build a conceptual geological model of a reservoir system. Then the mechanical and petrological properties of the major rocks in the geological model must be sufficiently investigated to create a numerical model. Additional laboratory experiments might be required to collect data on specified rocks to improve the reliability of the numerical analysis. Finally, history matching is applied to refine the numerical model of a reservoir to reproduce observed data. All data obtained through geophysical exploration methods, such as microgravity measurements, seismic exploration, electrical or electromagnetic exploration, etc., can be used in history matching to improve the accuracy of future forecasts. Geophysical postprocesses are used to convert changes in pressure, temperature, salinity, CO2 saturation, etc., calculated by reservoir simulation into changes in geophysical observables (Ishido et al. 2011, section 5). Since there are uncertainties in many aspects of the numerical model, such as small-scale inhomogeneity and upscaling, uncertainty analysis is necessary for a probability-based prediction. In geomechanical modeling, discontinuous structures including joints, fractures, and faults have a governing role in fluid flow and rock stability. Studies on water injection-induced seismicity in depleted gas/oil reservoirs show that earthquakes of relatively greater magnitude (M3 or greater) are mostly related to the reactivation of preexisting faults, favorably or unfavorably oriented, within or

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Fig. 23 Flowchart of modeling with coupled THM simulation and history matching using a geophysical postprocessor

surrounding the reservoir (Lei et al. 2008, 2013). Therefore, estimating fault stability and sustainable fluid pressures for underground storage of CO2 is an important issue in geomechanical modeling (Rutqvist et al. 2008; Streit and Hillis 2004). Known major faults in or near target aquifers can be avoided during site screening. Since a fault of a dimension of a few hundreds/thousands of meters is sufficient to produce  M3/M5 earthquakes as indicated by the empirical relationship between source dimension and earthquake magnitude (Utsu 2002), faults that are not resolvable by geophysical surveys must also be properly addressed (Mazzoldi et al. 2012).

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Numerical Simulation for THM Coupling Analysis There is a current focus on coupled THM analysis as a budding technology. This technology is used to predict injection-induced changes in rock properties, formation deformation, stress redistribution, and fracture/fault stability. Although the simulation technology is still in development, there are a number of choices of research-oriented or commercial software for reservoir simulation and/or stress analysis, such as TOUGH2 and FLAC3D. TOUGH2 is a multiphase reservoir simulation program developed by the Lawrence Berkeley National Laboratory (LBNL) in the US FLAC-3D (Itasca 2000) and is a commercial software for stress analysis. As a promising combination, the “TOUGH-FLAC” approach with couplers developed by Rutqvist et al. (2002) has proven useful in the analysis of deformation accompanied with fluid flow within hard and soft rocks in geothermal studies (Todesco et al. 2004), in CCS studies (Funatsu et al. 2013; Rinaldi and Rutqvist 2013; Rutqvist et al. 2008), and in natural analogues (Cappa et al. 2009). A schematic of the couplers and physical quantities handled by the TOUGHFLAC approach is shown in the center of Fig. 23. A reservoir is presumably a porous medium filled with formation water. If a fluid (CO2 in CGS) is pressure injected into this reservoir, the pore fluid pressure increases, and there is flow between the formation water and the pressure-injected fluid. Changes in pore fluid pressure lead to small changes in the reservoir rock. In addition, if there is a temperature difference between the reservoir and the pressure-injected fluid, as the fluid flows and spreads, heat is transported, and the temperature change causes rock deformation. The fluid flow simulator TOUGH2 calculates changes in the pore fluid pressure, temperature, degree of saturation, etc., and sends the results to the rock mechanics simulator in FLAC3D. The rock mechanics simulator then calculates the solid deformation and sends the changes in porosity, permeability, and capillary pressure back to the fluid flow simulator. The couplers are some built-in functions in TOUGH2 and FISH codes in FLAC3D (Rutqvist et al. 2002). Such coupling approaches, termed sequential coupling, work well for problems in which coupling is relatively weak. In the THM coupling simulation, the following parameters and models are required and should be investigated through laboratory experiments: (1) parameters governing the deformation and fracturing behaviors of a given rock; (2) petrophysical models linking porosity, intrinsic permeability, relative permeability, and effective confining pressure; and (3) permeability of fracture as a function of effective confining pressure. Rock properties and mechanical behaviors strongly depend on individual rock types and structures within the rock. Thus, individual rocks of a target reservoir system should be fully investigated to obtain reliable parameters. If a typical rock of the reservoir system has not been investigated by earlier studies, additional experimental study is required. Further, laboratory experimentation has a twofold role in geomechanical modeling. On one hand, it is the only way to get the physical/mechanical/hydraulic properties of a given rock and the constitutive laws required for conducting numerical models (Lei and Xue 2009; Lei et al. 2011a). On the other hand, a well-designed experiment is

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useful for verifying and improving a related numerical model by matching the numerical results with the experimental results (Lei et al. 2015). Permeability might change greatly due to deformation and fracturing (Zhang et al. 2007). In brittle rocks, fault rupturing can lead to a 2-order-of-magnitude permeability increase as estimated by in situ testing (Ohtake 1976) and laboratory experiments (Alam et al. 2014). Thus, permeability as function of deformation should be properly considered. In the TOUGH-FLAC approach, permeability is revised within Tough2 in every time step by built-in functions. In some previous works, permeability has been expressed as a function of volumetric strain (εv) or shear strain (εs) (Cappa et al. 2009; Cappa and Rutqvist 2011; Chin et al. 2000): k ¼ k0 ð1 þ βΔes Þ  n ϕ , φ ¼ 1  ð1  φi Þeev k ¼ k0 ϕi

(5) (6)

where ϕ and k are porosity and permeability, respectively, with ϕi and ki being the initial values. A β on the order 104 or n of 30 results in a 2-order-of-magnitude permeability increase for a fully reactivated fault (Fig. 24). As seen from Fig. 24, Eqs. 5 and 6 result in quite different behaviors. This should be examined in future studies.

Fault Stability Analysis: Coulomb Failure and Slip Tendency In most cases, the stress tensor is not fully defined or is badly defined, so rock failure analysis based on absolute stress tensors may lead to incorrect results. The earth’s crust is considered to be critically stressed; thus, a small change in stress may trigger earthquakes. The amplitude thresholds of the Coulomb failure stress change (ΔCFS) required to trigger earthquakes has been estimated to range from 0.01 to 0.03 MPa (Brodsky and Prejean 2005; Cochran et al. 2004; King et al. 1994; Lockner and Beeler 1999; Stein 1999). Based on Coulomb failure law, the critical condition for rupturing on a preexisting fault is

Fig. 24 Rock permeability as a function of volumetric strain for two different models

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 τ ¼ μσ e ¼ μ σ  Pf

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(8)

The tendency of a planar discontinuous structure such as a fault to undergo slip under a given stress pattern depends on the frictional coefficient of the surface and the ratio of shear to normal stress acting on the plane. The slip tendency of the fault is defined as the ratio of the shear stress and normal stress (Morris et al. 1996) and thus equals the friction coefficient: Ts ¼ τ=σ e

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Slip-tendency analysis is a technique that visualizes the stress tensor in terms of its associated slip-tendency distribution and the relative likelihood and direction of slip on interfaces at all orientations (Morris et al. 1996). It can be used in assessing the risks of geological CO2 storage (Kano et al. 2014). Under a uniform regional stress field, the most optimally oriented fault has the maximum slip tendency, as faults with greater slip tendency values are easier to rupture. Under the principal stress coordinate system (s1, s2, s3), the shear and normal stresses on a surface of given direction cosines (l, m, n) can be calculated from the three principal stress magnitudes (σ 1, σ 2, σ 3) as: τ2 ¼ ðσ 1  σ 2 Þ2 l2 m2 þ ðσ 2  σ 3 Þ2 m2 n2 þ ðσ 3  σ 1 Þ2 n2 l2 σ 2 ¼ σ 1 2 l2 þ σ 2 2 m2 þ σ 3 2 n2

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σ 1 ¼ kð1= sin ðϕÞ þ 1Þ=2 σ 2 ¼ σ 1  kR σ3 ¼ σ1  k

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where tanφ = 1/tan(2θ) = μ. Inserting Eq. 13 into Eq. 10 leads to the following equations for shear stress and normal stress: h i1=2 τ ¼ k ð 1  ϕÞ 2 l 2 m 2 þ ϕ 2 m 2 n2 þ n2 l 2   cscðφÞ þ 1  ð1  ϕÞm2  n2 σ¼k 2

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Thus, the slip tendency is independent of the choice of the unknown parameter k, and we can get a slip tendency normalized by the maximum. For such a partially defined stress field, we can draw the 3-D Mohr circles for shear and normal stresses normalized by k or the maximum shear stress. It is convenient to define an overpressure coefficient λ for fluid pressure (Terakawa et al. 2013):


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where P0 is the critical pore pressure required to initiate rupture on the optimally oriented fault for a given friction coefficient, Pmax (=σ 3), which is the maximum pore pressure above which hydrofracture occurs. In the geophysical/geomechanical modeling approach, one can develop a postprocessor to calculate ΔCFS and slip tendency. It can be done within Flac3D by writing a simple FISH program. ΔCFS and slip tendency are especially useful for analyzing the effect of injection to preexisting nearby faults that have not been involved in the numerical model. Figure 25 shows an example of slip tendency analysis for a location where only the direction of the principal stresses and the stress difference ratio R (=0.6) are given. Faults having a strike and dip in the red zones have relatively greater probability of being reactivated.

An Example of a Natural Analogue: The Matsushiro Seismic Swarm Driven by CO2-Quality Fluid Activity In geological CO2 storage, it is important to clarify the mechanisms and geomechanical conditions of worst-case events, such as damaging earthquakes and reservoir leakage, so that they can either be avoided or mitigated. It is most desirable to use an actual CGS site in which such events have actually occurred and have been well monitored. However, many pilot projects are sited in places with

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Fig. 25 (a) 3D Mohr circles and (b) normalized slip tendency stereoplots (LSP lower sphere projection) under an over pore pressure constant of 0.1 and a local stress field in which only the direction of the principal stresses and the stress difference ratio R are given

good conditions for safely pressing CO2 into the reservoir. Thus, it is valuable to carry out “natural analogue research,” analyzing similar phenomena caused by the activity of a natural CO2-quality fluid to examining the modeling technology. Here, we make a brief review of studies on the fluid-driven earthquake swarm in Matsushiro, central Japan, as a natural analogue of seismicity induced by fluid injection. In the Matsushiro area, which is located in the central and northern part of Nagano Prefecture, a series of more than 700,000 earthquakes occurred over a 2-year period (1965–1967). This swarm, termed the Matsushiro swarm, resulted in ground surface deformations (uplifts as large as 75 cm), cracking of the topsoil, enhanced spring outflows with changes in chemical compositions, and CO2 degassing. Ten million tons of CO2-rich saltwater was estimated to have seeped out from underground along the cracks (Ohtake 1976). Thus, the Matsushiro swarm is believed to have been triggered and driven by high-pressure CO2-rich fluid from deep sources. Data observed during the Matsushiro swarm can therefore be used as a natural analogue for examining THM coupling analysis (Cappa et al. 2009; Funatsu et al. 2013). In Matsushiro and surrounding areas, subsurface geophysical surveys have been frequently conducted since the occurrence of earthquake swarms, and underground data, such as seismic wave velocity structure data, are abundant. In addition, the surface geology is relatively well understood. The geological model was developed based on these existing data. Here, a new Matsushiro model is used, which is basically an improved model modified from earlier studies (Cappa et al. 2009; Funatsu et al. 2013). In the new model, the

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Fig. 26 Map showing basic features around the Matsushiro earthquake swarm. The model area is shown on the topographic map. Red dotted lines indicate the Matsushiro fault and the Southeast Boundary Fault (SEBF) of the Nagano basin. Contours show earthquake swarm migration (Modified from Hagiwara and Iwata 1968). The right plot shows a 3D model for numerical analysis viewed from the southwest

boundaries along all four sides are enlarged to limit the effect of boundary conditions. It covers a 50  50  6 km area with a focus dimension of 24  24  6 km centered at the intersection of the Matsushiro fault and SEBF (Fig. 26). In addition, the topography is also involved in the new model to simulate subsurface ground water flow. In order to better represent the deep structure in the area, a geological model of three lithology groups was constructed, considering the seismic profiles obtained so far. Two vertical faults that intersect at the center of the model are assumed. The faults are modeled as narrow zones of a new group termed “fault.” The regional stress field has its maximum compression axis in the east–west direction, and its minimum compression axis in the north–south direction. This

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Table 1 Mechanical properties Property Bulk modulus (GPa) Shear modulus (GPa) Cohesion (MPa) Ten. strength (MPa) Friction angle ( ) Dilation angle ( ) Biot’s coefficient Ini. Perm.(k0), (m2)

Aoki Besyo Basement 1.96 4.42 7.85 1.55 3.49 6.20 – – – – – – – – – – – – 0.9 0.8 0.8 1e17 1e18 1e18 k ¼ k0 ð1 þ βΔes Þ, β ¼ 30, 000

Fault/fault inters. 3.16 2.42 1.5 0.0 28.8 20 0.6 1e15/5e15

Porosity

0.05

0.05

0.01

0.01

model is divided into grids by steps so that the fault zone is split in small parts, while the surrounding matrix becomes coarser as the distance from the fault increases (depth, however, is equally split at 500 m intervals). The total number of elements is 9,248. Mechanical properties, which are set similar to those in Cappa et al. (2009), are listed in Table 1, and the geometry of the model is shown in Fig. 26. After failure, in order to incorporate strain softening behavior into the model, we decreased the cohesion and tensile strength with strain following two linear paths to given values. After failure, the friction angle and dilation angle also change with the shear strain. The associated parameters are listed in Table 1. Note that some parameters used this, and former studies differ significantly from laboratory-derived data for intact rocks. For instance, the values of Young’s modulus used in the numerical model appear too low. As we know, the real crust contains fractures and faults at all scales. It is impossible to represent all individual fractures and small faults in a model, so we have to adjust some properties, such as the bulk and shear moduli, as an upscaling technique. Similar techniques are used in core-scale simulation to account for preexisting microcracks in rock samples (Lei et al. 2015). The calculated horizontal displacements and uplifts at the ground surface are shown in Fig. 27. The maximum uplift, 66 cm, is obtained at the point where the faults cross 1 year after from the beginning of fluid injection. This value is close to the observed maximum value of 75 cm. The uplift pattern becomes asymmetric to the SEBF, which concurs with observations. Left-lateral slip along the two faults is also identified. Results of the new model match observed values better than previous studies. The uplift gradually stretches away from the intersection of the two faults along their extensions in a skewed rhombic pattern, indicating a faultcontrolled pore pressure diffusion process. Figure 28 compares the Matsushiro earthquake swarm migration and a calculated distribution of ruptured zones along the Matsushiro and east Nagano earthquake faults 180 and 720 days after injection began. Except for fractures at the surface, all fractures demonstrate shear mechanisms. Surface fractures show tensile modes. Calculated surface uplift is plotted in Fig. 29. For comparison, some data

CO2 Geological Storage

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Fig. 27 Calculated distributions of X- and Y-displacement and uplift of the ground surface 360 days after injection began

estimated from field observations (Kasahara 1970; Tsukahara and Yoshida 2005) are also plotted. In conclusion, the numerical model and coupled THM analysis using the TOUGH-FLAC3D approach successfully represent major characteristics of observed phenomena associated with the CO2-rich fluid-driven Matsushiro earthquake swarm.

Data Processing and Analysis of Injection-Induced Seismicity Statistical Properties of Injection-Induced Seismicity Based on ETAS Modeling It is well known that an earthquake triggers aftershocks following modified Omori’s law. In the case of injection-induced seismicity, it is important to be able to discriminate induced activity from background seismicity and statistically

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Fig. 28 A comparison of the Matsushiro earthquake swarm’s migration and calculated distribution of ruptured zones at 300, 360, and 450 days after injection began along the Matsushiro and east Nagano earthquake faults

separate fluid-induced and Omori-law-type aftershock triggering. The epidemictype aftershock sequence (ETAS) model (Ogata 1992), which incorporates Omori’s law by assuming that each earthquake has a magnitude-dependent ability to trigger its own Omori-law-type aftershocks. The ETAS model is an appropriate tool for testing the significance of changes in seismic patterns (Ogata 1992, 2001), detecting minor stress changes (Helmstetter et al. 2003), and extracting a fluid signal from seismicity data (Hainzl and Ogata 2005). Thus, it is particularly useful for analyzing injection-induced seismicity (Lei et al. 2008, 2013). In the ETAS model, the total occurrence rate is described as the sum of the rate triggered by all preceding earthquakes and a forcing rate λ0(t) that represents the background activity: λðtÞ ¼ λ0 ðtÞ þ νðtÞ, νðtÞ ¼

X

K 0 eαðMi Mc Þ ðt  ti þ cÞp

(16)

fi:ti PO2’’

O2− PO2’’

O2−+h

...

O2−+h e

h

...

O2(s)

O2(g)

The existence of this simultaneous ionic and electronic conductivity defines its “mixed ionic–electronic conducting” name (Sunarso et al. 2008; Zhang et al. 2011). During membrane operation, a driving force is established normally through oxygen partial pressure difference between two different membrane sides. Figure 2 provides the schematic of the process. Oxygen gas on high partial pressure side of the membrane approaches the surface of the membrane, adsorbed on the surface (in some cases), and, upon receiving electron, becomes an oxygen ion. This oxygen ion then diffuses through the membrane (via the oxygen vacancies throughout the membrane), the process of which is accompanied by simultaneous electron transfer (or hole) in the opposite direction (same direction) to maintain the charge balance. The oxygen ion arrives at the other side of the membrane and, upon releasing electron, becomes an oxygen gas again. The first and the third processes are defined as surface exchange reactions, while the second process is defined as bulk diffusion. In the absence of any mechanical defect and assuming a perfect sealing, dense MIEC membrane permeates only oxygen to the other side, thus achieving an absolute selectivity in such system.

Limiting Steps The oxygen transport rate through the membrane, i.e., the flux, is limited by the slowest step, either bulk diffusion or surface exchange reaction (Sunarso et al. 2008). Consequently, thickness of the membrane becomes an important variable. For a relatively thick membrane, bulk diffusion tends to dominate, and as the thickness is reduced, surface exchange reaction becomes more prevalent. The incorporation of oxygen from the atmosphere (high oxygen potential) into the lattice and the subsequent release of lattice oxygen back to the atmosphere (low oxygen potential) can be described by two simple surface reactions:

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1 O2 þ Vo€ þ 2e0 ! OxO ðhigh O2 potentialÞ 2

(2)

1 OxO ! O2 þ Vo€ þ 2e0 ðlow O2 potentialÞ 2

(3)

Here, O2, Vo¨, e0 , and OOx represent molecular oxygen, oxygen vacancy, electron, and lattice oxygen, respectively. Albeit their oversimplicity to address the complexity of the real surface reactions, they can be used as a starting point. The consequence of oxygen incorporation into the lattice and the release of lattice oxygen back to the atmosphere is the generation of chemical potential gradient across the membrane (when one side is exposed to low oxygen potential), and because of the mobility of the charge carrier species, a net flux of oxygen will occur toward the lower potential side.

Bulk Diffusion If bulk diffusion is predominant, oxygen flux can normally be described using Wagner equation as a function of the conductivity of the charge carrier species and the oxygen partial pressure (Wagner 1975): lnP00 o2

JO2 ¼

RT 42 F 2 L

ð 0

σel σion dðlnPO2 Þ σel þ σion

(4)

lnP o2

Here, σel, σion, PO2, R, F, and L represent electronic conductivity, ionic conductivity, oxygen partial pressure, ideal gas constant, Faraday constant, and membrane thickness, respectively. If the oxygen vacancies are proportional to the ionic conductivity (i.e., if all vacancies do not associate among each other), an assumption which is valid at low vacancy concentration, the ionic conductivity can be expressed by Nernst–Einstein equation: σion ¼

4F2 ½Vo€DV RTVm

(5)

Here, DV is the vacancy diffusion coefficient and Vm is the molar volume of the oxide. This relationship implies that the electronic conductivity is not limiting, e.g., when it is substantially higher than the ionic conductivity. Therefore, Eq. 4 simplifies into lnP00 o2

JO 2

DV ¼ 4Vm L

ð

 ::  VO dðlnPO2 Þ

(6)

0

lnP o2

The vacancy diffusion coefficient can be determined via experimental measurement of chemical diffusion coefficient and tracer diffusion coefficient, e.g., via 18 O–16O isotope exchange experiments. The oxygen vacancy concentration can be derived as a function of oxygen partial pressure at low concentration of defects

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which leads to simplification. More details on the various simplifications pertaining to different special cases can be found elsewhere (Sunarso et al. 2008).

Surface Exchange Reaction Surface exchange reaction normally involves a series of steps with each one may become the limiting step. The possible steps are adsorption from the gas phase, charge transfer reaction between the adsorbed species and the bulk, and surface diffusion of intermediate species (Sunarso et al. 2008). Further additional steps are possible when every other gas impurity components such as CO, CO2, and CH4 which are exposed to the surface are taken into account. Oxygen flux equation can be derived theoretically by assuming the slowest step among the proposed reaction steps and using the law of mass action related to the oxygen partial pressure or empirically, examples of which can be found elsewhere (Sunarso et al. 2008). An important variable defined as Lc, i.e., a characteristic thickness, signifies the membrane thickness below which surface exchange dominates while above it, bulk diffusion dominates. It is quite accurate to say that at Lc, oxygen transport is equally determined by surface exchange and bulk diffusion (Bouwmeester et al. 1994). Lc however is not an intrinsic property as it generally depends on the surface morphology and the operating conditions such as oxygen partial pressure and temperature (Sunarso et al. 2008).

Membrane Developments, Limitations, and Improvements Fluorite Oxide compounds with fluorite structure are often used as an ionic conductor (an electrolyte) due to its predominant ionic conductivity at a certain temperature range. The ideal fluorite structure is illustrated in Fig. 3. Fluorite compounds have a general formula of AO2, exemplified by calcium fluoride (CaF2). In such structure,

z y

z

x

x

y

Fig. 3 Ideal fluorite structure for AO2 compounds represented by CaF2 (left) and its packing (right). Blue atoms, A (Ca); green atoms, O (F)

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the A cations form cubic close packing and occupy the face-centered cubic positions, while the O anions occupy the tetrahedral interstices (Megaw 1973). Zirconia (ZrO2) represents the classical example of oxides with fluorite structure which forms an important family of electrolytes in conventional solid oxide fuel cells. It requires temperature above 700
C to have substantial conductivity. Zirconia exhibits phase transition from monoclinic to tetragonal between 1100–1200
C and tetragonal to cubic at 2300
C (Aldebert and Traverse 1985). The cubic phase can be stabilized to room temperature by (about 10 mol%) Zr4+ substitution with lower valence cations, e.g., Ca2+, Mg2+, and Ln3+ (lanthanides). The tetragonal phase can also be stabilized using a less amount (about 3 mol%) of specific dopant such as Y3+. The drawback of using zirconia lies on the very high temperature required to achieve substantial oxygen ionic conductivity which is closely related to the structure. The ionic conductivity of the monoclinic ZrO2 is negligible, i.e., 107–106 S cm1 which is improved for its tetragonal phase to 103–102 S cm1 and reaches 10 S cm1 for cubic ZrO2 beyond 2100
C. Higher conductivity can also be obtained at lower temperature by partially substituting ZrO2 with CaO, resulting in a conductivity value close to 101 S cm1 at 1300
C. An attractive alternative to zirconia is bismuth oxide. Bismuth oxide also experiences phase transition from monoclinic (α-phase) to cubic (δ-phase) at 730
C prior to melting at 825
C (Sammes et al. 1999). The cubic δ-phase of Bi2O3 has fluorite structure with ordered defects in the oxygen sub-lattice and is attractive in terms of its 1–2 orders of magnitude higher conductivity than yttriadoped zirconia, i.e., 1 S cm1 at 650
C. This superior ionic conductivity is attributable to the vacancy of a quarter of oxygen sites in the lattice, the electronic configuration of Bi3+ comprising 6s2 lone pair electrons which leads to the high polarizability of the cation (and high oxide ion mobility) and Bi3+ ability to accommodate highly disordered surroundings (Sammes et al. 1999). The cubic phase can be stabilized to room temperature by partially substituting Bi with Dy, Er, Gd, Ho, Lu, Tb, Tm, Y, and Yb (despite existing dispute on the resultant structure), among which Dy-, Er-, Ho-, and Tb-doped ones show the highest conductivity of 0.1–0.4 S cm1 between 650
C and 700
C. Another fluorite compound of interest is ceria (CeO2). Pure CeO2 is actually a mixed conductor showing almost similar ionic and electronic conductivities (Inaba and Tagawa 1996). This is quite consistent with the fact that cerium can change its oxidation state depending on the oxygen partial pressure, i.e., Ce4+ may be reduced to Ce3+ under reducing atmosphere (and the opposite) (Kuharuangrong 2007). The ionic conductivity of the ceria can be made predominant by partially substituting Ce with other metal cations having lower and fixed valence. The interest on ceria-based materials comes from its high oxygen ionic conductivity, i.e., its conductivity at 750
C is similar to that of yttria-doped zirconia at 1000
C. Despite the superior conductivity of Bi2O3-based materials, they are not stable and can be reduced easily in reducing atmosphere. In contrast, ceria-based materials are quite stable and therefore have been largely used to replace yttria-doped zirconia as an electrolyte for lower temperature operation (98 %, CO selectivity of 90 %, and H2 yield twice that of CO. Tsai et al. reported the same reaction using disk La0.2Ba0.8Fe0.8Co0.2O3-δ membrane incorporating Ni/α-Al2O3 catalyst where they observed during 500-h operation the

High Temperature Oxygen Separation Using Dense Ceramic Membranes

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increasing CH4 conversion from 17 % to 80 % in conjunction with constant CO selectivity of 99 % and H2/CO ratio of 2 (Tsai et al. 1997). Beyond 500 h up to 700 h, the conversion remained constant while CO selectivity decreased slightly to 95 %. Jin et al. utilized tubular La0.6Sr0.4Co0.2Fe0.8O3-δ membrane (made by isostatic pressing) and Ni/γ-Al2O3 catalyst and observed CH4 conversion larger than 96 % with CO selectivity larger than 97 % (at low CH4 feed concentration) between 825
C and 885
C (Jin et al. 2000). Ishihara and Takita reported partial oxidation of CH4 using disk La0.8Sr0.2Ga0.6Fe0.4O3 membrane with the presence of Ni and La0.6Sr0.4CoO3 catalysts where they obtained CH4 conversion of 30.6 %, CO yield of 29.2 %, and H2 yield of 30.2 % at 1000
C (Ishihara and Takita 2000). Membrane reactor for industrial scale applications requires membrane materials which can tolerate harsh conditions, i.e., operate under reducing and acidic gas atmosphere such as CH4, H2, and CO2 at high temperatures (>800
C). In this context, perovskite MIEC membranes have very limited applicability. Fluorite MIEC membranes, on the other hand, show more potential (Zhang et al. 2014).

Future Directions Substantial advances in the oxygen selective MIEC ceramic membrane technology have been demonstrated over the past decades as represented by systematic and multitude approaches and concepts which leads to several orders of magnitude improvement of oxygen fluxes relative to those obtained in the 1980s. These aspects were reviewed throughout this chapter. In terms of oxygen production, the MIEC perovskite membranes are successful with the operation mode of high pressurized air as the feed gas as these perovskite membranes have sufficient material stability under such gas atmosphere. However, in many cases of clean energy applications, pure oxygen is not required. For example, to continuously use the existing power generation infrastructure under the oxy-fuel concept (one of the clean energy schemes), an O2/CO2 mixture for combustion with not very high flame temperature is required to get highly CO2-concentrated flue gas. In such case, air separation via these MIEC membranes operated by sweep gas mode using part of the flue gas (CO2) instead of high pressurized feed gas mode will be more economical. The prerequisite for such operation is the robust membrane stability under acidic gases at high temperatures. Thus, future directions of this technology will be placed on materials development with improved operational stability under severe gas atmospheres containing CO2, CH4, H2, SOx, and so on. Once there is a breakthrough, the applications of such MIEC ceramic membranes will be expanded from the field of air separation to chemical synthesis like syngas production from methane partial oxidation with much savings in capital investment and operation cost. Acknowledgment The authors acknowledge the research funding provided by the Australian Research Council (FT120100178).

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Shao Z, Yang W, Cong Y, Dong H, Tong J, Xiong G (2000a) Investigation of the permeation behavior and stability of Ba0.5Sr0.5Co0.8Fe0.2O3-δ oxygen membrane. J Membr Sci 172:177–188 Shao Z, Xiong G, Cong Y, Yang W (2000b) Synthesis and oxygen permeation study of novel perovskite-type BaBixCo0.2Fe0.8-xO3-δ ceramic membranes. J Membr Sci 164:167–176 Sunarso J, Baumann S, Serra JM, Meulenberg WA, Liu S, Lin YS, Diniz da Costa JC (2008) Mixed ionic–electronic conducting (MIEC) ceramic-based membranes for oxygen separation. J Membr Sci 320:13–41 Sunarso J, Liu S, Lin YS, Diniz da Costa JC (2009) Oxygen permeation performance of BaBiO3-δ ceramic membranes. J Membr Sci 344:281–287 Sunarso J, Liu S, Lin YS, Diniz da Costa JC (2011) High performance BaBiScCo hollow fibre membranes for oxygen transport. Energy Environ Sci 4:2516–2519 Sˇvarcova S, Wiik K, Tolchard J, Bouwmeester HJM, Grande T (2008) Structural instability of cubic perovskite BaxSr1-xCo1-yFeyO3-δ. Solid State Ion 178:1787–1791 Tan X, Wang Z, Meng B, Meng X, Li K (2010) Pilot-scale production of oxygen from air using perovskite hollow fibre membranes. J Membr Sci 352:189–196 Ten Elshof JE, Bouwmeester HJM, Verweij H (1995) Oxygen transport through La1-xSrxFeO3-δ. I. Permeation in air/He gradients. Solid State Ion 81:97–109 Teraoka Y, Zhang H, Furukawa S, Yamazoe N (1985) Oxygen permeation through perovskitetype oxides. Chem Lett 14:1743–1746 Teraoka Y, Nobunaga T, Yamazoe N (1988) Effect of cation substitution on the oxygen semipermeability of perovskite-type oxides. Chem Lett 17:503–506 Tilley RJD (2013) Understanding solids – the science of materials. Wiley, Chichester Tsai C-Y, Dixon AG, Moser WR, Ma YH (1997) Dense perovskite membrane reactors for partial oxidation of methane to syngas. AIChE J 43:2741–2750 Tsai CY, Dixon AG, Ma YH, Moser WR, Pascucci MR (1998) Dense perovskite, La1-xAxFe1-yCoyO3-δ (A = Ba, Sr, Ca), membrane synthesis, applications, and characterizations. J Am Ceram Soc 81:1437–1444 Wagner C (1975) Equations for transport in solid oxides and sulfides of transition metals. Prog Solid State Chem 10:3–16 Wang H, Cong Y, Yang W (2002) Oxygen permeation study in a tubular Ba0.5Sr0.5Co0.8Fe0.2O3-δ oxygen permeable membrane. J Membr Sci 210:259–271 Wang L, Imashuku S, Grimaud A, Lee D, Mezghani K, Habib MA, Shao-Horn Y (2013) Enhancing oxygen permeation of electronically short-circuited oxygen-ion conductors by decorating with mixed ionic-electronic conducting oxides. ECS Electrochem Lett 2:F77–F81 Watanabe K, Yuasa M, Kida T, Shimanoe K, Teraoka Y, Yamazoe N (2008a) Preparation of oxygen evolution layer/La0.6Ca0.4CoO3 dense membrane/porous support asymmetric structure for high-performance oxygen permeation. Solid State Ion 179:1377–1381 Watanabe K, Yuasa M, Kida T, Shimanoe K, Teraoka Y, Yamazoe N (2008b) Dense/porous asymmetric-structured oxygen permeable membranes based on La0.6Ca0.4CoO3 perovskitetype oxide. Chem Mater 20:6965–6973 Wu K, Xie S, Jiang GS, Liu W, Chen CS (2001) Oxygen permeation through (Bi2O3)0.74(SrO)0.26Ag (40% v/o) composite. J Membr Sci 188:189–193 Zhang K, Sunarso J, Shao Z, Zhou W, Sun C, Wang S, Liu S (2011) Research progress and materials selection guidelines on mixed conducting perovskite-type ceramic membranes for oxygen production. RSC Adv 1:1661–1676 Zhang K, Shao Z, Li C, Liu S (2012) Novel CO2-tolerant ion-transporting ceramic membranes with an external short circuit for oxygen separation at intermediate temperatures. Energy Environ Sci 2:5257–5264 Zhang K, Liu L, Shao Z, Xu R, Diniz da Costa JC, Wang S, Liu S (2013) Robust ion-transporting ceramic membrane with an internal short circuit for oxygen production. J Mater Chem A 1:9150–9156 Zhang K, Liu L, Sunarso J, Yu H, Pareek V, Liu S (2014) Highly stable external short-circuitassisted oxygen ionic transport membrane reactor for carbon dioxide reduction coupled with methane partial oxidation. Energy Fuels 28:349–355

Part V Climate Change Mitigation: Advanced Technologies

Photocatalytic Water Splitting and Carbon Dioxide Reduction Nathan I. Hammer, Sarah Sutton, Jared Delcamp, and Jacob D. Graham

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Photocatalytic Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Photocatalytic Water Splitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Photocatalytic CO2 Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Heterogeneous CO2 Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Homogeneous CO2 Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Photocatalytic water splitting, which involves the simultaneous reduction and oxidation of water-producing hydrogen and oxygen gas, provides a means of harnessing the sun’s power to generate an energy source in a clean and renewable fashion. Photocatalytic reduction of carbon dioxide to form hydrocarbons such as methane not only promises reduced emission of an important greenhouse but also a new source of fuel. Concerns over the effects of global climate change and the eventual demise of fossil fuels make the search for clean alternative energy sources a top priority. This chapter details the progress in these two increasingly important areas: hydrogen production by photocatalytic water splitting and photocatalytic carbon dioxide reduction.

N.I. Hammer (*) • S. Sutton • J. Delcamp Department of Chemistry and Biochemistry, The University of Mississippi University, Oxford, MS, USA e-mail: [email protected]; [email protected]; [email protected] J.D. Graham Johns Hopkins University, Baltimore, MD, USA e-mail: [email protected] # Springer Science+Business Media New York (outside the USA) 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_46

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Introduction It is an understatement to say that the consumption of energy is a critical requirement for modern human civilization. The rapid industrialization and technological progress that permeate every facet of life would not be possible without the cheap and abundant energy sources enjoyed by mankind today. Annual worldwide energy consumption reached 497 exajoules in 2006, and with current conditions, energy demands are expected to grow 44 % by the year 2030 (Energy Information Administration and International Energy 2009). Currently, fossil fuels provide the vast majority of this energy as they are easily obtainable, abundant, and energetically dense. In order to keep up with this pace, society’s reliance on fossil fuels will grow dramatically in the coming years if alternative sources of energy are not developed. It is now well accepted in society that human dependence on fossil fuels presents a number of problems. Competition for fossil fuel-based sources of energy will have destabilizing geopolitical effects as the supply of these valuable resources declines. However, the most publicized consequences of the continued use of fossil fuels come in the form of environmental pollution. Sulfur dioxide, nitrogen oxides, cadmium, and mercury are all released as a result of burning fossil fuels, with coal being the largest contributor. Under the right conditions, these pollutants produce easily visible results in the form of acid rain and smog, while other combustion products, such as carbon dioxide, may not appear to have an immediately visible effect. Although CO2 can generally be considered harmless (at least physiologically to plants and animals – including humans), the quantities released annually into the atmosphere (about six billion tons) could possibly result in climate-altering effects. Concerns over “global warming” and, more recently, “global climate change” have captivated the attention of world governments and are currently transforming society in areas ranging from concern over automobile emissions to managing carbon footprints (Hansen and Sato 2004; Fischer et al. 1999; Luthi et al. 2008; McMichael and Woodruff 2004; Jackson and Schlesinger 2004; Schimel et al. 2000; Armaroli and Balzani 2007; Caetano et al. 2008; Zhang et al. 2007). Certain atmospheric gases such as CO2 are thought to trap long wavelength, thermal radiation in the Earth’s atmosphere through the “greenhouse effect” and CO2 itself is considered a greenhouse gas. Other important greenhouse gases include water, methane (CH4), nitrous oxide (N2O), and ozone (O3). The historical development of the greenhouse effect is rather quite interesting and dates back to the nineteenth century and scientists including Svante Arrhenius (Arrhenius 1896). The basic mechanism behind the greenhouse effect is depicted in Fig. 1. Radiation from the sun is absorbed by the Earth and is converted to heat. This heat is radiated back into space but some wavelengths of radiation corresponding to the vibrational normal modes of greenhouse gases are absorbed by these gases. This energy is then reemitted in all directions, including back toward the Earth, rather than into space. The overall effect is a “trapping” of heat energy in the atmosphere. Ice core samples possess trapped gaseous bubbles that reveal atmospheric CO2 concentrations dating back as far as 800,000 years (Fischer et al. 1999; Luthi et al. 2008). They have shown a correlation between higher CO2 concentration and

Photocatalytic Water Splitting and Carbon Dioxide Reduction Fig. 1 Various wavelengths of solar radiation are absorbed by the Earth’s surface and transformed into heat, which is eventually reradiated back into space. Greenhouse gases, such as CO2, absorb some of this infrared radiation and reemit it in all directions, including back toward the Earth’s surface

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Sun

CO2

Surface of Earth

higher average global temperatures. However, this correlation is delayed from the effect of the oceans and other buffer systems (Hansen and Sato 2004). With current conditions, an eventual average global temperature increase of several degrees Celsius is possible. Along with sea level rise, acidification of the oceans, and glacial melt, the rise in average temperature could destabilize much of the Earth’s current ecology with altered fauna migration and flowering times. These circumstances also would likely diminish food supplies as environmental conditions change. Although the dangers of global climate change have been in public thought for decades, solutions remain elusive for technical and economic reasons (Keith 2009). The possible solutions to global warming are numerous and varied, but most can be divided into two avenues of approach: removing sources of CO2 or capturing released CO2. An example of a geoengineering form of the latter would be injecting CO2 underground. Groundwater is the major sink for CO2 injected underground, and the possibility of long-term containment is difficult to predict (Gilfillan et al. 2009). While removing CO2 from the atmosphere would help in reversing the trend of global warming, replacing current fossil fuel-dependant energy sources with non-CO2-emitting energy sources is a more long-term solution. Of all the 6 billion tons of CO2 released annually, 80 % is due to the burning of fossil fuels. Nuclear, geothermal, wind, hydroelectric, and solar methods of energy production emit no CO2 and are much cleaner sources of energy than fossil fuels. A geothermal, wind, or hydroelectric energy supply is renewable and clean but has limited implementation in specific areas. Nuclear energy is a very real alternative to fossil fuels but is not renewable, and fissile materials will eventually be depleted. Solar-derived energy has the most potential as a permanent replacement for fossil fuels and as a means by which to transform one form of energy into another, and photovoltaics have emerged as perhaps the most promising avenue for that capture and conversion.

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Although the development of solar energy as an alternative energy source seems like the perfect solution to society’s energy needs, long-term storage and realistic energy density are obstacles. Many have touted hydrogen gas as an attractive alternative to fossil fuels as an energy carrier (Barreto et al. 2003; Crabtree et al. 2004; Dunn 2002; Moriarty and Honnery 2009). Hydrogen’s reaction with oxygen yields only water and heat, and this heat can easily be used as a source in automobiles or generators (Crabtree et al. 2004). Hydrogen storage in tanks involves high-pressure or cryogenic storage (Schlapbach and Zuttel 2001; Zuttel 2004). Other methods involve hydrogen adsorption onto certain specialized surfaces with metal hydrides having the highest hydrogen storage density (Zuttel 2004). Currently, most hydrogen production is dominated by steam reformation of natural gas (Crabtree et al. 2004). An efficient, cheap, and renewable method of hydrogen production would allow hydrogen gas to become the primary energy carrier in automobiles and in stationary applications. Coupling the storage and transportation potential of hydrogen gas with solar energy-based production would allow for the creation of an inexpensive and highly useful source of energy. It is often noted in reviews and by advocates of solar energy that the sun provides many thousands of times the annual energy consumption of the Earth, and harnessing only a fraction of this energy would be adequate. Shown in Fig. 2 is a solar emission spectrum obtained on the campus of the University of Mississippi. This emission mimics a blackbody curve, and it is readily apparent that most of the light from the Earth’s yellow sun that reaches the Earth’s surface is in the visible region of the electromagnetic spectrum. The number of photons reaching the Earth’s surface drops dramatically as ultraviolet (UV) wavelengths are approached. Dips in the spectrum correspond to absorption by different atmospheric gases such as water vapor. Various methods exist for harvesting solar energy, but the use of photocatalysts provides perhaps the most viable option with their reversible Fig. 2 Solar emission spectrum obtained at the University of Mississippi

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oxidation–reduction capabilities. Photocatalytic water splitting, which involves the simultaneous reduction and oxidation of water-producing H2 and O2, provides a means of harnessing the sun’s power to generate an energy source in a clean and renewable fashion. Besides the production of an alternative to fossil fuels, photocatalytic processes can turn the tide against global climate change in a more direct way. Photocatalytic materials can reduce carbon dioxide to form hydrocarbons such as methane and ethanol, essentially taking exhaust and turning it back into fuel. This chapter details the progress in these two increasingly important areas: hydrogen production by photocatalytic water splitting and photocatalytic carbon dioxide reduction.

Photocatalytic Processes A photocatalytic process relies on a semiconductor’s adsorption of light to create stored energy and the use of that energy to do some form of useful work – in this case, serving as a catalyst for the production of a desired reaction product. In semiconductors, groups of closely spaced electronic energy levels form bands, namely, the conduction and valence bands, as shown schematically below in Fig. 3. When incident light has energy that is greater than that of the band gap of the semiconductor material, electrons in the valence band of the material are excited to the conduction band. At the same time, holes are created in the valence band. Photocatalytic reactions then occur on the surface of the semiconductor, where these newly generated electrons and holes are located. Many important considerations go into the engineering of a useful photocatalyst. A few of these include matching the band gap to the radiation wavelength (or frequency/energy) to be employed, the suppression of the recombination of electron–hole pairs, and appropriate sensitization by other materials. The conduction band is higher in energy and less populated with electrons than the valence band, and the energy separation of these two bands is commonly referred to as the band gap. This band gap limits the minimum energy (or wavelength) of incident photons able to be absorbed. Photons that are absorbed promote electrons (e
) across the band gap from the filled valence band into the empty conduction band creating a hole (h+) in the valence band. Thermal relaxation of the electron–hole pair to the band edge can occur or recombination of the electron–hole pair can result, although this takes longer to occur (on a picosecond timescale). While the electron–hole pair exists, the photocatalyst can perform useful reduction and oxidation reactions by accepting electrons into its valence band or donating the promoted electrons in its conduction band. When an electron moves to the surface of the photocatalyst and has the correct potential, anion radicals (A
in Fig. 3) are produced, while cation radicals (B+ in Fig. 3) are produced from electron holes at the surface. As mentioned above, there are a number of design considerations to keep in mind in order to create a useful photocatalytic material. Suppression of the recombination of electron–hole pairs in a photocatalyst is essential to improving its efficiency

2714 Fig. 3 In a semiconductor, electrons (e
) are promoted from the valence band to the conduction band when photons of light are absorbed. Electron holes (h+) are created with the excitation of electrons. The creation of this electron–hole pair allows for the reduction and oxidation of other species

N.I. Hammer et al. A– Reduction A

–

e– e e Conduction Band –

Photons Band Gap

Valence Band + + h h+ h

B Oxidation

B+

(Hurum et al. 2005; Mohapatra et al. 2008; Fox and Dulay 1993; Colombo and Bowman 1996; Kaneco et al. 1998). Trapping of a promoted electron, hole, or both impedes the detrimental recombination process. An example of electron–hole trapping would be using a sacrificial reagent to donate electrons to a photocatalyst after excitation. Electrons donated into the valence band provide a longer lifetime for the excited electron in the conduction band. Oxygen and several inorganic oxidizing species have been shown to serve as good recombination inhibitors (Fox and Dulay 1993). Sensitization of semiconductors by dye molecules is another important design element employed to both increase the excitation rate and extend the excitation wavelength window (Fox and Dulay 1993; Younpblood et al. 2009). Photoelectrons are provided by a photosensitive dye that is in contact with the semiconductor material, and charge separation occurs at the surfaces between the dye, semiconductor, and electrolyte. The semiconductor serves primarily as the charge carrier, rather than the source of electrons and holes. Physically adsorbing the molecules to be reduced or oxidized (A and B, respectively, in Fig. 3) by the photocatalyst is another important design element that is essential to successful catalytic activity (Fox and Dulay 1993; Li et al. 2008). This is because of the fact that the recombination of photogenerated electrons and holes is very fast. There is no time for diffusion of the charge acceptor to the site of oxidation or reduction. Electron transfer is kinetically competitive only when the donor or acceptor molecule is adsorbed before the reaction of interest is to take place (Fox and Dulay 1993). Doping of other atoms and molecules into semiconductor photocatalysts to modify the electronic structure is also an important area of research in recent years that will be discussed in the later sections of this chapter (Fox and Dulay 1993; Yeredla and Xu 2008; Bhattacharyya et al. 2008; Choi et al. 1994; Yan et al. 2005; Wang et al. 2000; Bae et al. 2008; Livraghi et al. 2008; Jagadale et al. 2008; Graciani et al. 2008; Kesselman et al. 1997; Fang et al. 2008; Varghese et al. 2009; Gai et al. 2009; Hong et al. 2005; Hidalgo et al. 2009; Usubharatana et al. 2006; Osterloh 2008; Domen et al. 2000; Kudo and Miseki 2009).

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−2.0

CdSe

H+/H2 WO3 Fe2O3 2.3eV

MoS2 1.75eV

1.1eV

3.0eV

Si 2.25eV

1.7eV

3.0eV

3.2eV

3.4eV

GaP

2.8eV

2.0

5.0eV

V vs. NHE (pH0)

1.0

TiO2

2.4eV

CdS

KTaO3 SrTiO3 0

SiC

ZnS

ZrO2

3.6eV

−1.0

O2/H2O

3.0

4.0

Fig. 4 Band structures of common semiconductor photocatalysts relative to NHE. Note that in this representation, the valence band is at the bottom and the conduction band is on the top (Reproduced with permission from Kudo and Miseki (2009))

The number of photocatalysts developed for water splitting and carbon dioxide reduction increases more each year and many of these materials are cataloged below in the following two sections of this chapter. Important considerations already mentioned above in creating an effective photocatalyst include suppressing electron–hole recombination and achieving effective charge separation. Another important consideration is the selection of the best semiconductor for the desired photocatalytic reaction. The choice of semiconductor material and the other species that are incorporated into it such as sensitizers and dopants are critical in achieving the optimal overlap of band gap with the wavelengths of light. Shown in Fig. 4 are the band structures of a few representative semiconductor photocatalysts relative to the normal hydrogen electrode (NHE) at pH = 0 (Kudo and Miseki 2009). In the NHE, hydrogen’s standard electrode potential is defined as zero (2H+ + 2e
! H2, E = 0.0 V), and the potential of all other electrode reactions are defined as relative to hydrogen. To effectively use the abundant visible solar radiation shown in Fig. 2, the band gap (the height of the bar in Fig. 4) needs to be less than about 3 eV. This energy corresponds to photons of about 400 nm, right at the visible edge of the solar emission spectrum. However, to be effective in water splitting or carbon dioxide reduction, the location of the top and bottom of the band gap is also very important. Photocatalytic materials have promising and practical uses in many areas as wide ranging as organic synthesis (Fox and Dulay 1993; Kudo and Miseki 2009) and the degradation of hazardous waste (Bahnemann 2004; Hoffmann et al. 1995). Here, the interest is in the application of semiconductor photocatalysts to the splitting water to create a new source of hydrogen gas and the reduction of carbon dioxide to useful forms. In the following two sections, the application of photocatalytic semiconductor materials for these purposes is discussed and many examples of recently developed materials are listed.

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Photocatalytic Water Splitting Water splitting is the simultaneous reduction and oxidation of water to produce H2 and O2. In the early 1970s, the Honda–Fujishima effect was reported, in which water splitting was achieved with a TiO2 electrode under ultraviolet (UV) irradiation (Fujishima and Honda 1971, 1972). In their configuration, which is illustrated in Fig. 5, a platinum electrode and a TiO2 electrode are connected through an external load and immersed in water. When irradiated with UV light, current flows from the platinum electrode to the TiO2 electrode. Oxidation proceeds at the TiO2 electrode, while reduction proceeds at the platinum electrode. These processes are given by: 1 Oxidation : 2hþ þ H2 O ! O2 þ 2Hþ 2

(1)

Reduction : 2e
þ 2Hþ ! H2

(2)

where h+ are electron holes. The overall chemical equation for this process is thus: 1 H2 O ! O2 þ H2 2

(3)

Not all semiconductor materials are appropriate for the photocatalytic splitting of water. As mentioned above, it is important to choose a semiconductor material that exhibits a band gap appropriate for the desired photochemical reaction. In the case of water, the top level of the valence band must be more positive than the oxidation–reduction potential of Eq. 1 – the oxidation of water to form oxygen gas and two protons. This reaction occurs at 1.23 V relative to NHE. The lower level of

Pt

TiO2

h+ e– e– H2 e– e–

h+

H++ O2

e–

UV h+

H+

H2O

e– h+

Honda-Fujishima effect

Fig. 5 Cartoon schematic of the photocatalytic water splitting setup employed by Fujishima and Honda (1971, 1972)

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the conduction band must be more negative than the oxidation–reduction potential of Eq. 2, the reduction of the hydrogen cation, to create the desired product hydrogen gas. This, as all freshman chemistry students can attest to is 0 V relative to NHE. Honda and Fujishima’s choice in their original paper was TiO2. As evident from Fig. 4, the band gap for TiO2 is approximately 3.2 eV (different sources report 3–3.5 eV, depending if the TiO2 is in the rutile or anatase form), requiring photons with wavelengths less than about 400 nm. This energy requirement is right on the edge of usable visible light and therefore either violet or ultraviolet photons are required to mobilize electron–hole pairs in TiO2. This is unfortunate since most photons hitting the Earth are longer in wavelength as illustrated from Fig. 2. For this reason, there have been many attempts to improve on the efficiency of the photocatalytic water splitting process. Since Honda and Fujishima’s initial discovery, a number of architectures for achieving efficient photocatalytic water splitting using both ultraviolet and visible light have been developed. However, the overall quantum efficiencies of these architectures have been less than stellar (less than 10 % for catalyzing Eq. 3) (Osterloh 2008), and wide-scale utilization has still not been achieved. For solarbased water splitting to be practical, several goals must be met. One is that the photocatalyst must efficiently adsorb solar radiation. TiO2, for example, requires UV light, while most of the sun’s photons have energy in the visible region of the electromagnetic spectrum (or longer wavelengths) as shown in Fig. 2. The band gap of the photocatalyst must also be tuned so that both the reduction and oxidation processes necessary for water splitting are energetically possible. This requirement is indicated in Fig. 4 with dotted lines intersecting the various photocatalyst materials for these two processes. Another consideration is that these reduction and oxidation reactions be spatially separated to prevent recombination of the freshly produced H2 and O2. This last requirement needs clever engineering of the photocatalytic material and is one reason for the large number of publications in this area each year. Excellent reviews summarize the extensive literature that has been amassed over the past few decades on the subject of photocatalytic water splitting. These reviews detail the various photocatalytic materials employed and the clever architectures that have been engineered to improve the efficiency of this process. Table 1 catalogs a number of the reports described in detail in these literature reviews (Osterloh 2008; Kudo and Miseki 2009; Yang et al. 2005; Navarro et al. 2009; Zong and Wang 2014; Vaneski et al. 2014; Abe 2010; Hernández-Alonso et al. 2009; Kudo et al. 2004; Xie et al. 2013; Zhang and Guo 2013; Janáky et al. 2013). The band gap of the photocatalyst material and the light source employed to mimic solar radiation in most cases are listed. Also included in Table 1 are the H2 and O2 activities reported from these studies. High-powered mercury (Hg) and xenon (Xe) arc lamps are commonly employed as the light sources in experiments that test the photocatalytic ability of newly developed materials. It is not feasible to use actual solar radiation in experiments to test for photocatalytic activity because a constant flux of a known range of wavelengths is desired so that the photocatalytic responses of different materials can be directly compared. Hg lamps are useful for high-powered, shortwavelength UV excitation, and Xe lamps cover both longer-wavelength UV and are

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Table 1 Materials for photocatalytic water splitting

Photocatalyst Sulfide-based photocatalysts CdS

Band gap (eV)

CdS CdS–ZnS Pt/CdS Pt/CdS:Ag CdS quantum dots–titanate nanosheets hybrid CdS/alumina CdS/CNT CdS/CNT particles and nanotubes CdS/Ag2S nanosheets and nanorods CdS/Al-HMS particles CdS/colloidal rhodium CdS/ETS-4 CdS–glass nanosystem CdS-cluster-decorated graphene nanosheets CdS-incorporated special glass CdS/LaMnO3 particles CdS/M-MCM-41 CdS/Ti–MCM-41 particles and nanotubes CdS/Ti–MCM-41 particles and nanotubes CdS/MgO particles CdS/MoO3 core (MoO3)–shell(CdS) CdS/Ni/NiO/KNbO3 particles CdS/pani particles CdS/silicas rod-like CdS/SrS particles CdS/TiO2

Cocatalyst

Light source

Pt

150 W Hg

Pt/RuO2

450 W Xe

2.35 2.4 2.35 2.9

300 W Hg 500 W Hg 900 W Xe 300 W Xe

H2 activity (μmol/h)

1–10 per 5 mg 2.8 mL/44 h/2.75 mg 250 40 11,440 1,000 per g

Pt

41.3–180.8 819 92.5

Pt

874

Ru Rh

825.9 Low 175 3,570 56,000

Pt

O2 activity (μmol/h)

1.4 mL/44 h/2.75 mg

1,549 595 47.11 250

Pt

875

Pt

290 5,250 150

Pt

299.1 33 615 8.4 (continued)

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Table 1 (continued)

Photocatalyst CdS/TiO2 nanowires and nanoparticles CdS/TiO2 particles CdS/(Pt-TiO2) particles CdS/TiO2NTs nanoparticles and nanotubes CdS/TiO2NTs nanoparticles and nanotubes CdS/Na2Ti2O2(OH)2 nanoparticles and nanotubes CdS/zirconium titanium phosphate particles CdS/zeolite CdS/ZnO CdS/ZnO core-shell nanorods CdS/ZnO CdS–ZnO–CdO CdS/N-doped graphene nanoparticles and nanosheets In-doped CdS on ZrO2 particles Cd1
xZnxS particle Cd1
xZnxS particle with nanotwins Cd1
xZnxS nanoparticles Cd0.1Zn0.9S nanoparticles and microspheres Cd0.1Zn0.9S nanospheres Cd0.2Zn0.8S particles Cd0.2Zn0.8S particles Cd0.5Zn0.5S CdZnS (containg Ag22S)

Band gap (eV)

Cocatalyst

Light source

H2 activity (μmol/h) ~107

O2 activity (μmol/h)

4,224–9,800 2,670 12.7

Pt

2,680

Pt

~1,080

Pt

2,300

ZnS

2,455 1,805 3,870

Pt RuO2 Ru

~6,200 ~75 1,050

Pd

~800 ~850–16,320 17,900 2,640 403.75

21,850

Pt Pt

965–1,260 2,290–3,200 ~350 39062.5 (continued)

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Table 1 (continued)

Photocatalyst Cd0.1Zn0.9S–CNT particles Cd0.5Zn0.5S/TNTs particles and nanotubes Cd0.8Zn0.2S/HNbWO6 Cd0.8Zn0.2S/HNbWO7 ZnxCd1
xS–CuS nanospheres ZnxCd1
xS–CuS nanoparticles nanosheets Reduced graphene oxide–ZnxCd1
xS particles CdS QDs-sensitized Zn1
xCdxS CdS–ZnS CdS–ZnS CdS/ZnS/n-Si CdS–ZnS/silica particles [Pt/(CdS/n-Si)]/ZnS Sr-doped CdS–ZnS nanoparticles Ba-doped Cd0.8Zn0.2S nanoparticles ZnIn2S4 ZnIn2S4 nanoplates and nanotips ZnIn2S4 floriated microspheres ZnIn2S4 microsphere ZnIn2S4 nanosheet flower-like microspheres ZnIn2S4 microspheres (petals/sheets) ZnIn2S4 floweringcherry sphere ZnIn2S4 with irregular lumps ZnIn2S3+m microspheres

Band gap (eV)

Cocatalyst

Light source

H2 activity (μmol/h) 1563.2

O2 activity (μmol/h)

13,200

Pt Pt

~625 536 2,080

Pt

2466.7

1,824

2,128

2.35

300 W Hg

Pt

2283.9 250 1584.8 ~268 647.3 ~500 ~700

Pt

257 10,574

Pt

8,420

Pt

562.25–612.5 766.8

Pt

692

Pt

136.5

Pt

~55

Pt

159.5 (continued)

Photocatalytic Water Splitting and Carbon Dioxide Reduction

2721

Table 1 (continued)

Photocatalyst ZnIn2S4/MWCNTs ZnIn2S4/fluoropolymer particles and fibers ZnIn2S4 microspheres with transition metals Cu-doped ZnIn2S4 microspheres Ni-doped ZnIn2S4 petals CdIn2S4 nanopetals and nanotubes CdIn2S4 nanopetals CdxIn2S4-Zn1
xIn2S4 particles CuInS2 microsphere built by flakes CuGa3S5 particles CuGa3S5 particles CuGa3S5 particles AgGaS2 particles AGa2In5S8 (A = Cu or Ag) AGa2In5S8 (A = Cu or Ag) AgIn5S8 (CuIn)xCd2(1
x)S2 microspheres (CuIn)xCd2(1
x)S2 microspheres (CuIn)xCd2(1
x)S2 microspheres (CuIn)xCd2(1
x)S2 microspheres AgInZn7S9 Zn1
xCuxS Cu-doped ZnS shell structure particles (CuIn)xZn2(1
x)S2 microspheres (CuIn)xZn2(1
x)S2 particles with hexagonal plane

Band gap (eV)

Cocatalyst

Light source

H2 activity (μmol/h) 6,840 ~398.3

Pt

4,000

Pt

757.5

Pt

~45

O2 activity (μmol/h)

6,960 6,476 590 Pt

59.4

Rh NiS Pt Cu: Rh

300 800 1,000 ~3,000 10,666.70

Ag; Rh

3,433.30

Pt

59.4 649.9

Pt

2,456 274.5

Pt

1172.5

Pt

3,133 ~370 ~210

Ru

990.45

Pt

2,280

(continued)

2722

N.I. Hammer et al.

Table 1 (continued)

Photocatalyst (CuIn)xZn2(1
x)S2 particles with nanosteps structure (CuIn)xZn2(1
x)S2 particles with nanosteps structure ZnS-coated ZnIn2S4 microspheres and rod-like grains ZnS–CuInS2–AgInS2 particles ZnS–CuInS2–AgInS2 platelike particles (CuxAg1
x)2ZnSnS4 particles ZnS ZnS ZnS, with AgInS2 or CuInS2 ZnS:Cu ZnS:Ni ZnS:Pb, Cl Tungsten-based photocatalysts (AgBi)0.5WO4 Ag2WO4 AgBiW2O8 AgInW2O8 BiWO4 BiYWO6 Ca2NiWO6 CsTaWO6 HNbWO6 HTaWO6 KInW2O8 Li2CoW2O8 LiCrW2O8 LiInW2O8 MNgWO6 (M: Rb, Cs) MTaWO6 (M: Rb, Cs) NaBiW2O8

Band gap (eV)

3.1

Cocatalyst

Pt

1413.3

Pt

103

Ru

7733.3

Ru

1,208

Ru

~750

Pt Pt or Ru

2.5 2.3 2.3

3.5 3.1 2.8 3.1

Pt Pt Pt Pt, NiOx

2.7

RuO2 Cr2O3-Pt Pt

3.0, 2.6 3.8 3.1 3.1 3 1.6, 2.6 3.3, 2.5, 1.9 3.5 2.4, 2.9 3.8 3.5

Light source

H2 activity (μmol/h) 320

125 W Hg 200 W Hg 300 W Xe

22 per 12 mg 13,000

300 W Xe 300 W Xe 300 W Xe

450 280 40

0.1

O2 activity (μmol/h)

5.8

Pt Pt Pt Pt Pt Pt NiOx NiOx Pt (continued)

Photocatalytic Water Splitting and Carbon Dioxide Reduction

2723

Table 1 (continued)

Photocatalyst NaInW2O8 PbWO4

Band gap (eV) 3.6 3.9

Cocatalyst Pt RuO2

SnWO4 WO3 WO3 WO3 in presence of Fe3+ or Ag+ WS2

1.6, 2.7 2.8

Pt Pt for H2 Pt

ZnWO4 ZrW2O7(OH)2 ZrW2O8 Titanium oxides AgLi1/3Ti2/3O2 B/Ti Oxide

3.3 3.9 4

RuO2/Pt Pt Pt

2.7 3.2

Pt for H2 Pt

BaBi4Ti4O15 Ba:La2Ti2O7 BaLa4Ti4O15 BaTi4O9

3.1 3.8 3.85

Pt NiOx NiOx RuO2

Bi4Ti3O12 Ca0.25La0.75TiO2.25 N0.75

3.1 2

CaTiO3:Rh Cr/Ta:SrTiO3 Cs2La2Ti3O10

3.4–3.5

Pt for H2, IrO2 for O3 Pt for H2 Pt NiOx

Cs2Ti2O5 Cs2Ti5O11 Cs2Ti6O13 Gd2Ti2O7

4.4 3.75 3.7 3.5

None None None NiOx

H+-Cs2Ti2O5 H2Ti4O9 K2La2Ti3O10 K2LaTi3O10 K2LaTi3O10-Au

Light source 200 W Hg–Xe

NiOx Ni, Pt, RuO2 Pt

O2 activity (μmol/h)

24

12

65 300 W Xe 500 W Xe

1,220 per g

1,000 W Xe

0.05 mL/h/10 mg

400–450 W Hg

22

450 W Hg 450 W Hg 200 W Hg–Xe

300 W Xe 400–450 W Hg

400–450 W Hg

None 3.4–3.5

H2 activity (μmol/h)

100 W Hg 400–450 W Hg 450 W Hg 450 W Hg

24 11

8.2 5,000 per g 4,600 per g 33

3.7

0.6 5.5

3 230

8.5 0.21 700

0.11 340

500 90 38 400

198

852 560 2,186

1,131

841 per g

16

Not significant (continued)

2724

N.I. Hammer et al.

Table 1 (continued)

Photocatalyst K2Ti2O5 K2Ti4O9 K4Nb6O17–TiO2 intercalated KLaZr0.3Ti0.7O4

Band gap (eV)

Cocatalyst Pt Pt

NiOx

2.1

La2TiO5

Pt for H2, IrO2 for O2 NiOx

La2Ti3O9

NiOx

La2Ti2O7, doped with Fe, Cr La2Ti2O7:Ba

Pt NiOx

La2Ti2O7:Cr La2Ti2O7:Fe La2Ti2O7

2.2 2.6 3.8

Pt for H2 Pt for H2 NiOx

La4CaTi5O17

3.8

NiOx

M2Ti6O13 (M = Na, K, Rb) Na2Ti3O7 Na2Ti6O13

RuO2

Nb2O5:TiO2 (anatase)

Pt and RuO2

N-doped H2Ti4O9 N-doped K2Ti4O9, KTiNbO5 N-doped TiO2 PbBi4Ti4O15 PbTiO3 Pt/SrTiO3:Cr,Ta Pt/SrTiO3:Rh Pt/SrTiO3:Rh Pt/TiO2 Pt/TiO2 Pt/TiO2

O2 activity (μmol/h)

450 W Hg 3.91

LaTiO2N

Light source

H2 activity (μmol/h) 34.7 4.8

Pt RuO2

400–450 W Hg 300 W Xe

230

116

30

41

400–450 W Hg 400–450 W Hg 500 W Hg

442

Stoich

386

Stoich

400–450 W Hg

5,000

400–450 W Hg 400–450 W Hg 400 W Xe

200 W Hg/Xe 450 W Xe

460 nm

0.3 1.8 1.7 per 0.5 g

Pt 1.9–2.8

H2 activity (μmol/h) 30

0.9 per 0.5 g

125 W Hg 400 W Hg 450 W Hg

550 301 Trace 800

400

450 W Hg

30 46 4,100 19

30 23 2,200 9.5

450 W Hg

730

290 (continued)

2728

N.I. Hammer et al.

Table 1 (continued)

Photocatalyst GaN:ZnO

Band gap (eV)

GaN:ZnO

Gd3TaO7 Ge3N4 H+-CsCa2Nb3O10 H+CsLaNb2O7 H+-KCa2NaNb4O13 H+-KCa2Nb3O10 H+-KLaNb2O7 H+-KSr2Nb3O10 H+-RbCa2Nb3O10 H+-RbLaNb2O7 H1.8Sr0.81Bi0.19Ta2O7

Cr/Rh oxide

3.6

3.88

H2K2Nb6O17 H2La2/3Ta2O7 H4Nb6O17 HCa2Nb3O10 HCa2Nb3O10 In2O3(ZnO)3 In2O3/Cr:In2O3 InP K0.5La0.25Bi0.25Ca0.75 Pb0.75Nb3O10 KBa2Ta3O10

Cocatalyst RuO2

NiO RuO2 Pt Pt Pt Pt Pt Pt Pt Pt None Pt

400–450 W Hg 500 W Hg–Xe 400–450 W Hg 100 W Hg

4

NiOx

2.6

Pt Pt Pt for H2 NiO, Pt Pt

750 W Hg 300 W Xe Hg/Xe 250 W Hg

Pt

450 W Xe

NiOx

400–450 W Hg 450 W Hg 450 W Hg

3.5

KCa2Nb3O10 KCa2Nb3O10

Pt RuOx

KNb3O8, KTiNbO5, CsTi2NbO7 KTaO3

Pt

KTaO3 doped with Ti

Light source 450 W Hg and 300 W Xe 450 W Hg and 300 W Xe 400 W Hg 450 W Hg

3.6

Ni NiO

500 W Hg/Xe 400–450 W Hg 500 W Xe

H2 activity (μmol/h) 1 mmol/h/0.3 g

O2 activity (μmol/h) 0.29 mmol/h/ 0.3 g

1,400 8,300 2,200 18,000 19,000 3,800 4,300 17,000 2,600 250

700 10 3 39 8 46 30 16 2 110

0.4 940

459

220 19 mmol/h/g 78 per 0.1 g 1.1

None 1.3

2–5 per 30 mg Trace amounts 170 100 per g 96 per 0.3 g 420 nm >410 nm 300 W Xe 300 W Xe 1,000 W Xe 1,000 W Xe–Hg >290 nm >290 nm >290 nm >290 nm >290 nm

Light

TEOA TEOA TEOA, NEt4Cl TEOA TEOA TEOA TEOA TEOA, BNAH TEOA, BNAH AA, pyridine AA, pyridine, KCl AA, pyridine, KCl Water TEOA TEA TEA TEA, H2O TEOA, H2O

Electron, proton, additive source

Table 3 Materials for homogeneous photocatalytic carbon dioxide reduction

50

0.1 trace 0.1 0.3 0.1

15 27 48 30 0 20 ~1.2 3 2 – – – 80 ppm 80 80 70 0.5a 2.6

CO (TON)

DMF MeCN DMF DMF DMF DMF

–

DMF DMF DMF DMF DMF DMF DMF DMF MeCN H2O H2O H2O water MeCN MeCN DMF MeCN MeCN

Solvent

4.0 2.0 1.0 2.8 0.7

– – – – – – – 25 14 9b 76b 76b – – – – – –

HCO2H (TON)

0.120

0.07 – – 0.08 –

– – – – – – – – – 0.003 0.025 0.025 – – – 0.05 – –

φ

(Gholamkhass et al. 2005)

(Matsuoka et al. 1992) (Matsuoka et al. 1992) (Matsuoka et al. 1992) (Matsuoka et al. 1992) (Matsuoka et al. 1992)

(Takeda et al. 2008) (Hawecker et al. 1983) (Hawecker et al. 1983) (Takeda et al. 2008) (Takeda et al. 2008) (Hawecker et al. 1983) (Portenkirchner et al. 2012) (Takeda et al. 2014) (Takeda et al. 2014) (Boston et al. 2013) (Boston et al. 2013) (Boston et al. 2013) (Yuan et al. 2011) (Sato et al. 2013) (Behar et al. 1998) (Grodkowski et al. 1997) (Lehn and Ziessel 1982) (Lehn and Ziessel 1982)

References

2746 N.I. Hammer et al.

MeCN MeCN DMF MeCN MeCN DMF DMF DMF DMF DMF MeCN DMF DMF DMF

– – – 5 5 – – – – 157 78 149 316d – 0.8a 0.2a 4 6 4 101 10 3 9 12 40 12 113d –

1,000 W Xe 1,000 W Xe 250 W 300 W Xe 300 W Xe Hg >420 nm >420 nm >420 nm 480 nm 480 nm 480 nm 500 W Xe 300 W Hg

TEOA, H2O TEOA, H2O TEOA TEA TEA TEOA, BNAH TEA TEA TEA TEOA, BNAH TEOA, BNAH TEOA, BNAH TEOA, BNAH TEOA

CoCl2 CoCl2*12 CoCl2*12 10 11 26 27 27 27 28 28 28 29 30

41 41 41 13 13 6 41 43 44 6 6 41 6 –

MeCN

–

–

UV*

DMF DMF DMF DMF DMF DMF DMF DMF DMF DMF DMF DMF

– – 562 671 315 353d 234d – – – – –

170 240 – – 13 315d 358d 207 3,029 1,138 1 1

Hg Hg 500 W Xe 500 W Xe 500 W Xe 500 W Xe 500 W Xe >500 nm >500 nm >620 nm >420 nm >420 nm

17 Bound TEOA, BNAH 18 Bound TEOA, BNAH 19 Bound TEOA, BNAH 19 Bound TEOA, BNAH-OMe 20 Bound TEOA, BNAH 21 Bound TEOA, BNAH 22 Bound TEOA, BNAH 23 Bound BNAH, TEOA 23 Bound BIH, TEOA 24 Bound BIH, TEOA 25 Bound TEA 25 Bound TEA Intermolecular photosensitized catalyst systems CoCl2 13 TEA, MeOH – – – – – 0.062 – – – – – – – –

–

– 0.093 0.04 0.06 0.04 0.03 0.02 0.15 0.45 0.12 – –

(continued)

(Matsuoka et al. 1993; Ogata et al. 1995a) (Lehn and Ziessel 1982) (Lehn and Ziessel 1982) (Hawecker et al. 1983) (Dhanasekaran et al. 1999) (Dhanasekaran et al. 1999) (Gholamkhass et al. 2005) (Schneider et al. 2011) (Schneider et al. 2011) (Schneider et al. 2011) (Takeda et al. 2014) (Takeda et al. 2014) (Takeda et al. 2014) (Tamaki et al. 2012a) (Ishida et al. 1990)

(Gholamkhass et al. 2005) (Gholamkhass et al. 2005) (Tamaki et al. 2012a) (Tamaki et al. 2012a) (Tamaki et al. 2012a) (Tamaki et al. 2012a) (Tamaki et al. 2012a) (Tamaki et al. 2012b) (Tamaki et al. 2013a) (Tamaki et al. 2013b) (Schneider et al. 2011) (Schneider et al. 2011)

Photocatalytic Water Splitting and Carbon Dioxide Reduction 2747

41 41 41 42 42 13

42 40 13

13

13

38 39 13

13

13

30 30 30 31c 31 32

33 33 34

34

34

34 34 35

36

37

TEA, MeOH

TEA, MeOH

TEA, MeOH TEA, MeOH TEA, MeOH

TIPOA, MeOH

TEOA, MeOH

TEA TEA TEA, MeOH

TEOA BNAH, H2O BNAH TEA TEA TEA, MeOH

Electron, proton, additive source

UV*

UV*

500 W Hg 500 W Xe UV*

UV*

5.0

5.6

0.3 0.3 5.6

13

10

140 ~55 4.8

>420 nm >420 nm UV* UV*

158 158 100. Interestingly, 33 was also paired with anthracene 40 to give the highest TON values observed with an organic sensitizer. It should be noted that 33 was recently shown to operate as a photocatalyst independent of a photosensitizer for 30 TON (Bonin et al. 2014b). With the exception of Neumann’s RWGS reaction catalyst, the above systems have used an organic electron and proton source. These are often present in solvent quantities as amine additives (TEA and TEOA, typically 1:5 with the listed solvent). However, several researchers have noted that addition of a second electron/proton source has resulted in substantially higher reactivities. These additional sources are often suggested to be a co-catalyst which received electrons from the stoichiometric amine reductant and delivers them efficiently to the photosensitizer or catalyst. The most commonly observed sources are ascorbic acid (AA), 1-benzyl-1,4-dihydronicotinamide (BNAH), and most recently, 1,3-dimethyl-2-phenyl-2,3-dihydro-1Hbenzo[d]imidazole (BIH). Care must again be taken concerning the background reactions associated with AA which can decompose to CO. BIH has been shown to directly lead to a >10x increase in catalyst turnover numbers and a threefold increase in already high ϕ values (Tamaki et al. 2012b, 2013a). BIH has led to some of the highest quantum yields and TONs to date and will likely find utility in further studies.

Future Directions Photocatalytic water splitting and photocatalytic carbon dioxide reduction each offer the promise of cheap and plentiful sources of energy for society’s future. In addition, the transformation of carbon dioxide from a harmful waste product to usable energy source is a win/win proposition. However, the development of efficient

Photocatalytic Water Splitting and Carbon Dioxide Reduction

2751

photocatalytic materials that make either of these processes viable on large scales has not been realized. With such a clear and potentially substantial payoff, many synthetic chemists have been attracted to this problem. In this very active field, advances are constant as the search for an ideal photocatalyst continues.

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Simultaneous CO2 and H2S Sequestration by Electrocatalytic Conversion for Chemical Feedstock Synthesis Nosa O. Egiebor and Jonathan Mbah

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Electrochemical CO2 Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aspen PlusTM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Membrane Electrode Assembly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Design and Stability Study of Cathode Electrocatalysts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cost Analysis of Electrochemical Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Splitting of H2S Over a Solid Membrane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Design and Composition Ratios of Supported Electrocatalyst . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

This paper addresses the development of an innovative ionic membrane consisting of electrocatalysts and electrolyte assembly that can be used in an electrochemical cell to produce useful chemicals via simultaneous splitting of hydrogen sulfide (H2S) and carbon dioxide (CO2) content feedstock. The cell consists of an endurance membrane electrode assembly (MEA) material with CO2 and H2S feedstock and operates near 120–145
C. Thus, a benign method of CO2 mitigation is achieved, and at the same time useful chemicals are produced from two pollutant gases. We have successfully conducted a preliminary study in

N.O. Egiebor Department of Chemical Engineering and Division of Global Engagement, The University of Mississippi, Oxford, MS, USA e-mail: [email protected] J. Mbah (*) Department of Chemical Engineering, Florida Institute of Technology, Melbourne, FL, USA e-mail: [email protected]; [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_88

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our laboratory. The overall Gibbs energy, ΔG, of the process is (49.27 kcal/ mol), with a net energy output of about +1.06 V per mole. The instability of the cathode electrode due to the poisoning of electrode materials, corrosive aqueous media, and the chemistry nature of the electrode kinetics can be addressed by implementing electrocatalyst design scheme, which takes into consideration the location of the active ingredients and support materials of the electrocatalyst in order to enhance activity, stability, and selectivity. The aim is to research, formulate, and design anode and cathode electrocatalyst materials which are not susceptible to degradation in corrosive aqueous environment. Solid electrolytes from cesium hydrogen sulfate and from NafionTM family that conducts only hydrogen protons with added nanoscale hygroscopic oxide (silica) to maintain their integrities were studied. Operation at high pressures ensured that the membrane remained hydrated. Proper positioning of active and support materials during catalyst impregnation will eliminate any catalytic poisoning of active materials.

Introduction Carbon dioxide (CO2) and hydrogen sulfide (H2S) are both greenhouse gases and pose a challenge to the modern society where environmental pollution has to be minimized to an acceptable level. CO2 reduction over aqueous media in electrochemical cells has been reported in many literatures (Fujita 1999; Gattrell and Gupta 2006), but to date no report on simultaneous oxidation and reduction techniques for H2S and CO2 containing gases using solid media is available. There are so many disadvantages inherent with using aqueous media, for example, solubility issue of CO2 with decrease in temperature is a major drawback with aqueous systems. This project tends to propose a novel technique of simultaneously splitting CO2 and H2S containing gases into useful chemicals via a solid membrane. Since both H2S and CO2 often occur together in petroleum and natural gas resources and are major by-products of integrated gasification combined cycle (IGCC) power plants, a technique that can simultaneously split both gases and at the same time produce a valuable energy fuel resource is certainly very desirable. Such a technical advancement will invariably contribute significantly to CO2 sequestration, and toxic H2S gas utilization for clean energy production. The concentrations of H2S present in natural gas generally range from trace amounts to more than 80 %. Caldeira et al. (2003), while CO2 is the main end product of fossil hydrocarbon combustion for energy. Currently, CO2 and H2S are separated using a double-absorber Selexol process which preferentially removes H2S as product leaving CO2 as a separate product stream. Sequestration of CO2 in geological formations includes deposition in oil and gas reservoirs, unmineable coal seams (due to seam thickness, depth, and structural integrity), and deep saline reservoirs, such as in oceans. This approach takes into consideration that many of the large emitters of CO2 are sited near geological formations that can be tailored into storage facilities. In the case of oil and gas

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reservoirs, additional revenue can be generated from enhanced oil recovery with carbon dioxide injection. Given the perspective of this program, this method will provide a low net cost as a result of the enhanced oil recovery. However, the studies are still being conducted to understand the utility of the technique for carbon dioxide sequestration and the behavior of injected CO2 over time in these depleted oil wells. Such studies have included the determination of the extent to which the CO2 moves within the geological formation, and what physical and chemical changes occur to the formation when CO2 is injected (Wise et al. 2009). The adsorption of CO2 in coal beds to displace methane due to its higher adsorptivity than methane provides another possible technical alternative to CO2 sequestration, but limited researches have been conducted in this area (Grimes 2005). which are not sufficient to justify this approach since sequestration capacities of these basins are yet to be quantified. Similar to the enhanced oil recovery, the recovered methane provides a value-added product stream to the CO2 sequestration process. In comparison, the saline formations do not generate any valueadded by-products but do have higher storage capacity for injected CO2. The key issues in these programs are the safety of CO2 storage in saline formations and perhaps potential and emerging environmental problems (Clarkson et al. 1997; Bachu and Adams 2003). Despite the modest successes recorded by these programs, minimizing CO2 air pollution and emission is still a major concern because the long-term effects of these methods are not yet clear. Rock layers may be weakened as a result of formation of carbonaceous acid if CO2 happens to react with underground water. The recent recorded events of oil spillages in our high seas and oceans, worldwide, is a reminder that we ought to be cautious of the adverse effect that may proceed from the enhanced oil recovery and other nondestructive CO2 sequestration approaches. The electrochemical approach proposed here, and described in the sections that follow, has the potential to avoid the major drawbacks associated with current approaches for carbon dioxide sequestration. Electrochemical carbon dioxide sequestration method has also been considered by many researchers (Pe´rez-Rodrı´guez et al. 2011; Kaneco et al. 2006a). Some of the electrochemical approaches make use of aqueous media while others consider solid media. The use of electrochemical conversion to split CO2 has shown to produce carbon monoxide and formic acid in aqueous solution in the presence of most flat metallic electrodes (Kaneco et al. 2006b). Nevertheless, it has been proven that only copper is a suitable electrode for the formation of hydrocarbons such as methane and ethylene, which can be used as fuel gases (Lee et al. 2011; Li and Oloman 2007; Chang et al. 2009). High current yields were only achieved with large overpotentials (1.5 V vs. SCE). Some of the Faradaic yields exceeded 90 %. The primary reduction intermediate was proposed to be CO, while weakly adsorbed onto the Cu electrode, interfered with the cathodic hydrogen production reactions. The adsorbed CO was thus reduced to hydrocarbons and alcohols, with the yields increasing with more negative potentials. However, the temperature of operation must be low enough to obtain significant product efficiencies since the solubility of CO2 decreases with increasing temperature. Owing to the freezing temperature of

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water, few reports have dealt with the electrochemical reduction of CO2 in an aqueous solution at less than 273 K. As a result of the relatively low solubility of CO2 in aqueous solutions, methods for increasing its solubility have to be sought. A possible solution is to perform the electroreduction at high pressures or in nonaqueous solutions. Formation of methane, methanol, CO, and formic acid has been reported by electroreduction of CO2 with H2. This process requires an enormous amount of overvoltage. It has been hypothesized that using hydrogen radicals instead of hydrogen molecules to react with CO2 will circumvent this problem of overvoltage encountered. Hydrogen radicals are very reactive and can easily attack CO2 to form methane. The use of oxygen selective membranes has also been applied to split CO2 into C and O2 or partial conversion to CO and ½O2 by noncatalytic and catalytic means (e.g., thermal, electrochemical, radiolytic, etc.), followed by subsequent removal of carbon deposits in the reactor (Bockris 2005; Toyir et al. 2001; Ordorica-Garcia et al. 2006). Reverse water gas shift and Fischer Tropsch reactions were also considered using bimetallic catalyst. In this approach, the first catalyst initiates the conversion of CO2 to CO, and the second catalyst facilitates the conversion of CO to organic compound (Hoek et al. 1985) through Fischer-Tropsch synthesis. It is worthy to note that electricity generation accounts for 42 % (2397.3 millions of metric tons) of the total CO2 emissions in the USA alone excluding emissions from US territories in 2007 (Rayne 2008). The two IGCC power plants in the USA each have a capacity of 250 MW. Currently, CO2 and H2S are separated using a double-absorber Selexol process which preferentially removes H2S as product leaving CO2 as a separate product stream (Gomberg et al. 1984; Ku et al. 2005). These two by-products can subsequently be utilized as feedstock to an electrochemical cell system for useful chemical synthesis. Although the cost of electricity (COE) is less for an IGCC plant with CO2 and H2S cocapture compared to those IGCC plants that capture 80 % CO2 and H2S separately (5.48 and 6.67 US¢/kWh) respectively, the sale of methane and sulfur will eventually close this gap (Klara and Wimer 2007; Hockstad and Cook 2009). Based on the review of the available options, the chemistry provided by simultaneous splitting of H2S and CO2 can provide a cost-effective solution, provided the electrode kinetics can be achieved at low cost. Our starting electrochemical feedstock will be procured from CO2 and H2S vendors.

Electrochemical CO2 Reduction Aspen PlusTM Varieties of commercially available process simulators, such as Aspen PlusTM, can ease the analysis of an electrochemical system. Electrochemical system may include feed preprocessors, heat exchangers, turbines, bottoming cycles, etc., all of which can be very effectively modeled in process simulation software

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EJECTOR2 FCO2 EJECTOR1 FH2S

HEATER 1

CO2

H2S ANODE

+

CATHODE

Q2

Q3

H

RCO2

Q Q1

SSPLIT2 PRODUCT2

PRODUCT1

SSPLIT1 RH2S

CH4, H2O

SULFUR

Fig. 1 Aspen PlusTM electrochemical cell model flowsheet. Dotted lines represent energy streams. The process involves passing H2S through the anode compartment of the electrochemical cell to generate H+ and electron. At the cathode compartment, CO2 is reduced in the presence of the electron and H+ to product

(Campanari 2001; Ersoz et al. 2006; Aspen PlusTM 2010). The concept is shown in Fig. 1. Fresh H2S (FH2S) and unreacted H2S (RH2S) from the anode chamber are mixed in the block called EJECTOR 1 and fed to the anode compartment where it contacts the catalytic anode and hydrogen proton selective membrane. The H2S then split into hydrogen protons, electrons, and elemental sulfur. The sulfur flows out of the anode chamber as a low-viscosity fluid at temperature of operation (120–145
C). The solid membrane is impermeable to the electrons which are then forced through the external circuit as a heat duty (Q3) via the electrode. The hydrogen protons migrate through the solid membrane as hydronium ion and at the catalytic cathode combine with the electrons and fresh CO2 (FCO2) feed that was mixed with unreacted CO2 (RCO2) from the block called EJECTOR 2 to form methane and water. The heat duty, Q3, appears as available energy which is used to drive the system since the process is highly exothermic. The overall Gibbs energy, ΔG, of the process is (49.27 kcal/mol), with a net energy output of about +1.06 V per mole, as shown in Eq. 1, because of the favorable thermodynamics of water formation. 4H2 S þ CO2 ! CH4 þ 2H2 O þ 4SðlÞ ð2FaradaysÞ@ΔG ¼ 49:27 Kcal=mol@400 K

(1)

The outcome of the process simulation using AspenPlusTM package whose schematic is shown in Fig. 1 provides viable information on the proposed approach. One of the benefits of using the developed Aspen PlusTM model is that sensitivity analyses can be performed in an easy and time-saving manner, which helps to understand the effects of variations of the operating parameters on the

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1.02

1.0 0.82 0.8 0.62 0.6 0.42

0.4

0.22

0.2

Current density (A/cm2) Fuel Iput (cm3/min)

Efficiency (h) and Voltage (v)

1.2

0.02

0.0 0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Uf Efficiency

Current Density

Fuel Input

Voltage

Fig. 2 Aspen PlusTM simulation: effect of fuel utilization factor (Uf) on the cell current density, cell efficiency, and fuel input for the simultaneous splitting of CO2 and H2S feedstock. This is based on 4:1 H2S to C content feed

electrochemical cell’s performance. Figure 2 illustrates the results of sensitivity analyses performed using Aspen PlusTM. The utilization factor (Uf) is one of the most important operating parameters for most electrochemical cells and has significant effects on the cell voltage and efficiency. The utilization factor is defined as Uf = vH2S, consumed/vH2S,equivalent, where vH2S, consumed is the volumetric flow rate of H2S consumed in the electrochemical reaction at the anode compartment. However, this analysis is based on 4:1 molar ratio of H2S to C consumed. This is the preferred possible ratio for a galvanic process to proceed based on reaction Eq. 1. The electrode design will help balance the cost-effectiveness of the overall process. The effects of fuel utilization on the cell voltage, cell efficiency, current density, and required fuel input for H2S/CO2 splitting electrochemical cell are shown. Current density is a direct measure of the rate of electrode kinetics. If Uf is increased from 0.4 to 0.95, the cell voltage will increase because the fuel is more depleted. The current density will increase, which can be realized by increasing the CO2 flow at the cathode, resulting in more H2S being consumed. Three major requirements for the success of this operation are identifiable: 1. The issue pertaining to cathodic electrode degradation needs to be resolved before meaningful progress is made. 2. Designing good electrode configurations for the cathode such that CO2 can easily be activated and be selective to the desired end products is another issue that needs to be addressed.

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3. Fabrication of an effective membrane electrode assembly (MEA) system that has good mechanical integrity, fast electron transport, and a good ionic conductivity.

Membrane Electrode Assembly These requirements can be fulfilled by (a) considering the effect of electrocatalyst design, which considered the location of the active ingredients and support materials during electrocatalyst formulation and their composition ratios in order to enhance activity, stability, and selectivity; (b) utilizing a solid electrolyte with good ionic conductivity (Nafion@ families 0.1 S/cm around room temperature) or cesium hydrogen sulfate, CsHSO4; and (c) an innovative MEA which will consist of an anode with added nanoscale hygroscopic oxide (silica), a cathode either with or without added nanoscale hygroscopic oxide, with the solid electrolyte sandwiched between them as shown in Fig. 3. The nanosilica particles also play a role in water adsorption. When the water produced by electrochemical reaction at the cathode back-diffuses from cathode to anode, the silica, which has hygroscopic property, will adsorb the water. The water back-diffusion process also lends benefits by hydrating the membrane. As a result of the formation of strong absorption bonds between the water molecules and silica due to Van Der Waals forces, elevated temperatures cannot desorb the water adsorbed onto silica (Miyake et al. 2001). The silica at the cathode tends to retain the water which subsequently keeps the membrane from dehydrating. This self-hydrating membrane electrode assembly technique will enhance the system performance without external humidification. At our temperature of operation (120–145
C), sulfur is a low-viscous fluid and can flow out of the electrolytic cell without hindrance. The electrochemical system will employ solid-state electrolyte that transports only hydrogen proton or hydronium ions at operating temperature. Their ionic conductance is based on H+ protons being transported as hydronium (H3O+) ions

Fig. 3 Schematic of membrane electrode assembly (MEA) for CO2 and H2S splitting

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Fig. 4 Schematic of electrochemical cell

and have been tested for their good ionic conductivities. Membrane surfaces are modified with nanoscale hygroscopic oxide (silica) to prevent H2O product from back-diffusing from cathode to anode with added advantage of keeping the membrane hydrated for easy transport of H3O+ ions. The electrochemical cell schematic is shown in Fig. 4 and the experimental setup for the simultaneous splitting of H2S and CO2 in Fig. 5. Besides the membrane, the MEA is composed of two electrodes as electrocatalytic layers and two gas diffusion layers (GDL) made of carbon materials (see Fig. 3).

Design and Stability Study of Cathode Electrocatalysts The electrocatalytic materials for the cathode can be selected to mimic what is obtainable in photosynthesis in plants where CO2 is converted into organic compounds in the presence of H2O using the energy from the sun; the hydrogen is split into its protons and electrons and used to generate chemical energy. In photosynthesis, the CO2 molecule is initially bonded to nitrogen atoms, making reactive compounds called carbamates (Gust and Moore 1989). These less stable compounds can then be broken down, allowing the carbon to be used in the synthesis of other plant products, such as sugars and proteins. In the electrochemical cell, the overall cell reaction potential will supply the energy that splits the CO2 while sunlight provides the energy during photosynthesis in plants. In the electrochemical process, the electrical potential provides the driving force necessary to convert CO2 into methane and water at the cathode compartment by using the hydrogen protons and electrons generated from H2S split

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Fig. 5 Experimental setup of CO2 and H2S splitting system

Table 1 Postulated cathodic reaction mechanism for methane synthesis

M1 ! M1 xþ þ xe

(1)

xH2 O ! xHx þ xOH

(2)

xe þ xHþ ! xH

(3)



M2 þ xH ! xM2  H

(4)

CO2 þ xM2  H ! CH4 þ 2H2 O þ xM2  H

(5)

M1 þ M2 þ xH2 O ! CH4 þ 2H2 O þ xM2  H

(6)

at the anode compartment in the presence of highly active bimetallic electrocatalysts (M1 and M2). The postulation is that in a first step, the catalyst enabled the CO2 to form a reactive carbon monoxide (CO) species and oxygen atom. The catalyst’s next useful step is to enable the hydrogen protons to grab the very highly reactive CO species from the CO2 split, producing methane. The oxygen atom from the split reacts with other protons to produce H2O. Thus CO2 is used as a source of chemical synthesis. We have in Table 1 postulated a mechanism for CO2 conversion to methane at the cathode as pertaining to our electrochemical synthesis. A bimetallic catalyst (M1 and M2), in which one metal acts as the electron donor for the production of hydrogen radical while the other acts as a catalyst for the reduction of CO2, was formulated using impregnation method to serve as the cathode electrocatalyst. At the cathode, metal M1 converts the migrated hydronium

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ion from the anode reaction to hydrogen with subsequent conversion to hydrogen radical. The hydrogen radical is adsorbed locally onto another metal (M2) of known catalytic activity toward CO2 hydrogenation. The advantage is that other intermediates formed will be reduced by the highly active hydrogen radical/metal hydride formed. Electrocatalyst M1 will be chosen such that it can form a galvanic couple with electrocatalyst M2; in that case, the reaction rates would further be enhanced since the process would circumvent the need for an external electric field. Certain transition metals have these capabilities. Depending on the electrode design, the end product may be methanol or methane or other hydrocarbons. The challenge is to design a suitable electrode system that is compatible with electrolyte membrane and selective toward the production of methane and water and not susceptible to degradation in corrosive aqueous environment. The solubility of CO2 in water decreases with increase in temperature which implies that at the temperature of operation water produced will not be in solution with CO2. More also, the hydration equilibrium constant is small (1.7  103), hence CO2 remains as molecules, given that the rate constants are 0.039 s1 for the forward reaction (CO2 + H2O ! H2CO3) and 23 s1 for the reverse reaction (H2CO3 ! CO2 + H2O). The water produced will be used to hydrate the membrane instead. At the anode, the electrolytic splitting of H2S occurs very easily since H2S possesses a very low Gibbs energy of formation (ΔG = 8.9 kcal/mol @ 145
C), so a small amount of electrical energy can split it into elemental sulfur and hydrogen proton (Mbah et al. 2008). This initial energy demand is subsequently compensated by the overall Gibbs free energy of the process (ΔG = 49.27 kcal/ mol). While the primary means of splitting H2S and CO2 in this application appears to be electrochemical, the elevated temperatures at the membrane interface where CO2 is adsorbed and subsequently reacts also appears to be indicative of potential thermal catalytic processes.

Cost Analysis of Electrochemical Process Electrolytic splitting of the extracted CO2 and H2S can yield sulfur, methane, and water. This process is illustrated in Figs. 1 and 2. The value of the methane makes the system more profitable. The energy benefit of electrolytic splitting of the CO2 and H2S is shown in Eq. 1. The energy costs required to do it electrochemically are significantly low when compared to other electrochemical methods. As a result, this is potentially such a cost-effective procedure that it can have a positive influence on the cost-effectiveness of IGCC energy. This is illustrated by the conceptual economic analysis in Table 2 for IGCC energy (Krakow et al. 2006) initially developed for hydrogen production but modified herein for methane production. It considers the plant capital cost and life, the operating and maintenance costs, and the offsetting revenue from the sale of sulfur to determine the cost of methane. The cost of $137/t of sulfur for performing the Claus process exceeds the $63/t market value of the sulfur. The $74/t difference is a penalty that operators currently

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Table 2 Economic analysis of hydrogen sulfide/carbon dioxide splitting in an IGCC power plant Power plant parameters IGCC Plant capacity (Gross MW) On line (Days/year) Coal consumption (Tons/day) Coal sulfur content (%) Electrochemical plant investments Apparatus to remove carbon dioxide Electrolyzer Balance of plant Total electrochemical plant investments Annual capital and O&M costs Annualized capital costs Labor Catalysts, water and other operating costs Electricity Total annual capital and O&M costs Methane production costs Costs to produce 1 Ton of S + 125 lb. of H2 Avoided cost of claus process/Ton of S Net production cost of 1 lb. of H2 Net production cost of 1 lb. of CH4 Gas Market price of sulfur ($/LB) Market price of CH4 ($/LB) Cost of electricity US$/kWh Gross profit ($/LB.)

315 335 63 2.5 $ 1,350,000 $ 6,460,000 $ 3,325,000 $ 11,135,000 $ 1,500,000 $ 525,000 $ 40,000 $ 2,500,000 $ 4,565,000 $ 215 $ 137 ($ 0.63) ($ 0.63) $ 2.50 $ 0.08 ($ 0.07) $ 1.25

pay to get rid of the hydrogen sulfide by-product gas. This penalty would be avoided by using the electrochemical/electrolytic process where the total value of the two products (sulfur and methane) exceeds the cost of the electrochemical processing. Methane costs will vary based on location and also by the quantity. The $1.25/lb. profit on the methane and sulfur increases the cost-effectiveness of IGCC energy by over $1/MWh. This is achieved without claiming any economic credit for purifying the CO2 in the acid gas to make it more suitable for splitting.

Splitting of H2S Over a Solid Membrane The electrochemical system is operated near (120–145
C) using a solid electrolyte membrane. Natural separation of the H2S gas, CO2, liquid sulfur, CH4, and H2O occurs in such a system. Hydrogen sulfide introduced at the anode compartment is electrolyzed at the surface of the solid electrolyte producing hydronium ions that pass through the electrolyte and liquid sulfur that pools at the bottom of the positive compartment from which it is withdrawn through a drain. The pool of liquid sulfur

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Fig. 6 (a) Current density versus voltage generated, (b) SEM image (25.0 kV  40 500 pm) of electrolyzed pellet of CsHSO4 membrane with layers of 65 wt% sulfur deposit

forms a barrier that keeps H2S away from the drain. Figures 6a, b show the current density/voltage relationship and the resulting SEM spectrogram of electrolyzed sulfur by wt% in the electrochemical splitting of H2S to elemental sulfur over a solid membrane using anodic electrocatalysts comprising of ruthenium (IV) oxide/ cesium hydrogen sulfate/pt black/ p-Dichlorobenzene and cathodic electrocatalyst comprising of platinum black/p-Dichlorobenzene. The oxidation of H2S to H+ and sulfur ( H2 S ! 2Hþ þ 2e þ 1=8 S8 ) over a supported metal component is an important step involved in the splitting system. Most noble metal catalysts such as Pt, Pd, Ru, and Ir have high selectivity toward H2S splitting. Noble catalysts are expensive, so augmentation is carried out by formulating metal composite using more of the less expensive materials from other groups to serve as the support materials and less of the expensive materials as the active ingredients. If dispersion of the active materials is carried out effectively during impregnation, then less quantity of more expensive materials can be utilized compared to using bulk active materials. Nevertheless, choice eletrocatalytic materials must have high density of catalytic active sites and not susceptible to poisoning. Other potential electrocatalysts can be selected from both non-noble and noble transition metals and their bimetallic alloys and base metals. For the anode configuration, electrocatalyst precursors could consist of noble and non-noble metals of transition elements or their compounds and base metals. In some cases, main group elements and their compounds may be included. Impregnation technique is used in electrocatalyst synthesis from these precursors because it enables proper control of electrocatalyst design parameters – activity, stability, regenerability, and selectivity. These precursors include salt solutions of CuSO4  5H2O, RuC13, H2PtC16, hydrated copper chloride, hydrated zinc oxide, Pd(NO3)2, NaOH solution, PdO.nH2O, aluminum oxides, hydrated nickel chloride, iridium (III) chloride hydrate, p-Dichlorobenzene, ruthenium (IV) oxide, and hydrated cobalt chloride.

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These materials have proven to possess excellent catalytic properties toward H2S oxidation and/or CO2 reduction. Electrocatalyst formulation using these precursors focuses on increasing the catalytic active sites and altering of the surfaces of the materials, harnessing their properties to products that have good mechanical strength at operating conditions since material integrity is an issue as discussed in the previous section. The resulted electrocatalysts after impregnation and calcinations provide the required activity, selectivity, and stability needed for both the cathode and anode reactions. It has been shown that even though copper electrode is suitable for the formation of hydrocarbons such as methane and ethylene from CO, it lacks stability. Thus, improving the stability of copper using this formulation method is desirable.

Design and Composition Ratios of Supported Electrocatalyst Stability of the cathodic compartment is of utmost priority in this design since this is where major degradation is most prominent due to poisoning of active sites. In using impregnation techniques, it is essential to have an understanding of both chemical and physical properties of the support and the chemistry of the impregnating solution in order to control the physical properties of the finished catalyst. Loading of active metals and support materials should be varied in order to obtain optimum dosage. However, trade-off between catalyst activity and stability should be expected. Changes in selectivity can also arise from changes in intrinsic chemical activity of the active component. Typically this can be affected by use of multicomponent catalysts in which case the location of the difference components ideally should be the same. Poisoning of the catalyst by impurities introduced with the reactants can often be minimized by placing the active material deep within the catalyst support structure, and since most catalyst supports are also good absorbents, poisons frequently can be selectively removed by such absorption before reaching the active surface. A catalyst design modification would be the deposition of a poison-resistant catalyst component close to the surface and a poison-sensitive component deep within the support. The poison resistance location of the active component becomes a critical factor in proper catalyst design. The use of electron probe microanalysis (EPMA) will provide information on the location not only of active materials but also potential catalyst poisons. Blockage of the support-pore structure is critically dependent upon the poresize distribution of the support. Normally a correct balance of large and small pores is required; the former to aid reactant transport and the latter to provide the large surface necessary for the optimal dispersion of the active components. Porous carbon material with high activated carbon content as a support material serves this purpose. Characterization of supported catalyst species, particularly with regard to metalsupport and metal-metal interactions, should be carried out possibly using temperature-programmed reduction/oxidation (TPR/O) equipment. The techniques of catalyst preparation involves two simple steps, dispersing the active material in a liquid form and immobilizing this dispersed material as it is

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Fig. 7 (a) Dispersion observed for formulated cathode electrocatalyst (Cu/RuO2) using catalyst design approach; (b) cross sectional view of MEA comprising of the designed electrocatalyst formulated

reconverted to an insoluble solid form. One way of doing this is to allow the material to react with the insoluble support surface. This implies that support surface should be reactive with the soluble active material. This becomes a drawback since the support material is carbon, which has peculiar and variable properties tending to form charge-transfer complexes as an electron donor, but it also can act as a weak cation exchanger by virtue of acidic surface oxide groups. Interactions between the active materials and support in terms of immobilizing the active ingredients on the support surface are either the cationic or anionic exchange with protons or hydroxyl groups on the surface. To enhance the supports cationic exchange, the carbon with γ-alumina together with bonding agents such as alumina, silica, etc. are washcoated before impregnation which then provides the necessary reactive surface for the active ingredients. In this way atomic dispersion of active ingredients is in principle possible. The proton or hydroxyl group is provided by the γ-alumina. Temperatureprogrammed reduction and oxidation will provide valuable guides to the thermal treatment and reduction stages of electrocatalyst preparation. As previously mentioned, copper is a good reduction cathode electrocatalyst but suffers severely from thermal instability at elevated temperature and in corrosive environment. Stability will be improved by supporting it in a high surface material such as high-carbon porous material. Catalyst retention on support materials, regenerability, stability, activity, and selectivity is very important. Cyclic voltammetry potential sweep test should be applied to evaluate the stability of synthesized catalysts. Of equal importance is the weight lost by thermogravimetric analysis using simultaneous DSC-TGA instrument. This is very important since some materials have the tendencies to lose their integrity in the presence of sulfur and corrosive environments as was found. Furthermore, by evaluating the responses of each electrocatalytic material the catalyst loading required and the partial pressures of component gases that provide the best reactivity can easily be found. Figure 7a is a surface morphology view of cathode electrocatalyst formulated by applying catalyst design scheme where poison-sensitive Cu component is

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Fig. 8 (a) Control MEA – interface 1100; (b) MEA with no catalyst design approach nterface 2500; (c) a– interface 10,000; (d) b – interface 5,000

embedded deep within carbon support while poison-resistant component ruthenium (IV) oxide, RuO2, is close to the surface. Figure 7b illustrates a typical MEA fabricated from this electrocatalyst (see also Fig. 3); the cross-sectional view was analyzed for any apparent separation or tearing of the individual layers after several cycles. The image has been annotated to indicate the approximate thickness of each of the layers of assembly, namely, Gas Diffusion Layer  116 μm; Micro Porous Layer  100 μm; Proton Exchange Layer  52.6 μm. At higher magnification, no delamination was observed in MEA fabricated using the designed electrocatalyst. The results of this investigation are summarized in Fig. 6. Mesoporous investigation is shown in Fig. 8. Figure 8a shows the interface between the microporous (electrocatalyst) and proton exchange (Nafion) layers of an MEA which electrocatalyst layer was formulated using impregnation design approach with the noble metal-based catalyst 4 wt% (RuO2) on the surface and 1.6 wt% active Cu embedded deep on the support (control membrane). At lower magnification of 1100, no apparent gap or tearing of the interface was observed at 125
C and varying cell pressures. Figure 8b depicts the same interface in the MEA which electrocatalyst layer was formulated using impregnation method but with no catalyst design approach. This image shows a more pronounced division between the two layers. This feature was very clear when we look at these membrane

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microstructures at higher magnifications, 10,000. Figure 8c shows the control membrane’s interface at 10,000x magnification. A relatively smooth transition is still seen between the layers even at this magnification. In contrast, Fig. 8d shows a distinct channel dividing the two layers at half the magnification. This channel would be enough to increase the ohmic proton exchange resistance of the membrane. This indicates that catalyst design, if monitored properly, provides good promise in eliminating cathode electrode degradation currently faced in many electrochemical applications. Different electrode/electrolyte attachments should be tested since this is a major issue in electrochemical applications that utilize solid electrolyte where delamination of membrane increases the cell ohmic resistances: as interfacial delamination width and area fraction increases, the ohmic resistance increases. Characterization of MEA may include the use of X-ray diffractometer (XRD), scanning electron microscopy (SEM), simultaneous differential calorimetrythermogravimetric analysis (DSC-TGA), cyclic voltammeter, Quantachrome instruments (BET for specific surface, pore sizes), and electrochemical impedance spectroscopy (EIS).

Conclusion Carbon dioxide and hydrogen sulfide are both greenhouse gases and pose a challenge to the modern society, where environmental pollution has to be minimized to an acceptable level. Since both H2S and CO2 often occur together in petroleum and natural gas resources, and are major by-products of integrated gasification combined cycle (IGCC) power plants, a technique that can simultaneously split both gases is desirable. The advantages offered by electrochemical approach using CO2 and H2S as feedstock to reduce air pollution and at the same time conduct carbon dioxide sequestration cannot be overemphasized, thereby providing a vista to the long-sought method of CO2 mitigation. Currently, CO2 and H2S are separated using a double-absorber Selexol process which preferentially removes H2S as product leaving CO2 as a separate product stream. These two separate streams can be channeled into an electrochemical cell apparatus for production of useful chemicals. This approach is useful in the integrated gasification combined cycle power plants (IGCC), which currently extract sulfur from the process stream as hydrogen sulfide using the Claus Process along with unsequestered CO2 stream. Our process is cost effective and overcomes the energy barrier associated with previous electrochemical processes. At the temperature range of operation (120–145
C), sulfur is a low-viscosity liquid and can flow out of the electrolytic cell without hindrance. Although, the COE is less for an IGCC plant with CO2 and H2S cocapture compared to those IGCC plants that capture 80 % CO2 and H2S separately (5.48 and 6.67 US¢/kWh) respectively, the sale of methane and sulfur will eventually close this gap.

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Future Directions Electrochemical reduction of CO2 into value-added chemicals using renewable energy is one approach to help address CO2 emission as it will recycle “spent” CO2 (carbon neutral cycle) and it provides a method to store or utilize otherwise wasted excess renewable energy from intermittent sources, both reducing our dependence on fossil fuels. Current electrolysis cells accomplish either high Faradaic yield (often >95 % selectivity) for a desired product or reasonable current density, whereas both need to be high for a commercial process. Catalysts for the selective reduction of CO2 into different interesting products have been developed, but catalysts that simultaneously exhibit overpotentials (e.g. 100 mA/cm2) needed for commercial applications are still lacking. The quest for such catalysts could be aided by more fundamental studies focusing on elucidation of reaction mechanisms for distinct catalysts, an area in which reports are few. Novel catalysts have both low overpotential and high activity for CO2 reduction reactions. Few efforts to date have focused on the effects of electrolyte composition on electrochemical CO2 reduction, despite the fact that electrolytes have been known to affect almost every electrochemical process. Electrolyte choice has profound effects on current density, product selectivity, and energetic efficiency in CO2 reduction. More also, CO2 electrolysis is much more sensitive to the structure and composition of the microporous layer. Significant strides will be made to enhance catalyst activity while reducing overpotential. Such efforts will greatly benefit from fundamental mechanistic studies, as well as modeling of new classes of catalytic materials. Fine-tuning the electrolyte composition for a given catalyst offers a further opportunity for performance enhancement. A key opportunity resides in optimization of electrode structure and/or composition.

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Power-to-Gas Michael Sterner

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Need for a Storage Transition in Energy Transition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Storage in the Context of Energy Transition and Flexibility Options . . . . . . . . . . . . . . . . . . . . . Power-to-Gas in the Context of Energy Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Technology Components of Power-to-Gas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Charging Technology Water Electrolysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Charging Technology Methanation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gas Storage Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Storage System Power-to-Gas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Beginnings of Power-to-Gas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . PtG Hydrogen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Power-to-Gas Methane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Efficiency, Potentials, CO2 Emissions, and Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Advantages and Disadvantages of Hydrogen and Methane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Decarbonization with Power-to-Gas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Technical Pathway of Decarbonization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Costs of Decarbonization with Power-to-Gas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Necessary Policy Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Concluding Remark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Changes in the Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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This chapter was originally published in M. Sterner, I. Stadler, Energiespeicher – Bedarf, Technologien, Integration- 2009. Published with kind permission of Springer-Verlag Berlin Heidelberg. All Rights Reserved. M. Sterner (*) Forschungsstelle Energienetze und Energiespeicher (FENES), Fakultät f€ ur Elektro- und Informationstechnik, OTH Regensburg, Regensburg, Germany e-mail: [email protected] # Springer-Verlag Berlin Heidelberg 2014 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_89

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Abstract

This chapter provides an overview on the storage technology power-to-gas for the decarbonization of all energy sectors. Other than “negative emissions” with CCS or biomass, which have clear limits in potentials, costs and environmental benefits, storage and energy conversion technologies like power-to-gas and power-to-x enable the decarbonization by neutralizing the CO2 footprint of all energy services. Via the conversion of renewable electricity into chemical energy carriers like renewable hydrogen or renewable hydrocarbons, the existing fossil infrastructure with vast and sufficient storage and transport capacities can be used with carbon neutral renewable energy. After showing the demand for storage technologies, the technology components of power-to-gas are described, building the basis for the storage system power-to-gas itself that is described in detail, including efficiency, potential, CO2 emissions, and costs. In conclusion, a technical pathway of decarbonization including costs is described for the industrial nation of Germany and necessary policy frameworks are derived.

Introduction No energy system can do without storage. Storage is essential for energy security. Each energy transition needs also a storage transition. Storage will be an essential part of decarbonization worldwide. As several international summits pointed out, we need to complete decarbonization in industrialized nations by 2050. That means the exit of fossil energy carriers such as coal, oil, and natural gas. The good news is that this is actually doable: there is enough renewable energy potential, to shift completely to renewable and clean energy sources. The storage technologies also exist and are ready to be deployed. Decarbonization is possible without CCS and large-scale deployment of biomass by using vastly available wind and solar resources, transformed in biomass-like energy carriers. The technological and economical dimension of the storage technology power-to-gas in a decarbonization scenario is described in the following chapter.

The Need for a Storage Transition in Energy Transition Storage in the Context of Energy Transition and Flexibility Options No energy system can do without storage. Storage is essential for energy security. Each energy transition needs also a storage transition. Storage will be an essential part of decarbonization worldwide. As several international summits pointed out, we need to complete decarbonization in industrialized nations by 2050. That means the exit of fossil energy carriers such as coal, oil, and natural gas. The good news is that this is actually doable: there is enough renewable energy potential, to shift completely to renewable and clean energy sources (Sterner and Stadler 2014).

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Among renewable energy technologies, wind and solar power have proven to be the most cost- and land-use-efficient technologies to harvest the energy that is in our environment. The downside is of course the intermittency of wind and solar power, but there are solutions to this: – Flexible generation (e.g., flexible gas turbines and gas CHPs [combined heat and power]) – Flexible consumption (e.g., demand side integration) – Network expansion – Storage In electricity supply, the exact matching of generation and consumption (loads) is essential for a stable supply. The chain consists of generation, transport via networks, and consumption. First of all, not all electricity from wind and solar generators must be integrated into the electricity system. It is economically not feasible to include the “last” kilowatt-hour, since some power peaks are rather high and the energy contained in those peaks is not enough to refinance the respective flexibility option. Flexible Generation The conventional generation capacities need to be flexibilized: fast ramping will become mandatory to include cheap wind and solar power, which does not follow any market command but is as naturally available as nature is. Fast ramping can be done by gas turbines and gas CHPs but not at the required scale by lignite coal or nuclear plants. The latter require a very high utilization rate over the years to cover their investment-intensive capital cost. Gas turbines are not capitalintensive. So both technically and economically, gas technologies offer the best “fossil” solution for backing up wind and solar. Hydropower and biomass electricity can do the same, but they are as well rather capital-intensive and limited in potential. Flexible Demand: Demand Side Integration Flexibilizing the power consumption is being done for demand side integration, as a combination of demand side response and demand side management, since the 1970s in the form of night heating systems and flexible tariffs. In Germany, there were state subsidies for night heating systems; in Belgium, highways were lit during the night. France shifted the major share of its heating system towards electricity. The goal in each case was to increase the utilization rate of nuclear power plants. Nowadays, demand side flexibility potentials exist at the GW scale, but they need to be market stimulated. It will be mandatory for new electricity consumers like electromobility and heat pumps. These new devices need to be connected and controlled via smart grid technologies in order to stabilize and not destabilize power network operation. The largest advantage of demand side management is the very low investment cost, since the major process is financed separately and demand side management is just an additional function. However, this potential is

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also limited, since the manufacturing of products or consumer needs can be delayed by some minutes or hours, but not for days, if there is no wind and solar power for longer periods. Also, for a safe and stable network operation, a nearly 100 % availability and reliability is necessary. This availability is a challenge for demand side management in industrial applications that follow a different major function rather than the additional function demand side management. Network Expansion The expansion of electricity networks is another flexibility option, which is so far the most efficient integration option in terms of economy and technology, as long as a total underground cabling is not necessary. Wide area networks, like a pan European network, are therefore an essential element of future energy systems. But network expansion also has its limits: it can balance the spatial component of fluctuating wind and solar power but not the temporal component. In addition, public acceptance is not always given. The temporal balancing can only be done by storage. Storage Storage is needed as a flexibility option – today and tomorrow. The stability of today’s system is based on stored fossil energy: coal piles, gas caverns, and so on. This functionality has to be provided also in future energy systems, since wind and solar power may be increased infinitely, due to weather conditions, still up to 80 % of the peaking power of a nation is required as backup capacity. This will be achieved by gas power plants, using the existing gas infrastructure, that offer what has been missing in the power sector: immense storage capacities.

Power-to-Gas in the Context of Energy Storage A storage system consists of three parts: 1. Charging 2. Storing 3. Discharging These three parts can be in one system (e.g., batteries), several parts in one system (e.g., pumped hydro), or even distributed parts over several various sectors (intersectoral energy storage, e.g., Power-to-Gas), as shown in Table 1. These storage technologies can be classified again in different ways: – Technology • Electrical • Electrochemical • Chemical • Mechanical • Thermal

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Table 1 Three parts of energy storage in various applications for electricity storage

Charging

Lithium-ion battery Internally fixed energy and power units

Storing Discharging

Pumped hydro Water pumps Two reservoirs Water turbine

Power-to-Gas Electrolysis (and methanation) Gas storage Gas turbine/vehicle/heating system

– Temporal balancing • Short-term storage • Long-term storage Thermal energy storage is still the cheapest option to store energy and is being used widely, but it is not suitable for electricity storage, since the conversion step is “one way” from power to heat. The reconversion of heat to power is very inefficient and thus not feasible. The focus of the following part is electricity storage. Pumped Hydro, Batteries, and Compressed Air as Short-Term Storage Among electricity storage, pumped hydropower plants is an old, established technology that is very efficient for power storage. It is, however, a classical short-term storage technology, and its expansion is limited to geography, ecological impact in the form of land use, and public acceptance in general. The second option is batteries. Electromobility gives an impressive drive on this technology, which has been used in power plants for ages. Battery power plants are also feasible for electricity grid stabilization: they can react much faster than conventional power plants and therefore balance wind and solar in no time. In combination with renewables, stationary battery systems can take over the stability services of conventional power plants and replace them. There has been a misbelief in the past that the increase of renewables in the electricity grid is limited to 30 %. This is, from an electric engineering perspective, not true: all technologies are available to operate an electric grid even at 100 % renewables. The third option is compressed air, but compared to pumped hydro and batteries, it is not feasible and only two plants in Huntorf, Germany (60 MW charging power), and in McIntosh, USA (50 MW), are in operation worldwide. Pumped hydro and batteries offer a feasible and highly efficient short-term storage option. The drawback is the high cost for capacity and the self-discharging over time in the case of batteries. There is therefore the need for a long-term storage facility, and the gas infrastructure offers this. One standard gas cavern can fuel a gas power plant with 800 MW rated capacity for 3 months. The question remains: how can we use this infrastructure for wind and solar power? The answer is Power-to-Gas. Power-to-Gas as Long-Term Storage and Decarbonization Technology Power-to-Gas is a new storage technology that interlinks the power with the gas sector. It allows in the first step to split water into hydrogen and oxygen via

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electrolysis and the use of renewable power. In the second step, hydrogen is combined with CO2 to form a substitute for natural gas (SNG, synthetic natural gas), which is 100 % compatible with the natural gas infrastructure. The access for renewable energy is then given to millions of households with a gas network connection. The renewable gas (windgas, solargas) can then fuel the necessary backup gas power plants. For short-term balancing, pumped hydro and batteries offer of course much cheaper storage services with double efficiency, but when it comes to long-term storage, Power-to-Gas is the most cost-efficient option: a kilowatt-hour storage capacity costs 200–300 € for batteries and only 0.2–0.3 € for gas storage. With Power-to-Gas, a decarbonization of mobility and nonenergetic use of fossil resources in the chemical industry is possible. A short overview of sectoral and cross-sectoral energy storage units is shown in, embedding the described different pathways and applications of Power-to-Gas within the energy system. This promising new technology is described in the following:

Technology Components of Power-to-Gas Power-to-Gas is an energy storage system that consists of various technologies. The systems are described in section “The Storage System Power-to-Gas” and the necessary technologies in this part. The main part of Power-to-Gas is the charging unit, which contains water electrolysis (section “Charging Technology Water Electrolysis”) and optionally methanation (section “Charging Technology Methanation”). The storage and discharging unit are usually the conventional existing technology parts: salt caverns, aquifers, gas turbines, CHPs, heating units, and CNG (compressed natural gas) cars and hence not described in detail in this chapter but in the main book Energy Storage – Demand, Technologies, Integration at Springer-Editors (Sterner and Stadler 2014). Chemical energy storage is the backbone of the conventional energy supply. Solid (wood & coal), liquid (crude oil), and gaseous (natural gas) energy carriers are different types of energy storage themselves. Also in the energy transition, chemical energy storage plays an important role, especially in its function as long-term storage for the electricity sector but also as a distributor of fuel for mobility and heat. This chapter will, besides the conventional storage technologies, take a deep look into the storage of renewable energies in the form of gaseous (Power-to-Gas) energy carriers.

Charging Technology Water Electrolysis There are three different technologies available for water electrolysis, which are of technical relevance and differ in function, operating conditions, and stage of development:

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– Alkaline electrolysis (AEL) – Proton exchange membrane electrolysis (PEM) – High temperature electrolysis of steam (HTES) or solid oxide electrolysis (SOE) These different electrolysis technologies can be implemented as an atmospheric or a pressurized electrolysis system in various stack designs and plant peripheries, which are described in Sterner and Stadler (2014).

Alkaline Electrolysis (AEL) The alkaline electrolysis of water is a widely proven and well-established large-scale technology. Realized sites were constructed nearby large power plants because of the continuously required power for the electrolysis unit. The largest atmospheric alkaline electrolysis unit in the world with 156 MW nominal power is situated at the Assuan retaining dam in Egypt, with a hydrogen production rate of 33,000 standard cubic meter per hour. The technology is proven and commercially available since many decades. Nevertheless, there is a need for optimization and adoption to the new requirements of fluctuating renewable energies in terms of dynamics and efficiencies. Figure 1 shows the schematic construction and the function of an alkaline electrolysis cell. Water circulates through both halves of the cell, which are separated by an ion-conducting membrane. Potassium hydroxide (KOH) 20–40 % by weight is added to the water to increase its conductivity. Thus, the inner resistances in the cell decrease and the conversion efficiency rises. Porous electrodes with a large surface are located on both sides near the membrane. The decomposition voltage of

Fig. 1 Sectoral and cross-sectoral energy storage units within the energy system (Source: Sterner and Stadler 2014)

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water is 1.23 V. If an ideally equal or realistically higher voltage is applied to these electrodes, the water on the side of the cathode is split into atomic hydrogen and hydroxide ions (HO
), as described by the cathode reaction (Eq. 1). 2H2 OðlÞ þ 2e
! H2 ðgÞ þ 2OH


(1)

The generated atomic hydrogen reacts to molecules, rises, and is separated from the electrolyte. At the same time, hydroxide ions pass through the membrane and react to water and atomic oxygen in the anodic reaction (Eq. 2), releasing an electron. 2OH
! 1=2 O2 ðgÞ þ H2 OðlÞ þ 2e


(2)

The generated oxygen molecules are separated from the electrolyte and extracted. The consumed water has to be refilled, the electrolyte is recycled. Two electrons are required in each half of the cell for the whole reaction (Eq. 3). They are provided by the power source and transported via the closed electrical circuit. H2 OðlÞ ! H2 ðgÞ þ 1=2 O2 ðgÞ

(3)

The cell frame seals the cell against external influences, isolates the electrons from each other, and serves as a carrier for the membrane. The circulation of the electrolyte and hence the homogenous load distribution is ensured by the flow of rising gas bubbles at low loads. At higher loads, an active agitation has to be implemented.

Membrane Electrolysis (PEM) The membrane electrolysis (also called Proton exchange membrane or PEM electrolysis) originates from the fuel cell technology and is based on the inverted processes of a fuel cell. It is better suited for a dynamic and pressurized operation than the alkaline electrolysis and needs less space, but to present, it has only been realized in a rather small kW-scale. A PEM electrolysis cell (Fig. 2) consists of a proton conducting membrane, which is usually permanently fixed on both sides with the electrodes to the so-called membrane electrode assembly (MEA). A solid polymer electrolyte (SPE) like Nafion™ is coated on the electrodes. It is highly porous and accomplishes on one hand the current flow from the bipolar plates to the electrode and on the other hand the transport of water and product gases. The bipolar plates conduct water via engraved canals to the anode and permit the withdrawal of product gases. In addition, they serve to supply a uniform current density distribution over the electrolyte. The PEM electrolysis cell differs fundamentally from the alkaline electrolysis cell in its function. Water is supplied to the anode and split to atomic oxygen and two protons in the anode reaction (Eq. 4) with the decomposition voltage applied.

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Fig. 2 Function of the alkaline electrolysis (Source: Sterner and Stadler 2014)

H2 OðlÞ ! 1=2 O2 ðgÞ þ 2Hþ þ 2e


(4)

The oxygen is withdrawn whereas the protons pass through the membrane and react in the cathode reaction (Eq. 5) with two electrons to form hydrogen. 2Hþ þ 2e
! H2 ðgÞ

(5)

Hence, only the anode side is flushed with water. In theory, hydrogen is only produced in the cathode side of the cell. In reality, this side contains high humidity. Compared to the alkaline electrolysis, where partially residues have to be washed out of the electrolyte, the resulting hydrogen contains far less waste materials and has a higher purity. Therefore, the need for hydrogen purification and treatment after the cell is less in the PEM technology, but it is currently still twice as expensive as the alkaline technology.

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High Temperature Electrolysis of Steam (HTES) In the high temperature electrolysis of steam (HTES), a part of the energy for water splitting is supplied by high calorific heat in the range of 850–1,000  C. The cell voltage can be reduced by 0.5 V to less than 1 V compared to PEM, and alkaline electrolysis and high efficiencies can be realized. The function of the HTES is based on the reverse reaction of the solid oxide fuel cell (SOFC) (Fig. 3). Both halves of the cell are separated by an oxygen ion conducting solid electrolyte, on which the electrodes are applied on both sides. Overheated steam is fed to the cathode and reacts with two electrons to form hydrogen and oxygen ions on the cathode side (Eq. 6). Hydrogen can be extracted, and the oxygen ions diffuse through the electrolyte to the anode, where they react to atomic oxygen, releasing two electrons (Eq. 7). H2 O þ 2e
! H2 þ O2


(6)

O2
! 2e
þ 1=2 O2


(7)

Overall reaction equation:

Fig. 3 Function of the membrane electrolysis (Source: Sterner and Stadler 2014)

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H2 O ! H2 þ 1=2 O2

(8)

All of these three different approaches of electrolysis technologies have their reason and application. The AEL is the most proven one, inexpensive and well established, but needs a lot of space and has not the best efficiencies. The PEM electrolysis is efficient in conversion and space but rather expensive. The HTEL (high temperature electrolysis) is the most efficient technology, using surplus heat from other processes. However, it is also the most complex technology in terms of lifetime and technology readiness level.

Charging Technology Methanation It is possible to transform the electrolytically produced hydrogen with the use of CO2 to gaseous or liquid hydrocarbons. To generate methane, which is chemically the main constituent of and almost identical to natural gas, the methanation synthesis is used. As hydrogen integration in the existing energy infrastructure is limited, further processing with an additional expenditure is appropriate. By processing hydrogen with the following technologies, it is easier to store, transport, and use it.

Chemical Versus Biological Methanation There are two ways of methanation: the chemical and the biological way. The different parameters are described in Table 2. The Sabatier Process Already in 1902, the French chemist Paul Sabatier discovered the transformation of carbon dioxide to methane via a chemical synthesis. Hence, the scientist is the eponym to this chemical reaction, the “Sabatier process.”

Table 2 Different parameters of the chemical and the biological methanation (Sterner and Stadler 2014) Operating temperature in  C Pressure in bar Overall reaction Plant size CO2 gas quality Rate of production

Chemical methanation 200–600

Biological methanation 40–60

5–80 4H2 + CO2 ! CH4 + 2H2O Large plants up to more MW

1–3

High syngas quality and gas upgrading necessary; H2 temporary storage Up to 325 m3/h (Audi e-gas plant, Werlte)

kW scale (up to single digit MW scale possible) No requirements Up to 540 l per day and liter pure culture

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The industrial breakthrough of the CO-methanation succeeded during the oil crisis in the 1970s. In this period, oil prices rose sharply and through the linked price natural gas became more expensive as well. This put a burden on the economy of industrial nations, which were forced to find different solutions. Besides the expansion of nuclear energy, one approach was the production of “synthetic natural gas” (SNG) by gasifying coal to syngas and converting it via methanation to SNG. Especially brown coal was used because of its cheap price and its abundance in industrial nations. The produced gas mixture had a relatively low content of methane and needed to be upgraded before feeding it into the natural gas network. Chemical Reactions The chemical methanation consists of two chemical reactions that run at the same time: the methanation of carbon monoxide (CO) and the water gas shift reaction (WGSR). CO-methanation is state of the art for decades already to gasify coal and was enhanced during the 1960s as explained before. Its chemical reaction proceeds as described by Eq. 9: 3H2 þ CO ! CH4 þ H2 O

ΔHR ¼
206 kJ=kg

(9)

The WGSR produces water and carbon monoxide (Eq. 10): H2 þ CO2 ! CO þ H2 O

ΔHR ¼ 41:5 kJ=kg

(10)

ΔHR ¼
164:5 kJ=kg

(11)

The resulting reaction is described in Eq. 11: 4H2 þ CO2 ! CH4 þ 2H2 O

The negative sign of the molar reaction enthalpy indicates that the reaction is highly exothermic and thus sets energy free, respectively heat. A thermal management, which reliably dissipates the released energy, is necessary to provide an uninterrupted operation. To accelerate the reaction, a catalyst is used. Operation pressure and temperature may vary according to the applied reactor concept, though general conditions of 200–300  C and 20 bar can be assumed.

Sources of CO2 CO2 has to be provided as reactant gas. The following three sources are basically accessible: 1. Extraction from air 2. Fossil sources (coal power plants) 3. Renewable sources (biogas facilities) Theoretically, any exhaust mass flow from industry or any energy supply station as well as ambient air could be used. However, the source has to fulfill the demands of a certain degree of purity as well as being able to provide the necessary quantity.

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Purity is the determining factor, as, e.g., sulfur degrades the catalyst of the methanation. The CO2 flow is mixed with hydrogen in the methanation reactor, and thus, the degree of purity has to be even higher than the CO2 reactant gas flow. The origin of CO2 is relevant due to ecological reasons. Taken from a coal power plant, the plant will improve its carbon footprint, which is good on the one hand. On the other, it is contradictory to the aim of the energy transition, which implies the decrease of fossil energy carriers in favor of an increase of renewable energy carriers. Considering this, the exhaust mass flow from biogas facilities is excellently suitable. The CO2 originates from plants, which collected it during recent years. By contrast, fossil CO2 had been safely stored for thousands of years and thus would additionally pollute the environment. Biomass itself is a low-carbon CO2 source as long as the associated land use is carbon neutral and does not provoke new greenhouse gas emissions by direct and indirect land-use changes. Thus, residual biomass or residues are the ideal biogenic CO2 sources. To separate CO2 from air today is technically complicated and expensive. There are very good starting points at the research and development sides, which will become more attractive in future. Therefore, this is also a considerable eco-friendly source of CO2, as it closes the carbon cycle as well. More details on the origin and use of CO2 are described in section “Power-to-Gas Methane.”

Use of Exhaust Heat Methanation is an exothermic reaction as described in section “The Sabatier Process.” It is recommended to use the exhaust heat of the process to increase efficiency, cost-effectiveness, and improve the carbon footprint. Heat is also generated in the upstream electrolysis; hence, an overall heat management is appropriate. Generated heat can be used for: 1. Internal process heat (purification of gas) 2. Power generation (Organic ranking cycle – ORC) 3. Integration of a heat sink (district heating) The most obvious use is to cover the internal heat demand of the overall process, e.g., in the purification of reactant and resulting gas. However, the process heat also has the necessary temperature level to convert heat to electricity. This could be realized with the use of a conventional steam turbine or alternatively by an ORC or Kalina cycle. However, the operating mode of the complete unit has to be considered. If the primary application of the unit is to store excessive electric energy in the gas network, the conversion of heat into electricity is counterproductive. Feeding the heat into the district heating would be an adequate solution in this case, but appropriate heat consumption throughout the whole year has to be guaranteed. If the district heating cannot continuously distribute and use the heat in summer, operational disruptions at the methanation unit could occur.

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Reactor Concepts Reactor concepts in general have to address two basic demands: – Dissipation of heat (as explained above) to prevent hot spots – A flexible operating method A hot spot is a punctual overheating of the catalyst inside of the reactor. As a result, the catalyst can be deactivated or even profoundly damaged. In both cases, the operation mode is disturbed permanently. The flexible operating mode is necessary to serve the future increase of power fluctuations in the power network, due to volatile renewable energy feed-in. This implies the operation at different levels of load. The reactor mass is critical in this context. Fixed-Bed Reactor In this concept, the gas usually passes through the reactor from the top to the bottom to avoid any swirling of the fixed-bed. The danger of hot spots is rather high compared to other technologies. They have to be eliminated by constant intercooling of the gas. This can be achieved by several heat exchangers placed inside the gas flow or by inserting cold reactant gas. An advantage of this technology is its high availability and reaction time during a cool start, since only the walls of the reactor and the catalyst have to be heated to operating temperature. On the contrary, the process is very sensitive to fluctuations in its load due to a fast cooling down. Fluidized-Bed Reactor The fluid streams through the reactor with a relatively high velocity to swirl up the catalyst. In this way, a swirling layer with fluid-like properties is created. The temperature distribution inside the reactor is homogenous, but the inner walls of the reactor tend to wear out with time due to the swirling layer. A low fluid flow is not able to swirl up the catalyst layer; on the other hand, when operating with high fluid flows, dwell time inside the reactor is too short and there is danger of removing particles from the catalyst. Both situations decrease the possibility of a flexible reactor operation. Three-Phase Reactor The reactor is filled with a fluid containing solid catalyst particles. This is also the reason for the name of the reactor: including the gaseous fluid flow, three states of matter are represented inside the reactor. The fluid is responsible for the thermal management. The main task is to dissipate generated process heat and thus to prevent hot spots. Moreover, heat can be applied in this way from outside to keep temperature on a constant level during operational interruption. However, this is only partly necessary, since the reactor mass is rather high due to a high fluid content. This allows to buffer short interruptions. A disadvantage results from the long warm-up time and therefore less flexibility.

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Gas Storage Technologies Already in the mid-nineteenth century, the construction of the gas infrastructure in Germany began – at first only for town gas – which, after the transition to natural gas in the 1970s, even in the twenty-first century is not finished. From the beginning, it was problematic to adapt the rather constant production of gas to the daily and seasonal fluctuations in the consumption. This was solved by developing gas storage facilities, at first with pressure-less gasometers via spherical gas tanks up to the underground storage with an enormous capacity, which dominates today. In the transition from fossil to renewable energies, the development of storage technologies like Power-to-Gas congruently gains importance and will take its time, as it is still in its infancy.

Gas Holders Aboveground The compressed gas containers explained in this section were developed for the storage of town gas. Only in individual cases they were also used for pure hydrogen. Any subsequent reference to mass storage is based on the requirements in the town gas era. Storage capacities in the future energy economy depending on renewable energies are required to be much bigger. The first mass storage for town gas, the so-called gasometers, worked at a lower overpressure than constant pressure gasometers at a variable volume. A typical example is the liquid seal gasholder, which realized the gas sealing against the atmosphere by water. Later, telescope containers, as seen in Fig. 4, which work with the same basic principle allowed a significantly higher storage capacity. The actual storage container was installed inside a supporting structure. After the telescope gasholder, the disk-type gasholder was established. In this technology, a piston in a cylinder created the storage volume at still low pressures. Due to limitation to pressures insignificantly higher than ambient pressure, shortly an interest for pressure vessels emerged. In contrast to gasometers, pressure vessels operate at a constant volume but variable pressure between a minimum and a maximum value. The usable quantity of gas between these pressures is called working gas, and the quantity below the acceptable minimal pressure is called “cushion gas,” while the proportion of working gas to cushion gas differs in the single pressure vessel technologies. Spherical gas tanks, as seen in Fig. 5, allow significantly higher operational pressures and thus energy storage densities, due to their favorable geometry. This technology offers the lowest specific consumption of material for the container, which is a critical aspect, as investment costs depend on material costs in the first place (Table 3). To date no storage technology for pure hydrogen is known. Pipe storage facilities are gas pipelines installed in a meandering shape in the floor near the surface. In contrast to underground storage in geological formations, these storage facilities can be installed in nearly any region. The usage of commercially available steel

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Fig. 4 Function of the high temperature electrolysis of steam (Source: Sterner and Stadler 2014)

Fig. 5 Gasometer (telescope principle) (Source: Sterner and Stadler 2014)

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Table 3 Typical dimensions of a spherical gas tank Diameter of the sphere Maximum pressure Storage capacity

40 m 10 bar 335,000 m2 (Vn – standard volume)

pipes allows an operation at significantly higher pressures in comparison to spherical gas tanks. The geometry of the long cylinder with a low diameter leads to a higher material consumption and thus higher specific investment costs. Therefore, also this storage technology is only used for small capacities and can only be applied to compensate minor consumption fluctuations.

Underground Gas Storage The storage capacity of a holder aboveground is basically limited by the economically reasonable geometric volumes in combination with the desired storage pressure, whereas material costs are the predominant factor. Big storage volumes at significantly lower area consumption can be realized in the geological underground. In addition, storage pressures of up to 200 bars and more are possible with increasing depth. As storage capacity depends on the product of volume and pressure in the first place, fundamentally bigger dimensions in capacity are possible in comparison to the storage aboveground. While the pressure vessels named above provide capacities of under one million m3 (Vn – standard volume), the averaged capacity of German underground storage facilities is at nearly 500 million m3 (Vn). This is the reason why underground storage became the state-of-the-art technology for big amounts of gas. Figure 6 shows the different types of underground storage. In the beginning, depleted deposits for hydrocarbons and porous aquifers were used as storage. Later they were complemented by artificially created salt caverns. To a low extent, porous formations and salt caverns were used for the storage of town gas, which comprises 50 % hydrogen. For many years, the storage of pure hydrogen takes place in specially equipped salt caverns. All of the internationally installed underground gas storage facilities have in common: 1. The high safety against unintended escape of gas through the sealing rock layers of up to several hundred meters thickness – compared to the thin thickness of a few centimeters for overground containers 2. High storage capacity established by big geometric volumes and high operational pressures 3. Low surface usage overground 4. Low specific installation and maintenance costs compared to storage overground 5. Feasibility being coupled to the availability of suitable geological formations, which is a big limitation to a lot of regional cases

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Fig. 6 Spherical gas tank in Gelsenkirchen (Source: Sterner and Stadler 2014)

6. Extensive positive experience in a lot of industrialized nations and therefore good conditions for the acceptance of future storage of hydrogen Salt Caverns Salt caverns are artificially created cavities in underground salt rock. If sufficiently big and homogenous salt rock formations are available, a drilling is sunk into the rock with a diameter of less than 1 m and sealed with a cemented steel pipe. Afterwards, the cavity is created by the so-called solution mining process. The big advantage of the further explained process is that for creating the cavern, neither an extensive tunnel has to be sunk nor a person or machine has to be transported underground. All work can be executed overground, which is a considerable advantage in costs and time compared to conventional mining. To inject the required water for the solution process into the drilling, two concentric tubes are inserted into it at first, as seen in Fig. 7. Water is pressed through the inner tube, which dissolves the salt rock. Through the annular gap between the tubes, the evolving brine is brought overground and either used as a raw material or conducted into the sea environmentally friendly. Additionally, a protective fluid (blanket) is injected into the annular gap to prevent an uncontrolled rupture of the brine. The time-dependent spatial development of the cavern can be controlled by sonar measurements and thus applied to the requirements. The aim is to create a cavity which effectively uses the available salt rock and which provides a safe long-term storage of gas. The unique creeping properties of salt rock make these caverns tight for gases, as long as the permitted operational pressure is maintained. Nevertheless, the creeping leads to a decreasing volume over time.

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Fig. 7 Options for gas storage in the geological underground (Source: KBB UT)

As soon as the cavern obtained the required volume, tightness tests are executed, the cavern is modified for operation with gas, and the first gas is filled in. In the first step, the tightness of the drilling has to be proved – an important requirement for further approval as gas storage. Afterwards, the cavern is equipped with a casing for the exploration of gas as well as with a downhole safety valve. If the cavern head at the surface is damaged in the worst case, this valve prevents the blowout of gases from the cavern. The so-called brine removal string is inserted into the cavern and allows the displacement of the brine with the storage gas. Finally, the string is removed under pressure. Summing up, there are sufficient technologies available for a safe and economic storage of gas.

The Storage System Power-to-Gas The storage system Power-to-Gas (electricity to gas, PtG) is presented in this chapter. It is made out of the single conversion technologies, described in section “Technology Components of Power-to-Gas.” In general, two PtG concepts have to be differentiated based on the characteristics of their energy sources hydrogen (H2) and methane (CH4). Their deployment, as well as the extraction technologies used, make the main difference. In addition, there is the optional methanation stage. In the following, basic concepts of PtG are

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explained. The specific application for decarbonization and some projects is presented in section “Decarbonization with Power-to-Gas.”

The Beginnings of Power-to-Gas Energy Storage Demand in Dynamic Simulations: Hydrogen and Biomass In the course of expansion of renewable energies in Germany – mostly wind and photovoltaics – calls for energy storage grew ever louder since the early 2000s. While it has been sufficient for a long time to consider the annual balance sheet, which is based on only one value for wind and solar power generation, dynamic simulations of a power system containing a large percentage of renewable energies have detected and revealed a large storage and balance demand. This demand could not be supplied by conventional German storage technologies, such as pumped hydro, battery power plants, or compressed air storage. Solely, caverns exclusively for hydrogen have been considered as solution (see Sauer 2006; VDE 2013). Since there is no infrastructure for hydrogen and a very limited potential for hydropower buildout, pure renewable energy systems depend on bioenergy as balancing energy. The Combi Power Plant at the ISET Kassel, Now Fraunhofer IWES In the 1990s, Enßin, F€uller, Hahn, Rohrig, and their colleagues, at the Institute for Solar Energy Supply Technology (ISET) in Kassel, built a database for feed-in from wind turbines as part of the 250-MW measuring program. Since the early 2000s, this data has been used for wind forecasts and the construction of virtual power plant in the form of a wind turbine cluster (see Ernst et al. 2004; Ernst 2003; Enßlin et al. 1993). The project called “Combined Power Station” (see Fig. 8) resulted from their work and was able to prove that, at any point of time, power supply based on 100 % renewable energies was possible in Germany at a scale of 1–10,000, measured at the necessary energy supply and demand. To achieve this goal, wind turbines of Enercon GmbH, photovoltaic plants of Solarworld AG, and biogas plants of Schmack Biogas GmbH were combined and controlled in real time according to German load profile. Only power storage was simulated as the pump storage plant Goldisthal. That is how it was possible to rebut presumptions that purely renewable power systems were not able to provide a stable power supply (see Mackensen et al. 2008). Reinhard Mackensen’s analyzes showed that the expansion of renewable energies to the full extent would mainly be based on wind power and photovoltaics and thus require major balancing measures in the form of storage capacities or stored biomass. It is neither possible to provide these balancing measures by expanding pump storage plants nor can enough biomass be produced on the available areas (see Mackensen et al. 2008; Mackensen 2011). The core problem was to realistically upscale installed biomass and storage capacity by a factor of 10,000. One approach of the ISET was to interconnect the power and gas sector and thus be able to store wind and solar energy in the form of hydrogen in the natural gas grid. It would then

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Fig. 8 The brine process – cavern creation in the salt rock (Source: KBB UT)

be possible to flexibly reconvert it into electricity via gas turbines and cogeneration plants (see WBGU 2008). Methanol Production from CO2 and Biomass Gasification at the ZSW Stuttgart In the 1990s, Andreas Bandi, Thomas Weimer, Michael Specht, and their colleagues, at the Centre for Solar Energy and Hydrogen Research (ZSW) in Stuttgart, developed a synthesis to produce methanol from atmospheric CO2 and solar energy. A small-scale pilot plant was set up, which extracts CO2 from the air by means of adsorption and electro dialysis. It then chemically reacts the CO2 to methanol using hydrogen from solar powered electrolysis. At this point, the technical feasibility of CO2 recycling to produce methanol was successfully proven (see Bandi 1995; Specht 1998; Specht et al. 2000; Weimer 1996). In the 2000s, research at the ZSW concerning hydrogen and chemical energy sources focused on biomass gasification. They developed a process of their own (Absorption Enhanced Reforming Process) to produce a hydrogen-rich gas from biomass via two coupled fluidized bed reactors (see Weimer 1996; Specht et al. 2006, 2010).

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The First Coupled Power and Gas Grid in the WBGU-Bioenergy Report Until the middle of the 2000s, it became clear that the biomass potential is and will be limited. The increase in food prices in 2008 got the “food-versus-fuel debate” going and brought up the question to which degree biomass can and should be energetically used (see FAO 2008; Sachs 2008). The WBGU-Bioenergy Report shows that, while bioenergy is very well suited to balance fluctuating wind and solar energy, the necessary sustainable potential is not available. Both authors, J€urgen Schmid and Michael Sterner of the ISET Kassel, came to the conclusion that, because of its scarcity, bioenergy is best integrated into the existing natural gas grid via fermentation, gasification, and methanation (see WBGU 2008; Sterner and Schmid 2009). In this way, existing transport and storage capacities can be used and thus provide energy to all sectors via power plants, cogeneration plants, gas cars, and gas heating. In addition, it is possible on the one hand to separate CO2 and establish an actual CO2 sink and on the other hand to integrate fossil coal, which will last a long time, in a climate-friendly way. In the end, this integrated energy system consisted of an electricity and a gas system, which were coupled via gas power stations and cogeneration plants on the one hand and an electrolyser, which produced hydrogen for fuel cells, on the other (see Fig. 9). Schmid and Sterner presented this system along with the combined power station at the

Fig. 9 Combined power station at the ISET (Source: Sterner and Stadler 2014)

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16th European Biomass Conference (see Schmid and Sterner 2008; Sterner and Schmid 2008). Michael Specht and his colleagues from the ZWS Stuttgart presented their paper on chemical energy conversion of biomass (see Bandi 1995). Having the accordant background, he produced the idea to improve the possibility of integration of hydrogen into the natural gas grid by using the Sabatier reaction. As shown in Fig. 9, the syngas CO2 from coal and biomass is used for methanation. Patent, Studies, and Projects Concerning Power-to-Gas At this point, both institute’s preliminary work was merged together and the Powerto-Gas concept was elaborated. In 2009, this led to a patent application (see Specht et al. 2009) and a doctoral thesis on Power-to-Gas, which made the concept of chemically storing energy from wind and solar plants well known and put it into context with energy transition (see Sterner 2009). As another consequence, the first PtG plant for methanation of CO2 in Germany was developed in Stuttgart by the order of Waldstein, the founder of SolarFuel GmbH (see Fichtner 2011; Specht et al. 2008). In addition, different pilot projects were launched. While studies were carried out for E-On, Greenpeace Energy, and Audi AG in Kassel, hardware was refined in Stuttgart. Both activities paved the way for the realization of pilot projects and the publication of the new concept. In energy economy, this concept was made well known by a number of associations: the research papers by the Fraunhofer IWES (formerly ISET) on which the long-term scenario of the Federal Environment Ministry (BMU) is based (see Nitsch et al. 2012), the report published by the German Advisory Council on the Environment (SRU, see SRU 2011), the Federal Environment Agency’s “UBA Energy Goals 2050” (see UBA 2010), and the VDE ETG Storage Study (see VDE ETG 2012). So far, the greatest PtG project has been realized by Audi AG and fuels 1,500 vehicles with CO2-neutral gas.

PtG Hydrogen The storage system PtG hydrogen (PtG-H2) uses electricity surplus from renewable energies to produce hydrogen. Hydrogen can potentially be used in several different ways, e.g., as an admixture in the natural gas grid or it can be used energetically at a different point of time and place if filled in a compressed hydrogen tube trailer. Following stages are passed through: – Storing: Storing technologies – Alkaline electrolysis (AEL) – Proton exchange membrane electrolysis (PEMEL) – High temperature electrolysis (HTEL) – Storage: Storage media – Gas grid

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– Cavern storage – Gas and oil deposits – Aboveground storage – Extraction: Extraction technologies – Fuel cell – Gas turbine, combined cycle plant, cogeneration plant – Gas heating, gas hat pump, refrigeration machines – Fuel cell vehicles, rocket propulsion – Material use Possible Plant Concepts High-quality natural gas in Germany is composed of 96 % by volume methane, 1 vol % CO2, 2 vol% nitrogen (N2), and 1 vol% hydrocarbons, such as propane and butane (see Henel et al. 2013). According to the DVGW (German Technical and Scientific Association for Gas and Water), the admixture of 1.5 % hydrogen is possible. Higher blending quotas cause research needs and adjustment requirements for certain applications, such as gas turbines, porous storage, or natural gas tanks in vehicles, which are limited to 0–4 %. For this reason, PtG hydrogen storage systems differ in regard to the way hydrogen is used after electrolysis. In this book, the use of hydrogen is distinguished between material (1) and energetic. Furthermore, energetic use can be divided into use in an infrastructure exclusively for hydrogen (2) and use in an already existing gas infrastructure (3). There is a clear presentation of how hydrogen can be used in Fig. 10.

Material Use An industrial plant or a refinery with a great need for hydrogen can be attached directly to a PtG-H2 plant (Fig. 11). Since most industrial applications need constant supply, the system includes hydrogen tank as buffer. Hence, requirements for PtG-H2 systems are a location with great availability of renewable energy sources and a suitable consumer for the H2. There is a great climate protection potential in the reduction of iron by applying the direct reduction process (DRP) rather than the CO2-intensive blast furnace process. The DRP uses hydrogen to withdraw oxygen from the ore (Fe2O3). As a result of this reaction, there is pig iron and water. Another advantage of the DRP is that there is less than 1 % carbon in the pig iron. After the blast furnace process, up to several percent carbon has to be removed in order to meet DIN (German Institute for Standardization) norms, according to which pig iron, the staring product for steel, has to contain less than 2 % carbon.

Energetic Use via Hydrogen Infrastructure When, in the future, a hydrogen economy has been established, it will be possible to use hydrogen directly in a hydrogen-only system (Fig. 12). Regions with already

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Fig. 10 Coupling of electricity and gas system via electrolysis in the WBGU Report on bioenergy (Source: WBGU 2008)

Fig. 11 Overview of the possible uses of hydrogen (Source: Sterner and Stadler 2014)

existing suitable hydrogen storage and lines are eligible starting points as well as regions with a high density of consumers in chemistry parks. This is researched in the course of the BMBF project “HYPOS” for eastern Germany, which examines wind-photovoltaic-hydrogen hybrid parks and hydrogen test fields including Germany’s first hydrogen storage (see HYPOS 2014). Storage options for shortterm storage are, along with hydrogen lines, aboveground H2 tanks. Long-term

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Fig. 12 Schematic representation of a PtG system for material use of hydrogen (Source: Sterner and Stadler 2014)

storage can be realized in gas caverns. Porous storage is not suitable for hydrogen storage because of microbiological hydrogen sulfide emergence, which results in corrosion. In times of deficits due to fluctuating renewable energies, this system reconverts hydrogen to electricity via especially adapted gas turbines or fuel cells and thus acts as electricity storage. In this case, an independent hydrogen infrastructure provides seasonal balance for times of both low winds and sunshine hours. In addition, hydrogen can be used for transport when sold at hydrogen stations or in the field of heat supply. Realization is obstructed by high costs for the expansion of an independent hydrogen infrastructure and high prices for hydrogen extraction technologies, such as fuel cell vehicles, fuel cell cogeneration plants, and reconversion units.

Energetic Use via Admixture to Natural Gas and Use of Existing Gas Infrastructure From today’s point of view, an independent hydrogen infrastructure is only financially reasonable in some regions with a great demand for hydrogen, industrial consumers, and existing, suitable storage facilities, such as cavern storage. Matters are different, when hydrogen is added to natural gas using the existing gas infrastructure. The gas grid is expanded over all of Germany and there are highcapacity cross-border interconnections. Furthermore, state-of-the-art consumers which only need slight adaptions to higher hydrogen percentage can be used in all energy sectors. These already existing technologies make development of new ones redundant. The challenge here is hydrogen tolerance of specific components (Fig. 13). In this field, there are research needs and adjustment requirements to increase the technically possible blending quota of 1–2 vol% (see Henel et al. 2013). In a PtG hydrogen storage system, surplus electricity is used for water splitting in an electrolyser (Fig. 13). In order to prepare hydrogen produced in this manner for feed-in to the gas infrastructure, it is fed to a gas storing unit including a compressor.

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Fig. 13 Energetic use of hydrogen in a hydrogen-only infrastructure (Source: Sterner and Stadler 2014)

From that point on, usage is possible, in consideration of hydrogen tolerances shown in Fig. 22, in all kinds of ways: reconversion to electricity, heat, transport, or material use. When used for seasonal balancing, the mixture of hydrogen and natural gas can be stored, other than pure hydrogen, in all gas storages up to a blending quota of 1 % hydrogen. Along with salt cavities, porous storage is an option. Buffering on a shortterm scale is possible in aboveground gas storages. Furthermore, the gas mixture can be brought to all consumers in households, business, and industry via the gas grid. Among others, possible applications are gas engines, condensing gas boilers, gas heat pumps, gas stoves, gas tools, gas base materials, or reconversion to electricity for peak-load supply.

Power-to-Gas Methane In addition to electrolysis, there is another storing technology, methanation, in the Power-to-Gas methane (PtG-CH4) storage system. Hydrogen and carbon dioxide (CO2) are reacted biologically or chemically to methane (CH4) and water (H2O) (see Sterner 2009). Main advantages of this system are easier compressibility, storage, transport, and usage, due to higher energy density of methane. Disadvantages result from the additional procedural step, which needs CO2, causes waste heat and therefore

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reduces efficiency of the overall process. Among others, intelligent heat concepts can compensate for this disadvantage by using waste heat for vaporization in high temperature electrolysis (section “Efficiency, Potentials, CO2 Emissions and Costs”). A PtG-CH4 system can be composed of the following components: – Storing: Storing technologies – Electrolysis – Alkaline electrolysis (AEL) – Proton exchange membrane electrolysis (PEMEL) – High temperature electrolysis (HTEL) – Methanation – Chemical methanation – Biological methanation – Storage: Storage media – Gas grid – Cavern storage – Gas and oil deposits – Aboveground storage – Extraction: Extraction technologies – Fuel cell – Gas turbine, combined cycle plant, cogeneration plant – Gas heating, gas hat pump, refrigeration machines – Gas vehicles, ships, airplanes – Material use Possible Plant Concepts In the field of PtG-CH4, there are different concept categories, which are all based on the concept shown in Fig. 14 (see Sterner 2009). Bidirectional interconnection of power and gas grid in order to store renewable energies is the general idea of Power-to-Gas (section “The Beginnings of Power-toGas”). Electricity surpluses power water splitting. In the process of methanation, thus produced hydrogen and CO2 are reacted to methane. This requires one of several different possible sources of CO2, such as Carbon Dioxide Capture and Storage (CCS), biogas plants, sewage plants, atmospheric CO2, industrial processes, or conventional power plants. Renewable methane can be temporarily stored in gas storage or fed into the gas grid. Once there, it can be reconverted to electricity via gas turbines, cogeneration plants, etc., or be used in the heat and transport sector. What differs between each concept from another is the CO2 sources and how it is integrated into the process of methanation.

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Fig. 14 Schematic representation of hydrogen use in the existing gas infrastructure (Source: Sterner and Stadler 2014)

Fig. 15 Basic concept of PtG methane (Source: Sterner 2009)

Atmospheric CO2 Methane produced with atmospheric CO2 and renewable electricity is CO2 neutral (Fig. 15). It is possible to decrease the content of CO2 in the atmosphere by connecting the combustion process with a CCS system.

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There are different ways to extract CO2 from the air: 1. 2. 3. 4.

Adsorption Absorption Condensation Membrane separation

Since the concentration of CO2 in the atmosphere is only ca. 400 ppm or 0.4 ‰, every one of these processes is energy-intensive. Therefore, pure CO2 sources should be used in order to increase efficiency and profitability of PtG plants. This system is given its raison d’être by regions worldwide which offer a great potential of renewable energies but are far from consumers. Since air is the only source of CO2 in these regions, this system makes it possible to use their potential and decrease their dependence on natural gas imports (see Sterner 2009). Two of the four abovenamed extraction technologies are very energy-intensive: Condensation requires considerable cooling of the air; membrane separation requires a very high pressure to extract CO2 from the air. These processes are standardly applied in air separation units (ASU) for industrial extraction of nitrogen, oxygen, and noble gases, such as argon (see Specht et al. 2000). From today’s point of view, with respect to effort and losses, technologies based on absorption and adsorption are favored. Absorption Process An alkaline solution, such as sodium hydroxide (NaOH), potassium hydroxide (KOH), or calcium hydroxide (Ca(OH)2), absorbs CO2 from the air and reacts to a carbonate like sodium carbonate (Na2CO3). Now, an acid can dissolve CO2 from the carbonate. In order to restore acid and alkaline solution, an electrodialysis with bipolar membranes is carried out. In this electrochemical process, protons (H+) and hydroxide ions (OH
) are being separated by an electric field. These ions are produced by splitting water, which in turn is activated by a bipolar membrane. According to tests in the laboratories of ZSW Stuttgart, absorption and electrodialysis put together require 2.28 MWh per ton CO2 (see Bandi 1995; Specht et al. 2000). In practice, this value is higher. Adsorption Process The adsorption process uses a batch procedure, in which first CO2 is adsorbed and then emitted and thus made available, when supplied with low calorific heat. Adsorption processes, such as the pressure swing adsorption (PSA), are standard in gas preparation and purification technologies. The advantage is that low temperature heat from different processes (e.g., electrolysis, CHP, possibly synthesis) can be used for desorption. The Climeworks company produces and runs a commercially available demonstration plant capable of extracting atmospheric CO2. One cycle takes some 6 h.

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First of all, air is conducted through the adsorption chamber, where CO2 adheres to cellulose granulate. It takes 3 h before enough CO2 is accumulated. After another 3 h at 95  C and reduced pressure, the desorption phase has completed the cycle. Under these conditions, it is possible to extract 99.5 % pure CO2 from the cellulose with a vacuum pump. It is possible to extract 80 % of all CO2 molecules from the air with this plant using a sorbent. In absolute numbers, this means 800 m3/h air and 4 kg/d respectively 1,000 kg/a CO2 (see Gebald et al. 2011, 2013; Wurzbacher et al. 2011). In the future, ca. 1,000 t CO2/a with a composition of 99.9 % CO2, 30 ppm O2, and 20 ppm H2O will be achievable on a 100 m2 area. Energy input is between 200 and 300 kWh electricity per ton CO2 mainly for the fan and between 1,500 and 2,000 kWh/t CO2 for low calorific heat (supply temperature: 105  C, return temperature: 95  C) mainly for desorption. Costs for extraction are expected to decrease in the future to some 200 €/t from today ca. 800 €/t with an expenditure of ca. 30 €/t for electricity and heat (see Gebald 2013).

This demonstration plant was installed at the beginning of 2013 and proved its suitability for daily use under different environmental conditions. It is planned to cooperate with Audi, which provides CO2 for the PtG plant in Werlte (see Audi 2014).

CO2 from Biogas Treatment Plants Principle This concept’s base material for CO2 is biomass or waste, which is being fermented in a digester. Depending on dwelling time and the kind of digester, the purified biogas can contain up to 45 % CO2. For a lot of technical applications, the inert CO2 is obstructive, which is why biogas is purified to natural gas quality (>96 % CH4) prior to feed-in into the natural gas grid. For this reason, the purified biogas is called biomethane and can be stored, distributed, and used in all fields of application via gas grid. Using the existing gas infrastructure has many advantages: already existing technology can be applied and, contrarily to on-site conversion to electricity, waste heat can be used more specifically. This makes exploitation of biogas more efficient. Processes for gas separation are adsorption, absorption, chemical absorption, membrane separation, or cooling (see Beil 2008). In combination with PtG, thus extracted very pure CO2, which is normally blown into the atmosphere, can be used for methanation. Together with electricity surpluses and hydrogen it is reacted to methane. When there is no sufficient electricity surplus for hydrogen production or hydrogen buffers are empty, CO2 can simply be stored and used when needed (Fig. 16).

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Fig. 16 PtG methane using atmospheric CO2 (Source: Sterner 2009)

Advantages The great advantage of coupling these processes is a more efficient use of resources and energy: in this system, waste heat produced by methanation can entirely be used for the fermentation or treatment procedures. By using CO2, a naturally bound resource, methane production of a biogas treatment plant can almost be doubled if PtG is applied. Additionally, the climate-damaging methane slip of treatment plants can be avoided. Biomass Gasification Variant Instead of a digester, a gasification plant can be used for solid biomass. When supplied with heat and oxygen, carbon hydrate compounds are split into CO, H2, H2O, CH4, and CO2. This gas mixture is catalytically reacted to methane after purification and conditioning. A PtG plant can provide this process with oxygen and hydrogen and increase its gas yield by using surplus electricity.

CO2, a Component of Gas from Biogas and Gas Purification Plants Principle Direct methanation of biogas or sewage gas is possible even without previous CO2 separation (Fig. 17). Both gases consist of 50–60 % methane and 40–50 % CO2 and small amounts of accompanying substances. This gas is conducted from the digester to methanation, where CO2 from biogas or sewage gas and renewable hydrogen can react to high percentage methane.

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Fig. 17 PtG methane using CO2 from biogas treatment or biomass gasification (Source: Sterner 2009)

By connecting a biogas plant to a PtG system, which also eliminates the additional energy expenditure for biogas treatment, it can produce twice as much methane. Advantages of Biological Methanation This process can be realized both chemically and biologically. Especially biological methanation seems suitable in this case, because the necessary bacterial strains are already contained in biogas and sewage treatment plants. Additionally, parts of the infrastructure of already existing biogas and sewage treatment plants can be used and thus save investment cost. This includes premises, electrical installations, and, if applicable, biogas or sewage gas utilization (conversion to electricity, gas grid, etc.). Especially in combination with municipal infrastructure (e.g., transport fleet), on-site PtG at a sewage treatment plant is very promising. Along with integration into existing biogas or sewer-gas plants, another possibility is methanation in pure cultures. This has the advantage of increasing conversion rate at reduced dwelling time, because bacterial strains can be treated more specifically.

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CO2 from Flue Gas Emitted by Coal Power Stations Principle The main shortcoming of today’s coal usage is its CO2 emission. In the light of worldwide coal reserves, concepts for separation, sequestration, and storage (carbon capture and storage – CCS) are developed and put to the test (see Sterner 2009). It is far more realistic, to use CO2 from coal power stations energetically or materially (carbon capture and use – CCU), rather than store it in potentially leaky formations underground. There are different processes for separating carbon dioxide from waste gases of combustion processes: In a downstream separation of waste gas after combustion, during the gasification stage before combustion for combined cycle plants using coal gasification, or during combustion in a pure oxygen atmosphere (oxyfuel combustion process, Fig. 18). Oxyfuel Combustion Process Since one product of water electrolysis is pure oxygen, latter process seems most attractive. If electrolysis cannot provide enough oxygen, an air separation unit can. This is more energy intensive and decreases the overall system’s efficiency. Taking

Fig. 18 PtG methane directly reacting a CH4/CO2 mixture from biogas or gas purification plants (Source: Sterner 2009)

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everything into account, this process may still be more advantageous than energyintensive downstream separation. Allocation of Emissions The allocation of CO2 emissions is quite a challenge. On the one hand, CO2 is disposed of by the power plant, on the other hand it is not emitted until the combustion of methane, whose production is based on renewable energies. For this reason, the concept is climate neutral at best. Clear allocation of emissions to coal power stations or gas consumers is required. Otherwise, emissions can be outsourced from the power sector to the heat and transport sector, where the emissions trading law does not apply. So-called green washing of coal power plants is to be avoided. It is of great importance for this concept that coal power stations are not operated above their must-run limit when methanation is in progress in times of great wind and solar feed-in. In this way, energetically pointless conversion of a chemical energy source to an electrical one and following reconversion (so-called chemical short circuit) can be avoided. Renewable feed-in is mainly there to replace fossil power plants. Electrolysis must not be supplied with electrical energy by fossil power plants.

CO2 Recycling from Gas Power Stations and Other Sources Principle In order to create a closed carbon cycle, the oxyfuel combustion process can be applied to combustion of thus produced methane in gas power stations. This requires spatial proximity of storing and extraction technology, because pure oxygen from electrolysis is needed for clean burning, whose only product gases are carbon dioxide and water. Thus produced CO2 can be recycled to methane; therefore, the carbon cycle is closed, and the use of CO2 is climate neutral. Other Sources Another possibility is the use of fossil CO2 from energy-intensive industrial plants, such as steel works, paper mills, or cement plants. They supply their high energy consumption for process heat (possibility of waste heat integration) by combustion of fossil energy sources. This source of CO2 is very favorable, because they also allow reduction of material, nonenergetic CO2 emissions. Further sources are waste gases from engine test benches or special industrial processes.

Efficiency, Potentials, CO2 Emissions, and Costs Efficiency Increases Because of Integration of High Temperature Electrolysis Irrespective of which specific process is applied to produce a specific end product, all production variants for synthetic carbon hydrates have one thing in common: while

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Fig. 19 PtG methane using CO2 emitted by coal power stations via oxyfuel combustion process (Source: Sterner 2009)

production of hydrogen is an endothermic reaction at the beginning, during the exothermic synthesis of hydrogen and carbons to carbon hydrates, such as methane, methanol, gasoline, diesel, kerosene, or waxes, parts of previously supplied electrical energy are released in the form of heat. It is this thermodynamic fundamental principle efficiency losses compared to pure hydrogen production are based upon for production of synthetic carbon hydrates. These losses can only be compensated for by reintegration of waste heat released during the process. One way to achieve this is to vaporize feed water and supply thus produced vapor to steam electrolysis (HTEL). Now, electrical energy only has to supply the net calorific value (NCV) instead of the gross calorific value (GCV), which it has to provide for water electrolysis. This thermodynamic saving of 16 % electrical energy by recuperating waste heat allows production of synthetic carbon hydrates with an efficiency similar to pure hydrogen production. These two process chains are compared in Figs. 19 and 20. The thermodynamic maximum efficiency is 84 % for each one, which equals the difference between GCV and NCVof hydrogen (NCVH2/GCVH2 – ratio). Efficiency rates expected in practice are between ca. 65 % and 79 %.

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Fig. 20 High temperature electrolysis for hydrogen production from steam without recuperation of waste heat from syntheses (Source: Sterner and Stadler 2014)

Efficiency Rates of Power-to-Gas Systems A complete PtG system contains 1. 2. 3. 4. 5.

Transformer (η = 90 %) Electrolyser (η = 70 %) Methanation (η = 82.5 %) Compression and gas storage (η = 97 %) And an extraction technology, which can vary depending on the energy service

These average efficiency rates result in different overall efficiency rates (see Table 4). Efficiency of pure PtG hydrogen storage systems are some 5–12 % higher than systems with methanation, because of the missing interim step.

Potentials for Energy Storage Other than the power grid, the gas grid offers enough transmission and storage capacity. In gas storage, there is a chemical respectively thermal storage capacity of 217 TWh with considerable potential for expansion. Thus stored gas can provide some 120 TWh electricity or 20 % of Germany’s gross power consumption and fill all major gaps in renewable energy supply, if reconverted efficiently via sufficient combined cycle plants at an efficiency rate of 60 %. For systems including methanation, this capacity is completely available. For feed-in of hydrogen, respective limits have to be considered. Assuming an average tolerance of 1–2 %, there is 2–4 TWh storage capacity for hydrogen. However, this value is purely theoretical, because it is based on the assumption that hydrogen is evenly distributed over Germany. Many gas grids’ flows vary with the season. In reality, mainly hydrogen caverns are suited for hydrogen storage.

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Table 4 Efficiency chains for different PtG storage systems (source: own depiction, based on (Sterner and Jentsch 2011), completed by recuperation of waste heat from synthesis for HTEL) Path Power-to-Gas Power to hydrogen Power to methane Power to hydrogen Power to methane Power to hydrogen Power to methane Power sector Power to hydrogen to power Power to methane to power Transport sector Power to hydrogen to motor power Power-to-gas to motor power Power to methane to motor power Heat sector Power to methane to heat and power Power to methane to heat

Overall efficiency (%) 54–79 49–78 57–80 50–78 64–84 51–79

Boundary condition Compression to 200 bar (gas storage) Compression to 80 bar (long-distance and transport lines) No compression

34–51

Conversion to electricity via fuel cell

30–38

Combustion in combined cycle plant (60 %)

38–53

Use in fuel cell (60 %)

24–49 18–37

Reconversion via combined cycle plant and use of electric vehicle (80 %) Combustion in gasoline engine (35 %)

43–68

CHP (45 % heat, 40 % power)

53–84

Condensing boiler (105 %)

For comparison, pump storage plants have a storage capacity of 0.04 TWh. If, theoretically, all 42 M existing cars in Germany were electric vehicles with a capacity of 20 kWh each and on the grid at the same time, they could provide 0.42 TWh storage capacity. This calculation is realistically based on the assumption that half of the cars can be used to balance deficits. At a discharge rate of 60 GW, they could stabilize the power grid for some 7 h. Extraction of all gas storage would suffice, at the same rate, for 2,000 h or 3 months. This comparison makes clear what a huge storage potential Power-to-Gas has. Along with storage capacity, the gas grid supplies a well expanded transport and distribution network. While typical transmission lines limit transmissions to 3.5 GW (two 380 kV three-phase systems), the long-distance trans-Europe natural gas pipeline can transport gas equal to some 70 GW. This means the coupling of power and gas grid does not only make storage of great amounts of energy possible, it also allows their spatial separation of storing and usage of renewable methane. This is a unique selling proposition of PtG.

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CO2 Emissions of Power-to-Gas Potential to Decrease CO2 Emissions with Renewable Electricity Only Two things are of importance for the climate impact of PtG storage systems: The source respectively supply of electricity and the substituted energy source. In summary, it can be said that only renewable, CO2-free electricity is environmentally friendly and has a decreasing effect on emissions. Gray electricity from coal or gas for hydrogen or methane production is not only energetically absurd but also causes many times over the emissions conventional hydrogen or methane do. This is revealed even by a simplistic greenhouse gas balance: If cheap lignite electricity (1,161 g CO2-eq./kWh) is conversed to methane at an efficiency of 60 % (1,935 g CO2-eq./kWh) and reconverted to electricity via combined cycle plant at an efficiency of 60 %, storage electricity with 3,225 g CO2-eq./kWh has been produced (see Table 5). This is almost eight times the amount of fossil power from natural gas. The same applies for transport: at a thrifty consumption of 40 kWh/100 km (ca. 4 l diesel or 0.4 kWh/km) a vehicle fuelled by lignite PtG emits 774 g CO2eq./km, which is six times more than fossil diesel (126 g CO2-eq./km). In spite of this negative environmental balance, lignite electricity is in discussion to supply PtG, because it is currently the cheapest power on the market. At this point, opposing goals of economy and ecology, as discussed in section “The Need for a Storage Transition in Energy Transition”, become clear. Potential to Decrease CO2 Emissions: Also a Question of Which Energy Source Is Substituted The second point of climate impact of PtG is the question, in which order fossil energy sources are substituted. It is essential, if the federal government’s goals are to be achieved and climate protection is to be further established, to substitute all fossil energy sources with renewable energies, renewable fuels, and energy storage in all sectors. First, the procedure of substitution should remove emission-rich energy sources, such as coal, subsequently low-emission energy sources, e.g., natural gas. As shown in Table 5, substitution of lignite and hard coal in the power sector is the first choice from a climate protection point of view. In the first step, coal is replaced by wind, sun, and water power, and in the second step by energy storage, such as Power-to-Gas. Since PtG is only deployed in rare times of deficits of renewable energies, efficiency losses are acceptable. Substitution of gasoline and diesel fuels makes sense, as long as they cannot be replaced by direct usage of renewable electricity in electric vehicles. An extrapolation of the potential to decrease CO2 emissions from one single plant to all of Germany is only possible, if surplus quantities are taken into account (section “The Storage System Power-to-Gas”). As a rule, it can be said that:

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Table 5 Emissions of fossil energy sources and PtG storage systems in g CO2-eq. per energy unit (kWh) and per energy service resp. in g CO2-eq. per km mileage at a very moderate consumption of 40 kWh/100 km (ca. 4 l diesel/100 km); based on 100 % combustion, conversion losses included. Reference system 2010. Gray electricity mix emissions: 546 g CO2-eq./kWh (Source: Icha 2013) g CO2-eq./kWhth g CO2-eq./kWh Energy source combustible energy service Fossil systems Lignite 404 1,161 (η = 0.35) Hard coal 339 902 (η = 0.38) Natural gas 202 411 (η = 0.49) Natural gas 202 224 (η = 0.9) Heating oil 266 296 (η = 0.9) Diesel 266 Natural gas 202 PtG systems (efficiency of electricity to gas: 60 %) Lignite – gas 1,935 3,949 (η = 0.49) Gray 950 1,857 (η = 0.49) electricity – gas Wind gas 33 68 (η = 0.49) Lignite – gas 1,935 2,050 (η = 0.9) Gray 950 1,011 (η = 0.9) electricity – gas Wind gas 33 37 (η = 0.9) Lignite – gas 1,935 Gray 950 electricity – gas Wind gas 33

g CO2-eq./km mileage

Energy service Power

Heat 106 81

Transport

Power

Heat

774 364

Transport

13

– The deployment of renewable electricity is a basic prerequisite – The more CO2 intensive a substituted energy source, the greater the reduction potential

Costs of PtG Market Conditions Hydrogen produced by steam reforming of natural gas causes production costs of 3–4 €-¢/kWh, natural gas costs 2–3 €-¢/kWh at the stock market, and gray electricity between 1 and 6 €-¢/kWh (see EEX 2014). Surplus electricity for even smaller prices is only available for a very small number of hours, which shows how difficult it is for PtG to competitively convert Power-to-Gas. Economic Efficiency PtG is a very young energy technology; today, it cannot be realized economically. Investment costs for new plants are between 2,500 and 5,000 €/kW; operating costs

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Fig. 21 High temperature electrolysis for carbon hydrate production from steam and CO2 with recuperation of waste heat from syntheses for vaporization of water. Similar efficiency rates as pure hydrogen production (Source: Sterner and Stadler 2014)

are mainly subject to electricity prices, which vary between 0 €-¢/kWh (very rare) and 9 €-¢/kWh (average price for wind power). Figure 21 shows results of elaborated cost calculation that were made in the course of the project “Energy Storage Concepts” for PRG hydrogen and PtG methane. These results are shown as a range from optimistic (low investment and operating costs, low interest rates, and low risk) to pessimistic expectations (high investment and operating costs, high interest rates, and high risk). All assumption can be seen in detail in Henel et al. (2013). Economically competitive production of renewable hydrogen or methane requires more than 7,000 h electricity supply at 0 €-¢/kWh without further levies. From today’s point of view, this scenario seems more than unlikely. Only after a concept with electricity supply costs of 5 €-¢/kWh in base load operation (more than 7,000 h) has been developed, e.g., sail powered energy, it will be possible to supply hydrogen for 8–17 €-¢/kWh and methane for 13–24 €-¢/kWh. If levies for CO2 or prices for natural gas were to increase, renewable gases could be an economical and sustainable alternative, even for higher costs. It becomes clear that hydrogen can only be produced economically in the most optimistic case, which means almost constant electricity supply at stock market prices or below can be used. But this means that something else than surpluses of wind or solar energy are used, because they occur only very rarely and not on a constant basis. If gray electricity is used, the product gas is the same as fossil gas concerning disadvantages in the CO2 balance and marketing. In many places in Germany, feed-in management is used to curtail surpluses. At the moment, the absolute value is within limits: in the past year, only ca. 1 ‰ of Germany’s energy consumption has been curtailed.

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A basic rule for PtG: only if electricity supply is mainly renewable (more than 80 %), the produced gas has the privilege to be equal to biogas. This simplifies the connection of the PtG plant to the gas grid and the gas’ benchmark is increased from 2–3 €-¢/kWh (fossil natural gas) to 7–8 €-¢/kWh (bio-natural gas). If the stored gas is reconverted to electricity via gas power station, thus generated power costs some two times more because of the complete electricity storage chain. From today’s point of view, market entry seems most likely in the field of fuels for transport or resources for the chemical industry, because the price level is higher in there than in the electricity and heat market. Hydrogen Versus Methane On the one hand, a PtG hydrogen storage system does not require a methanation unit and therefore saves efficiency and costs. On the other hand, costs are not assessable for the adaption of plants incompatible to hydrogen in the gas infrastructure or setting up a hydrogen infrastructure. For this reason, the exhaustion of hydrogen admixture quotas of 1–2 % including downstream methanation is favorable for longterm storage with PtG, from today’s point of view. More information can be found in the gas grid development plans (see Netzentwicklungsplan Gas 2012).

Advantages and Disadvantages of Hydrogen and Methane PtG Hydrogen A PtG hydrogen storage system is favorable, for reasons of efficiency and costs, as long as admixture limits of hydrogen are not exceeded or hydrogen can be stored and used locally. It has to be preconceived that, for small natural gas flows, admixture limits are reached very quickly and storage has to be applied in order to level hydrogen feed-in. Unlike for methane and natural gas, there are no comprehensive solutions suitable for the mass. While fuel cell technology is subject to research in auto industry and heat supply long since, technologies ready for the market are merely announced time and again. Furthermore, market entry is only possible, and even then merely in small quantities, if subsidized by companies or the public purse. It is also yet to be seen if fuel cells will come on top of e-mobility, conventional powertrains, electric heat pumps, and alternative renewable heating systems based on wood and sun. When adding hydrogen to the natural gas, changing fuel properties of the gas mixture have to be taken into account. For one thing, the volumetric calorific value decreases by some 7 %, depending on the natural gas quality, if 10 % by volume hydrogen is added. This has to be compensated for by an increased quantity to be supplied, which in turn requires adaption of, for example, compressors. The adaption of the natural gas infrastructure to higher admixture quotas is associated with the need for research and high costs. Figure 22 shows which components are particularly affected and the existence of need for adaption and research.

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Fig. 22 Range of gas production costs in €-¢/kWh for PtG hydrogen and PtG methane for different electricity prices and full load hours in the DVGW project “Energy Storage Concepts.” Hydrogen paths are represented in blue, methane in orange, each in a range from optimistic to pessimistic. Electricity supply is plotted from 0 €-¢/kWh (plant costs only) over an average value for stock market prices (5 €-¢/kWh) to electricity supply by a wind power plant (9 €-¢/kWh), each for different periods of use and utilization time (the year has 8,760 h). Reference costs for gases and fuels made with fossil and biogenic energy are depicted as dashed lines (Source: adapted from Henel et al. (2013))

In the transport sector, it has to be taken into account that natural gas must not contain more than 2 % by volume hydrogen, because higher concentrations may cause embrittlement of steel tanks in CNG vehicles. But also for reconversion to electricity, high shares of H2 are problematic: gas turbines are only operational, as specified by the manufacturer, for admixture quotas between 1 % and 3 % by volume, because of changing combustion characteristics (increased flame velocity, different temperature, etc.). For this reason, even cogeneration plants which are, according to manufacturer’s data, hydrogen-tolerant up to 25 % are in practice operated with only 15 %. In general, it is assumed that the admixture limit for hydrogen in the natural gas grid is 1–1.5 %. High local feed-in of hydrogen may cause problems if the natural gas load flow is low, because limits are exceeded locally. Additionally, there are some industrial gas applications, which use gas as “flaming tool” (e.g., drying in the porcelain and glass industry). Fluctuating gas quality can have a strong influence on the product quality (see Henel et al. 2013). Since conditions and requirements in long-distance and distribution gas grids vary strongly both locally and regionally, each possibility for the feed-in of the additive gas hydrogen has to be checked individually.

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According to the FNB’s (long-distance grid operators) gas grid development plans, increasing the admixture limit from today’s 1–1.5 % to 10 % requires the replacement of all compressors, which costs 3.6 Bio. € in the long-distance grid alone (see Netzentwicklungsplan Gas 2012). Advantages and disadvantages of feed-in of hydrogen into the gas grid versus PtG methane are compared in Fig. 23 and Table 6.

PtG Methane The storage system PtG methane has certain advantages compared to the hydrogen system and other long-term storage systems but also disadvantages. The systems advantages are obvious. It is possible to integrate renewable methane in today’s energy infrastructure without any problem, since it has the same quality, it can fully replace natural gas (“replacement gas”). Unlike hydrogen, the use of renewable methane is uncritical regardless of admixture quotas for gas turbines, porous storage, distribution lines, seals, and applications, such as combustion engines or gas stoves.

Fig. 23 Hydrogen tolerance of specific components of the gas infrastructure (Source: Henel et al. 2013)

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Table 6 Advantages and disadvantages of a PtG storage system with hydrogen and methane Hydrogen Advantages Efficiency Storing technology Storage Extraction technology Feed-in into the gas grid

Methane Advantages

Disadvantages

54–84 %

Equal

49–79 %

Equal Equal

Equal

Equal

Infrastructure Transport Storage Application

Material demand, climate impact, and plant operation

Energy density (specific calorific value at 0  C and 1.013 bar or space requirement for storage) Transformation costs

Independent of CO2, therefore more flexible siting (except for usage of atmospheric CO2 for methanation)

Disadvantages

Additive gas: today’s admixture limit 1–1.5 %; max. 2 % by Volume Largely nonexistent, no affordable and fully developed application technology Additional hydrogen storage necessary for fluctuating load flow of natural gas 3.0 kWh/m³

Cheaper than methane up to the admixture limit

Storing: Electricity – H2 Storage Extraction: H2 – electricity Transport, storage

Replacement gas: no limit

Existing infrastructure including application technologies, usable to the full extent Possible CO2 sink if operated in CCS mode

Necessity of a CO2 source, continuous methanation is based on upstream hydrogen production

10.0 kWh/m³ Three times more, smaller storage system possible

Only storing and additional methanation and CO2 supply versus hydrogen

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Furthermore, there exists already a large and widely distributed infrastructure for energy transport, storage, and application technology. This means there are wellestablished state-of-the-art applications in every energy sector and in the chemical industry. Another advantage is the higher volumetric energy density of methane compared to hydrogen, which makes smaller storage systems possible and saves cost and space. With reference to one standard cubic meter, the calorific value of methane is 3.3 times that of hydrogen. The cost situation of this storage system requires a differentiated review. Up to the admixture limit of hydrogen, a system without methanation is more economical, because they operate without CO2 supply and methanation units. As soon as that limit is reached, it is more cost-efficient to store renewable energy in the form of methane instead of adapting the German infrastructure to a higher admixture quota of hydrogen. A disadvantage of PtG methane is its need for CO2 supply. Efficiency losses of the overall process reflect the additional expenditure. But, on the other hand, the extraction and storage of atmospheric CO2 is a possibility to reduce its concentration in the air by the energy system itself and in the long run, CO2 extraction from air might become a necessity in fighting global climate change anyway and therefore cheaply available. In any way, it is important to operate PtG with a closed carbon cycle.

Decarbonization with Power-to-Gas So far, the necessity for energy storage and the physical, economical, and ecological parameters of the technology of Power-to-Gas have been described in detail. Now, a brief outlook on the potential for decarbonization with Power-to-Gas is given in the context of the energy transition in Germany and more over is given.

Technical Pathway of Decarbonization As seen, PtG can be very useful for the decarbonization of electricity and heat: It offers the required long-term storage for weeks of no wind and solar energy at reasonable cost and is a supplement/addition to biomass, geothermal energy, and solar energy for decarbonizing heating and cooling systems. The access is also given for mobility: although electric vehicles will be the most efficient way of using wind and solar power, their range is limited. Long-distance mobility, lorries, ships, and airplanes still demand energy carriers with high energy density. These can be hydrogen or SNG from Power-to-Gas or even wind kerosene or wind diesel from Power-to-Liquid. Biofuels will have their share also in heavy duty applications like tractors, but their potential is limited and not sufficient to cover all high energy density fuel demand (Sterner and Schmid 2009). A possible pathway towards decarbonization of the whole energy sector is given in Fig. 24. Power-to-Gas or Power-to-X will also be required to decarbonize the chemical industry. This sector is also using large amounts of fossil fuels like oil and gas in a nonenergetic way. To decarbonize industrialized nations not only by 80 % (2  C goal) but by 95 % (1.5  C goal), Power-to-X will become a requirement, since there

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Fig. 24 Energy transition scenario for all energy sectors in Germany until 2050 – costs and savings in Mio. €/a (Source: Gerhardt et al. 2014)

are no other technologies left that can technically do this. As mentioned, biomass does not have the potential but chemical products from wind and solar do.

Costs of Decarbonization with Power-to-Gas So technically, the energy transition and decarbonization is doable. And it is also feasibly regarding costs: wind and solar show generation costs below 10 €-cts/kWh and are therefore less expensive than new coal, gas, or nuclear power generation. What is missing is the cost for storage and balancing. The EU imports fossil energy carriers worth 400 Bio. € each year. If this money would be saved by the implementation of locally available renewable energy, it could refinance the necessary expensive infrastructure for networks and storage. There are calculations for Germany, that show a macroeconomic return of invest rate of 4–7 %, if a moderate increase of fossil fuels prices are assumed (see Fig. 25 and Gerhardt et al. (2014)).

Necessary Policy Framework What is then left for decision makers in the EU and worldwide? First of all, remove subsidies for fossil energy. Second, a must for the energy transition is the interlinkage of electricity, gas, heat, and transport sectors. The technical possibilities are given and should be used (Fig. 26).

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Fig. 25 Energy transition scenario for all energy sectors in Germany until 2050 – primary energy sources and demand in TWh/a (Source: Gerhardt et al. 2014)

Fig. 26 Technical pathways of the decarbonization of energy sectors, mobility, and chemical industry via renewable energy and interlinked energy storage and transport infrastructure and Power-to-Gas/Heat/Fuels at the heart of the system (Source: Sterner and Stadler 2014)

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Energy markets should be merged via energy storage and energy transmission. Power-to-Gas and Power-to-X are essential technologies that save costs by using existing storage and transmission infrastructure. Storage technologies should be developed in Europe to create jobs and values in the EU with these complex system technologies that would be needed worldwide at some point of time in future. But without framework conditions, we would not see a large-scale development of storage that is needed to bring costs down by mass production. To reduce import dependence, it is helpful to build up strategic “renewable reserves.” The still costintensive technologies like storage or electromobility should be cross-financed by CO2 funds, fossil fuel savings, and cheap renewables. To enable this transition, market barriers have to be removed. That includes better access of storage and renewables to control power markets, the avoiding of double taxing, and the implementation of limited tax exemptions. The storage problem is solved technically and global markets are ahead, but in history, no new energy technology did its way to the market without official support. Another requirement is the mandatory use of renewable power for storage, electromobility, and heat pumps. Otherwise, with fossil power, these new technology do not have the desired impact on climate change. And last but not least: policy makers need to explain to people the need of this energy transition due to climate change, import dependency, and depleting fossil resources in an open, transparent, and decisive way. We can find nice technical, eco-friendly solutions that are economic, but if we don’t convince society, we would implement decarbonization. Besides an energy transition, there is therefore also a strong need for the transition of storage and the transition of consciousness and awareness.

Concluding Remark The chapter shows that BioCCS (Biomass and CCS) is not the only option to reach the 1.5 °C climate target and that storage systems are ready for decarbonization of all sectors

Changes in the Future • Cost updates will be implemented. • Eventually emission reduction scenarios will be integrated.

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Reduction of Greenhouse Gas Emissions by Catalytic Processes Gabriele Centi and Siglinda Perathoner

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Short Introduction to Catalytic Concepts, Materials, and Technologies . . . . . . . . . . . . . . . . . . . Reduction of NCGG Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methane (CH4) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nitrous Oxide (N2O) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fluorocarbons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Catalytic Conversion of CO2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CO2 Use to Produce Monomers for Advanced Materials Polymers . . . . . . . . . . . . . . . . . . . . . . . . . . CO2 Hydrogenation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Urea and Derivate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Organic Carbonates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CO2 in Reforming Reactions and as Selective Oxidant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CO2 Utilization in Biocatalytic Routes and to Reduce Impact of Bioprocesses . . . . . . . . . . Introduction of Renewable Energy in the Chemical Production Chain Through CO2 Utilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Catalytic technologies for the abatement of greenhouse gases (GHGs) can effectively limit the increasing tropospheric concentration of GHGs and reduce their contribution to global warming. After introducing the general possible applications of catalytic technologies for GHG abatement, two specific cases are discussed: (1) reduction of anthropogenic emissions of non-CO2 GHGs (N2O and CH4) and (2) reduction or conversion of CO2. G. Centi (*) • S. Perathoner Dip. Ingegneria Elettronica, Chimica ed Ingegneria Industriale (DIECII), University of Messina, ERIC aisbl and CASPE-INSTM, Messina, Italy e-mail: [email protected]; [email protected]; [email protected] # Springer International Publishing Switzerland 2017 W.-Y. Chen et al. (eds.), Handbook of Climate Change Mitigation and Adaptation, DOI 10.1007/978-3-319-14409-2_49

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Combustion is one of the main options for controlling methane emissions. The use of catalytic combustion may yield economic benefits, due to the usually low concentration of methane in its emissions, and avoid the formation of by-products in traces like formaldehyde, which may be more harmful than methane itself. The types of catalysts, mechanism of action, and reactor options (regenerative catalytic combustion, reverse flow catalytic combustion, and catalytic combustion using a rotating concentrator) are discussed. The catalytic control of N2O emissions shows different specificities, because different types of emission sources are present. The catalytic abatement or reuse of N2O from industrial emissions (particularly adipic and nitric acid production), the treatment of emissions from power plants or waste combustion, the alternatives of catalytic decomposition or reduction, and the role of the other gas components (O2, NOx, SOx) are analyzed. The problem of the catalytic conversion of fluorocarbons is also briefly discussed. The case of carbon dioxide is different because, in this case, the issue is the development of cost- and energy-effective catalytic routes for its conversion to usable products. There are many catalytic routes for using CO2 as a building block in organic syntheses to obtain valuable chemicals and materials. Attention has focused recently on the catalytic conversion of carbon dioxide to fuels. In this case as well, different options exist, such as hydrogenation to form oxygenates (e.g., methanol) and/or hydrocarbons, dry reforming with methane, reverse water gas shift, or, in a longer-term perspective, different methods using solar energy directly or indirectly (via bioconversion). Limitations and possible advantages of these different options are analyzed.

Introduction The control of GHG emissions from anthropogenic sources is becoming a global challenge. In addition to regions such as Europe at the forefront of measures to reduce GHG emissions, there is a global trend to adopt advanced environmental political measures to reduce GHG emissions. EU leaders agreed on 23 October 2014 the domestic 2030 GHG reduction target of at least 40 % compared to 1990, following the roadmap on GHG emissions approved from the European Parliament for their reduction to 80 % with respect to 1990. On 11 November 2014, a historic US-China Joint Announcement on Climate Change reported that the USA and China joined the European Union in committing to new limits on GHG emissions. These three economic powerhouses emit about as much each year as the rest of the world combined, so their commitments have important implications for the world’s ability to stay within its carbon budget. The USA will reduce GHG emissions 26–28 % from 2005 levels by 2025. China announced its intent to peak carbon dioxide emissions around 2030 (around ten billion metric tons per year, with respect to emissions leveling off between 2030 and 2040 at approximately 12–14 billion metric tons per year) and to strive to peak earlier by reducing carbon emissions per unit of GDP by

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40–45 % from 2005 levels by 2020. The Cop 20 (UN climate change) conference (Lima, 1–12 December 2014) for the first time commits all countries – including developing nations – to cutting GHG emissions. The IPCC Fifth Assessment Report, finalized in November 2014 (Pachauri and Meyer 2014), showed how the “warming of the climate system is unequivocal” and “continued emission of greenhouse gases will cause further warming and longlasting changes in all components of the climate system, increasing the likelihood of severe, pervasive and irreversible impacts for people and ecosystems.” The report also remarked that “without additional mitigation efforts beyond those in place today, and even with adaptation, warming by the end of the twenty-first century will lead to high to very high risk of severe, widespread, and irreversible impacts globally (high confidence).” The implementation of the decisions taken at a political level coincides with the scientific indications deriving from the cited IPCC report that it is necessary to accelerate the measurer to reduce GHG emissions. Catalytic technologies offer effective cost-basis solutions for their control (Centi et al. 1999, 2003a). The “Technology Roadmap on Energy and GHG Reductions in the Chemical Industry via Catalytic Processes,” prepared recently by the IEA and the ICCA in collaboration with Dechema (IEA 2013), evidences the role of catalysis to meet the objectives of GHG reduction in the chemical industry, with a potential impact on the reduction of energy intensity by 20–40 % as a whole by 2050. In absolute terms, such improvements could save as much as 13 EJ and 1 Gton of CO2-eq. per year by 2050 versus a “business-as-usual” scenario. The white paper “Available and emerging technologies for reducing greenhouse gas emissions from the petroleum refining industry” prepared by US EPA (2010) shows the role of catalysis in reducing GHG emissions in refinery industry, one of the highest industrial consumers of energy. Although catalysis has been associated traditionally to chemical production and refinery, except for the relevant cases of catalytic converters for mobile sources and DeNOx systems for the reduction of NOx emissions from stationary sources, catalytic technologies for GHG emissions have a broader area of applications, as discussed in this chapter. By including the potential role of converting CO2 as a way to trade on a worldwide scale renewable energy (presented later), the potential is of several Gton CO2-eq. Catalytic technologies have thus the potential, although still underestimated, to be one of the pillars to reach the political goals to reduce GHG emissions. We may distinguish between direct and indirect roles of catalytic technologies in contributing to climate change goals. The direct role is associated to catalytic technologies for the conversion of GHG, either for direct conversion to not harmful products (e.g., conversion of N2O to N2) or having lower GWP (e.g., conversion of CH4 to CO2) or for reutilization of GHG (e.g., N2O utilization as selective oxidation or utilization of CO2 as raw material). In the latter case, it is important to distinguish when the utilization leads to an effective reduction of GHG impact on a LCA basis. For example, the reaction of CO2 with high-energy molecules such as epoxides to form carbonate needs to account the impact on GHG of forming the epoxide but also the positive impact of producing an alternative material to those based on fossil fuels.

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Therefore, the impact is not relative to utilization only of CO2 as raw material but to the associated effect on LCA bases. It is possible to indicate an effectiveness factor (EF) to the various routes for reducing GHG emissions, for example, for carbon dioxide. Sequestration and storage (CSS) has an average EF value of around 0.5, because it is necessary to consider the energy necessary to capture and store CO2. On the contrary, several of the routes for chemical utilization of CO2 have an EF value higher than one, for the benefit in substituting other materials starting from fossil fuels only (Centi and Perathoner 2014; De Falco et al. 2013). When renewable energy is utilized in the process of converting CO2 to valuable fuels, EF may be even larger than a decade on a timescale of 20 years. It is thus necessary to account this EF value in estimating the impact of the different routes of utilization of GHG and not only the direct amount of GHG utilized as raw material. The indirect role of catalytic technologies in contributing to climate change goals is related to various aspects, from the role of catalysis to produce biofuels having lower GHG impact (on LCA bases) with respect to the equivalent fossil fuel-based ones to the role of catalysis in developing new production routes having a better efficiency of using raw materials and energy (Centi and Perathoner 2014). There are additional aspects more difficult to estimate in terms of positive impact on climate change goals. For example, enabling a new competitive catalytic route to produce polyurethane foams (using CO2 as one of the feedstocks), in addition to a specific benefit (compared to production of conventional polyether polyols, the production of polyols with 20 wt% CO2 allows for GHG reductions of 11–19 % as shown by von der Assen and Bardow 2014), allows further benefits related to the utilization of the foam to insulate buildings. We limit discussion here, however, to only routes related to the direct role of catalytic technologies in contributing to climate change goals. A further necessary preliminary differentiation is between technologies for converting non-CO2 greenhouse gases (NCGG) and those related to utilization of carbon dioxide (CO2), due to the different types of sources and problems to address. In fact, NCGGs have typically a GWP (over a 20-year time horizon) significantly larger than CO2, which is conventionally put equal to one: 72 for CH4, 289 for N2O, to values ranging from 3000 to over 16,000 for hydrofluorocarbon depending on the specific structure. The emissions of NCGGs are lower of those CO2: in 2010, the sum of NCGG emissions was about 15 Gton CO2-eq. with respect to about 35 Gton CO2-eq. emissions of CO2 from fossil fuel exploitation plus land use change (Montzka et al. 2011). On the average, NCGGs contribute to about 35–45 % of total climate forcing from all LLGHGs (range represents direct forcing to the sum of direct and indirect forcing). Climate or radiative forcing is the time-dependent responses of the warming influence. Cut NCGG emissions could substantially lessen future climate forcing, with additional ancillary benefits that include reduced costs for climate mitigation relative to CO2-only approaches, improvements in air and water quality, reduced acid deposition, and decreased eutrophication of aquatic ecosystems (Montzka et al. 2011). There is a tendency to increase NCGG emissions, for example, due to the increase of shale gas production (CH4) and biofuels (N2O, due to the larger use of fertilizers in monocultures).

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Short Introduction to Catalytic Concepts, Materials, and Technologies The reduction of GHG emissions by catalytic processes belongs to the general area often referred to as environmental catalysis or catalysis for environment protection, which is part of the broader area of catalysis for sustainable industrial production (Cavani et al. 2009). The largest part of catalytic technologies in this field is based on solid catalysts, because cost, pressure drop, effectiveness in a wide range of experimental conditions, low sensitivity to deactivation, and ease of management and handling are the critical aspects for these applications. Solid (heterogeneous) catalysts offer advantages over homogenous catalysts from these points of view and for this reason predominantly used in the area of environmental catalysis. The term “solid or heterogeneous catalyst” indicates a material having one or both of the following characteristics: • Increases the reaction rate (moles converted per unit time) of a chemical reaction, thus enhancing the conversion of a reagent, that is, the moles of a reactant converted with respect to inlet moles of the reactant • Changes favorably the reaction rate of one reaction with respect to competing reactions, thus enhancing the selectivity, that is, the fraction of moles of the reagent(s) converted to the desired product The catalyst itself does not undergo any permanent change, although it participates in the reaction mechanism providing an alternative reaction pathway, which modifies the energy associated with the pathways of reaction (activation energies of formation of reaction intermediates). However, the thermodynamics of the reaction (e.g., the net reaction enthalpy and free energy) do not change. The catalyst thus changes the kinetics, not the thermodynamics, of the reaction. A catalyst may undergo a progressive modification with time, leading to an alteration of the catalytic behavior (usually associated with a loss in catalytic performance, that is, catalyst deactivation), even if formally the catalyst is not modified in the catalytic cycle. This is a consequence of chemical reaction and/or of external factors (e.g., other components of the feed, the reaction temperature, etc.). The three properties that characterize a catalyst are (1) activity, (2) selectivity, and (3) stability (i.e., no deactivation). However, there are a number of other aspects equally important for the choice of the catalyst, such as its texture (porosity) and shape, its macro- and microstructure, and its mechanical strength properties. In defining the activity of the catalyst, differentiation must be made between the following aspects: • Intrinsic activity, that is, the rate of reaction not affected by mass or heat transfer limitations (see below), which may refer to total weight or volume of the catalyst or to the amount of the active phase or component; the units of measure are moles per time and per mass or volume.

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• Effective activity, that is, the measured rate of reaction (effective activity depends on the conditions of testing, because it can be influenced by mass or heat transfer limitations); the units of measure are the same as for intrinsic activity. The ratio between effective and intrinsic activity defines the effectiveness factor (η) of the catalyst. • Catalyst performances and specifically the following quantities: 1. Conversion: the ratio between the molar flow of reactant converted with respect to the inlet molar flow of the same reactant. 2. Selectivity: the ratio between molar product flows at the outlet of the reactor with respect to the inlet molar flow of the reactant. 3. Yield: the conversion multiplied by the selectivity. 4. Productivity: the ratio between molar product flows at the outlet of the reactor and catalyst weight or volume. The units of measure are the same as those for the reaction rate, but the two concepts should not be confused. Conversion, selectivity, and productivity depend on the integrated change in the reaction rate(s) along the reactor. Therefore, these parameters (often indicated as global activity parameters) are not intrinsic characteristics of the catalyst. When more than one reactant is present, conversion, yield, and selectivity should refer to the limiting reactant, that is, the reactant that may limit (also considering reaction stoichiometry) the conversion. However, these parameters (conversion, yield, and selectivity) also can refer to other reactants, and it is therefore a good practice to indicate the reference reactant. While all these terms depend on the reaction conditions (reaction temperature and reactant composition), conversion, selectivity, yield, and productivity also depend on the type of reactor and space velocity (total volumetric flow of the reactants divided by the volume of the catalyst). The inverse of the space velocity is defined as the contact time, that is, the time required by the flow of reactants to fill the volume occupied by the catalyst. Sometimes, the space velocity refers to the apparent volume of the catalyst, that is, the total volume of the catalyst (this volume depends on the grain size and packing of the pellets) and sometimes to the specific catalyst volume, that is, considering the void fraction of the catalytic bed. For this reason, it is preferable to refer not to the catalyst volume but to the mass of catalyst. In this case, the units of measure of the space velocity (indicated also as space–time) are gċsċmol
1, that is, the inverse of the units of measure of the reaction rate, although the two concepts are different. In gas–solid catalytic reactions, the space velocity is often defined as GHSV (gas hourly space velocity), which is exactly the same definition as that of space velocity, but the time unit is hours instead of seconds. In liquid–solid reactions, the equivalent definition is LHSV (liquid hourly space velocity). In the discussed applications, the reactant(s) is typically present in one or more different phases (gas and/or liquid) with respect to the solid catalyst. The reactant (s) should thus diffuse to the catalyst surface before reacting. The reactant(s) diffuses across the boundary gas or liquid layer that surrounds the solid catalyst body (pellet, layer, or film) and diffuses inside the catalyst pore volume. These two steps are referred to below as external and internal diffusion. Often in environmental

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applications, the rate of these steps is slower than the rate of the chemical reaction (s) occurring at the catalyst surface, and therefore the rate of the overall process becomes controlled by the mass transfer. Gradients in concentration through the boundary fluid layer and throughout the catalyst pore volume develop. The heat transfer to or from the catalyst surface (due to the heat generated or consumed by the reaction) can also determine temperature gradients within the catalyst pellet or layer and through the fluid boundary layer. The magnitude of the effect depends on the effectiveness of internal and external heat transfer, which is a function of the rate of heat generation/consumption, the solid characteristics, and the fluidodynamics of the system. The presence of thermal or concentration gradients influences considerably selectivity, activity, and/or stability. Therefore, proper reactor design integrated with catalyst design is critical to improving performances. Different types of reactors are used commercially in these reactions. The choice depends on various factors, such as the catalyst characteristics, mass and heat transfer limitations, scale-up, fluidodynamic and flow regimes, pressure drop, liquid holdup, etc. However, often there is a contrast between optimal conditions for efficient multiphase contact, high catalyst effectiveness and wetting efficiency, and low fouling/attrition and pressure drop. In these cases, new types of reactors based on structured catalysts are an attractive alternative to conventional reactors, due to low-pressure drop, the absence of a need for catalyst separation, and the large geometrical surface area. Structured catalysts offer an efficient multiphase contact and minimize the influence on the reaction rate and selectivity of the reagents’ diffusion and products’ back-diffusion. They also offer some additional advantages: easy catalyst separation and handling, minimization of contamination of the solution by the catalyst, safer operation, improved heat supply and removal, and easier scale-up and technology manageability. The latter characteristics of the structured catalysts often are the critical factors for the selection of these technologies in environmental protection applications. Four main types of macrostructured catalysts can be distinguished: (1) monoliths, (2) foams, (3) cloths, and (4) membranes. The main classes of catalysts used for the reduction of GHG emissions are metals (noble and not noble metals, typically supported), oxides (typically multicomponent metal oxides in the bulk or support form), and solid acids (clays, mixed oxides, and, in particular, ordered metal oxides: zeolite and mesoporous materials). Solid catalysts come in a multitude of forms and can be loose particles or small particles on a support. The support can be a porous powder, such as aluminum oxide particles, or a large monolithic structure, such as the ceramics used in some applications. The choice depends on many requirements, but the critical ones are the type of reaction and relative reaction conditions and the choice of the reactor to use. Industrial catalysts are generally shaped bodies of various forms, for example, rings, spheres, tablets, and pellets. Monolithic-type catalysts, similar to those in automobile catalytic converters, are also used. The production of heterogeneous catalysts entails numerous physical and chemical steps. The conditions in each step have a decisive influence on the catalyst properties. Catalysts must therefore be manufactured under precisely defined and

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carefully controlled conditions, including the control of the level of the impurities in raw materials, which may have a dramatic effect on the performances. Depending on their structure and method of production, solid catalysts can be divided into three main groups: (1) bulk catalysts, (2) supported catalysts, and (3) ordered porous structure catalysts. Bulk catalysts are used when the active components are cheap, there are no specific diffusional limitations on the reaction rate under industrial relevant conditions, and other specific requirements (e.g., density and mechanical resistance for fluid-bed reactor applications) are absent. Supported catalysts are the class of catalysts most used industrially. They are used under the following circumstances: • When expensive active components such as noble metals are employed and there is the need for their effective dispersion over a support that also provides the stabilization of these metal nanoparticles against their sintering • When a modification of the properties of an oxide by supporting it over another oxide is necessary • When the density of the catalyst and its mechanical properties are not suited for the specific reactor operation, as well as in other cases The most common class of ordered porous structure catalysts are zeolites, but there are many more examples, from ordered mesoporous materials (e.g., mesoporous silica such as SBA-15 and MCM-41) to other class of inorganic or inorganic–organic hybrid materials. Zeolites are microporous crystalline solids with well-defined structures. Generally, they contain silicon, aluminum, and oxygen in their framework and cations, water, and/or other molecules within their pores. Many occur naturally as minerals, but the most used commercially are synthetic one due to their better reproducibility. A defining feature of zeolites is that their frameworks are made up of four connected networks of atoms. These tetrahedra can then link together by their corners to form a rich variety of beautiful structures. The framework structure may contain linked cages, cavities, or channels, which are of the right size to allow small molecules to enter – that is, the limiting pore sizes are roughly between 3 and 10 Å in diameter. There are nearly 200 different types of framework structures prepared and identified, but the theoretical number is much larger. Zeolites have the ability to act as catalysts for chemical reactions taking place within the internal cavities.

Reduction of NCGG Emissions Methane (CH4) Methane is the second most important long-lived GHG. Approximately 40 % of methane is emitted into the atmosphere by natural sources (e.g., wetlands and termites), and about 60 % comes from human activities (about 400 Mt/y) by different sources (Fig. 1).

Reduction of Greenhouse Gas Emissions by Catalytic Processes Coal Mining 8%

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Agriculture (*)3

%

Enteric Fermentation 27%

Landfills 12%

Percentage Oil & Gas 24%

0

5

10

Wasterwater 7%

15

20

25

Rice Cultivation 7%

Stationary & Mobile Sources 3%

Other sources 6%

Biomass 3%

(*) Manure management

Fig. 1 Estimated global anthropogenic methane emissions by source, 2015

Atmospheric methane reached a new high of about 1,824 ppb in 2013, due to increased emissions from anthropogenic sources. Around half of methane emissions from anthropogenic activities derive from sewage disposal, rice cultivation, livestock, and burning of biomass. The remaining part is associated with production, transport and use of natural gas, coal mining, and disposal of solid waste. A considerable part of the methane emitted is converted to CO2 and water in the troposphere by reaction with hydroxyl radicals, around 500 Mt/y. The total methane removed annually in all sinks is estimated to be about 600 Mton/year, but a large amount uncertainly exists in the balance of methane emissions. The current role of methane in global warming is large, contributing 1.0 W m
2 out of the net total 2.29 W m
2 of radiative forcing (Pachauri and Meyer 2014). The expected increase in shale gas production will further increase impact on climate changes, because the carbon footprint of shale gas (on average, integrated over 20 years) is higher than that of conventional natural gas and coal (about 51 gC per MJ with respect to about 38 and about 30, respectively). Methane emissions from the oil and gas industry derive mainly from the venting of unused gas during oil production, the use of natural gas to purge or to operate pipeline equipment, and leakage from the gas distribution system. It is estimated that these emissions will nearly double in two decades (due to the increase in gas production and pipeline transport) unless abatement measures are taken. Coal measures contain methane, which will be released by mining. The methane is removed by drainage of the coal measures before and during mining; the rest is

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removed in the ventilation air while mining is taking place. Drainage gas is high in methane concentration and can be used directly to generate electricity. The emissions associated to production and transport of coal is expected to increase in the future from the current value of about 22–33 Mton/year by year 2020 unless actions are taken. A major source of methane emissions is the anaerobic decomposition of solid wastes in landfills, although the amount generated depends upon the method of dumping and on the composition of the waste and therefore vary considerably from country to country. It is expected that methane emissions from solid waste disposal will increase from the current 32–62 Mton/year by year 2025. Other anthropogenic sources of methane include sewage treatment, rice growing, livestock, and biomass burning. The large majority of these emissions are associated to developing countries. Methane emissions from sewage treatment are expected to increase from current 35 Mton/year value to 58 Mton/year, while those deriving from rice growing have leveled off in the last two decades. Livestock (mainly enteric fermentation in ruminants) contributes an estimated 49 Mton/year of methane emissions, but significant is also contribution from the anaerobic decomposition of manure. Biomass burning gives rise to direct emissions of methane, but has also the negative impact of reducing the ability of the soil to act as a sink. An increase of about 20–25 % of these emissions is estimated in two decades. The increase in methane emissions should be contrasted by introducing highly efficient technologies to limit the emissions that can be reduced, because only a part of the global emissions of methane can be effectively controlled. The complexity of the problem derives from the very broad range of situations and type of emissions, e. g., various methodologies should be used and integrated. It is possible to distinguish between two main types of sources: (i) confined, e.g., the gas is physically contained and can be managed with industrial process units, and (ii) diffused, e.g., methane is produced over a large land or aqueous area. The strategies for mitigation of the two cases are different (Stolaroff et al. 2012). For the latter case of diffuse sources, three general strategies of mitigation have been developed: suppressing methanogenesis, biocovers, and caps. The latter may be related to catalytic technologies, differently from the first two methodologies, although the first deals on enzymatic catalysis that however is not covered here. Caps are a typical method for controlling landfill emissions, being the land or manure ponds covered with an impermeable layer (a plastic sheet or layer of clay) and an array of wells and pipes to collect the gas then treated as discussed later. An alternative possibility is to use materials, such as liquid solvents and nanoporous zeolites, which can capture effectively the fugitive methane emissions (Kim et al. 2013). The methane stream produced during the regeneration of these capture materials can be then treated as discussed below. Table 1 reports examples of typical concentrations of CH4 in some relevant cases of methane sources. Concentrated streams (above about 40 %) can be used as chemical feedstocks, with syngas, methanol, and carbon black production among the main possibilities (but requiring typically further treatments to purify the gas and concentrate above about 95 %). In the concentration range 30–60 %, different

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Table 1 Examples of typical concentrations of CH4 in relevant cases of methane sources (Adapted from (Stolaroff et al. 2012)) Source Arctic air (current reference free air) Swine feeding or dairy milking ventilation air Enclosed manure storage headspace US landfill, at surface Fugitive methane emissions at shale gas production wells Coal mine VAM Anaerobic digester gas Landfill drainage gas Coal postmining drainage gas Coal premining drainage gas Natural gas, at wellhead

Methane concentration, vol fraction 2–8 ppm (1.8 ppm) 10–300 ppm 140–28,000 ppm (2.8 %)