Aligning Climate Change and Sustainable Development Policies in Asia [1st ed. 2021] 9811601348, 9789811601347

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Hooman Farzaneh Eric Zusman Yeora Chae   Editors

Aligning Climate Change and Sustainable Development Policies in Asia

Aligning Climate Change and Sustainable Development Policies in Asia

Hooman Farzaneh • Eric Zusman • Yeora Chae Editors

Aligning Climate Change and Sustainable Development Policies in Asia

Editors Hooman Farzaneh Interdisciplinary Graduate School of Engineering Sciences Kyushu University Fukuoka, Japan

Eric Zusman Sustainability Governance Centre Institute for Global Environmental Strategies Hayama, Japan Center for Global Environmental Research National Institute for Environmental Studies Tsukuba, Japan

Yeora Chae Korea Environment Institute Sejong, Korea (Republic of)

ISBN 978-981-16-0134-7 ISBN 978-981-16-0135-4 https://doi.org/10.1007/978-981-16-0135-4

(eBook)

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 This work is subject to copyright. All rights are solely and exclusively licensed 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, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

The term “co-benefits” has come to occupy a central place in policy discussions involving climate change and sustainable development over the past three decades. The reason these discussions increasingly feature co-benefits is that mitigating climate change while cleaning the air, improving public health, creating new jobs, and delivering other development benefit can save money and lives. Yet, because policymakers, researchers, and others working in related fields often lack the analytical tools and practical experiences with aligning climate and sustainable development policies, the potential for co-benefits has frequently gone unrealized. This book aims to make sure that the potential to achieve co-benefits is no longer a lost cause. To ensure policymakers and other interested audiences can seize on that opportunity, the book employs a unique combination of analytical methods and case studies to demonstrate how factoring co-benefits into decisions can enhance outcomes in several policy-relevant contexts in Asia. The book begins with an introductory chapter that provides an overview of the definition and evolution of the concept of co-benefits. This is followed by a second section that shares quantitative approaches to estimating co-benefits, spotlighting the important role of cities in this regard. A third section presents a series of case studies from the energy sector in Northeast and Southeast Asia. A final section concludes with new perspectives on co-benefits that range from linking climate change with biodiversity and social justice to leveraging co-innovation to facilitate the transfer of co-benefits technologies. The book is not only practical but timely. As countries in Asia and beyond seek to achieve their Paris Agreement climate targets and the Sustainable Development Goals (SDGs), they will increasingly look for ways to integrate responses to these two processes. Co-benefits will hence continue to grow in importance through 2030. Therefore, while this book is targeted to the reader who is already familiar with climate policy and sustainable development processes, its use, like the term co-benefits itself, will likely attract an expanding readership over time. For similar reasons, the book should also appeal to those already working on but hoping to v

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expand the scope of their studies on clean energy, climate mitigation, sustainability transitions, and comparable themes. The book represents the collective efforts of a committed network of researchers based in Asia. Drafts of many of the books chapters were presented at a workshop convened by Kyushu University, the Ministry of Environment, Japan, and the Asian Co-benefits Partnership on January 25, 2021. Chapters 1, 4, 7, 8, 9 and 10 benefited from research and programmining supported by the Ministry of Environment, Japan as part of its comissioned work on promoting co-benefits from air pollution control. The editors express their deep appreciation to the Ministry of Environment, Japan for this funding and to the authors for their efforts to contribute to the book and the lofty goals it aspires to achieve. Fukuoka, Japan Hayama, Japan Sejong, South Korea December 2020

Hooman Farzaneh Eric Zusman Yeora Chae

Contents

1

An Introduction to Co-benefits: Core Concepts and Applications . . . Eric Zusman, Yeora Chae, Hyunkyu Kim, and Hooman Farzaneh

Part I 2

3

4

6

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The Quantitative Modeling of Climate Co-benefits and Sustainable Development

The Urban Sustainable Development Index: A Comparative Analysis of Low Emission Strategies in Urban Areas . . . . . . . . . . . . . . . . . . Ayas Shaqour and Hooman Farzaneh

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A Quantitative Model for Forecasting Energy Demand and CO2 Emissions in Pakistan: Toward a Sustainable Energy System . . . . . Sajid Abrar and Hooman Farzaneh

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A Multiple Benefits Assessment of the Utilization of High-Efficiency Heat Only Boilers in Ulaanbaatar, Mongolia . . . . . . . . . . . . . . . . . . Hooman Farzaneh and Eric Zusman

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Part II 5

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The Co-benefits of Climate Change Mitigation Strategies

Quantifying and Integrating Co-benefits of Renewable Energy Policies in South Korea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ho-Cheol Jeon, Yong Jee Kim, and Yeora Chae

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The Co-benefits of Renewable Energy Policies in Japan: Barriers and Ways Forward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Takai Etsujiro

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Quantifying the Co-benefits of Solar Energy in China: Opportunities and Barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Mao Xianqiang, Xing Youkai, and Eric Zusman

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Contents

Part III

New Perspectives on Co-benefits

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Biodiversity Co-benefits: Narrowing the Gap Between Analysis and Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Kaoru Akahoshi and Eric Zusman

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Creating Social Co-benefits for Sustainable and Just Society . . . . . . 149 So-Young Lee

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Enabling Japan’s Low Emissions Technology Collaboration with Southeast Asia: The Role of Co-innovation and Co-benefits . . . 163 Nandakumar Janardhanan, Ngoc-Bao Pham, Kohei Hibino, and Junko Akagi

Chapter 1

An Introduction to Co-benefits: Core Concepts and Applications Eric Zusman, Yeora Chae, Hyunkyu Kim, and Hooman Farzaneh

1.1

Introduction

The year 2015 brought two landmark agreements that signaled a growing willingness from many countries to steer onto more sustainable development paths. The first of these landmark agreements, the 2030 Agenda for Sustainable Development (and its Sustainable Development Goals (SDGs)), endorsed a range of 17 social, economic, and environmental goals to help developed and developing countries reorient development paths from 2015 to 2030 (Olsen et al. 2019). In line with principles of sustainable development, the 2030 Agenda for Sustainable Development called on all countries to formulate and implement integrated development strategies that worked across multiple social, economic, and environmental objectives (Zhou and Moinuddin 2017). With the agreement over the SDGs, policymakers would seek integrated solutions to a variety of development issues, including climate change (TERI 2017; Kainuma et al. 2017). A few months after the SDGs, the Paris Climate Agreement offered a second critical indication that many countries were ready to alter development paths. The Paris Agreement called for countries to make “efforts to limit the temperature increase to 1.5
C above pre-industrial levels” (UNFCCC 2015). Further, to grant countries flexibility in how they achieved these goals, the Paris Agreement

E. Zusman (*) Sustainability Governance Centre, Institute for Global Environmental Strategies, Hayama, Japan Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan e-mail: [email protected] Y. Chae · H. Kim Korea Environment Institute, Sejong, Japan H. Farzaneh Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Fukuoka, Japan © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 H. Farzaneh et al. (eds.), Aligning Climate Change and Sustainable Development Policies in Asia, https://doi.org/10.1007/978-981-16-0135-4_1

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strengthened a bottom-up pledge and review mechanism for climate actions that had begun to take shape a decade earlier (Zusman 2008). Under this pledge and review mechanism, countries would develop and submit their own nationally determined contributions (NDCs) to the United Nations Framework Convention on Climate Change (UNFCCC) (UNFCCC 2015). By placing the emphasis on country ownership and bottom-up participation, there was hence a strong incentive to align national climate actions with other sustainable development priorities. Mirroring the SDGs, there was a growing need for integrated solutions to climate and other sustainability concerns (TERI 2017; Kainuma et al. 2017). As suggested above, not only was 2015 a year to be welcomed by the international community, it also presented new opportunities for policymakers from different countries and diverse backgrounds. In terms of these opportunities, an internationally agreed consensus was forming that the world would need to change course to avoid climate and other planetary crises (Rockström et al. 2009). For decision makers working on climate specifically or sustainable development generally, never before had such a mandate to move their agendas forward been given such high-level support. Further, both the SDGs and Paris Agreement suggested that country efforts to mitigate climate change should be integrated with actions on other dimensions of sustainable development (Amanuma et al. 2018). Yet the opening of these opportunities also presented policymakers with important questions. Chief among these questions was how to strengthen the integration between climate change and other sustainable development concerns (King 2003)? This question—which is also the main question addressed in this book—has taken on an added degree of importance as policymakers have struggled to achieve the SDGs and Paris Agreement pledges, in part, due to the challenges of aligning their climate and sustainable development agendas (Hajer et al. 2015). Fortunately, policymakers and other relevant stakeholders would not need to start with blank slate in answering this question. In fact, for nearly 30 years, there has been a significant amount of research on a term that sits at the center of this book and a concept that could help join climate and sustainable development in a variety of contexts: co-benefits (Elkins 1996). Co-benefits refer to the collection of benefits that result from actions that mitigate climate change while achieving other sustainable development objectives (ACP 2016; Miyatsuka and Zusman 2008). In addition to the climate benefits from reducing heat-trapping gases or climate-warming pollutants, co-benefits include reductions in air, water, and waste pollution as well as improvements in public health and the creation of new jobs. Though there has been a significant amount of research on co-benefits, there has been less progress with its applications. In fact, one of the challenges for researchers and policymakers is employing the concept of co-benefits to help support the formulation and implementation of integrated solutions to climate change and sustainable development concerns. This book will aim to address three areas that can help policymakers and other stakeholders work toward these mutually beneficial ends. 1. Analytical Methods: The first section provides an overview of recent advances in the techniques and tools that can be used to quantify co-benefits. The section aims

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to shed light on how several of the methods and indices used to assess co-benefits. In so doing, it underlines the growing importance for policymakers to not only measure a range of impacts but to understand the data and the steps that go into a co-benefits analysis. 2. Case Studies: The second section illustrates how to use different analytical methods in case studies from countries in Asia. The section demonstrates that one of the areas where there exist significant potential for co-benefits is renewable energy. While quantifying co-benefits from renewables is hence necessary, it may not be sufficient. There may be other barriers to achieving co-benefits; the chapters in this section also outline how these barriers can be overcome. 3. New Perspectives on Co-benefits: The third section describes new perspectives on biodiversity and social co-benefits as well as how the concept of co-innovation can help deliver co-benefits. The section stresses that there are variety of entry points through which co-benefits can be achieved as well as a need to understand the institutional and socioeconomic enablers needed to realize co-benefits. The remainder of this introductory chapter is divided into two sections. The next section provides an overview of the different lines of research on co-benefits, highlighting the term’s origins and applications. The third section summarizes the findings from the book’s chapters and points to a way forward for future research.

1.2

Co-benefits: Origins and Applications

The concept of co-benefits originated in the 1990s (Elkins 1996; Burtraw and Toman 1997; Ayres and Walter 1991).1 At that time, researchers working on the concept were most interested in persuading cost-conscious policymakers in developed countries that investing in greenhouse gas (GHG) mitigation was economically feasible. To make this case, they argued that some actions that mitigate GHGs also led to improvements in air quality and public health as well as increases in eco-friendly jobs and clean technologies that could offset mitigation costs (Jochem and Madlener 2003). Further, as these development co-benefits tended to be local, near-term, and more certain than climate benefits, they could also appeal to politicians who were unlikely to support actions that delivered only global, long-term, and more uncertain benefits (Krupnick et al. 2000). In this view, co-benefits were seen additional development benefits of climate mitigation policies (such as a carbon tax) in mostly developed countries (Morgenstern 1991; Markandya and Rübbelke 2004). With this initial developed country perspective on co-benefits in hand, researchers would employ energy, economic, air pollution, and health models to identify the magnitude of these offsetting benefits. This was typically done by looking at the air quality and resulting health impacts from a hypothetical climate

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At that time, co-benefits were often referred to as “ancillary benefits.”

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policy. In many instances, the magnitude of the health benefits from that policy was greater than its costs. As such, factoring co-benefits into a climate policy helped demonstrate that said policy was economically sound. Further, factoring co-benefits into a climate policy decision could not only strengthen the justification for that policy but also enhance its design (Pearce 2000). In the years since that initial work, a second phase began that placed a greater focus on co-benefits from developing countries (see for example, Aunan et al. 2004). This shift in focus came due to an increase in the availability of data and flexibility of modelling frameworks. It also represented the realization that if only developed and not developing countries mitigated climate change, it would be difficult to avoid the worst impacts of a warming climate. The participation of developing countries was needed to help avert these impacts (Zusman 2008). However, for many developing countries, mitigating climate change fell much further down the policy agenda than alleviating poverty, ensuring a steady supply of food and energy, and providing essential goods and services (Uchida and Zusman 2008). Given this understandable ranking of policy preferences, researchers recognized that co-benefits could help calm concerns that efforts to mitigate climate change would come at the expense of achieving higher-order development priorities. Climate change and development were not necessarily substitutes; carefully designed interventions could make them complementary (Pearce 2000). The above logic has since led to a sharp increase in studies that would help to quantify the co-benefits from different sectoral policies and projects in developing countries (see again Aunan et al. 2004). In estimating these benefits, researchers would help to bring a few points into focus. The first was that the magnitude of the local development co-benefits tended to be larger in developing than developed countries. This was because developing countries generally had more polluted air and denser populations; hence, even modest changes in the production of sustainable energy or the provision of sustainable transport could have larger marginal impacts on the environment and human health (Pearce 2000). This finding held across a large number of studies. For example, Nemet et al. (2010) reviewed 37 relevant peer-reviewed studies on air quality co-benefits and found that the estimated co-benefits of developed countries ranged from $2 to 128/tCO2, while those of developing countries fell between $27 and 196/tCO2. An additional shift that occurred from analyzing benefits in developing countries involved the definition of co-benefits. More concretely, by looking a broader range of often sectoral or development as opposed to climate policies and projects, co-benefits in developing countries were often seen as the climate benefits of options meant first and foremost to achieve sustainable development priorities (Miyatsuka and Zusman 2010). Yet another major shift in the definitions of co-benefits would occur approximately a decade later. The key to this shift was a growing literature from atmospheric scientists who focused on what had previously been viewed as air pollutants that could warm (or cool) the climate in the near term. Pollutants such as black carbon would remain in the atmosphere for much shorter times than GHGs such as carbon dioxide (CO2); during that much shorter period, however, they would have a

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Phase 1 (1990): Developed countries achieve development co-benefits from climate policies (e.g. CO2 tax)

Phase 2 (2005): Developing countries achieve climate co-benefits from sectoral policies and projects

Phase 3 (2010): All countries achieve air, climate and health co-benefits from migang SLCPs

Phase 4 (2015): All countries achieve a range of co-benefits from a variety of entry points and enablers

Fig. 1.1 Four phases of co-benefits’ research

much stronger warming effect on the climate. Moreover, removing what would collectively be termed short-lived climate pollutants (SLCPs)—including black carbon, methane, and tropospheric ozone—would also be good for air quality, health, crop yields, and other development needs. Backed by both atmospheric science and modelling research, several studies would show that policies and projects mitigating SLCPs could also deliver significant benefits for climate and development (UNEP/WMO 2011; UNEP APCAP and CCAC 2019; ACP 2014). A final fourth stage on the work on co-benefits has arguably built upon and extended lessons learned from the previous phases (see Fig. 1.1 for an illustration of the four phases). In this phase, the key development has been the advent of the SDGs and the Paris Agreement. As noted in the introduction of this chapter, both of these international agreements represented a realization among many countries that business-as-usual development paths were ultimately unsustainable (Amanuma et al. 2018). In addition, the collective insights from many years of co-benefits’ research revealed that it is feasible for different countries to work on co-benefits differently. More concretely, some policymakers may want to work through a climate, development, air pollution, or even biodiversity entry point to mitigate climate change and achieve other priorities (see Chap. 11 for a review of the entry point argument). Table 1.1, which summarizes the results of more than 30 studies published since 2014 (and the Paris Agreement and SDGs), illustrates the proliferation of entry points and related variation in applications of co-benefits. For example, the table lists not only energy and climate policies but also from wastewater projects and lifestyle changes. Beyond this variation in applications in this fourth and current phase, researchers have continued to pursue work on the estimation of co-benefits on increasingly ambitious climate targets. For example, recent work from Wang et al. (2020) shows that the full benefits of California’s pledge to achieve net-zero emissions by 2050

National climate policies NDCs or medium-term mitigation strategies Integrated nationallevel air pollution and climate policies Subnational climate policies Carbon tax/fee Low carbon plans Technology promotion policies Structural changes to city’s economy Climate finance projects (in multiple sectors)

Type of policy and sectoral focus Climate change policies Global/regional climate policies (based on IPCC scenarios)

• Reductions in premature mortality and morbidity (including disability adjusted life years (DALY)) • Reduction in noncommunicable diseases • Reductions in premature mortality and morbidity • Reductions in multiple forms of pollution

• Reductions in air pollutants (PM, SO2, and NOx) • Improvements in air quality

• Reductions in multiple air pollutants (fine particulate and ozone) • Improvements in air quality • Reductions in multiple air pollutants (PM and ozone) • Improvements in air quality

• Reductions in premature mortality and morbidity

• Reductions in premature mortality and morbidity

Environmental benefits

Health benefits

Table 1.1 Summary of co-benefits studies 2014–present

• Reductions in time spent in traffic • Improvements in educational opportunities and outcomes

• Reductions in fossil fuel dependencies • Creation of green jobs (in the renewable energy sector) • Improvements in energy security • Creation of green jobs • Improvements in infrastructure and land use • Reductions in healthcare expenditures

–

Socioeconomic benefits

ADB (2017)

Buonocore et al. (2018), Liu et al. (2018), Jiang et al. (2016)

• Achievement of subnational climate targets

• Reductions in CO2

Li et al. (2018), New Climate Institute (2015a, b, c, d, 2016)

Markandya et al. (2018), Shindell et al. (2017)

Source(s)

• Achievement of NDC targets

• Achievement of Paris Agreement targets

Climate benefits

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• Reductions in premature mortality and morbidity –

Panel D. Policies in construction sector Low carbon/green/sus- – tainable building policies

Waste management/ 3Rs policies (recycling of home appliances)

Energy efficiency policies (often in heavy industries such as cement or steel) Wastewater and waste management policy Wastewater or waste to – energy policies/project using natural ecosystems to help treat wastewater

Energy policy Clean energy policies

• Modest to significant reductions in GHGs

• Increases in reutilization rates of waste • Reductions in landfill costs • Increases in land for other productive purposes

• Modest reductions in GHGs (not quantified)

• Modest reductions in GHGs (from the reuse of methane for energy)

• Increases in access to energy resource (biogas) (especially for rural communities)

• Reductions in land pressures • Reductions in multiple air pollutants • Reductions in energy use

• Reductions in energy costs

• Significant reductions in CO2 or CO2eq

–

• Significant reductions in air pollutants (PM, SO2 and NOx)

• Reductions in strains on the energy system (from improving energy use intensity)

• Reductions in CO2

–

• Reductions in multiple air pollutants

(continued)

Balaban and de Puppim Oliveira (2017)

Rashidi et al. (2017), Menikpura et al. (2014), Challcharoenwattana and Pharino (2015), Mittal et al. (2017)

Islam (2018), Laramee et al. (2018), Hagen et al. (2017)

Zhang et al. (2015)

Tham et al. (2018)

1 An Introduction to Co-benefits: Core Concepts and Applications 7

Type of policy and sectoral focus Health benefits Transport policy Improvements in vehi- • Reductions in premacle technologies ture mortality and morShifting to public bidity (including transport disability adjusted life More active lifestyles years (DALY)) Changes in urban design Reliance on information and communication systems Improved diet and lifestyles Policies promoting • Reductions in premahealthier diets and ture mortality and morlifestyles bidity (including disability adjusted life years (DALY)) • Reductions in other diseases Replace solid fuels with cleaner energy sources using cook stoves

Table 1.1 (continued)

• Reductions in oil demand • Reductions in travel times by lowering urban congestion • Creation of jobs (in transportation sector)

• Healthier and more active lifestyles (with varying units of measurement)

• Women’s time management • Improve household diets

–

• Reduce indoor air pollution

Socioeconomic benefits

• Significant reductions in multiple pollutants (PM2.5 and NOx) • Improvements in air quality

Environmental benefits

• Reductions in CO2 from moving and growing food • Reductions in methane from avoided decomposition in landfill or open dump

• Modest reductions in GHGs

Climate benefits

Anderman et al. (2015)

Chan et al. (2017), Quam et al. (2017)

Rashidi et al. (2017), Xia et al. (2015), Dhar and Shukla (2015), Mittal et al. (2017), Pathak and Shukla (2016)

Source(s)

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would be nearly twice as much as the annual costs. Many of the studies summarized in Table 1.1 also suggest that deepening of climate commitments can yield even greater benefits. Finally, following studies that have looked at interlinkages between different SDGs, there has also been growing reliance on a systems’ logic that maps the possible connections between different streams of benefits (Zhou and Moinuddin 2017; Coopman et al. 2016; Nilsson et al. 2017). This is perhaps best exemplified by the diagram in Fig. 1.2 that helps elucidate the multiple pathways that policymakers could move through to achieve improvements in well-being (Karlsson et al. 2020). The remainder of this book follows some of the recent trends and echoes findings from previous work. In terms of previous work, all of the chapters suggest that integrating different kinds of co-benefits into climate, sectoral, and development policy decisions can strengthen the economic rationale for mitigating climate change. Further reiterating key findings, the chapters also demonstrate that the inclusion of co-benefits in decision-making processes can enhance the design of relevant policies, and that the magnitude of development co-benefits is likely to be greater in developing than developed countries. The quantification of different benefits—especially climate, air quality, and health benefits—should be the standard practice in climate and other sectoral benefits as countries pursue alternative development paths. This will pay dividends for the planet and its people. In terms of extensions, the book also pushes the frontiers of current knowledge on co-benefits and its applications. Most notably, the first section outlines several novel approaches to quantifying co-benefits. The second section demonstrates how co-benefits of renewable energy can be quantified in several countries in Asia—a region where the estimates of developmental co-benefits have been sizable. The final section makes links aforementioned systems’ logic by illustrating the importance of social and biodiversity co-benefits as well as co-innovation in a world where climate interacts with socio-technical and natural resource systems. The next section of this introductory chapter summarizes the key findings from the other chapters in this book.

1.3

Chapter Summaries

This section provides a brief summary of the main claims and conclusions from the book’s remaining chapters.

1.3.1

Analytical Methods

As home to more than half of the world’s population, cities offer significant opportunities and challenges to moving down sustainable, low emission development paths. For similar reasons, urban policymakers increasingly require analytical tools to guide them down these paths. Chapter 2 presents the Urban Sustainable

Fig. 1.2 Co-benefits from Karlsson et al. (2020)

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Development Index (USDI), a composite index that can help measure the comparative sustainable development performance for cities in the Asia-Pacific region. Based on 13 indicators related to energy and climate, urban planning, the local economy, and social welfare, the chapter opens the black box of the USDI as well as demonstrates the results from its application. Carefully planned investments in rapidly developing countries’ energy sectors can yield sizable climate, air quality, health, and other development benefits. Chapter 3 employs a bottom-up model energy model known as the Model for Analysis of Energy Demand (MAED) to project energy demand from 2017 to 2052 and evaluates the co-benefits of business-as-usual and sustainable development scenarios in Pakistan. The results of the modelling underline that harvesting renewable and other clean energy sources offers a cost-effective avenue to achieving climate and other development priorities. In coal-dependent countries, even modest shifts in energy production and consumption can pay significant dividends for air quality, public health, and the climate. Chapter 4 outlines the steps involved in quantifying the GHG and air pollution emissions from replacing older heat only boilers (HOBs) with efficient units in Ulaanbaatar, Mongolia. The chapter provides an overview of a user-friendly spreadsheet simulation model to identify opportunities for reducing energy consumption, GHG emissions, and air pollution when operating HOBs.

1.3.2

Case Studies

As of 2017, South Korea’s renewable share was only 7.6%. However, the South Korean government committed to increase this share in its 3020 implementation plan (RE 3020) in December 2017. This significant increase will be needed to achieve the country’s recently announced net-zero goal by 2050. Yet, the cost-effectiveness of renewable energy remains a contested issue in South Korea. Chapter 5 analyzes the co-benefits from South Korea’s renewable energy policy as well as related GHG mitigation measures. It finds that, despite the methodological challenges of monetizing some co-benefits, even conservative analyses show that installing a new 30.8GW solar photovoltaic in line with RE3020 will still deliver significant cost savings (2.5 trillion Korean Won) in net benefits through 2045. As such, a significant increase in renewables’ share even after 2030 (i.e., more than 20%) is a costeffective direction for energy policy in South Korea. In Japan, efforts to tap solar energy have built upon plans to promote renewable energy that followed the 2011 Great East Japan Earthquake. Chapter 6 describes the post-2011 policies that can deliver co-benefits from solar energy; analyzes the technical, social, and political barriers to implementing those policies; and presents a simple analytical method for quantifying the co-benefits of those policies. The chapter further underlines how a concept known as Regional Circulating and Ecological Sphere (R-CES)—that calls for greater reliance on local resources for

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energy and livelihoods—can provide a useful framework for crafting countermeasures needed to overcome key barriers to taking advantage of solar energy. China’s has already taken ambitious steps to capitalize on vast stores of renewable energy. Chapter 7 evaluates the magnitude of co-benefits of solar power in China through 2050. The assessment demonstrates that continued expansion of solar photovoltaic and solar thermal utilization will lead to the following sizable annual reductions in multiple pollutants over the next three decades: SO2 (2.10Mt/per year), NOx (2.09 Mt/year), PM (0.91 Mt/year), and CO2 (5140Mt/per year). The steady increase in solar energy use can also deliver nearly 1.6 trillion RMB/per year by 2050. Most of these benefits come from energy production/substitution (89%), while 11% are attributable to addressing local environmental concerns (4%) or reducing CO2 (7%). The chapter concludes that supportive enabling reforms such as accelerating the adoption and deployment of smart grids construction could deliver even more co-benefits.

1.3.3

New Perspectives on Co-benefits

Chapter 8 focuses on a different approach to co-benefits than in the previous sections: an approach concentrating on biodiversity co-benefits. The chapter offers a simple, intuitive framework to identify key entry points for achieving biodiversity co-benefits. The chapter also argues that a critical next step in motivating policymakers to work through these entry points is to strengthen the interface between action-oriented and analytical research. The former action-oriented work often lacks rigorous assessment of different benefits; the latter analytical work frequently lacks practical applications of key findings. The chapter concludes by providing recommendations for narrowing the gap between analysis and action. A growing body of evidence suggests that the climate crisis has widened social inequalities. Chapter 9 looks at a category of co-benefits called “social co-benefits.” Noting the heightened emphasis on social inequality in international climate negotiations, the chapter provides good practice examples of how social co-benefits can be mainstreamed into climate-related projects and policies in Asia. It further argues that the sustained delivery of social co-benefits necessitates context-appropriate forms of participatory governance. Technology transfer is and will continue to play a critical role in achieving climate and other co-benefits. Chapter 10 argues that the key to facilitating the transfer of co-benefits technologies is “co-innovation.” Co-innovation is a collaborative and iterative approach to jointly conceptualizing, manufacturing, and scaling up technologies. Like the concept of co-benefits itself, it underscores the importance of delivering multiple benefits to multiple stakeholders. It also presents examples of technology collaboration between Japan and Southeast Asia and examines how co-innovation and co-benefits can help each other.

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References ACP (2014) Asian co-benefits partnership white paper 2014 bringing development and climate together in Asia. Hayama, Japan. http://www.cobenefit.org/publications/images/ ACPwhitepaper_FY2013.pdf ACP (2016) Asian co-benefits white paper 2016 putting co-benefits into practice: case studies from Asia. Hayama ADB (2017) Future carbon fund: delivering co-benefits for sustainable development. Manila. https://www.adb.org/publications/future-carbon-fund-benefits-sustainable-development Amanuma N, Zusman E, Lee S-Y, Gamaralalage JDP, Mitra BK, Pham N-B, Nakano R et al (2018) In: Zusman E, Amanuma N (eds) Governance for integrated solutions to sustainable development and climate change: from linking issues to aligning interests. IGES, Hayama. https://www. iges.or.jp/en/about/staff/zusman-eric?page¼%2C2 Anderman TL, DeFries RS, Wood SA, Remans R, Ahuja R, Ulla SE (2015) Biogas cook stoves for healthy and sustainable diets? A case study in Southern India. Front Nutr 2:28 Aunan K, Fang J, Vennemo H, Oye K, Seip HM (2004) Co-benefits of climate policy—lessons learned from a study in Shanxi, China. Energy Policy 32(4):567–581 Ayres R, Walter J (1991) The greenhouse effect: damages, costs and abatement. Environ Resour Econ 1(3):237–270 Balaban O, de Puppim Oliveira J (2017) Sustainable buildings for healthier cities: assessing the co-benefits of green buildings in Japan. J Clean Prod 163:S68–S78 Buonocore JJ, Levy JI, Guinto RR, Bernstein AS (2018) Climate, air quality, and health benefits of a carbon fee-and-rebate bill in Massachusetts, USA. Environ Res Lett 13(11):114014 Burtraw D, Toman M (1997) The benefits of reduced air pollutants in the US from greenhouse gas mitigation policies. Resources for the Future Discussion Paper 98-01, Washington, DC Challcharoenwattana A, Pharino C (2015) Co-benefits of household waste recycling for local community’s sustainable waste management in Thailand. Sustainability 7(6):7417–7437 Chan EYY, Wang SS, Ho JYE, Huang Z, Liu S, Guo C (2017) Socio-demographic predictors of health and environmental co-benefit behaviours for climate change mitigation in urban China. PLoS One 12(11):e0188661 Coopman A, Osborn D, Ullah F, Auckland E, Long G (2016) Seeing the whole: implementing the SDGs in an integrated and coherent way-A research pilot by Stakeholder Forum, Bioregional and Newcastle University Dhar S, Shukla PR (2015) Low carbon scenarios for transport in India: co-benefits analysis. Energy Policy 81:186–198 Elkins P (1996) How large a carbon tax is justified by the secondary benefits of CO2 abatement? Environ Resour Econ 18:161–187 Hagen B, Pijawka D, Prakash M, Sharma S (2017) Longitudinal analysis of ecosystem services’ socioeconomic benefits: wastewater treatment projects in a desert city. Ecosyst Serv 23:209–217 Hajer M, Nilsson M, Raworth K, Bakker P, Berkhout F, de Boer Y, Rockström J, Ludwig K, Kok M (2015) Beyond cockpit-ism: four insights to enhance the transformative potential of the sustainable development goals. Sustainability (Switzerland) 7(2):1651–1660. https://doi.org/10. 3390/su7021651 Islam KN (2018) Municipal solid waste to energy generation: an approach for enhancing climate co-benefits in the urban areas of Bangladesh. Renew Sust Energ Rev 81:2472–2486 Jiang P, Xu B, Geng Y, Dong W, Chen Y, Xue B (2016) Assessing the environmental sustainability with a co-benefits approach: a study of industrial sector in Baoshan District in Shanghai. J Clean Prod 114:114–123 Jochem E, Madlener R (2003) The forgotten benefits of climate change mitigation: innovation, technological leapfrogging, employment, and sustainable development. In: Workshop on the benefits of climate policy: improving information for policy makers. Washington, DC Kainuma M, Ishikawa T, Pandey R, Kamei M, Nishioka S (2017) Climate actions and Interactions with SDGs. Hayama. https://pub.iges.or.jp/pub/climate-actions-and-interactions-sdgs

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Karlsson M, Alfredsson E, Westling N (2020) Climate policy co-benefits: a review. Clim Pol 20 (3):292–316 King P (2003) Integrated economic, social and environmental planning in the pacific region Krupnick A, Burtraw D, Markandya A (2000) The ancillary benefits and costs of climate change mitigation: a conceptual framework. Paper presented at the IPCC gas, expert workshop on assessing the ancillary benefits and costs of greenhouse mitigation policies. Washington, DC Laramee J, Tilmans S, Davis J (2018) Costs and benefits of biogas recovery from communal anaerobic digesters treating domestic wastewater: evidence from Peri-Urban Zambia. J Environ Manag 210:23–35 Li M, Zhang D, Li CT, Mulvaney KM, Selin NE, Karplus VJ (2018) Air quality co-benefits of carbon pricing in China. Nat Clim Chang 8(5):398 Liu Z, Adams M, Cote RP, Geng Y, Ren J, Chen Q, Liu W, Zhu X (2018) Co-benefits accounting for the implementation of eco-industrial development strategies in the scale of industrial park based on energy analysis. Renew Sust Energ Rev 81:1522–1529 Markandya A, Rübbelke DTG (2004) Ancillary benefits of climate policy. J Econ Stat 224 (4):488–503 Markandya A, Sampedro J, Smith SJ, Van Dingenen C, Pizarro-Irizar R, Arto I, González-Eguino M (2018) Health co-benefits from air pollution and mitigation costs of the Paris agreement: a modelling study. Lancet Planet Health 2(3) Menikpura SNM, Santo A, Hotta Y (2014) Assessing the climate co-benefits from waste electrical and electronic equipment (WEEE) recycling in Japan. J Clean Prod 74:183–190. https://doi.org/ 10.1016/j.jclepro.2014.03.040 Mittal S, Pathak M, Shukla PR, Ahlgren E (2017) Ghg mitigation and sustainability co-benefits of urban solid waste management strategies: a case study of Ahmedabad, India. Chem Eng Trans 56:457–462 Miyatsuka A, Zusman E (2008) Fact Sheet No . 1 What Are Co-Benefits? ACP Fact Sheet, no. 1: 1–3 Miyatsuka A, Zusman E (2010) What are co-benefits? Asian Co-benefits Partnership (ACP). Available at https://www.cobenefit.org/about/ Morgenstern R (1991) Toward a comprehensive approach to global climate change mitigation. Am Econ Rev 81(2):140–145 Nemet GF, Holloway T, Meier P (2010) Implications of incorporating air-quality co-benefits into climate change policymaking. Environ Res Lett 5(1):014007 New ClimateInstitute (2015a) Assessing the achieved and missed benefits of a possible intended nationally determined contribution for Switzerland. https://newclimate.org/wp-content/uploads/ 2016/01/20151111_switzerland_cobenefits-en.pdf New ClimateInstitute (2015b) Assessing the achieved and missed benefits of Chile’s intended nationally determined contribution. https://newclimate.org/wp-content/uploads/2015/10/ 20151007_cobenefits_chile.pdf New ClimateInstitute (2015c) Assessing the achieved and missed benefits of Japan’s intended nationally determined contribution. https://newclimate.org/wp-content/uploads/2015/06/ assessing-the-achieved-and-missed-benefits-of-japan_v2.pdf New ClimateInstitute. (2015d) Assessing the achieved and missed benefits of South Africa’s intended nationally determined contribution. https://newclimateinstitute.files.wordpress.com/ 2015/10/cobenefits-of-indcs-october-2015.pdf New ClimateInstitute (2016) Co-benefits of climate action: assessing Turkey’s climate pledge. https://newclimate.org/wp-content/uploads/2016/10/benefits_of_climate_action_turkey.pdf Nilsson M, Griggs D, McCollum D, Stevance A (2017) A guide to SDG interactions: from science to implementation Olsen SH, Zusman E, Steele R, Marsden E, Antoinette Virtucio Ma (2019) Strengthening the environmental dimensions of the sustainable development goals in Asia and the pacific: stocktake of national responses to sustainable development goals 12, 14, and 15. Manila. https://www.adb.org/sites/default/files/publication/481246/environmental-dimensions-sdgsstocktake-report.pdf

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Pathak M, Shukla PR (2016) Co-benefits of low carbon passenger transport actions in indian cities: case study of Ahmedabad. Transp Res Part D: Transp Environ 44:303–316 Pearce D (2000) Policy frameworks for the ancillary benefits of climate policies. CSERGE Working Paper GEC 2000-11 Quam VGM, Rocklöv J, Quam MBM, Lucas RAI (2017) Assessing greenhouse gas emissions and health co-benefits: a structured review of lifestyle-related climate change mitigation strategies. Int J Environ Res Public Health 14(5):468. https://doi.org/10.3390/ijerph14050468 Rashidi K, Stadelmann M, Patt A (2017) Valuing co-benefits to make low-carbon investments in cities bankable: the case of waste and transportation projects. Sustain Cities Soc:34 Rockström J, Steffen W, Noone K, Persson A, Chapin F III, Lambin E, Lenton TM et al (2009) Planetary Boundaries: Exploring the Safe Operating Space for Humanity. Ecol Soc 14(2):32 Shindell D, Borgford-Parnell N, Brauer M, Haines A, Kuylenstierna JCI, Leonard SA, Ramanathan V, Ravishankara A, Amann M, Srivastava L (2017) A climate policy pathway for near- and long-term benefits. Science. https://doi.org/10.1126/science.aak9521 TERI (2017). SDG Footprint of Asian NDCs: exploring synergies between domestic policies and international goals. Delhi. http://www.ndcfootprints.org/index.php Tham R, Bowatte G, Dharmage S, Morgan G, Marks G, Cowie C (2018) Health co-benefits and impacts of transitioning from fossil-fuel based to cleaner energy sources in higher-income countries: what do we know? In ISEE Conference Abstracts (vol. 2018, no. 1) Uchida T, Zusman E (2008) Reconciling local sustainable development benefits and global greenhouse gas mitigation in Asia: research trends and needs. Reg Policy Res 11(1):57–73 UNEP APCAP and CCAC (2019) Air pollution in Asia and the pacific: science-based solutions. United nations environment programme. Nairobi. http://www.ccacoalition.org/en/resources/airpollution-asia-and-pacific-science-based-solutions UNEP/WMO (2011) Integrated assessment of black carbon and tropospheric ozone. http://www. unep.org/dewa/Portals/67/pdf/BlackCarbon_report.pdf UNFCCC (2015) Paris agreement. https://unfccc.int/resource/docs/2015/cop21/eng/l09r01.pdf Wang T, Jiang Z, Zhao B, Gu Y, Liou KN, Kalandiyur N, Zhang D, Zhu Y (2020) Health co-benefits of achieving sustainable net-zero greenhouse gas emissions in California. Nat Sustain:1–9 Xia T, Nitschke M, Zhang Y, Shah P, Crabb S, Hansen A (2015) Traffic-related air pollution and health co-benefits of alternative transport in Adelaide, South Australia. Environ Int 74:281–290 Zhang S, Worrell E, Crijns-Graus W (2015) Evaluating co-benefits of energy efficiency and air pollution abatement in China’s cement industry. Appl Energy 147:192–213 Zhou X, Moinuddin M (2017) Sustainable development goals interlinkages and network analysis: a practical tool for SDG integration and policy coherence. Hayama. https://sdginterlinkages.iges. jp/files/IGES_ResearchReport_SDG Interlinkages_Printing Version.pdf Zusman E (2008) Recognising and rewarding co-benefits in the post-2012 climate regime: implications for developing Asia. In: The climate regime beyond 2012. Hayama, Japan. http://pub. iges.or.jp/modules/envirolib/upload/1030/attach/split06_chapter5.pdf

Part I

The Quantitative Modeling of Climate Co-benefits and Sustainable Development

Chapter 2

The Urban Sustainable Development Index: A Comparative Analysis of Low Emission Strategies in Urban Areas Ayas Shaqour and Hooman Farzaneh

2.1 2.1.1

Introduction The Need for Sustainability

Sustainable development is one of the core concerns discussed today by policymakers and decision-makers. Addressing climate change, clean water, waste management, microplastics, poverty, and basic human rights are key to achieving a sustainable future. Governments and civil society are actively participating in the creating sustainable development models that “suits our current needs, without compromising the future.” In 2015 the United Nation’s sustainability summit was held at New York, where it introduced the 17 Sustainable Development Goals (SDGs), which were an urgent a call for nations to take action globally and tackle the main sustainability issues such as tackling poverty, economic growth, human health, equal and better education, decreasing inequality, climate change, and the safety of the environment (United Nations 2015). Later that year, the Paris Agreement was adopted to address climate change and set the goal of maintaining global warming below 2C. The Paris Agreement also aimed to support countries working toward these goals and raise their capacity to mitigate the impacts caused by climate change (United Nations, Summary of the Paris Agreement, United Nations Framew. Conv 2015). Hence, there is a growing need for solutions that can enable decisionmakers and planners to: • Navigate through the many complex and intricate sustainability challenges in the best way possible; • Measure the socioeconomic and environmental impacts of potential solutions; and. A. Shaqour · H. Farzaneh (*) Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Fukuoka, Japan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 H. Farzaneh et al. (eds.), Aligning Climate Change and Sustainable Development Policies in Asia, https://doi.org/10.1007/978-981-16-0135-4_2

19

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A. Shaqour and H. Farzaneh

• Measure the performance and success of the current sustainability interventions in their cities compared to other cities.

2.1.2

Co-benefits and Climate Change

The concept of Co-benefits has been picking up momentum in both the academic and political circles. This concept is intended to incentivize the adoption of policies that can achieve multiple goals within a single policy or decision. The co-benefit approach can be used to prioritize sustainable development-related policies and measure their multiple benefits relating to the mitigation of climate change, such as improving local air pollution and public health (Mayrhofer and Gupta 2016). Therefore, a better understanding of climate policies’ co-benefits can shed light into how to design policies that contribute to both climate and wider sustainable development objectives (Nemet et al. 2010; Karlsson et al. 2020; Farzaneh et al. 2014). In order to measure the multiple benefits of a policy, there is a need for methods and indicators that can capture the policy’s impacts and co-benefits.

2.1.3

Sustainability Indicators

Sustainability indicators are tools to evaluate the sustainability and performance of any chosen system, where a system is composed of multiple interrelated and quantifiable variables. Sustainability indices are essential to understand the intricate nature of the elements that make up a system. For example, any country’s environmental and economic performance is a function of a complicated relationship between environmental, energy, social, and economic variables. Hence, to measure such a complex system, indicators are used to capture valuable insights and information that correlate to that system’s sustainable development (Kılkış 2015; Mayrhofer and Gupta 2016; Nemet et al. 2010; Farzaneh 2017a,b). The use of indicators within policy-making depends on several factors (Karlsson et al. 2020; Shah et al. 2019; World Bank Indicators 2020): • The nature and design of the specific indicator; • The nature of policy and decision-making process within a country; and • The complication of how the factor is used and the relation it holds to the sustainability goals.

2 The Urban Sustainable Development Index: A Comparative Analysis of Low. . .

2.1.4

21

Urban Sustainable Development Index

Cities use varying definitions for specific indicators, notably green spaces, municipal waste collection, public transportation systems, and social welfare. In such cases, the urban sustainability index (USDI) has sought to standardize the definition used. The USDI is a composite index used to measure the comparative sustainable development performance of urban areas. The USDI benchmarks cities in urban areas in the Asia-Pacific region based on their performance in four primary areas of energy and climate, city planning, local economy, and social welfare, as depicted in Fig. 2.1. The USDI was initially introduced as a tool for the comparative analysis of the different low emissions development strategies (LEDs) in urban areas. It is developed to allow urban planners to measure the socioeconomic and environmental impacts of the planned LEDs and monitor the success of sustainability interventions in their cities. It is a useful tool to trigger learning, action, and collaboration among the Asia-Pacific cities and to improve future performance. USDI also measures the achieved co-benefits from the implementation of LEDs in different areas.

Fig. 2.1 Composition of the USDI

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A. Shaqour and H. Farzaneh

2.2

Modeling Methodology

At the local level, the USDI benchmarks cities based on 13 indicators in four groups of energy and climate, city planning, local economy, and social welfare. The index is applied to 12 cities in the Asia-Pacific region. Energy and climate-related indicators include GHG emissions, air pollution (NOx, PM10, and PM2.5), and final energy consumption. City planning indicators include clean water accessibility, public transport development, waste collection and management, and urban green space. The local economy and social welfare progress are assessed by measuring the local GDP, labor productivity, unemployment rate, life expectancy, public health, and education.

2.2.1

Indicators’ Collection and Formulation

The application of the USDI to the 12 cities in the Asia-Pacific region required an extensive process of data collection for each city. The collected input data were used to create the main indicators. The process of creating these indicators involves the collection of data entries (ix, y) for each city Um as depicted in Fig. 2.2. The USDI was constructed, as seen in Fig. 2.2, by first selecting the mentioned indicators and their respective data. The data was collected for 12 cities in the AsiaPacific region, using an extensive data collection process for each of the selected cities. The selected indicators were divided into four groups, where each group contains different indicators and data entries: 1. Energy and climate. (a) (b) (c) (d) (e)

GHG emissions (Mt) Annual mean NOx (ppm) Annual mean PM10 (μg/m3) Annual mean PM2.5 (μg/m3). Final energy consumption (PJ)

Fig. 2.2 Overview of the data processing method of the USDI

2 The Urban Sustainable Development Index: A Comparative Analysis of Low. . .

23

2. City planning. (a) (b) (c) (d)

Clean water accessibility (%) Public transportation system (km/km2) Waste collection and management (%) Green area per capita (square meter)

3. Social welfare. (a) Life Expectancy Index (b) Public Health Index (c) Education Index 4. Local economy. (a) Per capita GDP (USD) (b) Per worker labor productivity (USD) (c) Unemployment rate (%). The selected indicators are the following:

2.2.1.1

Final Energy Consumption

The total final energy demand includes the sum of energy consumption in the three sectors of industry (electricity, manufacturing, agriculture, and constriction), buildings (residential and commercial), and transport (public, private, and municipal fleets). The total final energy demand for the USDI was calculated as follows (Cassar et al. 2013): ET ¼ E Ind þ E Tran þ E Res þ E com

ð2:1Þ

where ET, EInd, ETran, ERes, and Ecom refer to the final energy demand in the industry, transport, residential building, and commercial sectors, respectively. EInd ¼

XX Q  SIτj  EIτj τ

ð2:2Þ

j

where Q is the value-added ($), SI is the industry share in  the whole sector valuePJ added and is the energy intensity in each industrial sector and j refer to the Þ, and τ technology type and subsector, respectively. E Tran ¼

XX v

f

PKM  SRvf  EIvf

ð2:3Þ

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A. Shaqour and H. Farzaneh

PKM ¼

XX v

ð2:4Þ

V vf U vf Dvf Ovf

f

PKM is the total passenger kilometers; SR is the mode share (%); EI is the energy intensity (liter/km); V is the number of each vehicle in use; U is the utilization rate (%); D is the average annual distance traveled (km); O is the occupancy rate (person/ vehicle); and v and f refer to the vehicle type and technology type, respectively. For the residential sector: E Res ¼

X X i

ND  DWSij  DWZij  EIij



ð2:5Þ

j

ND ¼

Pop  α θ

ð2:6Þ

For the commercial sector: ECom ¼

X X k

FA  CSkj  EIkj



ð2:7Þ

i

ND is the number of dwellings; DWS is the share of each dwelling type (%); DWZ is the size of each dwelling type (sqm); EI is the energy intensity (kWh/sqm); FA is the total floor area (sqm); and CS is the share of each building type in the total floor area (%), respectively. α indicates the share of population type; and θ refers to the percentage of the population type (e.g., person/household). i, j, and k refer to the dwelling type (i.e., single room, double room, etc.); type of technology (i.e., heating, cooling, cooking, lighting, etc.); and type of building (i.e., school, mall, shop, office, etc.)

2.2.1.2

GHG Emissions and Air Pollution

GHGs are gases that trap thermal energy inside the earth’s atmosphere, causing a global rise in temperature. They includes 81% CO2, 10% methane, and 7% nitrous oxide. CO2 is mainly produced by burning fossil fuels, biological materials, and specific chemical reactions and is principally removed by plants and trees. Methane is primarily produced by agriculture, livestock, and the transportation and production process of coal, natural gas, and oil. Nitrous oxide is the product of wastewater treatment, burning of solid wastes and fuels, as well as emissions from agriculture and the industrial sectors (Bell and Morse 2011). In the calculation process of the USDI, locally developed emission factors were used to estimate the amount of GHG emissions and air pollutions in each city.

2 The Urban Sustainable Development Index: A Comparative Analysis of Low. . .

2.2.1.3

25

Public Transportation System (km/km2)

The performance of the public transportation system was evaluated based on the total length of urban rails per metropolitan land area in each city.

2.2.1.4

Waste Management and Water Accessibility (%)

Waste is a global challenge facing the world and affecting every living organism, most importantly humans (Takeshita et al. 2020; Gómez-Sanabria et al. 2020). The poor handling of waste causes human health problems and affects economies and tourism. This calls for the importance of waste management in urban cities and the proper handling of industrial and human waste products to lead to a cleaner, healthier, and sustainable future. Water management and clean water access are at the essence of sustainability in a healthy ecosystem and daily human life. The data on waste management and water accessibility of each municipality were collected from the World Bank database (P. IEA, Energy Efficiency Indicators 2020 2020).

2.2.1.5

Green Space (m2)

Public and green spaces play a vital role in promoting cities’ sustainability, namely, in strengthening the connection between humans and nature. They therefore deliver multiple benefits for human and environmental health. The per capita green area was approximated from Organisation of Econnomic Cooperation and Development (OECD) statistics (Farzaneh 2019).

2.2.1.6

Per Worker Labor Productivity (US$)

Labor productivity measures the efficiency of the people in a city. It shows the total volume of output (measured in terms of gross domestic product, GDP) produced per unit of labor (measured in terms of the number of employed persons) in each city, during a given time reference period (U.S.E.P.A. EPA, Greenhouse Gas Emissions n.d.).

2.2.1.7

Life Expectancy Index

Life Expectancy Index (LEI) is a popular statistical measure of the average time a person in a city is expected to live, based on the year of his or her birth and current age. This index and other health indicators are key to understanding and quantifying the co-benefits of sustainable development and climate change mitigation on public health (Worldbank, Water n.d.). LEI is calculated as follows:

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A. Shaqour and H. Farzaneh

LEI ¼

LB  20 85  20

ð2:8Þ

LB is the life expectancy at birth. When LB is 20, the LEI is 0. When LB is 85, the LEI is 1. Life expectancy at birth is usually calculated by observing the mortality rate at a specific year in a particular city or country and calculating the life expectancy of a child born at that time, assuming the mortality rate being the same in the child’s lifetime. Data for LB were collected from the United Nations Development Program (UNDP) database (OCED, Metropolitan areas OCED n.d.).

2.2.1.8

Public Health Index HI ¼ 0:8ðLB  25Þ þ 1:5ð32  CMÞ

ð2:9Þ

CM is the mortality rate under five (per 1000 live births) collected from the United Nations Development Program database (OCED, Metropolitan areas OCED n.d.; Hassan Bhat et al. 2021).

2.2.1.9

Education Index

The education index is a part of the United Nations’ Human Development Index, indicating the level of education in a particular city or nation. Education is a key factor for the quality of life, well-being, as well as economic growth. The EDI is calculated taking the average of the expected years of schooling index or ESI and mean years of schooling index or MSI: EDI ¼

MSI þ ESI 2

ð2:10Þ

EDI data were collected from the United Nations Development Program database (OCED, Metropolitan areas OCED n.d.).

2.2.2

Data Normalization

For an indicator of the type “less is better”: Sx,y ¼

ix,y  Maxðix,y Þ Minðix,y Þ  Maxðix,y Þ

For an indicator of the type “more is better”:

ð2:11Þ

2 The Urban Sustainable Development Index: A Comparative Analysis of Low. . .

Sx,y ¼

ix,y  Minðix,y Þ Maxðix,y Þ  Minðix,y Þ

27

ð2:12Þ

Equation (2.11) is used to normalize and standardize indicators whose value has a negative correlation to sustainable development, where the maximum value of ix, y will score 0 and the minimum value will be 1. ix, y refers to the entry data value y for city x; Max(ix, y) and Min (ix, y) are the maximum and minimum values, respectively, of a particular indicator x out of all the cities y included; and finally Sx, y is the normalized value of ix, y. Equation (2.12) is used for indicators whose values correlate positively to sustainable development where the minimum value of ix, y scores 0 and the maximum scores 1.

2.2.3

Value Aggregation

Value aggregation refers to combining each of the indicators composing a group, as discussed previously, into one composite index for each city. The data is aggregated using the geometric mean as follows: USi ¼

Yn

S 1 i,n

1=n

ð2:13Þ

USi is the index group i (1, energy and climate; 2, city planning; 3, local economy; 4, social welfare), and n is the number of indicators for each dimension. This aggregation method scores each city from 0 to 1, where, if any of the indicators has a low score, the overall score is significantly reduced, unlike an equally weighted score. This property suggests that all the indicators of a group are important and correlated. For example, emitting very high amounts of GHG emissions will severely reduce the score even if other emissions like PM10 are very low.

2.2.4

USDI

Finally, the USDI is calculated by taking the weighted sum of the four indices for each city so that each composite index contributes equally to the USDI:

28

A. Shaqour and H. Farzaneh

USDI ðU m Þ ¼

X4

β USi i¼1 i

ð2:14Þ

Bi is the weight for each dimension and Um is city m. The final index is bound between 0 and 1, where 1 is the best score in terms of sustainability.

2.3

Results and Discussion

Figure 2.3 shows the USDI for the 12 selected cities in the Asia-Pacific region. Table 2.1 represents the input data used in the calculation of the USDI. Table 2.2 shows the normalized values of all the entry data for each city. Figure 2.4 represents the factors affecting the USDI in the selected cities. The USDI toolkits were designed and developed by the Energy and Environmental Systems laboratory (EES) at Kyushu University. The tool can be easily accessed and used by decision-makers, academics, researchers, students, and anyone interested in measuring and understanding the comparative sustainability performance of their selected city in relation to other reference cities (Figs. 2.5 and 2.6). These tools are used to measure the USDI for either baseline (current situation) or ex ante (scenario-based) assessments. Insights derived from such evaluation can help understand the urgency of bold and timely LEDs coupled with the social, environmental, and economic opportunities in each city.

1

0.914

0.862

0.9 0.8 0.7 0.6

0.726 0.572

0.5

0.546 0.451

0.398

0.4 0.3 0.2 0.1 0

Fig. 2.3 USDI ranking

0.245

0.418 0.407 0.308

0.908

Energy and climate GHG emissions (Mt) Annual mean NOx (ppm) Annual mean PM10 (μg/ m3) Annual mean PM2.5 (μg/ m3) Final energy consumption (PJ) City planning Clean water accessibility (%) Public transportation system (km/km2) Waste collection and management (%) Green area per capita (square meter) Local economy Per capita GDP (USD) Per worker labor productivity (US$) Unemployment rate (%) Social welfare Life Expectancy index Public Health Index Education Index

60.26 17 22

10

420.79

100

0.94

100

163.82

68,776 11,2000

3.6

0.98 0.95 0.88

32.873

1158.163

92.909

0.276

81.091

59.56

29576.364 56,727.273

5.5

0.864 0.698 0.714

Tokyo

54.211 32.227 65.727

Average cities

Table 2.1 Input data used in the USDI calculation

0.96 0.92 0.87

4.8

32,000 66,000

133.23

100

0.64

100

1000

22

36.149 68.4 49

Seoul

0.86 0.77 0.63

4.2

18,756 38,000

13.5

83

0.07

95

7306

36

255.304 51.2 79

Shanghai

0.74 0.19 0.52

5.3

5300 37,000

21.52

67

0.08

90

775

152.6

45.55 44.2 286

Delhi

0.84 0.72 0.64

5.7

6729 25,000

61.8

63

0.04

94

340

20

55.476 39.8 38

Bangkok

0.86 0.59 0.62

7.5

3425 8900

2

85

0.01

80

253

39

14.78 18.2 86

Hanoi

0.75 0.45 0.62

5.6

11,010 23,000

9.41

37

0.19

95

254

21

11.52 16.1 48

Jakarta

0.84 0.79 0.7

4.5

27,991 54,500

8.5

80

0.023

98

1008

17

51.84 38.3 36

Kuala

0.74 0.44 0.64

13.9

8939 17,000

6.1

77

0.003

70

429

22

19.2 31.2 49

Manila

0.97 0.94 0.81

2.2

57,714 12,5000

66

100

0.942

100

937

17

41.44 19.9 21

Singapore

0.96 0.92 0.92

3.2

84,700 11,7600

224.9

100

0.1

100

17

5

4.8 10.2 9

Sydney

2 The Urban Sustainable Development Index: A Comparative Analysis of Low. . . 29

Energy and climate GHG emissions (Mt) Annual mean NOx (ppm) Annual mean PM10 (μg/m3) Annual mean PM2.5 (μg/m3) Final energy consumption (PJ) City planning Clean water accessibility (%) Public transportation system (km/km2) Waste collection and management (%) Green area per capita (square meter) Local economy Per capita GDP (USD) Per worker labor productivity (US$) Unemployment rate (%) Social welfare Life Expectancy index Public Health Index Education Index 0.779 0.883 0.953 0.966 0.945 1 0.998 1 0.726

0.804 0.888 0.88 1 1 0.9

0.764 0.291

0.7

0.258

0.032 0.412

0.718

0.517 0.668 0.485

Tokyo

0.803 0.622 0.795 0.811 0.843

Average cities

Table 2.2 Normalized Input data used in the USDI

0.92 0.96 0.88

0.78

0.35 0.49

0.59

1

1 0.68

0.88 0 0.86 0.89 0.87

Seoul

0.5 0.763 0.275

0.829

0.189 0.251

0.052

0.73

0.833 0.071

0 0.296 0.747 0.79 0

Shanghai

0 0 0

0.74

0.02 0.24

0.09

0.48

0.67 0.08

0.84 0.42 0 0 0.9

Delhi

0.417 0.697 0.3

0.701

0.041 0.139

0.019

0.413

0.8 0.039

0.798 0.491 0.895 0.898 0.956

Bangkok

0.5 0.526 0.25

0.547

0 0

0

0.762

0.333 0.007

0.96 0.863 0.722 0.77 0.968

Hanoi

0.042 0.342 0.25

0.709

0.093 0.121

0.033

0

0.833 0.199

0.973 0.899 0.859 0.892 0.967

Jakarta

0.417 0.789 0.45

0.803

0.302 0.393

0.029

0.683

0.933 0.021

0.812 0.517 0.903 0.919 0.864

Kuala

0 0.329 0.3

0

0.068 0.07

0.018

0.635

0 0

0.943 0.639 0.856 0.885 0.943

Manila

0.958 0.987 0.725

1

0.668 1

0.287

1

1 1

0.854 0.833 0.957 0.919 0.874

Singapore

0.917 0.961 1

0.915

1 0.936

1

1

1 0.103

1 1 1 1 1

Sydney

30 A. Shaqour and H. Farzaneh

2 The Urban Sustainable Development Index: A Comparative Analysis of Low. . .

31

Fig. 2.4 Factors affecting the USDI

2.3.1

Delhi Clean Transport Scenario

Delhi’s transportation sector is the largest consumer of energy and represents a major contributor to GHG emissions and local air pollution. This sector is expected to experience a massive increase in fossil fuel consumption resulting from private vehicles’ fast growth. Delhi already has exceptionally high private car use levels, with around two million cars in the city. The Delhi clean transport scenario was based on the Sustainable Habitat submission, through augmenting public transport, i.e., by adding compressed natural gas (CNG) buses in the transport sector and the restructuring of the bus system. Promoting urban transport infrastructures, such as early adoption of BSES V and BSES VI auto fuel norms, allocating financial subsidy on newly purchased battery-operated 4 and 2 wheelers, and increasing ridership in Delhi metro were other useful options to promote seamless and clean mobility (APO 2017; Oliveira et al. 2015). Based on these actions and objectives of the initiatives above, the impacts of the implementation of the clean transport scenario in Delhi is reported in Table 2.3. Table 2.4 shows the improvements and changes in the USDI before and after implementing the clean transport scenario in Delhi. It can be observed that even with this new scenario, Delhi’s USDI is still far behind the average cities. The Delhi government’s focus seems to be more on gradual supply augmentation of traditional sources than envisioning a road map for a radical shift toward cleaner fuels or major demand-side management. On the contrary, it is seen that bold and strict decisions from the government or the judiciary like bans seem to work in Indian cities. Delhi’s various urban amenities are highly subsidized, and their price does not adequately reflect the input and operational cost, be it for electricity, water, LPG, waste disposal, etc.

A. Shaqour and H. Farzaneh

Fig. 2.5 USDI web-based tool

32

2 The Urban Sustainable Development Index: A Comparative Analysis of Low. . .

33

Fig. 2.6 USDI IOS application Table 2.3 Delhi clean transport scenario

Energy and climate GHG emissions (Mt) Annual mean NOx (ppm) Annual mean PM10 (μg/m3) Annual mean PM2.5 (μg/m3) Final energy consumption (PJ) City planning Clean water accessibility (%) Public transportation system (km/km2) Waste collection and management (%) Green area per capita (square meter) Local economy Per capita GDP (USD) Per worker labor productivity (US$) Unemployment rate (%) Social Welfare Life Expectancy Index Health Index Education Index

Baseline scenario

Clean transport scenario

Change

45.55 44.2 286 152.60333 774.5738

25.5 22.98 148.8 79.15 462.34

44% 48% 48% 48.10% 40.30%

0.08

0.128

+60%

5300

5830

+10%

5.3

2.3

56.60%

0.19

0.57

+200%

34

A. Shaqour and H. Farzaneh

Table 2.4 USDI evaluation in Delhi, after/before the implementation of clean transport scenario Scenario Baseline Clean transport Average cities

Energy and climate 0.376 0.447

City planning 0.305 0.321

Local economy 0.302 0.368

Social welfare 0 0.079

USDI 0.246 0.304

0.773

0.485

0.475

0.555

0.572

Using the USDI, the clean transport scenario’s co-benefits can be evaluated across multiple areas such as social welfare—for example, with improvements in the health index, decreasing unemployment, and improving the transport system coverage.

2.3.2

Shanghai Master Plan Scenario

By 2040, Shanghai aims to become a world-class global city; an international economic, finance, trade, shipping, and scientific innovation center; as well as a cultural metropolis. To achieve these goals, the city will take measures to control construction and population growth and protect the environment and improve urban safety. According to the plan, the city’s population will be limited to 25 million by 2040; the same target is set for 2020. Shanghai had 24.3 million residents at the end of 2014. The Shanghai master plan scenario and its USDI results are depicted in Tables 2.5 and 2.6. After the implementation of the master plan in Shanghai, it can be observed that it will promote USDI. However, both energy and climate and city planning are still behind the average cities (UNDP, Human Development Data n.d.; Farzaneh et al., 2016). In Shanghai, implementing LEDs will positively affect per capita carbon emissions and per unit GDP carbon emissions. An evaluation of USDI in Shanghai showed that the tertiary sector’s growth based on modern, knowledge-intensive, and service-based would result in increasing the USDI. Therefore, Shanghai’s government should continue to pursue its policy to relocate its heavy industry to make room for the tertiary sector. Moreover, Shanghai’s local government needs to strengthen its economic restructuring policy and rely on technological improvements to reduce carbon emissions (Farzaneh et al. 2019; Farzaneh and Xin 2020).

2.3.3

Kuala Lumpur Sustainable Urban Energy System Scenario

Kuala Lumpur’s energy profile is affected by many factors, including population, income, economic structure, energy prices, end-use efficiencies, climate conditions, urban forms, built environments, and access to regional and national energy markets.

2 The Urban Sustainable Development Index: A Comparative Analysis of Low. . .

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Table 2.5 Shanghai master plan scenario Energy and climate GHG emissions (Mt) Annual mean NOx (ppm) Annual mean PM10 (μg/m3) Annual mean PM2.5 (μg/m3) Final energy consumption (PJ) City planning Clean water accessibility (%) Public transportation system (km/km2) Waste collection and management (%) Green area per capita (square meter) Local economy Per capita GDP (USD) Per worker labor productivity (US$) Unemployment rate (%) Social welfare Life Expectancy Index Health Index Education Index

Baseline

Master plan

Change

255.31 51.2 79 36 7306

217.0135 43.52 67.15 30.6 5625.62

15% 15% 15% 15.00% 23.00%

0.07

0.091

+30%

18,756 38,000 4.2

21,569.4 47,500 2

+15% +25% 52.38%

0.77

0.83

+7.79%

Table 2.6 Shanghai scenario results Scenario Baseline Master plan Change

Energy and climate 0.323 0.361 11.76%

City planning 0.376 0.383 1.86%

Local economy 0.396 0.483 21.97%

Social welfare 0.501 0.523 4.39%

USDI 0.399 0.437 9.52%

Implementation of mitigation measures in the energy sector can play an important role in increasing the sufficiency of resources to meet energy demand at competitive and stable prices as well as improving the resilience of the energy supply system in this city. According to the sustainable urban energy system scenario, (1) solar energy utilization and (2) waste-to-electricity are two promising LEDS that can improve the resilience of the energy supply system in this city. Besides promoting renewable power generation and waste-to-electricity, minimizing the carbon emissions from anthropogenic activities can be acheived by enhancing energy efficiency. Despite having the industrial sector gradually phased out from Kuala Lumpur City, the direct and indirect emissions from commercial and residential sectors are undeniably significant. Tables 2.7 and 2.8 show the expected improvement in the USDI after implementing this scenario in Kuala Lumpur (Farzaneh 2018). The co-benefits of such policies can also be observed in city planning, local economy, and social welfare.

36

A. Shaqour and H. Farzaneh

Table 2.7 Kuala Lumpur scenario Baseline

Sustainable energy

Change

51.84 38.3 36 17 1008

27.99 32.17 31.32 14.79 604.8

46% 16% 13% 13.00% 40.00%

0.02

0.06

+200%

27,991

28,027.39

+0.13%

4.5

2.5

44.44%

0.79

0.85

+7.59%

Energy and climate 0.796 0.856

City planning 0.36 0.374

Local economy 0.484 0.53

Social welfare 0.543 0.565

USDI 0.546 0.581

7.54%

3.89%

4.02%

9.50%

6.41%

Energy and climate GHG emissions (Mt) Annual mean NOx (ppm) Annual mean PM10 (μg/m3) Annual mean PM2.5 (μg/m3) Final energy consumption (PJ) City planning Clean water accessibility (%) Public transportation system (km/km2) Waste collection and management (%) Green area per capita (square meter) Local economy Per capita GDP (USD) Per worker labor productivity (US$) Unemployment rate (%) Social welfare Life Expectancy Index Health Index Education Index Table 2.8 Kuala Lumpur scenario results Scenario Baseline Sustainable energy Change

Figure 2.7 shows the result of the scenario evaluation in the four main categories of indicators, where Kuala Lumpur is performing well in the local economy, social welfare, and energy and climate. However, Kuala Lumpur falls short in city planning, an area where Shanghai had the highest index in this group. Figure 2.8 shows the results after the implementation of the new scenarios in the three cities. Figure 2.8 shows the USDI comparison between all the scenarios for the selected cities. It can be observed from this figure that Delhi shows the largest change in the USDI, followed by Shanghai and Kuala Lumpur.

2 The Urban Sustainable Development Index: A Comparative Analysis of Low. . .

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Fig. 2.7 Scenario analysis in the selected cities

%Increase

New

Base

6.41%

Kuala Lumper

0.581 0.546 9.52%

Shanghai

0.437 0.399 23.58%

Delhi

0.304 0.246 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Fig. 2.8 USDI comparison

2.4

Conclusion

In this chapter, the USDI was introduced, and its developing methodology has been explained and discussed. Based on the results, Tokyo obtains the highest overall index score (0.914) followed by Sydney (0.904) and Singapore (0.862). These top three cities consistently perform well above the average across the most dimensions.

38

A. Shaqour and H. Farzaneh

This suggests that these wealthier cities are likely adopting and effectively implementing policies in the areas coverd by the USDI. The insights obtained from the evaluation of the USDI in Delhi’s selected cities, Kula Lumpur and Shanghai, emphasized the urgency of bold and timely LEDs coupled with the social, environmental, and economic opportunities. The application of the USDI in these cities revealed that the LEDS, nonetheless, continue to be of strategic importance for constructing the necessary enabling environment, such as de-risking investment in renewable energies, as well as social policies to cushion the social challenges of decarbonizing energy systems. In other words, a well-designed enabling environment can help to seize these benefits and unlock investment in the selected cities. With this in mind, the USDI represents an interest-oriented approach to mobilizing multiple benefits and argues that multiple benefit assessments can be important drivers of ambitious and effective environmental and social policy. It will help the local decision-makers measure the impacts of the implementation of the LEDs on promoting the local economy, local businesses, and jobs, increasing people’s health and well-being, unburdening governments, freeing resources, and empowering local communities and citizens.

References APO (2017) The 2017 APO productivity Databook. https://www.apotokyo.org/publications/ ebooks/apo-productivity-databook-2017/ Bell S, Morse S (2011) An analysis of the factors influencing the use of indicators in the European Union. Local Environ 16:281–302. https://doi.org/10.1080/13549839.2011.566851 Cassar LF, Conrad E, Bell S, Morse S (2013) Assessing the use and influence of sustainability indicators at the European periphery. Ecol Indic 35:52–61. https://doi.org/10.1016/j.ecolind. 2012.07.011 Farzaneh H (2017a) Multiple benefits assessments of the clean energy development in Asian cities. Energy Procedia, 136:8–13 Farzaneh H (2017b) Development of a bottom-up technology assessment model for assessing the low carbon energy scenarios in the urban system. Energy Procedia 107:321–326 Farzaneh, H. (2018). Devising a clean energy strategy for Asian cities., Springer New York Farzaneh H (2019) Energy systems modeling: principles and applications. Springer, New York Farzaneh H, Suwa A, Dolla CN, Oliveira JA (2014) Developing a tool to analyze climate Co-benefits of the urban energy system. Procedia Environ Sci 20:97–105 Farzaneh H, Xin W (2020) Environmental and economic impact assessment of the low emission development strategies (LEDS) in Shanghai, China. APN Sci Bull 10(1):1–14 Farzaneh H, Doll CN, Puppim de Oliveira JA (2016) An integrated supply-demand model for the optimization of energy flow in the urban system. J Clean Prod 114:269–285 Farzaneh H, De Oliveira JA, McLellan B, Ohgaki H (2019) Towards a low emission transport system: evaluating the public health and environmental benefits. Energies 12(19):3747 Gómez-Sanabria A, Zusman E, Höglund-Isaksson L, Klimont Z, Lee S, Akahoshi K, Farzaneh H, Chairunnisa (2020) Sustainable wastewater management in Indonesia's fish processing industry: bringing governance into scenario analysis. J Environ Manag 111241 Hassan Bhat T, Jiawen G, Farzaneh H (2021) Air pollution health risk assessment (AP-HRA), principles and applications. Int J Environ Res Public Health 18:1935

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Karlsson M, Alfredsson E, Westling N (2020) Climate policy co-benefits: a review. Clim Policy 20:292–316. https://doi.org/10.1080/14693062.2020.1724070 Kılkış Ş (2015) Composite index for benchmarking local energy systems of Mediterranean port cities. Energy 92:622–638 Mayrhofer JP, Gupta J (2016) The science and politics of co-benefits in climate policy. Environ Sci Policy 57:22–30. https://doi.org/10.1016/j.envsci.2015.11.005 Nemet GF, Holloway T, Meier P (2010) Implications of incorporating air-quality co-benefits into climate change policymaking. Environ Res Lett 5. https://doi.org/10.1088/1748-9326/5/1/ 014007 OCED, Metropolitan areas OCED (n.d.). https://stats.oecd.org/Index.aspx?DataSetCode¼CITIES Oliveira JA, Doll CN, Siri J, Dreyfus M, Farzaneh H, Capon A (2015) Urban governance and the systems approaches to health-environment co-benefits in cities. Cad Saude Publica 31(suppl 1):25–38 P. IEA, Energy Efficiency Indicators 2020 (2020). https://www.iea.org/reports/energy-efficiencyindicators-2020 Shah SAA, Zhou P, Walasai GD, Mohsin M (2019) Energy security and environmental sustainability index of South Asian countries: a composite index approach. Ecol Indic 106:105507. https://doi.org/10.1016/j.ecolind.2019.105507 Takeshita S, Farzaneh H, Dashti M (2020) Life-cycle assessment of the wastewater treatment technologies in Indonesia’s fish-processing industry. Energies 13:6591 U.S.E.P.A. EPA, Greenhouse Gas Emissions (n.d.). https://www.epa.gov/ghgemissions/inventoryus-greenhouse-gas-emissions-and-sinks United Nations, UN general assembly, Transforming our world : the 2030 agenda for sustainable development, 2015 United Nations Developement Reports (UNDP), Human Development Data (n.d.). http://hdr.undp. org/en/data United Nations, Summary of the Paris Agreement, United Nations Framew. Conv. Clim Chang (2015) 27–52. http://bigpicture.unfccc.int/#content-the-paris-agreemen World Bank Indicators (2020). https://data.worldbank.org/indicator Worldbank, Water (n.d.). https://www.worldbank.org/en/topic/water/overview

Chapter 3

A Quantitative Model for Forecasting Energy Demand and CO2 Emissions in Pakistan: Toward a Sustainable Energy System Sajid Abrar and Hooman Farzaneh

3.1

Introduction

Energy is the life and backbone of the country’s economy and society, and any disturbance in the continual supply of energy severely affects the country’s economic and social outlook. Pakistan is unfortunate to face this problem since 2006 when the electricity deficiency caused an increasing gap between the supply and demand of energy. This situation of shortage of energy supply has resulted in the shutdown of industries and created inconveniences for the public. It has also caused a hindrance to the economic development of the country. The current energy system of Pakistan is highly dependent on fossil fuels and imports. According to the Energy Statistics Yearbook 2018 published by the Hydrocarbon Development Institute of Pakistan (HDIP), the total primary energy was 88.25 million TOE, including 47.0% imports, during 2017. The final consumption was disaggregated as 17.8% oil (including LPG), 46.7% gas, 19.7% coal, and 15.7% electricity (Ministry of Energy (Petroleum Division) | Hydrocarbon Development Institute of Pakistan 2018). The global environmental challenges, i.e., climate change, global warming, etc., are becoming alarming for countries worldwide. For developing and least developed countries, it is a significant challenge to meet international targets to mitigate and control GHG emissions, especially CO2 (Farzaneh 2018). Statistical data published by the International Energy Agency (IEA) showed that Pakistan’s total CO2 emissions from burning fossil fuels were 183 million tonne CO2

S. Abrar · H. Farzaneh (*) Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Fukuoka, Japan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 H. Farzaneh et al. (eds.), Aligning Climate Change and Sustainable Development Policies in Asia, https://doi.org/10.1007/978-981-16-0135-4_3

41

42

S. Abrar and H. Farzaneh

Fig. 3.1 Trend of CO2 emissions and sectoral share in 2017

(International Energy Agency 2019). Figure 3.1 shows the trend in CO2 emissions from the burning of fossil fuels. During 1990–2017, CO2 emissions increased by 227.7%. The transport sector is the main contributor to oil consumption, resulting in a significant amount of CO2 emissions. Due to the increased demand for electricity, coal consumption has been rising in Pakistan, resulting in increased CO2 emissions and contributing more than any driver to climate change. Although Pakistan makes a minimal contribution to GHG emissions, the country is highly vulnerable to climate change and extreme weather events. The associated costs for climate resilience policies are a critical hurdle for the government. The concept of co-benefits, which emphasizes the local benefits from the climate change mitigation actions, may help offset a reasonable share of the costs involved in such policies (Doll and Oliveira 2017; Farzaneh 2017a,b). Public health is the most important co-benefit that is achieved through improved air quality. Moreover, CO2 emissions are often accompanied by other air pollutants (such as NOx) and particulate matter, causing cardiovascular and respiratory diseases (Oliveira et al. 2015; Farzaneh et al. 2019). Energy security is another co-benefit of climate change mitigation (Farzaneh et al. 2016a). Deployment of local renewable energy can reduce dependence on imported fossil fuels and increase national energy security (Farzaneh et al. 2014). Moreover, it may also improve economic stability by reducing the effects of price shocks on energy commodities due to fluctuation in international markets. Distributed renewable energy sources are also a feasible and economical source of energy to access marginalized and remotely located areas. Renewable technologies are more labor-intensive than traditional power generation facilities. These technologies can help local governments to introduce more green jobs and decrease the unemployment rate. The global scope of climate change has forced nations to rely more heavily on regional and global assistance, cooperation, and collaboration. This can significantly help Pakistan access the resources and technologies for its local adoption and mitigate environmental impacts. To this end, this chapter discusses a methodological approach that can be used to forecast global trends of energy consumption and its related CO2 emissions in Pakistan, which can help decision-makers in analyzing required commitments that should be considered to reduce CO2 emissions and

3 A Quantitative Model for Forecasting Energy Demand and CO2 Emissions in. . .

43

achieve related co-benefits, including energy and cost savings as well as increased energy security in the future.

3.2

Model for Analysis of Energy Demand (MAED)

The Model for Analysis of Energy Demand (MAED) was developed by the International Atomic Energy Agency (IAEA) to help member states to forecast energy and electricity demand (IAEA 2006). It uses both simulation and accounting techniques to project future energy demand, based on economic, social, and technological factors. Social factors involves demographic aspects such as population and lifestyles. Economic factors consists of varaibles such as the level of production (i.e., gross domestic production). Technology relates to the efficiency and market penetration of different technologies. MAED is a bottom-up model. While making calculations, it includes detailed characteristics and technical information about the system. In MAED, the energy sector is divided into four primary sectors, namely, industry, transportation, household, and service. These sectors are further divided into sub-sectors or end-use categories (Fig. 3.2).

3.2.1

Household Sector

The MAED model computes the household energy demand by disaggregating it into five end-use categories, i.e., space heating, air-conditioning, cooking, water heating, electric appliances, and fossil fuel for lighting. The main driver for energy consumption in the household sector is the number of dwelling (NDW) that can be computed by dividing the total population (POP) by the number of people per household, household size (θ). The household sector can be divided into different categories (i), i.e., small, medium, and large size. The following equations are used to calculate the useful energy demand (uf).

3.2.1.1

SHuf ¼

Space Heating (SH) X



h NDWi  SDWi  HDD  ADWi  EHAi  HLDWi  24 i day

 ð3:1Þ

where SDWi: share in total dwellings [%]; ADWi: floor area [m2]; EHAi: effective  heating area [%]; HLDWi: total heat loss from walls and ceilings [kWh/ C  m2  h];

Air Conditioning

Cooking

Water Heating

Elect. Appliances

Air Conditioning

Cooking

Water Heating

Elect. Appliances

Transport

Inter-city

Intra-city

Passenger

Fig. 3.2 Basic structure of the MAED model

Space Heating

Rural

Space Heating

Urban

Household

Freight

Water Heating Motive Power Motive Power

Motive Power

Motive Power

Motive Power

Elect. Appliances

Cooking

Air Conditioning

Space Heating

Electric Req

Thermal Req

Construction

Electric Req

Thermal Req

Agriculture

Service

Electric Req

Thermal Req

Mining

Industry

Electric Req

Thermal Req

Manufacturi ng

Energy Demand

44 S. Abrar and H. Farzaneh

3 A Quantitative Model for Forecasting Energy Demand and CO2 Emissions in. . .

45



HDD: heating degree days [ C-days]. Heating degree days (HDD) are calculated using the process suggested by (Doll and Oliveira 2017).

3.2.1.2

Air-Conditioning (AC)

ACuf ¼

X i

NDWi  ACOWN  UNTi  UECi

ð3:2Þ

where AC _ OWN: AC ownership [%]; UNTi: number of appliances units per dwelling; UECi: specific electricity consumption [kWh unit =year].

3.2.1.3

Electric Appliance (AP)

APuf ¼ NDW 

X

APP OWN j  UNTi  UEC j

ð3:3Þ

j

where APP _ OWNj: appliance ownership [%]; UNT: number of units per dwelling.

3.2.1.4

Cooking (CK) CKuf ¼ NDW  PCE CK  θ

ð3:4Þ

kWh PCE _ CK per capita energy consumption for cooking [Capita ].

3.2.1.5

Hot Water (HW) HWuf ¼ NDW  DH  PCE HW  θ

ð3:5Þ

where DH: share of dwelling with hot water facility [%]; PCEHW:per capita energy kWh consumption for hot water [Capita ].

46

3.2.2

S. Abrar and H. Farzaneh

Transport Sector

As it is shown in Fig. 3.2, depending upon the factors affecting energy consumption in the transport sector, it can be divided into the following sub-sectors and end-use categories (Fig. 3.3). In this sector, the deterministic parameters include passengers’ mobility (i.e., passenger-kilometer PKM), the modal share of types of vehicles, energy intensity, and load factors. The ownership of vehicles, especially private cars, is correlated with income and GDP. Gompertz function can be used to forecast car ownership as follows (Farzaneh 2019): V t ¼ γeαe

βGDPt

ð3:6Þ

Vt refers to the car ownership in the year t, γ is the saturation level for the particular vehicle, and α and β are the statistical coefficients. The saturation level depends upon the population density and structure of the urban system. For Pakistan’s case, it is calculated to be 725 (cars/1000 persons) (Amber et al. 2018). The per capita activity of passengers (PKM/capita) can be estimated using a sigmoid function (Farzaneh et al. 2016b): 

PKM Capita

Fig. 3.3 Transport sector in the MAED model

 ¼ t

γ 1 þ α exp ðβt Þ

ð3:7Þ

Transport Sector

Freight

Passenger

Intra City

Inter City

3 A Quantitative Model for Forecasting Energy Demand and CO2 Emissions in. . .

47

γ is the saturation level PKM/capita in a specific region;  γ and  β are coefficients. PKM The saturation level is considered to be about 11,000 Capita in Pakistan (Singh 2006). The final energy consumption in the transport sector can be calculated by using the following formula: EUT ¼

XX v

f

PKMU  SUT

f ,v

 EIUTv,f

ð3:8Þ

where v is the vehicle type, f is the fuel type, PKMU is the urban PKM, SUT is the modal share (%) of urban transport in total, and EIUT is the fuel intensity (kWh/PKM).

3.2.3

Industry Sector

The industry sector is disaggregated into agriculture, manufacturing, mining, and construction. This sector’s key driver is the level of economic activity (value added) and energy intensity in sub-sectors. Due to the lack of data in Pakistan, the industry sector is divided into the agriculture, general industry, and power sub-sectors. The sub-sectors include manufacturing, construction, and mining activities. For these sub-sectors, the future demand is computed using the total valued-added of the sector, the share of each sub-sector, and energy intensity (the amount of energy required to produce unit worth of value added): EIN ¼

X ss

QIN  SHss  EIss

ð3:9Þ

where QIN: value added by the industry [$]; SH: share of sub-sectors (ss) [%]; EI: energy intensity of sub-sectors (ss) [kWh/$]. In the case of the power system, the total primary energy consumption is considered as the activity level, which is expressed in the following equation: EPG ¼ E G  SHTH  EI

ð3:10Þ

where EG[kWh] is the total electricity generation; SH[%]TH is the share of thermal power generation in total power supply mix, and EI[MJ/kWh] is the energy intensity.

3.2.4

Service Sector

The service sector includes the following sub-sectors in Pakistan: 1. Wholesale and retail trade; 2. Transport, storage, and communication;

48

S. Abrar and H. Farzaneh

3. Finance and insurance; and 4. General government services (hospitals, educational institutes, etc.). In MAED, the service sector is further disaggregated into end-use categories (air-conditioning, space heating, appliances, other thermal uses, and motive power). In the service sector, energy demand is the function of the floor area and specific energy requirement, which can be estimated as follows: EServic ¼ TFArea  F Area  SEC

ð3:11Þ

where TFArea is the total floor area in [sqms], FArea is the floor area that is cooled or heated, and SEC is specific energy consumption [kWh/m2/year].

3.2.5

Final Energy

The following formula is used to calculate the amount of useful energy: FE ¼ UE:MP=ƞ

ð3:12Þ

Here, FE is the total final energy, MP is the energy carrier0s market penetration, and ƞ is the conversion efficiency.

3.3 3.3.1

Data Demographic Data

Population is the main driver for energy demand. In this study, the demographic data, i.e., urban and rural population and household size, is collected from the Pakistan National Census 2017 (Pakistan Bureau of Statistics 2017). Future population projections are taken from the United Nations (United Nations D of E and SA 2019) estimates of the medium variant. The data on household/dwelling characteristics, i.e., categories, size, and share of different fuels for thermal uses, is collected from the Statistics Bureau of Pakistan (SBP) (Pakistan Bureau of Statistics 2016). The input demographic data used in the model are reported in Tables 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, and 3.8.

3 A Quantitative Model for Forecasting Energy Demand and CO2 Emissions in. . . Table 3.1 Demographic data in 2017

Parameter Population Urban Urban population Urban dwellings Share of urban population Urban household size Share of population in large cities Rural Rural population Rural dwellings Rural household size

49

Unit [million]

Value 207.77

[million] [million] [%] [Capita/HH] [%]

75.58 12.19 36.38 6.20 19.10

[million] [million] [Capita/HH]

132.19 20.01 6.61

Table 3.2 Characteristics and specific energy demand for dwellings in urban and rural area in 2017 Parameter Dwelling share Total area of dwelling Effective area for space heating Heat loss Share of dwelling having AC facility Specific energy for cooking Specific energy for water heating Share of dwelling having water heating facility Table 3.3 Air conditioner and other appliances’ ownership (%) in 2017

Unit [%] [m2] [%] [Wh/m2/ C/h] [%] [kWh/cap/ year] [kWh/cap/ year] [%]

Urban Small 24.87 76 12

Medium 69.25 126 22

Large 5.89 177 32

Rural Small 30.4 126 11

Medium 64.4 177 23

Large 5.2 253 32

0.54

0.53

0.53

0.54

0.53

0.53

21.7

21.7

21.7

3.8

3.8

3.8

180

180

180

180

180

180

110

110

110

110

110

110

77

77

77

42

42

42

Home appliance Air conditioner Television Refrigerator Room-cooler Washing machine Water pump Fan Lights

Urban [%] 21.7 86.4 77.1 25.1 82.9 68.3 99.4 99.4

Rural [%] 3.8 48.1 41.9 11.2 44.4 46.8 95.9 95.9

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S. Abrar and H. Farzaneh

Table 3.4 Household appliance specification and energy requirement Appliance Television Refrigerator Room-cooler Washing machine Water pump Fans Lights

Wattage 100 220 185 500 380 60 40

Usage (day/year) 365 365 180 120 365 300 365

Usage (h/day) 4 8 13 1.5 2 12 4

Units 1 1 3 1 1 5 10

Table 3.5 AC specification and energy requirement Dwelling type Small Medium Large

Wattage 1460 @ 75% 1950 @ 75% 1460 @ 75%

Usage (day/year) 120 120 120

Usage (h/day) 8 8 8

Usage (h/year) 960 960 960

Units 1 1 2

Table 3.6 Penetration (%) of different fuels for household thermal use in 2017

Fuel Biomass Electricity Solar Fossil fuel

Urban [%] Space heating 11.71 0.07 0.00 88.22

Water heating 5.21 0.08 0.00 94.72

Cooking 5.21 0.08 0.00 94.72

Rural [%] Space heating 81.33 0.04 0.00 18.64

Water heating 80.86 0.04 0.00 19.11

Cooking 80.86 0.04 0.00 19.11

Rural [%] Space heating 81.33 18.64

Water heating 80.86 19.11

Cooking 80.86 19.11

Table 3.7 Efficiency (%) for different fuels in 2017

Fuel Biomass Fossil fuel

Urban [%] Space heating 18.00 63.00

Water heating 18.00 63.00

Cooking 13.50 53.00

Table 3.8 Percentage share of fuels in fossil fuel for the household sector Fuel Share of fuels

3.3.2

Unit [%]

Oil 8.3

Natural gas 91.7

Mobility and Lifestyle Data

The data on the PKM, TKM, vehicle population, and modal shares are taken from the Economic Survey of Pakistan, reported in Tables 3.9, 3.10, 3.11, and 3.12 (Finance Division G of P. Pakistan Economic Survey 2018).

3 A Quantitative Model for Forecasting Energy Demand and CO2 Emissions in. . . Table 3.9 Passenger and freight activity

3.3.3

Parameter Intracity distance travelled Intercity distance travelled Car ownership Intercity car-kilometers Freight ton-km (TKM)

Unit [km/prsn/day] [km/prsn/year] [person/car] [km/car/year] [109 tkm]

51 Value 5.34 1950.10 25.47 1500 203.34

Economic Data

Gross value added and growth rate are taken from the World Bank (Bank TW. World Bank Open Data n.d.). The share of different sectors is collected from the Pakistan Economic Survey (Change IP on C. Emission Factor Database n.d.) (see Table 3.13). The energy intensity values for different sectors are calculated from the Pakistan Energy Year Books (Ministry of Energy (Petroleum Division) | Hydrocarbon Development Institute of Pakistan 2018) (Table 3.14).

3.3.4

Emission Factor Data

Data on emission factors are collected from the Intergovernmental Panel on Climate Change (IPCC Emission Factor Database, n.d.) (Change IP on C. Emission Factor Database n.d.) for oil, natural gas, and coal (Table 3.15).

3.4

Results and Discussion

Figure 3.4 shows the future projection of the final energy demand and its related CO2 emissions in the business-as-usual scenario. Based on the model results, the total final energy demand is expected to increase from 86 to 395 Mtoe, which will result in CO2 emissions rising from 153 to 946 Mt. The natural gas demand is estimated to grow from 28 to 160 Mtoe, which will bring a significant challenge to the government in order to supply sufficient fuel as the domestic production does not seem to keep pace with this increasing demand trend. Consequently, the government may have to consider importing LNG to tackle this problem. The share of natural gas demand in the household sector will increase from 13% to 21%, mainly due to reduced demand for biomass for indoor cooking from 63% to 21%. The electricity demand significantly increases in this sector from 23% to 56% due to rising air conditioner ownership in buildings. The amount of CO2 emissions increases from 11 to 28 Mt in the household sector, consequently. In the transport sector, gasoline demand rises from 23% to 40% due to the increased use of private cars in cities. The car ownership is expected to increase from 39 [cars/1000 person] to 708 [cars/1000 person], which is close to Pakistan’s saturation level. The results indicate a

Parameter Modal Share Load Factor Fuel type Share by fuel Energy Intensity

Unit [%] [p/vehicle] – [%] [l/100 km]

Car 37.06 2.6 Gasoline 82 9.1 Diesel 10.5 10

CNG 7.5 8.1

Table 3.10 Intercity transport characteristics and technical data Two wheelers 47.21 1.6 Gasoline 100 2.5

Taxi 2.91 2.6 Gasoline 91.6 7.1 CNG 8.37 6.4

Three wheelers 1.82 1.8 Gasoline CNG 91.6 8.37 4.55 8.1

Vans 5.79 12 Gasoline 91.6 5

CNG 8.37 5.61

Bus 5.21 50 CNG 100 23.14

52 S. Abrar and H. Farzaneh

3 A Quantitative Model for Forecasting Energy Demand and CO2 Emissions in. . .

53

Table 3.11 Intracity transport characteristics and technical data Parameter Modal share Load factor Fuel type Share by fuel Energy intensity

Unit [%] [person/vehicle] – [%] [l/100 km]

Table 3.12 Intracity transport characteristics and technical data

Private Car – 2.6 Gasoline 82 9.1

Diesel 10.5 10

Parameter Fuel type Modal share Energy intensity

CNG 7.5 8.1

Unit – [%] [l/100 tkm]

Public Vans 35.72 12 Gasoline 91.6 5

Pickup Diesel 5.17 6.7

Bus 47.2 50 Diesel 100 28.6

Truck Diesel 91.6 2.3

Train 17.1 – Diesel 100 –

Train Diesel 3.24 2.3

Table 3.13 Gross value added and share of different economic sectors Sector Share [%] Gross value added [billion $]

Agriculture 19 45.64

Service 53.18 127.74

General industry 26.32 63.22

Energy 1.5 3.60

Table 3.14 Technical data for the economic sector Sector Agriculture General industry Service Power generation

Energy intensity Unit Value [MJ/US $] 0.77 [MJ/US $] 16.76 [MJ/US $] 1.07 [MJ/kWh] 10.93

Share of fuels [%] Oil Natural gas 1.8 – 7.1 48.8 38.6 23.1 32.7 56.9

Coal – 35.3 – 10.4

Electricity 98.2 8.8 38.3 –

Table 3.15 Emission factors for calculation of CO2 for different fuels Fuel Emission factor

Unit [kg/TJ]

Oil 63,100

Natural gas 56,100

Coal 96,100

remarkable increase in CO2 emissions from 16 to 40 Mt in the transport sector. Both the industry and service sectors will experience a significant increase in energy demand from 45 Mtoe and 3.3 Mtoe to 310 Mtoe and 21.5 Mtoe, respectively (Fig. 3.5). Figure 3.6 represents the impact of economic growth on the future forecast of final energy demand and CO2 emissions in Pakistan. The annual average growth rate of GDP is considered to vary within three levels of low (2.5%), current or medium (5.55%), and high (7%). As can be observed from this figure, economic growth leads to increased energy consumption and CO2 emissions. This rapid growth in energy consumption is linked to an increased level of GDP. This growth will affect people’s income levels and consequently drive up their purchasing power, leading to the

54

S. Abrar and H. Farzaneh Total Final Energy Demand and CO2 Emission

450.0 350.0

Oil

Natural Gas

Electricity

Biomass

CO2 Emission

1000

Solar

900 800 700

[Mtoe]

300.0

600

250.0

500

200.0

400

150.0

[MT CO2]

400.0

Coal

300

100.0

200

50.0

100 0

0.0 2017

2022

2027

2032

[Year]

2037

2042

2047

2052

Fig. 3.4 Total final energy demand and CO2 projection in the business-as-usual scenario

increased penetration of high-energy-intensive appliances such as air conditioners to ensure thermal comfort. In the transport sector, this may favor the growth of private modes of transportation.

3.5

Policy Considerations

Scenario-based analysis of future demand projections is essential for addressing future socioeconomic changes in the country. These scenarios are primarily based on national policies and international commitments and obligations. The following are the different categories of national policies for consideration that may have a shortand long-term impact on energy demand and, consequently, CO2 emissions.

3.5.1

National Climate Change Policy

To mainstream climate change in vulnerable sectors of the economy and steer toward national climate resilience, the National Climate Change Policy was introduced in 2012 by the Government of Pakistan (Ministry of Climate Change 2012). A comprehensive framework for mitigation actions was then introduced to implement this climate change policy (GoP 2013). Considering different opportunities and barriers, it formulates the short-, medium-, and long-term plans of the climate change mitigation actions. The inclusion of these policies in demand analysis will help illustrate the impacts of environmental consideration on Pakistan’s future energy demand scenario.

2047

2052

200.0

250.0

300.0

2017

2022

2027

2032

2037 [Year]

Natural Gas CO2 Emissions

2042

Oil

2047

2052

0

200

400

600

800

1000

0.0

5.0

10.0

15.0

20.0

25.0

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

Fig. 3.5 Sectoral energy demand and CO2 projection in the business-as-usual scenario

0.0

50.0

100.0

150.0

Electricity Coal

Industry Sector Final Enery Demand and CO2 Emissions

0 2042

0.0

2032 2037 [Year]

5

10.0

2027

10

20.0

2022

20

25

30

15

2017

Natural Gas Electricity CO2 Emissions

30.0

40.0

Oil Solar Biomass

[MT CO2]

[MT CO2]

Household Sector Final Energy Demand and CO2 Emissions

[Mtoe] [Mtoe]

50.0

350.0

[Ktoe]

[Mtoe]

2017

2017

2027

2032

2037 [Year]

2042

Diesel CNG CO2 Emissions

2047

2022

2027

Electricity Natural Gas

[Year]

2032

2037

2042

Oil CO2 Emissions

2047

Service Sector Final Enery Demand and CO2 Emissions

2022

Electricity Gasoline Total

Transport Sector Final Enery Demand and CO2 Emissions

2052

2052

0

0

5

10

15

20

25

30

35

40

10

20

30

40

50

[MT CO2] [MT CO2]

60.0

3 A Quantitative Model for Forecasting Energy Demand and CO2 Emissions in. . . 55

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S. Abrar and H. Farzaneh

Final Energy Demand and CO2 Emission [Economic Scenrio]

600 500

Low Demand Low CO2 Emission

Medium Demand Medium CO2 Emission

1600

High Demand High CO2 Emission

1400

[Mtoe]

1000

300

800 600

200

[MT CO2]

1200 400

400 100

200

0

0 2017

2022

2027

2032 2037 [Year]

2042

2047

2052

Fig. 3.6 Future projections of the energy demand and CO2 emissions with economic development

3.5.2

Improvement in Energy Efficiency and Deployment of Renewable Energies

Improvement in energy efficiency is the most important factor that can effectively reduce energy demand and environmental impacts. Like other developing countries, Pakistan has a reasonable scope for reducing energy demand in nearly all sectors. Government policies such as energy auditing, economic incentives for efficiency practices in industries, and subsidized access to the efficient electric appliance for domestic applications should be considered in scenarios for reducing overall energy consumption. Power transmission and distribution networks accounted for 19% of energy losses in 2017, and led to higher consumer-end prices for electricity. The government has planned to reduce these prices by 10% by minimizing the transmission and distribution losses through reforms (GoP 2014). Similar considerations are also in place for the improvement of efficiency of power-generating facilities. The power generation sector accounts for the largest share, i.e., 30% in total CO2 emissions. Since 2006, Pakistan has begun to face power shortfalls, and in the subsequent periods, this supply-demand gap continued to widen. To overcome this problem in a short time, the government implemented power projects mainly based on imported/domestic coal and imported reliquefied natural gas (RLNG). The immense potential of local coal reserves (i.e., 176 billion tonnes) made coal-based generation the least cost-effective scenario. Thus, the governments’ action plans to expand low CO2 emission-based coal technologies such as carbon capture and storage (CCS), coal bed methane capture, and coal fluidized bed combustion will be critical to control the environmental impacts of coal-burning activities.

3 A Quantitative Model for Forecasting Energy Demand and CO2 Emissions in. . .

57

Pakistan is blessed with immense potential of renewables (especially solar and wind) and hydropower that can be an important option in the least CO2 emission energy generation mix. Hydropower is also strongly linked to the water security challenges for the agriculture-based economy of Pakistan. The government has planned to reduce renewable energy tariffs by 15% by making the energy mix based on the least cost and renewable energy resources.

3.5.3

Economic Growth

The key driver for rapid energy demand is economic growth. According to the United Nations (UNDESA 2019), the Government of Pakistan has an ambitious target to attain a growth rate of 8% from 2018 to 2025. However, this rapid economic growth will significantly increase energy demand by increasing gross domestic production (GDP) and income. On the contrary, this growth can help the country economically invest in clean energy projects to mitigate and control emissions in long-run planning. Hence it is essential to consider the government priorities for allocating funds for harnessing renewable energy; exploring indigenous resources, i.e., natural gas; and incentivizing energy conservation and saving. In the transportation sector, the increase in private vehicles’ use is highly correlated with income levels. In this situation, the local government’s policies to support public transportation with relatively clean energy solutions (i.e., natural gas or electricity) will impact energy demand and emissions.

3.5.4

Structural Reforms

The governmental policies such as those focusing on the agriculture sector to ensure domestic food security, incentivizing export-oriented manufacturing industries, and targeting the construction industry to meet the growing demand of households for increasing population will significantly impact future energy demand.

3.5.5

Electrification

The high cost of national electric grid expansion to connect remote areas has resulted in 70.79% access to electricity for the population as of the year 2017. The government is planning to increase the rate of electrification to 90% in 2025.

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Conclusion

This chapter provided a systematic modeling approach that can be used to predict energy demand and its related CO2 emissions in Pakistan. We used the model to emphasize the benefits from integrating different sub-sectors. In the coming decades, the use of energy in Pakistan will present society with new challenges for which new strategies have to be developed. The results of the model revealed that a significant increase in energy demand from 86 to 395 Mtoe would be expected in the near future, which will result in rising CO2 emission from 153 to 946 Mt. There is a hope that future government policies will help identify sustainable development pathways that improve energy efficiency and deploy renewable energies, which may bring insight into schemes for renewable energy performance and selecting the best instruments for harnessing renewable energy in Pakistan.

References Amber KP, Aslam MW, Ikram F, Kousar A, Ali HM, Akram N et al (2018) Heating and cooling degree-days maps of Pakistan. Energies 11:1–12. https://doi.org/10.3390/en11010094 Bank TW. World Bank Open Data (n.d.). https://data.worldbank.org/ Change IP on C. Emission Factor Database (n.d.). https://www.ipcc.ch/ Doll CN, Oliveira JA (2017) Urbanization and climate co-benefits: implementation of win-win interventions in cities. Taylor & Francis, Milton Park Farzaneh H (2017a) Multiple benefits assessments of the clean energy development in Asian cities. Energy Procedia 136:8–13 Farzaneh H (2017b) Development of a bottom-up technology assessment model for assessing the low carbon energy scenarios in the urban system. Energy Procedia 107:321–326 Farzaneh H (2018) Devising a clean energy strategy for Asian cities. Springer, New York. ISBN: 978-981-13-0781-2 Farzaneh H (2019) Energy systems modeling: principles and applications. Springer, New York Farzaneh H, Suwa A, Dolla CN, Oliveira JA (2014) Developing a tool to analyze climate co-benefits of the urban energy system. Procedia Environ Sci 20:97–105 Farzaneh H, McLellan B, Ishihara KN (2016a) Toward a CO2 zero emissions energy system in the Middle East region. Int J Green Energy 13(7):682–694 Farzaneh H, Doll CN, Puppim de Oliveira JA (2016b) An integrated supply-demand model for the optimization of energy flow in the urban system. J Clean Prod 114:269–285 Farzaneh H, De Oliveira JA, McLellan B, Ohgaki H (2019) Towards a low emission transport system: evaluating the public health and environmental benefits. Energies 12(19):3747 Finance Division G of P. Pakistan Economic Survey (2018) GoP (2013). Framework for Implementation of Climate Change Policy (2014–2030) Government of Pakistan. Climate Change Division, Islamabad, Pakistan GoP, Ministry of planning development and R. Pakistan Vision 2025 2014 IAEA (2006) Model for analysis of energy demand (MAED-2) user’s manual. IAEA, Vienna, p 196 International Energy Agency (2019) CO2 emissions from fuel combustion. Outlook:1–92. https:// doi.org/10.1670/96-03N Ministry of Climate Change. National Climate Change Policy 2012 Ministry of Energy (Petroleum Division) | Hydrocarbon Development Institute of Pakistan (2018) Pakistan Energy Year Book 2018: 156

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Oliveira JA, Doll CN, Siri J, Dreyfus M, Farzaneh H, Capon A (2015) Urban governance and the systems approaches to health-environment co-benefits in cities. Cad Saude Publica 31(suppl 1):25–38 Pakistan Bureau of Statistics (2016) Pakistan Social and Living Standards Measurement survey Pakistan Bureau of Statistics (2017) District wise population by sex and rural/urban Government of Pakistan. 6th Popul Census 13 Singh S (2006) The demand for road-based passenger mobility in India: 1950-2030 and relevance for developing and developed countries. Eur J Transp Infrastruct Res:6. https://doi.org/10. 18757/ejtir.2006.6.3.3448 UNDESA (2019) World Population Prospects 2019. https://population.un.org/wpp/Download/ Standard/Population/

Chapter 4

A Multiple Benefits Assessment of the Utilization of High-Efficiency Heat Only Boilers in Ulaanbaatar, Mongolia Hooman Farzaneh and Eric Zusman

4.1

Introduction

Coal is the cheapest and most abudant fuel available in Mongolia, accounting for over 90% of the total final energy consumption. According to the US Energy Information Administration, the demand for coal consumption in Mongolia has peaked at 8800 thousand short tons in 2018, which has led to worsening air pollution (U.S. Energy Information Administration (EIA) n.d.). Mongolia’s most polluted air is found in Ulaanbaatar, Mongolia’s capital, with almost 46% of its population and 49% of its gross domestic product. Mongolia’s National Agency for Meteorology, Hydrology, and Environment Monitoring reported that, in December 2015, the measured PM2.5, PM10, sulfur dioxide, and nitrogen dioxide levels were far in excess of global standards (NSO.MN n.d.). Today, Ulaanbaatar is known as one of the worst cities in the world for air pollution. Driven by population growth and economic development in this city, the demand for heating has been growing rapidly by 40% between 2006 and 2018, and this demand is expected to increase from 20 PJ in 2018 to 30 PJ in 2030 (NSO.MN n.d.). The intensive migration from rural to urban areas resulting in informal settlements called “gers” where home to more than half of the Ulaanbaatar’s population. In ger districts, inhabitants use traditional heating systems such as coal-based stoves without adequate emission controlling mechanisms, making them a key source of air

H. Farzaneh (*) Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Fukuoka, Japan e-mail: [email protected] E. Zusman Sustainability Governance Centre, Institute for Global Environmental Strategies, Hayama, Japan Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 H. Farzaneh et al. (eds.), Aligning Climate Change and Sustainable Development Policies in Asia, https://doi.org/10.1007/978-981-16-0135-4_4

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pollution, including particle matter and sulfur oxides. Many people live in old buildings with insufficient thermal insulation of walls and roofs and poorly sealed windows in urban areas. Therefore, customers must increase their heating use to compensate for high heat losses and maintain warm room temperatures. The most common heating system used in gers is the heat only boiler (HOB) with a closed combustion chamber and a chimney vented to the outdoors. These HOBs have short stacks, so the emissions remain low in the atmosphere and close to people’s living quarters. Emissions from the inefficient HOBs are a significant contributor to ground-level air pollution, especially during the winter, when PM2.5 levels can reach up 20 times those considered safe. Poor air quality in Ulaanbaatar has been linked to an increased risk of respiratory disease and even mortality (World Health Organization 2016). Despite progress made, the heating system’s structure remains fragmented in gers, and a holistic optimization of the HOB supplies is needed. In 2014, as part of the Japan-Mongolia partnership to promote the Joint Crediting Mechanism (JCM) for low-carbon development and cooperation with a Japanese boilermaker, a project was started to upgrade inefficient HOBs in Ulaanbaatar. The high-efficiency HOB that was installed as part of these efforts includes an air heater, cyclone separator, and combustion air blower. A roof was built to protect coal from rain and reduce its moisture content. The coal-feeding mechanism was also improved to further enhance the combustion process. Based on the above discussion, this chapter aims to outline the steps involved in quantifying the greenhouse gas (GHG) emissions and air pollution from replacing old HOBs with high-efficiency models in Ulaanbaatar. Toward this end, a spreadsheet simulation model was developed to examine how much energy is consumed and wasted and also to assess the opportunities for reducing energy consumption, GHG emissions, and air pollution during the operation of HOB. The total emissions of GHGs and air pollutants are estimated using the formula “coal consumptions
emission factor.” The amount of coal consumed by the HOB depends almost entirely upon the HOB efficiency, the coal quality, and the HOB’s quantity of heat. In the simulation model developed for this project, the primary input data includes the net amount of the project activity’s heating load demand during the specific period and the type of coal consumed by the HOB. The HOB efficiency is considered as the key variable which should be calculated more precisely. The co-benefit assessment is based on calculating emission differences between a base case and alternative policy scenarios, estimating impacts for each scenario, and comparing them against each other. Two scenarios that will be evaluated in this chapter include (1) the baseline scenario, which reflects the existing operation condition of the HOB, and (2) the intervention scenario, which consists of the policy interventions to reduce the amount of coal consumption and emissions by improving the thermal efficiency of the HOB. The chapter will then further discuss the scope to quantify additional benefits (other than reducing environmental pollutants and greenhouse gases) such as improving health conditions, increasing employment, and strengthening energy security.

4 A Multiple Benefits Assessment of the Utilization of High-Efficiency Heat. . .

4.2 4.2.1

63

Modeling Framework Spreadsheet Simulation Model

An overview of the spreadsheet simulation model is shown in Fig. 4.1. The model operates with the Microsoft Excel software and provides an analytical framework for conducting a co-benefit assessment; it also has a unique interface for visualizing co-benefits during the development and implementation process. The model allows for either ex post (project data assessment) or ex ante (scenario-based) estimates.

4.2.2

Calculation of the Thermal Efficiency

In this simulation model, a detailed assessment of the thermal efficiency was devloped based on ASME Test Code 4.1 (ASME 2013). Using the estimated value of the thermal efficiency from the ASME Test Code 4.1, the amount of coal feed was calculated. The thermal efficiency is estimated by quantifying all the losses occurring in the boilers using the indirect method. The various heat losses occurring in the boiler are listed as follows: • • • • • • • •

L1: Loss due to dry flue gas L2: Loss due to hydrogen in fuel L3: Loss due to moisture in the fuel L4: Loss due to moisture in the air L5: Loss due to carbon monoxide L6: Loss due to surface radiation, convection, and other unaccounted. L7: Unburned losses in fly ash. L8: Unburned losses in bottom ash.

Boiler efficiency by indirect 100  (L1 + L2 + L3 + L4 + L5 + L6 + L7 + L8).

Fig. 4.1 Overview of the HOB spreadsheet simulation model

method

¼

64

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H. Farzaneh and E. Zusman

Calculation of the Coal Consumption

Based on the estimated value of the thermal efficiency, the amount of coal consumed by the HOB can be calculated as follows: mc ¼

PHp ηHOB GCVc

ð4:1Þ

where mc: mass flow rate of coal (t/h); GCVc: gross calorific value of coal, kJ/kg.

4.2.4

Environmental Impact Assessment

The following formulas were used to estimate the reductions in CO2 and other pollutants from improving the efficiency of the HOB (Farzaneh 2019; EPA n.d.): ERt ¼ BE t  IE t

ð4:2Þ

BE t ¼ PH t =ηB,HOB
EF p,coal

IEt ¼ PH t =ηI,HOB
EF p,coal þ EC t
EF p,Grid

ð4:3Þ

and

ð4:4Þ

where ERt: emission reductions during the period t (Mt); BEt: baseline scenario emissions during the period t (Mt); IEt: intervention scenario emissions during the period t (Mt); PHp: net heat quantity supplied by the HOB during the period t [GJ]; ηB, HOB: boiler efficiency in the baseline scenario (%); ηI, HOB: boiler efficiency in the intervention scenario (%); EFcoal: pollutant’s emission factor of coal (t/tcoal); EFgrid: pollutant’s emission factor of the grid electricity consumed by the HOB [t/MWh]; ECt: electricity consumption by the newly added components during the period t [MWh]. Using the Environmental Protection Agency’s (EPA) standard emission factors, the reductions in GHG emissions and other air pollutants can be estimated (Global burden of disease (GBD) 2018). Figure 4.2 shows the calculation process and input data used in the simulation model.

4.2.5

Health Impact Assessment

Deaths, years of life lost (YLLs), years lived with disability (YLDs), and DALYs are all metrics used to evaluate the health burden of pollution. Deaths and YLLs are

4 A Multiple Benefits Assessment of the Utilization of High-Efficiency Heat. . .

65

Fig. 4.2 Calculation flow in the simulation model Table 4.1 Total DALYs and mortality rates of the most critical diseases in Ulaanbaatar, Mongolia

Chronic obstructive pulmonary disease (COPD) Ischemic heart disease (IHD) Cerebrovascular disease (stroke) Lung cancer (LC) Acute lower respiratory infections (ALRI) Tuberculosis and bronchus (TB)

DALYs 1614

Background mortality rate (per 100,000) 23

11922 9686 1490 10804 2484

150.9 109.7 18.14 276.82 15.7

mortality metrics, while YLDs are used to assess morbidity, and DALYs are used to calculate overall mortality and morbidity (Farzaneh 2018; Hassan Bhat et al. 2021; Oliveira et al. 2015). DALYs are found in most studies that estimate pollution’s health impacts. In this study, DALYs was selected as an indicator for illsutrating the links between mortality and different diseases. According to the WHO, DALYs is the sum of years of potential life lost due to premature mortality and the years of productive life lost due to disability. The effect estimates for DALYs measured as the percent change in the health outcome per every unit change in the PM concentration. Thus, despite the relative sparseness of data, the findings indicate that particulate matter emitted from the HOBs in Ulaanbaatar has serious adverse effects on public health. In terms of lost life years collected from the Global Burden of Disease Website, Ulaanbaatar’s most critical diseases are shown in Table 4.1. (Table 4.1 underlined the importance of ischemic heart disease (IHD), acute lower respiratory infections

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(ALRI), and stroke, which together account for nearly one-third of all lost life years (Ministry of the Environment and Green Development, Mongolia (2014). A strategy comparable to those employed over the last decade to explore the association between daily exposure to air pollution and subsequent health impacts has been employed for this epidemiological investigation. The morbidity and mortality mesaures are calculated as a function of relative risk. The population attributable risk fraction (PAF) for each disease is calculated using relative risk (RR). PAF, in this instance, is the fraction of background disease due to PM2.5 exposures and is defined in as (Ostro 2004): PAFD,p ¼

RRD,p  1 RRD,p

ð4:5Þ

Each disease-specific PAF is then multiplied by the DALYs of that disease to arrive at DALYs’ quantity attributable to PM2.5 in that year. Upper and lower bounds for each PAF are also calculated. D and p refer to the selected disease (i.e., lung cancer, etc.) and the pollutant type (PM). The following equation can calculate the DALYs attributable to selected disease (D) in the exposure group ( p) in each scenario: DALYsD,p

    y y ¼ DALYsD
PAFD,p y y

ð4:6Þ

The values of DALYsD can be collected from Table 4.1. The DALYs averted from the intervention scenario can be estimated by using the following formula:   y ¼ DALYsD,p,B  DALYsD,p,I ADALYsD,p, y

ð4:7Þ

where ADALYsD, p represents the averted DALYs from the intervention scenario. B and I refer to the baseline and intervention scenarios, respectively. Dose-response curves for mortality risk are derived from integrated exposure-response data provided by the authors of the Global Burden of Disease (WHO 2019). The economic benefit of the adverted DALYs due to replacing the existing HOBs with the new one in Ulaanbaatar can be translated into a monetary value by multiplying averted DALYs by the gross domestic product (GDP) (The Word Bank 2018). The term “economic benefit” here indicates the average GDP level attributable to what one person in perfect health would accomplish in each country over 1 year. In other words, it can be considered as the amount of savings which can be earned from avoiding GPD loss due to illness and death, as follows:     $ y SavingD,p ¼ GDP½$=y
ADALYsD,p y y

ð4:8Þ

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where GDP refers to the per capita GDP estimated at about USD 1700 in 2018 (40% of Mongolia) (The Word Bank 2018).

4.2.6

Relationship Between the Unemployment Rate and the Economic Benefit

To investigate the statistical relationship between the unemployment rate and the economic benefit from the adverted DALYs, Okun’s law was used in this study. The relation between growth and unemployment (a proxy for labor force) has been discussed among classical economists since the 1960s. Okun’s law has been a widely studied subject in advanced economies. It defines an inverse association between cyclical fluctuations in the output gap and the unemployment gap. The value of the coefficients varies from country to country and from one-time period to another. Okun’s law can be expressed by using the following formula: Δuc,n ½% ¼

β
SavingD,p =Pop
100 GDP

ð4:9Þ

whereΔuc, n: Change in the unemployment rate by replacing one HOB with the new technology; β: Okun’s law coefficient, which is estimated by using historical data on unemployment rates and GDP; Pop: Population; β is estimated on the basis of the historical data on the unemployment rate, GDP, and population in Mongolia, which were collected over the last 30 years. A multiple linear regression analysis was performed to estimate the value of this coefficient, which suggests β ¼ 0.3705 for the case of Mongolia.

4.2.7

Energy Security

Improving the HOB’s thermal efficiency by deploying the intervention scenario can bolster regional or national energy security in Mongolia. Fuel saving can reduce the reliance on imports of coal shortly. To quantify the amount of fuel saving, the following formula can be used: FS½t=h ¼ F Baseline F Intervention where FS and F refer to the fuel saving and fuel consumption, respectively.

ð4:10Þ

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Intervention Scenarios

Figure 4.3 shows the five main improvements which are considered in the proposed high-efficiency HOB, including (1) automatic stoker coal feeder, (2) coal storage, (3) air preheater, (4) air fuel adjustment, and (5) high-efficiency particle removal cyclone. The primary influence of modern coal feeding devices is optimizing the combustion air and reducing fly ash. Wet coal is less efficient as a fuel. An air preheater is used to preheat the inlet air by recovering the exhaust gas’s thermal energy, increasing the inlet air temperature, and decreasing the temperature of the exhaust gas. The main impact of air preheating on improving thermal efficiency can be evaluated by reducing the loss due to dry flue gas. Adding a roof for the rain protection will reduce the moisture content of coal, which improves combustion efficiency. In this simulation, the following empirical equation was used to calculate the moisture reduction caused by rain protection: Moisture ¼ 0:0815d þ M

ð4:11Þ

where M: moisture content of the coal feed (%); d: the period of storage (day). Air ratio control strategy can play a fundamental role in the safe and profitable operation of the HOB. This is because the HOB combustion zone’s air-to-fuel ratio directly impacts fuel combustion efficiency and environmental emissions. Basically, the combustion air feed rate is adjusted by a flow controller such as a damper and a forced draft (FD) fan or induced draft (ID) fan to maintain a desired pressure inside the boiler. This can also help ensure there is sufficient influx of fresh air into the combustion chamber and removal of exhaust gas from the chimney

Fig. 4.3 Proposed high-efficiency HOB in this study

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Fig. 4.4 Cyclone removal efficiency

The cyclone dust collector uses centrifugal force to remove large and highvolume dust from the exhaust gas. The following formula can be used to calculate the amount of ash removed by the dust collector: mash,out ¼ mash,in 1  ηcy




ð4:12Þ

where mash, out: outlet mass flow rate of fly ash from the dust collector; mash, in: inlet mass flow rate of fly ash to the dust collector; ηcy: dust removal efficiency. Two types of cyclones with the average and high efficiencies were considered in this simulation method, and the dust removal efficiency was collected from Fig. 4.4.

4.4

Results and Discussion

The detailed input data used in the simulation model for the baseline and invention scenarios are shown in Table 4.2.

4.4.1

Environmental Benefits

Table 4.3 shows the comparison between the baseline scenario and the intervention scenarios. It can be observed from this table that the three scenarios of the air preheater, air feed adjustment, and coal feeder (vibrating stoker) can reduce energy losses and improve the HOB efficiency. Both scenarios with the air adjustment and coal feeder (vibrating stoker) perform better than other scenarios in terms of thermal

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Table 4.2 Input data used in the simulation model Ambient condition Ambient temp. ( C) Relative humidity (kg/kg dry air) Wind speed (m/s) Boiler information Boiler type Rated power (kW) Heat duty (kW) Coal feeder Lateral surface area (m2) Surface temp. ( C) Exhaust gas temp. ( C) Coal type Interventions 1. Cyclone dust collector 2. Air preheater

Baseline scenario

Intervention scenario

10 0.0204

10 0.0204

3.5

3.5

E-BIO 600 600 260 Hand-feed 18 60 190 Lignite

E-BIO 600 600 260 Vibrating stoker 18 60 190 Lignite

– –

High efficient , ηcy ¼ 90% Air temp. after preheater ¼ 40 C Flue gas outlet temp. after preheater ¼ 162 C 5% reduction in the moisture content of coal Using damper, controller, and FD fan Excess air ¼ 40% Electric power ¼ 135 kW

3. Coal storage

–

4. Air feed adjustment

– Excess air¼ 200%

efficiency. However, the highest thermal efficiency can be obtained by deploying the coal feeder scenario due to its successful burning of coal. The results show that heating combustion air by deploying the air preheater scenario can raise boiler efficiency by 10% for every 30 C in temperature increase. Using Eq. (4.2), the reduction potential in GHG emissions and co-benefit achievement by the intervention scenarios are reported in Table 4.4. Figure 4.5 shows the variation of the GHG emission reductions and co-benefits in the intervention scenarios. Since the excess air factor in all scenarios is higher than its value under the stoichiometric condition, coal can undergo a complete combustion reaction with a sufficient amount of air and no emissions of carbon monoxide. Therefore, there are no expected co-benefits from reducing carbon monoxide emissions in all of the intervention scenarios. The diagrams suggest that higher values of reduction in GHG emissions tend to yield higher co-benefit values for all intervention scenarios. This can be illsutrated by plotting the levels of reductions on an x-y axis. The less coal burned in the boiler,

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Table 4.3 Comparison between the baseline and the intervention scenarios Results Scenarios

Base

Coal Storage

Energy Glance Heat output (kWh) 260.000 260.000 Heat Input (kWh) 483.283 474.400 Heat Loss 1. Heat loss in dry exhaust 28.705 28.705 gas (%) 2. Heat loss due to forma- 6.833 6833 tion of water from H2 in fuel (%) 3. Heat loss due !o mois- 5.618 4.775 ture in fuel (%) 4. Heat loss due to mois- 0.999 0.999 ture in air (%) 5. Heat loss due to 0.000 0.000 incomplete combustion (%) 6. Heat loss due to radia- 3.604 3.604 tion and convection (%) 7. Heat loss due to 0.164 0.000 unburnt in fly ash (%) 8. Heat loss due to 0.277 0.277 unburnt in bottom ash (%) Total heat loss (%) 46.201 45.194 Thermal Efficiency (%) 53.799 54.806 Mass Flow Fuel flow rate (kg/h) 105.501 103.562 Air flow rate (kg/h) 2512.826 2466.643 Exhaust gas flow rate 2610.130 2562.158 (kg/h) GHG emissions and Air Pollution (kg/h) GMG 181.921 178.577 GHG emission from 0.000 0.000 etectncity SO2 1.849 1.818 PM 2.125 2.086 CO 0.000 0.000 NOx 0.278 0.272

Cyclone

Air preheater

Coal Feeder

Air feed Adj.

260.000 483,283

260.000 408.068

260.000 371.466

260.000 376.677

28 705

19.588

13.039

13.967

6.833

6.569

6.833

6.833

5.618

5.401

5.618

5.618

0.999

0.681

0.433

0.466

0.000

0.000

0.000

0.000

3.604

3.604

3.604

3.604

0.164

0.164

0.136

0.164

0.277

0.277

0.297

0.277

46.201 53.799

36.285 63.715

30.007 69.993

30.975 69.025

105.501 2512.826 2610.130

89.082 2121.749 2203.909

81.091 836.955 911.296

82.229 913.982 989 822

181.921 0.000

153.608 0 000

139.830 0.000

141.792 0.137

1.849 0.212 0.000 0.278

1.561 1.794 0.000 0.234

1.421 1.511 0.000 0.213

1.441 1.656 0.000 0.216

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Table 4.4 GHG emission reduction and co-benefits in the intervention scenarios

GHG (t/y) SO2 (kg/y) PM (kg/y) CO (kg/y) NOx (kg/y)

Coal storage 16.72

Cyclone 0.00

Air preheater 141.56

Coal feeder 210.45

Air feed adj. 200.65

Combined scenarioa 368.74

154.96

0.00

1438.53

2138.05

2038.91

3731.54

195.26

9561.48

1653.42

3070.47

2343.48

14480.63

0.00

0.00

0.00

0.00

0.00

0.00

25.51

0.00

215.99

321.09

306.13

562.59

a

Excluding the effect of air feed adj. (Since the coal feeder and the air feed adjustment are having the same impacts on controlling the amount of air feed, only the coal feeder will be considered in the combined scenario)

the less GHG and related pollutants are emitted, and the more co-benefits can be achieved. However, there is not a one to one relationship between GHGs and PM. This is because the vibrating stoker coal feeder can increase the expected co-benefits in two ways: (1) by improving the thermal efficiency through reducing the amount of coal feed and (2) by removing dust from the exhaust gas by reducing the amount of fly ash as the combustion product which is composed of the particulates. Besides, adding a cyclone separator would only reduce PM’s amount, with almost no impact on GHG emissions. Excess air factor is an essential parameter for the HOB boiler’s daily operation, significantly influencing the burning condition and fuel gas emissions. In the baseline scenario, the excess air factor was reported at 200%. Controlling the excess air factor level by deploying the air feed adjustment scenario can improve HOB performance and decrease GHG emissions and air pollution. As shown in Fig. 4.6, for every 1% decrease in the excess air factor, on average, the GHG emissions and air pollution decrease by 1.24 tons and 0.03 tons per annum, respectively. According to the air preheater scenario, recovering a part of the heat energy from the flue gas from increasing the inlet air temperature can improve the HOB efficiency. Flue gas temperature is one of the main reasons for the high loss. Figure 4.7 shows the impact of inlet air temperature on GHG emissions and air pollution. As the inlet temperature increases by 40  C, the GHG emissions and air pollutions decreases by 180 ton and 4.2 ton per annum, respectively. Although the HOB is designed to burn coal containing 40 percent or more moisture, a reduction in coal moisture content can significantly improve operation and performance and reduce stack emissions. It can be observed from Fig. 4.8 that

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Fig. 4.5 GHG emissions reduction vs. co-benefits

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Fig. 4.6 Impact of the air feed adjustment scenario on GHG emissions and air pollution

Fig. 4.7 Impact of the air preheater scenario on GHG emissions and air pollution

decreasing 10% of the moisture content of coal will lead to a decrease in an emission reduction of 30 tons for GHG and 700 kg for air pollution per year. The results revealed that there is scope to quantify additional benefits (other than reducing environmental pollutants and greenhouse gases) such as improving health conditions, increasing employment, and strengthening energy security. Hence, the following section will outline the methodology used to quantify the

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Fig. 4.8 Impact of coal moisture content in the coal storage scenario on GHG emissions and air pollution

health and economic benefits of improving the HOB’s technical performance in Ulaanbaatar.

4.4.2

Health Co-benefits

To assess the current situation in the baseline scenario, PM data in Ulaanbaatar were obtained from the air quality analysis of Ulaanbaatar (The Word Bank 2011). According to this report, the population-weighted annual average exposures of PM emitted from all HOBs installed in Ulaanbaatar are estimated at 57 (μg/m3) with a yearly emission of 1300 ton; this is based on the assumption that the HOBs provided only 14% of the total heating load demand of the households in this city. Comparing the annual PM emissions reported here with the value shown in Table 4.5 for the base scenario, the total number of the installed HOBs in this city 1300ðyt Þ was approximated to be around 120 (0:0021 t
5000  120). Table 4.5 shows the ð hÞ ðhyÞ estimated values of the annual DALYs attributable to PM emissions in the baseline scenario. According to the model results, by deploying the intervention scenario (explained in Table 4.3), about a 14.49 (t/y) reduction in PM emissions would be expected from replacing only one HOB with the new technology in Ulaanbaatar. This amount corresponds to about 0.64 (μg/m3) reduction in PM’s population-weighted

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Table 4.5 DALYs of different diseases caused by PM emissions from 122 HOBs installed in Ulaanbaatar Relative risk (lower limit) Relative risk (upper limit) PAF (lower limit) PAF (upper limit) DALYs (lower limit) DALYs (upper limit)

COPD 1.100 1.311 0.091 0.237 147 383

IHD 1.239 1.842 0.193 0.457 2299 5448

Stroke 1.169 1.768 0.145 0.434 1401 4207

LC 1.088 1.520 0.081 0.342 120 510

ALRI 1.306 1.437 0.234 0.304 2533 3285

TB 2.125 2.338 0.529 0.572 1315 1421

Total

7815 15254

Table 4.6 Estimated health co-benefit from replacing one HOB with the new technology in Ulaanbaatar Relative risk (lower limit) Relative risk (upper limit) PAF (lower limit) PAF (upper limit) DALYs (lower limit) DALYs (upper limit) Averted DALYs (lower limit) Averted DALYs (upper limit)

COPD 1.099 1.308 0.090 0.235 145 380 1.3 2.6

IHD 1.238 1.837 0.192 0.456 2291 5431 8.5 17.9

Stroke 1.168 1.763 0.144 0.433 1393 4193 7.7 14.0

LC 1.086 1.515 0.080 0.340 119 507 1.4 3.0

ALRI 1.303 1.433 0.232 0.302 2511 3265 21.6 19.6

TB 2.111 2.322 0.526 0.569 1307 1414 7.9 7.2

Total

7766 15,189 48 64

Fig. 4.9 Share of averted DALYs in the different diseases

concentration in this city. The health co-benefits from deploying the intervention scenario are reported in Table 4.6. Figure 4.9 represents the share of the averted DALYs in different diseases, which indicates the remarkable impact of the intervention scenario on reducing health damage of PM emissions, especially in terms of ALRI, IHD, and stroke.

4.4.3

Multiple Benefits

The multiple benefits (air pollution, health, and economic) from implementing the combined intervention scenarios are depicted in Fig. 4.10. It can be observed from

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Fig. 4.10 Multiple benefits from the intervention scenario (one HOB)

this figure that adding one new efficient HOB in Ulaanbaatar results in reducing about 365 tons of GHG emissions and about 14 tons of PM emission, which will also be associated with nearly 64 years of a healthy life and an annual saving of USD 109,000 in Ulaanbaatar’s local economy. The model featured in this chapter can also be used to estimate the impact of scaling up the project and quantifying the mid-term expected multiple benefits from the intervention scenario to replace about 250 HOB in Ulaanbaatar. To evaluate the future impact of the intervention scenario in Ulaanbaatar, a simple projection was made based on the projections for the number of total households in each year from census data obtained from Mongolia’s Annual Statistical Yearbook series (The Word Bank 2018). Base on the census data, the number of apartment houses is estimated to increase from 150,000 in 2012 to 600,000 in 2030. The following assumption was also considered in developing the projection for the model: • Fourteen percent of total heating load demand in these houses is supplied by the HOBs in this city (World Bank 2011); • The total number of installed HOBs in Ulaanbaatar is 250 in 2030 (The Word Bank 2011); • The average annual growth rate of the per capita GDP in Mongolia is 5.9% in 2018; • Population growth (annual %) in Mongolia was reported at 1.796% in 2018; and • The unemployment rate in Mongolia is 6.36% in 2018.

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Table 4.7 Expected environmental, health, and economic benefits from replacing 250 HOBs in Ulaanbaatar in 2030

Co-benefits Reduction in GHG emissions (t) Reduction in PM emission (t) Averted DALYs Savings (M$) Reduction in unemployment rate (%) Energy security in terms of fuel saving (t/y)

2030 92,298 3621 16,000 44.2 0.32 200

The results of the mid-term assessment in 2030 are represented in Table 4.7. It is noted that the significant reduction in the unemployment rate driven by economic growth (GDP) is a result of ongoing increases in the size of the labor force and the level of productivity in the whole society and, therefore, the impacts of new jobs from manufacturing the HOB itself will be small. Replacing the existing HOBs with high-efficiency boilers will also support Mongolia’s energy security by saving about 200 tons of coal in 2030.

4.5

Conclusion

This study explored the application of a quantitative spreadsheet simulation model, which was used to quantify the multiple environmental, health, and economic benefits from replacing current HOBs with the high-efficiency ones in Ulaanbaatar. The model estimated what co-benefits would accrue if local air quality and GHG emissions were the main criteria used in the decision-making process. The assessment of multiple benefits is critical because the project’s actual implementation may depend on support from different stakeholders who value a range of benefits. The results revealed that the intervention scenarios could reduce air pollution and improve health and bolster national energy security through significant savings in coal and electricity consumption as well as reducing a reliance on imports of fossil fuels to Mongolia. The results also indicate that the unemployment-reducing effect is a direct consequence of local GDP growth; this suggests that employment from the co-benefits projects comes through GDP per capita growth. However, the major reduction in the unemployment rate driven by economic growth is a result of ongoing increases in the size of the labor force and the level of productivity; therefore, the impacts of new jobs from manufacturing technology are likely too small. It merits underlining that the interpretation of health and economic benefits largely depends on the level of confidence or uncertainty of various input factors. These confidence intervals need to be taken into consideration when recommending actions.

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References ASME (2013) PTC 4-2013, Fired Steam Generators, Performance Test. ASME, New York EPA (n.d.) Emission Factors for Greenhouse Gas Inventories. https://www.epa.gov/sites/ production/files/2018-03/documents/emission-factors_mar_2018_0.pdf Farzaneh H (2018) Devising a clean energy strategy for Asian cities. Springer, New York Farzaneh H (2019) Energy systems modeling: Principles and applications. Springer, New York Global burden of disease (GBD) (2018) Institute for Health Metrics and Evaluation. https://www. healthdata.org/gbd Hassan Bhat T, Jiawen G, Farzaneh H (2021) Air pollution health risk assessment (AP-HRA), principles and applications. Int J Environ Res Public Health 18:1935 Ministry of the Environment and Green Development, Mongolia (2014) Air pollution and health in Ulaanbaatar, Final project report. https://static1.squarespace.com/static/53856e1ee4b00c6f1fc1f602/ t/5b16f48670a6ad09ed1eef6d/1528231054429/UB+Final+Report+July+10.pdf NSO.MN (n.d.) National statistics office of Mongolia holds its first board meeting. https://www.en. nso.mn/content/252 Oliveira JA, Doll CN, Siri J, Dreyfus M, Farzaneh H, Capon A (2015) Urban governance and the systems approaches to health-environment co-benefits in cities. Cadernos de Saºde Pºblica 31 (Suppl 1):25–38 Ostro B (2004) Outdoor air pollution, assessing the environmental burden of disease at national and local levels. World Health Organization Protection of the Human Environment, Geneva. 9241591263 The Word Bank (2011) Sustainable development series: discussion paper sustainable development department East Asia and pacific region, Mongolia. In: air quality analysis of Ulaanbaatar improving air quality to reduce health impacts The Word Bank (2018) GDP per capita (current US$) - Mongolia. https://data.worldbank.org/ indicator/NY.GDP.PCAP.CD?locations¼MN U.S. Energy Information Administration (EIA) (n.d.). https://www.eia.gov/international/overview/ country/MNG WHO (2019) A heavy burden the direct cost of illness in Africa. https://www.afro.who.int/ publications/heavy-burden-productivity-cost-illness-africa World Bank (2011) Ulaanbaatar, Mongolia, air monitoring and health impact baseline (AMHIB) report: Annex A. Particulate matter concentrations/Baseline in Ulaanbaatar, June 2008–May 2009 World Health Organization (2016) Health indicators. https://untobaccocontrol.org/impldb/wpcontent/uploads/mongolia_2018_annex-1_health_indicator_2016.pdf

Part II

The Co-benefits of Climate Change Mitigation Strategies

Chapter 5

Quantifying and Integrating Co-benefits of Renewable Energy Policies in South Korea Ho-Cheol Jeon, Yong Jee Kim, and Yeora Chae

5.1

Introduction

Recently, South Korea announced that it would make efforts to achieve net-zero emissions by 2050. Korea already has been working to reduce greenhouse gas (GHG) emissions with diverse policies and measures in many sectors. However, climate change is not the only environmental issue that is a concern for South Korea. Annual average particulate matter (PM2.5) concentrations were 23μg/m3 in 2018 and 2019 (National Institute of Environmental Research 2020). National emission standard have been exceeded violated over 50 times in 2018 and 2019. It is expected that annual premature mortality associated with PM2.5 will be the highest among Organisation of Economic Co-operation and Development (OECD) countries (OECD 2017). The South Korean government has to deal with these two serious environmental and health risks like many other countries. Co-control policies to reduce PM2.5 and GHGs simultaneously have therefore become a priority in South Korea. Carefully designed co-control and co-benefit policies would help to resolve these problems in more cost-effective manner. Policies that promote renewable energy have potential to deliver co-benefits. Increasing the share of renewable energy to replace coal-fired power generation is included in both South Korea’s Amendment to the Roadmap for the National GHG Reduction for 2030 and Comprehensive Plan on Fine Dust Management. Although a recent report by the International Renewable Energy Agency (IRENA) indicates that renewable power generation costs in 2019 were lower than the cheapest new coal plants, moves to expand renewable energy such as solar photovoltaic (PV) devices and wind power continue to face economic and financial barriers, especially with regard to initial capital costs (IRENA 2020). The results of

H.-C. Jeon · Y. J. Kim · Y. Chae (*) Korea Environment Institute, Sejong, South Korea e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 H. Farzaneh et al. (eds.), Aligning Climate Change and Sustainable Development Policies in Asia, https://doi.org/10.1007/978-981-16-0135-4_5

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cost-benefit analysis for renewable energy can vary based on the location where the renewable energy facility has been installed, weather conditions, technological developments, and the analysis method itself. However, in many cases, the benefits of renewable energy are ignored or underestimated. Meanwhile, the cost of renewable energy becomes relatively unfavorable when the damage caused by fossil fuel power generation is underestimated. Recent literature indicates that renewable energy has multiple co-benefits (Dimanchev et al. 2019; EPA 2018; Luderer et al. 2019), which can be broadly classified into six categories: (1) reduced global warming, (2) improved public health, (3) inexhaustible energy, (4) creation of jobs and other economic benefits, (5) stable energy prices, and (6) reliability and resilience. In general, renewable energy replaces fossil fuels, thereby reducing GHG emissions and air pollution. According to the Global Burden of Disease (GBD) study, 3.4 million premature deaths were attributed to outdoor air pollution across the globe in 2017, suggesting that air pollution is a major health and environmental risk. The International Energy Agency (IEA) (2019) reports that the share of global electricity generation reached almost 27% in 2019. Renewable power needs to increase to nearly half of the total power generation by 2030, and IRENA (2018) expects it would increase to 85% by 2050. Renewable energy is a more reliable and unlimited source of energy supply, which could also help to stabilize energy prices. However, renewable energy requires additional labor compared to large fossil fuel power plants, which are typically mechanized and capital intensive. Therefore, replacing coal-fired power plants with renewable energy could create more jobs. Since addressing climate change and improving public health by reducing GHGs and air pollution are more perceptible and explicit than other benefits, we will focus on these two benefits. This chapter examines South Korea’s renewable energy policy, and analyzes the co-benefits of renewable energy expansion. South Korea’s total GHG emissions in 2016 was about 694.1 million tons CO2eq., a 0.2 ton increase from 2015. The country is ranked sixth after the USA, Russia, Japan, Germany, and Canada among Annex I countries and 11th when including non-Annex I countries. According to IEA statistics, South Korea’s energy-related total greenhouse gas emissions per capita in 2017 were 11.7 tons CO2eq, which was significantly higher than the average of 8.9 tons in other the OECD countries. Meanwhile, the average annual PM2.5 concentrations in South Korea were twice as high as OECD countries in 2017. Seoul is ranked 27th among the capitals of 87 countries in the world (IQAir 2019) in terms of average PM2.5 exposure. The poor air quality is likely to lead to severe health issues such as asthma, lung cancer, heart disease, myocardial infarction, and cerebral stroke. The Comprehensive Plan on Fine Dust Management promulgated in 2019 includes a variety of policy instruments, such as limiting coal-fired power generation, eco-friendly cars, and enhanced emission standards. Two of the key co-benefits of adopting renewable energy are GHG and air pollutant emission reductions. As of 2017, the share of renewable energy power generation in South Korea was only 7.6%, which is very low compared to Germany’s 33.6%, the UK’s 29.7%, France’s 29.7%, and Japan’s 15.6% (IEA

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85

2018). Moreover, waste and bioenergy account for around 71%, but solar PV and wind power comprise only 21% of renewable power generation. An increasing share of renewable energy such as solar PV and wind power in South Korea will significantly reduce GHG emissions and air pollution, which is likely to bring greater benefits than expected. In this context, South Korea’s renewable energy policy needs to be understood more broadly within the framework of climate change and air pollution reduction policies. This chapter evaluates the co-benefits of South Korea’s GHG mitigation measures that can be quantified and monetized. Accordingly, we have focused on solar photovoltaic (PV) power plants. The remainder of this paper is organized as follows. Section 5.2 describes GHG mitigation, air pollution reduction, and renewable energy policies in South Korea, while Sect. 5.3 describes the methodology. In Sect. 5.4, we discuss our estimation results and conclude with a summary and policy implications in Sect. 5.5.

5.2

Climate Change, Air Pollution, and Renewable Energy Policies in South Korea

This section briefly reviews South Korea’s plans to address climate change and air pollution and promote renewable energy. The renewable energy policy needs to be understood in the context of national climate change and air pollution plans. In the Intended Nationally Determined Contributions (INDCs) submitted in June 2015, South Korea announced a GHG reduction target of 37% below business-asusual (BAU) levels by 2030. An amendment to the National 2030 Roadmap to enhance domestic reductions and effectively implement specific policies was released in 2018. The amendment reflects the national plan for air pollution control established in 2018 and the energy transition announced in 2017. The total GHG emissions in South Korea in 2017 reached 709.1 million tons CO2eq, a 142.7% increase from 1990 and a 2.4% rise compared with 2016. Energy consumption accounts for 651.8 million tons CO2eq, or 86.8%. Although the growth rate of GHG emissions after the 2000s was lower than in previous periods, there has been no remarkable decrease even in the 2010s. Moreover, total and net emissions in 2017 reached a record high (Fig. 5.1). Strong policy packages are needed to alter this trend and achieve government set targets. Basically, environmental policy can be categorized into two types, market- and regulation-based. The energy or pollution taxes or emission trading systems (ETS) are representative market-based instruments, while command-andcontrol instruments are regulatory mechanisms. The South Korean government decided to introduce market-based instruments with typical regulatory policies. The government established the National Emission Allowance Allocation Plan for Phase I (2015–2017) in 2014 and Phase II (2018–2020) in 2017. In addition to more general cross-sectoral instruments to reduce GHG emissions, the roadmap also includes several sector specific measures. In the BAU scenario, the GHG emissions from the energy sector were projected at 333.2 million tons in 2030. The GHG reduction target in the energy sector was 42.2% (140.5 million tons) by

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800 700 600 500

Waste Agriculture Industrial Processes Energy LULUCF

400 300 200 100 0 -100



















Fig. 5.1 Trends in national greenhouse gas emissions and removals (1990–2017)

2030. The sector’s main policy measures include increasing the share of renewable energy to 20% by 2030, early retirement of coal-fired power plants, limiting the entry of new coal power, transitioning from coal to a liquefied natural gas (LNG) power plant, demand management, and distributed renewable energy, among others. The key to reducing GHG emissions in the energy sector is to switch from coal-fired to renewable power generation. However, the share of coal-generated electricity remained at 40.4% in 2019, while new and renewable energy accounted for only 5.8%. Table 5.1 demonstrates sectoral BAU and emission goals. Air pollution, particularly fine dust (PM2.5, PM10), has recently become one of the most serious environmental concerns in South Korea. A survey conducted in 2019 by the Korea Environment Institute (KEI) showed that there is a huge public demand for improving air quality. In this survey, respondents indicated that they had the lowest levels of satisfaction with air quality among a number of environmental issues (water, noise, natural scenery, etc.) (Fig. 5.2). The South Korean government announced a Comprehensive Plan on Fine Dust Management in 2019, which aims to reduce PM2.5 emissions by 35.8% by 2022 from 2014 levels. This plan aims to have the annual PM2.5 concentration decrease to 17–18μg/m3 from 25μg/m3 levels and the annual number of low air quality days to fall from 64 to 40 for the same period (MoE 2019) (Fig. 5.3). The primary measures to reduce air pollution are strengthening control over emissions from coal-fired power plants and increasing penetration rates of renewable energy in the power sector, stricter permissible emission levels for business facilities and “Dust Cap Regulation” in the industrial sector, tighter emission standards and restrictions for diesel vehicles, and encouraging eco-friendly cars such as electric, hybrid, and fuel cell vehicles in the transportation sector. Air quality worsens in the spring and winter seasons due to air temperature, wind speed, and high energy demand. The government will take emergency actions that adjust or limit coalfired power generation and bans cars with high emissions, among others, during these periods. The South Korean government announced the renewable energy 3020 implementation plan (RE 3020) in December 2017, with a goal to increase the share of

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Table 5.1 2030 GHG emission reduction roadmap

Sector Emission reduction by sectors

Reduction measures

Industry Buildings Transportation Waste Public Agriculture and livestock Etc. Transformation

E-new business and CCUS Forest carbon sinks Overseas reductions Domestic reduction Total

Reduction rate (Compared to BAU) (%) 20.5 32.7 29.3 28.9 25.3 7.9

BAU (MtCO2eq) 481.0 197.2 105.2 15.5 21.0 20.7

Emissions after reduction (MtCO2eq) 382.4 132.7 74.4 11.0 15.7 19.0

10.3 (333.2)

30.5 –

–

7.2 (Deterministic)
23.7(Additional) 34.1
10.3

–


38.3

4.5

–

850.8

–

32.5 574.3 536.0

32.5 37.0

Fig. 5.2 Korea’s air quality and pollutants emissions by year

renewable power generation, which stood at 7.6% as of 2017, to 20% by 2030. Furthermore, it includes a switch from bio- and waste-oriented renewable power generation to PV and wind-oriented renewables. Specifically, RE 3020 is set to install PV and wind power over 95% of new capacity by deploying agricultural PV and buildings. Moreover, the RPS for energy suppliers will be gradually strengthened, a feed-in tariff will be introduced for small renewable users, and an eco-environmental energy fund will be raised for utility-scale renewable projects. The use of fossil fuels and nuclear power generation should be reduced through the electricity market to increase the share of renewable power generation. South Korea has a unique electricity market, which has three distinct characteristics. The

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Fig. 5.3 Strategic targets of PM2.5 concentration (~22)

electricity market in South Korea is operated based on cost (variable costs), i.e., costbased pool (CBP), while many other countries’ power market apply a price-based pool (PBP). Second, Korea Electric Power Corporation (KEPCO) is the only buyer in the power market. Moreover, KEPCO bids only the purchase quantity, excluding the electricity market price based on demand estimates. Third, South Korea’s electricity market is independent; i.e., it is not linked to other countries’ power systems. These characteristics of the South Korean electricity market make it possible to easily increase the share of renewable power generation through policies on power generation costs, for example, taxes on fossil fuels for power generation. The increased cost of fossil fuel generation secures the competitiveness of renewable energy generation.

5.3

Methodology

This chapter analyzes the main benefits of installing solar PV power plants by 2030. The South Korean government plans to increase renewable energy to 20% by 2030. According to the RE3020 plan, PV and wind power will be the primary sources of renewable energy rather than waste and bioenergy in 2030. In particular, to raise the share of renewable power generation to 20% by 2030, a renewable capacity of 48.7GW needs to be installed. There are plans to install 30.8 GW of the 48.7GW solar PV power plants by 2030. This chapter estimates the costs and benefits such as carbon dioxide (CO2) reduction, energy-savings, and air pollutant emission reductions by replacing renewable energy with fossil fuel such as coal and LNG. To analyze the co-benefits of renewable energy, we made the following assumptions. Total electricity demand from “The 8th Basic Plan for Long-term Electricity Supply and Demand” has been used for analysis. We assume that the electricity demand is fixed after 2031 since it has demand forecast estimates only up to 2031. Electricity

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Fig. 5.4 Electricity generation from LNG and coal

demand from 2030 to 2031 is expected to be about 0.2%. The share of coal and LNG power generation after 2031 is also fixed. The costs and benefits can vary only with the share of each power generation source. The RE3020 plan has only objectives— i.e., 20% of renewable share in 2030—but does not have an annual PV installation plan. The chapter assumed that PV will be installed evenly every year from 2020 to 2030. It also assumed that the BAU electricity generation from LNG and coal power plants is fixed after 2031. Figure 5.4 shows the BAU electricity generation from LNG and coal power plants used in the chapter. Cost data to build and operate power plants for each energy source, emission factor for calculating GHG, and air pollutant emissions are shown in Table 5.2 (Lee et al. 2018). The utility costs for coal, LNG, and PV are the average values of recently constructed power plants. Benefits of replacing coal and LNG with PV include reduced GHG and air pollutants. The chapter calculated co-benefits using GHG and air pollutants’ damage costs. Air pollutants and GHG emissions have different pathways that affect humans and other receptors. Given that the effects of climate change from GHGs are global, the damage costs have to be evaluated globally. Accordingly, the chapter adopts the social cost of carbon from IWG (2016), which estimates costs based on integrated assessment models. Meanwhile, even though air pollution has transboundary issues, it has more likely to register damages and premature death within the country where the air pollution is emitted. The chapter uses the estimates from Ahn et al. (2018) for these impacts. Ahn et al. (2018) employs the impact pathway approach to estimate the marginal social costs, i.e., monetized damages per pollutant emitted, as shown in Fig. 5.5. Air pollutants’ dispersion is simulated by a popular chemical transport model (CTM), the Community Multiscale Air Quality. In the first step, emissions are categorized by source (point, mobile, and area) and by pollutants (PM2.5, SO2, NOx, VOCs, NH3). The chemical transport model creates

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Table 5.2 Characteristics of power plants by source Contents Utility

Costs

Emission factors

Lifetime (year)-Economic expirationInstallation capacity (MW) Self-consumption (%) Facility utilization rate (%) Construction cost (KRW 1000/kW) Maintenance (KRW/kWmonth) Fuel cost (KRW/Gcal) Transmission/ Construction cost connection cost (KRW/kW) Maintenance cost (KRW/kWmonth) Policy implemen- Law enforcement cost tation cost (KRW/kWh) Infra subsidy (KRW/kWh) CO2 (kg/MWh) NOx (kg/MWh) SOx (kg/MWh) PM2.5 (kg/MWh)

Coal 30 1000 4.60 80 1920 5525

LNG 30 900 1.80 80 1009 3623

21,260 42,000

49,499 16,000

30.86

29.97

PV 15 0.1–3 1 20 935 Construction cost  1.5% – Included in construction cost –

0.88

0.34

–

0.3

0.3

–

823.0 0.4251 0.8575 0.0138

362.5 0.1266 0.0062 0.0049

– – – –

Source: Lee et al. (2018)

Fig. 5.5 Impact pathway approach to estimate monetary damages from air pollutant emission

a source-receptor matrix to calculate the marginal contribution of emissions in a source region to the ambient concentration of PM2.5 in a receptor region.1 The doseresponse relationship between human health, particularly premature death and exposure to PM2.5 concentration change, is adopted from Hoek et al. (2013), who 1

The full CTM approach to analyze the change of the ambient concentration needs running a CTM model for each case. However, it requires enough in terms of expertise, time, and resources (Gilmore et al. 2019).

5 Quantifying and Integrating Co-benefits of Renewable Energy Policies in. . . Table 5.3 Social costs of CO2 and air pollutants

Range Lower bound Average Upper bound

CO2 (KRW/ton) 15,950 52,402 77,466

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Air pollutants (KRW/g) NOx SOx PM2.5 5.8 6.5 94.0 11.5 13.0 188.8 17.3 19.3 282.0

Source: IWG (2016) and Ahn et al. (2018)

draw the relationship between PM2.5 concentration and all-cause death by using meta-analysis of 13 cohort studies. The final step is the monetary valuation for premature death. The value of a statistical life (VSL) is used to monetize the mortality risk reduction value. Although the VSL has led to ethical objection from some who argue that it presents a trade-off between health and money, a vast literature shows that people generally make such trade-offs (Muller and Mendelsohn 2006). A crucial drawback of VSL is that it has a wide range of estimates. It implies that depending on which value we choose, the final valuation result can lead to a different conclusion. Even though Ahn et al. (2018) suggest various estimates from the literature, we choose US$3 million ($2005).2 Finally, Table 5.3 shows the social costs of CO2 and air pollutants. With the factors described, we calculate costs and benefits as follows (Box 5.1): Box 5.1 Quantification of Cost, Benefits, and Co-benefits of Solar PV Installation • Equations Costt ¼ constructionsolar  installt þ ΔMaintenance  installedt

ð5:1Þ

CO2t ¼ ΔEFCO2  instralled t

ð5:2Þ

Energyt ¼ ΔFuelCosts  instralledt

ð5:3Þ

AirAP,t ¼ ΔEFAP  instralledt

ð5:4Þ

• Variables Costt: Cost of replacement to solar PV from coal and LNG constructionsolar: Construction cost of solar PV installt: Installed solar PV at year t ΔMaintenance: Maintenance cost difference between solar and fossil fuels (coal and LNG) installedt: Cumulative solar PV installation until year t CO2t: CO2 emission reduction at year t ΔEFCO2: CO2 emission factor difference between solar PV and fossil fuels (continued) 2

We finally used the value of KRW 3 billion derived through the benefit-transfer method.

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Box 5.1 (continued) Energyt: Energy-saving co-benefits at year t ΔFuelCostsCO2: Fuel costs difference between solar PV and fossil fuels AirAP,t: Air pollutant AP reduction at year t where AP includes SOx, NOx, and PM2.5 ΔEFAP: Air pollutant AP emission factor difference between solar PV and fossil fuels Box 5.2 explains monetization equations of CO2 and air pollutant emission reduction. Box 5.2Monetization of CO2 and Air Pollutant Emission Reduction • Equations CO2SCt ¼ SCCO2  CO2t

ð5:5Þ

AirSCAP,t ¼ SCAP  AirAP,t

ð5:6Þ

• Variables CO2SCt: Monetized CO2 reduction at year t SCCO2: Social costs of CO2 reduction AirSCAP,t: Monetized air pollutant AP reduction at year t SCAP: Social costs of air pollutant AP

5.4

Results

CO2 and air pollutant emission reduction from installing solar PV power plants are summarized in Fig. 5.6. The results show that annual emission reduction of CO2, SOx, NOx, and PM2.5 will be 27.4 million tons, 10,317 tons, 23,233 tons, and 433 tons, respectively. Employing the cost and the social costs of CO2 and air pollutants, the chapter performed a cost-benefit analysis of solar PV power plants. Since the lifespan of solar PV power plants is 15 years, the chapter estimated cost and benefits until 2045. Table 5.4 shows cost, energy-saving, and monetized air pollutants and CO2 emission reduction. The results estimate the cumulative cost at KRW 25,926 billion and the sum of benefit and co-benefits at KRW 28,456 billion. Figure 5.7 shows net-cost changes by considering benefits and co-benefits. The results suggest that including co-benefits significantly alters the outcome of the costbenefit analysis. If we include all the co-benefits in the cost-benefit analysis, the net-cost becomes negative in 2040. Our results indicate that the inclusion of co-benefits can sigincificantly strengthen the economic rationale for promoting renewable energy.

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Fig. 5.6 CO2 and NOx, SOx, and PM2.5 emission reduction

5.5

Conclusion and Policy Implications

Renewable energy is a key solution to cut CO2 emissions and help mitigate climate change. Moreover, edging out coal power generation could have multiple co-benefits such as health improvement from air pollutants. According to IEA (2020a, b), energy efficiency improvement, behavior changes, and electrification are central to achieving net-zero emissions by 2050. As a net-zero measure, electrification implies that the share of renewable power generation should be increased rapidly. South Korea’s renewable share, as of 2017, is only 7.6%, and it relies heavily on waste and bioenergy power generation. South Korea’s government announced RE3020, under which renewable power generation will be increased to 20% by 2030. The crucial

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Table 5.4 Cost and benefits of solar PV power plants Single-year (billion KRW)

Cumulating (billion KRW)

Cost Energy saving AP Lower bound Average Upper bound CO2 Lower bound Average Upper bound Cost Energy saving AP Lower bound Average Upper bound CO2 Lower bound Average Upper bound

2020 3535 162 120

2025 2284 770 130

2030 1398 1,109 240

2035 183 875 250

2040 79 379 130

2045 22 105 40

120 120

250 390

480 720

490 740

260 400

100 140

20

60

80

70

30

10

80 130

190 290

280 420

230 340

100 150

30 40

3535 162 120

17,287 2925 530

25,925 7879 1510

25,925 12,695 2730

25,926 15,504 3620

25,926 16,306 3980

120 120

960 1390

2930 4310

5380 7980

7170 10,650

7890 11,730

20

230

610

1010

1230

1300

80 130

760 1130

2010 2980

3300 4870

4050 5980

4260 6300

Fig. 5.7 Net-cost changes by consideration of co-benefits

barrier to expanding renewable energy is higher costs compared to fossil fuel power generation. However, recent literature reports that renewable power is even cheaper than the cheapest new coal plants in 2019. Moreover, the co-benefits of renewables are usually ignored in the cost-benefit analysis.

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This study reviews South Korea’s renewable energy policies, establishes a goal by 2030, and quantifies its co-benefits. However, our analysis has obvious limitations. Above all, we include only premature death from air pollution reduction and energy savings as co-benefits of renewable energy as a measure to mitigate climate change. Energy security, productivity, ecosystem services, and employments are representative co-benefits that are not easy to quantify and monetize. In particular, employment related to the installation of renewable energy facilities could be a great co-benefit in the era of the COVID-19 pandemic. According to the South Korean government’s plan, renewable energy will replace coal power and other fossil fuel power generation. According to Garrett-Peltier (2017), renewable energy creates 7.49 full-time-equivalent (FTE) jobs per $1 million spending, while only 2.65 FTE jobs are created from $1 million spending on fossil fuels. IRENA (2020) reports that renewable energy could employ more than 40 million people by 2050. The increase in employment from the investment in renewable energy can generate a co-benefit of economic recovery, i.e., green or sustainable recovery from the COVID-19 pandemic (IEA 2020b; OECD 2020). Accordingly, our results underestimate the benefits of solar PV power plants. Second, we assumed the costs of installing a solar panel as a constant. However, IRENA (2019) shows solar PV cost declined by between 66% and 84% in 2010 – 2018. Therefore, the benefits of our study are possibly further underestimated. Even though the results form this analysis may be underestimated, they show that installing solar PV brings environmental and social benefits that are greater than its costs. Specifically, installing a new 30.8GW PV as the RE3020 plan achieves KRW 2.5 trillion in net benefits until 2045. Since the South Korean government has recently introduced targets to reach net-zero emissions by 2050, electrification and expanding renewables are necessary. Our results imply that a significant increase in renewables’ share even after 2030, i.e., more than 20%, will be a cost-effective policy.

References Ahn CY et al (2018) Estimation of social costs of air pollutants. KEI Focus 7(6):11 Dimanchev EG, Paltsev S, Yuan M, Rothenberg D, Tessum CW, Marshall JD, Selin NE (2019) Health co-benefits of sub-national renewable energy policy in the US. Environ Res Lett 14. https://doi.org/10.1088/1748-9326/ab31d9 EPA (2018) Quantifying the multiple benefits of energy efficiency and renewable energy: a guide for state and local governments 1–17 Garrett-Peltier H (2017) Green versus brown: comparing the employment impacts of energy efficiency, renewable energy, and fossil fuels using an input-output model. Econ Model 61:439–447. https://doi.org/10.1016/j.econmod.2016.11.012 Gilmore EA, Heo J, Muller NZ, Tessum CW, Hill JD, Marshall JD, Adams PJ (2019) An intercomparison of the social costs of air quality from reduced-complexity models. Environ Res Lett 14. https://doi.org/10.1088/1748-9326/ab1ab5

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Hoek G, Krishnan RM, Beelen R, Peters A, Ostro B, Brunekreef B, Kaufman JD (2013) Long-term air pollution exposure and cardio- respiratory mortality: a review. Environ Health 12:43. https:// doi.org/10.1186/1476-069X-12-43 IEA (2018) World Energy Outlook 2018. Int. Energy Agency IEA (2019) Renewables 2019: Analysis and forecast to 2024. Int. Energy Agency IEA (2020a) World Energy Outlook 2020. Int. Energy Agency IEA (2020b) Sustainable recovery: world energy outlook special report. World Energy Outlook 185 IQAir (2019) World Air Quality Report. 2019 World Air Qual Rep 1–22 IRENA (2018) Global energy transformation: a roadmap to 2050, global energy transformation. A Roadmap to 2050 IRENA (2019) Renewable Power Generation Costs in 2019 IRENA (2020) Measuring the socio-economics of transition: Focus on jobs, International Renewable Energy Agency, Abu Dhab IWG (2016) Technical Support Document:-Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis-Under Executive Order 12866 Lee GD, Park MD, Jeon YJ, Shin HC, Yang JH, Kim YK, Park HJ (2018) “A study on estimation of levelized cost of electricity by source” in Korean Luderer G, Pehl M, Arvesen A, Gibon T, Bodirsky BL, de Boer HS, Fricko O, Hejazi M, Humpenöder F, Iyer G, Mima S, Mouratiadou I, Pietzcker RC, Popp A, van den Berg M, van Vuuren D, Hertwich EG (2019) Environmental co-benefits and adverse side-effects of alternative power sector decarbonization strategies. Nat Commun 10:1–13. https://doi.org/10.1038/ s41467-019-13067-8 MoE (2019) Comprehensive plan on fine dust management Muller NZ, Mendelsohn R (2006) The air pollution emission experiments and policy analysis model (APEEP) National Institute of Environmental Research (2020) Annual report of air quality in Korea 2020 OECD (2017) OECD Environmental Performance Reviews: Korea 2017 OECD (2020) Making the Green Recovery work for jobs, income and growth. OECD, Paris, pp 21–32

Chapter 6

The Co-benefits of Renewable Energy Policies in Japan: Barriers and Ways Forward Takai Etsujiro

6.1

Introduction

The Fukushima Daiichi Nuclear Power Plant accident occurred in March 2011 following the Great East Japan Earthquake. In the wake of that accident, the Japanese government decided to shut down the country’s nuclear power plants. To compensate for the steep drops in nuclear power, Japan began to rely more heavily on thermal power plants. The turn to thermal power, however, offered what amounted to a stopgap not sustainable solution to Japan’s power needs. Rather, the growing threats of climate change have generated a pressing need to shift from fossil fuels to renewable energy. Such a shift is not only essential to mitigate climate change but can lower electricity prices, boost the energy self-sufficiency rate, create jobs, reduce local air pollution, and improve health. The wide range of benefits listed above are often known as co-benefits. The term co-benefits refers to all the benefits that can be achieved from a policy or project that mitigates climate change. As such, co-benefits often include both more stable climate and an assortment of other environmental, social, and economic benefits. Over the past three decades, the literature on co-benefits has grown significantly. However, there remains a tendency in this literature to focus chiefly on the quantification of different benefits from hypothetical modelling scenarios (Mayrhofer and Gupta 2015). There have been fewer efforts that complemented this modelling work with analysis of the kinds of policies and related barriers to achieving those benefits. This paper aims to fill that hole in the literature by focusing on the case of postFukushima energy policy in Japan. The main purpose of this paper is to describe the policies that can deliver co-benefits from renewable energy in Japan; analyze the technical, social, and political barriers to implementing those policies; present a

T. Etsujiro (*) Sustainable Governance Center, Institute for Global Environmental Strategies, Hayama, Japan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 H. Farzaneh et al. (eds.), Aligning Climate Change and Sustainable Development Policies in Asia, https://doi.org/10.1007/978-981-16-0135-4_6

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simple method for quantifying co-benefits from those policies; and underline how a concept called regional circulating and ecological sphere (RCES) can provide a useful framework for moving past key barriers (MOEJ 2018; Takeuchi 2018). The remainder of the paper is divided into four sections, including the introduction. Section 6.2 offers a review of Japan’s post-Fukushima energy policy with a focus on renewable energy. Section 6.3 presents a survey of barriers to renewable energy in Japan. Section 6.4 provides an overview of a simple method to quantify co-benefits from solar energy. The final section concludes with a discussion of RCES.

6.2

Post-Fukushima Energy Policy

After the Fukushima Daiichi Nuclear Power Plant accident in March 2011, most nuclear power plants in Japan, including those not affected by the earthquake directly, stopped operation. The cessation of nuclear power generation, which accounted for about 25% of the power supply composition before the earthquake, resulted in serious power shortages and measures such as planned blackouts. After conducting regular inspections at nuclear power plants nationwide, the nuclear power plant could not be restarted due to anxiety from local residents. At that time, Japan’s Democratic Party called for a review of the energy mix and denuclearization. Further, a new thermal power plant began operations to cover the power shortage, and greenhouse gas (GHG) emissions increased sharply. In addition, a jump in fossil fuel energy exports led to additional increases in GHGs and hurt Japan’s trade balance (Edahiro 2013). In 2013, the control of the Japanese government switched from the Democratic Party to the Liberal Democratic Party. With the change in government, a decision was made to re-examine the energy plan. That re-examination then led to the restart of only a few nuclear power plants—and a still heavy reliance on thermal power and fossil fuel imports. Around the same juncture, the Japanese government announced a policy of reducing greenhouse gases by 26% in 2030 compared to 2013 as part of its Intended Nationally Determined Contribution (INDC) (Japan 2015) under the Paris Agreement submitted to the United Nations Framework Convention on Climate Change (UNFCCC) in 2015. To meet these targets, the long-term energy supply and demand outlook has been announced that the power supply mix for 2030 will be 56% for thermal power, 20–22% for nuclear power, and 22–24% for renewable energy (Ministry of Economy 2015). Regarding these goals, the Japanese government has stated that these are “ambitious goals [that] are internationally comparable.” A year after formally pledging these targets to the UNFCCC, Japan promulgated a global warming countermeasure plan and clarified the measures and national policies that each entity should undertake regarding the medium-term goal for

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2030. At the same time, Japan outlined a long-term path to achieve the reduction target of reducing GHG emissions by 80% by 2050 (Japan 2016). A few years later, Japan would provide some additional policies and programs for this long-term strategy and achieving the Paris Agreement, noting that a decarbonized society was its final goal to be achieved in the latter half of this century. One of the main policies and programs was the feed-in tariff. In 2012, the feed-in tariff (FIT) system was introduced as a renewable energy measure. The FIT requires general electric utilities to purchase the power generated by renewable energy for a certain period of time at a fixed price. As a result, the renewable energy business operator can secure the predictability of investment recovery and invest without risk. Due to the FIT system, renewable energy began to spread gradually with most of the growth from solar power generation. In 2017, Japan would pass a revised FIT law to overcome some of the challenges that had arisen to greater growth. In addition, for large-scale solar power generation, a bid system was introduced to promote competition among businesses and reduce high costs for consumers. Though there has been clear progress under the FIT system, the diffusion rate of renewable energy lags behind other countries. In addition, while large-scale solar power generation and wind power generation are steadily reducing their costs, they are still expensive compared to international standards. To further expand the introduction and reduce costs, it will be necessary to integrate renewable energy into the power market, like other power sources, while ensuring efficient coordination. Against this backdrop, Japan is considering a shift to the feed-in premium (FIP) system. The FIP system is a method of adding a premium to the market price when renewable energy power producers sell electricity in the market. This premium is added to realize the self-sustaining spread of renewable energy and complete free competition. This allows renewable energy to participate in market transactions while ensuring investment incentives. Under the FIP system, renewable energy is more exposed to price competition with other power sources, and it is easy to encourage operators to reduce costs. Businesses sell power generated by renewable energy in the wholesale power trading market. At the same juncture, the government will offer a premium by adding the difference between the FIP price—which is the standard for power sale income—and the reference price—which is based on the market price. As a result, the business operator can secure an incentive to earn a premium income in addition to power sales income in the market. The FIP price is set either by the Procurement Price Calculation Committee established by the Ministry of Economy, Trade and Industry for each power source category and scale or by using a bidding system. Under the FIP system, the reference price changes depending on the time of the day and the season, and the price rises when there is a shortage of electricity. Therefore, operators have incentives to ensure the stability of electricity supply by introducing storage batteries, cogeneration, and promoting the utilization of demand response, to optimize the entire power system. Some renewable energies are suitable for the FIP system and some are not. Power sources (large-scale solar power generation and wind power generation) whose

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generation costs are steadily reduced through technological innovation are suitable for the FIP system. On the other hand, residential solar power generation and smallscale solar power generation which are power sources that can be flexibly installed near the demand area are not as suitable. Geothermal power generation and biomass power generation are power generation methods that utilize the energy resources existing in the region. Although the power generation costs have not been reduced yet, it is desirable to utilize them to contribute to strengthening resilience in the case of disaster. The ultimate aim should be to reduce cost while choosing the most preferable power sources in each region (Ministry of Economy 2019b). Even with efforts to promote renewable energy, there is significant criticism from within and outside Japan that the Ministry of Economy, Trade and Industry is still supporting coal-fired power plants following the Fukushima accident. Japan’s Ministry of the Environment is cognizant of this criticism and is working to restrict coalfired power, but the jurisdiction over energy policy belongs to the Ministry of Economy, Trade and Industry; the Ministry of the Environment is therefore hamstrung in how much it can influence policies enabling thermal power. Amid the growing global efforts, mainly in Europe, for investment withdrawal (divestment) from coal-fired power generation, Japanese financial institutions that continue to invest in coal-fired power generation continue to face intense scrutiny. Japan’s coal-fired power generation technology emits less carbon dioxide per unit of power generation than overseas rivals but significantly more than natural gas or renewables.

6.3

Barriers to Introducing Renewable Energy

When renewable energy is introduced into the market, there are many obstacles. But technological advances and cost reduction can overcome barriers. This chapter lists different types of barriers and provide clues as to how to overcome these barriers.

6.3.1

Technical Barriers

With the expansion of renewable energy, system constraints such as power generation, power transmission, substation, and power distribution can pose a problem. There can also be issues when the balance between supply and demand is lost. The electric power may disturb the frequency of delivery and damage equipment. This is particularly likely to happen because electricity demand increases during the daytime when people’s lives and industrial activities are active and decreases during the nighttime. In addition, there are challenges related to seasonality as the demand for air-conditioning increases during the summer and winter and decreases during spring and autumn. In the case of thermal power generation, system fluctuations are less likely to occur because these demand fluctuations can be dealt with flexibly.

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However, the amount of power generated by solar power and wind power depends on weather conditions is difficult to adjust arbitrarily. Moreover, since the nature of the electric current is a direct current, it needs to be passed through an electronic device that is sent to a power transmission line. But this device is vulnerable to rapid changes in the flow of electricity. Therefore, the addition of solar power generation or wind power generation to the power system can lead to power failures (Lin and Chen 2013). These technical challenges can be particularly problematic in Japan. In Europe and the United States, the electric power network spreads in a mesh, and when there is an excess or shortage of electric power, the excess is used for other regions. On the other hand, Japan is a land mass that spreads long vertically, and the electric power company has been supplying electricity exclusively to each region so far; the power system is distributed in closed form within the region, and there is limited flexibility between regions. To prevent grid constraints, it is necessary to keep costs as low as possible to deal with uneven distribution of renewable energy resources in each location and to develop networks that support the large-scale introduction of renewable energy. Since the cost of investing new equipment to transmit renewable energy will be high, it is important to extend electricity lines as much as possible if there is unused one. The cost should be kept as low as possible by using transmission lines jointly across regions, but this is not happening in Japan. It is also important to encourage renewable energy power producers to balance supply and demand in the electric power market to suppress the expansion of influence on grid operation. The FIT law requires renewable energy operators to comply with output control without compensation for up to 30 days per year. With the increase in the amount of renewable energy introduced, a system that enables control for 30 days or more is needed and is now being adopted. This will allow for more renewable energy to be accepted (Ministry of Economy 2019a).

6.3.2

Social Barriers

Solar and wind power can confront problems due to location constraint. The amount of power generated by solar power generation per installation area is much smaller than that of thermal power generation or nuclear power generation, and securing a site for installation has been a problem in Japan. It is common to develop a commercial solar power plant on an inexpensive land in the suburbs or to install a solar power generation panel on the roof of a business building or a house to generate private power. When introducing commercial solar power generation into mountainous areas, forests may be cut down to open land, which may lead to the destruction of nature. In the case of a rooftop of a house, some people may express concerns about public nuisances from the destruction of the landscape or added light pollution. Regarding wind power generation, onshore wind power generation will not be built near residential areas due to noise, vibration, and landscape problems.

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The available flat land will be limited, and there is potential damage to wildlife such as birds (Pasqualetti 2011). Some of the social challenges relate specifically to wind power. For example, it is difficult to expand the development of onshore wind power generation. With regard to offshore wind power generation, there are issues with the rules regarding the exclusive use of the sea area and the coordination of interests with fisheries, ship operations, and other stakeholders. In the ocean, the effects of noise and vibration will not cause a problem, and the turbine can be made larger and placed at a higher altitude, so it can be expected to reduce the cost per power generation amount and lead to a large generation volume. Another set of social barriers involve the FIT. Some consumers and industry are opposed to the introduction of renewable energy under the FIT system, suggesting it will lead to higher electricity prices. In addition, some local governments have indicated an opposition to subsidizing the introduction of solar power generation from public funds amid a tight budget due to the low birth rate and aging population. Although the solar power generation systems are more affordable from overseas manufacturers, Japanese consumers hesitate to purchase technologies from overseas manufacturers because they are worried about their poor quality; this prevents the spread of low-cost solar power generation. Others have expressed concerns that the supply of power will become unstable due to the introduction of renewable energy due to some intermittency issues covered in the “Technical Barriers” section (Ministry of Economy 2016). In many countries, the energy industry is oligopolistic, and in many cases there are only a few operators, but even in Japan, the power supply is monopolized by all ten general electric utilities that exist in each region (Souvik and Gangulyb 2017). It is only recently that Consumers were given the option of investing in energygeneration businesses. The liberalization of electricity retailing in 2016 has also allowed consumers to choose their electricity company. The entry of various businesses into the electricity retail business has stimulated competition, encouraged the provision of various services, and reduced prices. Environmentally conscious consumers have also been given the option of paying a premium to buy renewable electricity instead of thermal or nuclear power.

6.3.3

Political Barriers

With the impact of the Fukushima Daiichi Nuclear Power Plant increasing the need for renewable energy, it was believed that solar power and wind power would become major power sources. Solar power generation has been adopted at a relatively steady rate due to the efforts of general electric utilities, but general electric utilities have not included wind power generation and other renewable energies in the portfolio. The slow uptake of these forms of renewable energy are partially attributable to the fact that they compete with the conventional power generation. Energy conservation was strongly promoted because it was able to boost efficiencies

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while maintaining and strengthening the existing industrial structure. After the oil crisis of 1973 and the Gulf War of 1991, oil prices rose particularly sharply, and momentum to promote renewable energy increased in many countries (Martinot and Beck 2004), but Japan responded mainly by promoting energy conservation. This has therefore been a mainstay of energy policy since 1973. Moreover, solar power was not considered a significant threat to that structure (Moe 2011). However, utilities in Japan perceived the adoption and spread of other forms of renewables as much greater threat to their political and economic power. Therefore, when Japan enacted the RPS system and obliged general electric utilities to use electricity generated by renewable energy (generating themselves or purchasing from other companies is obliged), they lobbied to keep the amount of obligation so small that investment in renewable energy remained limited. Over the same juncture, Chinese competitors invested heavily in renewable energy research and development, surpassing Japan in terms of productivity and cost savings (Tamura 2019). With the exception of solar power—which has gained some momentum recently—Japan’s use of renewables remains below its potential.

6.4

Quantification of Co-benefits

Thus far, the paper has discussed Japan’s energy policy and barriers to the introduction of renewable energy. In the next section, the method of quantifying co-benefits from reductions in air pollution will be described. As noted earlier, Japan has decided on the energy mix for 2030 in the NDC that was pledged to the Paris Agreement. Based on this and the current power generation data, the chapter will calculate the power generation increase by solar power generation by 2030 and quantitatively evaluate the co-benefits brought about by the replacement of thermal power generation with solar power generation. Assuming that the installed amount of solar power generation increases linearly from 2020 to 2030, 4100 MW will be installed every year. It is assumed that this will replace thermal power generation from coal or liquefied natural gas (LNG). From the change in the amount of power generated by coal and LNG thermal power generation in 2020 and 2030, the chapter calculates the percentage replaced by solar power. The emission factor can estimate the emission amount of pollutants that are generated per power generation amount of thermal power generation for each fuel type (see Table 6.1). Figures 6.1, 6.2, 6.3, and 6.4 show the emission reductions of CO2 and each pollutant. Figure 6.1 shows that by 2030, CO2 emissions can be reduced by nearly Table 6.1 Emission factors for SOx, NOx, PM2.5, and CO2 (Nansai and Moriguchi 2012) Emission factor Coal LNG

SOx (kg/MWh) 0.161 0

NOx (kg/MWh) 0.123 0.061

PM2.5 (kg/MWh) 0.00582 0.00101

CO2 (kg/MWh) 326.16 212.4

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Fig. 6.1 Emission reduction of CO2

200,000 Tons of CO  reduced

150,000 100,000 50,000 2020

2022

2024

2026

Replacing LNG

Fig. 6.2 Emission reduction of PM2.5

2030

Replacing Coal

Tons of PM  reduced

3.0 2.0 1.0

2030

2028

2029

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

Replacing LNG

Replacing Coal

     

5HSODFLQJ&RDO







 





 



 

7RQVRI62[UHGXFHG

2027

5HSODFLQJ&RDO

70 60 50 40 30 20 10 2020

Tons of NOx reduced

Fig. 6.3 Emission reduction of NOx

2026

2024

2025

2023

2022

2021

2020

-

5HSODFLQJ/1*

Fig. 6.4 Emission reduction of SOx

2028

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200,000 tons. The figure also shows that a large emission reduction effect can be obtained for SOx, NOx, and PM2.5. Japan’s thermal power generation is known to be relatively clean due to advanced technology, but it can be seen that replacement with solar power generation has a large impact on climate change countermeasures and air quality improvement.

6.5

Regional Circular and Ecological Sphere

An important question that follows logically from the quantification of co-benefits is as follows: How can those and potentially even more benefits be achieved? The answer to that question could involve the concept of RCES. To understand that concept, it is important to note that the government of Japan formulates an Environmental Basic Plan about once every 6 years and stipulates general guidelines for comprehensive and long-term measures for environmental conservation. In April 2018, the fifth Environmental Basic Plan was published; the new plan has RCES at its core. The concept of RCES is an idea that calls upon local communities to make full use of regionally available resources to form an independent and decentralized society while complementing and supporting the local resources from neighboring areas. Decentralization is seen as a way to simultaneously solve complex economic, environmental, and social issues (MOEJ 2018; Takeuchi 2018). The concept of RCES is relevant to this paper because it places a premium on the promotion of multiple forms of renewable energy. Not simply solar power but also wind power, hydropower, biomass, waste energy, and geothermal energy are essential to a decarbonized society and sustainable growth. Further, although the distribution of renewable energy resources varies from region to region, every region has an abundance of at least one resource. This abundance is suggested by data from the Ministry of the Environment, Japan, that suggests that sunshine and wind conditions are estimated to be up to about 1.8 times the energy demand. In other words, energy self-sufficiency is possible without relying on fossil fuel imports or nuclear power. Before fossil fuels such as kerosene became commonplace, people lived right next to forests in Japanese rural societies, picking firewood and getting timber as a building material. Appropriate human involvement in forests allowed light to enter the forest floor, promote a healthy diet, and contribute to the cultivation of biodiversity. In this way, the natural area that people have formed through agriculture and forestry while staying close to nature over a long period of time is called Satoyama. The use of biomass resources as fuel for power generation and heat sources also leads to the conservation of forests and provides disaster prevention effects such as water source recharge, landslide prevention, and windbreak prevention. In recent years, the intensification of natural disasters due to climate variability has become apparent, and the damage caused by heavy rains and strong typhoons is becoming more frequent. Against this background, the construction of a hydraulic dam will not only supply electricity to the local area by hydroelectric power

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generation but also help prevent floods and droughts. A construction plan that takes into consideration the protection of the local nature and landscape is required (Dams 2000). Another advantage of the RCES concept is that it does not stop by simply promoting the use of local renewable resources up to their potential. It also underlines the social benefits of more decentralized resource use patterns. Japan’s population has continued to increase since the end of World War II, but since 2005 it has peaked and is in the process of decreasing. In Japan, especially in rural communities where employment is scarce, there are many cases where young people migrate to the city when they enter college or get a job and do not return. The local population is rapidly decreasing due to the declining birth rate and this outflow of people. In the past, factories were located in rural areas and used as places of employment, but they have often declined due to de-industrialization and the relocation of factories overseas. Creating employment is important for regional revitalization, and this requires keeping young people in rural areas and preventing population decline. Renewable energy is one of the few growing industries that can create jobs in rural areas (Souvik and Gangulyb 2017). These jobs are one of the additional benefits of renewable energy—and many also help overcome some of the barriers discussed previously. There are other co-benefits as well. From an economic point of view, the current arrangement wherein local residents and companies purchase electricity from general electric utilities leads to the outflow of wealth from rural areas to cities. Selfsufficiency of electricity contributes to the realization of an independent community, where wealth is circulated in the region. Currently, about 90% of the municipalities in Japan have a deficit in their energy balance, and funds are flowing out of the region, but by using this money for investment in the introduction of renewable energy, there will be potential to build a strong regional economy. Furthermore, when the power supply is cut off due to a typhoon or an earthquake, energy can be self-sufficient in the area, which will increase resilience to disasters—yet another co-benefit. The multiple co-benefits that could potentially flow from RCES are critically important for local consumers, companies, and local governments. The identification, quantification, and incorporation of these co-benefits in planning processes can help convince decision-makers that may oppose the uptake and spread of renewables to change their position. They may also help advance policies that have a similar direction and motivation such as the “Ministry of the Environment Renewable Energy Acceleration/Maximization Promotion Program 2018 Edition” that is promoting the utilization of renewable energy mainly in local economies (Japan 2018).

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107

Conclusion

In Japan, thermal power generation and nuclear power generation have been used to meet the increasing demand for electricity as the economy expands. However, due to problems such as climate change, air pollution, fuel costs, and energy insecurity, the drawbacks of thermal power generation have become increasingly clear. In addition, the Fukushima Daiichi Nuclear Power Plant accident revealed the danger of nuclear power generation. Since the Great East Japan Earthquake, discussions on energy security have moved forward. Furthermore, population decline and industrial decline are becoming more prominent in local communities, and there is a demand for integrated solutions to interrelated social, economic, and environmental problems. To solve these problems, as well as overcome many of the barriers to renewable energy, the RCES offers a useful planning framework. Reducing dependence on thermal power generation will lead to the elimination of air pollution and improvement of health, especially in areas close to thermal power plants. Costs of imported fuels from abroad will be reduced, and the trade balance will be improved. The economy will not be affected by changes in resource prices and international conditions (Sen et al. 2016). If the introduction of renewable energy expands and a power generation, storage, and distribution system is established, power can be self-sufficient even when large-scale centralized power plants are shut down or transmission lines are cut off. If a power retailer is established in a rural area, the overreliance on an electric power company in an urban area can be reduced, while the local economic and employment gains can be realized. In the short term, consumers will be burdened by the FIT scheme’s levy for promoting renewable energy generation, but in the long term, the burden of fuel costs will be eliminated, increasing economic benefits. Thus, promoting renewable energy creates diverse and widespread co-benefits in addition to climate change mitigation. The transition from thermal and nuclear power generation to renewable energy is hampered by vested interests, the government’s stance of refraining from change, and insufficient technological innovation at this time. In the future, when technological innovations in the area of renewable energy and storage batteries occur domestically and internationally, prices would decline, and a simultaneous solution of various problems could be achieved. However, reshaping current institutions and infrastructure will require significant effort, cost and administrative leadership.

References Dams WC (2000) Dams and development: a new framework for decision-making Edahiro J (2013) 東日本大震災後の日本のエネルギーをめぐる状況 Japan, M. of E (2015) 日本の約束草案(2020年以降の新たな温室効果ガス排出削減目標) Japan, M. of E (2016) 地球温暖化対策計画の概要

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Japan, M. of E (2018) 平成30年版環境白書・循環型社会白書・生物多様性白書 地域課題の 解決に資する地域循環共生圏の創造 Kentaro Tamura AK (2019) Decarbonised Energy Technologies—Japan’s Competitiveness at Stake Lin SY, Chen JF (2013) Distributed optimal power flow for smart grid transmission system with renewable energy sources. Energy 56:184–192 Martinot E, Beck F (2004) Renewable energy policies and barriers. In: Encyclopedia of energy. Academic Press/Elsevier Science, Amsterdam Mayrhofer J, Gupta J (2015) The science and politics of co-benefits in climate policy. Environ Sci Policy 57:22–30 Ministry of Economy, T. and I (2015) 長期エネルギー需給見通し Ministry of Economy, T. and I (2016) 電力の小売全面自由化って何? Ministry of Economy, T. and I (2019a) 再エネと安定供給~求められる「発電を続ける力」 Ministry of Economy, T. and I (2019b). 総合資源エネルギー調査会 基本政策分科会 再生可能 エネルギー主力電源化制度改革小委員会 中間取りまとめ(案) Moe E (2011) Vested interests, energy efficiency and renewables in Japan. Energy Policy, November MOEJ (2018) Creation of a regional circular and ecological sphere (Regional CES) to address local challenges. https://www.env.go.jp/en/wpaper/2018/pdf/04.pdf Nansai K, Moriguchi Y (2012) NOx, SOx and PM emissions factors of Japanese stationary sources (EF-JASS, ver.2) Pasqualetti MJ (2011) Social barriers to renewable energy landscapes. Geogr Rev 101(2) Sen S, Ganguly S, Das A, Sen J, Dey S (2016) Renewable energy scenario in India: opportunities and challenges. J Afr Earth Sci 122:25–31 Souvik S, Gangulyb S (2017) Opportunities, barriers and issues with renewable energy development – a discussion. Renew Sust Energy Rev 69:1170–1181 Takeuchi K (2018) Regional circular and ecological sphere. 2018. https://archive.iges.or.jp/en/sdgs/ sts.html

Chapter 7

Quantifying the Co-benefits of Solar Energy in China: Opportunities and Barriers Mao Xianqiang, Xing Youkai, and Eric Zusman

7.1

Introduction

In recent years, the Chinese government has successfully implemented a range of energy savings and emission reduction policies, including structural adjustments, technological updating, and managerial improvements. Among the areas targeted in these policies, the one with the greatest potential to deliver co-benefits is solar energy. Fortunately, China has begun to realize this potential over the last decade. In 2019, for example, China’s installed solar power capacity reached 204.68 GW or over 8000 times the capacity a decade ago. Meanwhile, solar power generation reached 223.8 TW, representing a nearly 1500-fold increase over the same figure 10 years prior (China Electric Power Yearbook n.d.; China Electricity Council 2018, 2019a, b; NEA 2016). This tremendous growth did not occur by accident. It is attributable to significant and deliberate policy changes. By including carefully crafted incentives in high-level policy documents such as the Renewable Energy Law and the 13th Five-Year Plan for Solar Energy Development, China has created an enabling environment that continually fostered the growth of the domestic solar industry and led industry M. Xianqiang (*) Center for Global Environmental Policy, Beijing Normal University, Beijing, China School of Environment, Beijing Normal University, Beijing, China e-mail: [email protected] X. Youkai Center for Global Environmental Policy, Beijing Normal University, Beijing, China E. Zusman Sustainability Governance Centre, Institute for Global Environmental Strategies, Hayama, Japan Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 H. Farzaneh et al. (eds.), Aligning Climate Change and Sustainable Development Policies in Asia, https://doi.org/10.1007/978-981-16-0135-4_7

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stakeholders to harvest previously untapped resources. Further, these targeted incentives have focused on not only photovoltaic panels but also solar thermal utilization. As solar energy has come to occupy a larger share of the energy mix, it has replaced fossil fuels and thereby reduced emissions of greenhouse gases (GHGs) (most notably carbon dioxide (CO2)) as well as conventional air pollutants. This chapter estimates the energy savings, pollution reduction, climate mitigation, and other co-benefits from the spread of solar energy in China. The estimation that sits at the core of this chapter suggests that continued expansion of solar photovoltaic and solar thermal utilization will lead to the following sizable annual reductions in multiple pollutants over the next three decades: SO2 (2.10 Mt/year), NOx (2.09 Mt/year), PM (0.91 Mt/year), and CO2 (5140 Mt/year). The steady increase in solar energy use can also deliver nearly 1.6 trillion RMB/year by 2050. Most of these benefits come from energy production/substitution (89%), while 11% are attributable to addressing local environmental concerns (4%) or reducing CO2 (7%). The chapter concludes by discussing possible barriers to the continued uptake of solar and research that can help overcome these challenges.

7.2

Solar Energy in China

Before estimating the co-benefits, it is important to review China’s potential to generate solar power. China’s total solar radiation resources are abundant—though there is considerable variation in the potential to tap these resources across different parts of the country. In general, solar radiation tends to be greater in China’s plateaus than the plains and larger in the western dry region than eastern humid regions (see Fig. 7.1). Solar power generation includes solar photovoltaic power generation and solar thermal power generation. Solar photovoltaic power generation sits at the core of China’s solar power policies and strategies. The lack of experience in design, construction, operation, and maintenance, as well as shortages of technical capabilities on core components and devices, has nonetheless made it difficult to develop this use of solar. Illustrating as much, China’s solar thermal power generation capacity was only 13.9 MW in 2015, accounting for only 0.03% of total solar power generation capacity. As such, the chapter calculates the co-benefits of based only on solar photovoltaic power generation. In recent years, the Chinese government has issued a series of official documents to promote solar energy (see Table 7.1). One of the instruments codified in some of the listed laws, plans, and policies is the feed-in tariff (FIT). Since September 2013, China has employed an FIT but varied the approach across different regions based on resource endowments and construction costs (Table 7.2). In each of these regions, the benchmark on-grid price (specified in the FIT) of solar photovoltaic power generation has been set at different levels. Based on the development of the photovoltaic industry and cost changes in solar power generation, China’s National Development and Reform Commission (NDRC) and other relevant departments adjusted the benchmark price in line with energy supplies, needs, and other

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Fig. 7.1 Spatial distribution of solar radiation in China (Source: China’s Renewable Energy Development Roadmap 2050)

considerations. On April 28, 2019, the NDRC issued the policy document that regulated the price. Table 7.2 and Fig. 7.2 illustrate how that price changed over time (Table 7.3). From 2011 to 2017, China’s investment in solar power generation fluctuated due to power demands, policy changes, and other factors. From 2011 to 2017, the cumulative investment in solar power generation was 147.1 billion RMB, accounting for 5.78% of the total investment in the power generation industry. Year 2012 witnessed the lowest investment amount, 9.9 billion RMB, accounting for 2.65% of the total investment in power generation industry. In 2013, the investment amounted to 32.3 billion RMB, accounting for 8.34% of the total investment in power generation industry. In early 2013, investment in the photovoltaic industry reached a saturation point with capacity outpacing demand. To address the excess capacity problem, China’s State Council issued a directive entitled “Opinions on Promoting Healthy Development of Photovoltaic Industry.” The directive asked the industry to achieve advanced technology levels, reduce material consumption, and meet other environmental protection standards. These reforms led to an investment “cool-down” in 2014. However, even with these perturbations, the amount of investment in solar power generation industry generally increased from 15 billion RMB in 2014 to 28.5 billion RMB in 2017.

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Table 7.1 Policies to promote solar energy development Date Feb 28, 2005 July 4, 2013

Department The National People’s Congress

Policy/planning Law of renewable energy (Revised)

The State Council

Feb 29, 2016

National Energy Administration (NEA)

Nov 7, 2016

National Development and Reform Commission (NDRC), National Energy Administration (NEA) National Energy Administration (NEA)

Several Opinions on Promoting the Healthy Development of the Photovoltaic Industry Guidance on the establishment of a system for the development and utilization of renewable energy The 13th Five-Year Plan for Electric Power Development (2016–2020)

Dec 8, 2016 Dec 10, 2016 Dec 29, 2016 Nov 8, 2017 Oct 30, 2018 Jan 7, 2019 May 10, 2019 May 28, 2019

National Energy Administration (NEA) National Development and Reform Commission (NDRC), National Energy Administration (NEA) National Development and Reform Commission (NDRC), National Energy Administration (NEA) National Development and Reform Commission (NDRC), National Energy Administration (NEA) National Development and Reform Commission (NDRC), National Energy Administration (NEA) National Development and Reform Commission (NDRC), National Energy Administration (NEA) National Energy Administration (NEA)

The 13th Five-Year Plan for Solar Energy Development The 13th Five-Year Plan for Renewable Energy Development Energy production and consumption revolution strategy (2016–2030) Implementation plan to solve the problem of wasted water, wind, and solar Action Plan of Clean Energy Consumption (2018–2020) Notice on Promoting On-Grid Wind Power and Photovoltaic Power Generation Without Subsidy Notice on Establishing and Perfecting Consumption Guarantee Mechanism for Renewable Energy Power Notice on matters related to the construction of wind power and photovoltaic power generation projects in 2019

While investment fluctuated but generally increased, the amount of solar power capacity and generation moved in a steadily upward direction. As noted previously and depicted in Figs. 7.3 and 7.4, the amount of solar power capacity and generation grew more than a 1000-fold over the decade between 2009 and 2019 (Figs. 7.5 and 7.6). In some ways paralleling solar capacity and generation, China’s solar thermal utilization has also developed rapidly. Solar thermal utilization covers household water heaters, public building water heaters, building heating and cooling, and industrial and agricultural heating. In 2018, the installed solar thermal collecting area amounted to 482.3 km2 or about 32 times that in 1998. China’s solar thermal utilization was equivalent to 72.31 Mtce/year of coal or 337.631 GWth of electricity (China Solar Thermal Alliance n.d.-a, b). The development of traditional solar

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Table 7.2 Types of solar photovoltaic power generation resource areas Resource area Type I resource area

Type II resource area

Type III resource area

Provinces and prefectures Ningxia, Qinghai (Haixi), Gansu (Jiayuguan, Wuwei, Zhangye, Jiuquan, Dunhuang, and Jinchang), Xinjiang (Hami, Tacheng, Aletai, and Kelamayi), Inner Mongolia (other regions besides Chifeng, Tongliao, Xinganmeng, and Hulunbeier) Beijing, Tianjin, Heilongjiang, Jilin, Liaoning, Sichuan, Yunnan, Inner Mongolia (Chifeng, Tongliao, Xinganmeng, and Hulunbeier), Hebei (Chengde, Zhangjiakou, Tangshan, and Qinhuangdao), Shanxi (Datong, Shuozhou, Xinzhou, and Yangquan), Shanxi (Yulin and Yanan), Qinghai (other regions besides Type I resource area), Gansu (other regions besides Type I resource area), Xinjiang (other regions besides Type I resource area) Regions other than Type I and Type II resource areas

Source: National Development and Reform Commission Note: Benchmark on-grid prices of solar photovoltaic power generation were different for various types of solar resource areas. Prices of solar photovoltaic power generation in Tibet were set separately 1.2

Benchmark on-grid price (feed-in-tariff)/ guidedprice RMB/kWh (Tax included)

1.0 0.8

1.00 0.95 0.90

1.00 0.95 0.90

1.00 0.95 0.90

0.98 0.88 0.80

0.6

0.85 0.75 0.65

0.75 0.65 0.55

0.70 0.60 0.50

0.55 0.45 0.40

0.4 0.2 0.0 Approved a er Sep 1, 2013 or approved before Sep 1, 2013 but operate a er Jan 1, 2014

2014

Type Ϩresource area

2015

Jan 1, 2016 Jan 1, 2017 Jan 1, 2018

Type ϩresource area

May 31, 2018

Jul 1, 2019

Type Ϫresource area

Fig. 7.2 Benchmark feed-in tariffs (on-grid price/guided-price) for solar power generation in various solar resource areas

thermal utilization, however, has stagnated since 2015 as the market for solar water heaters has not expanded (see Figs. 7.7 and 7.8). With the technology updating and the acceleration of industrialization, China’s renewable energy made considerable progress in a short period of time. Yet there have been some stumbling blocks. For example, to spur additional growth of solar capacity and generation, efforts were made to connect clean power sources to the

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Table 7.3 Benchmark feed-in tariffs for solar photovoltaic power generation from 2013 to 2019

Release date Aug 26, 2013

Effective date Approved after Sep 1, 2013, or approved before Sep 1, 2013, but operate after Jan 1, 2014

Departments National Development and Reform Commission

Dec 22, 2015

Jan 1, 2016

National Development and Reform Commission

Dec 26, 2016

Jan 1, 2017

National Development and Reform Commission

Dec 19, 2017

Jan 1, 2018

National Development and Reform Commission

May 31, 2018

May 31, 2018

Apr 28, 2019

Jul 1, 2019

National Development and Reform Commission, Ministry of Finance, National Energy Administration National Development and Reform Commission

Policy Notice on promoting the healthy development of the solar photovoltaic industry by exerting price leverage Notice on improving the benchmarkingbased price for onshore wind power and solar photovoltaic power generation Notice on adjusting the benchmarkingbased price for solar photovoltaic power generation and onshore wind power generation Notice on the price policy of solar photovoltaic power generation projects in 2018 Notice on the matters related to solar photovoltaic power generation in 2018

Notice on improving the on-grid electricity price mechanism for solar photovoltaic power generation

Benchmark price/ guided price of various type of resource areas (RMB/kWh) (tax included) Type Type Type I II III 0.90 0.95 1.00

0.80

0.88

0.98

0.65

0.75

0.85

0.55

0.65

0.75

0.50

0.60

0.70

0.40

0.45

0.55

Note: (1) Before July 1, 2019, it was the benchmark on-grid price, and after that, it was the guidedprice. (2) The price of solar photovoltaic power generation in Tibet was set separately

7 Quantifying the Co-benefits of Solar Energy in China: Opportunities and. . . 12%

32.3

28.5 9.83%10%

30 25 20

8% 7.07%

15.5

15 3.95% 9.9

6%

5.54%

15 10

24.1

21.8

8.34%

4.07%

4%

2.65%

2%

5

0%

0 2011

2012

2013

2014

2015

2016

2017

Percentage of power investment (%)

Investment in Solar Power Genera on (Billion RMB)

35

115

Investment in Solar Power Genera on Percentage of power genera on investment

250

12% 10% 8% 6% 4% 2% 0%

200 150 100 50 0

Installed solar power generation capacity

Percentage of total generation capacity(%)

Installed Solar power generation capacity(GW)

Fig. 7.3 Investment in solar power generation in China (Source: China Electric Power Yearbook)

Percentage of total generation capacity

Fig. 7.4 Installed solar PV power generation capacity in China

energy grid. However, the traditional coal-fired power generation-based power transmission system did not integrate well with the fluctuating solar PV power generation.1 Since 2016, relevant governmental departments have released a series of policies aimed at easing relevant bottlenecks. Joint national and local efforts have largely been successful in this regard, and the scale of abandoned solar PV power has fallen accordingly (Fig. 7.9).

1 National Development and Reform Commission. The 13th Five-Year Plan for Renewable Energy Development Dec, 2016.

M. Xianqiang et al. 3.5% 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0%

250 200 150 100 50 0

Solar power generation

Percentage of total power generation (%)

Solar power generation (TWh)

116

Percentage of total power generation

Fig. 7.5 Yearly solar PV power generation in China. Source: (1) Data from 2009 to 2017 comes from China Electric Power Yearbook, (2) China Electricity Council. China Power Industry Statistics Express 2018, (3) China Electricity Council. China Power Industry Statistics Express 2019, (4) National Energy Administration (NEA). The 13th Five-Year Plan for Solar Energy Development. Dec, 2016. Note: Power generation in 2009 is the sum of geothermal, tidal, and solar power generation

Fig. 7.6 Various types of solar power generation. (a) South wall PV in Baoding, China (Photographer: Xing Youkai). (b) Distributed PV panel (Photographer: Xing Youkai)

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500

solar thermal utilization(km2)

450 400 350 300 250 200 150 100 50 0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Fig. 7.7 Solar thermal utilization (solar water heating system) in China. Data Source: China Solar Thermal Alliance, 2019, Report on the Operation Status of China’s Solar Thermal Utilization Industry

Fig. 7.8 Solar water heater system in China. (a) Solar water heating system on roof in Beijing (Photographer: Gao Yubing, Liu Qian). (b) Solar water heating system in rural area (Photographer: Xing Youkai)

7.3

Methods and Data for Quantifying Co-benefits from Solar Energy

Harvesting solar energy can yield significant co-benefits—in terms of both energy saved and reductions in air pollution (such as SO2, NOx, and PM) and GHG emissions. This section calculates those benefits by evaluating how much solar energy replaces energy from coal-fired power plants or other fossil fuel-powered sources. The reductions in air pollutants and CO2 are calculated by multiplying the fossil fuel energy replaced by relevant emission factors. In calculating these benefits, the chapter distinguishes between physical reductions in emissions and the monetized savings from energy conservation or improvements to the environment. The

M. Xianqiang et al. 8 7 6 5 4 3 2 1 0

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7% 6%

6% 5.49

5%

4.6

4% 3%

3% 2%

2% 1% 0%

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2018

Abandoned Solar Power

Percentage of solar power generation (%)

Abandoned Solar Power (TWh)

118

2019 Percentage of solar power generation

Fig. 7.9 Abandoned solar power in China. (Source: Data taken from the National Energy Administration, PRC)

relevant formulas to calculate the “physical” and “monetary” values for the co-benefits follow below: CobenefitsPENGt ¼ CobenefitsPENGSE þ CobenefitsPENGST t

t

¼ SSEt ∙ E SEt þ SST t ∙ E ST t CobenefitsPLAPt ¼ CobenefitsPLAPSE þ CobenefitsPLAPST t

ð7:1Þ t

¼ SSEt ∙ LAPSEt þ SST t ∙ LAPST t CobenefitsPGHGt ¼ CobenefitsPGHGSE þ CobenefitsPGHGST t

¼ SSEt ∙ GHGSEt þ SST t ∙ GHGST t

ð7:2Þ t

ð7:3Þ

CobenefitsPENGt : Fossil fuel energy substitution from solar energy use in China at time t CobenefitsPENGSE : Fossil fuel energy substitution from solar power use at time t t CobenefitsPENGSE : Fossil fuel energy substitution from solar thermal use at time t t CobenefitsPLAPt : Local air pollutant (including SO2, NOx, PM, etc.) emission reduction from solar energy use in China at time t CobenefitsPLAPSE : Local air pollutant (including SO2, NOx, PM, etc.) emission t reduction from solar power use at time t CobenefitsPLAPSE : Local air pollutant (including SO2, NOx, PM, etc.) emission t reduction from solar thermal use at time t CobenefitsPGHGt : Greenhouse gas (including CO2, etc.) emission reduction from solar energy use in China at time t CobenefitsPGHGSE : Greenhouse gas (including CO2, etc.) emission reduction from t solar power use at time t

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Table 7.4 Data sources for co-benefit calculation Year 2014

2017 2018

2019

2019

Institutes Energy Research Institute NDRC, China National Renewable Energy Center, China Renewable Energy Society, and other institutes Greenpeace Energy Research Institute NDRC, China National Renewable Energy Center, Children’s Investment Fund Foundation China Photovoltaic Industry Association, CCID Think Tank Energy Research Institute NDRC

Report title Sino-Danish Renewable Energy Development Programme China Wind, Solar and Bioenergy Roadmap 2050 Co-benefits of Wind and Solar PV Power in China China Renewable Energy Outlook 2018

Roadmap for the Development of China’s Solar Photovoltaic Industry (2018 Edition) China Solar PV Outlook 2050

CobenefitsPGHGSE : Greenhouse gas (including CO2, etc.) emission reduction from t solar thermal use at time t SSEt : Scale (quantity) of solar power generation at time t SST t : Scale (quantity) of solar thermal utilization at time t E SEt : Parameter of fossil fuel substitution from solar power use at time t E ST t : Parameter of fossil fuel substitution from solar thermal use at time t LAPSEt : Parameter of local air pollutant (including SO2, NOx, PM, etc.) emission reduction from solar power use at time t LAPST t : Parameter of local air pollutant (including SO2, NOx, PM, etc.) emission reduction from solar thermal use at time t GHGSEt : Parameter of greenhouse gas (including CO2, etc.) emission reduction from solar power use at time t GHGST t : Parameter of greenhouse gas (including CO2, etc.) emission reduction from solar thermal use at time t CobenefitsM t ¼ PENGt ∙ CobenefitsPENGt þ PLAPt ∙ CobenefitsPLAPt þ PGHGt ∙ CobenefitsPGHGt

ð7:4Þ

CobenefitsM t : Monetary co-benefits from solar energy use in China at time t PENGt ∙ : Price parameter of energy substitution (RMB per unit) at time t PLAPt : Price parameter of local air pollutant emission reduction (RMB per unit) at time t PGHGt : Price parameter of CO2 emission reduction (RMB per unit) at time t The quantification of the co-benefits is based on data from a variety of sources and projections as shown in Table 7.4. In making these calculations, the chapter assumes that China’s solar power generation and solar thermal utilization will continue to develop quickly. The amount of energy replaced is based on the projected amount of solar power

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Table 7.5 China’s solar energy development plan and prospect Year 2018 2020 Plan 2020 E 2025 2030 2035 2040 2045 2050

Installed solar power generation capacity (GW) 174.61 1103

Solar power generation (TWh) 177.51 1503

Solar thermal utilization (km2) 4822 8003

263a 7304 1480a 30004 3557a 4217a 50004

280a 8774 1752a 35004 4189a 5013a 60004

923a 1066(746GWth)5 1210a 1375a 1561a 1773(1241GWth)5

Source: (1) China Electricity Council. China Power Industry Statistics Express 2018. (2) China Solar Thermal Alliance. Report on the Operation Status of China’s Solar Thermal Utilization Industry. (3) NEA. “13th Five-Year Plan” for Solar Energy Development. (4) Energy Research Institute of NDRC, etc. China Solar PV Outlook 2050. 2019. (5) Energy Research Institute NDRC, China National Renewable Energy Center, China Renewable Energy Society, and other institutes. China Wind, Solar and Bioenergy Roadmap 2050. 2014. GWth is converted to km2 with reference to the Report on the Operation Status of China’s Solar Thermal Utilization Industry published by the National Solar Thermal Industrial Technology Innovation Strategic Alliance Note: aFor the years without planned or predicted data, the blanks are filled according to the interpolation calculation of the authors

generation and solar thermal utilization from 2020 to 2050; the relevant projections are drawn from the national solar energy development plans directly or relevant research reports on solar energy development. When development target values are not available for specific years, interpolation is employed to generate reasonable estimates. Based on relevant policies, plans, and research, the chapter assumes that solar energy capacity, generation, and utilization will follow the course illustrated in Table 7.5 and Fig. 7.10.

7.3.1

Energy Efficiency and Emission Parameters

When calculating the benefits, it merits underlining that the continuous penetration of renewable energy (including solar power generation and solar thermal utilization) into the energy mix and steady improvement of clean coal utilization will make China’s electric power industry cleaner in the future. Energy efficiency improvements and reductions in the intensity of air pollutant and GHG emissions will also influence the parameters and projections for calculating co-benefits. These changes are reflected in the data in Table 7.6. The chapter relies on a relatively straightforward approach to calculate the monetized total benefits of solar energy application. That approach involves multiplying the amount of energy supply, air pollutant emission reduction, and CO2

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7000

2000 1800

6000 1600 5000

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1000 3000

800 600

2000

400 1000 200 0

0 2018

2020 Plan

2020 E

Solar power generation capacity (GW)

2025

2030

2035

2040

Solar power generation (TWh)

2045

2050

Solar Thermal Utilization (km2)

Fig. 7.10 China’s solar energy development scenario

emission reduction by relevant price parameters. Energy prices, environmental tax rates, and carbon trading prices are influenced by market fluctuations’ public policies, and other factors have considerable uncertainties. The chapter monetizes the co-benefits based on 2018 prices (Tables 7.4 and 7.7).

7.4

Results

The co-benefits from China’s solar energy use can be calculated as shown in Table 7.8 and Fig. 7.11. In 2018, the co-benefits from solar thermal utilization amounted to 72.31 Mtce/year of energy saved as well as reductions of SO2 0.30 Mt/year, NOx 0.32 Mt/year, PM 0.21 Mt/year, and CO2 163.42 Mt/year. According to these calculations, the estimated benefits from solar thermal application are greater than the co-benefits of solar power generation. As the scale of solar photovoltaic in China continues to expand, however, the co-benefits will increase, and the ratio will shift. In 2050, for instance, the co-benefits of solar energy production and consumption are projected to be energy savings of 1921.94 Mtce/ year, reductions of 2.10 Mt/year of SO2 emissions, reductions of 2.09 Mt/year of NOx emissions, reductions of 0.91 Mt/year of PM emissions, and reductions of 5140 Mt/year of CO2 emission. The co-benefits measured in monetary terms of China’s solar energy utilization are presented in Table 7.9 and Fig. 7.12. Like the assessment of the changes in emission levels, the magnitude of these co-benefits are expected to grow significantly over the next three decades. More concretely, the co-benefits from solar energy use in China will reach nearly 1.6 trillion RMB/year in 2050—or about 14.4 times the comparable figure in 2018. Of the total benefits, approximately 86%

SO2 NOx PM

CO2 emission reduction (g/kWh) Energy (tce/m2) Local air pollutant emission SO2 reduction (kg/m2) NOx PM CO2 emission reduction (t/m2)

Energy (gce/kWh) Local air pollutant emission reduction (g/kWh)

20181 308 0.200 0.190 0.040 841 0.1502 0.6252,3 0.6552,3 0.4302 0.3392,3 2020 306 0.199 0.189 0.040 838 0.149 0.623 0.652 0.428 0.337

2025 303 0.197 0.187 0.039 829 0.148 0.616 0.646 0.424 0.334

2030 300 0.195 0.185 0.039 820 0.146 0.610 0.639 0.419 0.330

2035 295 0.192 0.182 0.038 806 0.144 0.599 0.628 0.412 0.325

2040 290 0.189 0.179 0.038 793 0.141 0.589 0.618 0.405 0.319

2045 285 0.185 0.176 0.037 779 0.139 0.579 0.607 0.398 0.314

2050 280 0.182 0.173 0.036 766 0.136 0.569 0.596 0.391 0.308

Source: (1) China Electricity Council. China Power Industry Annual Development Report 2019. (2) China Solar Thermal Alliance. Operation Status Report of China’s Solar Thermal Utilization Industry. (3) WANG Qingyi. Energy Statistics 2018 Note: aThe solar thermal utilization replaced energy mix can be complex, including coal, electricity, natural gas, biomass, etc. In the present study, we employed the comprehensive emission parameter of fossil fuel energy use referenced from Energy Statistics 2018 (Wang 2018) to calculate the co-benefits

Solar thermal utilization substitution of fossil energy consumptiona

Year Solar power substitution of thermal power generation

Table 7.6 Energy efficiency and emission parameters for solar energy co-benefit accounting

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Table 7.7 Price parameters of co-benefit accounting Indicator Energy (RMB/tce)

Local air pollutant emission reduction (RMB/t)

SO2 NOx PM

CO2 emission reduction (RMB/t)

Normalization coefficient /

Price 743.44

1/0.95 1/0.95 1/2.18

12,632 12,632 5505

/

21.81

Source China Thermal Coal Price Index released by the National Development and Reform Commission, PRC The Schedule of Tax Items and Tax Rates in the Environmental Protection Tax Law of the PRC

China Carbon Forum. China Carbon Pricing Survey 2019

Note National average price in 2018

The tax rate of air pollutants ranges from 1.2 RMB per kg pollutant equivalent to 12 RMB per kg pollutant equivalent. In this research, we use 12.0RMB per kg pollutant equivalent, or 12,000RMB per ton pollutant equivalent Average carbon trading price of China in 2019

Note: The prices of energy, local atmospheric pollutants, and greenhouse gas emission are determined, by referring to the China Thermal Coal Price Index issued by the NDRC, the Environmental Protection Tax Law of the PRC, and the carbon trading price in China. All prices are the 2018 price term

will come from photovoltaic, and solar heating will account for 14%. Most of the estimated benefits are expected to stem from energy production/substitution (89%), and the remaining 11% will come from environmental benefits (4%) and reductions in CO2 emissions (7%).

7.5

Barriers to Solar Energy

Though both recent progress and projections for China’s solar energy developments are impressive, several challenges lay ahead. These challenges begin with the frequently remote location of photovoltaic power sites. The significant distances make the costs of grid connection much higher than other power sources. Meanwhile, the fluctuations (instability) of solar power generation have an impact on grid stability, leading to the abandonment of generated solar power. Another set of challenges involve land use. Compared with traditional coal-fired power plants, the land use efficiency and power generation hours of solar photovoltaic power generation are much lower. The same problem can be found with solar thermal utilization. In the future, the rapid development of solar energy, including

CO2 emission reduction (Mt/a)

Local air pollutant emission reduction (Mt/a)

Co-benefit indicators Energy production/substitution (Mtce/a)

PM

NOx

SO2

Solar power generation Solar thermal utilization Total Solar power generation Solar thermal utilization Total Solar power generation Solar thermal utilization Total Solar power generation Solar thermal utilization Total Solar power generation Solar thermal utilization Total

Table 7.8 Co-benefits from solar energy use in China 2020 85.82 119.44 205.26 0.06 0.50 0.55 0.05 0.52 0.57 0.01 0.34 0.35 234.65 269.92 504.57

2018 54.60 72.31 126.91 0.04 0.30 0.34 0.03 0.32 0.35 0.01 0.21 0.21 149.28 163.42 312.70

1035.18

308.31

0.43 726.87

0.39

0.76 0.03

0.60

0.74 0.16

0.57

402.28 0.17

136.42

2025 265.86

1789.18

352.16

0.52 1437.03

0.45

1.01 0.07

0.68

0.99 0.32

0.65

681.42 0.34

155.82

2030 525.60

3215.74

393.22

0.63 2822.52

0.50

1.40 0.13

0.76

1.40 0.64

0.73

1206.34 0.67

173.99

2035 1032.35

3760.33

439.07

0.71 3321.26

0.56

1.60 0.16

0.85

1.60 0.75

0.81

1409.05 0.79

194.28

2040 1214.77

4395.78

489.97

0.81 3905.81

0.62

1.83 0.19

0.95

1.83 0.88

0.90

1645.37 0.93

216.80

2045 1428.57

5140.01

546.77

0.91 4593.24

0.69

2.09 0.22

1.06

2.10 1.04

1.01

1921.94 1.09

241.94

2050 1680.00

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Energy benefit (Mtce/a)

2000 1500 1000 500 0 2018

2020

2025

2030

Solar Power Genera on

2035

2040

2045

2050

Solar Thermal U liza on

2.0 1.5 1.0 0.5 0.0 SO2 NOx PM SO2 NOx PM SO2 NOx PM SO2 NOx PM SO2 NOx PM SO2 NOx PM SO2 NOx PM SO2 NOx PM

Local air pollutants emission reduc on (Mt/a)

(1) Energy production/substitution benefits 2.5

2018

2020

2025

Solar Power Genera on

2030

2035

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Solar Thermal U liza on

CO2 emission reduc on (Mt/a)

(2) Local air pollutants reduction benefits 6000 5000 4000 3000 2000 1000 0 2018

2020

2025

Solar Power Genera on

2030

2035

2040

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Solar Thermal U liza on

(3) CO2 mitigation benefits Fig. 7.11 Co-benefits of solar energy production and consumption in China in the future. (1) Energy production/substitution benefits. (2) Local air pollutant reduction benefits. (3) CO2 mitigation benefits

Total

Total

CO2 emission reduction

Local air pollutant emission reduction

Co-benefit indicators Energy production/substitution

Solar power generation Solar thermal utilization Subtotal SO2 Solar power generation Solar thermal utilization Subtotal NOx Solar power generation Solar thermal utilization Subtotal PM Solar power generation Solar thermal utilization Subtotal Subtotal Solar power generation Solar thermal utilization Subtotal Solar power generation Solar thermal utilization

2018 40.59 53.76 94.35 0.45 3.81 4.26 0.43 3.99 4.42 0.04 1.14 1.18 9.85 3.26 3.56 6.82 44.76 66.26 111.02

2020 63.80 88.79 152.60 0.70 6.29 7.00 0.67 6.59 7.26 0.06 1.88 1.95 16.20 5.12 5.89 11.00 70.36 109.45 179.80

Table 7.9 Co-benefit evaluation results from solar energy use in China (billion RMB/a) 2025 197.65 101.42 299.07 2.18 7.19 9.37 2.07 7.53 9.60 0.19 2.15 2.34 21.32 15.85 6.72 22.57 217.95 125.01 342.96

2030 390.75 115.85 506.60 4.32 8.21 12.52 4.10 8.60 12.70 0.38 2.46 2.84 28.06 31.34 7.68 39.01 430.88 142.79 573.67

2035 767.50 129.35 896.85 8.48 9.16 17.64 8.05 9.60 17.66 0.74 2.75 3.48 38.79 61.55 8.57 70.12 846.31 159.44 1005.76

2040 903.11 144.43 1047.55 9.98 10.23 20.21 9.48 10.72 20.20 0.87 3.07 3.94 44.35 72.42 9.57 82.00 995.86 178.03 1173.89

2045 1062.06 161.18 1223.24 11.73 11.42 23.15 11.15 11.97 23.11 1.02 3.42 4.44 50.71 85.17 10.68 95.85 1171.13 198.67 1369.80

2050 1248.99 179.87 1428.85 13.80 12.74 26.54 13.11 13.35 26.46 1.20 3.82 5.02 58.02 100.16 11.92 112.08 1377.25 221.70 1598.96

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Fig. 7.12 Monetized co-benefit evaluation of solar energy in China in the future. (1) Energy production/substitution benefits. (2) Environment benefits. (3) CO2 emission reduction benefits. (4) Total co-benefits

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solar photovoltaic and solar thermal utilization, will increase land occupation. The limitation of land supply for developing solar energy facilities might become an issue in the future. A third group of hurdles involve policy consistency and continuity. Since 2019, the subsidy has been cancelled for photovoltaic power FIT. Though the on-grid electricity price of solar power generation may continue to decrease in the future, the shift in policy makes it unclear whether the ambitious solar energy development targets could be achieved or not with less government support.

7.6

The Way Forward

This chapter has described some of the key policies promoting solar power and estimated the co-benefits from further penetration of solar power into China’s energy mix. It has demonstrated that the magnitude of the co-benefits are already significant and could grow sharply in the decades to follow. It further underlined that the largest proportion of estimated benefits come from energy savings as opposed to improving the local environment or controlling GHGs. These findings also suggest potentially fruitful avenues for future research. One such avenue involves expanding the types of estimated co-benefits. Besides energy savings, human health improvement benefits and the creation of green jobs may provide additional support for solar promotional policies. Further, it would be useful to employ energy-environment-economic (3E) models, including computable general equilibrium (CGE) models, to examine changes in co-benefits from combined policy scenarios, especially for price, tax, and trade policies. Another potentially illuminating angle on research is to integrate some of the barrier analysis in emission reduction scenarios. Interviews with policymakers, industrial experts (including solar photovoltaic and solar thermal utilization production and application), and other informed stakeholders can shed light on the technical, economic, and institutional barriers to solar energy development. It can also use that information to make more accurate forecasts of China’s solar energy development in the future and make reasonable adjustments to pertinent modelling parameters (such as the timing of technology changes or the penetration rates of technologies).

References China Electric Power Yearbook (n.d.) China Electricity Council (2018) China Power Industry Statistics Express China Electricity Council (2019a) China Power Industry Annual Development Report China Electricity Council (2019b) China Power Industry Statistics Express

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China Solar Thermal Alliance (n.d.-a) Operation Status Report of China’s Solar Thermal Utilization Industry China Solar Thermal Alliance (n.d.-b) Report on the Operation Status of China’s Solar Thermal Utilization Industry National Energy Administration (NEA) (2016) The 13th Five-Year Plan for Solar Energy Development Wang Q (2018) Energy statistics. Innovative Green Development Program, Beijing

Part III

New Perspectives on Co-benefits

Chapter 8

Biodiversity Co-benefits: Narrowing the Gap Between Analysis and Action Kaoru Akahoshi and Eric Zusman

8.1

Introduction

In 1992, the international community negotiated the United Nations Framework Convention on Climate Change (UNFCCC) and the Convention on Biological Diversity (CBD) at the United Nations Conference on Environment and Development. These landmark agreements would help spark an early interest in the wide range of benefits from addressing climate change at the same time as biodiversity. In the years that followed, climate change policymakers and researchers would refine their understanding of the actions that protect the climate (such as preserving forests) while enhancing biodiversity. Over the same period, biodiversity policymakers and researchers would broaden their appreciation of actions intended to protect endangered species and preserve ecosystems while mitigating greenhouse gases (GHGs) or increasing climate resilience. The recognition of these benefits, then, helped open the door for work on what will be termed biodiversity co-benefits—or the collection of benefits generated from actions that protect the climate while preserving biodiversity. The interest in biodiversity co-benefits, therefore, began to take shape approximately two decades ago. Yet, unlike most chapters in this book, the breadth and depth of discussions around biodiversity co-benefits have not been as significant as

K. Akahoshi (*) Sustainability Governance Centre, Institute for Global Environmental Strategies, Hayama, Japan e-mail: [email protected] E. Zusman Sustainability Governance Centre, Institute for Global Environmental Strategies, Hayama, Japan Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 H. Farzaneh et al. (eds.), Aligning Climate Change and Sustainable Development Policies in Asia, https://doi.org/10.1007/978-981-16-0135-4_8

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research on co-benefits from energy- or air pollution-related interventions. This situation has nonetheless begun to change. An important reason for the shift is the agreement over the 2030 Agrenda for Sustainable Development and its Sustainable Development Goals (SDGs). The SDGs emphasize taking an integrated approach to development planning that works across the social, economic, and environmental dimensions of sustainable development (UN 2015). With an SDG focused chiefly on climate change and two goals concentrating on life on land (SDG 14) and below water (SDG 15), the space to build meaningful links between climate change and biodiversity in policy and practice has expanded considerably (Olsen et al. 2019). As this space has expanded, the scope for clarifying which actions could yield benefits that help protect the climate and preserve biodiversity has also increased. The main purpose of this chapter is to not only shed light on the origins of the interest in biodiversity co-benefits but provide a simple, intuitive framework to identify the entry points for achieving those benefits. The article will also argue that a critical next step in motivating policymakers to work through these entry points is to strengthen the interface between action-oriented and analytical research. The former type of work often lacks rigorous assessment of different benefits; the latter often lacks practical applications of key findings. Analytically robust applications of research on biodiversity co-benefits are much needed to understand the limitations and potential of this concept. The hope is that this chapter will give rise to these robust applications by supporting greater integration not only between climate change and biodiversity but actions at different levels (Amanuma et al. 2018). The remainder of the chapter is divided into five sections. The next section concentrates on the origins of biodiversity co-benefits. Section 8.3 outlines the natural science, economic, and political reasons these benefits should be considered more actively. Section 8.4 describes some of the entry points for achieving these co-benefits; Sect. 8.5 reviews a representative subset of studies on biodiversity co-benefits. Section 8.6 concludes with a call for more integration within but also between levels of decision-making on biodiversity co-benefits.

8.2

The Origins of Biodiversity Co-benefits

As noted previously, both the UNFCCC and CBD were negotiated in 1992. For much of the next decade, the international climate and biodiversity processes progressed along parallel but gradually convergent tracks. Moreover, though the UNFCCC moved more quickly, the CBD would be the first process to highlight the links between climate change and biodiversity at the international level. The Fifth Conference of the Parties (COP5) to the CBD would establish the first connection between climate change and biodiversity in 2000. This connection was illustrated in a decision of COP5 that pointed to climate change as a key cause of coral reef bleaching. That decision further encouraged the UNFCCC to intensify actions to reduce the effect of climate change on water temperatures and curb the socioeconomic impacts of coral bleaching on affected countries and communities (CBD 2000). The subordinate organizations working within the CBD—notably the

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Subsidiary Body on Scientific, Technical and Technological Advice (SBSTTA)— would help advance efforts to curb these impacts by requesting more scientific advice be provided on these matters to the parties to the CBD. The Ad Hoc Technical Expert Group (AHTEG), which was set up and worked intermittently from 2002 to 2009, provided information on the interaction between climate change and biodiversity and on the means of integrating biodiversity conservation into climate change mitigation and adaptation measures to the UNFCCC (Secretariat of the Convention on Biological Diversity 2009). International climate processes would make the specific connection between a changing climate and biodiversity around the same period as the CBD. For example, in 2002, the Intergovernmental Panel on Climate Change (IPCC) published a technical paper that brought the link between climate change and biodiversity more sharply into focus. The paper underlined changes in terrestrial and marine ecosystems were often associated with climate change—for example, increasing the intensity and frequency of extreme climate-related events could disrupt ecosystems. It further cautioned about the adverse effects of climate mitigation in the forestry, land use, and energy sectors on biodiversity. The report finally suggested that actions that promote the conservation and sustainable use of biodiversity for reasons other than climate change could boost humanity’s capacity to adapt to climate change— effectively illuminating another climate-biodiversity link (IPCC 2002) (see Fig. 8.1). Another critical step involved the above IPCC report using familiar language to discuss the benefits resulting from working on climate change at the same time as biodiversity. At this juncture, the then commonly used term “ancillary benefits” (often used more frequently than co-benefits at the time) (Pearce 2000) began to appear in the context of potential impacts of agroforestry—that is, efforts to conserve biodiversity could protect long-term carbon sinks. The report would also underlined the additional benefits for climate adaptation from increasing

Fig. 8.1 History of international discussion on biodiversity and climate change (Source: Authors)

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biodiversity—namely, the protection and conservation of biodiversity could help retain a diverse gene pool, boosting the capacity to adapt in the future. On the other hand, actions for mitigation and/or adaptation of climate change, such as the soon-tobe-discussed Reducing Emissions from Deforestation and Forest Degradation (REDD+) initiatives, originally intended for climate change mitigation, have been expanded to include biodiversity conservation in forests and soil on the site or surrounding area. In these cases, this would yield biodiversity co-benefits generated from climate change measures. The IPCC report would also pick up on another theme that would gain prominence in discussions of co-benefits: there are potential synergies and trade-offs between climate change adaptation and mitigation actions and conserving and sustainably using biodiversity as well as other aspects of sustainable development (see Box 8.1) (Gitay et al. 2002). Box 8.1 Trade-Offs Between Climate Change and Biodiversity Co-benefits have been recognized as offering a win-win set of solutions to climate and biodiversity challenges. But not all actions are good for the climate and biodiversity. There may also be adverse or undesirable impacts of some climate actions on biodiversity or vice versa. For example, promoting afforestation (or converting natural forests to artificial forests) may capture carbon, but it could possibly reduce the number of tree species making up the forest and other native species, and adversely affect biodiversity. In a similar vein, large-scale deployment of bioenergy plantations and afforestation of non-forest ecosystems can have negative side effects for biodiversity and ecosystem functions. For instance, the large-scale deployment of intensive bioenergy plantations, including monocultures, replacing natural forests and subsistence farmlands, will likely have negative impacts on biodiversity and can threaten food and water security as well as local livelihoods, including by intensifying social conflict (IPBES 2017). As noted previously, one of the main reasons the discussion of biodiversity co-benefits began to gain traction in the climate processes was REDD+. At the 13th Conference of the Parties (COP13) to the UNFCCC held in Bali, Indonesia, in 2007, one of the key themes was how to reduce GHG emissions from deforestation and forest degradation (UNFCCC 2007). Reducing these emissions was critical because approximately 20% of the world’s GHG emissions in 2000 were due to deforestation and land use changes. The excessive logging of forests and land use conversion (often due to poor forest governance in developing countries) were chiefly responsible for these sizable contributions. As noted in the high-profile Stern Review (published the year prior to the IPCC report), preventing deforestation and forest degradation was more economical and efficient than trying to absorb CO2 by planting new trees and forests (Stern 2008). With the advent of REDD+, there would be even more convergence in the substance of the UNFCCC and CBD processes. For example, the decision at the

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CBD’s 12th Conference of the Parties in 2014 called for the recognition of the fact that biodiversity and ecosystems are vulnerable to climate change. The next year, the Conference of the Contracting Parties to the Ramsar Convention on Wetlands— focusing on the conservation of wetlands—COP12 underlined the role of wetland ecosystems in disaster risk management and the role of wetlands as a source of livelihoods that could increase resilience (Ramsar Convention 2015). The connection was arguably made even more concrete in the 2015 Paris Agreement that is now the key international climate agreement with reference to ecosystems in Article 5 and adaptation measures in Article 7 (UNFCCC 2015). Though both the CBD and UNFCCC processes began to uncover possible linkages between climate change and biodiversity, the 2030 Development Agenda and the SDGs may help accelerate convergence between these processes. This is partially because of the previously mentioned inclusion of separate SDGs focusing on both climate change and biodiversity. It is more important because of the recommendations to work across different goals and targets to achieve synergies and manage possible trade-offs. To encourage policymakers to do so on a regular basis, the first step is clarifying the importance of recognizing biodiversity co-benefits.

8.3

The Importance of Biodiversity Co-benefits

A key consideration for decision-makers is why selecting any of action is important. One reason accounting for the co-benefits highlighted in this chapter is critical are is there exist strong natural science links between climate and biodiversity. Another reason is that there is also economic and political motivations for acting on two sets of related concerns together. These reasons are elaborated upon below. As discussed previously, natural science is increasingly showing that climate change and biodiversity are closely related. According to the Millennium Ecosystem Assessment, climate change is likely to become one of the most significant drivers of biodiversity loss by the end of the century. Further, climate change is already forcing biodiverse environments to adapt through either shifting habitat, changing life cycles, or the development of new physical traits (World Resource Institute 2005). On the other hand, biodiversity can reduce the negative effects of climate change. Conserved or restored habitats can remove CO2 from the atmosphere, thus storing carbon. Conserving natural terrestrial, freshwater, and marine ecosystems and restoring degraded ecosystems (including their genetic and species diversity) are essential because ecosystems play a key role in the global carbon cycle and adapting to climate change. At the same time, these resources provide ecosystem services that help sustain humanity and development. A related reason involves a growing understanding of how biodiversity conservation affects climate change adaptation or maladaptation and disaster prevention (see Box 8.2).

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Box 8.2 The Possibilities of Maladaptation The conservation and sustainable use of biodiversity and ecosystem restoration play important roles in climate change mitigation and adaptation, desertification prevention, and disaster risk reduction. This is becoming more evident with the increasing frequency and intensity of extreme weather events caused by climate change. The importance of biodiversity and ecosystem services as a buffer to protect communities through ecosystem-based climate change adaptation measures (EbA) and natural disaster risk reduction (Eco-DDR) can enhance local resilience and adaptability through the sustainable management, conservation, and regeneration of ecosystems. This can also have desirable ripple effects on income generation and reductions in socioeconomic vulnerability, frequently improving human health and delivering other livelihood benefits in the process. The other side of the above advantages are growing concerns about “maladaptation” (IPCC 2014). Maladaptation comes in many forms. Across these different forms, a common theme is that action that may benefit a group at a particular time may become maladaptive over time in future climates to the same or other stakeholders. There is a growing emphasis on formulating adaptation to avoid or minimize the negative impacts on biodiversity (Ministry of Environment Japan 2016). Yet another reason for factoring in a full set of benefits involves economic and financial considerations. For many policymakers, the main objection to investing in climate change or biodiversity is high costs. This is particularly the case when those costs are compared to more immediate development priorities such as industrial development. However, a full accounting of all of the benefits of both climate change and biodiversity interventions may show that these often unaccounted benefits can outweigh the costs (ACP 2014; Uchida and Zusman 2008). In a related manner, understanding the benefits and costs may be helpful political reasons. For some politicians, investing in protecting an ecosystem or a rare species may seem like a poor use their time and resources. Other politicians may harbor similar sentiments about devoting resources to avoid or adapt to climate change. However, when these issues are paired together, the full portfolio of benefits may lead to changes in both the political and economic calculus. This is even more likely if the links can be established between actions that deliver biodiversity and climate benefits with additional social co-benefits (see Chap. 8 on social co-benefits).

8.4

Visualizing Biodiversity Co-benefits

Though there is a growing understanding of the need to recognize the multiple benefits of integrating climate and biodiversity, there were few efforts to clearly and systematically illustrate these connections. In consequence, it may be challenging for policymakers to craft interventions capable of delivering these benefits.

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Figure 8.1 can help illuminate possible linkages and inform potential interventions. As illustrated in Fig. 8.1, there are two potential categories of actions through which biodiversity co-benefits can be achieved: namely, climate change and biodiversity entry points. Some examples of these entry points are described below. If approaching biodiversity from the climate change side (from the bottom of Fig. 8.2), a few possibilities merit attention. One is the additional benefits could be achieved through mitigation actions in non-land use sectors—for example, a renewable energy project could protect rare species and fauna if explicitly designed with these conservationist ends in mind. Another entry point involves protecting forests and land from unsustainable logging and cultivation via REDD+. This presumes that efforts are made to safeguard against the introduction of invasive species. Finally, from a climate perspective, there are also efforts to build resilience or adapt to climate change that could have additional positive effects on marine or terrestrial ecosystems and the living creatures inhabiting them. This is the case, for instance, with efforts to protect coastal communities from intense storms that could also preserve seascapes and marine wildlife. The other possible approach to biodiversity co-benefits would be through biodiversity entry points. These include interventions that protect marine ecosystems that can simultaneously build resilience and facilitate adaptation to more intense storms and sea level rise. Another set of entry points involves preserving terrestrial ecosystems, which could deliver additional benefits for storing carbon. Finally and perhaps

Fig. 8.2 Illustration of biodiversity co-benefits (Source: Authors)

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most indirectly, actions targeting the protection of wildlife could also be useful for climate mitigation or adaptation; this will often require a careful effort to design, for example, a wildlife sanctuary in ways that use lower carbon energy sources or that help buffer against climate impacts. Though the above figure is useful for illustrating possible interventions, it should be borne in mind that there is no one universally appropriate perspective or set of entry points. The determination of which benefits to pursue through which interventions will be context-specific, depending on factors such as level of development, natural resource endowments, and stakeholder demands in the country or community in question. Furthermore, though there can be a tendency to view the work on co-benefits as privileging one main benefit over a secondary set of co-benefits, this chapter is not suggesting such a hierarchy; rather, it is offering a menu of possible linkages and interventions that can be made when working on actions that sit at the intersection of different approaches to addressing climate change and preserving biodiversity.

8.5

Research on Biodiversity Co-benefits

To maximize biodiversity co-benefits, there have been several studies that have worked from a climate and biodiversity entry point or employed a more balanced synergies-trade-offs view. This section provides non-exhaustive review of several of these studies. The review will illustrate that, though research is making a stronger case for taking actions to achieve biodiversity co-benefits, room exists to strengthen the interface between more analytical and action-oriented research.

8.5.1

The Biodiversity Entry Point

As for the biodiversity entry point, identifying where and how biodiversity benefits overlap with climate benefits has helped understand the dynamic interplay between both sets of concerns. Several researchers have tried to quantify the impacts of carbon sequestration on biodiversity conservation; others are more oriented to spurring actions on the ground. One such study looked at the biodiversity co-benefits of sustainable forest management in Sabah, Malaysia. To understand the conditions that can help deliver these benefits, the research estimated the diversity of medium- to large-bodied forest-dwelling vertebrates using a heat-sensor camera trapping system. It also examined the amount of above-ground, fine-roots, and soil organic carbon through ground surveys and aerial imagery. These techniques were employed in both sustainable and conventionally logged production forests to see if the differences in management strategies and techniques had implications for biodiversity. The study found that the varieties of vertebrate species and amount of carbon sequestered

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were very similar in pristine forests with little or no logging and those with 3–8 years of low-impact logging: this latter point helped demonstrate sustainably harvesting forests did not require an absolute prohibition on logging but a carefully considered sense of moderation (Imai et al. 2009). Another study sought to strengthen the interface of climate change and ecosystem science by identifying points of convergence between biodiversity protection, carbon storage, and the economic viability of conservation measures in one of the world’s most endemic-rich and threatened ecosystems: the western Andes of Colombia. Toward this end, it performed in situ carbon assessments generating secondary forest and cattle pastures, combining these with biodiversity surveys of birds and dung beetles and then economic analyses to examine whether carbon-based payment for ecosystem services (PES) can provide cost-effective conservation benefits. The results from this work revealed that naturally regenerating secondary forests accumulate significant carbon stocks within 30 years and support biodiverse communities, including protecting many species at risk of extinction. Given that land used for cattle farming, the principal land use in the region, provides minimal economic returns to local communities, policies and measures that promote forest regeneration can deliver both local benefits and provide globally significant carbon and biodiversity co-benefits at minimal cost (Gilroy et al. 2014).

8.5.2

Climate Change Entry Point

In contrast to research that starts with biodiversity, there have also been studies that take climate change as a point of departure. This section reviews a representative sample of these studies. One such example from that subset revolves around co-benefits from sequestering carbon in forests. Research on this issue began by investigating the prospective environmental benefit from forest carbon sequestration—improvements in water and air quality—in Wisconsin (United States). The study estimated the reductions in agricultural externalities (soil erosion, nitrogen, and atrazine pollution) as well as additional benefits from an afforestation program; this was done by using a fieldlevel modeling to approximate the reductions in nitrate and atrazine pollution (surface water pollution typically from agricultural run-off) and soil erosion resulting from a forest carbon sequestration policy. Existing benefit estimates were used to quantify the value of reduced soil erosion and some benefits from enhanced wildlife habitat. The study concluded that the full range of often substantial benefits and costs should be accounted for in the development of climate policies (Plantinga and Wu 2003). Another line of work that starts from climate change and then moves to biodiversity focuses on REDD+ in its entirety. In this case, there has been discussion of the optimal approach to bring additional benefits for biodiversity into a mechanism intended to preserve carbon sinks. An example of research illustrating this approach outlined five options that could theoretically help capture the added

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benefits for biodiversity from forest-based climate change mitigation. The proposed options ranged from structuring REDD+ so that the benefits of biodiversity would be promoted but without a financial incentive to the creation of two separate mechanisms concentrating on biodiversity and forest conservation. By clarifying the strengths and limitations of these approaches, the study concludes that those working on REDD+ need greater clarity on its advantages and drawbacks to build a consensus around its management and implementation. As stakeholders advocating for biodiversity conservation engage more with those working on REDD+, clearly demonstrating the benefits from a variety of options can help relevant stakeholders understand the implications of policy and institutional changes (Phelps et al. 2012). Other studies have sought to examine how the admittedly vague language in the REDD safeguards calling for the “consideration of biodiversity conservation” could be operationalized in Borneo, Indonesia, and Peninsular Malaysia. The study in question considered the positive impacts on biodiversity of forest monitoring methods using an aircraft-mounted laser system to assess forest degradation from commercial logging. The study found that the density and species composition of small mammal populations (rodents and tupai) varied based on the distance from logging roads. These mammal populations were important because they spread seeds and turn over the soil in a manner that can help regenerate the tree canopy. These findings indicate that good forest management practices, such as limiting the density of skid trails and logging roads, can prevent forest degradation, limit CO2 emissions, and are consistent with the letter and spirit of the REDD+ safeguards (Okuda 2003) (Box 8.3). Box 8.3 REDD+ Safeguards From its inception, the architects of REDD+ recognized the mechanism should do no harm to the environment or people. To make good on that commitment, in 2010 at the UNFCCC COP 16, negotiators agreed on a set of seven safeguards. Of the seven, safeguard 5 is most relevant to biodiversity: That REDD+ actions are consistent with the conservation of natural forests and biological diversity, ensuring that the actions referred to in paragraph 70 of this decision are not used for the conversion of natural forests, but are instead used to incentivize the protection and conservation of natural forests and their ecosystem services, and to enhance other social and environmental benefits. . . . (REDD+SES 2012) In addition to safeguards, there have been notable efforts to deliver additional benefits beyond a stable climate. For example, since 2005, the Climate, Community & Biodiversity (CCB) Standards has provided a set of systematic and objective criteria to identify and promote land management projects that effectively address social and environmental risks and deliver significant benefits for the climate, local communities, and biodiversity. This is pursued through an impact assessment and monitoring in the CCB Standards (CCBA 2014).

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143

A Synergies and Trade-Offs Framework

A third set of studies does not offer a single perspective or entry point but rather employs an arguably more balanced framework for considering climate change and biodiversity synergies and trade-offs. In one such study, the starting point is how sharply increasing global demand for biomass for energy and materials can affect climate change and biodiversity. More concretely, the study explored the impacts on climate change and biodiversity from harvesting forests for forest plantations in Norway. For these purposes, the researchers employed integrated assessments of climate and biodiversity impacts using ecoregion-specific characterization factors (CFs) to quantify short- and longterm transformational impacts of land use on biodiversity loss for mammals, birds, amphibians, reptiles, and plants at the regional and global levels. It also analyzed climate and biodiversity impacts over a very-short- (GWP20 and land occupation), medium- (GWP100 and land core transformation) and long-term (GTP100 and land transformation after 100 years) time frames. In general, the study found that biodiversity loss and climate change delivered the most significant impacts shortly after logging; however, there was also variation in the nature of impacts for the removal of specific tree species over different time horizons. This variation underlined the need for “spatially and temporally explicit analyses [of] life-cycle impacts from landderived products, and [integrating] multiple and complementary indicators for climate change and biodiversity impacts into a common framework to better inform decisions. . .” (Iordan et al. 2018). Another set of studies that employs this synergy and trade-offs framework involves EbA to help local communities adapt to the adverse impacts of climate change. Governments and international donors have increasingly embraced this approach as part of climate change adaptation initiatives. For instance, an EbA project entitled “Ecosystem-based Adaptation through South-South Cooperation,” funded by the Global Environmental Facility (GEF) and implemented by the United Nations Environment Programme (UNEP) and China that ran from 2013 to 2019, aimed to enhance the climate resilience of communities in the dryland of Mauritania, Himalayan forests in Nepal, and the coastal zone of the Seychelles. It sought to investigate these matters by building institutional capacity, mobilizing knowledge, and transferring EbA technologies based on China’s experience. During implementation, the project encountered challenges related to local land use conflicts, national changes in governments, and regional extreme climatic conditions. An important lesson from the project was EbA often touches off complex socioeconomic dynamics that require considerable investments of time, highly skilled management, and deft decision-making. Another lesson was that donors may need to adopt a longer-term management and funding perspective due to not only project complexity but the long lifetimes of trees and forests (Mills et al. 2020). The final study reviewed on this theme examines why carbon and biodiversity conservation are not easily interlinked. The study aimed to highlight difficulties of making these linkages by explaining the fundamental ecological differences between carbon and biodiversity. Toward that end, it highlighted that scientific findings on

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taxonomic, phylogenetic, genetic, and functional aspects demonstrate that biodiversity is inherently non-substitutable. For those reasons, there exists ecological differences between biodiversity and carbon, and the measures implemented for the best management of biodiversity on a landscape will often differ from those for storing carbon on a landscape. Therefore, the study advocated “decoupling approach” rather than seeking co-benefit (coupling) approach. This acknowledges the major spatial and temporal trade-offs between activities for biodiversity conservation and for carbon conservation and also suggests that a decoupled approach leads may lead to projects that perform better than similar coupled projects (Potts et al. 2013).

8.6

Conclusion: Advancing Biodiversity Co-benefits at Multiple Levels

This chapter has provided an overview of the origins of the interest in biodiversity co-benefits, noting that increases in this interest are often associated with milestones in key international processes. It then underlined both the scientific and economic and political rationale for recognizing these co-benefits in decision-making processes. It followed the discussion of these different rationales with an easy-to-follow illustration of some of the main entry points for achieving these co-benefits while also underlining the growing need to adopt a synergies and trade-offs framework. It finally concluded with a representative sample of studies that work from different entry points or employ the synergies-trade-offs perspective. The description of these studies underlines that there is growing sophistication in the methods used to analyze different kinds of biodiversity co-benefits just as there is a sharply escalating need for applying this research to practical problems. This final section recommends how the gaps between more analytical and applied research can be narrowed at different levels. At the local and community level, one way to help close these gaps would be to equip communities with the tools and resources to fully understand the benefits of preserving the climate and protecting the climate themselves. Disseminating such tools has the potential to lower the costs of data collection. It also can help empower communities to identify their own context-appropriate solutions to climate and biodiversity problems. Finally, it can lead to stronger connections between biodiversity, climate change, and numerous social concerns (i.e., stable residence, liveable wages, and access to essential goods and services). At the national level, a useful bridge would be to make a concerted effort to integrate climate change concerns into biodiversity policies while also integrating biodiversity concerns into climate policies. The obvious choice for this integration is the Nationally Determined Contributions (NDCs) that countries have pledged to the UNFCCC following the Paris Agreement. The climate change process and the NDCs may be the highest profile process and policies, but it is not the only area

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where such integration could be helpful. An additional area that is likely to have significant impacts involves the COVID-19 stimulus packages. In the wake of the COVID-19 pandemic, many governments are recognizing the need to focus more on biodiversity. Stimulus packages that direct resources to research on biodiversity or climate change can be structured to look at policy designs that address both biodiversity and climate change. At the international level, a possible connection involves the global processes that began this chapter: namely, the UNFCCC and CBD. The expanding amount of research on the linkages between climate and biodiversity suggest a need for considerably strengthening the integration between these two processes. This could involve, for example, greater efforts to have sessions on biodiversity at the UNFCCC and climate change at the CBD. Other forward strides could be made by reporting on policy integration—especially the NDCs under the Paris Agreement. Meanwhile, the use of community-based assessment tools and data collection could also feed into both the UNFCCC and CBD processes. As this last example implies, there is a need for not simply integration between climate change and biodiversity but between the local, national, and global levels on these issues. Both forms of integration—horizontal and vertical—will be crucial for advancing action of biodiversity co-benefits. This leads to a final point meriting attention: namely, how to integrate research on governance at different levels with research on biodiversity co-benefits (Betsill and Bulkeley 2006; Bulkeley and Betsill 2005). There is significant amount of work on multi-level governance that could be used to inform work on biodiversity co-benefits. This could involve, for example, bringing in insights from work on governance into technical modelling and monitoring studies or using the technical modelling and monitoring studies to enrich understandings of what forms of governance work best in which contexts.

References ACP (2014). Asian co-benefits partnership white paper 2014 bringing development and climate together in Asia. Hayama, Japan Amanuma N, Zusman E, Lee S-Y, PJD G, Mitra BK, Pham N-B, Nakano R, Nugroho SB, Chiu B, Agatep PM, Romero J (2018) In: Zusman E, Amanuma N (eds) Governance for integrated solutions to sustainable development and climate change: from linking issues to aligning interests, Hayama, IGES Betsill MM, Bulkeley H (2006) Cities and the multilevel governance of global climate change. Glob Gov 12:141–159 Bulkeley H, Betsill M (2005) Rethinking sustainable cities: multilevel governance and the ‘urban ’ politics of climate change. Environ Polit 14(1):42–63 CBD (2000) Progress report on the implementation of the programme of work on marine and coastal biological diversity (implementation of decision IV/5) CCBA (2014) CCB Standard. Retrieved from https://www.climate-standards.org/ccb-standards/ Gilroy JJ, Woodcock P, Edwards FA, Wheeler C, Baptiste BLG, Medina Uribe CA, Haugaasen T, Edwards DP (2014) Cheap carbon and biodiversity co-benefits from forest regeneration in a hotspot of endemism. Nat Clim Chang 4(6):503–507. https://doi.org/10.1038/nclimate2200

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Gitay H, Suarez A, Watson RT, Dokken DJ (2002) Climate change and biodiversity. Geneva, Switzerland Imai N, Samejima H, Langner A, Ong RC, Kita S, Titin J, AYC C, Lagan P, Lee YF, Kitayama K (2009) Co-benefits of sustainable forest management in biodiversity conservation and carbon sequestration. PLoS One 4(12). https://doi.org/10.1371/journal.pone.0008267 Iordan CM, Verones F, Cherubini F (2018) Integrating impacts on climate change and biodiversity from forest harvest in Norway. Ecol Indic 89(April 2017):411–421. https://doi.org/10.1016/j. ecolind.2018.02.034 IPBES (2017) Land degradation and restoration. Retrieved from https://ipbes.net/assessmentreports/ldr IPCC (2002) Technical Paper V. Retrieved from https://archive.ipcc.ch/pdf/technical-papers/ climate-changes-biodiversity-en.pdf IPCC (2014) Climate change 2014: impacts, adaptation, and vulnerability. Retrieved from https:// www.ipcc.ch/site/assets/uploads/2018/02/WGIIAR5-Chap14_FINAL.pdf Mills AJ, Tan D, Manji AK, Vijitpan T, Henriette E, Murugaiyan P, Pantha RH, Lafdal MY, Soule A, Cazzetta S, Bégat P, KEP V, Lavirotte L, Kok JT, Lister J (2020) Ecosystem-based adaptation to climate change: Lessons learned from a pioneering project spanning Mauritania, Nepal, the Seychelles, and China. Plants People Planet 00(May):1–11. https://doi.org/10.1002/ ppp3.10126 Ministry of Environment Japan (2016) Basic concept of climate change adaptation on biodiversity adaptation in Japan. Retrieved from https://www.env.go.jp/nature/biodic/kikou_tekiou-pamph/ adaptation_en.pdf Okuda T (2003) Research on experimental studies for upgrading the REDD mechanism in ways that incorporate ecosystem services and values. pp. 6–8. https://doi.org/10.16309/j.cnki.issn.10071776.2003.03.004 Olsen SH, Zusman E, Steele R, Marsden E, Virtucio MA (2019) Strengthening the environmental dimensions of the sustainable development goals in Asia and the Pacific: Stocktake of national responses to sustainable development goals 12, 14, and 15. Manila Pearce D (2000) Policy frameworks for the ancillary benefits of climate policies Phelps J, Webb EL, Adams WM (2012) Biodiversity co-benefits of policies to reduce forest-carbon emissions. Nat Clim Chang 2(7):497–503. https://doi.org/10.1038/nclimate1462 Plantinga AJ, Wu JJ (2003) Co-benefits from carbon sequestration in forests: evaluating reductions in agricultural externalities from an afforestation policy in Wisconsin. Land Econ 79(1):74–85. https://doi.org/10.2307/3147106 Potts MD, Kelley LC, Doll HM (2013) Maximizing biodiversity co-benefits under REDD+: a decoupled approach. Retrieved from https://iopscience.iop.org/article/10.1088/1748-9326/8/2/ 024019 Ramsar Convention (2015) COP12 Resolution. Retrieved from https://www.ramsar.org/sites/ default/files/documents/library/cop12_res13_drr_e_0.pdf REDD+SES (2012) Standards to support the design and implementation of government-led REDD + programs that respect the rights of Indigenous Peoples and local communities and generate significant social and environmental benefits. REDD + Social & Environmental Standards. (September). Retrieved from http://www.redd-standards.org/standards/redd-social-and-environ mental-standards-version-2/5-redd-ses-version-2-english/file Secretariat of the Convention on Biological Diversity (2009) Connecting biodiversity and climate change mitigation and adaptation. Montreal Stern N (2008) Key elements of a global deal on climate change Uchida T, Zusman E (2008) Reconciling local sustainable development benefits and global greenhouse gas mitigation in Asia: research trends and needs. Reg Policy Res 11(1):57–73

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Chapter 9

Creating Social Co-benefits for Sustainable and Just Society So-Young Lee

9.1

Introduction

We live in an age of extremes. Significant disasters, including the recent COVID19 pandemic, have changed the way we understand risk and vulnerability. The heatwaves we experience each year brings temperatures that continue to break records; what makes the situation worse is that extreme weather and unprecedented risk is predicted to become more intense and frequent with climate change. These growing risks threaten human life and public health. Even more worrying is that those most adversely affected by these risks tend to be vulnerable groups of people, i.e., elderly or workers in low-income jobs. Not surprisingly, this situation tends to be most grave in less developed countries where there is generally a greater dependence on local natural resources. Since the 2030 Agenda for Sustainable Development and Paris Agreement were adopted in 2015, there has been more interest into the interrelationship between climate change mitigation and the livelihoods of the underprivileged. There have been, in fact, a growing number of quantitative studies and policies that were intended to avoid negative environmental impacts or decouple economic and environmental problems; but the examination of the social and environmental interactions in these studies and policies remains rather limited. As both Sustainable Development Goals (SDGs) under the 2030 Agenda on Sustainable Development and Nationally Determined Contributions (NDCs) under the Paris Agreement place a greater emphasis on the interrelationship between climate change and social goals, the achievement of not just co-benefits but social co-benefits is a matter of timely and urgent concern.

S.-Y. Lee (*) Institute for Global Environmental Strategies (IGES), Hayama, Japan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 H. Farzaneh et al. (eds.), Aligning Climate Change and Sustainable Development Policies in Asia, https://doi.org/10.1007/978-981-16-0135-4_9

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The growing body of research and policy guidelines on the topic of climate and social justice could offer useful insights into how to incorporate social co-benefits into the design and implementation of relevant plans and policies. Much of this research starts with the underlying assumption that climate change (and many other environmental crises) can unfortunately widen social inequities. The fact that disadvantaged segments of society tend to experience the most serious climate change impacts is evidence of the strong correlation between environmental problems and social injustice and these impacts tend to be—especially great on the livelihoods of the underprivileged (Hejnowicz et al. 2015; Tagg and Jafry 2018). This is particularly unfair because studies show that those who did not make significant contributions to climate change suffer the most from its adverse effects (Bulkeley et al. 2013; Chatterton et al. 2013; Derman 2014). The concept of social co-benefits include benefits ranging from green jobs to greater equity between social groups and genders. While much of the co-benefits literature emphasizes the importance of quantifying different types of benefits, there are many issues involved in the implementation of social co-benefit initiatives that go beyond a quantitative analysis; more projects and policies would deliver social co-benefits from sharing lessons learned from existing cases. There are good practices of achieving social co-benefits on the ground that already exist in several cities in Asia. This chapter therefore reviews cases involving social co-benefits followed by a brief analysis of the term's origin. Then, the chapter will argue the active engagement from citizens and stakeholders is a useful means of implementation to achieve social co-benefits. The importance of the improved participation in both decision-making process and practice cannot be overemphasized when social co-benefits are considered. In conclusion, the chapter will argue for a multi-level multi-benefit governance approach complemented by active citizen participation is needed for a sustainable and just society.

9.2

Social Co-benefits in Climate Negotiations

The linkages between climate change and sustainable development trace back more than two decades to a period when international climate change negotiations focused on concerns beyond reductions in greenhouse gas (GHG) emissions. The key milestone during this period was the agreement over the United Nations Framework on Climate Change (UNFCCC). The UNFCCC was itself negotiated during the United Nations Conference on Environment and Development (the first Rio meeting) that also marked the official international endorsement of the concept of sustainable development. Since 1992, there have been decisions under the UNFCCC (2008) that underlined the need to ensure development proceeds in a sustainable manner with the recognition and prioritization of social issues (Decision2/CP.13). In addition to decisions under the UNFCCC, there have been several other attempts to strengthen the link between climate change and other development priorities. The most notable was the Clean Development Mechanism (CDM) that

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operated as part of the Kyoto Protocol: one of the main goals of the CDM was to promote sustainable development in host countries (UNFCCC 1997). In a similar vein but outside the formal auspices of the UNFCCC, the climate finance mechanism with arguably the greatest potential to promote sustainable development is the Gold Standard. The Gold Standard is a certification scheme through which forwardlooking project proponents can demonstrate and verify that credits from a climate change project contribute more broadly to sustainable development. Environmentally and socially responsible investors can purchase credits from the goal standard at a premium reflecting the Gold Standard certification. The announcement of the SDGs to achieve the 2030 Agenda for Sustainable Development marks a potentially important turning point in the history of sustainable development as these goals and targets are supposed to be implemented in an integrated manner (Open Working Group on SDGs 2014; UN General Assembly 2015). Following the agreement over the SDGs, the Gold Standard for the Global Goals (an updated version of the aforementioned Gold Standard) has been introduced to offer an approach to more systemtically link climate finance with the SDGs (Pickering et al. 2017). The co-benefit research that the Asian Development Bank (ADB) (2017) conducted provides a quantitative analysis of a wide range of social co-benefits, including created jobs, improved education for children, empowered women, and more. The ADB conducted this analysis on 36 CDM projects under the Future Carbon Fund portfolio using a CDM Sustainable Development Tool as well as Gold Standard Sustainable Development Tool and Social Carbon Standard tool. The results of those analyses are presented in Box 9.1. Box 9.1 Delivered Key Co-benefits for Sustainable Development (Source: ADB 2017, p. 17) • Capacity addition of 1200 MW resulting in approximately 2.89 million MWh of renewable energy generation per annum. • Improved air quality for about 1.31 million people. • More than 14,000 additional jobs in the region. • About 1.39 million people benefitted by improved energy efficiency measures and services. • 8.74 million people potentially gain access to stable and reliable energy in the region. • Improved education facilities for more than 8500 children. • Reduced traffic congestion and upgraded urban transport services for 300,000 daily commuters. • Approximately 39,400 people gained access to health services. • More than 5000 women empowered through sustainable livelihoods. The international climate finance mechanism with arguably the greatest potential to promote co-benefits is the Green Climate Fund (GCF). The GCF places an emphasis on environmental, economic, and social co-benefits, and suggests

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recognizing these benefits are important to ensure that funded activities adhere to sustainable development criteria. The proposal template for GCF Funding requires a clear narrative that outlines potential co-benefits beyond mitigating GHGs in more concrete terms—for example, project proponents can highlight social co-benefits that cover improvement in health and safety, access to education, cultural preservation and improved access to energy, social inclusion, improved quality of public utilities, and so forth. For the main investment criteria, the sustainable development potential requires social co-benefits and also places a premium on gender-sensitive development impact in line with the gender strategy of the GCF (GCF 2015). In addition to the GCF, some countries are considering social co-benefits in their national climate policies. The inclusion of these benefits in those policies is increasing as more countries aim to achieve the SDGs. Although the questions of how social co-benefits should be factored into different mechanisms and policies still should be discussed, the consideration of whether to include social co-benefits or not would is no longer a question. Rather consideration of these benefits is a requested component for the most of the investment projects and programs from international donors and development agencies.

9.3

Implementation of Social Co-benefit Initiatives

As mentioned in the introductory chapter of this book, when defining co-benefits, the Intergovernmental Panel on Climate Change (IPCC) underlines the need “to capture dimensions of the response to mitigation policies from the equity and sustainability perspectives” (IPCC 2001, p. 51). Moreover, the ADB suggests that co-benefits are “the additional positive social, environmental, and economic benefits attributed to climate mitigation projects above and beyond the main benefit of expected GHG reduction” (ADB 2017, p. 4). The co-benefits achieved from the HOB in school project in Chap. 4 were the result of technology changes that led to an approximately 50–70% improvements in boiler efficiency as well as reductions in dust concentration, nitrogen oxide (NOx), sulfur dioxide (SO2) emissions and particulate matter (PM) emissions. Furthermore, the most important benefits beyond the technology improvements to the boilers were the cleaner working condition and better environment for students—that is, social co-benefits covered by the concept from IPCC and ADB. The IPCC also noes that the socioeconomic dimension needs to be “case- and site-specific” as its impacts “depend on local circumstances and the scale, scope, and pace of implementation” (IPCC 2014, p. 17). It is therefore a complex task to conduct a social assessment of co-benefits when the local conditions and implementation contexts vary (Ürge-Vorsatz et al. 2014). In this case, it would be useful to investigate good practice cases of the implementation of activities that deliver social co-benefits in Asia. The lessons learned from the existing cases could encourage more projects and policies deliver these potential benefits. The following section will share a few examples with a focus on social co-benefits from, for example, an effective public transportation for low-income citizens and the elderly; a small-

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scale energy creation and transition with the involvement of women and local people; and the active participation of citizens for a low-carbon society.

9.3.1

Inclusive Ridership for Low-Income and Elderly Citizens

The transport sector in Asia has faced a long list of negative externalities from worsening congestion to increasing GHG emissions. Metropolitan Manila is the densely populated political economic center of the Philippines, and transport in Manila is essential to the country’s development. However, the rapid pace of urbanization and motorization has left Manila with heavy traffic and extended commutes, and the development of the transport sector has contributed to GHG emissions, accounting for more than a third of national energy-related emissions. The National Climate Change Action Plan for 2011–2028 supports an integrated transport master plan that covers non-motorised transport (NMT), including bicycle sharing to reduce the quantity of vehicles. A bicycle sharing system is a program in which users rent and return a bicycle over a publicly available network. Most of the benefits of bicycle sharing systems come from shifting motorized short-distance trips to NMT. The Transport Emissions Evaluation Model for Projects (TEEMP) can help calculate the co-benefits of a bicycle sharing system. The TEEMP estimated these benefits based on a scenario where 2000 bicycles were prepared for the first year of the trial in 2012 and that number was expanded to 20,000 over 5 years in Manila. The results of the analysis showed that the bicycle sharing system “could potentially result in 10,828.6 tCO2 of abated CO2—translating to roughly 196.9 kgCO2/bicycle/year” (ACP 2016, p. 31). As a result, the bicycle sharing becomes a viable NMT approach to deliver co-benefits. The co-benefits generated from the bicycle sharing systems, however, extend beyond emission reductions. The most obvious benefit of the bicycle sharing systems is the cost-effectiveness as the systems service; with a modest cost, many commuters can use the system to increase their mobility over large areas. The bicycle sharing systems also encourages further employment opportunities through the maintenance of the facilities and the manufacture of hardware as well as the operational systems including call centers. Aside from the improvement of mobility and job creation, the systems provide a long-term benefit in terms of healthier lifestyle through the physical activity on a bicycle and better air quality that could reduce healthcare costs and increase productivity. Some of the more important benefits listed above are social in nature. For instance, the bicycle sharing system provides better accessibility and connectivity to public transportation, especially for low-income individuals in the Manila metropolitan area. This is particularly important for those who significantly rely on the bicycle sharing without purchasing their own transporting equipment. By placing the bicycle stations close to public transportation facilities, bicycle sharing can also serve

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as a feeder for and encourage the use of public transport. Finally, the users of the system can shift short-distance trips that might otherwise be serviced by personal vehicles to cycling (ACP 2016). Unlike the Manila case, Toyama in Japan has faced the issue of decreasing population and aging society in the early 2000s. These demographic changes resulted in a hollowing out of the city center. Therefore, Toyama set up a Compact City Development in 2002, and the policy under this development emphasized the importance of integrating the three dimensions of sustainable development. In other words, it emphasized not only economic growth but also social and environmental development. Many of the interventions that aimed to achieve these objectives were evident in local transport policies, and these policies proved successful in delivering multiple benefits. For instance, they helped reduce CO2 through the public transport system such as light rail transit (LRT) and city tram loop line and set the 30% reduction of CO2 by 2030 compared to 2010 (even while the residential population in the city increased). Toyama became famous due in part to the recognition that its LRT delivered a wide range of benefits, especially for the increased mobility of elderly citizens (ACP 2016). Along with the LRT infrastructure, the additional improvement for the elderly included low carriage floors as well as wheelchair accessibility to the stations. Moreover, a preferential fare for elderly was set, and the frequency of trains was increased to accomodate more riders. As a result of these changes, the ridership of the new LRT doubled on weekdays and increased by 3.5 times on weekends, and the number of elderly passengers increased sharply after the LRT operation started (Toyama City 2014). This improved the public transport system and created social co-benefits for the elderly; it also revitalized economic activities in the city center and mitigated CO2. By integrating the three dimensions of sustainable development, both Manila and Toyama created value in the social and economic as well as environmental dimensions. The approaches used in these cities suggests the potential of local transport policies to go beyond emission reductions and create social co-benefits. The approaches also illustrate concrete examples of solutions that deliver outcomes that are conistent with the letter and spirit of the 2030 Agenda on Sustainable Development and the Paris Agreement.

9.3.2

Energy Creation with Women and Locals

It was mentioned earlier that the GCF emphasizes social co-benefits and promotes a gender-responsive approach from the project proposal all the way through to project implementation. The reason that the GCF highlights gender is the adverse effects of climate change fall more heavily on women, especially in low-income countries. Women tend to suffer more from these effect due to long-running inequalities and dependencies on natural resources. Further, many women rely heavily on local resources for their livelihoods, for example, they are responsible for cultivating

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food and collecting water and fuel for cooking that are affected by climate change (UN WomenWatch 2008, 2009; Terry 2009; Figueiredo and Perkins 2013; Alston 2015). What is worse is that it is often poor women and their children who suffer the most from household air pollution during the cooking and heating processes (World Health Organization (WHO) 2014; Cameron et al. 2016; Lee and Zusman 2019). Rather than being a passive victim of climate change and other environmental challenges, the ADB supported a multi-country project that aimed to show how women could mitigate climate change and narrow gender gaps. One of the pilots for this larger project was located in Dong Hoi, a coastal city in Vietnam. The Dong Hoi pilot project demonstrated women have potential to become change agents by contributing to sustainable development and climate mitigation. More concretely, the project focused on engaging women in the biogas supply chain, and equipping them with the technical, construction, business, and marketing skills needed to create bio-digester supply business so they could reap economic benefits while mitigating climate change. The existing data of the Vietnam National Biogas Programme indicated that during the last decade, there were over 1700 masons who had received training but the number of female trainers was less than 0.2% (ACP 2016a; Lee and Zusman 2019). Hence, the pilot project initiated trainings in cooperation with the Dong Hoi Women’s Union and created an opportunity for the National Biogas Programme to bring in women producers and users of biogas technologies. As a result, eight Biogas Mason Enterprises were established, and seven of them were women-led. Beyond providing better incomes for the female employees in both assistant and leadership roles, the enterprises worked to build 300 new digesters in Dong Hoi that reduced about 1579 tons CO2eq annually. In addition, the project also made it possible to use bio-slurry for organic fertilizer and replaces the use of chemical fertilizer that contributes to GHG emissions (ACP 2016a; Lee and Zusman 2019). During the trainings and implementations of the pilot project, women increased their understanding of opportunities to earn climate finance, and they become actively involved in promoting social co-benefits between social issues of gender equality, poverty reduction and climate change mitigation. A similar social co-benefit was delivered through the implementation of an advanced cookstove pilot project in Lao PDR that was also part of this larger multi-country ADB project. In this pilot, an innovative approach was taken to empower a segment of the population that is frequently left out of the employment market, namely, disabled women (ACP 2016b). When a co-benefit approach focuses on climate change mitigation, women and local communities (where women often live and work) are often overlooked. This is partially because co-benefits from mitigation differ from co-benefits from adaptation. Adaptation projects such as mangrove restoration, sustainable water management, and soil conservation management tend to consider social impacts on vulnerable groups and engage affected communities because they are often viewed as the victims of the climate crisis. However, a co-benefit approach that focuses on mitigation may downplay these social impacts and pay less attention to those suffering from climate change. This does not suggest that these social issues should be excluded from mitigation activities. On the contrary, because mitigation often aims to empower people and

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communities, there is a need to highlight gender sensitivity and support local involvement in mitigation activities. These even more important as women often have no access to the kinds of political and representative channels required to articulate their needs. This, in turn, leads to the absence of women's voices in decision-making process as well as a lack of adequate information sharing. As suggested by the Dong Hoi case, when women and local peoples’ active participation in decisions is guaranteed, they can become change agents who are capable of delivering multiple benefits. Their full engagement or leadership therefore should be promoted in all stages of the decision-making processes— from the planning, implementation, and evaluation of projects and plans. This full engagement would also have the added benefits of generating locally relevant solutions (Fischer 2000; Newig 2007; Derman 2014). To help strengthen the active participation of women and other marginalized groups, social networks among communities and regions could serve as platforms that link with established players to engage in mutually beneficial learning process that spread successful solutions to climate and other problems (Khan 2013; Frantzeskaki et al. 2014). The next case expands the scope of inclusivity beyond gender and local people, and introduces how to achieve social co-benefits through participatory governance with multiple stakeholders. The case shows how to develop and implement an innovative co-benefit project by citizens and for citizens.

9.3.3

Low-Carbon City Through Participatory Governance

Seoul is the densely populated and technologically advanced capital city of the Republic of Korea. Because of its large population and high level of development, Seoul consumes a significant amount of Korea’s energy, i.e., by 2015, Seoul’s energy consumption accounted for more than 10% of the total amount of Korea. When adding current consumption levels to future demands, Seoul is likely to reach the level of energy needs that is equivalent to what one nuclear power plant generates in a year (Seoul Metropolitan Government 2015; ACP 2018). In 2011, the then newly elected Seoul mayor aimed to implement an innovative environmental policy and energy saving plan along with the full and active participation from citizens. That participation involved setting up several channels that allowed for far more two-way mutual communication between government and residents in Seoul than happened in the past. One of the important examples of where there was considerable participation was the One Less Nuclear Power Plant project. That project had the ambitious goal of saving two million tons of oil equivalent (TOE) of energy consumption (equals to the capacity of one nuclear power plant), by 2014. The project was motivated by a desire to reflect the demands from citizens who sought safe and sustainable energy to avoid a crisis comparble to the Fukushima disaster in Japan. The project covered various initiatives that encouraged citizens’ involvement and engagement, including the creation of energy self-sufficient villages, dissemination of solarphotovoltaic (PV) power plants for the individual households or cooperative-sharing power plants, car-sharing systems, and many more small-scale innovations.

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The main role of the Seoul government in this project was supporting diverse initiatives through the amendment of relevant ordinances, the assistance of the implementing team as well as the encouragement of private sector investment in technologies (such as PV). The Seoul government also aimed to facilitate citizens’ voluntary participation in the installation of small-scale generators in their household. As a result, PV facilities with a total capacity of 101 MW were installed in 10,069 public facilities, schools, commercial buildings, and individual homes as of 2015 (ACP 2018). The One Less Nuclear Power Plant project was successful as it achieved its goal 6 months ahead of schedule. One of the essential elements that contributed to this outstanding result is the active participation of various groups of citizens in the project's implementation. Active participation here implies not only the participation of individual citizens but also the cooperation between the private sector and civil society that led to the speedy deployment of small-scale PV installation across apartment blocks (that also increased energy self-sufficiency in the city). Further, the efforts to create new more participatory forms of governance arrangement built around the aforementioned continuous two-way dialogue between government and citizens helped to make the project even more sucessful. This dialogue helped build networks and collaborative partnerships that grew in size and supported the scaling of innovative approaches to conserving energy. Up until the Comprehensive Plan for One Less Nuclear Power was finalized by citizens in 2012, there were 16 meetings among the Seoul government, civil society, and advisory group of experts as well as several open town hall meetings that contributed to the draft review and created forum to collect inputs from the public. The success in the generation of multiple benefits through the participatory governance in the One Less Nuclear Power Plant project led to Phase 2 of the project with extended activities. The Phase 2 set a new task that further considered the social dimension of sustainable development such as supporting energy-poor households by establishing energy-sharing communities. It also set out a more ambitious goal to reduce energy equivalent to the capacity of two nuclear power plants or ten million tons of GHG emissions (ACP 2018). In terms of the decisionmaking processes, the Phase 2 repeatedly conducted multi-stakeholder meetings and discussions; moreover, it set up a committee to ensure elements of the project were socially inclusive, especially for the energy-poor households who received insufficient support during the Phase 1. These additional aspects for the Phase 2 demonstrate the potential for exponential gains from the mutually reinforcing relationship between environmental and social co-benefits.

9.4

Conclusion: Multi-level Multi-benefits

A possible limitation of the projects and programs described above is their sustainability. As most of the initiatives are funded by a specific project fund or ad hoc governmental financial support, one might ask whether these efforts continue after that support ends. To be truly transformational, a critical step forward is securing

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investment from local governments and communities in their own social co-benefit climate change initiatives. While concerns over whether this step is taken are justified, an important lesson learned from the cases reviewed in this chapter is that the participation, inclusion and stakeholder engagement in the planning and implementation of integrated solutions to climate change and sustainable development can bring long-lasting results (Chiu et al. 2018; Lee and Zusman 2019). The key to making these programs and policies sustainable is to take advantage of recent trends in international climate negotiations as well as the cases already mentioned above: that is, multi-level multi-benefit climate governance approach that also supports the active participation of citizens. A good practice example of multiple stakeholder governance at multiple levels can be found in the ADB gender project. The bio-digester pilot in Dong Hoi was successful in part because it offered clearly visible evidence of how women can mitigate climate change while earning other livelihood, economic, and social benefits. At the higher levels of government, then, officials could clearly see the benefits of the pilot and started considering policies to provide finance and other enabling reforms to support, replicate, and scale up that gender-responsive mitigation project. Besides this Dong Hoi biogas initiative, the project in Lao PDR on advanced cookstoves worked with the Ministry of Natural Resources and Environment, the principal government agency responsible for climate change-related issues, and with the Lao Women’s Union, the key women’s organization in the country. It also aimed to enhance both agencies understand the importance of gender-responsive approaches to climate change mitigation. After over 3 years of continuous dialogue, eventually the Ministry of Natural Resources and Environment invited the representative from the Lao Women’s Union to join the inter-ministerial climate change coordinating group. This, in turn, led to the inclusion of gender in the National Climate Change Action Plan. This case, then, also highlights the importance of working with multiple stakeholders at multiple levels to achieve multiple benefits (Lee and Zusman 2019). A similar inference can be drawn from the bicycle sharing program in Manila. That program required the coordination of the multiple departments and agencies such as transport and communications, land use and planning, infrastructure, finance, health, and statistics because the streets needed to be shared by various public transport modes. Further, sucessful implementation not only necessitated coordination within the Manila City administration but the collaboration and engagement among different local government units and constituents under the Manila metropolitan area. This case again suggests effective multi-stakeholder engagement could help support the redesign of a transport system to accommodate demands of commuters as well as deliver benefits of different segments of society. The case also fits well with trends in global climate policy that encourage countries to think carefully about how innovative projects such as bicycle sharing fit within wider policies and institutional reforms. The ultimate goal of most efforts to achieve social co-benefits is to provide benefits to the community, local people, and society rather than to limit benefits for specific sectors or stakeholders. In other words, achieving social co-benefits must be based on multidimensional and multidisciplinary approach as the vulnerability of

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local people, communities, and regions varies across locations as well as sociodemographic groups. Hence, solutions also should be varied, rather than one-fits-all, across different places; furthermore, it is crucial that those solutions are bottom-up and engage the community that is affected. The Communique of the G7 Summit held in 2018 reaffirms that participating countries hold a strong commitment to implement the Paris Agreement through reducing emissions while strengthening and financing resilience and reducing vulnerability as well as ensuring a just transition. The multi-level, multi-benefit approach outlined in this section of the chapter applies this same logic when considering a just transition: government strategies should be designed to create coalitions between energy sector workers, labor unions, ecological and social movement activists, and local communities. In the context of the transformational change needed to meet the Paris Agreement and achieve the SDGs, no one is left behind through engaging all affected stakeholders in a dialogue to identify pathways to a sustainable future. Hence, policymakers need to connect their policymaking to local contexts, and this is best done by including those communities and citizens in policy making processes, especially from the marginalized groups who are affected the most by the outcomes of those processes. Achieving co-benefits through participatory governance, that is, when other voices are heard and reflected into the decisionmaking as well as the implementation process, can deliver long-lasting success for the environmentally sustainable and socially just future.

References ACP (2016a) ‘New roles for women in the biogas supply chain in Vietnam’. ACP Good Practice Map. ACP, Hayama. Available at https://www.cobenefit.org/good_practice/detail/pdf/ACP_ vietnam-bio.livelihood.pdf ACP (2016b) ‘Gender integration in the supply of improved cookstoves in Lao PDR’. ACP Good Practice Map. ACP, Hayama. Available at https://www.cobenefit.org/good_practice/detail/pdf/ ACP_lao-ics.livelihood.pdf ACP (2018) ‘Achieving social and environmental co-benefits through participatory governance in Seoul, Korea: The case of one less nuclear power plant’. ACP Good Practice Map. ACP, Hayama. Available at https://cobenefit.org/good_practice/detail/pdf/ACP_korea_seoul_ 180213.pdf Alston M (2015) Women and climate change in Bangladesh. In: ASAA women in Asia series. Routledge, London Asian Co-benefits Partnership (ACP) (2016) Asian co-benefits partnership white paper 2016 putting co-benefits into practice: case studies from Asia. Hayama: Japan. Available at https://cobenefit. org/publications/white_papers.html Asian Development Bank (ADB) (2017) Future carbon fund: delivering co-benefits for sustainable development. ADB, Manila Bulkeley H, Carmin J, Broto VC, Edwards GAS, Fuller S (2013) Climate justice and global cities: Mapping the emerging discourses. Glob Environ Chang 23:914–925 Cameron C, Pachauri S, Rao ND, McCollum D, Rogelj J, Riahi K (2016) Policy trade-offs between climate mitigation and clean cook-stove access in South Asia. Nate Energy 1. International Institute for Applied Systems Analysis (IIASA), Laxenburg

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Chatterton P, Featherstone D, Routledge P (2013) Articulating climate justice in Copenhagen: antagonism, the commons, and solidarity. Antipode 45(3):602–620 Chiu B, Zusman E, Lee S (2018) Ch 2: The co-benefits of integrated solutions in Asia: an analysis of governance challenges and enablers. In: Zusman E, Amanuma N (eds) Governance for integrated solutions to sustainable development and climate change. IGES, Hayama Derman BB (2014) Climate governance, justice, and transnational civil society. Clim Pol 14 (1):23–41 Figueiredo P, Perkins PE (2013) Women and water management in times of climate change: participatory and inclusive processes. J Clean Prod 60:188–194 Fischer F (2000) Citizens, experts and the environment: the politics of local knowledge. Duke University Press, London Frantzeskaki N, Wittmayer J, Loorbach D (2014) ‘The role of partnerships in ‘realising’ urban sustainability in Rotterdam’s City Ports Area, The Netherlands’. J Clean Prod 65:406–417 Green Climate Fund (GCF) (2015) GCF Concept Note Template. Available at http://www. greenclimate.fund/documents/20182/46529/4.4_-_Concept_Note_Template.docx/f671be96bc20-4f0b-a716-02e36bc44a10 Hejnowicz AP, Kennedy H, Rudd MA, Huxham MR (2015) Harnessing the climate mitigation, conservation and poverty alleviation potential of seagrasses: prospects for developing blue carbon initiatives and payment for ecosystem service programmes. Front Mar Sci 2(32):1–22 Intergovernmental Panel on Climate Change (IPCC) (2001) In: Metz B et al (eds) Third assessment report climate change 2001 mitigation. Cambridge University Press, Cambridge IPCC (2014) In: Edenhofer O et al (eds) Climate change 2014 mitigation of climate change: working group III contribution to the fifth assessment report of the IPCC. Cambridge University Press, Cambridge Khan J (2013) What role for network governance in urban low carbon transitions? J Clean Prod 50:133–139 Lee S, Zusman E (2019) Ch. 29 Participatory climate governance in Southeast Asia: lessons learned from gender-responsive climate mitigation. In: Jafry T (ed) Routledge handbook of climate justice. Routledge, London Newig J (2007) Does public participation in environmental decision lead to improved environmental quality? Towards an analytical framework. Res Pract Sustain Future 1:51–71 Open Working Group on SDGs (2014) Open Working Group proposal for SDGs. Available at https://sustainabledevelopment.un.org/content/documents/1579SDGs%20Proposal.pdf Pickering A, Arnold B, Dentz H, Colford J, Null C (2017) Climate and health co-benefits in low-income Countries. Environ Health Perspect 125(3):278–283 Seoul Metropolitan Government (2015) Seoul’s exemplary environment policies: pleasant, healthy and sustainable city, Seoul. SMG, Seoul Tagg N, Jafry T (2018) Engaging young children with climate change and climate justice. Res All 2 (1):34–42 Terry G (2009) No climate justice without gender justice: an overview of the issue. Gend Dev 17 (1):5–18 Toyama City (2014) Compact city based on public transport [Kokyo kotu wo jiku to shita konpakuto na machidukuri] (in Japanese), in: The Fifth EST Transport and Environment Award. 4–15 UN Framework on Climate Change (UNFCCC) (1997) Kyoto Protocol. Available at http://unfccc. int/resource/docs/convkp/kpeng.pdf UN General Assembly (2015) Transforming our world: the 2030 Agenda for Sustainable Development. Session 17. Agenda items 15 and 116 UN WomenWatch (2008) ‘Gender perspectives on climate change’, 52nd session of the Commission on the Status of Women. Available at http://www.un.org/womenwatch/daw/csw/csw52/ issuespapers/Gender%20and%20climate%20change%20paper%20final.pdf

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Chapter 10

Enabling Japan’s Low Emissions Technology Collaboration with Southeast Asia: The Role of Co-innovation and Co-benefits Nandakumar Janardhanan, Ngoc-Bao Pham, Kohei Hibino, and Junko Akagi

10.1

Introduction

The widespread adoption of low emissions technologies in rapidly developing countries is critical to resolving the climate emergency.1 However, many fastgrowing economies lack the energy efficient, renewable, and other advanced technologies needed to mitigate climate change. Technology transfer could help address these countries need. Yet the “affordability,” “adaptability,” and a host of other “market concerns” present significant barriers to low emissions technology transfer (Janardhanan 2020). To a considerable extent, these barriers arise from overly linear perspectives on technology transfer. These perspectives envisage technology hardware as moving one way from developed supplier countries to developing recipient countries. While this linear view arguably oversimplifies a complex reality, it suggests several sticking points frustrating the transfer of technology: namely, much of the discussion around the technology transfer process and its outcomes pay insufficient attention to the potential of benefits of new technologies in developing countries. This chapter places that process and its potentially beneficial outcomes front and center. It argues that the key to unlocking the potential of technology transfer is to work toward a co-innovation process. In this process, both developed and developing country stakeholders collaborate in a joint effort to tailor the technology to local

1

This paper builds on the arguments on the previous researches conducted on co-innovation, one on India-Japan collaboration (Janardhanan et al. 2020) and other on India-Japan-China context (Janardhanan 2020). Several sections from the previous research papers have been used in this paper.

N. Janardhanan (*) · N.-B. Pham · K. Hibino · J. Akagi Institute for Global Environmental Strategies (IGES), Hayama, Japan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 H. Farzaneh et al. (eds.), Aligning Climate Change and Sustainable Development Policies in Asia, https://doi.org/10.1007/978-981-16-0135-4_10

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implementing contexts at reasonable costs. Further, throughout this process, a deliberate effort is made to recognize the climate as well as the domestic environmental, social, and economic co-benefits resulting from co-innovation. By making the process more collaborative and recognizing a wider range of benefits, developing country stakeholders are likely to have a greater interest in pursuing the transfer of low emissions technologies. The reframing of this process and its desired outcomes could ultimately make all participants better off and help the world achieve 1.5
temperature targets ín the Paris Agreement and the Sustainable Development Goals (SDGs) (UNESCAP 2018). The remainder of this chapter focuses on demonstrating the above argument. The next section describes some of the barriers to technology transfer; it also details how dynamic interactions between co-innovation and co-benefits can help overcome some of the more significant hurdles. A third section then presents case studies from Japan to countries in Southeast Asia to illustrate the potential of a co-innovative process focused on achieving co-benefits to move past these barriers. The final section concludes.

10.2

Co-innovation and Co-benefits

If technology transfer was easy and straightforward, a critical piece of the climate change mitigation puzzle would already be in place. However, more than three decades of experience have demonstrated that this is not the case. Unfortunately, that experience has shown that there are many—sometimes interlocking—barriers to the smooth transfer of advanced technologies from developing to developed countries. These barriers begin with adapting a technology to the relevant implementing context. Adapting to a new technology by the consumers and its wider acceptability as well as lack of capacity to operate and maintenance are significant concerns in a host country. How the consumers perceive a new technology and to what extent these technologies persuade users about the technology reliability, etc. can play a determining role in its uptake and use. Affordability of imported technologies has been a critical challenge to technology transfer, despite the importance these technologies have in the recipient country. As there is a lack of advanced technology to meet the growing domestic needs, developing country customers end up paying a premium to access the technology supplied by source countries. These challenges are augmented by concerns that imported technology will adversely affect the recipient country’s domestic industries, pushing the domestic manufacturers out of the market or turning them into mere suppliers and resellers. On certain occasions, overseas players are seen as adversely affecting the growth of domestic industries as the former’s more efficient technologies systematically overtake the latter in competitive markets.

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Co-innovation emerges as the possible alternative to conventional technology transfer in these contexts, where it is able to capitalize on the recipient country’s advantages in terms of cheap labor and systematically integrate into the local market by promoting mutual learning about the opportunities and challenges. Additionally, as co-innovation also encourages local players to step into the ideation to production to marketing stages, this could also benefit the local economy. Often the question that arises is about the need for co-innovation when stakeholders can depend on conventional markets to sell advanced technology equipment or market-based approaches toward technology transfer. However, multiple limitations of these approaches slow the flow of technology from one country to another, reinforcing the need for a model based on co-innovation. First, in conventional technology transfer, the source country with the technological know-how can often fail to understand the demand conditions as well as various factors such as cost sensitivities, climatic conditions under which the equipment needs to operate, design needs of the consumers, etc. in a specific market. Second, the recipient country partner will have adequate knowledge of these demand conditions, consumer expectations, and policy mechanisms as well as legal requirements related to technology development. Third, the collaboration of the recipient and source country in jointly pooling resources and fine-tuning the innovation is likely to lead to a better outcome than a finished product or equipment imported from an overseas arena. Fourth, co-innovation typically brings benefits in the form of technological expertise to the source country as well as local knowledge of the recipient country.

10.2.1 Defining and Operationalizing Co-innovation The definition of co-innovation used in this chapter is “a collaborative and iterative approach by two or more partners for jointly innovating, manufacturing and scaling up technologies” (Janardhanan et al. 2020). In this chapter, co-innovation is discussed in the context of Japan’s collaboration with Southeast Asian countries. This is also seen as “the shared work of generating innovative and exceptional design conducted by various actors from firms, customers, and collaborating partners” (Saragih and Tan 2018). Co-creation and co-development are discussed widely in industry circles as two or more stakeholders coming together to develop equipment or better technology. However, these models have several limitations in terms of recognizing the innovative inputs given by various actors and stakeholders outside the product development arena. On the other hand, co-innovation, while highlighting the contributions of various actors and stakeholders involved in the innovation stage, also reflects the dynamic role of the actors in shaping the product or equipment with innovative inputs in a continuous process. Co-innovation also entails the continuous exchange of knowledge among all the stakeholders, including scientists, manufacturers, and the end-users of technology, with the aim of improving the product. It thereby

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captures the efforts of all the stakeholders in comparison to the co-creation and co-development frameworks, which places greater emphasis on the creation and development stages than the innovation stage. It is also believed that while “codevelopment or co-creation is [an] economic model based on maximising the returns on design investments through product sales, co-innovation aims to generate knowledge and incorporate for continuous technology improvement, to remain competitive in markets that are constantly being redefined. Hence, co-innovation brings in profound changes in the industrial world’s operating rules” (Maniak and Midler 2008). In addition, Mainik and Milder point out that “while co-development usually involves a smaller group of partners, co-innovation [entails] cooperation of a wider set of partners outside the traditional channels.” The below framework (Fig. 10.1) explains the phases of co-innovation as well as the role of each partner and the associated benefits to each stakeholder. In order to explain the process better, the chapter divides the framework into three main phases: collaboration, co-innovation, and outcomes. The first phase of the process includes both (or more than two) partners identifying the need and benefits of cooperation. In the case of the source country and recipient country, there exists a mutual agreement to enter into a collaborative initiative. During this phase, the partners may be able to identify their purpose for collaboration, benefits, and the required inputs in terms of soft skills and hard skills for designing a joint venture. One of the most critical elements here is the efforts of the stakeholders in planning the financial resources or entering into agreements for securing adequate monetary means for the collaborative initiative. This phase also provides an opportunity for the partners to agree on legal matters that are necessary to carry forward the required collaborative work. In cases where both parties decide to institutionalize their collaboration, whereby their respective soft skills and hard skills need a common platform for fine-tuning, the stakeholders can consider the possibility of collaborative laboratories or technology collaboration laboratories (co-labs) (Fig. 10.1). The next phase plays a central role in the overall process. This phase consists of several key steps in the co-innovation process. In this phase, the first step is co-design and co-development. This step consists of ideation, conceptualization, and developing a product design based on a mutual agreement among participating stakeholders. Translating a concept into the designing of particular machinery or equipment requires significant joint efforts. The next key step involves co-production or co-manufacturing, which broadly consists of industrial-level joint production of machinery or equipment by participating stakeholders. The third step in the co-innovation phase is co-monitoring and evaluation; these are critical processes that include preliminary field testing and operational product revision until a final product is agreed upon for the co-monitoring activities. This step also can involve processes ranging from product testing to marketing and sales at a commercial scale. The last phase in the process consists of co-learning and scaling up, which involves product revision based on market knowledge, capacity building, as well as further transfering the product to other potential markets. While there are four possible phases, it is an important point to note is that co-innovation does not necessarily go through all the specified steps—rather,

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Fig. 10.1 Co-innovation framework (Source: Authors)

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Table 10.1 Comparison of business-as-usual vs. co-innovation scenarios Category 1. Discretion 2. Research and development 3. Supply 4. Product specifications 5. Funding 6. Human resource 7. Pricing

Business-as-usual Based in source country or entity By source partner

Co-innovation Locally led Joint R&D

Import basis Specifications originally made for the source partner Product is largely developed by source partner funding Dispatch of managers and experts from Japan Expensive and uncompetitive

Local production Localized Co-financing Local human resource development Competitive

Source: Authors

co-innovation can be initiated from any stage depending on the agreement between the collaborators (Table 10.1). The comparison of co-innovation with the traditional technology transfer approach presented in the table above underlines the differences between both approaches across seven key areas. This is specifically discussed in the context of Japan’s partnership with other countries. This explanation is aimed at providing a detailed understanding on how co-innovation can be distinguished from other approaches to technology transfer.

10.2.2 The Role of Co-benefits in Co-innovation The chapter highlights the social, environmental, and economic co-benefits of broader environmental as well as climate mitigation and related initiatives. These include a wide range of socio-economic advantages, as well as environmental benefits from introducing a technology. While the main intended objective of introducing a technology is often economic, highlighting its social or environmental co-benefits helps decision-makers recognize its additional value. The recognition of co-benefits opens up a “window of opportunity” for additional policy goals to be achieved (Mayrhofer and Gupta 2016). The recognition of these benefits can also help allay concerns over GHG mitigation costs. As demonstrated in Fig. 10.2, different types of co-benefits can be expected from different stages of the co-innovation process. For example, during the earlier co-design phases, there are significant skill and knowledge acquisition benefits that accrue to collaborating stakeholders. The co-production and manufacturing begins to deliver the economic as well as some social (jobs created) and environmental benefits. The co-monitoring helps to demonstrate these benefits while again also building knowledge and skills. Last but not least, the scaling of the technology leads to the spread and multiplication of all of the benefits. As demonstrated in

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Fig. 10.2 The dynamic relationship between co-benefits in co-innovation (Source: Authors)

Fig. 10.2, the recognition and delivery of these benefits can also feedback into and enhance the co-innovation process. The case studies that follow, then, highlight the dynamic between co-innovation and co-benefits.

10.2.3 Early Examples of Co-innovation Co-innovation is not an entirely new approach in commercial interactions between multiple stakeholders. In the history of India’s engagement with Japan, one of the most fruitful examples of co-innovation is the collaboration between Japan’s Suzuki Motors and India’s Maruti Suzuki Automobile Limited (Janardhanan et al. 2020). Though not formally called co-innovation, it exemplifies some of the crucial steps of co-innovation. Suzuki Motors and Maruti Suzuki formed Maruti Suzuki Automobile Limited in the late 1980s as a public limited company with the support of the Indian government. This company has also been an active platform for Suzuki Motors to jointly experiment with several of their new technologies that fit the Indian consumer and the road conditions. The technologies developed as part of the joint venture of Maruti Suzuki helped introduce advanced energy efficient technologies in the passenger vehicle transportation segment, yielding co-benefits in the form of efficient mobility and reduced emissions. Today, Maruti Suzuki is one of the most accepted motor vehicle companies in India. It also has one of the largest shares of passenger vehicles in India. In order to systematically analyze cases of co-innovation, the categories in Table 10.2 are used to examine to what extent the case studies fully or partially match the key elements of co-innovation as well as the co-benefits the case

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Table 10.2 Methodology and outcome Collaboration entry stage

Extent of collaboration

Co-design and co-development Co-production/comanufacturing Co-monitoring and evaluation Co-learning and scaling up

The collaboration among the stakeholders can begin at any stage ranging from co-design to co-learning and scaling up

Expected project outcome

This is the expected outcome that includes monetary, environmental, and social benefits of co-innovation activity

Achieved outcome Source Recipient partner partner Achieved Achieved outcome outcome for the for the source recipient partner partner

Co-benefits Areas of co-benefits for both the partners. This includes advantages including socioeconomic and environmental benefits of the collaboration

Source: Authors

generated. Table 10.2 can help identify and establish the main design features of an institutional framework for co-innovation (Table 10.2).

10.3

Japan’s Technology Transfer to Southeast Asia and Opportunities for Co-innovation

The Southeast Asian region offers many examples of technology collaboration with Japan given its geographical vicinity and historical relationships. The amount of Japan-based projects that have been transferred to Southeast Asia have been nearly 1.5 times larger than that of China, $367 billion to $255 billion, and are expected to mobilize another $3 billion between 2020 and 2022, nearly half of which would come from the Japan International Cooperation Agency (Glosserman 2020). The COVID-19 pandemic also stimulated discussions within Japan to shift its investments from China to Southeast Asia (Kyodo 2020; Bloomberg 2020). The long history of cooperation makes it possible to analyze whether there have been cases that match with the co-innovation framework and, if so, how these can be replicated at scale to overcome barriers to technology collaboration (Table 10.3). In the remainder of the chapter, we examine three cases, one each from Vietnam, Cambodia, and Indonesia.

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Table 10.3 Case studies of co-innovation Country Indonesia

Sector Waste

Key stakeholders Surabaya City and Kitakyushu City (Technical inputs by Dr. Koji Takakura et al.)

Vietnam

Energy

DAWACO, Institute for Global Environmental Strategies, the City of Yokohama and Ebara Vietnam Pump Company Limited

Cambodia

Water

Phnom Penh Water Supply Authority (PPWSA), Kitakyushu City and JICA

Details Takakura Composting Method (TCM) is a simple composting method that was developed in Surabaya City of Indonesia as a tool to promote municipal solid waste management. It started from Surabaya City calling for assistance to Kitakyushu City Energy collaboration in Da Nang City in Vietnam. DAWACO has decided to work with the Institute for Global Environmental Strategy (IGES) and the City of Yokohama to use a different approach to solve the problems Phnom Penh Water Supply Authority (PPWSA) installed a water distribution block system in Phnom Penh under the support of JICA and Kitakyushu City government, Japan

Co-benefits Contributing to emission reduction

Improved energy efficiency, emission reduction

Contributing to emission reduction

Source: Authors

10.3.1 Case Study: Takakura Composting Method Takakura Composting Method (TCM) is a simple composting method that was developed in Surabaya City of Indonesia as a tool to promote municipal solid waste management. It started to gain widespread application when Surabaya City requested assistance from Kitakyushu City, its long time collaborating partner, to improve their waste management practices in 2001 when the Keputih landfill was shut down and waste had accumulated across the city. Kitakyushu City sent a team of experts through the Kitakyushu International Techno-Cooperative Association (KITA) in 2004 using the Japan Fund for Global Environment (JFGE). The mission team conducted a study and developed a locally suited composting method in collaboration with the local non-governmental organization (NGO) (Pusdakota Surabaya) over the 3-year project term. It proactively adopted locally available materials (e.g., rice husks, rice bran, etc.) and local fermentation foods as the starter of compost, suggesting that TCM can be adapted to any climatic and cultural conditions all over the world. It is simple and easy, cheap, and effective— the required time for fermentation is just about 2 weeks compared to 3–4 months typically associated with the conventional static-windrow composting method.

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The method was subsequently named after the inventor, Koji Takakura (under the original company J-POWER Group JPec Co., Ltd.). The TCM was initially applied to the municipal composting center, but the scope was subsequently expanded to a home composting tool, known as the Takakura Composting Basket. The advantage of TCM is that all the materials for home composting can be purchased in local markets for less than USD 10 per unit. So the technology transfer has been only in a form of knowledge, while all necessary hardware can be locally procured and modified depending on the local needs and context (Akagi et al. 2018; Maeda 2009).

10.3.1.1

Takakura Technology: Opportunities for Collaboration

The unique part of this technology transfer is that it started based on the existing cityto-city collaboration relationship between Surabaya City and Kitakyushu City. This collaboration framework allowed smooth cross-sector collaboration and involved a wide range of stakeholders. The relationship between these two cities started back in 1997, and the scope of collaboration has been steadily expanding from human resource development to waste to water to energy to public health over the past 20 years. Through various successes and the strengthening of mutual trust, the two cities concluded a green sister city agreement in 2014 (Akagi et al. 2018). The other notable success factor was the strong initiatives by the Surabaya City government which functioned synergistically with the TCM project. The city initiated a “Green and Clean Campaign” from 2005 to promote waste reduction and recycling, including training and appointment of environment cadres in each community, effective utilization of existing social networks (e.g., women’s association), promotion of waste banks (communal junk shop), and city-wide competition on green and clean communities. Surabaya City also took the initiative to promote TCM by replicating composting centers and distributing composting baskets freely to communities. Through these concerted efforts, the amount of waste disposal to landfill decreased from 1500 tonnes/day in 2005 to 1000 tonne/day in 2009, a 30% decrease in five years which was a significant achievement (Maeda 2009).

10.3.1.2

Identifying Co-innovation

The TCM was based on the traditional knowledge of aerobic composting methods, and the innovation part was the optimized use of local fermentation food and other locally available materials. The original idea behind this technology emerged from Takakura’s experiences and knowledge. Hence, it cannot be called a joint technology development. However, the later development and fine-tuning of the technology was through collaboration with the local NGO and extensive feedback from the communities and local governments. In that sense, it would be fair to say that co-design and co-development took place to some extent. Arguably the most noteworthy success factor was the co-innovation of social system that enabled

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Table 10.4 Methodology and outcome: Takakura Composting Extent of collaboration

Entry stage

Co-design and co-development

Co-production/ comanufacturing Co-monitoring and evaluation Co-learning and scaling up

Co-developed with local NGO and feedback from the communities Not relevant

Not relevant Method improved through co-learning; scaling up occurred in Surabaya and other cities

Expected project outcome

Contribute to waste reduction and recycling in the city of Surabaya

Achieved outcome Source Recipient partner partner • The suc• 30% reduccessful tion of waste development in 5 years of an appro• Contribpriate uted to the composting success of method the Green • The and Clean increased Campaign opportunity • Enhanced of getting cleaning and funding for greening of replication to the city other cities/ • Reduction countries of spending in municipal solid waste management • Improved awareness and education • Created job opportunities

Co-benefits • GHG emission reduction by reduced transportation and CH4 emissions from landfills

Source: Authors

dramatic waste reduction. The initiatives of Surabaya City was instrumental but would not have been so successful without TCM that addressed the organic waste issue. On the other hand, TCM could not have been so successful without a social supporting system that Surabaya City developed as part of the Green and Clean Campaign. Both aspects complemented each other and worked synergistically and thus were indispensable to the success of the project (Hennida 2013; UCLG 2011) (Table 10.4).

10.3.1.3

Potential Opportunity for Scaling Up

Surabaya City has replicated the municipal composting centers using TCM (capacity: 1–2 tonne/day waste input) throughout the city. Initially, it started from one composting center at Pusdakota in 2004. The number increased up to 25 in 2015 (Surabaya city government 2015). A much larger-scale composting center (capacity: 20 tonne/day waste input) was developed with the assistance of JICA in Surabaya

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City in 2014. This facility was designed, constructed, and operated by Nishihara Corporation, a waste management operator based in Kitakyushu City. This project was also based on the city-to-city collaboration between the two cities (Akagi et al. 2018). In Hai Phong City in Vietnam, another sister city partner of Kitakyushu City, Takakura helped the local environment company (URENCO Hai Phong) to optimize the existing composting center by using TCM. This was further scaled up to 70 tonne/day waste input and potentially can be scaled up up to 200 tonnes/day waste input (Nuzir et al. 2019; URENCO Hai Phong 2019). From the success in Surabaya City, TCM became famous in Indonesia, and especially the home compost basket has been gradually replicated in other cities. Through the network of Kitakyushu City and also JICA’s composting training course that Dr. Takakura has been in charge of since 2005, TCM has been disseminated to many developing countries, particularly in Southeast Asia (Maeda 2009) and South America (Takakura 2020).

10.3.1.4

Key Challenges and Lessons Learned

Despite the popularity of TCM, not all projects following the success in Surabaya City have been successful. One reason could be that the methodology was not accurately interpreted without proper instruction from Dr. Takakura. Another possible reason was the lack of a social supporting system which was available in Surabaya (Takakura 2016a, b). The key lessons learned from this case study are threefold. First, technology alone cannot solve social issues, and there needs to be a social system that matches well with the appropriate technology. Second, an adequate institutional environment is critical for co-innovation to happen. Third, co-innovation can have larger impacts if it provides an innovative solution to challenging and often systemic social and environmental issues” (Stanford Graduate School of Business 2019).

10.3.2 Co-innovation for Addressing Water Security Challenges in Da Nang City of Vietnam Da Nang is the sixth most populated city in Vietnam, with an area of about 1255 km2 and a population of 1,141,100 people at the end of 2019 (GSO 2019). The city is located in the middle of Central Vietnam, between Hanoi and Ho Chi Minh City. Over the last decade, Da Nang has turned itself into a rapidly growing hub for transportation, services, and tourism. It has also becoming a fast moving center for real estate and private property development. Investment into the city also comes from tourism, with an estimate of 8.7 million visitors in 2019 (GoV 2019), and this number is expected to continue increasing in the coming years. The growth in population and tourism has created a significant pressure on the city’s old water supply infrastructure. It is anticipated that by 2030 the total water demand of Da Nang will grow more than

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Table 10.5 Electricity consumption and costs for water production (2015–2017), before the technology transfer Year Amount of water production (m3) Electricity consumption for water production (kWh) Electricity costs for water production (billion VND)

2015 73,883,879 18,383,718 30,937

2016 81,172,695 21,372,577 36,418

2017 87,898,547 21,922,726 36,934

Source: Ninh 2019

twice the amount that can currently be supplied by the city’s water utility. Water demand for Da Nang City could even increase to fourfold within the next 10 years. Consequently, demand for energy consumption for water production will also significantly increase over the next decade, placing a significant risk on water security for the city in the near future. Actual energy demand for water supply increased from 18 GWh in 2015 to 21 GWh in 2017 (Ninh 2019) (Table 10.5). Water supply services in Da Nang City have been managed and operated by Da Nang Water Supply Company (hereinafter referred to as “DAWACO”), a water supply joint-stock company. DAWACO has been operating four water treatment plants (WTPs) throughout the city with a total design capacity of 210,000 m3/day, before the project started. One of the main water treatment plants is Cau Do WTP, with an initial design capacity of 170,000 m3/day. However, due to a high water demand from the city, most of the plants have to operate at a higher design capacity, thus total actual operating capacity of the plants ranging from 220,000 to 270,000 m3/day, as of 2017. Most of the city’s raw water and clean water pumps are quite old and operating with very low efficiency (only about 50% for raw water pumps and less than 64% for clean water pumps), and make a significant amount of noise due to a possible intrusion phenomenon. Again, this situation presents a huge potential risk to safe operations of the water pumps, consequently threatening the water security and water supply of Da Nang City itself. Understanding the difficulties of mobilizing the resources needed for a conventional supply-oriented approach to address these challenges, the top management board of DAWACO has decided to work with the Institute for Global Environmental Strategy (IGES) and the City of Yokohama to use an innovative approach to solve the problems. Through co-innovation, a joint team was established to facilitate the process of know-how and technology transfer at the DAWACO from Yokohama City to Da Nang City. As a result, three existing conventional raw water pumps and six existing clean water pumps that operated with low energy efficiency were replaced by Japanese higher energy efficiency water pumps using inverters (83% for intake pumps and 90.6% for clean water distribution pumps). These new water pumping systems have been customized through a co-design process (concept development) to address specific conditions and requirements of the recipient plants. Results after 1 year of operation of the new water pumping systems demonstrated remarkable progress. The project revealed that (1) maximum capacity of the pumps can be increased from 18,870,000 m3/year to 20,800,000 m3/year for intake pumps and from 84,000,000 to 101,620,000 m3/year for distribution pumps; (2) electricity

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Table 10.6 Co-innovation benefits: Performance parameters of the old and new transferred water pumps

Item Number of water pumps Energy efficiency

Flow rate of new water pumps since installation (dated 30/08/2017) until by the end of 2017 (m3) Electricity consumption in 2017 (kWh) Actual operating capacity in 2018 (m3/year) Total electricity consumption in 2018 (kWh) Actual operating capacity in 2019 (m3/year) Total electricity consumption in 2019 (kWh)

Cau do raw water pumping station Old raw water New raw pumps water pumps 3 3 50.5% (when 83% (when 2 pumps oper- 2 pumps ated in operated in parallel) parallel) 5,853,822

Cau do clean water pumping station (to distribution network) Old clean New clean water pumps water pumps 6 6 63.3% (when 90.6% (when 5 pumps oper- 5 pumps ated in operated in parallel) parallel) 21,621,208

503,429

3,935,060

263,422

21,913,338 1,884,547

75,228,480 992,335

21,744,450 1,870,023

3,113,454

13,691,583

10,898,844

74,229,098 1,078,354

13,509,696

11,069,711

Source: Based on the results of authors’ interviews and questionnaire surveys conducted with DAWACO (2019)

consumption will be reduced from 1730 MWh/year to 780 MWh/year for intake pumps and from 16,610 MWh/year to 14,050 MWh/year for distribution pumps; (3) electricity costs will be reduced from 2.93 billion VND/year to 1.33 billion VND/year for intake pumps and from 28.23 billion VND/year to 23.89 billion VND/year; and (4) cost saving amounts, thanks to reduced operating costs, for intake pumps will be 1.6 billion VND/year and 4.34 billion VND/year for distribution pumps (Ninh 2019). Meanwhile, the actual recorded data from the date of installation of the new water pumping system (30 August 2017) until the end of 2019 is presented in Table 10.6. Results from the actual operation and performance of the transferred technologies clearly show that: • Performance of both raw and clean water pumping systems have significantly improved, leading to increased water supply capacity to meet the city’s growing water demand. • Energy/electricity consumption for water production has been reduced considerably, contributing to lower business costs and indirectly reducing environmental load through the reduction of greenhouse gas (GHG) emissions. This will help contribute to the city’s goal of cutting GHG emissions and reducing the impact of climate change, a factor that greatly affects current raw water resources.

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Identifying Co-innovation

Yokohama City and Da Nang City have been working together to promote technical cooperation on infrastructure development and environmental measures through the city-to-city cooperation model. After expressing concerns about existing water challenges and the strong interest of Da Nang City in collaborating with Yokohama City to address these problems, a feasibility study was officially conducted in 2015 on installing new water pumping systems that would be transferred from Japan to DAWACO. Positive results from this feasibility study led to an agreement between the two cities to actually implement this technology transfer project and install high-energy efficiency water pumping systems. Yokohama Water Co., Ltd. successfully completed the process of replacing existing conventional water pumps with Japanese higher efficient ones in two water pump stations owned and operated by DAWACO in 2017. Introduced pumps using advance inverters have reduced power consumption and CO2 emissions while addressing other environmental problems. After the installation of the new water pumping systems, both cities continued working together to co-monitor the performance of new pumping systems; and consequently this has also created an opportunity to maintain a good relationship between both parties; and it is believed that it will lead to new business opportunities in the future (Table 10.7).

10.3.2.2

Co-innovation to Address the Water Security Challenges

As mentioned earlier, the joint project team has utilized the co-innovation approach, including co-design and development; co-production and manufacturing in Vietnam to reduce the costs, co-monitoring, and evaluation of the actual performance of the new installed pumping systems; and replication, scale up, and co-learning to ensure co-benefits for both parties across the co-innovation process.

Benefits from this Technology Transfer Project The results after 1 year of the installation of replacing pumps and operation by DAWACO have demonstrates the actual effectiveness of the project. The total electricity costs of operating pumps in 2018 have fallen about 5.77 billion VND/year; electricity consumption for water production has been reduced 3400 MWh/year, and the estimated payback period will be around 6 years (provided that there is no external financial support) (Ninh 2019). Energy saving achieved by replacing the pumps was estimated to contribute to reducing around 738 tCO2/year (IGES 2020). This project has also significantly contributed to improved water security, ensuring stable and sustainable water supply in Da Nang City. This also has positively contributed to the city’s relevant

Source: Authors

Co-learning and Scaling up

Co-production/ comanufacturing Co-monitoring and evaluation

Entry stage Co-design and co-development

DAWACO is now working together with Japanese partner to monitor and evaluate the operation and efficiency of the new water pumping systems. Monitoring data is stored in a SCADA system, and both sides can check and obtain data on a daily basis through the online system Method improved through co-learning; replication and scaling up are being implemented and observed in Ho Chi Minh and Hue City

Extent of collaboration Co-design and development of technical specifications for new water pumping systems together with local partner (DAWACO) Not relevant

Expected project outcome Contribute to improve energy efficiency of the old raw water and clean water pumping system. Meanwhile, it is also expected to increase the overall pumping capacity

Achieved outcome Source partner • Successful development of new water pumping system to meet the demand of local partner under local conditions • Increased opportunity of getting funding for replication to other cities (e.g., Ho Chi Minh, Hue)/countries • Having a better market presence in Vietnam • Shared carbon credit

Table 10.7 Methodology and outcome: DAWACO-Japan collaboration in Da Nang City, Vietnam Recipient partner • Significantly increased energy efficiency of the water pumping systems (3 raw water pumps and 6 clean water pumps) • Increased pumping capacity and enhanced energy saving • Improved stability and safe water supply, consequently improved water security • Reduction of greenhouse gas emission • Reduction of spending in operating costs of water supply system for the Da Nang City

Co-benefits • Improved energy efficiency of the water pumping systems; thus contribute to improved stability, safe water supply, and water security of Da Nang City • Contributed to the reduction of greenhouse gas emission

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Table 10.8 Co-innovation benefits in achieving relevant SDGs and its targets Performance parameters Increase efficiency of pumps Improvement of water supply capacity

Electricity saving from operation process GHG emission reduction Significantly reduction of operation costs

Results Efficiency of intake pump improved from 50.5% to 83% and for water distribution pump from 63.3% to 90.6% Increased capacity from 18.87 million m3/year to 20.8 million m3/year for intake pumps and from 84 million m3 to 101.62 million m3/year for distribution pumps Electricity consumption for water production was reduced around 3400 MWh/year Contributes to reducing emissions estimated at 738 tCO2/year (actual monitored data recorded in 2019) Total electricity costs of operating pumps in 2018 were reduced nearly 6 billion VND/year

Contributing to relevant SDGs SDG-6 and SDG-11 SDG-6 and SDG-11

SDG-7, SDG-11, SDG-12 SDG-13 and SDG-11 SDG-11

Source: Janardhanan 2020, IGES (2020), Ninh (2019)

targets under SDG 6 (water and sanitation), SDG 7 (ensure access to affordable, reliable, sustainable, and modern energy for all), SDG 11 (make cities and human settlements inclusive, safe, resilient, and sustainable), SDG-12 (sustainable consumption and production), and SDG 13 (combating climate change and its impacts) (Table 10.8).

10.3.2.3

Potential Opportunities for Scaling Up

Following the great success of this project, a similar process has been employed in an effort to replicate and scale up this model in other cities in Vietnam, including Hue and Ho Chi Minh City. Da Nang project’s success also helped to accelerate the decision-making process in other cities. For example, Yokohama Water Company has also successfully transferred advanced Japanese inverters from drinking water treatment facilities in Hue and Ho Chi Minh. Horizontal business networks in Vietnam have also been growing due to the experiences from this project.

10.3.2.4

Key Challenges and Lessons

Several critical lessons were learned from this case study. First, it is important to ensure that the technology transfer projects address local needs and are appropriate to local contexts. Second, there is a need to ensure that there is a locally led initiative and close communication among all relevant stakeholders. Third, advanced technology, equipment and machinery should be locally manufactured/produced in order to reduce the costs and enhance the possibility for replication and scale up.

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Table 10.9 Achievements of JICA’s technical cooperation 1993 (Ex ante) 25% 10 h a day 72% 48% Not drinkable

Item Water supply coverage Water supply rate Non-revenue rate (steal and leakage) Water bills payment rate Water quality

2006 (Ex post) 90% 24 h a day 8% 99.9% Drinkable

Source: Kitakyushu City

10.3.3 Case Study: Installation of Water Distribution Block System in Phnom Penh Phnom Penh Water Supply Authority (PPWSA) installed a water distribution block system in Phnom Penh under the support of JICA and Kitakyushu City government, Japan. Since the dispatch of a JICA expert from Kitakyushu City in 1999, a series of technical cooperation projects were carried out, and the scope extended from the water supply system to water quality improvement, including the capacity building of PPWSA. These remarkable achievements (summarized in the Table 10.9) are known as the “Miracle of Phnom Penh” (Suzuki and Kuwajima 2015).

10.3.3.1

Water Distribution: Opportunities for Collaboration

In the early 1990s, multiple donors were in Phnom Penh to support their recovery from the civil war that ended in 1991. JICA formulated a master plan for the restoration of the water supply service in 1993, and in 1999, a staff of the Water Bureau of Kitakyushu City was dispatched as a JICA expert to support the implementation of these plans based on the requests of the former Ministry of Health and Welfare and the former Director General (DG) of the PPWSA, H.E. Ek Sonn Chan. The expert suggested installing the water distribution block system, which was developed in Kitakyushu City in the 1980s to increase water revenue by reducing water leakage. Upon confirmation of the technical feasibility of this plan in Phnom Penh, PPWSA, Kitakyushu City, and JICA set out to work on the first technical cooperation project in 2001.

10.3.3.2

Identifying Co-innovation

The conceptualization and ideation stages of the co-innovation process led to the development of a master plan by Kitakyushu City that reflected local needs and proposed potential solutions. Then, many of the ideas in this master plan were incorporated in JICA’s Small-Scale Partnership Program (1-year project). The financial support for the project not only came from JICA but also PPWSA and

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Kitakyushu City (Akagi 2020). Kitakyushu City offered to provide second-hand telemeters and a personal computer with dedicated software (which were not available on site), and technical guidance from relevant staff. JICA supported the shipping of the aforementioned equipment and transfer of short-term experts (Kitakyushu City staff) to help with guiding installation on site. The PPWSA conducted the procurement and installation of roadside stations that would incorporate the telemeters. Five out of the 42 water distribution block systems were completed in the project period, while the remaining 37 were taken over by the PPWSA and JICA experts after the the first stage of the project formally closed (Akagi 2020). Kitakyushu City continued to support elements of the project beyond this first stage, especially capacity building for operation and maintenance with a follow up JICA technical cooperation project (2003–2006). The scope of the follow up project included “operation and maintenance of water distribution pipes,” “water quality management,” “maintenance of electrical equipment,” and “water treatment technology.” Two long-term experts and 32 short-term experts were dispatched by Kitakyushu City, while 50 staff people were assigned in PPWSA and other relevant Cambodian authorities (Ministry of Industry, Mines and Energy). Three staff people from the Water Bureau of Yokohama City were also placed on the board of this cooperation project upon a request from Kitakyushu City. In addition to the staffing decisions summarized above, the Director General of PPWSA also assigned one staff each for each water distribution block and introduced a unique evaluation system. That system reflected the staff’s performance in managing the leakage rates in their personnel evaluation, creating incentives that brought leakage rates down to world class levels. This resulted in increasing revenue water and created a virtuous cycle, i.e., increase in the number of citizens with access to tap water, increase in income to PPWSA, and increase in the institutional capacity of the PPWSA itself (Table 10.10). The PPWSA further committed to bring the tap water quality to drinkable levels. Accordingly, the support from Kitakyushu City and JICA shifted to how to realize drinkable water quality management and offered necessary support with this goal in mind. In 2005, the Director General of the PPWSA declared that this goal had been reached—tap water in Phnom Penh was safe to drink. All the knowledge transferred to PPWSA are documented in manuals that they themselves update taking into account the local context. The partnership between PPWSA, Kitakyushu City, and JICA continues to grow stronger and extends in many directions.

10.3.3.3

Potential Opportunities for Scaling Up

Backed by the success of aforementioned projects, two subsequent JICA projects were implemented in order to deploy the “Miracle of Phnom Penh” to other major cities in Cambodia. In 2011, the relevant Cambodian authorities and Kitakyushu City signed a Memorandum of Understanding (MoU) to support basic water supply plans for nine major cities. Since Kitakyushu City developed a Kitakyushu Overseas

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Table 10.10 Methodology and outcome: PPWSA-Japan collaboration in Phnom Penh City, Cambodia Extent of collaboration

Entry stage

Co-design and co-development

Co-production/ comanufacturing Co-monitoring and evaluation

Co-learning and scaling up

Co-developed with PPWSA, JICA, and Kitakyushu City PPWSA with support from Kitakyushu PPWSA with support from Kitakyushu Expanded to 9 regional cities with the involvement of national authority as well

Expected project outcome

Contribute to improving the water services by installing a water distribution block system

Achieved outcome Source Recipient partner partner Kitakyushu PPWSA City • Improvement • Contribuof water secution to the rity development • Recovery of of recipient basic infrastruccity ture • Capacity • Improvement building for of institutional city staff capacity • Market • Capacity access for building of staff local compa- Ministry of nies Industry, Mines JICA and Energy • Contribu• Improvement tion to the of water secudevelopment rity and public of recipient health in city Cambodia

Cobenefits • Increased reputation and fame • GHG emission reduction due to drastic water leakage reduction

Source: Authors

Water Business Association (KOWBA) in 2010 for promoting local companies’ overseas water business development, this MOU offered a good opportunity for the city government as well for revitalizing the local economy. As of December 2019, the projects enhancing water supply have been carried out in all of the nine cities through a public-private partnership (PPP). The membership companies of KOWBA (that include Uni-Elex, Geocraft, EIM Electric, Metawater, Yaskawa Electric) also joined the projects. In addition, Phnom Penh and Kitakyushu City concluded a sister city agreement in 2016, and now the scope of cooperation is not only the water sector but also sewage treatment, low carbon development, and solid waste management sectors (Akagi et al. 2018).

10.3.3.4

Key Challenges and Lessons Learned

In Phnom Penh, shortly after the civil war, there was a huge challenge for PPWSA to restore and make the water supply system sustainable. This challenge reflected not

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only the lack of infrastructure but also the lack of effective governance, institutional capacity, and human resources. Co-innovation was achieved because of the strong leadership and consistent will of the director general of the PPWSA, willingness of local staff, and continuous and generous support from JICA and Kitakyushu City. Locally led initiative and close communication among stakeholders were some the keys to this successful cooperation, as they made it possible to bring necessary resources together in a timely manner and sometimes change conventional practices. Delivering clear results during the early stage of the project were also important in motivating the counterpart to collaborate on the project. Also, timely and carefully designed interventions to increase the motivation of staff helped to achieve project goals.

10.4

Conclusion

The transfer of technology from one country to another is not a new phenomenon. Hence, the objective of this chapter was not to reinvent the wheel, but to examine the feasibility of technology collaboration in a manner that enhances long-term partnership and delivers benefits to multiple stakeholders under the framework of co-innovation. The chapter also highlighted the co-benefits through co-innovation in this developed-developing country technology collaboration. Apart from demonstrating how the concept of co-innovation supported technology collaboration between Southeast Asia and Japan, the chapter also raised several critical questions and offered some useful answers. First, the chapter underlined that the promotion of appropriate technology in developing countries is critical to low carbon development. Collaboration with developed economies will be helpful in this regard and well-designed institutional mechanisms will help facilitate technology transfer. The chapter also suggested that, while advanced technology is vital for helping a country move toward low carbon development, making these technologies locally adaptive is important. Second, this paper highlighted that co-innovation can help deliver co-benefits, while the continuous delivery of these benefits incentivizes co-innovation. Co-innovation helps in addressing the adaptability, affordability, and acceptability concerns pertaining to technology transfer and facilitates better integration of clean technologies in developing countries. Integration of clean energy technologies will lead to achieving multiple co-benefits (apart from the intended chiefly economic objectives of a particular project), as seen in the case studies. The three case studies demonstrated that there are co-benefits in terms of energy efficiency improvement and GHG emission reductions. On the other hand, recognizing the multiple benefits of advanced technology and collaboration of recipient and source country will help incentivize co-innovation initiatives. As co-innovation initiatives can help speed up the integration of technologies into relevant contexts and also customize the product or technology to suit the local conditions, there are

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clear benefits for stakeholders affected by this process. These begin with but extend beyond the cost savings that participating industries accrue from the co-innovation process. The cases reviewed in this chapter are from three countries in the Southeast Asia. There are many other instances of technology collaboration between and advanced and developing countries. It is hoped that highlighting these cases as examples of technology collaboration will also throw light on the possibilities of expanding similar collaboration to other areas where co-innovation can deliver co-benefits. Acknowledgment The preparation of this chapter has immensely benefitted from the support of the JSPS Bilateral Joint Research (JSPS-ICSSR Research) Grant 2021 as well as the strategic research fund of the Institute for Global Environmental Strategies, Japan. The authors wish to thank Eric Zusman for his comments and valuable suggestions on earlier versions of this chapter.

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