Adapting the Built Environment for Climate Change: Design Principles for Climate Emergencies 0323953360, 9780323953368

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Table of contents :
Cover
Adapting the Built Environment for Climate Change
Copyright
List of contributors
Contents
Untitled
1 Introduction to adapting the built environment for climate change
1.1 Signs of a climate emergency ahead
1.2 The irreversible need for the adaptation of the built environment to climate emergency
1.3 Outline of the book
Acknowledgments
References
2 A framework for risk assessment
2.1 Introduction
2.2 Principles of risk assessment
2.2.1 Definitions for complex risk
2.2.2 IPCC risk assessment framework
2.3 Risks derived from climate change to cities: hazards and perspectives
2.3.1 Direct hazards
2.3.1.1 Heat waves and the urban heat island
2.3.1.2 Urban flooding
2.3.1.3 Droughts
2.3.2 Other dynamic hazards
2.4 Conclusions
Acknowledgments
References
3 Scenarios for urban resilience—perspective on climate change resilience at the end of the 21st century of a photovoltaic-...
3.1 Introduction
3.2 Methodology
3.2.1 Different scenarios of climate changes
3.2.2 The mixed-use energy community
3.2.3 Settings of the model in TRNSYS
3.3 Results and discussion
3.4 Conclusions
Acknowledgment
References
4 Urban resilience through green infrastructure
4.1 Introduction
4.2 Key components for sustainable, livable, and resilient cities through green infrastructure
4.2.1 Urban ecological resilience
4.2.2 Urban water resilience
4.2.3 Urban climate resilience
4.2.4 Urban social resilience
4.3 Access, design, and implementation of green infrastructure
4.4 Strategies and policies for building city resilience
4.5 Concluding remarks
References
5 Climate-resilient transportation infrastructure in coastal cities
5.1 Introduction
5.2 Climate change resilience of transportation infrastructure
5.3 Quantifying resilience to climate change and coastal flooding
5.3.1 Assessing present and future coastal flood risk
5.3.2 Assessing the consequences of exposure
5.4 Achieving climate resilience through adaptation
5.4.1 Adaptation decision-making frameworks
5.4.2 Scales of adaptation
5.4.3 Increasing robustness
5.4.4 Increasing rapidity
5.4.5 Increasing redundancy
5.4.6 Increasing eesourcefulness
5.5 Valuing climate resilient infrastructure
5.5.1 Adapting equitably
5.6 Conclusion and future trends
References
Further reading
6 Climate change risks and bridge design
6.1 Introduction
6.2 Climate change projections and uncertainties
6.3 Climate change risks to bridges
6.3.1 Accelerated material degradation
6.3.2 Increased long-term deformations
6.3.3 Higher local scour rates
6.3.4 Additional demands on thermal deformation capacity and higher risk of thermally induced stresses
6.3.5 Higher risks from extreme natural events
6.4 Design of bridges in a changing climate
6.4.1 Stage 1: Importance rating
6.4.2 Stage 2: Identification of potential climate change risks
6.4.3 Stage 3: Analysis of potential climate change risks
6.4.4 Stage 4: Design strategy selection
6.4.5 Stage 5: Evaluating the final design
6.5 Challenges and research needs
6.5.1 Data availability and uncertainty
6.5.2 Challenges related to final design evaluation
Acknowledgments
References
7 Resilience of concrete infrastructures
7.1 Introduction
7.2 Concrete resilience
7.3 Resilience
7.3.1 Loss model
7.3.2 Prolongation of travel
7.3.3 Connectivity loss
7.3.4 Recovery model
7.4 A case study
7.4.1 Calculation
7.5 Conclusions
References
8 Challenges surounding  climate resilience on transportation infrastructures
8.1 Introduction
8.2 Conceptual framework
8.3 Literature review
8.4 Road transport infrastructure
8.5 Railway transport infrastructure
8.6 Airport infrastructure
8.7 Port infrastructure
8.8 Research methodology
8.8.1 Issues in seeking to achieve climate resilience
8.9 Case studies
8.9.1 Europe
8.9.2 Asia
8.9.3 Africa
8.9.4 Latin America
8.9.5 North America
8.9.6 Australia and New Zealand
8.10 Discussion
8.11 Conclusion and future direction
References
9 A worldwide survey of concrete service life in various climate zones
9.1 Introduction
9.2 Backgrounds
9.3 Climate
9.4 Service life prediction
9.5 Results
9.6 Conclusions
References
10 Effect of global warming on chloride resistance of concrete: a case study of Guangzhou, China
10.1 Introduction
10.2 Temperatures and relative humidity: past and future
10.3 Chloride diffusion models
10.4 Results and discussion
10.5 Conclusion
References
11 Resilient cooling of buildings to protect against heatwaves and power outages
11.1 Introduction
11.2 Methodology
11.2.1 Data collection
11.2.2 Data processing
11.2.3 Development of a definition
11.2.4 Focus group and follow-up-discussions
11.3 Results
11.3.1 Resilience against what?
11.3.2 Resilience: at which scale? And for how long?
11.3.3 Definition of “resilient cooling for buildings”
11.4 Discussion
11.5 Conclusion
Acknowledgments
References
12 Climate change and building performance: pervasive role of climate change on residential building behavior in different ...
12.1 Introduction
12.1.1 Effects of climate change on building behavior: summary results from the literature
12.2 Methodology
12.2.1 Climate data generator
12.2.2 Energy software for dynamic building simulation
12.2.3 The case study
12.3 Results and discussions
12.4 Conclusion
References
13 Climate-responsive architectural and urban design strategies for adapting to extreme hot events
13.1 Introduction
13.1.1 Climate change and extreme hot events
13.1.2 Necessary to use climate-responsive design strategies for adapting to extreme hot events
13.2 Climate-responsive architectural design strategies for extreme hot events
13.2.1 Effectiveness of climate-responsive architectural design strategies in different climates
13.2.2 Effectiveness of climate-responsive architectural design strategies in the subtropical climate
13.2.3 Shading and ventilation design strategies for buildings in subtropical high-density cities
13.3 Urban adaptive design strategies in responding to extreme hot events
13.3.1 Effectiveness of cooling materials for mitigating urban heat island
13.3.2 Urban geometry design for ventilation and shading
13.3.2.1 Urban geometry and ventilation
13.3.2.2 Urban geometry and shading
13.3.3 Urban greenery design for cooling city
13.4 Conclusion
Acknowledgments
References
14 Resilience of green roofs to climate change
14.1 Introduction
14.1.1 Built environment and urban transition
14.1.2 Nature-based solutions toward circular cities
14.2 Green roof as engineered system
14.2.1 Green roof classification
14.2.2 Green roof layers
14.3 Buildup green roof resilience through value
14.3.1 Environmental value
14.3.1.1 Air quality enhancement
14.3.1.2 Carbon sequestration
14.3.1.3 Biodiversity promotion
14.3.1.4 Stormwater management
14.3.1.5 Acoustic insulation and noise reduction
14.3.2 Social value
14.3.2.1 Esthetic integration
14.3.2.2 Well-being and life quality
14.3.2.3 Rooftop gardens
14.3.3 Economic value
14.3.3.1 Life span extension
14.3.3.2 Energetic efficiency
14.3.3.3 Energy production
14.3.3.4 Real-state valorization
14.3.3.5 Business development
14.4 How to increase green roofs’ resilience to water scarcity?
14.4.1 Vegetation
14.4.2 Substrates
14.5 Conclusion
Acknowledgments
References
15 Permeable concrete pavements for a climate change resilient built environment
15.1 Introduction
15.2 Properties of permeable concrete
15.2.1 Composition and mix design
15.2.2 Pore structure
15.2.3 Permeability
15.2.4 Strength
15.2.5 Durability
15.3 Factors controlling the performance of permeable concrete
15.3.1 Cement content and water/cement (w/c) ratio
15.3.2 Aggregates
15.3.3 Additives
15.3.4 Chemical admixtures
15.3.5 Compaction and placement
15.4 Clogging
15.4.1 Laboratory studies
15.4.2 Field investigations
15.4.3 Unclogging maintenance methods
15.5 Current state-of-the-art in permeable concrete pavements
References
16 Building design in the context of climate change and a flood projection for Ankara
16.1 Introduction
16.2 Climate change and its effects
16.2.1 Climate change effects on buildings
16.3 Climate change flood risk analysis and effects on buildings
16.4 Case study about a “flood” risk analysis in Ankara
16.5 Future trends
Acknowledgments
References
17 Amphibious housing as a sustainable flood resilient solution: case studies from developed and developing cities
17.1 Climate change and flood vulnerability
17.2 Research methodology
17.3 Adaptive techniques to combat flash floods: a comparative analysis
17.4 Amphibious housing: origin and development
17.5 Amphibious living: the Dutch experience
17.6 Amphibious living: the Thai experience
17.6.1 Flash floods in Thailand
17.6.2 Amphibious houses of Thailand
17.7 Amphibious living: the Jamaican experience
17.7.1 Flood prone areas of Bliss Pastures and Port Maria
17.7.2 Amphibious houses of Jamaica
17.8 Comparative analysis
17.9 Conclusion
References
18 Nature-based solutions and sponge city for urban water management
Acronyms
18.1 Introduction
18.2 The study methodology
18.2.1 The data collection and analysis
18.2.2 Screening and eligibility
18.2.3 Quantitative analysis: a bibliometric analysis
18.2.4 Thematic analysis
18.2.5 Interviews for sponge city topic
18.3 The review of nature-based solutions to tackle water-related issues
18.3.1 The general statistical analysis and bibliometric analysis of publications of NBS on urban water issues
18.3.2 Thematic analysis
18.4 The discussion of sponge city as part of nature-based solutions
18.4.1 Bibliometric analysis of sponge city publications
18.4.2 Thematic analysis of sponge city publications
18.4.3 The relationships between sponge city and nature-based solutions on urban water management
18.5 Conclusions and future trends
Acknowledgments
Appendix
References
Index
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Adapting the Built Environment for Climate Change

Woodhead Publishing Series in Civil and Structural Engineering

Adapting the Built Environment for Climate Change Design Principles for Climate Emergencies

Edited by

Fernando Pacheco-Torgal C-TAC Research Centre, University of Minho, Guimara˜es, Portugal

Claes-Go¨ran Granqvist A˚ngstro¨m Laboratory, Uppsala University, Sweden

Woodhead Publishing is an imprint of Elsevier 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, OX5 1GB, United Kingdom Copyright © 2023 Elsevier Ltd. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. ISBN: 978-0-323-95336-8 (print) ISBN: 978-0-323-95337-5 (online) For information on all Woodhead Publishing publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Matthew Deans Acquisitions Editor: Gwen Jones Editorial Project Manager: Emily Thomson Production Project Manager: Anitha Sivaraj Cover Designer: Miles Hitchen Typeset by MPS Limited, Chennai, India

List of contributors

Iftekhar Ahmed Department Bangladesh

of

Architecture,

BRAC

University,

Dhaka,

Shady Attia Department of Urban and Environmental Engineering, University of Liege, Lie`ge, Belgium I˙dil Ayc¸am Faculty of Architecture, Department of Architecture, Gazi University, Ankara, Turkey Joa˜o C. Azevedo Centro de Investigac¸a˜o de Montanha, Instituto Polite´cnico de Braganc¸a, Braganc¸a, Portugal Cristina Baglivo Department of Engineering for Innovation (DII), University of Salento, Lecce, LE, Italy Ivar Bjo¨rnsson Division of Structural Engineering, Lund University, Lund, Sweden Cristina S.C. Calheiros Interdisciplinary Centre of Marine and Environmental Research (CIIMAR/CIMAR), University of Porto, Novo Edifı´cio do Terminal de Cruzeiros do Porto de Leixo˜es, Matosinhos, Portugal; Institute of Science and Environment, University of St. Joseph, Macao, P.R. China Faith Chan School of Geographical Sciences, Faculty of Science and Engineering, University of Nottingham, Ningbo, P.R. China; School of Geography, University of Leeds, Leeds, United Kingdom; Water@Leeds Research Institute, University of Leeds, Leeds, United Kingdom Jinxin Chen State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, P.R. China Ali Cheshmehzangi Department of Architecture and Built Environment, Faculty of Science and Engineering, The University of Nottingham, Ningbo, P.R. China; Network for Education and Research on Peace and Sustainability (NERPS), Hiroshima University, Hiroshima, Japan

xiv

List of contributors

Innocent Chirisa Administration, Ezekiel Guti University, Bindura, Zimbabwe; Department of Urban & Regional Planning, University of the Free State, Bloemfontein, South Africa Paolo Maria Congedo Department of Engineering for Innovation (DII), University of Salento, Lecce, LE, Italy Rojina Ehsani Department of Civil and Environmental Engineering, Amirkabir University of Technology, Tehran, Iran Rijalul Fikri Department of Civil Engineering, Syiah Kuala University, Banda Aceh, Indonesia Davide Forcellini Department of Civil and Environmental Engineering, University of San Marino, Serravalle, San Marino Alessandra Gandini TECNALIA, Basque Research and Technology Alliance (BRTA), Parque Tecnolo´gico De Bizkaia, Derio, Spain Leire Garmendia Mechanical Engineering Department, School of Engineering in Bilbao, University of the Basque Country (UPV/EHU), Bilbao, Spain Da´niel Honfi Transport Department, City of Stockholm, Stockholm, Sweden Mingyang Hong Civil and Transportation School, South China University of Technology, Guangzhou, P.R. China Junyi Hua School of International Affairs and Public Administration, Ocean University of China, Qingdao, P.R. China Oskar Larsson Ivanov Division of Structural Engineering, Lund University, Lund, Sweden Jonas Johansson Division of Risk Management and Societal Safety, Lund University, Lund, Sweden Sara Kalantari Department of Civil and Environmental Engineering, Amirkabir University of Technology, Tehran, Iran Alalea Kia Department of Civil and Environmental Engineering, Imperial College London, London, United Kingdom Erik Kjellstro¨m Rossby Centre, Swedish Meteorological and Hydrological Institute, Norrko¨ping, Sweden

List of contributors

xv

Lei Li School of Geography, University of Nottingham, Nottingham, United Kingdom; School of Geographical Sciences, Faculty of Science and Engineering, University of Nottingham, Ningbo, P.R. China Sheng Liu School of Architecture, Southwest Jiaotong University, Chengdu, P.R. China; Faculty of Architecture, The University of Hong Kong, Hong Kong, P.R. China Michael V. Martello Department of Civil & Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States Domenico Mazzeo Department of Engineering for Innovation (DII), University of Salento, Lecce, LE, Italy; Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria, Rende, CS, Italy Thembani Moyo Department of Urban & Regional Planning, University of Johannesburg, Johannesburg, South Africa Amro Nasr Division of Structural Engineering, Lund University, Lund, Sweden Tariro Nyevera Development Governance Institute (DEGI), Harare, Zimbabwe Fernando Pacheco-Torgal C-TAC Research Centre, University of Minho, Guimara˜es, Portugal Pinar Pamukcu-Albers Department of Geography, University of Bonn, Bonn, Germany Sofia I.A. Pereira Universidade Cato´lica Portuguesa, CBQF - Centro de Biotecnologia e Quı´mica Fina – Laborato´rio Associado, Escola Superior de Biotecnologia, Porto, Portugal Laura Quesada-Ganuza Mechanical Engineering Department, School of Engineering in Bilbao, University of the Basque Country (UPV/EHU), Bilbao, Spain Chao Ren Faculty of Architecture, The University of Hong Kong, Hong Kong, P.R. China Pelin Sarıcıo˘glu Faculty of Architecture, Department of Architecture, Gazi University, Ankara, Turkey Fariborz M. Tehrani Department of Civil and Geomatics Engineering, California State University, Fresno, CA, United States

xvi

List of contributors

Francesca Ugolini Istituto per la Bioeconomia—Consiglio Nazionale delle Ricerche, Sesto Fiorentino, Italy Andrew J. Whittle Department of Civil & Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States Jianguo Wu School of Life Sciences, School of Sustainability, Arizona State University, Tempe, AZ, United States Tianyu Xie School of Civil Engineering, Southeast University, Nanjing, P.R. China Shi Yin Faculty of Architecture, The University of Hong Kong, Hong Kong, P.R. China; School of Architecture, South China University of Technology, Guangzhou, P.R. China Xinyu Zhao State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, P.R. China Adriana Zuniga-Teran School of Geography, Development & Environment, Udall Center for Studies in Public Policy, University of Arizona, Tucson, AZ, United States

Contents

List of contributors 1

Introduction to adapting the built environment for climate change Fernando Pacheco-Torgal 1.1 Signs of a climate emergency ahead 1.2 The irreversible need for the adaptation of the built environment to climate emergency 1.3 Outline of the book Acknowledgments References

xiii 1 1 5 9 11 11

Part 1 Risk assessment and scenarios of climatic resilience 2

3

A framework for risk assessment Laura Quesada-Ganuza, Leire Garmendia and Alessandra Gandini 2.1 Introduction 2.2 Principles of risk assessment 2.2.1 Definitions for complex risk 2.2.2 IPCC risk assessment framework 2.3 Risks derived from climate change to cities: hazards and perspectives 2.3.1 Direct hazards 2.3.2 Other dynamic hazards 2.4 Conclusions Acknowledgments References Scenarios for urban resilience—perspective on climate change resilience at the end of the 21st century of a photovoltaic-powered mixed-use energy community in two European capitals Cristina Baglivo, Paolo Maria Congedo and Domenico Mazzeo 3.1 Introduction 3.2 Methodology 3.2.1 Different scenarios of climate changes

17 17 18 21 24 26 26 29 30 31 31

37 37 39 40

vi

4

Contents

3.2.2 The mixed-use energy community 3.2.3 Settings of the model in TRNSYS 3.3 Results and discussion 3.4 Conclusions Acknowledgment References

42 43 44 48 49 49

Urban resilience through green infrastructure Pinar Pamukcu-Albers, Joa˜o C. Azevedo, Francesca Ugolini, Adriana Zuniga-Teran and Jianguo Wu 4.1 Introduction 4.2 Key components for sustainable, livable, and resilient cities through green infrastructure 4.2.1 Urban ecological resilience 4.2.2 Urban water resilience 4.2.3 Urban climate resilience 4.2.4 Urban social resilience 4.3 Access, design, and implementation of green infrastructure 4.4 Strategies and policies for building city resilience 4.5 Concluding remarks References

53

Part 2 5

53 55 56 57 57 58 58 60 63 63

Climate emergency adaptation of infrastructures

Climate-resilient transportation infrastructure in coastal cities Michael V. Martello and Andrew J. Whittle 5.1 Introduction 5.2 Climate change resilience of transportation infrastructure 5.3 Quantifying resilience to climate change and coastal flooding 5.3.1 Assessing present and future coastal flood risk 5.3.2 Assessing the consequences of exposure 5.4 Achieving climate resilience through adaptation 5.4.1 Adaptation decision-making frameworks 5.4.2 Scales of adaptation 5.4.3 Increasing robustness 5.4.4 Increasing rapidity 5.4.5 Increasing redundancy 5.4.6 Increasing eesourcefulness 5.5 Valuing climate resilient infrastructure 5.5.1 Adapting equitably 5.6 Conclusion and future trends References Further reading

73 73 75 77 79 81 83 83 84 86 88 89 90 92 95 96 98 107

Contents

6

7

8

Climate change risks and bridge design Amro Nasr, Ivar Bjo¨rnsson, Da´niel Honfi, Oskar Larsson Ivanov, Jonas Johansson and Erik Kjellstro¨m 6.1 Introduction 6.2 Climate change projections and uncertainties 6.3 Climate change risks to bridges 6.3.1 Accelerated material degradation 6.3.2 Increased long-term deformations 6.3.3 Higher local scour rates 6.3.4 Additional demands on thermal deformation capacity and higher risk of thermally induced stresses 6.3.5 Higher risks from extreme natural events 6.4 Design of bridges in a changing climate 6.4.1 Stage 1: Importance rating 6.4.2 Stage 2: Identification of potential climate change risks 6.4.3 Stage 3: Analysis of potential climate change risks 6.4.4 Stage 4: Design strategy selection 6.4.5 Stage 5: Evaluating the final design 6.5 Challenges and research needs 6.5.1 Data availability and uncertainty 6.5.2 Challenges related to final design evaluation Acknowledgments References Resilience of concrete infrastructures Davide Forcellini and Rijalul Fikri 7.1 Introduction 7.2 Concrete resilience 7.3 Resilience 7.3.1 Loss model 7.3.2 Prolongation of travel 7.3.3 Connectivity loss 7.3.4 Recovery model 7.4 A case study 7.4.1 Calculation 7.5 Conclusions References Challenges surounding climate resilience on transportation infrastructures Innocent Chirisa, Tariro Nyevera and Thembani Moyo 8.1 Introduction 8.2 Conceptual framework 8.3 Literature review

vii

109

109 110 113 113 116 116 117 118 119 120 120 122 122 123 123 123 124 124 124 133 133 134 138 139 141 141 142 142 148 153 154

161 161 162 162

viii

Contents

8.4 8.5 8.6 8.7 8.8

9

10

Road transport infrastructure Railway transport infrastructure Airport infrastructure Port infrastructure Research methodology 8.8.1 Issues in seeking to achieve climate resilience 8.9 Case studies 8.9.1 Europe 8.9.2 Asia 8.9.3 Africa 8.9.4 Latin America 8.9.5 North America 8.9.6 Australia and New Zealand 8.10 Discussion 8.11 Conclusion and future direction References

167 167 167 168 168 169 170 170 170 171 172 173 174 174 177 177

A worldwide survey of concrete service life in various climate zones Sara Kalantari, Rojina Ehsani and Fariborz M. Tehrani 9.1 Introduction 9.2 Backgrounds 9.3 Climate 9.4 Service life prediction 9.5 Results 9.6 Conclusions References

183

Effect of global warming on chloride resistance of concrete: a case study of Guangzhou, China Mingyang Hong, Xinyu Zhao, Jinxin Chen and Tianyu Xie 10.1 Introduction 10.2 Temperatures and relative humidity: past and future 10.3 Chloride diffusion models 10.4 Results and discussion 10.5 Conclusion References

Part 3 11

183 184 186 190 192 197 197

201 201 203 206 207 210 211

Building adaptation to heat waves, floods

Resilient cooling of buildings to protect against heatwaves and power outages Shady Attia 11.1 Introduction 11.2 Methodology 11.2.1 Data collection

215 215 216 216

Contents

11.2.2 Data processing 11.2.3 Development of a definition 11.2.4 Focus group and follow-up-discussions 11.3 Results 11.3.1 Resilience against what? 11.3.2 Resilience: at which scale? And for how long? 11.3.3 Definition of “resilient cooling for buildings” 11.4 Discussion 11.5 Conclusion Acknowledgments References 12

13

Climate change and building performance: pervasive role of climate change on residential building behavior in different climates Cristina Baglivo, Paolo Maria Congedo and Domenico Mazzeo 12.1 Introduction 12.1.1 Effects of climate change on building behavior: summary results from the literature 12.2 Methodology 12.2.1 Climate data generator 12.2.2 Energy software for dynamic building simulation 12.2.3 The case study 12.3 Results and discussions 12.4 Conclusion References Climate-responsive architectural and urban design strategies for adapting to extreme hot events Sheng Liu, Shi Yin, Junyi Hua and Chao Ren 13.1 Introduction 13.1.1 Climate change and extreme hot events 13.1.2 Necessary to use climate-responsive design strategies for adapting to extreme hot events 13.2 Climate-responsive architectural design strategies for extreme hot events 13.2.1 Effectiveness of climate-responsive architectural design strategies in different climates 13.2.2 Effectiveness of climate-responsive architectural design strategies in the subtropical climate 13.2.3 Shading and ventilation design strategies for buildings in subtropical high-density cities 13.3 Urban adaptive design strategies in responding to extreme hot events 13.3.1 Effectiveness of cooling materials for mitigating urban heat island

ix

216 217 217 217 217 218 221 224 225 226 226

229 229 231 232 233 233 235 238 246 247

253 253 253 254 255 255 256 259 261 261

x

14

15

Contents

13.3.2 Urban geometry design for ventilation and shading 13.3.3 Urban greenery design for cooling city 13.4 Conclusion Acknowledgments References

262 265 268 269 269

Resilience of green roofs to climate change Cristina S.C. Calheiros and Sofia I.A. Pereira 14.1 Introduction 14.1.1 Built environment and urban transition 14.1.2 Nature-based solutions toward circular cities 14.2 Green roof as engineered system 14.2.1 Green roof classification 14.2.2 Green roof layers 14.3 Buildup green roof resilience through value 14.3.1 Environmental value 14.3.2 Social value 14.3.3 Economic value 14.4 How to increase green roofs’ resilience to water scarcity? 14.4.1 Vegetation 14.4.2 Substrates 14.5 Conclusion Acknowledgments References

273

Permeable concrete pavements for a climate change resilient built environment Alalea Kia 15.1 Introduction 15.2 Properties of permeable concrete 15.2.1 Composition and mix design 15.2.2 Pore structure 15.2.3 Permeability 15.2.4 Strength 15.2.5 Durability 15.3 Factors controlling the performance of permeable concrete 15.3.1 Cement content and water/cement (w/c) ratio 15.3.2 Aggregates 15.3.3 Additives 15.3.4 Chemical admixtures 15.3.5 Compaction and placement 15.4 Clogging 15.4.1 Laboratory studies 15.4.2 Field investigations 15.4.3 Unclogging maintenance methods

273 273 274 275 276 278 279 280 282 282 284 284 286 288 288 289

297 297 300 300 300 301 303 304 304 304 305 306 306 306 307 307 313 315

Contents

15.5 Current state-of-the-art in permeable concrete pavements References 16

17

18

Building design in the context of climate change and a flood projection for Ankara ˙ Ayc¸am ˘ and Idil Pelin Sarıcıoglu 16.1 Introduction 16.2 Climate change and its effects 16.2.1 Climate change effects on buildings 16.3 Climate change flood risk analysis and effects on buildings 16.4 Case study about a “flood” risk analysis in Ankara 16.5 Future trends Acknowledgments References Amphibious housing as a sustainable flood resilient solution: case studies from developed and developing cities Iftekhar Ahmed 17.1 Climate change and flood vulnerability 17.2 Research methodology 17.3 Adaptive techniques to combat flash floods: a comparative analysis 17.4 Amphibious housing: origin and development 17.5 Amphibious living: the Dutch experience 17.6 Amphibious living: the Thai experience 17.6.1 Flash floods in Thailand 17.6.2 Amphibious houses of Thailand 17.7 Amphibious living: the Jamaican experience 17.7.1 Flood prone areas of Bliss Pastures and Port Maria 17.7.2 Amphibious houses of Jamaica 17.8 Comparative analysis 17.9 Conclusion References Nature-based solutions and sponge city for urban water management Lei Li, Faith Chan and Ali Cheshmehzangi Acronyms 18.1 Introduction 18.2 The study methodology 18.2.1 The data collection and analysis 18.2.2 Screening and eligibility 18.2.3 Quantitative analysis: a bibliometric analysis 18.2.4 Thematic analysis 18.2.5 Interviews for sponge city topic

xi

317 320

327 327 329 332 336 338 344 345 345

349 349 350 350 351 355 357 357 357 359 359 361 364 368 368

371 371 371 375 375 376 376 377 377

xii

Contents

18.3

The review of nature-based solutions to tackle water-related issues 18.3.1 The general statistical analysis and bibliometric analysis of publications of NBS on urban water issues 18.3.2 Thematic analysis 18.4 The discussion of sponge city as part of nature-based solutions 18.4.1 Bibliometric analysis of sponge city publications 18.4.2 Thematic analysis of sponge city publications 18.4.3 The relationships between sponge city and nature-based solutions on urban water management 18.5 Conclusions and future trends Acknowledgments Appendix References Index

378 378 380 386 387 388 390 393 394 395 396 403

Introduction to adapting the built environment for climate change

1

Fernando Pacheco-Torgal C-TAC Research Centre, University of Minho, Guimara˜es, Portugal

1.1

Signs of a climate emergency ahead

Nobel prize winner Svante Arrhenius was the first to establish a quantitative link between changes in atmospheric CO2 concentration and climate changes on January 10, 1986, in a publication entitled “On the Influence of Carbonic Acid in the Air upon the Temperature of the Earth.” Still, it was only several decades later at the end of the 1950s that Arrhenius’ greenhouse effect was taken up as a major topic for the International Geophysical Year (Arrhenius et al., 2008). Much more recently two recipients of the 2021 Nobel of Physics were celebrated for their work on quantifying variability and reliably predicting global warming. Syukuro Manabe demonstrated how increased levels of carbon dioxide in the atmosphere lead to increased temperatures at the surface of the Earth while Klaus Hasselmann created a model that links together weather and climate, and developed methods for identifying specific signals, that help to prove that the increased temperature in the atmosphere is due to human emissions of carbon dioxide (NP, 2021). In the early 18th century, in the beginning of the Industrial Revolution, CO2 was 280 ppm but since then it had risen in a steady manner. And as a consequence 2016 was the first year with atmospheric CO2 concentrations above 400 ppm all year round (Betts et al., 2016). Stern (2006) predicted that by 2050 CO2 concentrations above 550 ppm. And some doomsday scenarios even mention that keeping the current level of emissions will imply a dramatic increase in CO2 concentration to as much as 731 ppm in the year 2130 leading to a 3.7 C global warming above preindustrial temperatures (Valero et al., 2011). The fact that CO2 concentrations had reach 400 ppm means that the 350 ppm boundary set in the Rockstro¨m et al. (2009) global sustainability model was already crossed risking “abrupt environmental change within continentalto planetary-scale systems.” Global warming can trigger the thawing of the permafrost-permanently frozen ground (Wilson et al., 2017)—where approx. 1 3 106 million tons (1000 GtCO2eq) are still retained and this can dramatically change global warming side effects. This astonishing figure is equivalent to the current worldwide production (34 GtCO2eq) during 30 years. According to Watts (2018) in February of last year the temperatures in the Arctic remained 20 C above the average for longer than a week having increased the melting rate. And the highest temperature ever recorded in the Arctic, 38 C has been officially confirmed. As a consequence, the replacement of ice by water will lead to a higher absorption of Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00016-0 © 2023 Elsevier Ltd. All rights reserved.

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Adapting the Built Environment for Climate Change

solar radiation that makes oceans warmer being responsible for basal ice melting (Tabone et al., 2019) and also for a warmer atmosphere. This constitutes a positive feedback that aggravates the aforementioned problem. The latest data on rates of melting combined with new models suggest that an ice-free Arctic summer could occur by 2030 (Screen & Deser, 2019). To make things worse the phenomenon known as Arctic amplification that meant the Artic was warming twice as fast as the rest of the world is based in an inaccurate calculation. Recent studies show that the Arctic is in fact warming four times faster than the global average (Jacobs et al., 2021). The warming of the Earth will also result in extensive permafrost thaw in the Northern Hemisphere. With thaw, large amounts of organic carbon are mobilized, some of which is converted and released into the atmosphere as greenhouse gases. This in turn, facilitates a positive permafrost carbon feedback, thus further warming (Tanski et al., 2018). According to Xu et al. (2018), three lines of evidence suggest that global warming will be faster than projected in the recent Intergovernmental Panel on Climate Change (IPCC) special report. First, greenhouse-gas emissions are still rising. Second, governments are cleaning up air pollution faster than the IPCC and most climate modelers have assumed. But aerosols, including sulfates, nitrates and organic compounds, reflect sunlight so the aforementioned cleaning could have a warming effect by as much as 0.7 C. And in third place, there are signs that the planet might be entering a natural warm phase because the Pacific Ocean seems to be warming up, in accord with a slow climate cycle known as the Interdecadal Pacific Oscillation that could last for a couple of decades. And these three forces reinforce each other. Recently Bamber et al. (2019) found that future sea level rise with the inclusion of thermal expansion and glacier contributions results for 2100 will exceed 2 m which is more than twice the upper value put forward by the IPCC in the Fifth Assessment Report. This is especially worrisome because 90% of urban areas are situated on coastlines, making the majority of the world’s population increasingly vulnerable to the current climate emergency (Elmqvist et al., 2019). At the same time, he United Nations estimates that by 2030 700 million people will be forced to leave their homes because of drought (Padma, 2019). No wonder that Wallace-Wells (2017) wrote about catastrophic scenarios that include starvation, disease, civil conflict, and war. Even the discreet and circumspect Joachim Schellnhuber Professor of theoretical physics expert in complex systems and nonlinearity, founding director of the Potsdam Institute for Climate Impact Research (1992 2018) lost his frugality views when he authored the foreword of the paper by Spratt and Dunlop (2018) in which he wrote: “climate change is now reaching the end-game, where very soon humanity must choose between taking unprecedented action, or accepting that it has been left too late and bear the consequences.” A recent paper (Lyon et al., 2021) analyzed climate scenarios beyond 2100 (many of the 140 million humans who were born in 2021 will still be alive beyond 2100) and their projections show that there will be a serious reduction in the areas available for agriculture and also that the tropical regions will no longer be inhabited by humans, thus helping to darken future perspectives. Most unfortunately, the solutions presented so far are at best of low ambition and noncost-efficient. On September 2021 The Economist noticed that the

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3

world’s biggest carbon-removal plant located in Iceland has started sucking carbon dioxide directly from the air. It will capture 4000 tons of CO2 every year. Of course, 4000 tons is almost nothing because it would require more than 100 years just to reach 0.5 million tons, the same as the carbon dioxide absorbed by 200,000 trees. Even assuming that the aforementioned Iceland carbon-removal plant would already be able to suck 1 million tons per year it would be better to avoid massive deforestation that is able to store 7.6 billion tons of carbon per year (Harris et al., 2021) than to build expensive carbon-removal plants (Iceland plant cost almost 15 million USD which means 75 USD/ton of carbon just for plant cost). It would be better for Iceland to copy Norway’s example that paid 24 million USD to Indonesia to avert almost 4.8 million tons of carbon-related deforestation which means a cost of just 5 USD per ton of carbon. And let us not forget that paying poor countries to avoid deforestation is also an excellent way to reduce the number of the many “millions of young people living in miserable conditions that can easily be radicalized to engage in terrorist actions” (Schmidt & Cohen, 2014). Not to mention that building carbon-removal plants will be unable to prevent the biodiversity crisis caused by deforestation that even worries the Financial Times. See the article below where one can read that Swiss Re estimates the value of biodiversity at 33 trillion USD a year (Arjalie`s, 2021). Gills and Morgan (2021) called it “the desperate last gasp of a moribund system” that looks at technologies as having the solutions to all the problems of humanity. Recently Alberro (2022) also criticized the humanity obsession with “technological fixes” that in her own words “merely serves as a last-ditch effort to alleviate the symptoms of the climate crisis while overlooking the need to effect multidimensional societal transformations.” Then, it is hardly a surprise that many in the scientific community decided to endorse civil disobedience groups like Extinction Rebellion the global environmental movement formed in October 31, 2018 (Mahase, 2019; Speijer, 2019; Aron, 2019). Not only endorse it but also as Gardner and Wordley (2019) argued a few weeks ago “scientists should join civil disobedience movements to fight these unprecedented crisis.” Back in 2017 Nature selected several crucial science events that shape that year and one of those events was AlphaGo Zero an amazing Artificial Intelligence capable of learn from its own. However, a search on Scopus publications allows for interesting comparisons between this AI event with Extinction Rebellion and Greta Thunberg—who began school climate strikes in August of 2018—showing how the former had much less impact on scientific publications (Fig. 1.1). The aforementioned impact of Greta Thunberg and the Extinction Rebellion movement can also be seen in a recent article having results of the first large-scale investigation of climate anxiety in 10,000 young people in 10 countries. The results showed that “59% very or extremely worried about climate change. Over 50% felt sad, anxious, angry, powerless, helpless, and guilty. Respondents rated the governmental response to climate change negatively and reported greater feelings of betrayal than of reassurance” (Hickman et al., 2021). A search on Google’s Ngram Viewer about how often the terms “climate change,” and “global warming,” appeared in English language books shows a steady rise beyond 1987 the very same year that the Bruntland report coined the term

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Greta Thunberg

Extinction Rebellion

AlphaGo Zero

600 500 400 300 200 100 0 2017

2018

2019

2020

2021

Figure 1.1 Evolution of the accumulated total number of publications. Articles/reviews/ chapters, books, and referenced conf. papers in Scopus.

“sustainable development” (AUS, 2021). Another recent search on Scopus database showed that although climate change is now a well-established expression more worrying terms are emerging. A search for publications having the terms (climate emergency, climate catastrophe or climate apocalypse) in title, abstract, and keywords retrieves 4432, 1425, and 122 documents meaning that climate apocalypse is the latest trend. Jones (2021) recently remembered that Floyd and Slaughter suggested that we need to call what is going on climate disruption, rather than global warming. He also suggested to adopted global weirding to encompass the growing intensity, complexity, and chaos in climate and ocean circulation systems. In his well-known essay “Deep Adaptation: A Map for Navigating Climate Tragedy,” Prof. Bendell challenged as paternalistic the views of those who think despair only brings negative things. He argues that despair is an essential step in understanding and reacting to an overwhelming reality, as is the climate catastrophe. Who knows, maybe this despair will allow youth in rich countries that have a high carbon footprint to stop being part of the problem and become part of the solution. Of course, we must hope that the aforementioned despair does not lead to radicalization and eco-terrorism actions (Global4cast, 2019). Some say Bendell went too far in his pessimistic views but a Professor of Physics at the University of Oxford wrote in an article published in August 2019 the following: “Let’s get this on the table right away, without mincing words. With regard to the climate crisis, yes, it’s time to panic” (Pierrehumbert, 2019). Furthermore, the repeated fiascos of the so-called Conference of Parties (COPs) to agree on important reductions on greenhouse gas emissions in Warsaw (CP-19) in 2013, in Lima (COP-20) in 2014, in Paris (COP21) in 2015, in Marrakech (COP-22) 2016, in Bon (COP-23) in 2017, in Katowice

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(COP-24) in 2018, in Madrid (COP-25) in 2019, and even the most recent COP-26 that just took place in Glasgow only worsened the climate change scenario. Two relevant events that took at the Glasgow conference merit to be reminded for what they mean. One was the tears of the COP President Alok Sharma and the other were the words of Frans Timmermans, EU Executive Vice-President, about his grandson: This morning, or an hour ago, my son Marc sent me a picture of my grandson, Kees, who is one year old. I was thinking Kees will be 31 when we’re in 2050, and it’s quite a thought to understand that if we succeed, he’ll be living in a world that’s liveable. He’ll be living in an economy that is clean, with air that is clean, at peace with his environment. If we fail, and I mean fail now within the next couple of years, he will fight with other human beings for water and food. (Timmermans, 2021)

1.2

The irreversible need for the adaptation of the built environment to climate emergency

In 2020 the Secretary General of the United Nations called on all governments to “declare a Climate Emergency in their countries until carbon neutrality is reached” (Guterres, 2020). But even for the best-case scenario, to be able to achieve climate neutrality (net-zero greenhouse gas emissions) by 2050. A very difficult goal. It will take hundreds of years for the world temperature to cool to preindustrial levels. That means that for the next hundreds of years the Humanity will have to live in a world 2 C warmer (than it was in the late 1800s) with extreme weather events such has heat waves, flash flooding and hurricanes. However, the truth is that the recent World Energy Outlook of 2021 says that “The successful pursuit of all announced pledges means that global energy-related CO2 emissions fall by only 40% over the period to 2050” (WEO, 2021) meaning that a more plausible scenario will involve 3 C warming (TE, 2021a, 2021b). In November 2021 Nature published the results of a survey showing that top climate scientists believe that by 2100 a 3 C warming is the most likely scenario and the percentage of those who still believe in a 1.5 C scenario is lower than the percentage of those who think we are heading to a 4 C warming world (Tollefoson, 2021). It is certainly no accident that the financial sector has been preparing for a temperature increase of 4 C for some time (TE, 2020). Climatic collapse consequences for the built environment are becoming more visible each year. Recently Belgium and Germany saw its rivers destroying thousands of buildings and killing many people. The Chinese city of Zhengzhou saw a year’s worth of rain in just three days. In June Canada broke its temperature record (49.6 C) and in July. Finland just saw its hottest night ever. In March of 2022 abnormally high temperatures were reported in Poles (in some cases 40 C higher than usual) but much worse than that, the heating takes place in both Poles at the same time (TE, 2022). Something that does not usually happen because at the moment the South Pole and the North Pole are in different seasons. In fact, the

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Arctic has just ended the winter season while the Antarctic region has just entered winter with 24/7 darkness for 6 months until September. And if last year in August Europe broke its record for maximum temperature, with 48.8 C, in Italy, it cannot be very surprising if in 2022 there is a new European record. A recent report by the Academy of Sciences of Australia mentions that temperatures of 50 C in Sydney and Melbourne, although still rare at 2 C global warming, are very likely to be regular occurrences at 3 C global warming (AAS, 2021). And let us not forget that this is just the Earth at 1.1 1.3 C warmer. Its therefore rather obvious that mitigation measures will not be enough and that urgent measures must be taken to adapt the built environment to climate emergency as it was advised by the first R of Bendell’s deep adaptation agenda (Bendell, 2018). A purpose for which this book intents to provide a contribution by reviewing the latest knowledge on the field. The resilient definition according to the United Nations Office for Disaster Risk Reduction encompasses the ability of a system, community or society exposed to hazards to resist, absorb, accommodate, adapt to, transform, and recover from the effects of a hazard in a timely and efficient manner, including through the preservation and restoration of its essential basic structures and functions through risk management (UNDRR, 2016). According to The Global Commission on Adaptation, which is led by Ban Ki-moon, 8th Secretary General of the United Nations, making infrastructure more climate-resilient can add about 3% to the upfront costs but has benefit cost ratios of about 4:1 (Now, 2019). An article on The Economist, about the cheapest way to cut carbon dioxide, shows that switching from diesel to electric vehicles delivers carbon cuts but at a very high cost while making buildings more energy-efficient provides one of the highest carbon abatement with low or even negative costs (TE, 2021c). No surprise then that the European Commission is putting so much “pressure” in building energy renovation. The high carbon abatement of energy building renovation is especially important in the context of the grave problems associated with the transition to clean energy. Wing et al. (2022) show a 26.4% increase in US flood risk by 2050 due to climate change alone under Representative Concentration Pathways (RCP) 4.5. And high-resolution flood risk estimates in the United States indicates current average annual losses of US$32.1 billion (US$30.5 33.8 billion) According to the IPCC heat waves are the most important and dangerous hazard related to the current climate catastrophe. Kew et al. (2019) reported that anthropogenic climate change has increased the odds of heat waves at least threefold since 1950. The consequences due to heat waves prediction do not even take into account the effect associated with Urban Heat Island (UHI). This phenomena is triggered by absorption radiation due to artificial urban materials, transpiration from buildings and infrastructure, release of anthropogenic heat from inhabitants and appliances, and airflow blocking effect of buildings (Pacheco-Torgal et al., 2015, 2020). The use of dark-colored surfaces has low reflecting power (or low albedo characteristics) as a consequence they absorb more energy and in Summer can reach almost 60 C, thus contributing for higher UHI effects. Nor does it take into account rare events like heatburst that can cause dramatic temperature swings like the one that took place in Portugal in May 2022 when the temperature rises 10 C in just

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5 minutes (Donn, 2022). Now add to this scenario the worrying conclusions of the recent study by Vecellio et al. (2022). The human body can survive a high temperature above 45 C at low humidity conditions, due to the natural cooling mechanism, associated with the evaporation of sweat and has been widely believed that a 35 C wet-bulb temperature (at 100% humidity) was the maximum a human could endure before they could no longer adequately regulate their body temperature, potentially causing heatstroke or death. However, the new evidence shows that the actual maximum wet-bulb temperature is lower—about 31 C. Of course, the conditions of the aforementioned study concern healthy young people, which means that an elderly person or an unhealthy young person will have an even lower wet-bulb temperature. If no adaptation measures are taken, this could mean an additional several thousand deaths/year from heat waves (and their synergic effects with air pollution). A recent review by Santamouris (2019) mentioned a projection of the future mortality of elderly population in Washington State, to increase between 4 and 22 times by 2045 and heat-related mortality in three cities in North-Eastern United States predicted a six to nine times increase by 2080 under the high emission scenario, RCP 8.5. On the positive side, Macintyre & Heaviside (2019) concluded that cool roofs could reduce heat-related mortality associated with the UHI by B25% during a heatwave. And this shows how cooling materials can be important in saving lives. In the last years some reviews were published about the consequences of climate change in the built environment. Stagrum et al. (2020) carried out an interesting review on the consequences of climate change. The most central climate change impact mentioned in the studies is the prospect of rising temperatures, causing drought and heat stress. Increasing rain loads and intensities are also pointed out as forthcoming and large problem, especially in places where this leads to more storm surges and flooding. However, although this is a major problem, few articles treating this issue were found. In general, little research has been found on the effect of future rain events on buildings. Even though it was found some studies on the impact of climate change on buildings in cold countries, there is a clear deficiency of literature from cold regions in general. There is also a major lack of studies where future climatic conditions have been used as a basis for laboratory experiments or field measurements, and only three were found the bulk of the adaptation measures discussed in this research including greening, cool materials, and phase-change materials. All these measures deal with hotter weather. There are notably fewer articles based on measures for adaptation to wetter weather. On the other hand, Sharifi (2020) found that mitigation measures may have negative impacts on adaptation by increasing exposure to risks, such as the urban heat island effect and flooding, and/or by eroding livelihood options of poor and marginalized groups and causing equity concerns. In contrast, adaptation measures may increase greenhouse gas emissions by, among other things, reducing efficiency and increasing energy demand. Ossola and Lin (2021) reported that the use of urban vegetation and blue-green infrastructures [nature-based solution (NBS)] that are increasingly used to foster urban sustainability and liveability are themselves vulnerable to the climate challenges they are meant to address. Heat waves, exacerbated by urban heat islands, may push species past their critical thresholds and destroy expensive NBSs. Increased

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frequency and intensity of extreme events under climate change may ultimately limit the ability of NBSs to survive and recover because climate extremes could recur well before NBSs can recover. Table 1.1 presents possible adaptations for the various ecological, technical, and social/governance elements that can be leveraged to increase NBS climate resilience and safety margins. Croce and Vettorato (2021) reviewed studies—concerning on the role of urban surfaces in fostering climate resilient and sustainable cities—that were published in the last 15 years, to answer three major questions: (1) which solutions do exist, (2) where can these be applied, and (3) which benefits do they provide. The discussion demonstrates that the use of urban surfaces might lead the development of multiple opportunities for improving the existing urban environments and supporting not only environmental but also social and economic resilience. The main conflicts and the potential synergies among different solutions emerged as a crucial aspect in the definition of a comprehensive approach to the urban surface use (Table 1.2). The bottom line is that the several reviews carried out in the field of adapting the built environment for climate change are too scarce and therefore fail to capture the essential knowledge already produced on this field, which is the motivation for this book.

Table 1.1 Possible adaptations for various ecological, technical, and social/governance elements that can be leveraged to increase NBS climate resilience and safety margins (Ossola & Lin, 2021). G

G

G

G

G

G

G

G

Use species with greater climate safety margins and with climatically-suitable provenance Couple species with complementary traits and increase biodiversity and community evenness Facilitate ecological processes and functions likely to succeed under climate change Increase NBS ecological resilience to urban stressors other than climate change technological elements Use technical systems with wider operating and safety margins to climate stressors Increase technical system redundancy and decrease of impacts of possible failures Minimize negative feedbacks on other nontechnical elements of NBS interventions Prioritize safe-to-fail NBS design that optimizes the performance of ecological and governance NBS elements

Social/governance elements G

G

G

G

G

Implement flexible, responsive, and accountable governance structures, policies, and regulations Involve all levels in society (i.e., private, business, public) to increase NBS multifunctionality and reduce tradeoffs Ensure NBS safety margins can be equitably maintained and increased across communities with different socioeconomic status Prioritize adaptive NBS based on predicted and unanticipated climate futures Push research, innovation, and education to find and implement innovative NBS pathways

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Table 1.2 Conflicts and synergies among surface uses on building surfaces.

The symbols in red (i.e., conflicting uses) and green (i.e., integrated solutions) refer to the five major clusters of surface uses listed in the first column (Croce and Vettorato, 2021).

1.3

Outline of the book

This book provides an updated state-of-the-art review on Adapting the Built Environment for Climate Change. The first part encompasses risk assessment and scenarios of climatic resilience (Chapters 2 4). Chapter 2 is concerned with a framework of a holistic risk assessment. It reviews basic concepts about climate change risk assessment, with a general outlook into risk assessment frameworks. It also includes the main risks derived from climate change hazards, both direct and systemic, and the aspects of the built environment to be considered for a holistic risk assessment, mainly based on the new IPCC AR6 report. Chapter 3 investigates some key components and dimensions and discusses some possible pathways to meet the needs for resilient cities.

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Adapting the Built Environment for Climate Change

Chapter 4 introduces analyzes the change in electricity supply from PV systems as a consequence of climate change in a hypothetical mixed energy community located in two European cities characterized by different climates, Rome and Berlin. The analysis was extended to possible climate change scenarios by including possible future climate effects due to mitigation policies, scenarios selected from the Fifth Assessment Report of the IPCC. Specifically, the RCP 4.5 and RCP 8.5 scenarios were included, that is, the stabilization scenario and the high emissions scenario. Climate emergency adaptation of infrastructures is the subject of Part II (Chapters 5 9). Chapter 5 presents an overview of the theoretical and practical dimensions of the design of climate-resilient transportation systems and relevant dimensions for infrastructure adaptation and planning, including valuation and assessment of equity Chapter 6 focuses on discussing the impacts of climate change to bridges and describes a conceptual framework as a guide for bridge designers on how to consider these impacts in bridge design. Chapter 7 investigates resilience and its application to concrete infrastructures subjected to seismic hazards and aiming to assess the recovery to various levels of preearthquake functionality. A case study is also considered to show the application of the proposed methodology to a real bridge. Chapter 8 provides a framework for action aimed at understanding climate resilience, transportation infrastructures, and issues in seeking to achieve climate resilience concerning transportation infrastructures including several case studies. Chapter 9 aims to assess the performance of concrete materials in various cases involving different applications and climate zones. Comparative evaluation of lifecycle measures, such as cost, energy, and emissions, is mapped with Envision’s sustainability rating measures as a robust framework for civil infrastructure. The presented study results highlight the sensitivity of evaluations to climate zone characteristics and provide insights on drafting the roadmap to implement climate change in practical engineering guidelines. In Chapter 10, we embark on a preliminary exploration of the effect of global warming on the durability of reinforced concrete structures under chloride ion attack in a humid and coastal environment Finally, Part III concerns building adaptation to heat waves and floods (Chapters 11 18). Chapter 11 reviews most of the existing resilient cooling definitions and the various approaches toward possible resiliency evaluation methodologies. It presents and discusses possible answers to the abovementioned issues to facilitate the development of a consistent resilient cooling definition and a robust evaluation methodology. Chapter 12 aims to provide an overview of building interior conditions under climate change in four very different climates. The locations under analysis are Miami, Damascus, Izmir, and Yakutsk, falling within the locations defined by the international Ko¨ppen-Geiger climate classification as tropical, arid, temperate, and continental. Chapter 13 provides a state-of-the-art review of the cooling effects of climateresponsive design strategies for adapting to the extreme hot events from the perspectives of architectural and urban design.

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Chapter 14 aims at giving an overview on the role of green roofs resilience to climate change, highlighting the provision of services and the mitigation and adaption capacity. Chapter 15 reviews the (1) properties of permeable concrete; (2) factors that influence their performance; (3) clogging mechanism; and (4) current state of the art to enable their widespread adoption as climate change resilient infrastructure in the built environment. Chapter 16 is concerned with the climate change risk assessments performed to reduce the impacts of climate risks. This chapter also includes a case study flood risk analysis. Chapter 17 contains an overview of indicators to determine the specific elements of resilience in the case study cities from the Netherlands, Thailand, and Jamaica. Then, it makes a comprehensive comparative analysis of the performance of amphibious housing as a sustainable flood resilient solution in the selected cities. Chapter 18 closes Part III with the bibliometric analysis and thematic analysis for NBSs and Sponge City Programme (SCP) studies within urban water management, respectively. Furthermore, we interviewed some stakeholders that once involved in the SCP projects to reveal the relations and differences between the concept of SCP and NBS, to explore the feasibility and transferability of those new solutions in different regions. Based on the assessment of extant NBS and SCP literature and interviews, we offered several recommendations for future research and practice.

Acknowledgments This research was supported by FCT-Fundac¸a˜o para Ciˆencia e Tecnologia within the scope of the project CEECIND/00609/2018.

References AAS. (2021). The risks to Australia of a 3 C warmer world. Australian Academy of Science. Available from https://www.science.org.au/files/userfiles/support/reports-and-plans/ 2021/risks-australia-three-deg-warmer-world-report.pdf. Alberro, H. (2022). HG wells, earthly and post-terrestrial futures. Futures102954. Arjalie`s, D.-L. (2021). Backing biodiversity to save ourselves. Financial Times. Available from https://www.ft.com/content/d29231ca-3bdc-4bd1-a477-5504c772259a. Aron, A. R. (2019). The climate crisis needs attention from cognitive scientists. Trends in Cognitive Sciences, 23(11), 903 906. Arrhenius, G., Caldwell, K., & Wold, S. (2008). A tribute to the memory of Svante Arrhenius (1859 1927): A scientist ahead of his time. IVA. Available from https://www.diva-portal.org/smash/get/diva2:139787/FULLTEXT01.pdf. AUS. (2021). How we discovered the climate problem. Australian National University. Available from https://science.anu.edu.au/news-events/news/how-we-discovered-climateproblem.

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Bamber, J. L., Oppenheimer, M., Kopp, R. E., Aspinall, W. P., & Cooke, R. M. (2019). Ice sheet contributions to future sea-level rise from structured expert judgment. Proceedings of the National Academy of Sciences of the United States of America, 116(23), 11195 11200. Bendell, J. (2018). Deep adaptation: A map for navigating climate tragedy. Institute for Leadership and Sustainability (IFLAS) Occasional Paper Volume 2. Ambleside, UK: University of Cumbria. Available from http://insight.cumbria.ac.uk/id/eprint/4166/1/ Bendell_DeepAdaptation.pdf. Betts, R., Jones, C., Knight, J., Keeling, R., & Kennedy, J. (2016). El Nin˜o and a record CO2 rise. Nature Climate Change, 6, 806 810. Croce, S., & Vettorato, D. (2021). Urban surface uses for climate resilient and sustainable cities: A catalogue of solutions. Sustainable Cities and Society, 75103313. Donn, N. (2022). Heatburst in Beja: Temperatures increased by 10oC in five minutes. % Portugal Resident. Available from https://www.portugalresident.com/heatburst-in-bejatemperatures-increased-by-10oc-in-five-minutes/. Elmqvist, T., Andersson, E., Frantzeskaki, N., McPhearson, T., Olsson, P., Gaffney, O., Takeuchi, K., & Folke, C. (2019). Sustainability and resilience for transformation in the urban century. Nature Sustainability, 2(4), 267. Gardner, C. J., & Wordley, C. F. (2019). Scientists must act on our own warnings to humanity. Nature Ecology & Evolution, 3(9), 1271 1272. Gills, B., & Morgan, J. (2021). No more excuses! Why the climate and ecological emergencies demand a new paradigm. Cadmus, 4(5), 83 102. Global4cast. (2019). Eco-terrorism is a matter of time. ,https://global4cast.org/2019/04/ecoterrorism-is-a-matter-of-time/.. Guterres. (2020). Secretary-General’s remarks at the Climate Ambition Summit. Available from https://www.un.org/sg/en/content/sg/statement/2020-12-12/secretary-generals-remarksthe-climate-ambition-summit-bilingual-delivered-scroll-down-for-all-english-version. Harris, N. L., Gibbs, D. A., Baccini, A., Birdsey, R. A., De Bruin, S., Farina, M., . . . Tyukavina, A. (2021). Global maps of twenty-first century forest carbon fluxes. Nature Climate Change, 11(3), 234 240. Hickman, C., Marks, E., Pihkala, P., Clayton, S., Lewandowski, E. R., Mayall, E. E., . . . van Susteren, L. (2021). Young people’s voices on climate anxiety, government betrayal and moral injury: A global phenomenon. Government Betrayal and Moral Injury: A Global Phenomenon. Available from https://papers.ssrn.com/sol3/papers.cfm?abstract_id 5 3918955. Jacobs, P., Lenssen, N., Schmidt, G., & Rohde, R. (2021). The arctic is now warming four times as fast as the rest of the globe. Available from https://agu.confex.com/agu/fm21/ meetingapp.cgi/Paper/898204. Jones, C. (2021). Getting Past Cassandra: 21 C Slaughter. Futures, 132102790. Lyon, C., Saupe, E. E., Smith, C. J., Hill, D. J., Beckerman, A. P., Stringer, L. C., . . . Aze, T. (2021). Climate change research and action must look beyond 2100. Global Change Biology. Mahase, E. (2019). Doctors for extinction rebellion: New group fights for planetary and public health. Macintyre, H. L., & Heaviside, C. (2019). Potential benefits of cool roofs in reducing heatrelated mortality during heatwaves in a European city. Environment International, 127, 430 441. Now, A. (2019). A global call for leadership on climate resilience. Global Commission on Adaptation.

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NP. (2021). Press release: The Nobel Prize in Physics 2021. Available from https://www. nobelprize.org/prizes/physics/2021/press-release/. Ossola, A., & Lin, B. B. (2021). Making nature-based solutions climate-ready for the 50 C world. Environmental Science & Policy, 123, 151 159. Pacheco-Torgal, F., Czarnecki, L., Pisello, A.L., Cabeza, L.F., & Goran-Granqvist, C. (Eds.). (2020). Eco-efficient materials for reducing cooling needs in buildings and construction: Design, properties and applications. Ossola, A., & Lin, B. B. (2021). Making nature-based solutions climate-ready for the 50 C world. Environmental Science & Policy, 123, 151 159. Pacheco-Torgal, F., Labrincha, J., Cabeza, L., & Granqvist, C. G. (Eds.), (2015). Ecoefficient materials for mitigating building cooling needs: Design, properties and applications. Woodhead Publishing, No. 56. Padma, T. (2019). African nations push UN to improve drought research. Available from https://www.nature.com/articles/d41586-019-02760-9. Pierrehumbert, R. (2019). There is no plan B for dealing with the climate crisis. Bulletin of the Atomic Scientists, 1 7. ˚ ., Chapin, F. S., III, Lambin, E., Lenton, T. M., Rockstro¨m, J., Steffen, W., Noone, K., Persson, A Scheffer, M., Folke, C., Schellnhuber, H., Nykvist, B., De Wit, C. A., Hughes, T., van der Leeuw, S., Rodhe, H., So¨rlin, S., Snyder, P. K., Costanza, R., Svedin, U., . . . Foley, J. (2009). Planetary boundaries: Exploring the safe operating space for humanity. Ecology and Society, 14(2), 32. Santamouris, M. (Ed.), (2019). Cooling energy solutions for buildings and cities. World Scientific. Schmidt, E., & Cohen, J. (2014). The new digital age: Transforming nations, businesses, and our lives. Vintage. Screen, J. A., & Deser, C. (2019). Pacific Ocean variability influences the time of emergence of a seasonally ice-free Arctic Ocean. Geophysical Research Letters, 2019. Sharifi, A. (2020). Trade-offs and conflicts between urban climate change mitigation and adaptation measures: A literature review. Journal of Cleaner Production122813. Speijer, D. (2019). Stop the assault on truth. Spratt, D., & Dunlop, I. (2018). What lies beneath: the understatement of existential climate risk. Breakthrough (National Centre for Climate Restoration). Available from https://climateextremes.org.au/wp-content/uploads/2018/08/What-Lies-Beneath-V3-LR-Blank5b15d.pdf. Stagrum, A. E., Andenæs, E., Kvande, T., & Lohne, J. (2020). Climate change adaptation measures for buildings—A scoping review. Sustainability, 12(5), 1721. Stern, N. (2006). Stern review on economics of climate change. Cambridge University Press. Tabone, I., Robinson, A., Alvarez-Solas, J., & Montoya, M. (2019). Submarine melt as a potential trigger of the North East Greenland Ice Stream margin retreat during Marine Isotope Stage 3. The Cryosphere, 13(7), 1911 1923. Tanski, G., Wagner, D., Fritz, M., Sachs, T., & Lantuit, H. (2018). Impetuous CO2 release from eroding permafrost coasts. TE. (2020). How much can financiers do about climate change?. The Economist. Available from https://www.economist.com/briefing/2020/06/20/how-much-can-financiers-do-aboutclimate-change. TE. (2021a). Three degrees of global warming is quite plausible and truly disastrous. The Economist. Available from https://www.economist.com/briefing/2021/07/24/threedegrees-of-global-warming-is-quite-plausible-and-truly-disastrous. TE. (2021b). This is what 3 C of global warming looks like. The Economist. Available from https://www.economist.com/films/2021/10/30/this-is-what-3degc-of-global-warming-looks-like.

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TE. (2021c). What is the cheapest way to cut carbon?. Available from https://www.economist.com/finance-and-economics/2021/02/22/what-is-the-cheapest-way-to-cut-carbon. TE. (2022). Parts of Antarctica have been 40 C warmer than their March average. The Economist. Available from https://www.economist.com/graphic-detail/2022/03/24/partsof-antarctica-have-been-40degc-warmer-than-their-march-average. Timmermans, F. (2021). SPEECH12 November 2021 Frans Timmermans at Stocktaking plenary at COP26. Available from https://ec.europa.eu/commission/commissioners/20192024/timmermans/announcements/frans-timmermans-stocktaking-plenary-cop26-0_en. Tollefoson, J. (2021). Top climate scientists are sceptical that nations will rein in global warming. Available from https://www.nature.com/articles/d41586-021-02990-w. United Nations Office for Disaster Risk Reduction-UNDRR. (2016). Report of the openended intergovernmental expert working group on indicators and terminology relating to disaster risk reduction. Available from https://www.undrr.org/publication/report-openended-intergovernmental-expert-working-group-indicators-and-terminology. Valero, A., Agudelo, A., & Valero, A. (2011). The crepuscular planet. A model for the exhausted atmosphere and hydrosphere. Energy, 36, 3745 3753. Vecellio, D. J., Wolf, S. T., Cottle, R. M., & Kenney, W. L. (2022). Evaluating the 35 C wetbulb temperature adaptability threshold for young, healthy subjects (PSU HEAT Project). Journal of Applied Physiology, 132(2), 340 345. Available from https://journals.physiology.org/doi/epdf/10.1152/japplphysiol.00738.20. Wallace-Wells, D. (2017). The Uninhabitable Earth: Famine, economic collapse, a sun that cooks us: What climate change could wreak—Sooner than you think. New York Magazine. July 10. Watts, J. (2018). Arctic warming: scientists alarmed by ‘crazy’ temperature rises. The Guardian, 27. WEO. (2021). Available from https://www.iea.org/reports/world-energy-outlook-2021. Wilson, R. M., et al. (2017). Greenhouse gas balance over thaw-freeze cycles in discontinuous zone permafrost. Journal of Geophysical Research: Biogeosciences, 122.2, 387 404. Wing, O. E. J., Lehman, W., Bates, P. D., et al. (2022). Inequitable patterns of US flood risk in the Anthropocene. Nature Climate Change. Xu, Y., Ramanathan, V., & Victor, D.G. (2018). Global warming will happen faster than we think.

A framework for risk assessment

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Laura Quesada-Ganuza1, Leire Garmendia1 and Alessandra Gandini2 1 Mechanical Engineering Department, School of Engineering in Bilbao, University of the Basque Country (UPV/EHU), Bilbao, Spain, 2TECNALIA, Basque Research and Technology Alliance (BRTA), Parque Tecnolo´gico De Bizkaia, Derio, Spain

2.1

Introduction

According to climate change predictions, if no action is taken, global warming will inevitably continue and worsen, causing sea-level rise, more frequent and intense floods, and more intense storms and hurricanes, droughts, and other climate extremes. The maximums in temperature rises are projected within urban centers and their areas of influence, highlighting the need for risk assessment methods and their relevance in the identification of vulnerable elements to later on develop adaptation strategies to achieve resilient urban environments (Sainz de Murieta et al., 2021). Therefore understanding future risks derived from climate change, including those arising from extreme events and hazards is becoming increasingly essential. The cities become more urbanized and their population continue increasing. The Intergovernmental Panel for Climate Change (IPCC), in their Fifth Assessment Report (AR5) in 2014 concluded that the “Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased” (IPCC, 2014). In its recent Sixth Assessment Report (AR6) (IPCC, 2022), it highlights that, due to the population growth expected in certain cities, the number of people estimated to live in urban areas highly exposed to climate change impacts is predicted to increase significantly. The AR6 report also states that, in urban areas, the risk faced by people and assets from hazards associated with climate change has increased since the AR5 (IPCC, 2022). Therefore the built environment is one of the main focus points of the adaptation actions to climate change, as cities enlarge due to the population growth and migration flows toward urban centers, all contributing to higher vulnerability to climatic hazards as heat waves, flooding, storms, and droughts. Besides the physical risks caused by higher frequency of extreme weather events, cities face challenges associated to their specific socio-economic, environmental, and cultural characteristics. Therefore these statements aligned with the fact that urbanization processes generate increasing vulnerability and exposure, which combined with climate change hazards, are the main drivers of urban risk and impact, making research in urban risk assessment against climate change a priority (IPCC, 2022). Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00017-2 © 2023 Elsevier Ltd. All rights reserved.

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The complexity of urban areas lies in the interaction of their social, ecological, and physical systems (Markolf et al., 2018), although cultural aspects are also relevant (Quesada-Ganuza et al., 2021). In cities, the interaction among settlements and infrastructures, characterized by the continuous interaction of multiple functional systems, increases the difficulty to understand and assess climate change risks (Dodman et al., 2022). There are several ways to address this complexity in literature, with the main one being a differentiated approach for specific systems and sectors within the city, that also influences the fragmentation of the management and adaptation policies (Dodman et al., 2022). Nevertheless, an overview of recent literature shows a shift of mind-set in the subject, tending to a more holistic approach to climate change impacts, losses and damages, as urban processes interact, considering more complex risks (Fraser et al., 2020; Simpson et al., 2021). For effective and holistic responses to climate change adaptation, especially when considering cities and their urbanized area, inclusive frameworks that integrate complex risks are a necessity (Olazabal & Ruiz De Gopegui, 2021; Pescaroli & Alexander, 2018; Simpson et al., 2021). Therefore different concepts and definitions are addressed in this chapter to better understand the different combinations of compound, systemic, or cascading risks that need to be considered when assessing the built environment. This book addresses the adaptation of the built environment to climate change from three perspectives: climatic resilience and management, infrastructures and emergency adaptation, and buildings adaptation to specific hazards caused by climate change. This chapter opens the first section and sets the framework and concepts for risk assessment throughout the book. With this goal in mind the chapters has a twofold purpose. The first one is to introduce and present the basic concepts that are needed for a framework in climate change risk assessment, considering the most recent and accepted definitions in literature. In addition, it includes various definitions of risk and different risk assessment frameworks, focusing specially in the well accepted IPCC framework. The second section aims to address and understand the main risks that climate change present for the built environment, both direct and systemic, from analyzing the main hazards and their interaction with urban areas and infrastructure. This chapter concludes with a general outlook into the aspects of the built environment to consider when assessing risk, the inclusion of responses as part of the frameworks, and the importance of complex risk assessment when addressing cities.

2.2

Principles of risk assessment

To make an introduction to risk assessment frameworks is important to address that most methodologies base their approach on the ISO 31000 (Leitch, 2010). The process for risk assessment following the ISO 31000 (Fig. 2.1) starts with the selection of potential risks, assessing them individually either qualitatively or quantitatively to evaluate their impact and shorting them depending on their severity (Creed et al.,

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Figure 2.1 The process for risk assessment following the ISO 31000 (Leitch, 2010; Scott et al., 2013). Source: Adapted from Scott, H., Mcevoy, D., Chhetri, P., Basic, F., & Mullet, J. (2013). Climate change adaptation guidelines for ports.

2019; Tonmoy et al., 2018). This is a linear risk assessment approach that fails to address more complex kind of risks that cannot be measured by just addressing individual components, but that need an assessment of bigger systems, as is the case of the effects of climate change (Cavallo & Ireland, 2014). As mentioned before in this chapter, cities are a complex interaction of different systems and therefore it is hard to understand their vulnerabilities. The realization of this complexity is causing a paradigm shift from single hazard and direct risks to more holistic approaches to climate change impacts and hazards, considering more complex risks (Fraser et al., 2020; Simpson et al., 2021). Complex risks are intrinsic to an extremely anthropogenic environment, such as cities. Hence, the analysis of risk must combine the natural and human factors that affect the magnitude of the risk, not only the hazard. In this context, in 2015, the United Nations member states adopted the Sendai Framework for Disaster Risk Reduction (SFDRR) (UNISDR, 2015), which was designed to improve upon the previous Hyogo Framework for Action (Fig. 2.2) (United Nations International Strategy for Disaster Reduction, 2019), based on the ISO 310001. The natural and human factors are within the Exposure and Vulnerability of both approaches. Furthermore, the updated Sendai framework considers human and ecological systems, in contrast to the just economic vulnerability considered in the Hyogo (United Nations International Strategy for Disaster Reduction, 2019). The Global Assessment Report on Disaster Risk Reduction published by United Nations International Strategy for Disaster Reduction (2019) also focuses on complex and systemic risks, addressing that to assess complex and interconnected systems, new views of risk are necessary and advocates for a more dynamic and three-dimensional view on risk. For this purpose, the report analyses and defines systemic risks addressing them in the context of urban areas and introduces a new Global Risk Assessment

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Figure 2.2 HYOGO and SENDAI frameworks from the UNISDR. Source: Adapted from the Global Assessment Report on Disaster Risk Reduction published by United Nations International Strategy for Disaster Reduction. (2019). Global assessment report on disaster risk reduction 2019. United Nations. https://www.un-ilibrary.org/content/ books/9789210041805.

Framework (GRAF 2020) (Fig. 2.3). This new framework includes global hazards (not only climate change hazards) and related exposure and vulnerability. Regarding climate change risk assessment, the main particularity is that adds a variety of systems and scales to the approach, compared to the Sendai framework from 2015. The SFDRR defines “the need for improved understanding of disaster risk in all its dimensions of exposure, vulnerability and hazard” (UNISDR, 2015). In this line, the Office of the United Nations Disaster Relief Coordinator (UNDRO) cites a definition from UNESCO for risk in its report meeting for Natural Disasters and Vulnerability Analysis, defining risk as “the probability of loss resulting from the product of hazard, vulnerability and value” (UNDRO, 1980). This definition has been widely adopted and adapted by the institutions dealing with disaster risk, such as the United Nations Office for Disaster Risk Reduction (UNISDR) and the IPCC. The IPCC adapted this definition for climate change assessment, developing it in each subsequent report. In its AR5 (IPCC, 2014), risk was defined as a “probability or likelihood of occurrence of hazardous events or trends multiplied by the impacts if these events or trends occur”; risk was therefore characterized as the “result of the interaction between hazard, vulnerability (susceptibility to harm) and exposure” (IPCC, 2014). This definition has been updated in the AR6, just published in 2022, to “The potential for adverse consequences for human or ecological systems,

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Figure 2.3 Global Risk Assessment Framework (GRAF 2020). Source: Adapted from The Global Assessment Report on Disaster Risk Reduction published by United Nations International Strategy for Disaster Reduction. (2019). Global assessment report on disaster risk reduction 2019. United Nations. https://www.un-ilibrary.org/content/ books/9789210041805.

recognizing the diversity of values and objectives associated with such systems. In the context of climate change, risks can arise from potential impacts of climate change as well as human responses to climate change” (IPCC, 2022). The components of risk have been updated to add that the risk is a result of the “dynamic interaction” of the climate hazards and the exposure and vulnerability of the systems under assessment (IPCC, 2022). This change comes to address that, as stated before in this chapter, there is a shift toward a more complex definition of risk in literature. In the last years the recent frameworks and methodologies developed for risk assessment to climate change have addressed risk as the potential and diverse impacts on human or ecological systems, as well as on the physical system, recognizing the complexity of those latent impacts (Gandini et al., 2021; QuesadaGanuza et al., 2021; Reisinger et al., 2020). This approach is necessary when addressing the built environment as systems, such as the human, economic, or ecological, interact with a physical environment that suffers the impact of climate change. To help understand the current state of the art of risk assessment in climate change research, the different definitions for complex risks that can be found within these frameworks need to be understood and defined, as well as the approach of the IPCC to complex risk assessment, as it is the most followed and accepted worldwide. These frameworks specially address cities and the urban areas as a focus and assess their particular vulnerabilities that need to be understood to provide a holistic approach to the risk assessment of the built environment.

2.2.1 Definitions for complex risk The analysis of the main risk assessment frameworks previously addressed in this chapter shows that there is a shift to more complex definitions of risk, especially when considering the urban and built environment, although there is still not a

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consistent agreed upon approach. To provide an overview of the current state of the art on complex risk, this section addresses the different types of risk defined within the AR5 and the more recent AR6 IPCC framework (Fig. 2.4), and Global Risk Assessment Framework (GRAF 2020) (Fig. 2.3) presented by the UNISDR. In its AR5, the IPCC acknowledged that risks can aggregate from multiple sectors, but does not consider complex risks in the risk assessment framework. Furthermore, as complex risks, only definitions for compound risk and emergent risk can be found in its glossary (IPCC, 2014). However, in the new 2022 AR6, risk, vulnerability, exposure, and impacts are studied as inherently complex, and aggregated, compounding, or cascading risks are considered as relevant (IPCC, 2022; Pescaroli & Alexander, 2018; Yokohata et al., 2019). Emergent risk is defined in the AR5s Chapter 19 as the risks that are caused by the interaction between climate phenomena and complex systems (IPCC, 2014). For the definition of aggregated, compounding, or cascading risks the AR6 seems to rely on the ones provided by Pescaroli and Alexander (2018) and the review by Simpson et al. (2021) (Fig. 2.5) other than the definition for compound risk already included in the 1.5 C Special Report of the IPCC (IPCC et al., 2018). Therefore compound risk is defined by the 2018 report as the risk that can emerge by the interaction of single, multiple coincident or sequential extreme events that interact to the systems or sectors exposed to them in one or more direction (IPCC et al., 2018). Some authors define aggregate risk as the “accumulation of independent determinants of risk” (Bansal & Ochoa, 2011; Simpson et al., 2021), and cascading risk is defined in the cited literature as the risk caused by effects, both one way or with feedbacks, of one event or trend causing others to develop, this being linked to the vulnerability component of risk (Lawrence et al., 2020; Simpson et al., 2021).

Figure 2.4 Graph showing UHI—linking temperatures urban morphology and land uses classification (Adapted from WMO, 2015).

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Figure 2.5 Interacting and complex risks within the Sixth Assessment Report Intergovernmental Panel for Climate Change framework. Source: Adapted from the Sixth Assessment report [IPCC. (2022). Climate change 2022: Impacts, adaptation, and vulnerability. In: Contribution of working group II to the Sixth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press] that adapted it from Simpson, N. P., Mach, K. J., Constable, A., Hess, J., Hogarth, R., Howden, M., Lawrence, J., Lempert, R. J., Muccione, V., Mackey, B., New, M. G., O’Neill, B., Otto, F., Po¨rtner, H.-O., Reisinger, A., Roberts, D., Schmidt, D. N., Seneviratne, S., Strongin, S., . . . Trisos, C. H. (2021). A framework for complex climate change risk assessment. One Earth, 4(4), 489 501. https://doi.org/10.1016/j.oneear.2021.03.005.

The AR6 report proposed a new framework to that of the AR5 that will be addressed later in this chapter, and with it adds the concept of key risk to the glossary, based on the terminology of the United Nations Framework Convention on Climate Change for those risks “especially relevant to the interpretation of dangerous anthropogenic interference with the climate system.” Hence, key risk is the one that presents high hazard or high vulnerability of the systems under assessment due to its severe consequences upon them (IPCC, 2022). Beyond IPCC, multiple terms have been used to describe complex risk. According to the UNISDR, disaster risk can be defined as “The potential loss of life, injury, or destroyed or damaged assets which could occur to a system, society or a community in a specific period of time, determined probabilistically as a function of hazard, exposure, vulnerability” (UNISDR, 2015). But, as cited before, the UNISDR in its 2019 report focuses on systemic risk and defines it as the one “endogenous to, or embedded in,” a system that could have “latent or cumulative risk potential to negatively impact overall system performance when some characteristics of the system change” even if the system itself at large is not considered to be at risk (Simpson et al., 2021; United Nations International Strategy for Disaster Reduction, 2019) (Table 2.1).

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Table 2.1 Complex risk terms and their definitions. Summary of complex risk terms and their definitions Key risks

Disaster risk

Emergent risk Compound risk Aggregate risk Cascading risk Systemic risk

Risks especially relevant to the interpretation of “dangerous anthropogenic interference with the climate system.” Key risk are the ones that present high hazard or high vulnerability of the systems under assessment for its severe consequences upon them (IPCC, 2022) The potential loss of life, injury, or destroyed or damaged assets which could occur to a system, society, or a community in a specific period of time, determined probabilistically as a function of hazard, exposure, vulnerability (UNISDR, 2015) “A risk that arises from the interaction of phenomena in a complex system” (IPCC, 2014) The risk that can emerge by the interaction of single, multiple coincident, or sequential extreme events that interact to the systems or sectors exposed to them (IPCC et al., 2018) The accumulation of independent determinants of risk (Bansal & Ochoa, 2011; Simpson et al., 2021) The risk caused by effects, both one way or with feedbacks, of one event or trend causing others to develop. It is linked to the vulnerability component of risk (Lawrence et al., 2020; Simpson et al., 2021) The one “endogenous to, or embedded in,” a system that could have “latent or cumulative risk potential to negatively impact overall system performance when some characteristics of the system change” even if the system itself at large is not considered to be at risk (Simpson et al., 2021; United Nations International Strategy for Disaster Reduction, 2019)

2.2.2 IPCC risk assessment framework Climate change risk is an ever-evolving area of research and therefore previous definitions and their limits may vary along the time. Across the board, these definitions understand risk as emerging from the interaction of different drivers of risk and hazards and stress the importance of understanding these interactions to assess risk (Raymond et al., 2020; Simpson et al., 2021). Hence, the key concepts that contribute to an understanding of risk include its determinants: hazard, exposure, and vulnerability. For these determinants and a further understanding of their interaction within risk assessment, the IPCC AR6 framework is going to be tackled. Exposure in this framework (IPCC, 2022) is defined as “The presence of people, livelihoods, species or ecosystems, environmental functions, services, and resources, infrastructure, or economic, social, or cultural assets in places and settings that could be adversely affected.” Hence, it refers to the elements in the area affected by the hazard. The concept of vulnerability is key to the characterization of risk, and its assessment implies characteristics and processes that are evaluated in different ways, depending on the discipline (Adger, 2006; Brooks, 2003). Hence, following the AR6 definition, vulnerability is “the propensity or predisposition of an element

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exposed to extreme events (i.e., climate change events) to be adversely affected,” and this vulnerability combined with hazard and exposure will determine the risk. A climate extreme or extreme event are defined by the IPCC as “The occurrence of a value of a weather or climate variable above (or below) a threshold value near the upper (or lower) ends of the range of observed values of the variable” (IPCC, 2022). The definition of vulnerability involves sensitivity to the hazard and the elements or systems lack of capacity to cope with the adverse effects of climate change. While sensitivity is a relatively straightforward concept defined as “susceptibility to harm” (Eligible et al., 1963), coping capacity is defined as: “The ability of people, institutions, organizations, and systems, using available skills, values, beliefs, resources, and opportunities, to address, manage, and overcome adverse conditions in the short to medium term” (Eligible et al., 1963). The new AR6 framework for risk has an expanded consideration of the responses among the determinants of risk and makes emphasis on their interactions (considering unidirectional, bidirectional, or aggregate) (IPCC, 2022) (Fig. 2.6). This refreshed approach makes more explicit the specifics of the interactions among determinants of risk, as well as among multiple risks, providing the basis for more detailed and accurate risk assessment. Therefore climate change risk assessment can present increasing complexity based on whether it considers, only a single driver for each determinant of risk,

Figure 2.6 Sixth Assessment Report Intergovernmental Panel for Climate Change framework. Source: Adapted from the Sixth Assessment report [IPCC. (2022). Climate change 2022: Impacts, adaptation, and vulnerability. In: Contribution of working group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press].

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multiple interacting drivers within determinants of risk, or even interacting risks. As mentioned, determinant refers to hazard, vulnerability, and exposure, within which the term driver refers to individual components of these that interact to affect the overall nature of a risk. When addressing climate change impacts, risks result from dynamic interactions between climate-related hazards and the exposure and vulnerability of the affected system; but with climate change responses, risks result from the potential for such responses not achieving the intended objective(s), or from potential tradeoffs or negative side effects (IPCC, 2022).

2.3

Risks derived from climate change to cities: hazards and perspectives

In the very interconnected urban world different socio-economic, environmental, technical, etc., systems interact and transfer risk among each other, increasing any risk or creating more complex ones. Hence, within cities the impacts and risks derived from climate change become complex and systemic since urban systems interact with climate in multiple and varied ways (Frank et al., 2017; IPCC, 2022). The possibility of occurring multiple hazards is high and this fact creates interaction between the multiple climatic risks and other nonclimatic counterparts, with the result of compounding risks affecting various systems within a city (Dodman et al., 2022; IPCC, 2022). Because of this, the complex impacts of climate change on the built environment are caused by the interaction between urban systems and climate change caused hazards (Frank et al., 2017). The most recent IPCC report identifies as the main direct hazards for cities, built environment and infrastructure, temperature extremes (and the urban heat island), flooding (including sea-level rise), as well as more dynamic interactions, such as cold spells, landslides, wind, fire, and air pollution. Therefore those are the hazards that will be analyzed in this section of the chapter. The interaction between them and their related compound and cascading risks for urban areas multiple systems is particularly important, taking into consideration that many cities are exposed to multiple hazards (Guerreiro et al., 2018).

2.3.1 Direct hazards 2.3.1.1 Heat waves and the urban heat island One of the main hazards that impact on urban areas are heat waves. As a general definition, the World Meteorological Organization (WMO) guidance on heat-health warning (WMO-No.1142) (UNEP & WMO, 2007; World Meteorological Organization, 2018) defines heat waves as periods of unusually hot and dry or hot and humid weather that have a duration of at least 2 3 days and a discernible impact on human activities (Jarosi´nska et al., 2018). Therefore heat waves can be characterized using two main indicators: temperature and relative humidity;

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distinguishing between dry and humid heat waves (Chen et al., 2019). Heat waves are a concerning hazard for urban population since the risk from them will worsen for cities and infrastructure (IPCC, 2022), with a minimum of half of the world’s population, considering the best case RCP 2.6 scenario, exposed to extreme periods of heat and humidity this century (Zhao et al., 2021). When assessing heat waves in urban areas, the urban heat island phenomenon must be a primary consideration. This phenomenon shows how morphology of an urban area affecting its shading and ventilation, the constructive and technical physical-chemical characteristics of urban elements and materials and the type and distribution of green spaces influence its intensity (Li and Bou-Zeid, 2013; Oke et al., 2017). Urban geometry and materials influence wind flow, energy absorption, and the ability of surfaces to release long wave radiation back to space (Gartland, 2010; Oke et al., 2017) causing the urban heat island effect (Fig. 2.4). Heat waves amplify the urban heat island effect (Santamouris, 2019), and combined with the increase on urban population and growth of the built environment, it will potentially affect half of the human population in the future (Huang et al., 2019; Zhao et al., 2018). Other than the proven and well researched consequences of high urban temperatures and heat stress for human health (IPCC, 2022), and their influence in mortality (He et al., 2021; IPCC, 2022), a main concern for the urban environment when considering heat is their effect on the reduction of thermal comfort, inside buildings and in urban environments. Thermal comfort is the key indicator that describes the subjective temperature experience that each person has, combining the impacts of solar radiation and shade, wind, air temperature and relative humidity on thermal sensation. The thermal comfort depends on building characteristics, such as thermal resistance and thermal mass of the envelope, ventilation, and shading, added to aspects related to the orientation and geographical position (Fig. 2.7). In the case of heat waves,

Figure 2.7 Graph showing characteristics of the built environment that affect thermal comfort outdoors and indoors.

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thermal comfort within urban spaces is a fundamental factor (He et al., 2021) that increases the effects of the climatic conditions. Thermal sensation is derived from thermal comfort and is key to a heat wave event. A human body at rest generates around 100 W of metabolic heat (as well as any absorbed solar heat), and if the ambient temperature is higher than the optimum central temperature of the human body (around 37 C), the human body cannot dissipate heat (Santamouris, 2019). On the other hand, sweating, the main process by which the human body regulates temperature, becomes less effective if the relative humidity is high, resulting in the accumulation of heat within the body and therefore an increase in morbidity and mortality. One of the main consequences of this phenomenon on the built environment is the increase on energy consumption (Santamouris et al., 2015; Santamouris, 2019) and the consequential thermal inequality (Mitchell & Chakraborty, 2015). Increased urban temperatures are also documented to affect the environmental quality of cities increasing the level of tropospheric ozone (Pyrgou et al., 2018; Santamouris, 2019) and affecting the air flow, causing an increase of the harmful atmospheric pollutants (Czarnecka & Nidzgorska-Lencewicz, 2014; Stedman, 2004). Finally, the bidirectional interaction between indoor and outdoor thermal conditions should be addressed when analyzing thermal comfort.

2.3.1.2 Urban flooding Floods are one of the costliest extreme hazard specially within the built environment (UNISDR, 2015). Floods include river (fluvial) floods, flash floods, pluvial floods and derived sewer floods, and can be caused by intense and/ or long-lasting precipitation (pluvial floods), snowmelt, dam break, and reduced conveyance due to ice jams and landslides (Hammond et al., 2015). Coastal cities also risk flooding derived from the increase of sea level rise and the intensity of rainfall and cyclone storms (coastal floods) (IPCC, 2022). Floods are natural phenomena which cannot be prevented and depend on precipitation intensity, volume, timing, antecedent conditions of rivers and their drainage basins. However, in the case of urban areas, flood risk increases with the interaction of these phenomenon and the built environment (Gandini et al., 2020; Hammond et al., 2015). Urban expansion, land use and land cover change, which enlarges impermeable surface areas through soil sealing, affecting drainage of floodwaters increase urban flooding risks (Kaspersen et al., 2017). The lack of adaptation measures to manage flooding impacts, for example, stormwater management, green infrastructure, and sustainable urban drainage systems, is the main driver of risk for urban systems (Dircke & Molenaar, 2015). When assessing the impact of floods, is important to consider direct and indirect damages, with direct including the physical damage caused to buildings and urban areas, as well as to infrastructure through direct contact with floodwaters. These direct damages may range from the soiling of basements and lower floors and longterm increases in residual moisture to the collapse of structures due to floodwater force. As seen with most risks, direct impacts are the most commonly studied and considered in assessments, at the expense of other categories, such as intangible impacts (Ward et al., 2013). In the case of infrastructure, direct impacts can be

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floodwaters directly damaging infrastructure elements, such as electricity substations or railway links, with the failure of these leading to indirect and cascading impacts to the urban system (Hammond et al., 2015).

2.3.1.3 Droughts Urban drought is classified in literature as a subtype of socio-economic drought, defined as a temporary water shortage situation that affects an urban area either due to a rapid decrease in water supply or a sudden increase in demand (Zhang et al., 2019). This kind of drought can have direct impacts on cities, including public health issues, strained economic situations, increased water prices, and an overall decrease in the life quality within the city. Commonly, the terms “urban drought” and water scarcity are used interchangeably in literature, both describing the imbalance between water supply and demand. According to the Food and Agriculture Organization, water scarcity is defined as “a gap between available supply and expressed demand of freshwater in a specified domain” (Steduto et al., 2012; Zhang et al., 2019). The scarcity of water in urban areas is very likely to increase due to climate change increasing warmer temperatures and derived heat waves, as well as from urbanization processes, changes in land use, and increase of urban population causing an over extraction of groundwater and surface water (Zhang et al., 2019). It is predicted that more than a quarter of the world major cities will exhaust their current water resources by 2050 (Flo¨rke et al., 2018; Zhang et al., 2019), increasing the risk of urban drought and amplifying the water stress in urban areas (Schewe et al., 2014). Service availability derived from the quality and capacity of infrastructure for the increasing demand as the population rises in cities is the main vulnerability compounding the risk of water scarcity in cities. Drought risk not only affects to locally exposed systems but also is relevant to consider dependence on water imported from distant areas that might be also exposed to drought and water scarcity (Zhang et al., 2019). Hence, droughts can interact in complex ways as urban interdependencies interconnect cities water supplies.

2.3.2 Other dynamic hazards Within the risks derived from climate change that affect the built environment and urban areas, some dynamic climate interactions have to be taken into consideration aside from the main hazards. The IPCC AR6 report signals as the ones relevant for cities, urban areas and infrastructure, cold spells, landslides, wind, fire, and pollution. Cold waves have and are expected to decrease in both frequency and intensity, urban areas and infrastructure can still be impacted by extreme cold events. Nevertheless, their intensity is increasing in some regions (IPCC, 2022). The risk of mortality derived by cold waves can increase in cities because of the demographic that are causing a growth in older population, more vulnerable to cold related risks (Kinney et al., 2015; Smid et al., 2019). Cold waves can also have an impact on infrastructure, both from the direct impacts of the weather conditions and ice storms

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on infrastructure, such as power lines or energy production plants, or indirect as increased energy demands (An˜el et al., 2017; IPCC, 2022). Landslides can be caused by a variety of combinations of climatic variables, such as precipitation, snowmelt, or temperature change (IPCC, 2022; Mateos et al., 2020), and they are intensified by the modification of natural slopes caused by urban development (Di Martire et al., 2012; Gariano & Guzzetti, 2016). Therefore the change in land use and natural land slope caused by urbanization is one of the drivers that combined with climatic conditions and hazards caused by climate change can increase the risk of landslide within urban areas (Gariano & Guzzetti, 2016), generating risk to the people and infrastructures. As seen when addressing the urban heat island phenomenon, urban morphology interacts and changes wind patterns, mainly, due to the increased surface roughness of the built environment (IPCC, 2022; Min et al., 2019). The interaction between wind and the urban geometry that causes the urban heat island effect can also increase both the thermal comfort within narrow streets (Dirksen et al., 2019; Pyrgou et al., 2018) and affect the dispersion of air pollutants (Czarnecka & Nidzgorska-Lencewicz, 2014). Also, it is important to consider that extreme events associated with strong winds may cause significant impacts on buildings and infrastructure. The last two dynamic interactions to consider for urban areas derive from the rise in temperature and heat waves and their interaction with the built environment, are namely fire and air pollution. In the case of fire, the increase in temperature and heat waves and the growth of urban areas interact to create higher risk of wildfires (Bento-Gonc¸alves & Vieira, 2020; Van Oldenborgh et al., 2020), with cities with more informal settlements being more at risk (IPCC, 2022). The extreme temperatures will also interact with certain pollutants, as seen when addressing heat waves. In addition, conditions, such as high temperatures and increased solar radiation, are documented to increase the level of tropospheric ozone (Pyrgou et al., 2018; Santamouris, 2019) and the urban geometry affecting the air flow can cause an increase of harmful atmospheric pollutants (Czarnecka & Nidzgorska-Lencewicz, 2014; Stedman, 2004).

2.4

Conclusions

The need for sustainable conservation and development of the built environment, together with the evidence that the climate threats to which it will be subjected are increasingly frequent entail the need to identify the risks faced by the built environment. Up to now mainly static climate change risk analysis, considering multiple criteria (physical, social, economic, environmental, cultural), has been undertaken. The recent analysis of the last IPCC special report and the UNDRR framework highlight the shift in literature toward a more holistic approach to climate change risk assessment. Interacting climate hazards and complex risk is now a key focus for risk assessment, especially for extreme events; indeed, the IPCCs updated the

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definition of risk acknowledges not only the diversity associated to human and ecological systems, but also the risks caused by human responses to climate change. That is, the risk is a result of the dynamic interaction between the different determinants of risks and human actions. These interactions shift risk assessment from a focus on individual climate hazards or hazard interactions as a single event to a set of multiple events that continually interact with evolving social and economic conditions and interventions, as mitigation and adaptation actions. Therefore a holistic consideration of the risks related to the impacts of climate change is especially necessary when addressing the built environment, involving the risks associated with the responses in the management, and decision-making processes. Furthermore, the inclusion of responses to climate change as possible drivers of risk broadens risk assessment to include positive outcomes, which is vital for making informed responses easier to process, giving different weights to the diversity of positive and negative consequences that can arise from both action and inaction. A holistic and dynamic risk analysis will support decision-making and lead to more sustainable and resilient built environment

Acknowledgments The authors wish to acknowledge the support of the SAREN research group (IT1619-22, Basque Government).

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Scenarios for urban resilience—perspective on climate change resilience at the end of the 21st century of a photovoltaic-powered mixed-use energy community in two European capitals

3

Cristina Baglivo1, Paolo Maria Congedo1 and Domenico Mazzeo1,2 1 Department of Engineering for Innovation (DII), University of Salento, Lecce, LE, Italy, 2 Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria, Rende, CS, Italy

3.1

Introduction

Cities, centers of social and economic life, are particularly vulnerable to the occurrence of extreme and sudden events, natural or man-made, affecting thousands and millions of people, resulting in loss of life, injuries, material and economic losses, and environmental impacts. Increasing rates of urbanization, insufficient infrastructure, uneven planning, and inefficient services lead to excessive resource consumption and intensified pollution. The analysis of urban neighborhoods is very complex, as it involves several variables including climatic properties, geometric design, type and number of buildings, building locations, distances, shading patterns, utilities, and different cultures and traditions (Congedo & Baglivo, 2021; Congedo et al., 2021a). Urban systems struggle with both internal dynamics, which are inevitable in complex systems in constant transition, and external changes, including floods, earthquakes, hurricanes, fires, pandemics, chemical explosions, terrorism, power blackouts, financial crises, cyber-attacks, war, and climate change. The concept of resilience first emerged to define how ecological systems manage risks and cope with change (Holling, 1973). Urban resilience is a concept that emerged in the early 1970s and is defined as the ability of cities to withstand, absorb, adapt to, and recover from a wide variety of future shocks that may occur (Bueno et al., 2021), managing and mitigating ongoing human and natural stresses, and protecting economic structure, technical systems, and infrastructure (ARUP, 2014). Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00012-3 © 2023 Elsevier Ltd. All rights reserved.

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Once the sudden change is established, one of the goals of resilience is to allow the population to adapt and live without being exposed to too much stress. Some studies have conducted literature analyses to define its concept and principles (Meerow & Newell, 2016; Rus et al., 2018). Many approaches and tools have been developed and used to measure climate resilience in cities (Mehryar et al., 2022). An understanding of this concept allows cities to be prepared for disasters and sudden events (Bu¨yu¨ko¨zkan et al., 2022); in fact, even though no city is completely safe from unforeseen risks, they can become more resilient to destructive forces. Preventive assessment of urban resilience, to manage and plan actions to be taken before and after disasters occur, has become crucial at various levels, which include planners, policymakers, and researchers (Sajjad et al., 2021). Theoretical and empirical investigations are critical to understanding how to implement resilient actions at the city level (Olazabal & Pascual, 2016). First, a city’s preparedness is characterized by a detailed understanding of risks, then by taking actions to reduce vulnerability and exposure, and finally by strengthening the awareness and participation of people and companies. Cities can emerge as driving forces for adaptation to change in which resilience becomes a central and crucial factor for sustainable development. The threat is not entirely negative, it can be taken as a great opportunity to generate change and open up new opportunities related to development and innovation (O’Farrell et al., 2019). Indeed, a resilient city is aware of how to adapt its systems and processes to ensure that they are as robust and reliable as possible in the face of shocks and stresses, rebuilding and improving after extreme events while focusing on the goal of restoring and ensuring long-term prosperity. Here, then, urban resilience can play a decisive role. The real challenge is to initiate a process capable of transforming negative events, shocks and stresses into positive factors on which to rebuild opportunities and possibilities for development. City governance and policies can proactively address climate change issues. This requires the development of indicators to quantify urban resilience, establish the baseline of applied policies, and measure and evaluate performance. Several approaches exist, but it is often the case that the proposed indicators are not standardized, consistent, or comparable over time or across cities. The ISO 37123 standard focuses on measuring resilience as a major contributor to a city’s long-term sustainability. The proposed indicators enable improved resilience in cities by promoting inclusive and collaborative approaches to governance at all levels. In the last few decades, accelerating energy demand and depletion of fossil fuels have dramatically changed the global energy landscape. Globally, there has been a shift toward the use of renewable energy sources to mitigate environmental crises resulting from climate change (Menyah & Wolde-Rufael, 2010). Renewable energy from resources, such as solar, wind, hydro, tidal, ocean waves, and geothermal (Ellabban et al., 2014), provides an alternative to conventional energy and is an important adaptation strategy for those who depend on natural resources for energy needs (Sapkota et al., 2014). The use of renewable energy and local electricity generation is increasingly adopted in both urban areas and rural communities (Mazzeo et al., 2021a).

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This diffusion implies several energy-related issues including more effective use of emerging technologies, reduction of economic costs, and security of supply. Threats to electricity security in the power system can be short-term, that is, as an episodic long-term, that is, as secular stress (Andy Stirling, 2014). Short-term episodic shock is a dynamic vulnerability of the electricity system and occurs unexpectedly at a given time (Kosai & Unesaki, 2020), caused by sudden disturbances. Long-term secular stress is a static vulnerability of the power system (e.g., environmental load, fuel depletion, growth in energy demand) (Christian, 2012). It is expected an increasing global temperature caused by climate change (He et al., 2022). Climate change emerges as a very important issue in the building sector (Baglivo et al., 2022) and must be considered in all stages of design and retrofit to reduce the energy demand of buildings (Baglivo, 2021). In this regard, a worldwide overview of the effects of climate change on buildings has been conducted to highlight how comfort and discomfort conditions inside buildings change differently over the years depending on the climate zone (Congedo et al., 2021b). Climate resilience has gained an essential role in research as well as in international policies. Climate resilience is the ability of people and systems to sustain and improve their livelihoods and development opportunities and well-being despite environmental, economic, social, and political disruptions caused by climate change (Clare et al., 2017; Tyler et al., 2016). A growing number of cities are adapting to climate change to improve their resilience. Given the complexity of urban systems in combination with accelerating climate and social change, it is difficult to measure the success of resilience improvement activities (Wilden & Feldmeyer, 2021). This chapter investigates the resilience of two hypothetical energy communities to imminent climate changes. The urban areas consist of both offices and residential buildings localized in Berlin and Rome. Their electricity supply comes from photovoltaic (PV) systems and when the supply from PV systems is not sufficient it is taken from the grid. Two possible scenarios of climate change are analyzed, considering the years 2020 and 2100.

3.2

Methodology

This work is focused on the comparison of the performances of a hypothetical energy community located in two different locations, Berlin and Rome. The two chosen cities have different climates, according to the Ko¨ppen climate classification, Berlin is classified as a Warm-summer humid continental climate “Dfb,” and Rome as Mediterranean climate “Csa” (Chen & Chen, 2013; Mazzeo et al., 2021b). The energy community consists of a mix of residential and office buildings, whose electricity is provided by a PV system as a priority, and when there is not enough it is taken from the grid when the production of electricity is in excess it is sent to the grid. Two different climate change scenarios were considered, which consider different mitigation policies. Analyses have been carried out on an hourly basis on TRNSYS software, considering the years 2020 and 2100.

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3.2.1 Different scenarios of climate changes The Intergovernmental Panel on Climate Change’s (IPCC) fifth assessment report presents four new Representative Concentration Pathways (RCP) scenarios that also consider the effects of mitigation policies (IPCC, 2014); they are reported in Table 3.1. This work reports the analysis of the same mix-use energy community located both in Rome and Berlin, by considering the RCP 4.5 and RCP 8.5 scenarios. Analysis of the literature (Feron et al., 2021; Jerez et al., 2015; Mu¨ller et al., 2019; Pe´rez et al., 2019; Zhao et al., 2020) shows that these scenarios are the most widely adopted. Fig. 3.1 shows the comparison of monthly horizontal solar radiation and external temperature trends in 2020 and 2100 for Rome and Berlin, considering the RCP 4.5. The RCP 4.5 scenario is called the stabilization emission scenario, and as shown in Fig. 3.1, it can be seen in both cities that efforts to mitigate climate change have been effective. There are few differences between 2020 and 2100, both in terms of horizontal solar radiation and external temperatures. Even in Berlin, it can be seen that in July and August, external temperatures in 2100 tend to be slightly lower than in 2020. The highest differences in external temperatures between 2020 and 2100 are about 4 C in November for Rome and almost 5 C in June for Berlin. Fig. 3.2 shows the comparison of monthly horizontal solar radiation and external temperature trends in 2020 and 2100 for Rome and Berlin, considering RCP 8.5. In this case, it is clear that scenario 8.5, defined as a high-emission scenario, is very critical, as it has a significant impact on both horizontal solar radiation and external temperature. In fact, in 2100 emerges a significant rise in external temperatures in

Table 3.1 Summary of the Representative Concentration Pathways (RCP). RCP

RCP 2.6

RCP 4.5

RCP 6.0

RCP 8.5

Emission scenarios Efforts to curb emissions Renewable energy generation Coal-fired energy generation Emission capture Bicycles Electric cars and trucks for the transport sector Petrol cars and trucks for the transport sector Public transport Average temperature increase ( C) Average rise of sea level (m) Increase in extreme weather Level of adaptation Costs required

Mitigation High Yes No Yes Yes Yes

Stabilization Medium Yes No No Yes Yes

Stabilization Medium Yes Yes No Yes Yes

High Low No Yes No No No

No

Yes

Yes

Yes

Yes 1

No 1.8

No 2.2

No 3.7

0.4 Small Low Low

0.47 Moderate Medium Medium

0.48 Moderate Medium Medium

0.63 Large High High

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Figure 3.1 Comparison of monthly horizontal solar radiation and temperature trends in 2020 and 2100 for Rome and Berlin, Representative Concentration Pathways 4.5.

Figure 3.2 Comparison of monthly horizontal solar radiation and temperature trends in 2020 and 2100 for Rome and Berlin, Representative Concentration Pathways 8.5.

both cities, for most months of the year. The highest differences in external temperatures emerged comparing 2020 with 2100 are about 8 C in August for Rome and March for Berlin.

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3.2.2 The mixed-use energy community The analysis is performed on an energy community consisting of ten identical office buildings and ten identical residential condominiums (consisting of three residential apartments each). Fig. 3.3 shows the weekly electric load trends during the first week of January for an office building and a residential apartment building. As shown in the graph, the offices are closed during the weekend, while the residential buildings have a consistent pattern throughout the week. The thermal system in the community is not powered by electricity. To decrease the variables of the problem, the electrical load of the neighborhood was considered the same for all years, despite climate changes and different locations. For residential buildings, the hourly electrical load of a real building was detected from the bills and reported equal for each apartment, given that the user type is identical. The residential buildings are equipped with electric vehicle (EV) charging stations. As regards the residential EV charge, a 24-kWh Nissan Leaf, with an average consumption of 0.1714 kWh/km, was considered to be charged during the night with a power of 3 kW between 9 pm and 10 pm for each apartment, namely each family. This corresponds to an average distance for each EV of 20 km/day. For the ten residential buildings, 30 EVs are considered to be charged between 9 pm and 10 pm. For office buildings, the electrical load requires energy for electrical lighting, electrical office devices, such as printers and PCs, and EV charging stations located in the parking lots of each building. The load for the LED lighting system requires 125 W in each room and turns on when occupants are present. When occupants are present, 75 W of power is required for two personal computers and a printer. As is evident from Fig. 3.3, the peaks are related to the hours scheduled for EV charging. All buildings have EV charging facilities, with the difference being that

Figure 3.3 The weekly electrical load of one office building and one residential condominium.

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Figure 3.4 The overall monthly electrical load of the ten office buildings and the ten residential condominiums.

residential buildings charge all EVs during nighttime hours (for 1 hour until 10 pm), while offices charge vehicles during the day (for 4 hours from 9 am to 12 pm). Also for office buildings, EV charging stations are provided to charge 24-kWh Nissan Leafs. Each building has four stations able to charge with a power of 2.3 kW, with overall power of 9.2 kW available, 8 EVs in 4 hours between 9 am and 1 pm. Each vehicle requires two hours to recover the daily consumption of 5.14 kWh/ day due to an average of 26.8 km per day and an average EV consumption of 0.1714 kWh/km (Mazzeo, 2019). Overall, for the ten office buildings, 40 EVs are considered to be charged between 9 am and 1 pm. Fig. 3.4 shows the total monthly electrical load of the ten office buildings and ten residential condominiums. In terms of annual load, the main contribution is provided by the energy required to charge EVs. The community’s power supply is covered by a 252.20-kW PV system.

3.2.3 Settings of the model in TRNSYS The software TRNSYS (Mazzeo et al., 2020) has been used to calculate the hourly electrical power values of the energy community for Rome and Berlin, considering the two RCP scenarios. Specifically, type 54a was used for the hourly meteorological data from the monthly average values of solar radiation, dry bulb temperature, and humidity ratio. In type 16g, solar radiation data are generally taken at hourly intervals and on a horizontal surface. This component interpolates radiation data, calculates several quantities related to the position of the sun, and estimates radiation on a range of

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surfaces of fixed or variable orientation. Type 16g allows horizontal radiation to be reported on an inclined plane. Type 94a models single or polycrystalline silicon PV panels and estimates hourly electrical power values. Type 25c is a subroutine for printing to output files from other types. The calculation is performed considering the 8760 hours of each year. Only one PV module has been chosen to perform the simulations on the TRNSYS software and therefore to obtain the electrical power values at each European location. The module chosen is Jakson 250 PV module, whose electrical characteristics are: G

G

G

G

G

G

G

G

G

G

The number of cells in the PV module is 72. The open-circuit voltage at reference conditions is 44 V. The short circuit current at reference conditions is 7.45 A. The voltage at the point of maximum power is 35.9 V. The current at the point of maximum power is 6.97 A. The nominal operating temperature of the PV cell is equal to 320.15 K. The area of the PV module is 1.62 m2. The temperature coefficient of the current under the reference conditions is 0.04%/ C. The temperature coefficient of the voltage under the reference conditions is 20.32%/ C. The nominal power, which is the maximum power of the PV module obtained from the product between the voltage and the current at the point of maximum power, is equal to 250.22 W.

The reference conditions are a temperature of 25 C and solar radiation of 1000 W/m2. All these electrical characteristics are provided by the manufacturer and are included in the TRNSYS from type 94.

3.3

Results and discussion

This section shows the performance of the PV system planned for the energy community in Rome and Berlin, considering different climate change scenarios, RCP 4.5 and RCP 8.5. Figs. 3.5 3.8 show the monthly comparison between 2020 and 2100, of total energy generated by PV (includes energy generated and sent to load and grid), excess energy sent to the grid, energy withdrawn from the grid as generated energy does not fully cover the load, and energy generated and sent to load. Figs 3.5 and 3.6 are focused on the RCP 4.5 and 8.5 scenarios of Rome, respectively. Regarding the energy generated by the PV system, in Rome RCP 4.5 (Fig. 3.5), it can be observed that the energy generated in 2100 is less than in 2020 for most months of the year; the energy generated in 2100 is greater than in 2020 in the months of June, July, November, and December. This trend is also confirmed by the excess energy that is sent to the grid; the months in which there is more excess energy in 2100 than in 2020 are June, July, November, and December. Only for 4 months (January to April) in 2100, the

Scenarios for urban resilience

Figure 3.5 Rome, Representative Concentration Pathways 4.5: comparison of PV performance in the years 2020 and 2100.

Figure 3.6 Rome, Representative Concentration Pathways 8.5: comparison of PV performance in the years 2020 and 2100.

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Figure 3.7 Berlin, Representative Concentration Pathways 4.5: comparison of PV performance in the years 2020 and 2100.

Figure 3.8 Berlin, Representative Concentration Pathways 8.5: comparison of PV performance in the years 2020 and 2100.

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energy community takes more energy from the grid than in 2020, for the rest of the months the community still takes from the grid but less than in 2020, this is a positive aspect. Finally, the energy sent to load in 2100 is higher in 2020 in the months of May, June, July, October, November, and December, which is half of the year. In Rome RCP 8.5 (Fig. 3.6), the energy generated is greater in 2100 than in 2020 for half of the months of the year (months of February, March, May, June, July, and August). These months also see a greater amount of excess energy sent to the grid in 2020 than in 2100. In 2100, the community draws less energy from the grid than in 2020 in the months of February, March, May, and June. Finally, the energy sent to load in 2100 is greater in 2020 for 5 months, that is, February, March, May, June, and July, instead, it is the same in January and August. Figs. 3.7 and 3.8 are focused on the RCP 4.5 and 8.5 scenarios of Berlin, respectively. Fig. 3.7 shows the trends of the PV system serving the energy community in Berlin under the RCP 4.5 scenario. Regarding the total energy generated by PV, it can be seen that it is higher in 2100 than in 2020 only in the months of April and June. Regarding the excess energy generated by PV, the values are higher in 2100 than in 2020 only in the months of April, June, and September. The energy that is drawn from the grid increases in 2100 in the averages of January, May, July, August, October, and November. The energy delivered to load in 2100 increases relative to 2020 in the months of February, March, April, June, and September. Fig. 3.8 shows PV trends in Berlin under the hypothesis of an RCP 8.5 scenario. The months in which there is higher total energy generated in 2100 than in 2020 are April, July, August, September, and October. These months are also the months in which there is a greater projection of excess energy. For most months of the year, the demand for energy from the grid in 2100 increases compared to 2020, particularly in January, February, March, April, May, June, and November. The amount of energy sent directly to load is higher in 2100 than in 2020 only in the months of July, August, September, and October. The data show that, in general, scenario 4.5 is a stabilization scenario for both cities, leading to little change from 2020. A comparison of the different scenarios shows that Berlin 8.5 suffers a greater impact than Rome 8.5 in 2100. Although the 8.5 scenario is a worst-case scenario, it is seen that there are greater differences in Berlin than in Rome. Berlin shows a high level of excess energy, but this is not always good because it does not always pay to overload the grid, especially at peak times. From a yearly point of view, Table 3.2 summarizes the percentage increase of the different yearly energy components, such as the generated energy, excess energy, energy from the grid, and energy sent to the load from 2020 to 2100. The table highlights that the energy community’s resilience to climate change strongly depends on the locality and RCP scenario considered. As a consequence, Rome is resilient to climate change only in the RCP scenario 8.5, being the energy generated, in excess and sent to the load greater and the energy from the grid lower in 2100 compared to those in 2020; instead, Berlin is resilient only in the RCP scenario 4.5. For this reason, a strong climate change provides energy benefits in a hot climate,

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Table 3.2 Percentage increase of the yearly generated energy, excess energy, energy from the grid, and energy sent to the load from 2020 to 2100, for Representative Concentration Pathways (RCP) 4.5 and 8.5.

Rome Berlin

RCP

Generated energy variation (%)

Excess energy variation (%)

Variation of the energy from the grid (%)

Variation of the energy sent to the load (%)

4.5 8.5 4.5 8.5

22.26 3.00 4.37 25.59

24.16 4.04 8.58 27.63

20.02 21.44 20.39 2.20

0.02 1.76 0.70 23.70

while a stable climate change gives rise to an improvement in the energy community performance in a cold climate. Climate change mostly influences the generated energy and excess energy compared to the energy drawn from the grid and sent to the load. All variations are greater in the continental climate of Berlin, which is colder than the Mediterranean climate of Rome and can exploit a lower insolation level.

3.4

Conclusions

Cities are vulnerable to a variety of unforeseen change scenarios, which can lead to rapid changes in the lives of the population. Resilience is a concept that indicates a city’s ability to adapt and recover from an unforeseen shock. Changes can be due to climate change, pandemics, and wars. All scenarios are unfortunately present today. The question then arises as to whether cities are ready to pick themselves up and deal with these changes without too much stress. Renewable energy sources are of great importance and their role is expected to become increasingly central to the life of cities. This work highlights the performance of the same hypothetical energy community located in two European cities with very different climates. According to the Ko¨ppen climate classification, Berlin is classified as a Warm-summer humid continental climate “Df and b,” Rome as Mediterranean climate “Csa.” The community consists of both residential and office buildings to have a hypothetical mixed community. The community’s electricity supply can come from a PV system that fully serves the area or from the grid. The electrical energy required by the load does not include the thermal systems, but it covers the services, lighting, and recharging of EVs. It should be noted that the peaks of electricity demand occur precisely when recharging EVs. Two different climate change scenarios were considered, which consider different mitigation policies, the RCP 4.5 and RCP 8.5 scenarios, that is, the stabilization and high emission scenarios, respectively. The hourly electrical power values are calculated in TRNSYS software, considering the years 2020 and 2100.

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A comparison of the different scenarios shows that Berlin RCP 8.5 suffers a greater impact than Rome RCP 8.5 in 2100. Although the RCP 8.5 scenario is a worst-case scenario, it is seen that there are greater differences in Berlin than in Rome. Berlin shows a high level of excess energy, but this is not always good because it does not always pay to overload the grid, especially at peak times. Strong climate change provides energy benefits in a warm climate, while stable climate change results in improved energy community performance in a cold climate. Climate change mainly affects the energy generated and the energy in excess compared to the energy taken from the grid and sent to the load. All changes are greater in the Berlin continental climate, which is colder than the Rome Mediterranean climate and can take advantage of a lower insolation level. This work evaluates the effect of climate conditions on an urban district, for different locations by varying the climate scenario, considering both pessimistic and optimistic future mitigation of greenhouse emissions. The other parameters that may affect the district’s performance are the type of PV module, its efficiency, installed power, and load trend. The choice of PV module impacts the production of electricity since if the PV module had been selected with higher efficiency, the PV production will be higher, resulting in more excess energy and greater satisfaction of the load. The positive effect is that in this way the load is more satisfied, the negative one is that it produces more excess energy. As far as the installed power is concerned, if the installed PV power was higher, there would be more excess energy production and a more satisfied load. The work analyzes an urban district consisting of a mixed load. It is evident from the results that charging EVs requires a large amount of electricity. Electrical vehicles are charged during the morning for office buildings and the night for residential buildings. If the load was purely residential, there would be the disadvantage of an increase of energy in excess and a decrease in satisfied load, because the load reaches its peak during the night. On the other hand, if the district consisted only of offices, with daytime vehicle charging, there would be a dual benefit of increasing load satisfaction and reducing excess energy.

Acknowledgment The authors are grateful to Professor Giuseppe Oliveti for his constant research support.

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Jerez, S., Tobin, I., Vautard, R., et al. (2015). The impact of climate change on photovoltaic power generation in Europe. Nature Communications, 6, 10014. Available from https:// doi.org/10.1038/ncomms10014, ISSN: 2041-1723. Kosai, S., & Unesaki, H. (2020). Short-term vs long-term reliance: Development of a novel approach for diversity of fuels for electricity in energy security. Applied Energy, 262 (114520). Available from https://doi.org/10.1016/j.apenergy.2020.114520. Mazzeo, D. (2019). Nocturnal electric vehicle charging interacting with a residential photovoltaicbattery system: A 3E (energy, economic and environmental) analysis. Energy, 168, 310 331. Available from https://doi.org/10.1016/j.energy.2018.11.057, ISSN: 0360-5442. Mazzeo, D., Matera, N., De Luca, P., Baglivo, C., Congedo, P. M., & Oliveti, G. (2021a). A literature review and statistical analysis of photovoltaic-wind hybrid renewable system research by considering the most relevant 550 articles: An upgradable matrix literature database. Journal of Cleaner Production, 295, 126070. Available from https://doi.org/ 10.1016/j.jclepro.2021.126070, ISSN: 0959-6526. Mazzeo, D., Baglivo, C., Panico, S., & Congedo, P. M. (2021b). Solar greenhouses: Climates, glass selection, and plant well-being. Solar Energy, 230, 222 241. Available from https://doi.org/10.1016/j.solener.2021.10.031, ISSN: 0038-092X. Mazzeo, D., Matera, N., De Luca, P., Baglivo, C., & Congedo, P. M. (2020). Worldwide geographical mapping and optimization of stand-alone and grid-connected hybrid renewable system techno-economic performance across Ko¨ppen-Geiger climates. Applied Energy, 276, 115507. Available from https://doi.org/10.1016/j.apenergy.2020. 115507, ISSN: 0306-2619. Meerow, S., Newell, J. P., & Stults, M. (2016). Defining urban resilience: A review. Landscape and Urban Planning, 147, 38 49. Available from https://doi.org/10.1016/j. landurbplan.2015.11.011, ISSN: 0169-2046. Mehryar, S., Sasson, I., & Surminski, S. (2022). Supporting urban adaptation to climate change: What role can resilience measurement tools play. Urban Climate, 41, 101047. Available from https://doi.org/10.1016/j.uclim.2021.101047, ISSN: 2212-0955. Menyah, K., & Wolde-Rufael, Y. (2010). CO2 emissions, nuclear energy, renewable energy and economic growth in the US. Energy Policy, 38(6), 2911 2915. Available from https://doi.org/10.1016/j.enpol.2010.01.024, ISSN: 0301-4215. Mu¨ller, J., Folini, D., Wild, M., & Pfenninger, S. (2019). CMIP-5 models project photovoltaics are a no-regrets investment in Europe irrespective of climate change. Energy, 171, 135 148. Available from https://doi.org/10.1016/j.energy.2018.12.139, ISSN: 0360-5442. O’Farrell, P., Anderson, P., Culwick, C., Currie, P., Kavonic, J., McClure, A., Ngenda, G., Sinnott, E., Sitas, N., Washbourne, C.-L., Audouin, M., Blanchard, R., Egoh, B., Goodness, J., Kotzee, I., Sanya, T., Stafford, W., & Wong, G. (2019). Towards resilient African cities: Shared challenges and opportunities towards the retention and maintenance of ecological infrastructure. Global Sustainability, 2. Available from https://doi. org/10.1017/sus.2019.16. Olazabal, M., & Pascual, U. (2016). Use of fuzzy cognitive maps to study urban resilience and transformation. Environmental Innovation and Societal Transitions, 18, 18 40. Available from https://doi.org/10.1016/j.eist.2015.06.006, ISSN: 2210-4224. Pe´rez, J. C., Gonza´lez, A., Dı´az, J. P., Expo´sito, F. J., & Felipe, J. (2019). Climate change impact on future photovoltaic resource potential in an orographically complex archipelago, the Canary Islands. Renewable Energy, 133, 749 759. Available from https://doi. org/10.1016/j.renene.2018.10.077, ISSN: 0960-1481. Rus, K., Kilar, V., & Koren, D. (2018). Resilience assessment of complex urban systems to natural disasters: A new literature review. International Journal of Disaster Risk

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Reduction, 31, 311 330. Available from https://doi.org/10.1016/j.ijdrr.2018.05.015, ISSN: 2212-4209. Sajjad, M., Chan, J. C. L., & Chopra, S. S. (2021). Rethinking disaster resilience in highdensity cities: Towards an urban resilience knowledge system. Sustainable Cities and Society, 69, 102850. Available from https://doi.org/10.1016/j.scs.2021.102850, ISSN: 2210-6707. Sapkota, A., Lu, Z., Yang, H., & Wang, J. (2014). Role of renewable energy technologies in rural communities’ adaptation to climate change in Nepal. Renewable Energy, 68, 793 800. Available from https://doi.org/10.1016/j.renene.2014.03.003, ISSN: 0960-1481. Tyler, S., Nugraha, E., Nguyen, H. K., Nguyen, N. V., Sari, A. D., Thinpanga, P., Tran, T. T., & Verma, S. S. (2016). Indicators of urban climate resilience: A contextual approach. Environmental Science & Policy, 66, 420 426. Available from https://doi.org/10.1016/j. envsci.2016.08.004, ISSN 1462 9011. Wilden, D., & Feldmeyer, D. (2021). Measuring knowledge and action changes in the light of urban climate resilience. City and Environment Interactions, 10, 100060. Available from https://doi.org/10.1016/j.cacint.2021.100060, ISSN: 2590-2520. Zhao, X., Huang, G., Lu, C., Zhou, X., & Li, Y. (2020). Impacts of climate change on photovoltaic energy potential: A case study of China. Applied Energy, 280, 115888. Available from https://doi.org/10.1016/j.apenergy.2020.115888, ISSN: 0306-2619.

Urban resilience through green infrastructure

4

Pinar Pamukcu-Albers1, Joa˜o C. Azevedo2, Francesca Ugolini3, Adriana Zuniga-Teran4 and Jianguo Wu5 1 Department of Geography, University of Bonn, Bonn, Germany, 2Centro de Investigac¸a˜o de Montanha, Instituto Polite´cnico de Braganc¸a, Braganc¸a, Portugal, 3Istituto per la Bioeconomia—Consiglio Nazionale delle Ricerche, Sesto Fiorentino, Italy, 4School of Geography, Development & Environment, Udall Center for Studies in Public Policy, University of Arizona, Tucson, AZ, United States, 5School of Life Sciences, School of Sustainability, Arizona State University, Tempe, AZ, United States

4.1

Introduction

“A resilient city is one that anticipates, plans, and acts to prepare for and respond to unexpected crises” (Pamukcu-Albers et al., 2021, p. 667). Resilience has become an important goal in urban systems since the highly uncertain effects of climate change in cities started to be felt. Cities are becoming more vulnerable to climate change day by day due to their already dense but still growing population, increasing demand for resources and ecosystem services, and the physical properties of urban systems. Due to settlement, transportation, and economic reasons, the density of impervious areas in and around cities is increasing persistently. Cities are expanding and, moreover, centers within the city are being increasingly linked to each other. In many cases, not only green areas are replaced by gray areas, but also green and blue areas are fragmented for various reasons, ecosystems are degraded, and surface water resources are depleted or polluted. This means that cities are a unique type of novel ecosystems, with many hydrological and ecological functions severely impaired. Urban resilience against climate change can hardly be addressed in cities where water management (stormwater control, flood risk, wastewater treatment, rising of sea level, water scarcity, etc.) is insufficient and effects of climate change such as heat island, heat waves or biodiversity loss threaten the safety, vital services such as water and food supply, and health of people living in the city. Scientific research on urban resilience has increased quickly during recent decades. A number of new studies have discussed the various definitions, historical developments, and key components and principles of the concept of urban resilience (Chelleri & Baravikova, 2021; Mun˜oz-Erickson et al., 2021), as well as governance and decision-making frameworks to apply resilience in urban settings (Saikia et al., 2021; Wardekker et al., 2020). Some of the aforementioned studies have a particular focus on the research-policy-society nexus. Indeed, policymakers Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00018-4 © 2023 Elsevier Ltd. All rights reserved.

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are increasingly active in making cities more sustainable from different perspectives (e.g., green mobility, energy efficiency, waste management, greenery) and committed to meeting the Sustainable Development Goals (SDGs) (UN, 2015a) and the targets of the Paris Agreement (UN, 2015b). The recovery plan recently delivered by the European Commission to support member states to withstand health, economic, and social impacts of the COVID-19 pandemic aims also to support sustainable development and city resilience, which is addressed through afforestation in urban areas. This is a good example of how urban resilience has become central in public policies. The resilience of cities depends greatly on protecting biodiversity and providing habitats (ecological resilience), managing water sustainably (water resilience), reducing the effects of heat island and heat waves (climate resilience), and assuring human health and social cohesion (social resilience) (Leichenko, 2011; Johannessen & Wamsler, 2017; Yang et al., 2021; Wardekker, 2021). In addition, the resilience of the city is not just about solving a single problem related to climate change or any other crisis, or achieving a single goal. It usually addresses complex problems involving multiple causes and effects with several goals, according to the complexity of urban systems. For instance, focusing on climate change only and not on urban growth can underestimate consequences and, in the end, be useless for adaptation (Chapman et al., 2017). Urban resilience refers to the “general resilience” of the urban landscape, not just the “specified resilience” to climate change (Wu & Wu, 2013). Nature-based solutions (NbS), as resilient intensifier practices to withstand stresses and shocks and improve coping capacity, contribute to the protection and sustainable management of ecosystems, provide ecosystem services that support human well-being and quality of life, ensure resource efficiency, and contribute to the sustainable living in, and sustainable development of, cities (Liu et al., 2021). Restoring and protecting forests and wetlands in a watershed to conserve water resources, regulate water flow and prevent soil erosion, create green roofs and parks to reduce the heat wave effect in cities, use permeable surfaces for stormwater control, and restore coastal habitats to increase carbon sequestration and contribute to climate change mitigation are some examples of NbS.1 Urban green infrastructure (UGI), as a nature-based infrastructure-related approach,2 is a strategically planned and interconnected network of natural and seminatural areas that contribute to ecosystem services through NbS (EC, 2013; Ferreira et al., 2021). UGI is often combined with blue (e.g., natural drainage systems, lakes, rivers, creeks, washes) and gray (culverts, downspouts, pervious pavement, slope, curb cuts) infrastructures to regulate hydrological processes, through, for example, direct runoff to green areas for in situ infiltration (Staddon et al., 2018). Hybrid infrastructure systems (blue green gray) can manage stormwater in a decentralized way, supporting gray infrastructure systems to reduce flooding risk and improve water quality. 1 2

https://www.naturebasedsolutionsinitiative.org/what-are-nature-based-solutions/. https://www.iucn.org/commissions/commission-ecosystem-management/our-work/nature-basedsolutions.

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To ensure urban resilience against climate change and other disturbances, NbS should become indispensable pillars of city policies, plans, and governance. Efforts to promote UGI need to be inclusive and contribute to increasing social justice and equity regarding the distribution and accessibility of UGI, which tend to be located in wealthy white neighborhoods, and to enhancing the procedural aspect of policymaking (UGI incentive programs), landscape design (types of amenities that favor underrepresented social groups), and the operation and maintenance (interactional justice) that ensures UGI’s function over time (Zuniga-Teran & Gerlak, 2019; Zuniga-Teran et al., 2021). In addition, urban planners and policymakers need to plan for sustainable urban developments, taking into account not only the restoration of green spaces and renaturalization of the urban landscape for today but also the ecological (biophysical), topographic, hydrological, and climatological responses of the city to the future effects of climate change. Thus it is essential to assess the effects and disturbances related to climate change, either natural or induced or amplified by human activities. Moreover, along with the services to be provided by ecosystems, it is necessary to address social issues and adaptation of climate change (Dumitru et al., 2020). Addressing social problems is to have inclusive processes that encompass the voices of vulnerable groups (Zuniga-Teran & Gerlak, 2019). With this approach, urban resilience is both a process that plays a role in city management or governance and the result that will serve the city’s purposes against climate change (Mun˜oz-Erickson et al., 2021).

4.2

Key components for sustainable, livable, and resilient cities through green infrastructure

It is now well documented that green spaces benefit physical, mental and social well-being (Madureira et al., 2018; Mavoa et al., 2019; Meyer-Grandbastien et al., 2020), as they allow individuals to connect to nature and to meet their basic needs for nature, as supported by the “biophilia hypothesis” of Wilson (1984). Thus green spaces enhance their quality of life (Ma et al., 2019; Vujcic et al., 2019). UGI, a network of strategically well-planned and interconnected green spaces, increases the quantity and quality of ecosystem services. UGI provides many ecological, social, and economic benefits through regulating runoff, storing water, reducing flooding, reducing wind speed, providing fresh air, sequestering carbon, regulating climate, providing habitat for species, increasing biological diversity, reducing energy consumption, and improving public health, thus enormously contributing to promoting urban resilience (Staddon et al., 2018). This is an important component of urban resilience, but it takes a lot more to address resilience in cities. It requires the successful integration of ecological (biological), water, social, and climate resilience to ensure the “general” resilience of the city to withstand unforeseen disturbances (not just the “specified resilience” to climate change) and adapt to changing conditions (Fig. 4.1). The concept is also related to sustainability and livability. Moreover, it is a socio-ecological approach that considers not only spatial features

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Figure 4.1 Urban resilience via urban green infrastructure: some key components and dimensions (drivers, e.g., climate change, natural hazards, anthropogenic and economicbased disturbances).

(heterogeneity, scales, etc.) but also human ecosystem interactions, socioeconomic infrastructure and processes and consequences of these interactions.

4.2.1 Urban ecological resilience Conservation of biodiversity and provision of habitats are integral parts of urban resilience (Colding, 2007). UGI contains essential components of biodiversity in cities at several scales, supporting genetic diversity, species diversity, and ecosystem diversity. Ecosystem structure is based on species diversity that assures a series of ecological processes and functions that results in ecosystem services and well-being delivered to humans. Urban landscapes include a diversity of habitats and ecosystems as part of their structures that contribute to human well-being by providing diverse ecosystem services and by avoiding or minimizing damages or negative impacts of urbanization-induced disturbances. Through these roles, UGI is the basis for a series of provisioning and regulating ecosystem services, directly and indirectly, demanded by urban communities. It is this array of ecosystem services supported by UGI that makes green infrastructure key to urban resilience. Without biodiversity and ecological processes and functions, the city could hardly assure any capacity to deal with and fight against climate, social, and

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economic crises. For example, it is through biodiversity and functional ecosystems that green infrastructure improves air quality via capturing dust particles (Wro´blewska & Jeong, 2021) and other pollutants, consequently reducing health problems. It is also through vegetation that UGI reduces energy demand in cities (Kumar et al., 2019) and captures carbon dioxide from the atmosphere which mitigates climate change. UGI seen at a broad scale is a network (patches, corridors, pathways, or conduits) favoring or controlling the movement of plants, animals, nutrients, sediments, energy, etc. (as well as people) in the city contributing to landscape connectivity and the resilience of green areas and the entire city. Soils in particular are extremely important in mitigating climate change impacts and also in alleviating the impacts of extreme rains, reducing the risk of floods and overflows from the pipe systems, hosting trees, and providing food and several other essential services. They are therefore of the utmost importance and priority components of the urban system that need preservation. Greater awareness of the impacts of impervious surfaces on the environment and human health and of the role of soils and their provision of ecosystem services within the urban area (Calzolari et al., 2016) should thus play a fundamental role in decision-making in cities (Bazzocchi, 2020).

4.2.2 Urban water resilience UGI plays a crucial role in managing water. It reduces flood risk, regulates the speed and timing of stormwater runoff, reduces water demand and increases water efficiency through rainwater harvesting, improves water quality, and prevents sedimentation and soil erosion. This is especially important in cities located in wet regions that have combined sewer systems to manage stormwater and wastewater due to possible overflow when there is too much runoff entering the combined system, resulting in sewage discharged into water bodies that can pose severe health threats to residents. UGI systems support or contribute to the resilience of engineering systems through four Rs—robustness (ability to reduce the impact of a disturbance), redundancy (having several systems in place to take over in case one fails), resourcefulness (ability to identify and respond to a disturbance), and rapidity (time it takes the failed system to return to functioning conditions) (Bruneau et al., 2003; Cimellaro, 2016; Zuniga-Teran & Staddon, 2019; Zuniga-Teran et al., 2020). Although cities located in arid regions usually do not have combined sewer systems, they are also turning to UGI for reasons related to urban resilience. These cities look at UGI as a rainwater harvesting infrastructure that can reduce water use for landscape irrigation and other nonpotable uses, as well as a decentralized stormwater management infrastructure that can reduce flooding (Zuniga-Teran & Tortajada, 2021), sometimes as part of citizen-driven initiatives, as in the case of Tucson, Arizona (Gerlak et al., 2021a,b).

4.2.3 Urban climate resilience In addition to flood mitigation, mentioned above, UGI provides air circulation (ventilation) through green corridors and generates a cooling effect due to evapotranspiration and shading. This reduces the heat island effect and improves air quality in

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cities (Rehan, 2016). Tree canopy reduces wind speed and increases relative humidity, affecting perceived temperature (Greenbelt Foundation, 2020). Moreover, UGI regulates microclimate depending on weather conditions that can provide shade and outdoor shelter during heat waves (Wang et al., 2015) and builds resilience to drought. Heat abatement through greening can also reduce the energy consumption in buildings, which peaks during heat waves. This way, UGI can prevent the overburden of electrical systems and potential blackouts.

4.2.4 Urban social resilience In addition to ecological, hydrological, and climate resilience, UGI contributes to social resilience. It is well documented that people who are connected to broader networks fare better during disasters, as they are able to connect to resources that allow them to withstand, respond, and adapt to change and maintain functionality (Adger, 2000; Berkes & Ross, 2013; Caniglia et al., 2016). UGI, due to its presence, spatial structure and multifunctionality, can address vulnerabilities related to drivers, such as climate change (flooding risk, heat, drought), provides spaces for physical activity and enjoyment of nature (public health) and promotes social interaction which is related to social cohesion and networks (Zuniga-Teran et al., 2020). Therefore UGI as a network of more or less natural sites is recommended to increase connectivity of social and ecological systems and connect citizens from all neighborhoods to the benefits of UGI systems (Zuniga-Teran & Gerlak, 2019), which enhances community resilience.

4.3

Access, design, and implementation of green infrastructure

Urban resilience is part of the SDGs for 2030. SDG 11 “Sustainable cities and communities: make cities and human settlements inclusive, safe, resilient and sustainable” (UN, 2015a) is directed to and focused on the components of urban resilience. One of the targets of this goal is to “provide universal access to safe, inclusive and accessible, green and public spaces, in particular for women and children, older people and people with disabilities.” However, access to urban green spaces is still an issue in many parts of the world. For instance, the deprivation of green areas to lower income neighborhoods is well documented (Pearsall & Eller, 2020; Huerta, 2022). In addition, in Europe, there are clear differences in access to green spaces in densely urbanized Mediterranean cities of low green space availability as compared to northern European cities (Wolff & Haase, 2019). In addition to the area available, accessibility should consider the quality of green spaces to enhance ecosystem services and well-being. There is evidence that cleanliness and a sense of order in green areas contribute to alleviating mental stress and depression (Meyer-Grandbastien et al., 2020; Jabbar et al., 2021), while poor maintenance and nonattractive design with dense vegetation obstructing the view (Lamb & Purcell,

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1990; Bjerke et al., 2006; Roovers et al., 2006; Ignatieva et al., 2017) can even increase discomfort and fear (Skogan & Maxfield, 1981; Zelinka & Brennan, 2001; Sreetheran & van den Bosch, 2014). Therefore the specific characteristics of green spaces and the physical and social outdoor activities that they facilitate are as important as the quality of the greenery itself. Green areas are most often visited by women when there is a great diversity of users and uses (Franck & Paxson, 1989), including family-related and child-care activities (Westover, 1986; Carr et al., 1992; Hutchison, 1994), physical activities (Krenichyn, 2004; Ode Sang et al., 2020), and social opportunities together with friends, mothers, or care workers (Curson & Kitts, 2000; Taplin et al., 1998) that increase the perception of safety. However, safety perception is related to a broader context depending on factors such as the lack of social inclusion, trust, and community identity within and between generational or cultural groups that may influence people in the use of local public green spaces (Seaman et al., 2010). In this regard, several studies have demonstrated that the involvement of communities—including minorities and lowincome dwellers—in decisional and operational processes can avoid gentrification and make choices more democratic, enhancing integration and collaboration and enjoyment of public places (Buijs et al., 2016; Lieberherr & Green, 2018; Anguelovski et al., 2018, 2020). Existing green (parks, forests, riparian corridors, green corridors, etc.) and blue (lakes, wetlands, floodplains, etc.) spaces in the city are important elements for UGI. They should be protected and included in the UGI network to provide different services (multifunctionality) to people and the city and to increase the resilience of the city against not only climate change but also other drivers and pressures (Fig. 4.2). In other words, UGI must be conceived and designed to be multifunctional and well integrated with the rest of the urban landscape. Existing but degraded green areas should be restored and returned to the network. Another way to expand the UGI network in the city is to restore and integrate spatially and functionally brownfields (abandoned or old industrial areas/mining areas, empty and abandoned areas, unused roads, unused railways, like in Berlin or New York) and areas under energy transmission lines that are seen as potential green areas. Roadside planting and restoration of river corridors in the city are also important green corridors that, with other local functions, will provide connectivity among main centers (hubs) of the network. According to Zuniga-Teran et al. (2020), the evaluation of the impact of UGI on urban resilience requires a multidimensional assessment addressing policies related to urban resilience, performance of engineering systems, connectivity between UGI sites for both people and species, and social resilience as UGI provides spaces for social interaction. By improving the performance of the UGI, Wang et al. (2021) show that ecosystem services-based multifunctionality analyses are helpful to urban planners and designers in finding optimal solutions. In particular, multifunctional landscape and resilient urban design and planning must seriously consider the 30 30 40 guideline (“optimal landscape compositions for biodiversity and therefore ecosystem services with no more than 30% intensive, no less than 30% extensive or protected -including 10% to 20% high quality habitat- and 40%

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Figure 4.2 Needs and pathways for designing/planning resilient cities.

intermediate intensity use” (Lavorel et al., 2022, p. 916)) to ensure critical natural capital and must explicitly deal with the widely recognized tradeoffs and synergies among key ecosystem services. In addition to multidimensional and multifunctionality assessments, scenario-based approaches are essential for designing and planning resilient urban systems. While both general approaches in terms of urban ecosystem services trade-offs/synergies and their implications for urban planning and management as discussed by Liu and Wu (2022) are needed, the “urban landscape planning/management” approach, in other words “the whole landscape approach”, seems more consistent with the notions of “general resilience” and urban sustainability.

4.4

Strategies and policies for building city resilience

The increasing awareness of climate change impacts (and more recently the effects of the COVID-19 pandemic) has raised the importance of mitigation and adaptation solutions globally. Based on the IPCC Report (IPCC, 2014), the Paris Agreement in 2015 (UN, 2015b) set a bond between 196 countries to limit global warming to 2 C compared to preindustrial levels by reducing greenhouse gas emissions and achieving climate neutrality by 2050, which was reinforced by the Glasgow climate pact in 2021 (UNFCCC, 2021a,b). In Europe, such an objective has been endorsed by the EU Parliament and Council through the European Climate Law (EC, 2020b),

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which aims to provide a direction by setting a pathway to climate neutrality, to set in legislation the EU’s 2050 climate-neutrality objective, and also to contribute to the implementation of the Global Sustainable Goals (UN, 2015a). Lately, the EU Adaptation Strategy (EC, 2021) defines how the “European Union can adapt to the unavoidable impacts of climate change and become climate resilient by 2050,” by making “adaptation smarter, swifter and more systemic, and by stepping up international action on adaptation to climate change.” Achieving sustainability goals and resilience within the urban environment embraces measures of urban planning and management that involve all the components mentioned above for which transdisciplinary collaboration between decision makers, stakeholders, urban planners, landscape ecologists, and designers is crucial (Ahern, 2013). In urban planning and management, adaptation strategies and measures imply UGI and NbS to ameliorate living conditions and environmental threats, thanks to the functions and services that trees and green areas provide (e.g., effects water cycle and regulation, thermal comfort, well-being, and health). The effects of UGI on urban resilience vary because UGI is composed of elements at different scales and used for different purposes, which will also respond to different effects of climate change or other drivers. For instance, at the country level, China has launched their “Sponge City” initiative to address severe flooding that occurred in 2014, which caused death and costly damage to the urban infrastructure in 137 cities. The Sponge City initiative started with 16 cities as pilot projects, the first of which is Wuhan. The goal of the initiative is to absorb the totality of rainwater that falls in the city, putting the water to beneficial use through UGI (Staddon et al., 2018). At the city level, Tucson, AZ is investing in resilience with UGI at the core of the plans. For example, in 2020, the City of Tucson launched the Million Trees initiative.3 The goal is to have one million trees planted by 2030. In addition, the city launched their “Storm to Shade” initiative that aims to create shade through UGI using stormwater as the source for irrigation. This way, the city can adapt to increasing heat, while reducing flooding risk.4 At the neighborhood/ town level, Bicester in the United Kingdom is an eco-town that accommodates 6000 homes and its associated social, commercial, and ecological infrastructure. The goal is to create a town with integrated water management systems, while working with stakeholders and community members. Construction of the town started in 2014 with 393 net-zero carbon homes (Staddon et al., 2018). The scale can be that of micro-scale and pocket parks, which are used for drainage of the water from pavements, or medium-scale (neighborhood scale: green roofs, rain gardens) or large scale (citywide, regional, or national: urban parks, green corridors, urban agriculture) and they all can be a part of the green infrastructure. Greening the public realm (streets, roads, avenues, boulevards, plazas) provides UGI and their benefits to all population groups (Zuniga-Teran & Gerlak, 2019), while household or individual site-scale greening provides benefits to very limited people.

3 4

#TucsonMillionTrees: https://www.tucsonaz.gov/newsnet/mayor-romero-launches-tucsonmilliontrees. https://www.govermeta.com/US/Tucson/110658501399328/Storm-to-Shade-Chubasco-a-Sombra.

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The enhancement and enlargement of green spaces but also the reduction of soil sealing, as soil is a major supporting element in UGI, are expected actions. In this regard, the initiative “Towards no net land take” (SEP, 2016) applied in local projects introduced the soil ecosystem services assessment as an urban planning decision tool. Indeed, new building areas (and enhancement measures for green spaces) can be identified on the basis of the soil quality and function (i.e., finding a tradeoff for new buildings in areas where soils provide limited ecosystem services). In the long term, this strategy contributes to connecting and strengthening UGI, to increasing biodiversity and to more effectively mitigate and adapt to climate change impacts as promoted by the European strategy on Adaptation to Climate Change (EC, 2021). Another important feature is biodiversity. According to IPBES (2019), humanity is the main cause of decline of marine and terrestrial ecosystems and is threatening species conservation. Nature and biodiversity conservation are extremely important to ecosystem resilience, as they are at the core of the provision of a wide range of services. The increasing awareness of the biodiversity decline has pushed the parties of the Convention of Biological Biodiversity in the COP15 to define the post-2020 Global Biodiversity Framework, which aims to halt and reverse the decline of biodiversity and promote sustainability, by pushing governments and members of societies to adopt its mission of “living in harmony with nature” (UN, 2021). In Europe, the EU Biodiversity Strategy for 2030 (EC, 2020a) aims to guarantee biodiversity preservation and enrichment not only in natural areas but also in urban settings. This strategy actually advocates for UGI and NbS in urban areas: “The promotion of healthy ecosystems, green infrastructure and nature-based solutions should be systematically integrated into urban planning, including in public spaces, infrastructure, and the design of buildings and their surroundings.” On the basis of this strategy, cities with more than 20,000 inhabitants have to develop Urban Greening Plans by the end of 2021 (article 2.2.8) to include biodiversity, accessible urban forests, parks, and gardens, urban farms, green roofs, and walls, tree-lined streets, urban meadows, and urban hedges, and the connection between spaces, elimination of the use of pesticides, and limit biodiversity harmful practices. Sustainability and resilience cannot avoid the adoption of circular economy and bioeconomy principles on the urban scale. In the currently globalized world, many resources come from distant places, but the current history makes it quite evident that resilience is enhanced when self-sufficiency increases and external inputs are lowered with short flows of energy and resources. This is a central tenet of landscape sustainability science (Wu, 2019, 2021). Therefore decreasing the actual needs by increasing the efficiency in the production and the use of local resources becomes an increasingly important goal. Also, in this context, UGI represents a possible solution, as a source of energy, goods, food and other resources. Urban agriculture and agro-forestry may provide goods and services to benefit human society and the environment, enhancing the resilience of cities. In addition, the application of NbS such as green roofs and green walls would limit the energy demand of buildings and, together with the installation of diffuse renewable energy production systems (solar panels,

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micro-wind turbines) would also likely reduce the dependence of energy from foreign and nonrenewable resources. Finally, it has been documented that there are synergies in the combination of agricultural systems and solar panels, in agrovoltaic systems, where both energy production and agricultural productivity are enhanced (Barron-Gafford et al., 2019). Therefore more research is needed to find other potential synergies between sustainability efforts, with the financial support for scaling up these combined efforts throughout the planet to enhance urban resilience.

4.5

Concluding remarks

Cities are becoming more vulnerable to climate change and other disturbances due to their already dense but still growing population, increasing demands for resources and ecosystem services, and the physical properties of the built environment. A resilient city requires a successful integration of ecological, water, social, and climate resilience components to withstand not only climate change but also anthropogenic perturbations, natural hazards, and economic-based unforeseen drivers and pressures. To achieve this goal, urban green spaces must be planned and designed with appropriate criteria and principles to form an interconnected and well-managed green network, properly combined with blue and gray infrastructures. At the same time, some tangible plans, measures, and applicable pathways to the future (e.g., greener cities, urban water decontamination and reuse, urban sprawl easily connected to downtown, green transports, affordable housing, green building, facilities and services, and internet) are needed. These pathways will create opportunities for the application of circular economy and bioeconomy principles. Moreover, decision-makers and planners must pay special attention to equity and justice issues on distribution, accessibility, procedure, rights and responsibilities, recognition, interaction, and mobility (displacement of vulnerable groups to make room for UGI or as a consequence of UGI through gentrification).

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Climate-resilient transportation infrastructure in coastal cities

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Michael V. Martello and Andrew J. Whittle Department of Civil & Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States

5.1

Introduction

Reliable and safe transportation infrastructure systems underpin well-functioning economies and societies, serving as the foundation of supply chains, and providing individual human mobility and access. Infrastructure assets for surface (road, rail, inland waterways, pipelines), marine, and air transportation systems (Table 5.1) are typically designed for a long service life ( . 50100 years) and must perform under a range of extreme loading conditions informed by historic observations of natural hazards. Anthropogenic climate change, driven by greenhouse gas emissions, is increasing global surface temperatures, and diminishing polar sea ice, leading to an increase in mean sea levels. While the long-term severity of these changes in climate can be tempered by emissions reduction and mitigation efforts, significant changes in climaterelated risk are likely under all emissions scenarios (Intergovernmental Panel on

Table 5.1 Common transportation modes and associated transportation infrastructure assets (after National Academies of Sciences Engineering & Medicine (NASEM), 2021). Transportation mode

Infrastructure assets

Surface

Roads, bridges, tunnels, culverts, traffic signals, toll collection systems, intelligent transportation systems (ITS) Tracks, bridges, tunnels, culverts, yards, maintenance facilities, stations, terminals, signals, power systems Bus garages, dedicated busways, ferry docks Pipes, pumping stations, compressor stations, manifolds, storage facilities Channels, locks, dams, terminals

Road

Rail Urban Transit Pipeline Waterways Maritime

Air

Docks, breakwaters, entrance channels, basins, container yards, roads and rail lines, container terminals, warehouses Airports, runways, taxiways, control towers, hangars, access roads, heliports

Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00007-X © 2023 Elsevier Ltd. All rights reserved.

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Climate Change IPCC, 2022). Coupled with long-term trends in regional weather conditions (precipitation and drought patterns, drought cycles, inter-annual tidal cycles) these global trends will result in more frequent and more extreme events1 (tropical and extra-tropical cyclones, extreme rainfall, storm surge, etc.) The resultant increases in stress on existing transportation systems will have wide-ranging effects, including shortened expected asset service lifespans, significant disruptions to the flow of goods and the mobility of individuals, as well as extensive damage to physical infrastructure. Ensuring the resilience of transportation systems to climate change therefore represents a fundamental societal challenge of the 21st century that will inevitably require significant capital investments, as well as paradigms shifts in infrastructure engineering and design. This chapter focuses on the resilience of transportation systems in coastal cities where climate change is expected to cause significant increases in flood exposure due to sea-level rise (SLR) and changes in the magnitude and frequency of extreme precipitation events (as well associated changes to riverine flood exposure2). More than 10% of the global population lives in low-elevation (urban or semiurban) coastal zones (LECZ, ,10 m above sea level; Columbia Climate School Center for International Earth Science Information Network (CIESIN), 2013) including 94.7 M people in the United States (29% of the population). Hallegatte et al. (2013) estimated an average annualized loss (AAL) of $6B due to flooding in 136 major coastal cities worldwide in 2005. By 2050 they project AAL will increase to $52B due to socio-economic development alone (including growth of transportation assets). They estimate the cost of adaptation projects to maintain the same level of flood exposure in 2050 (for an estimated SLR of 20 cm) will be $1 T/year. Their analyses also identify the 20 cities with the highest AAL in 2050 (and ratios of AAL to projected GDP), a list that includes 5 US cities.3 Many of these coastal cities serve as major maritime and air transportation hubs that support global trade and travel, and by virtue of their locations, related transportation infrastructure assets are often vulnerable to coastal flooding. For example, Kansai Airport, located in Japan, was constructed offshore in Osaka Bay in water depths exceeding 20 m. The runways, which are undergoing sizable long-term subsidence, are nominally located 3 m above sea level and are protected by a 4.4 m high perimeter seawall (Le et al., 2019). During Typhoon Jebi in 2018 the walls were overtopped by the storm surge and high waves (estimated at 4.2 m), resulting in flooding of the runways and airport closure that lasted more than 3 days. With climate change, such flood-related disruptions are expected to become increasingly frequent, posing a systemic risk to air transportation infrastructure. By 2100, 1

Estimates of effects of climate change on extreme events constitute a rapidly changing facet of climate science. Tropical cyclones are drivers of extreme rainfall and surge, but their joint hazards have only recently been investigated (Gori et al., 2022). Transportation facilities are also affected indirectly by cascading effects. For example, loss of vegetation due to forest fires can promote increased landslide hazards (Gariano & Guzzetti, 2016). 2 Anthropogenic subsidence is a major factor in flood risk for some delta cities, especially those that rely on local groundwater sources (Jakarta, Ho Chi Minh city). 3 Miami, New York-Newark, New Orleans, Tampa-St Petersburg, Boston.

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Yesudian and Dawson (2021) estimate than more than 100 (out of a total of 1238 LECZ airports) will lie below mean sea level, with potential for annual disruption of 20% of global commercial airline routes. Similar climate resilience challenges face surface transportation networks, with significant potential service impacts to roadway networks (Testa et al., 2015) and underground rapid transit systems in LECZ, as illustrated by the extensive damage to the transportation tunnels in New York due to Hurricane Sandy (Aerts et al., 2013; Nikolaou et al., 2020). Absent adaptation, the wide-ranging challenges posed by climate change and SLR represent an existential threat to surface transportation infrastructure systems. Here we address this topic by asking a number of basic questions: (1) How can we define and measure the climate change resilience of transport infrastructure systems? (2) How can we estimate the expected impacts of climate change and SLR on a given infrastructure system? And perhaps most importantly, (3) how can we successfully adapt infrastructure and improve the resilience of transport systems to climate change and SLR?

5.2

Climate change resilience of transportation infrastructure

The concept of resilience features prominently in a variety of fields, ranging from ecology to social sciences, engineering, and climate science and serves as a boundary object between these fields (Brand & Jax, 2007). Definitions across fields vary depending on the indeterminacy of a system of interest, with resilience of closed engineered systems typically characterized by the return to a predefined system state (i.e., single equilibrium) while resilience of more indeterminate/open systems require a greater number of (normative) value judgements to describe the system itself and its multiple potential equilibria (Davidson et al., 2016; Meerow et al., 2016). There are some aspects of resilience that are generally recognized across domains, despite the contextual nuances of domain-specific definitions. The National Academy of Science, Engineering, and Medicine (NASEM) defines resilience as the ability of a system to plan and prepare for adverse events and effectively absorb, recover, and adapt to adverse events (National Academies of Sciences Engineering & Medicine (NASEM), 2012). Linkov and Trump (2019) further suggest this definition is threat agnostic, separate from conceptions of risk, and that resilience is an intrinsic property of a system that describes its ability to respond to any possible disruption event. While such a definition can be useful in the context of system design, expansion, and multithreat analysis, it is ultimately too abstract to apply when considering a specific class of exposures and associated risks (e.g., climate change-related risks which are of primary interest here). Indeed, the physical impacts of different types of risk on individual system components can vary substantially, and hence, the concept of resilience requires a more granular interrogation of exposure-specific system characteristics. In this chapter we adopt

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the following definition of resilience presented by Intergovernmental Panel on Climate Change (IPCC) (2014): Resilience is the endogenous capacity of the system to cope with a predefined exogenous perturbation, responding or reorganizing in ways that maintains its perceived essential function, identity, and structure, while also maintaining the capacity for adaptation and transformation.

Ultimately, the resilience of a transportation infrastructure system is dependent on (1) the exogenous (i.e., external) exposure event(s) of interest, (2) intrinsic/ endogenous system characteristics that describe its response to exposure, and (3) a description of its core functionality, requiring some degree of subjective/normative judgement to contextualize system performance (e.g., daily number of passengers carried by the system). Martello et al. (2021) provide a topological mapping of concepts that inform infrastructure resilience and vulnerability in the context of urban rail transit networks (Fig. 5.1). Consistent with previously established definitions, system exposure, sensitivity, and adaptive capacity inform vulnerability to climate change (Federal Highway Administration (FHWA), 2017; Intergovernmental Panel on Climate Change (IPCC), 2007), while resilience is ultimately affected by vulnerability, adaptive capacity, and contextual characterizations of system performance. The commonly accepted “4Rs” of engineering resilience (Fig. 5.1; Ayyub & American Society of

Figure 5.1 Topology of concepts informing resilience of infrastructure systems to climate change (Martello et al., 2021). Source: From Martello, M. V., Whittle, A. J., Keenan, J. M., & Salvucci, F. P. (2021). Evaluation of climate change resilience for Boston’s rail rapid transit network. Transportation Research Part D: Transport and Environment, 97, 102908. https://doi.org/ 10.1016/j.trd.2021.102908.

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Civil Engineers, 2021; Bruneau et al., 2003) define the endogenous aspects of system resilience: (1) Robustness of the system to the exposure of interest; and (2) its Rapidity (of recovery) inform sensitivity, while (3) inherent topological Redundancy and (4) Resourcefulness in the deployment of available resources inform adaptive capacity. Within this framework, exogenous components of climate change resilience (i.e., projected climate forcings, historical data, expected climate-related events) are synthesized to inform an exposure event of interest. Endogenous components of resilience aim to describe how the physical infrastructure components respond to the exposure of interest (i.e., sensitivity), as well as the ability of the system to maintain functionality during the exposure event (i.e., adaptive capacity). The response of the system to the exposure event is contextualized by normative components of resilience, which aim to describe the relative priority of services across the system, and the time horizon of interest to decision makers. For example, for an urban transit network priority can relate to the distribution of passenger volumes among links within the network (e.g., Dall’Asta et al., 2006; Xing et al., 2017) or though further prioritization of socioeconomic factors to achieve more equitable access (Martello et al., 2021). These factors can include the relative reliance of riders on transit (e.g., inferred rates of car ownership), the relative income of passengers that rely on a given section of a transit line, or subsequent changes in mobility and accessibility of socially vulnerable groups (Sun et al., 2021). Notably, the resilience of a system is affected by permanent changes that can influence its behavior and response to exposure events. Such changes that are made to explicitly support the resilience of the system are typically referred to as adaptations, whereas changes which are perceived to undermine and decrease the resilience of the system can be considered instances of maladaptation (Magnan et al., 2016). Measures undertaken explicitly to promote resilience have the potential to be maladaptive, particularly when such measures result in unintended path dependencies or promote adverse feedback loops that result in negative long-term outcomes (Brown, 2011; Fisichelli et al., 2016; Pelling et al., 2015). Determination of whether an action or measure is maladaptive can be subjective and context dependent, particularly in situations where the benefits are distributed disproportionately across a region or over time.

5.3

Quantifying resilience to climate change and coastal flooding

Quantification of transportation system resilience to climate change requires a working knowledge of present and projected future climate exposure events, an adequate understanding of the relevant physical and organizational characteristics of the system of interest, as well as the ability to situate the system of interest within its socioeconomic and temporal context. Proper consideration of these factors is critical to characterize system performance in response to climate-related exposure

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events. While quantifying resilience may strike some as overly rigorous, a measurement of current system resilience to a set of exposure events can serve as a baseline from which the effectiveness of adaptation measures can be evaluated. Furthermore, the exercise of quantifying resilience to a set of climate stressors enables the identification of potentially vulnerable portions of a transportation system. Resilience quantification metrics for engineered systems can be methodologically classified as either subjective, probabilistic, or recovery curve-based metrics (He, 2019). Recovery curve-based resilience metrics typically recognize a temporal dimension of system response and recovery (Ayyub, 2014; Franchin & Cavalieri, 2015; Henry & Emmanuel Ramirez-Marquez, 2012) and are commonly employed to evaluate transportation networks (e.g., Chan & Schofer, 2016; Li et al., 2017; Martello et al., 2021; Wan et al., 2018; Zhang et al., 2018, 2019). At a high level, recovery curve-based metrics aim to characterize system performance over time, QðtÞ, where a baseline performance during a predisruption phase, Q0 , is compared to system performance during the disruption event (from the start of the response phase at t0 to the end of the recovery phase at t1) which is typically demarcated by a full recovery of baseline system performance at the postdisruption phase as shown in Fig. 5.2 (Wan et al., 2018). Ayyub (2014) notes postdisruption system

Figure 5.2 Generalized conception of system performance under exogenous perturbations (Martello et al., 2021). Source: From Martello, M. V., Whittle, A. J., Keenan, J. M., & Salvucci, F. P. (2021). Evaluation of climate change resilience for Boston’s rail rapid transit network. Transportation Research Part D: Transport and Environment, 97, 102908. https://doi.org/ 10.1016/j.trd.2021.102908.

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performance levels may be diminished after recovery depending on the level of component degradation or may be increased if significant system improvements are made during the recovery process. More formally, the resilience of a system to a predefined exogenous perturbation (e.g., flood event) is the level of system performance maintained during the response and recovery phases of a disruption relative to the expected performance based on a predisruption baseline over the same period. Several authors (Ayyub & American Society of Civil Engineers, 2021; Franchin & Cavalieri, 2015; Martello et al., 2021; Saadat et al., 2019; Zhang et al., 2018) mathematically represent this resilience metric, R, as: Ð t1 R5

t0

QðtÞdt

ðt1 2 t0 ÞQ0

(5.1)

Given the inherently networked structure of transportation infrastructure, graph theoretic measures of overall system connectivity (e.g., network efficiency; Latora & Marchiori, 2001) are an efficient way to characterize system performance of transportation networks (e.g., Ayyub & American Society of Civil Engineers, 2021; Li et al., 2017; Martello et al., 2021; Saadat et al., 2019; Testa et al., 2015; Xing et al., 2017; Zhang et al., 2018, 2019). Based on this definition, the speed of recovery and the shape of the performance curve through the disruption phase have a significant impact on the system resilience. However, cases of transportation network performance during and after natural-hazard events are poorly documented (Dawson et al., 2018). One notable exception is Chan and Schofer (2016) who provide insight into the recovery of the New York City rail rapid transit system to several natural hazards, including Hurricane Sandy. Other authors provide estimates of recovery time by formulating optimal system recovery strategies based on node restoration priority (e.g., Bhatia et al., 2020; Sela et al., 2017), though such studies neglect physical and temporal aspects of recovery and do not attempt to provide meaningful estimates of recovery times. Absent methods for estimating recovery over time, basic assumptions on the shape of the performance curve can approximate temporal recovery pattens. Martello et al. (2021) suggest the shape of the system performance curves through the response and recovery events corresponds to the level of disruption severity, with more severe events requiring a temporary system closure. Regardless of the shape of the recovery curve, the severity of performance loss primarily informs the level of system resilience. In the following subsections, we outline available methods of assessing present and future coastal flood exposure and how flood exposure relates to performance loss.

5.3.1 Assessing present and future coastal flood risk Current climate projections and expected SLR suggest the frequency and severity of extreme weather and coastal flood events will increase throughout the 21st

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century (Buchanan et al., 2016; Kopp et al., 2014). This expected increase in coastal flooding poses particular challenges for urban transportation infrastructure in coastal cities. In particular, current and future coastal flood risk represent a significant threat to rail rapid transit infrastructure (Martello et al., 2021) as demonstrated firsthand by the significant and extensive damage caused by Hurricane Sandy in 2012 (Aerts et al., 2013). In practice, understanding the resilience of transportation infrastructure to climate change requires a reliable and robust characterization of present and expected future climate stressors (i.e., exogenous components of resilience). Without sufficient data on the projected frequency and intensity of future climate stressors of interest, it is a practical impossibility to characterize the resilience of transportation infrastructure to climate change. As such, the availability of relevant climate projections is a necessary prerequisite for climate resilience or vulnerability analysis (Federal Highway Administration FHWA, 2017). In the absence of such climate projections, there may be preexisting publicly available data characterizing climate risks based on present climate conditions. For example, local, national, and international building codes typically provide maximum wind speeds for use in structural design, which can be used to estimate resilience due to extreme wind events. Similarly, federal agencies (e.g., US Federal Emergency Management Agency) typically publish flood maps, which consider historic flooding and expectations of present precipitation, riverine, and coastal flood risks. Local meteorological data, such as temperature extremes and tide gauge records, can also be used to characterize present levels of climate risk. In many cases, federal, state, and/or local government agencies have already performed more thorough investigations into both present and projected future coastal flood risks, making the information publicly available and readily accessible. For example, recent modeling work commissioned by MassDOT (Bosma et al., 2015; Woods Hole Group WHG, 2021) has characterized coastal flood risk with SLR for Greater Boston (Fig. 5.3) and has informed subsequent studies of future precipitation-based flood risk for the city of Boston (Boston Water & Sewer Commission BWSC, 2020). In circumstances where relevant information is lacking, additional modeling work can be undertaken to better characterize present and future climate risks, though there exists an inherent tradeoff between computational efficiency and model fidelity (Deierlein & Zsarno´czay, 2019). There are a variety of open source and commercial software available for modeling coastal flood risk. Coastal flood risk models are typically coupled models, wherein topometric, bathymetric, and meteorological inputs inform a model of wind shear-induced storm surge and long-period waves (e.g., ADCIRC, GEOCLAW) which in turn informs a near-shore wave model that attempts to capture shoreline wave dynamics (e.g., SWAN, STWAVE) thereby enabling high fidelity dynamic modeling of coastal flood events (Deierlein & Zsarno´czay, 2019). Less computationally expensive coastal flood modeling alternatives, such as the GEOCLAW-based model presented by Miura et al. (2021), can also allow for more rapid characterizations of present and future coastal flood risks.

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Figure 5.3 Projected 1100 year coastal flood depths under 10.79 m sea-level rise relative to year 2000 baseline (Woods Hole Group (WHG), 2021). Flood projections based on statistical analysis of hydrodynamic simulations of a large, representative sample of synthetic tropical and extratropical storms expected to impact Greater Boston. The Massachusetts Coastal Flood Risk Model has a vertical resolution of ,10 cm and a horizontal resolution of up to 3 m. Source: Courtesy Woods Hole Group (WHG). (2021). Massachusetts coastal flood risk model.

Absent the time, skill, or resources to complete a high-fidelity hydrodynamic coastal flood risk modeling exercise, a simple bath-tub approach can be employed instead, wherein the severity of a flood event at a given location is modulated by an SLR value and considered as the flood elevation across an entire region (e.g., see Oddo et al., 2020; Rasmussen et al., 2020). Such an approach will neglect nonlinearities in flood severity arising from regional bathymetry, wave dynamics, and storm direction but can provide a reasonable approximation of flood risk for evaluating transportation system resilience and relative performance of potential adaptation options.

5.3.2 Assessing the consequences of exposure Understanding the resilience of transportation infrastructure to climate change or climate-related hazards requires an understanding of the physical consequences of hazard exposure. In the particular case of assessing resilience to flood exposure, the lowest critical elevations (LCEs) of a given transportation infrastructure system

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serve as the primary indicator of inundation and impact to system performance (Jacob et al., 2008; Martello et al., 2021). LCEs are locations where flood water could conceivably inundate a system of interest and affect its operations, such as low-lying sections of roadway, subway station entrances, or ventilation shafts (Fig. 5.4; Jacob et al., 2008; Rosenzweig et al., 2011). Further characterization of the right of way location and elevation, as well as pertinent operational characteristics, such as vehicle dispatch locations, or track switch locations can then enable a more detailed understanding of the operational consequences of flood events (Martello et al., 2021). Detailed transportation infrastructure asset identification and geospatial characterization can also enable the prediction of asset-level flood damages and estimation of monetary losses (Compton, 2009; Kellermann et al., 2016). In many cases, the data required to characterize transportation system sensitivity and adaptive capacity is readily available within transportation agencies, though it may not be centrally located and may lack required geospatial metadata (Federal Highway Administration (FHWA), 2017). The performance of transportation networks can also be affected by adjacent interdependent infrastructure systems. Interdependencies can result in cascading failures (National Academies of Sciences Engineering & Medicine (NASEM), 2017; National Institute of Standards & Technology NIST, 2015; Linkov & Trump, 2019; National Academies of Sciences Engineering & Medicine (NASEM), 2021). For example, failure of the power grid can affect downstream transit infrastructure

Figure 5.4 Sample lowest critical elevation, a ventilation shaft at street level directly above Courthouse Station along the MBTA Silver Line in South Boston (Google Maps, n.d.). Source: Modified from Google Maps. (n.d.) Boston, MA. Retrieved January 8, 2020 from https://www.google.com/maps/@42.3547602,-71.0533024,13z.

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assets, such as traction power substations, resulting in significant systemwide disruptions (Miura et al., 2021). Failure of a tide gate for a stormwater sewer outfall could cause backflow in a storm surge potentially inundating low-lying road networks or rail rapid transit tunnels (Sullivan, 2022). Despite the potential for such disruptions arising from cascading failures, infrastructure interdependencies are at present typically poorly characterized by infrastructure managers (Chester et al., 2021). Where sufficient information is available, the characterization of such system interdependencies can allow for the prediction of cascading failures, enabling an improved understanding of transportation system resilience in the broader context of the adjacent built environment.

5.4

Achieving climate resilience through adaptation

Ultimately, efforts undertaken to understand and quantify the climate change resilience of transport infrastructure systems are motivated by the need to adapt these systems such that they can better resist present and future extreme climate stressors. Without adaptation, the expected increases in frequency and severity of climaterelated exposure events (Buchanan et al., 2016; Kopp et al., 2014; Strauss et al., 2021) will inevitably decrease the resilience of transportation systems and impinge upon their core functionality (Ayyub & American Society of Civil Engineers, 2021; Martello et al., 2021). While postdisaster response and recovery can be leveraged to enhance the resilience of a transportation network (Chester et al., 2021), proactively incorporating resilience into asset management and capital investment practices can enable the identification of vulnerabilities and opportunities to increase preparedness before a significant disruption event occurs (Caldera et al., 2021; Chen & Bartle, 2022; Chester et al., 2021). Efforts undertaken to adapt to climate change can take a wide variety of forms and span several spatial and temporal scales. Viewing potential adaptation measures through the lens of infrastructure resilience as defined above, adaptation can be broadly classified along four separate categories of system improvement: robustness, rapidity, redundancy, or resourcefulness4 (Caldera et al., 2021; Dawson et al., 2018).

5.4.1 Adaptation decision-making frameworks There are several dimensions to adaptation, not the least of which is the characterization and structuring of an appropriate decision-making process. Existing capital investment planning processes, are often insufficient for holistic needs of climate change adaptation planning. The inherent and deep uncertainty of climate change and its consequences makes for a particularly challenging decision environment. 4

As we note in a subsequent section, transportation system resilience can also improve as a consequence of exposure reduction, such as by the completion of a regional flood protection project outside the boundaries of the transportation infrastructure system.

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Several authors have proposed a variety of decision-making approaches, such as robust decision-making, dynamic adaptive policy pathways (DAPP), real options analysis (ROA), and flood damage allowances, specifically to accommodate the uncertain nature of adaptation planning (de Neufville et al., 2019; Ginbo et al., 2021; Oddo et al., 2020; Rasmussen et al., 2020; Ramm et al., 2018; Sriver et al., 2018). Regardless of the particularities, the fundamental aim of a given approach is to prepare a systematic framework that relies on available observations and projections to calibrate and inform an adaptation strategy given the prevailing uncertainty of future SLR and associated coastal flood risks. For example, in a DAPP approach, this can be as straightforward as the determination of preset condition/state (e.g., future sea level condition) that will trigger a specific adaptation pathway (Ramm et al., 2018). More sophisticated approaches, such as the flood damage allowance framework, attempt to calibrate adaptation policy by matching present and future annualized monetary flood losses (Rasmussen et al., 2020). While any of these decision-making frameworks can help calibrate and balance adaptation measures into the future, they nonetheless require a predefined decision space, particularly if alternative adaptation measures are under consideration. In the following subsections, we define and explore this decision space specifically for climate resilienceenhancing transportation infrastructure adaptation measures.

5.4.2 Scales of adaptation Adaptation alternatives exist across spatial, temporal, and organizational dimensions (Mesdaghi et al., 2022). Generally, as the spatial scale of an adaptation measure increases, so too does its temporal and organizational scale (i.e., bigger projects are more likely to be designed to last for a longer time and involve a greater number of public and private stakeholders; Mesdaghi et al., 2022). An inherent tradeoff exists between adaptation flexibility and scale, as the potentially greater benefits of larger projects typically arise from greater project complexity, a decrease in agency of individual decision-makers (i.e., increasing need for cooperation), and a decrease in implementation flexibility (de Neufville et al., 2019). In contrast with climate change mitigation, in which actions and outcomes are truly global in scale, climate adaptation is an inherently local issue (Cradock-Henry & Frame, 2021). While this aspect of adaptation is well-recognized throughout the literature, existing research largely focuses on the preparation of regional-level adaptation plans, generally neglecting the potential for individual organizations or stakeholders to adapt at smaller scales (e.g., Kirshen et al., 2020; Rasmussen et al., 2020). Furthermore, while there is an emerging understanding of the organizational dimension of (public sector) adaptation planning (e.g., Dawson et al., 2018; Mesdaghi et al., 2022), there have been few attempts to systematically characterize this dimension of adaptation planning, leaving researchers and practitioners to rely on institutional knowledge and intuition to ascertain the probable limits of intraand interagency adaptation planning capabilities. Given the limited resources and capital constraints of transportation agencies, understanding the range of potential adaptation options across spatial, organizational, and temporal dimensions (i.e., the feasible decision space) represents a

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crucial initial step in adaptation planning. While an organization can choose to implement local, self-contained asset-level adaptation projects, without much interaction with other organizations, neighborhood-level adaptation projects will likely require coordination with additional organizations (e.g., municipalities, government agencies, private sector corporations). The coordination between these organizations has the potential to introduce conflict, particularly if there are preexisting institutional cross-agency barriers to collaboration (Mesdaghi et al., 2022) or a degree of institutional rigidity limiting the adaptive capacity of organizations (Pelling et al., 2015). Such barriers can frustrate adaptation efforts, particularly if the interrelation and interagency dynamics between involved institutions is poorly understood. As such, an understanding of the organizational complexity inherent in potential adaptation options is salient and crucial for deciding among and between potential options. In addition to varying scales of organizational complexity, adaptation projects exist across spatial scales and can range from asset-level, and neighborhood-level measures, as well as to regional measures that can span municipalities and benefit large metropolitan areas (Solecki & Rosenzweig, 2022). Asset-level adaptation measures are typically organizationally self-contained and can range from comparatively short-term measures, such as the installation of deployable flood barriers at the entrances of Aquarium Station in Boston (Massachusetts Department of Transportation (MassDOT), 2021b; inset, Fig. 5.5), to longer-term measures, such as permanent elevation of infrastructure assets, such as traction power substations along the New York Metropolitan Transit Authority (MTA) Metro North’s Hudson Line (Fig. 5.6; Metropolitan Transit Authority (MTA), 2019). Larger, neighborhood-level adaptation measures, such as the proposed creation of a continuous elevated park along the waterfront in Downtown Boston (City of Boston, 2020), typically require increasing collaboration across the domain of relevant public agencies, as well as private sector stakeholders and the public at-large (Fig. 5.5). These measures are typically designed as longer-term adaptation solutions (e.g., 50year useful lifespans), though intolerable levels of preexisting risk and budgetary constraints may require shorter-term solutions (e.g., the in-kind replacement of a deteriorated coastally adjacent section of roadway). Regional measures (e.g., United States Army Corps of Engineers (USACE), 2019) also have the capacity to provide significant wide-ranging benefits to (public and private) agents in cities or metropolitan areas and associated ancillary benefits to transportation infrastructure. Such large-scale projects often require significant lead times (potentially a decade or more) due to extensive environmental review and federal permitting requirements (Kirshen et al., 2018) and consequently take a long-term planning approach (i.e., 50100 years). Due to their wide reach, transportation agencies are, at best, likely to play only a supporting role in the development, formulation, or implementation of such adaptation options, though coordinated transportation infrastructure system improvements may have a role in regional adaptation measures (Aerts et al., 2013). As such, in the absence of endogenous changes to transportation infrastructure, regional measures can perhaps be better conceptualized as an exogenous reduction in climate exposure, rather than as transportation infrastructure adaptation.

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Figure 5.5 Example of neighborhood-level adaptation plan proposed for Long Wharf in Downtown Boston (City of Boston, 2020b). Inset: example asset-level adaptation project (deployable flood barriers) recently completed to protect entrances to the MBTA Aquarium Station (Massachusetts Department of Transportation (MassDOT), 2021b). Source: Modified from City of Boston. (2020b). Coastal resilience solutions for downtown boston and north end—Final report. City of Boston. https://www.boston.gov/sites/default/ files/file/2020/10/Final_North%20End%20Downtown%20Final_EMBARGO_0.pdf and Massachusetts Department of Transportation (MassDOT). (2021b). MassDOT-FHWA resilience and durability pilot project report—Implementing coastal flood resilience solutions for the tip O-Neill Tunnel Egress 434 and the MBTA blue line aquarium station. MassDOT. Retrieved from https://www.fhwa.dot.gov/environment/sustainability/resilience/pilots/ 20182020_pilots/massdot_pilot_project/fhwahep21030.pdf.

5.4.3 Increasing robustness Adaptations to SLR and coastal flood risk often take the form of physical interventions requiring significant capital investments (e.g., City of Boston, 2020; Metropolitan Transit Authority (MTA), 2017). Physical interventions intended to harden a given asset, neighborhood, or region to flood risk such that it may better withstand future climate hazards are ultimately aimed at increasing the robustness of a transportation system to climate hazards. Adaptation measures to increase robustness can be as simple as elevating critical assets above a design flood elevation (Massachusetts Bay Transportation Authority (MBTA), 2019a) or comparatively more complicated projects, such as the installation of shore-based solutions that span across several organizational boundaries (e.g., Fig. 5.5).

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Figure 5.6 Example adaptation measure increasing system robustness. Elevation of an electrical substation along the MTA Metro North Hudson Line in Tarrytown, NY (Massachusetts Bay Transportation Authority (MBTA), 2019a). By elevating the substation above the design flood elevation (DFE), damage during a flood event can be minimized or avoided entirely. This lessens the system performance loss during a flood event (inset) thereby improving transportation system resilience. Source: Modified from Metropolitan Transit Authority (MTA). (2019). 2019 resiliency report: Update on agency-wide climate resiliency projects. MTA. https://new.mta.info/ document/10461.

Shorter term hardening measures, such as the installation of deployable flood walls, (Massachusetts Bay Transportation Authority (MBTA), 2019a; Massachusetts Department of Transportation (MassDOT), 2021b; Fig. 5.5 inset) or subway station entrance closures (Metropolitan Transit Authority (MTA), 2019) can effectively limit the operational impact of flood events. Oftentimes, several adaptation measures aimed at increasing robustness will be dependent upon one another to be effective, particularly in situations where multiple flood pathways expose the same portions of a transportation system (e.g., multiple lowest critical locations where water could flow into a subway system; Martello & Whittle, 2021). Installation of deployable hardening measures, such as flood doors or tunnel plugs either as a stand-alone solution (Sosa et al., 2017; Massachusetts Bay Transportation Authority MBTA, 2020; Metropolitan Transit Authority MTA, 2019), or as part of a larger regional solution (Mooyaart et al., 2014; United States Army Corps of Engineers USACE, 2015a) can also provide short-term protection

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during flood events, provided they are closed properly and in a timely manner. The nonstationarity of climate risks (e.g., increase in coastal flood risk due to SLR) will limit the useful life of deployable strategies, as they require increasingly frequent operation to ensure protection against climate extremes (Kirshen et al., 2018; Umgiesser, 2020). Deployable solutions are also prone to reliability issues, deployment failures, and operational errors, particularly if they are not regularly or properly maintained (Jonkman et al., 2013). By contrast, elevation of transportation infrastructure assets is a comparatively more passive adaptation measure to increase robustness. Where appropriate, elevating transportation infrastructure can ensure critical infrastructure components are undamaged during a flood event, potentially enabling a quicker performance recovery or the avoidance of operational impact and network disruption entirely (Fig. 5.6). Localized elevation of infrastructure assets, such as the elevation of commuter rail system substations above an SLR-informed design flood elevation (Massachusetts Bay Transportation Authority (MBTA), 2019a), can enable the temporary accommodation of flood waters with minimal losses to infrastructure, allowing for a more rapid postevent recovery. Neighborhood-level solutions can also incorporate the elevation of transportation assets, such as the elevation of transit station entrances and ventilation shafts as part of a broader coastal adaptation plan (e.g., see City of Boston, 2020).

5.4.4 Increasing rapidity In certain circumstances, increasing robustness to flooding may not be feasible, practical, or economically justifiable. In such instances, an alternative adaptation approach is to focus on the rate of service restoration during the recovery phase of a disruption event. Increases in rapidity can take the form of optimizing recovery strategies to minimize system downtime given prevailing resource constraints (Chang, 2021). Alternatively, the development of recovery strategies that aim to maximize overall system functionality can also increase time rate of recovery (e.g., Bhatia et al., 2020; Sela et al., 2017). While the formulation of optimal recovery strategies can perhaps be equally conceptualized as improvements in rapidity and resourcefulness, we include them here, as they are principally aimed at increasing the speed of system recovery. Aside from improved resource deployment strategies, system rapidity can also be increased by accommodating floodwaters.5 Adaptation measures that accommodate floodwaters can take the form of permanent design changes or shorter-term harm reduction measures. For example, in the aftermath of Hurricane Sandy, New York City Transit deployed significant additional pumping capacity, enabling the transit service to return more quickly than it would have been able to otherwise (Metropolitan Transit Authority (MTA), 2017; Fig. 5.7). Additional rapidity improving adaptations include drainage and culvert improvements, particularly in locations where legacy infrastructure is presently inadequate for conveying design storm flows. 5

Adaptation measures that are aimed at accommodating floodwaters can also be characterized as improvements in resourcefulness, particularly if they rely on deployment of resources.

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Figure 5.7 Example adaptation measure increasing system rapidity. Deployment of a pump train in the L train tunnel under the East River after Hurricane Sandy (Metropolitan Transit Authority (MTA), 2012). Deployment of additional pump capacity enabled more rapid dewatering of flooded tunnels, thereby increasing system recovery. As such, system performance during a flood event can recover more rapidly (inset) thereby improving transportation system resilience. Source: Courtesy Metropolitan Transit Authority (MTA). (2012). NYCT_6190 [Picture of a pump train dewatering the L train tunnel under the East River after Hurricane Sandy] [Photograph]. MTA. Retrieved from https://www.flickr.com/photos/mtaphotos/8159586659/ in/album-72157631938986786/.

Rapidity improvements can also be part of neighborhood-scale coordinated floodwater accommodation efforts aimed at minimizing localized flood impacts, such as the localized elevation of roadway segments to enable upsizing of drainage culverts (e.g., Hylan Boulevard reconstruction, New York Governor’s Office of Storm Recovery (NYGOSR), 2018). More ambitious neighborhood or city scale elevation efforts for accommodating floodwaters have few historic parallels, though the historic “raising of Chicago,” in which the streets and adjacent buildings were elevated by approximately seven feet to accommodate a combined sewer system (Chicago Daily Tribune, 1857), can serve as an extreme case study of regional accommodation by elevation.

5.4.5 Increasing redundancy For some types of transportation infrastructure systems, increasing redundancy is a prohibitively expensive adaptation measure. This is particularly true for rail rapid

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transit systems and roadway networks, where the installation of additional network segments, particularly in urban environments, requires either the acquisition of right of way, tunnel, and/or bridge construction. Consequently, investments in additional network segments typically takes a significant amount of time and capital. Even if the right of way is already owned by an infrastructure manager, a project as simple as double tracking a section of a rail network is likely to be a multimillion dollar capital investment (Massachusetts Department of Transportation (MassDOT), 2021a). Given the outsized costs, absent any substantial cobenefits (e.g., expansion of service to a dense urban area, or increasing peak hourly capacity) it is highly unlikely that such investments would be made solely to improve system redundancy, even if such additional links would provide significant value during disruptions. Recent global supply chain bottlenecks and related research on vaccine supply chains (Golan et al., 2021) suggests that there is a clear tradeoff between system efficiency and resilience, wherein system efficiency is most often prioritized in practice. Absent a clear elucidation of the risk management benefits, substantial investments in system redundancy are unlikely (Jin et al., 2021). Other transportation systems, such as bus rapid transit and maritime transportation systems, are comparatively more flexible and more capable of reorganizing without significant capital expenditures. Introducing additional network links connecting preexisting nodes (e.g., transit or bus stops, ferry terminals, coastal ports) can be readily considered during network redesign. For example, if considered jointly, the resilience of a bus and rail rapid transit network could be improved via the introduction of complimentary bus route parallel to a rail corridor, as well as via the introduction of bus service between rail rapid transit stations on separate lines (Jin et al., 2014). For example, several redundant bus (and subway) routes run parallel to the NYC MTA’s one train line, such as the M104 route from 125th Street in Harlem to Times Square 42nd Street stations (Fig. 5.8). In the event of a disruption (flood-related or otherwise) at rail transit stations along a portion of this route (e.g., 110th Street and 103rd Street stations) riders can transfer to the M104 bus running above the subway. In addition to incorporating redundancy directly into service planning and network design, additional bus transit service can also be introduced in real time in response to disruption events. Often referred to as bus bridging, the temporary provision of service between high travel rail transit stations and in place of disrupted transit lines can significantly increase the capacity of a disrupted network (Jenelius & Cats, 2015; Kepaptsoglou & Karlaftis, 2009) as demonstrated by the NYCT in response to Hurricane Sandy in 2012 (Metropolitan Transit Authority (MTA), 2017).

5.4.6 Increasing eesourcefulness Increasing resourcefulness can be viewed as an exercise in increasing the flexibility in the management of the transportation infrastructure system, better enabling agile responses to unexpected disruptions (Chester et al., 2021). Adaptation approaches which deliberately build in implementation flexibility can also help infrastructure managers better react as uncertainties are reduced in future over the lifespan of a

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Figure 5.8 Example adaptation measure increasing system redundancy. Designing public transit networks to include parallel bus and rail service (e.g., the M104 which runs parallel to the one train in the NYC MTA system) can enable riders to quickly switch between modes during a disruption event (e.g., loss of rail service at 103rd and 110th Street stations). This can lessen the system performance loss during a flood event (inset) thereby improving public transportation system resilience.

project, thereby minimizing adaptation regret (Brisley et al., 2016). In addition to optimizing recovery strategies and bus bridging, there are a variety of additional adaptation measures that can be employed to increase system resourcefulness. For example, improved sharing of real-time information to users (e.g., provision of road or transit station closure information) can better enable individuals to reorient and find alternative routes through a network during a disruption event, thereby minimizing overall system performance degradation (Mo et al., 2022). In addition to measures aimed at improving real-time operational flexibility, increases in resourcefulness can also be more organizational in nature, such as the development and implementation of new climate resilience design standards (e.g., Massachusetts Bay Transportation Authority (MBTA), 2019a; Stoothoff, 2019) or capital investment criteria that explicitly consider resilience to climate-related hazards (Massachusetts Bay Transportation Authority (MBTA), 2019b). Such changes enable infrastructure managers to shift internal resources and attention towards climate resilience without significant additional capital investment requirements. Resourcefulness can also be improved by shorter-term (i.e., 13 years) financially-based approaches, such as risk transfer. This can take the form of more conventional indemnity flood insurance policies (where the policy payout is directly proportional to the cost of damages up to the coverage limit), or more sophisticated reinsurance measures, such as the issuance of parametric catastrophe bonds (Chen & Bartle, 2022). For example, the New York City MTA has issued several series of parametric catastrophe bonds, thereby providing $100 M of flood (re)insurance coverage should a coastal flood event result in a certain level of flooding, as measured by local tide gauges (Evans, 2020). Such catastrophe bonds issuances enable transportation agencies to underwrite climate risks that might otherwise be uninsurable,

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though the cost of underwriting this risk is directly proportional to the occurrence probability of the insured event (Lee & Yu, 2002; Ma & Ma, 2013). As such, given that SLR will increasingly expose a larger proportion of assets to coastal flood risk with greater frequency, such risk transfer strategies are liable to become prohibitively expensive without substantive adaptation interventions. Risk transfer can nonetheless be a useful tool to limit the severity of low-probability climate risk by providing an immediate increase in short-term financial reserves immediately after a disruption event, thereby affording a more flexible deployment of existing resources, as well as the capacity to deploy additional resources outside standard operational capacities in response to disruption. Increases in resourcefulness do not necessarily require real-time data sharing, development of new design standards, or the creation of complicated financial instruments. For example, during seasonally high tides in Venice (colloquially known as “Acqua Alta”) pedestrian infrastructure is routinely modified to accommodate floodwaters, thereby enabling pedestrians to navigate city streets at a diminished capacity before floodwaters recede (Flaxington et al., 2015). While the implementation of such measures is admittedly suboptimal compared to simply avoiding flooding entirely, the temporary installation of walkways enables a higher level of system performance during a disruption event (i.e., for the duration of one or more high tide cycles). Given the fact that raising street levels or building floodwalls adjacent to canals is culturally and politically untenable in Venice, accommodating measures that maintain pedestrian traffic flow during disruption are an effective alternative, particularly in the absences of more regional flood protection projects, such as the recently completed MOSE barrier (Umgiesser, 2020).

5.5

Valuing climate resilient infrastructure

Climate change adaptation measures will generally require significant capital investment, and will require financial justification. As such, valuation of climate change adaptation projects cannot be easily overlooked, as adaptation projects must be justified relative to other potential public investments if they are to successfully compete for the limited quantity of available public funds. In other words, the benefits of an adaptation project should outweigh its costs. While the life cycle costs of an adaptation project or pathway are typically rather straightforward to conceptualize and quantify (e.g., the costs of a new floodwall consists of an upfront capital cost and sustained operation and maintenance costs) similar to other public infrastructure projects, the benefits of climate adaptation projects affect a wide range of stakeholders, providing indirect societal benefits that are less straightforward to conceptualize and quantify (Chen & Bartle, 2022). While indirect societal benefits can be difficult to fully assess and capture, the direct benefits of an adaptation project, the avoidance of damage-related losses during extreme events, is generally regarded as monetarily quantifiable, particularly for flood protection projects. Avoided flood-related losses can be characterized via the

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unit loss method, in which (avoided) losses (i.e., damage costs) are a function of the replacement cost and a damage factor relating flood severity to (avoided) damage for all assets of interest (de Moel, 2012; Wagenaar et al., 2016). The damage factor relates flood characteristics and associated asset-specific sensitivity to the estimated severity of damage. While many factors, such as wave action, flood duration, water salinity, sediment load, water quality, flood timing, asset age, and construction typology, can all influence actual flood damage, these factors are generally not considered in current methods of flood damage estimation (Pistrika et al., 2014; United States Army Corps of Engineers USACE, 1992; Dottori et al., 2016; Franco et al., 2020; United States Army Corps of Engineers (USACE), 2015b). Instead, flood depth is used as the sole/primary indicator of damage severity in standard flood damage cost estimation practices (de Moel, 2012; Gerl et al., 2016; Wagenaar et al., 2016; Kok et al., 2004). As such, the damage factor is typically described by a depth-damage function (de Moel, 2012; Kok et al., 2004; Budiyono et al., 2015; United States Army Corps of Engineers (USACE), 2015b; Wagenaar et al., 2016). These depth-damage functions are often created to characterize specific types of assets (e.g., single family residential structures; United States Army Corps of Engineers (USACE), 2006, 2015a, 2015b) and reflect asset-specific sensitivity to flood exposure. Unfortunately, there are at present few depth-damage curves potentially relevant for transportation infrastructure, with only a handful of relevant references in the academic literature (de Moel & Aerts, 2011; Habermann & Hedel, 2018; Kok et al., 2004; Vanneuville et al., 2003). Assuming a relevant depthdamage relationship exists for all transportation system assets of interest, adaptation benefits under a single flood event with a given return probability, fB ðpÞ, can therefore be expressed as the following: fB ðpÞ 5

n X

RCi fiDD ðhi ðpÞÞ

(5.2)

i51

where n denotes the number of flooded assets, RC i the replacement cost of an asset of interest, hi ðpÞ the flood depth at the asset of interest under the return probability, p, and fiDD ðxÞ the depth-damage relationship for the asset of interest. In this manner, adaptation benefits (i.e., avoided flood-related losses) can be characterized for several flood events of varying return probability for a given level of risk. Considering the benefits across all flood probabilities under a given level of climate risk (e.g., a given level of SLR), the benefits of an adaptation project in any given year, Bt , are equivalent to the expected annualized avoided losses (EAALt ), which are determined by the area under the avoided hazard damage probability distribution, fB ðpÞ (de Moel, 2012; Meyer et al., 2009; Saint-Geours et al., 2015): Bt 5 EAALt 5

ð1 0

fB ðpÞdp

(5.3)

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Thus from a benefitcost ratio (BCR) perspective, for an adaptation project to be financially justifiable, the present value of its expected costs, must not exceed the present value of the cumulative EAAL over its anticipated lifespan.6 Framing this mathematically: y P

BCR 5

t50 y P t50

Bt ð11rÞt

$1

(5.4)

Ct ð11rÞt

where Bt and Ct are the benefit and costs in year t respectively, r is the discount rate, and y is the lifespan of the adaptation project. Rephrased from a cost-benefit analysis perspective, for an adaptation project to be a viable investment, its net present value should be greater than zero: NPV 5

y X t50

Bt Ct 2 $0 ð11r Þt ð11r Þt

(5.5)

Note the selection of the discount rate, r, has a disproportionate impact on the perceived value of an infrastructure investment project, particularly those for which benefits accrue over an extended period (Lee & Ellingwood, 2015). Despite the sensitivity of valuation on discount rate selection, many authors do not critically examine discount rate selection choices and there is at present a lack of consensus on appropriate discounting approaches. While private sector actors and a small subset of the economic literature for publicsector financing considers risk-adjusted discounting approaches (e.g., Gollier, 2021; Lucas & Montesinos, 2020) the prevailing infrastructure investment discounting approaches presented in the literature are largely governed by policy and regulatory guidance set forth by public sector agencies (Stewart & Bastidas-Arteaga, 2019). There is significance variance in discounting rationales employed by government agencies and further variance in interpretation among authors who apply one of four main approaches: (1) use an accepted social discount rate7 (HM Treasury, 2020; Lee & Ellingwood, 2015; Vousdoukas et al., 2020); (2) set a schedule of declining discount rates (Lee & Ellingwood, 2015; Lowe, 2008; Stewart & Bastidas-Arteaga, 2019); (3) compare results across a range of discount rates (Lincke & Hinkel, 2018; Oddo et al., 2020); or (4) avoid discounting entirely (Buchanan et al., 2016; Hallegatte et al., 2013; Neumann et al., 2021; Rasmussen et al., 2020).

6

The lifespan or service life of an infrastructure project is ultimately project dependent. Typical lifespans for larger-scale infrastructure projects are in the range of 5075 years (Lee & Ellingwood, 2015). 7 The social discount rate adjusts for the value society attaches to present (over future) consumption and long-term expectations that future generations will be wealthier than present generations (HM Treasury, 2020). The social discount rate aims to capture society’s (i.e., taxpayers’) expectation of return on public sector investments.

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Notwithstanding the prevailing ambiguity surrounding discount rate selection, particularly in situations where benefits significantly outweigh the costs, a proper attempt at valuation enables a clearer presentation of the business case for adaptation projects. A defensible valuation can better enable public agencies to justify bond issuances to fund adaptation projects, thereby improving the likelihood of financing and tendering of the project. Clear delineation of project benefits can also enable the issuance of green bonds, which represent an emerging alternative method of accessing capital markets to finance adaptation projects (Keenan, 2019; Transportation Research Board TRB & National Academies of Sciences Engineering & Medicine (NASEM), 2021; Chen & Bartle, 2022). Lastly, in addition to the avoidance of direct damages, adaptation project benefits can also include the avoidance of indirect damages, such as the avoidance of emergency response costs, or lost farebox revenue. Other indirect societal cobenefits, such as the avoidance of disruption for commuters (Sun et al., 2021) freight delays, or regional economic interruption can also be quantified to further evaluate the potential benefits of adaptation projects (National Academies of Sciences Engineering & Medicine (NASEM), 2020).

5.5.1 Adapting equitably While it is important to ensure a given adaptation project provides a return on investment and makes financial sense, it is also important to ensure that benefits and burdens are equitably distributed. Climate change adaptation projects framed exclusively through the lens of enhancing resilience of engineered systems are liable to neglect adjacent social structures and institutional context, thereby increasing the likelihood that proposed solutions will perpetuate existing social inequities (Malloy & Ashcraft, 2020). More generally, the advancement and implementation of apolitical and technocratic adaptation solutions can effectively serve to disenfranchise vulnerable populations and the community at-large from the decisionmaking process, leaving no room for contestation of official plans (Adger et al., 2005; Yarina, 2018). Adaptation projects that neglect sociopolitical dimensions of planning have the capacity to exacerbate, redistribute, and create new forms of socio-spatial inequities across diverse urban contexts (Swanson, 2021). There is a rapidly expanding body of research focused on climate adaptation equity, as well as a separate body of research focused on transportation equity. While both areas of research focus on equity in the context of planning, transportation equity focuses to a greater extent on distributional equity and justice. Philosophically underpinned by either a Rawls’ egalitarian or capabilities approach (Pereira et al., 2017), distributive justice underpins commonly employed measures of transportation equity, such as mobility and accessibility (Sun et al., 2021). Accessibility refers to the ability to reach preferred destinations (e.g., job opportunities) and mobility refers to the ease with which individuals can travel to such preferred destinations, often measured in average travel time (Sun et al., 2021). Given sufficient information on demographics, user behavior, and impacts of adaptation,

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such measures can be employed to characterize the distributive equity of transportation infrastructure adaptation projects and subsequently inform decision making. Taking a more expansive view, existing adaptation equity literature suggests equitable adaptation efforts not only promote distributive justice, but also procedural, and recognition justice (Malloy & Ashcraft, 2020; Malloy, 2021; Swanson, 2021). Malloy and Ashcraft (2020) argue that equitable adaptation to climate change requires not only the engagement of vulnerable populations, but also agency in the decision-making process. Through the enfranchisement of vulnerable populations, planners and decision-makers are better positioned to negotiate normative aspects of planning with the community (i.e., consider community values and motivations), thereby increasing the likelihood of producing solutions that equitably provide value to all members of the community. Economic measures of equity can also be applied to further interrogate the distributive justice of adaptation infrastructure investments. Under the lens of a typical cost-benefit analysis, the best investment projects are those which provide the maximum net present value, irrespective of how these benefits are distributed across society. For example, traditional transportation planning approaches often ascribe value of time savings to transport users via market-based approaches; consequently, benefits accruing to wealthier users are valued more highly than those accruing to poorer users, all else being equal (Martens, 2017). Rather than simply measure the dollar value of benefits, Kind et al. (2017) instead provides a framework to measure the utility of benefits by scaling dollar values in accordance with measures of diminishing marginal utility and risk aversion. Through consideration of the marginal utility of benefits and costs in lieu of their absolute value, subsequent valuations instead allow decision-makers to maximize the net welfare rather than the net present value of a given investment (Keenan, 2019; Kind et al., 2017; Pereira et al., 2017). Though equity-weighted valuation methods typically lie outside existing public investment valuation frameworks, such valuations can provide decision makers with a useful method of comparing the equity of several economically viable adaptation alternatives (Keenan, 2019).

5.6

Conclusion and future trends

Resilience is a useful heuristic for framing and conceptualizing climate change adaptation of transportation infrastructure systems. When coupled with an adaptation decision-making framework and equitable planning practices, resilient design can ensure sensible, sustainable, and equitable investments are made in transportation infrastructure. Yet, there are several operational gaps in the literature which will need to be addressed in order for resilient design practices and infrastructure adaptation planning to become widely adopted. While there is an emerging understanding within the transportation field that natural hazards can significantly affect networked measures of infrastructure performance (e.g., Bhatia et al., 2020; Chang, 2021; Sela et al., 2017), there is a

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significant lack of performance models that attempt to explicitly relate physical infrastructure characteristics and climate-related vulnerabilities to performance degradation. There is a growing body of research aiming to address this gap for transportation infrastructure (e.g., Martello et al., 2021; Rosenzweig et al., 2011; Testa et al., 2015; Zhang et al., 2019) though additional research is needed to better understand the physical implications of climate exposure on transport infrastructure at a systemwide level. There is at present a significant lack of research relating the fragility of transportation infrastructure to potential climate-related damages or to quantify the benefits of adaptation projects (National Academies of Sciences Engineering & Medicine NASEM, 2021). While there is an emerging literature focused on other types of infrastructure (e.g., power grid infrastructure Chang, 2021; Haggag et al., 2021) and characterizations of general transportation infrastructure sensitivity to flood risk (e.g., de Moel & Aerts, 2011; Kok et al., 2004; Vanneuville et al., 2003) future research is needed to further elucidate the fragility of specific types of transportation infrastructure assets to specific climate stressors. Without an understanding of transportation infrastructure fragility to climate stressors, proper evaluation of the economic benefits of adaptation is not possible. Furthermore, while financial evaluation of transportation infrastructure investments typically guides investment decision frameworks (National Academies of Sciences Engineering & Medicine (NASEM), 2021), few climate adaptation valuation methods fully consider climaterelated uncertainty or the full range of physical and financial outcomes (de Neufville et al., 2019; Ginbo et al., 2021). Improved methods of valuing climate change adaptation projects that enhance the resilience of transportation infrastructure are clearly needed. Better characterization of infrastructure interdependencies should also be a priority area for research and practice (Chester et al., 2021) in order to understand how the performance of transportation infrastructure depends on adjacent infrastructure systems, such as the electric grid, stormwater systems, etc. As transit agencies contribute to climate change mitigation through the conversion to electric vehicle fleets, there will be increased interdependencies with the electric power grid, which is also increasingly vulnerable to disruption in extreme weather events (Haggag et al., 2021; Rosenzweig et al., 2011). Further research is needed to improve the assessment of the adaptive capacity inherent in existing transport infrastructure systems. Here, it is critical to improve the understanding of internal institutional structures, and which institutional actors are responsible for the climate change adaptation, finance, and risk management. The mapping of institutional practices relating to climate adaptation and risk management is an emerging area of research (Mesdaghi et al., 2022) with the potential to enable efficient maneuverability of existing institutions to better create and design climate resilient transportation infrastructure. A better understanding of intra- and interagency dynamics can further enable researchers, policymakers, and decision-makers to identify and realize the benefits of cross-agency collaboration in the pursuit of climate change resilience for transportation infrastructure systems.

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Enhancing the climate resilience of transport infrastructure will become an increasingly critical component of the responsible stewardship of our built environment. Designing climate resilient transportation infrastructure requires an understanding of projected future climate extremes, inherent transportation system characteristics, and an understanding of how transportation infrastructure relates to adjacent socio-economic and socio-political systems. A theoretical and practical understanding of these external, internal, and contextual dimensions of resilience can better enable infrastructure managers to formulate system- and hazard-specific adaptation projects. Without such adaptation, the wide-ranging challenges posed by climate change and SLR will represent an existential threat to our transportation infrastructure systems.

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Further reading Brisley, R., Wylde, R., Lamb, R., Cooper, J., Sayers, P., & Hall, J. (2016). Techniques for valuing adaptive capacity in flood risk management. Proceedings of the Institution of Civil Engineers—Water Management, 169(2), 7584. https://doi.org/10.1680/ jwama.14.00070 Budiyono, Y., Aerts, J., Brinkman, J., Marfai, M. A., & Ward, P. (2015). Flood risk assessment for delta mega-cities: A case study of Jakarta. Natural Hazards, 75(1), 389413. Available from https://doi.org/10.1007/s11069-014-1327-9.

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Kirshen, P., Borrelli, M., Byrnes, J., Chen, R., Lockwood, L., Watson, C., Starbuck, K., Wiggin, J., Novelly, A., Uiterwyk, K., Thurson, K., McMann, B., Foster, C., Sprague, H., Roberts, H. J., Bosma, K., Jin, D., & Herst, R. (2020). Integrated assessment of storm surge barrier systems under present and future climates and comparison to alternatives: A case study of Boston, USA. Climatic Change, 162(2), 445464. Available from https://doi.org/10.1007/s10584-020-02781-8.

Climate change risks and bridge design

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Amro Nasr1, Ivar Bjo¨rnsson1, Da´niel Honfi2, Oskar Larsson Ivanov1, Jonas Johansson3 and Erik Kjellstro¨m4 1 Division of Structural Engineering, Lund University, Lund, Sweden, 2Transport Department, City of Stockholm, Stockholm, Sweden, 3Division of Risk Management and Societal Safety, Lund University, Lund, Sweden, 4Rossby Centre, Swedish Meteorological and Hydrological Institute, Norrko¨ping, Sweden

6.1

Introduction

As a result of the industrial revolution, humans began to impose considerable changes to the environment and climate system at an alarming rate. The rate of these changes has not become slower since then. On the contrary, this rate has been steadily increasing. The Sixth, and latest, Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) asserts that the rate at which these changes are occurring is unprecedented in thousands, if not hundreds of thousands, of years and some of these changes, for example, sea level rise, are irreversible over hundreds, if not thousands, of years into the future (IPCC, 2021). These changes may have complex consequences that are difficult to foresee, including impacts on the safety and performance of built infrastructure systems. Since the functionality of our societies is strongly dependent on the performance of these systems (de Bruijne & van Eeten, 2007; Johansson & Hassel, 2010; Svegrup et al., 2019), understanding the impacts of climate change on infrastructures (Cremen et al., 2021) and their essential role for a sustainable future (Thacker et al., 2019) is of crucial importance. Evidence from previous natural hazards (Nasr et al., 2020) suggest that disruptions to the transportation infrastructure network often lead to considerable direct societal consequences as well as cascading effects that disturb other infrastructure systems. Similarly, if key elements of a network are disrupted, the functionality of the entire network, or parts of it, may be impaired. This chapter focuses on integral elements of the transportation network, namely, bridges. Notable examples of bridge collapses that underscore their associated dire consequences include the collapse of the Silver Bridge in 1967 (Cook et al., 2015; Lichtenstein, 1993), the collapse of I-90 Schoharie Creek Bridge in 1987 (Briaud et al., 2014; Cook et al., 2015), and the more recent collapse of the Morandi Bridge in 2018 (Calvi et al., 2019; Malomo et al., 2020). The importance of studying the impacts of climate change on bridges is further underscored by the fact that bridges are often designed for long service lives (that can exceed 100 years) and are in Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00010-X © 2023 Elsevier Ltd. All rights reserved.

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many cases being operated far beyond this. Furthermore, construction and maintenance of bridges is typically more resource-demanding than that of ordinary roads or railway lines. Maintenance and eventual replacement of bridges might be extremely challenging in urban areas with tight places for construction activities and complex interdependencies of infrastructure networks. This chapter briefly describes climate change projections and the uncertainties inherent to them (Section 6.2) and presents potential climate change impacts on bridges (Section 6.3). Subsequently, a conceptual framework for rationally considering the impacts of climate change in the design of bridges is presented (Section 6.4) and some of the important challenges and research gaps that need to be addressed to facilitate the consideration of climate change effects in the design of bridges are discussed (Section 6.5). Although the focus is on bridges, the identified climate change risks and the conceptual framework are argued to be of value for both other types of infrastructure and infrastructure elements.

6.2

Climate change projections and uncertainties

Currently available and accepted climate models predict considerable changes to the climate system in the future (IPCC, 2021). In addition to the already observed increases in the global average temperature, further warming is projected as a result of changing forcing factors, such as increasing greenhouse gas (GHG) concentrations. While some locations are expected to experience increased precipitation in the future, a decrease in precipitation is projected for other locations. In general, larger contrast between wet and dry regions and seasons is predicted (i.e., wet regions and seasons becoming wetter and dry regions and seasons becoming drier). Although for most regions a decrease in the relative humidity over land is projected, under some climate change scenarios certain regions are projected to experience an increase in the relative humidity over land (IPCC, 2013, 2021). Examples of other relevant climatic changes are found in Table 6.1. Climate conditions are characterized by considerable interannual and interdecadal variability. This variability, referred to as natural or internal variability, is one of three uncertainty sources in assessments of climate change projections (Hawkins & Sutton, 2009). The second major source of uncertainty relates to changes in forcing conditions, including future changes in GHG emissions and aerosol particle concentrations. This uncertainty is represented by so-called climate change scenarios. Over the past decades, several climate change scenarios have been developed based on different assumptions of, for example, population growth, economic and technological development, etc. For instance, in 1990 four different climate change scenarios, referred to as the SA90 scenarios, were introduced by the IPCC (IPCC, 1990). These scenarios were followed in 1992 by a set of six scenarios referred to as the IS92 scenarios (IPCC, 1992). In 2007 the Fourth Assessment Report of the IPCC adopted six other climate change scenarios referred to as the SRES scenarios (IPCC, 2007). The Fifth Assessment Report which followed in 2013 is based on four different climate change scenarios referred to as the

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Table 6.1 Projected future trends of different climate parameters/phenomena. Climate parameter/ phenomenon Temperature

Trend of change G

G

G

Temperature extremes

G

G

Solar radiation

G

Precipitation

G

G

G

Precipitation extremes

G

G

Droughts

G

Relative humidity

G

G

Storms

G

G

G

G

Sea level

G

G

Carbon concentrations in the atmosphere and oceans Ocean temperature

G

G

G

Run-off

G

References

Higher global mean Higher seasonal contrast in some locations Lower seasonal contrast in other locations Increased intensity and/or frequency of heat waves and hot conditions Decreased intensity and/or frequency of cold extremes Increases in some regions and decreases in other regions Global average increase over land areas Large regional and seasonal differences Increase in contrast between wet and dry regions and seasons Increase in intensity and/or frequency on a global scale and in most regions Degree of increase varies between regions Land area affected by increasing drought frequency and severity expands with increasing global warming Decrease in relative humidity over land for most regions. Increase in relative humidity over land for some regions under some scenarios Decrease of total number of tropical cyclones Increasing fraction of the most intense tropical cyclones Small overall changes in wind speed associated with extratropical cyclones. Changes following poleward migration of storm tracks in some regions Continued global sea level rise for centuries to come Increasing extreme sea levels in most locations An increase in carbon concentrations in the atmosphere and in oceans

IPCC (2021)

Continued warming More frequent and intense marine heat waves Increasing global run-off with large regional and seasonal differences

IPCC (2021)

IPCC (2021)

IPCC (2021) IPCC (2021)

IPCC (2021)

IPCC (2021)

IPCC (2021)

IPCC (2021)

IPCC (2021)

IPCC (2021)

IPCC (2021) (Continued)

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Table 6.1 (Continued) Climate parameter/ phenomenon Near surface permafrost area Ocean surface pH River floods

Trend of change G

G

G

G

Widespread permafrost thaw is projected to continue through this century and beyond Decrease in global ocean surface pH Increases in river floods in some areas, decreases in others More areas will be exposed to increases than decreases

References IPCC (2021) IPCC (2021) IPCC (2021)

Figure 6.1 Likely ranges (i.e., likelihood .66%) of global mean temperature rise by 2100 relative to the historical climate in the different SRES (IPCC, 2007) and RCP (IPCC, 2013) scenarios; the ranges in the different SRES scenarios are relative to the period 1980 1999 while those in the RCP scenarios are relative to the period 1986 2005.

RCP scenarios (IPCC, 2013). These scenarios are also adopted in the AR6 of the IPCC, which was published in 2021, in conjunction with another set of scenarios referred to as the SSP scenarios (IPCC, 2021). For the sake of comparison, the likely ranges of the global mean temperature rise at the end of century are illustrated in Fig. 6.1 for the SRES and the RCP scenarios. These scenarios are commonly adopted in most infrastructure-related climate change risk analysis studies (see, e.g., Stewart et al., 2011; Yang and Frangopol, 2019). It should be highlighted that, under the current state of knowledge, accurate probabilities cannot be reliably assigned to the occurrence of the different scenarios (van Vuuren et al., 2011).

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The third major source of uncertainty in assessments of climate change projections relates to climate models and their representation of the climate sensitivity. As an example, some climate models show increasing wind speed over parts of Western Europe while others do not (Kjellstro¨m et al., 2018). The contribution of each of the three uncertainty sources to the total uncertainty in climate change projections varies depending on several factors. For instance, in Hawkins and Sutton (2009), the contribution of internal variability to the total uncertainty was found to be substantially higher on regional scale projections in comparison to global scale projections and more in a short-term perspective with relatively small climate forcing than in a long-term perspective with strong climate forcing.

6.3

Climate change risks to bridges

Over 30 potential climate change risks to bridges have been identified in a previous study by Nasr et al. (2019), see Fig. 6.2. This section discusses five of these risks in more detail, namely: (1) accelerated material degradation, (2) increased long-term deformations, (3) higher scour rates, (4) higher risk of thermally induced stresses, and (5) higher risks from extreme natural events. It should be highlighted, however, that the selection of these risks does not reflect their criticality. The criticality of each risk would differ depending on the characteristics of the considered bridge and its location. Hence, no inference about the criticality of the different climate change risks to bridges should be drawn from the discussion herein. The interested reader is referred to Nasr et al. (2019) where a more elaborate discussion of climate change risks to bridges can be found.

6.3.1 Accelerated material degradation Material degradation is a significant aspect in the design and management of all bridge types, including concrete, steel, and timber bridges. In general, infrastructure deterioration is frequently highlighted as a major concern, even without considering climate change impacts. The annual direct cost of infrastructure deterioration was estimated in 2002 to be B22.6 billion USD in the United States alone (Koch et al., 2002). More recent estimates of this number may be significantly higher. In Australia, the annual cost of corrosion is estimated to be B32 billion AUD (B23.3 billion USD) (Nguyen et al., 2013). In the United Kingdom, the annual cost of corrosion damage to highway bridges is estimated to be B1 billion GBP in England and Wales alone (B1.34 billion USD) (Kashani et al., 2019). In addition, severe deterioration of bridges without proper inspection and maintenance can lead to more dire consequences that involve fatalities and/or injuries. In this regard, the tragic and well-known failure of the Silver Bridge in 1967, whose failure was partly attributed to severe deterioration and caused 46 fatalities, is a striking example (Cook et al., 2015; Lichtenstein, 1993). The more recent collapse of the poorly

Figure 6.2 Identified climate-change risks on bridges and the climate changes affecting them. Inside to outside: risk group, identified risk, responsible climatic change parameters. Arrows connecting the different risks represent the interdependencies discussed in (Nasr et al., 2019). D1: accelerated degradation of superstructure, D2: accelerated degradation of substructure, S1: heat-induced damage to pavements and railways, S2: increased long-term deformations, G1: higher scour rates, G2: bridge slope failure, G3: landslides, G4: foundation settlement, G5: rockfalls; debris flows; and snow avalanches, G6: soil liquefaction, G7: additional loads on piles, G8: clay shrinkage and swelling, I1: higher wave impact, I2: wind-induced loads, I3: additional snow loads on covered bridges, I4: thermally induced stresses, I5: drainage capacity, I6: hydrostatic pressure behind abutments, I7: loads on bridges with control sluice gates, I8: loss of prestressing force, I9: ice-induced loads, A1:water vessel collisions, A2: vehicle-pier collisions, A3: vehicle accidents, A4: train-pier collisions, E1: floods, E2: storms, E3: wildfires, O1: snow removal costs, O2: temporary bridge restrictions, O3: power shortage; Pm, Pk: higher and lower precipitation in some regions respectively, Tm: higher temperatures, Wm: more frequent/intense extreme winds, SLR: sea level rise, RHm, RHk: increase and decrease in relative humidity respectively, PFk: permafrost melt, P2: increase in precipitation contrast, Fm: higher in-cloud liquid water content of marine fogs, CCm: higher carbon concentrations, SRm: higher solar radiation, OTm: higher ocean temperature, PHk: decrease in global ocean pH, SFm: higher snowfall, Sm: increase in storms intensity/frequency, HWm: increase in intensity/frequency of heat waves, T2: higher temperature seasonal contrast, ROm: higher runoff, Wk: decrease in wind speeds, WL2: increased water fluctuations in rivers, SSm: higher soil salinity.

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maintained Morandi Bridge over the Polcevera River, Genova, Italy in 2018 with 43 fatalities is another (Calvi et al., 2019; Malomo et al., 2020). With respect to reinforced concrete bridges (and also concrete infrastructure in general), several studies have found that climate change can have undesirable effects on their durability, that is, accelerate their deterioration (Bastidas-Arteaga et al., 2010; Ko¨lio¨ et al., 2014; Mortagi & Ghosh, 2022; Nasr et al., 2022; Stewart et al., 2011; Wang et al., 2011). The main drivers of these negative effects include projected increase in temperatures, changes in the relative humidity, and increases in atmospheric carbon concentrations. One study conducted in 2011 determined a 400% increase in the risk of carbonation-induced damage in concrete infrastructure by the end of the century under certain climate change scenarios for some regions in Australia (Stewart et al., 2011). It should, however, be highlighted that the potential drop in the relative humidity in some regions can have some positive effects on the deterioration rate of concrete infrastructure, that is, even decrease the rate of deterioration (Bastidas-Arteaga & Stewart, 2015). The durability of steel bridges and other metallic infrastructure can also be negatively impacted by some of the projected changes to the climate in the future (Chaves et al., 2016; Cole & Paterson, 2013; Kumar & Imam, 2013; Nguyen et al., 2013; Roberge, 2013; Tidblad, 2012; Trivedi et al., 2014). In Tidblad (2012), for instance, it was found that, for some locations in Europe, the change in the corrosion rate of metals due to climate change can be as high as one corrosivity category (referring to five different corrosivity categories ranging from very low to very high, see Tidblad (2012)). The projected increase in temperature, changes in precipitation patterns, changes in relative humidity, changes in atmospheric carbon concentrations, and changes in atmospheric SO2 concentrations are the main contributors to the impact of climate change on the deterioration of metallic infrastructure (Nguyen et al., 2013). It is important, however, to note that the decrease in atmospheric SO2 concentrations, which is projected in most countries of the developed world due to the introduction of cleaner and more efficient technologies, can have considerable positive effects on the corrosion of metallic infrastructure (Nguyen et al., 2013). A critical aspect in both the design and maintenance of timber bridges is their durability performance. Studies of the influence of climate change on timber infrastructure have determined that these may degrade faster in some locations due to climate change (Bjarnadottir et al., 2013; Merschman et al., 2020; Nasr et al., 2022; Ryan et al., 2016; Salman et al., 2017). Fungal decay is the main mechanism in which timber elements deteriorate (Kumar & Imam, 2013). In Wang et al. (2008), a fungal decay model was developed based on a comprehensive study spanning over close to 40 years. According to this model, the projected increase in temperature and the projected increase in precipitation in some locations are predicted to increase the decay rate of timber infrastructure. For instance, a study conducted in 2012, which used the aforementioned decay model, showed that by the year 2080 an increase of up to 10% in the median decay rate in Brisbane and Sydney in Australia is projected (Wang & Wang, 2012). In addition to fungal decay, some studies have suggested that climate change can increase the degradation of timber

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structures due to insect attacks in some locations (Schwartz, 2010). This effect was attributed to, for example, the projected shorter and warmer winters which provide less harsh environments for insects.

6.3.2 Increased long-term deformations Long-term deformations (i.e., creep) of bridges are mainly a serviceability problem. However, in the case of posttensioned concrete bridges or elements, these deformations may significantly reduce prestressing forces which, in extreme cases, can lead to potentially catastrophic consequences. For instance, the collapse of the KororBabeldaob Bridge in Palau in 1996 is attributed, at least partly, to a significant loss of prestressing forces as a result of excessive creep deformations (Baˇzant et al., 2011). This bridge, which was a segmentally erected prestressed box girder bridge, experienced on average a striking 50% loss of prestressing forces due to excessive creep deformations. It is worth noting that the authors of that study identified close to 60 other bridges in the world that showed excessive creep deformations similar to that of the Koror-Babeldaob Bridge. Furthermore, it is stated that many bridges with similar problems probably exist but were not identified. It is well known that long-term deformations of concrete structures are affected by the ambient environmental conditions (Baˇzant & Panula, 1978; Baˇzant et al., 2015; England & Ross, 1962; Geymayer, 1972). The projected higher temperatures in the future as well as lower relative humidity over land in many locations can both result in higher creep deformations. Many models for assessing creep of concrete structures can be found in literature. In Nasr, (2022) five different creep models are used to assess the impact of climate change on creep of concrete infrastructure. The study determined that the results depend highly on the creep model used. It was also highlighted that creep modeling uncertainty has a significantly larger effect on the end of century creep coefficient than climate uncertainty.

6.3.3 Higher local scour rates Local scour under submerged bridge foundations (i.e., the removal of riverbed material caused by the flow of water) have been frequently highlighted as one of the main initiating causes for bridge failures (Briaud et al., 2007; Briaud et al., 2014; Cook et al., 2015; Flint et al., 2017; Lamb et al., 2019). A notable example is the collapse of the I-90 Schoharie Creek Bridge in 1987 in New York, shown in Fig. 6.3, which resulted in 10 fatalities (Briaud et al., 2014; Cook et al., 2015). Due to this event, as well as the collapse of other bridges in the same flood, a national database of bridge failures in the United States was established (Cook et al., 2015). Other examples of bridge failures due to scour are abundant in literature (Hagerty et al., 1995; Lamb et al., 2019). Several studies have considered the impact of climate change on scour under bridge foundations (Dikanski et al., 2016; Dikanski et al., 2018; Ekuje, 2018; Kallias & Imam, 2016; Khandel & Soliman, 2019; Khelifa et al., 2013; Liu et al., 2020; Yang & Frangopol, 2019). Climate change can increase scour problems mainly due to the projected increase in river discharges in some locations. River

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Figure 6.3 The collapse of the I-90 Schoharie Creek Bridge in 1987; reprinted from USGS (2012).

discharges can increase due to the projected higher run-off in some locations. For instance, Yang and Frangopol (2019) found that a 20-year discharge event in the Lehigh River, Pennsylvania, USA in 2020 may become a 13-year event by the end of century reflecting an increased risk of scour in that river. Nonetheless, it is worth mentioning that in Kallias and Imam (2016) scour modeling uncertainty was found to play a more important role than climate change uncertainty in modeling the impact of climate change on bridge pier scour. Similarly, Dikanski et al. (2018) found that uncertainty related to bridge asset data (e.g., foundation depth) can have a bigger role in modeling the impact of climate change on bridge scour.

6.3.4 Additional demands on thermal deformation capacity and higher risk of thermally induced stresses During a heatwave in 2018 in Chicago, USA, the DuSable Bridge (which is a movable bridge that opens its deck to allow for navigation) could not be opened due to the heat-induced closure of its joint. This incident draws attention to the possible risk of increased demand on the thermal deformation capacity of bridges due to climate change (Nasr et al., 2019). If bridges are unable to meet this additional demand, thermally induced stresses may arise. Thermally induced stresses can be of particular importance to bridges and infrastructure in general (Elbadry & Ghali, 1986; Santilla´n et al., 2015). Hejnic (1988), for instance, studied the thermally induced stresses in the Klement Gottwlad Bridge, Prague, Czech Republic and found that the thermally induced tensile stresses were larger than the tensile stresses caused by the whole live load. In Hagedorn et al. (2019) two examples of bridge collapses during construction that can be attributed to thermally induced stresses are presented. The projected increase in temperatures in the future as well as the more intense/frequent heat waves are the main climatic drivers for this risk. In

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addition, the possible higher solar radiation in some places (IPCC, 2021; McKenzie et al., 2011) may increase the temperature gradient between the top and bottom of bridge decks and result in stress increases. Few studies have focused on studying the impact of climate change on thermal deformations and stresses in infrastructure (Corce et al., 2017; Larsson, 2015; Santilla´n et al., 2015). Santilla´n et al. (2015), for instance, developed a methodology for assessing the impact of the higher future temperatures on the thermal stresses and displacements of infrastructure elements. For demonstrating the developed method, a case study of an arch dam was investigated. It was found that the annual average radial displacements can increase substantially due to climate change. Furthermore, the tensile stresses were also found to be affected by the future climatic conditions.

6.3.5 Higher risks from extreme natural events Extreme natural events (e.g., floods, storms, wildfires, earthquakes, etc.) are a major cause of infrastructure damage and failure worldwide (Hinkel et al., 2014; Hoeppe, 2016; Jevrejeva et al., 2018; Padgett et al., 2008; Ward et al., 2017). In Ward et al. (2017), for instance, the expected global annual damage due to river floods in urban areas under current conditions was estimated to exceed 90 billion USD even when current protection standards are included. According to Padgett et al. (2008) the total bridge damage and failure costs due to Hurricane Katrina, which occurred in August 2005, is estimated to have exceeded 1 billion USD. The literature is abundant with other examples of devastating extreme natural events (see, e.g., Lindsea, 1993; Easterling et al., 2000; Barredo, 2006). Although climate change can affect a number of different extreme natural events, for example, wildfires and tsunamis (Alhamid et al., 2022; McGuire, 2012; Nasr et al., 2019), this section focuses on floods and storms. Several studies have focused on investigating the impacts of climate change on floods (Allamano et al., 2009; Batchabani et al., 2016; Bronstert, 2003; Huang et al., 2012). Batchabani et al. (2016), for instance, studied flood levels in the Riviere Des Prairies Basin, Quebec, Canada under considerations of a changing climate. In the study, it was predicted that two bridges in the study area may be totally submerged under water due to flooding in the period 2040 2060. Allamano et al. (2009) found that 100-year flood events in the Swiss Alps will have 20 years return period (i.e., their frequency will increase fivefold) under a 2 C warming and a 10% increase in precipitation intensity. Increase in precipitation intensity/frequency and/ or sea level rise are the main parameters that have been cited to cause an increase in flood intensity/frequency due to climate change. In addition, in Schellnhuber et al. (2012) it is proposed that the projected decrease in ocean pH, increase in ocean temperature, and increase in the intensity and frequency of tropical cyclones can have a detrimental effect on the growth of coral reefs; reefs that provide a natural protection against floods. Beck et al. (2018) highlight the importance of coral reefs for reducing flood damages and estimate a twofold increase in the annual expected damages from flooding without coral reefs.

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The impact of climate change on storms have been investigated in several studies (Bjarnadottir et al., 2011; Bjarnadottir et al., 2013; Contento et al., 2020; Esmaeili & Barbato, 2021; Ryan et al., 2016; Salman & Li, 2017; Salman, Li, & Bastidas-Arteaga, 2017; Stewart & Li, 2010). Esmaeili and Barbato (2021), for instance, proposed a model for assessing the impact of climate change on hurricane wind hazards. In that study it was found that the design wind speeds along the US Gulf and Atlantic Coasts are expected to have an increase between 14% and 26% by the year 2060 depending on the considered climate change scenario. This increase corresponds to an average increase in the design wind-induced loads of between 30% and 59%. In addition to stronger and more frequent storms, sea level rise offers a higher launching level for storm surges which can further aggravate the impact of this risk. A formulation that can be used to predict storm surges under considerations of a changing climate was developed in Contento et al. (2020).

6.4

Design of bridges in a changing climate

As has been highlighted in the previous section, climate change can substantially affect the safety and performance of bridges and infrastructure in general. Hence, to ensure an unimpaired functionality of society (which will likely be critically dependent on the performance of infrastructure systems), it is important to consider these impacts in the design of bridges as integral links within transportation infrastructure networks. Nonetheless, the considerable uncertainty related to climate change (see Section 6.2) and its impacts on infrastructure renders this task extremely challenging. As a necessary first step towards solving this predicament, this section presents a conceptual framework that captures the different possible design choices in bridge design and gives guidance on how the problem can be approached in a rational manner. Four different design strategies for considering the impact of climate change in infrastructure design have been proposed in literature (Connor et al., 2013): (1) build to repair, (2) planned adaptation, (3) build for a predicted “pessimistic” scenario, and (4) progressive modification. In the first strategy, the infrastructure asset is designed based on current design provisions without regard to climate change. In the second, planned adaptation strategy, a low GHG emission’s scenario (or current provisions) is initially considered in design and features allowing for the infrastructure to be upgraded in the future to accommodate higher GHG emission’s scenarios are implemented. In the third strategy, the infrastructure is designed to accommodate a high GHG emission’s scenario. In the last design strategy, the infrastructure is progressively modified in response to climate change. Unlike planned adaptation, the initial design in this strategy does not necessarily allow for adaptability. However, the two strategies are very similar and, in many cases, planned adaptation is expected to outperform progressive modification (Connor et al., 2013). Hence, only the first three strategies are considered in the current framework.

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The logic of the framework is argued to be of relevance for broader infrastructure applications, but here focused on and exemplified for bridges. As a basis for the framework, alternative preliminary design solutions should be made, for example, for bridges, using different span arrangements, bridge types, material types, etc. Once the preliminary bridge solutions have been proposed, the framework then progresses according to the following five stages: (1) importance rating, (2) identification of the potential climate change risks, (3) analysis of the potential climate change risks, (4) design strategy selection, and (5) evaluating the final design. A detailed overview of the framework and the steps in each stage are presented in Fig. 6.4. In the remainder of this section these five stages are briefly discussed. The interested reader is referred to Nasr et al., (2021) for a more detailed description of the framework.

6.4.1 Stage 1: Importance rating The proposed framework starts with rating the importance of the bridge being designed. Different methods for rating bridge importance have been proposed in the literature (Leung et al., 2004; Moruza et al., 2016; Rowshan et al., 2003; Smith et al., 2002). Examples of criteria that are commonly used for importance rating are the Average Daily Traffic, the detour length, and the replacement cost and time for the bridge (see, e.g., Nasr et al., 2021, 2022). Here, it is also of importance to consider the wider infrastructure and societal impacts in assessing criticality (Svegrup et al., 2019). The output of this stage of the framework should guide the decision of whether a specific consideration of climate change in design is necessary or not. For uncritical bridges with low importance, a specific consideration of climate change is deemed unnecessary and hence a build to repair design strategy is selected. For critical bridges, however, a specific consideration of climate change is required.

6.4.2 Stage 2: Identification of potential climate change risks For bridges rated critical in Stage 1, a specific consideration of climate change impacts in design is suggested. For this purpose, climate change impacts relevant for the bridge under consideration need to be identified. Several methods can be used for risk identification (see e.g., Kaplan et al., 2001). Examples of commonly used risk identification methods include (Kaplan et al., 2001): (1) Failure Modes and Effects Analysis, (2) Hazard and Operations Analysis, (3) Event Trees, (4) Fault Trees, (5) Anticipatory Failure Determination, and (6) Holographic Modeling. An important criterion in risk identification is that the identified risks should be as exhaustive as possible (see, e.g., Aven and Zio, 2011; Chapman, 2001; Kaplan and Garrick, 1981; Kaplan et al., 2001; Raspotnig and Opdahl, 2013). Meeting this criterion often requires an appropriate combination of different risk identification methods. Several studies that aimed to identify climate change risks on infrastructure exists (Kumar & Imam, 2013; Meyer, 2008; Nasr et al., 2019; Schwartz, 2010) (see also Section 6.3).

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Figure 6.4 Conceptual framework for considering the risks of climate change in the design of bridges; Circles on the top left of each node represent the stage the node belongs to Nasr et al., (2021).

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6.4.3 Stage 3: Analysis of potential climate change risks Following the identification of the potential climate change risks in Stage 2 for the critical bridge proposals under consideration (from Stage 1), an analysis of these risks is required to differentiate between severe, significant, and negligible risks. In Nasr et al. (2022) a Multi Criteria Decision Analysis method is proposed that can be used for this purpose. In that method, climate change risks on bridges are represented by the following four components: (1) hazard (defined as the potential change in a climatic parameter within a certain reference period), (2) impact (defined as the probability of an adverse impact caused by the hazard), (3) vulnerability (defined as the probability of a reduction in performance and/or safety due to the hazard and the subsequent impact), and (4) the consequences of the reduction in performance and/or safety. The method is based on assessing these four components using indices and then aggregating them to rank the various risks. Many other examples of climate change risk analysis studies exist (Bastidas-Arteaga & Stewart, 2015; Dikanski et al., 2016; Seo & Caracoglia, 2015; Yang & Frangopol, 2019).

6.4.4 Stage 4: Design strategy selection Based on the results of Stage 3, the identified climate change risks for each critical bridge proposal can be categorized into severe, significant, or negligible. Subsequently, a design strategy can be chosen. For risks categorized as negligible, a build to repair strategy should be selected. Conversely, one of the two other design strategies (i.e., planned adaptation and build for a predicted “pessimistic” scenario) should be selected for risks categorized as nonnegligible (i.e., either severe or significant). For severe risks, relocating (or repurposing) the bridge in an effort to avoid the risk is first considered. However, relocation may not be feasible in many cases. If relocation is unfeasible or ineffective in avoiding the risk, a build for a predicted “pessimistic” scenario strategy should be selected. For risk categorized as significant, the framework guides the designer to consider: (1) whether the risk is observable or not? and (2) the costs associated with both design strategies (i.e., planned adaptation and build for a predicted “pessimistic” scenario) (see Nasr et al., (2021)). Following the selection of the design strategy for each risk, several final designs (corresponding to the alternative preliminary designs mentioned previously) are reached for the critical bridge proposals identified in Stage 1.

6.4.5 Stage 5: Evaluating the final design In the last stage of the framework, each of the alternative final bridge design solutions reached in the previous stages are evaluated considering the different climate change scenarios. Sa´nchez-Silva (2019) recently proposed that code provisions (which are primarily concerned with safety) should be supplemented with other provisions that address the long-term performance of infrastructure (e.g., robustness, resilience, and sustainability). The framework therefore includes that the final bridge design solutions should be evaluated from the following complementary perspectives: (1) risk

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acceptance requirements, (2) robustness requirements, (3) resilience requirements, and (4) sustainability requirements. Based on this evaluation, several acceptable final design solutions can be identified. These may then be compared from the four complementary perspectives mentioned above and the most suitable alternative may be selected.

6.5

Challenges and research needs

This chapter discussed the impacts of climate change to bridges and presented a conceptual framework for considering the impacts of climate change in bridge design. It should, however, be mentioned that the task of considering the impacts of climate change in bridge design in practice, through the application of the proposed, or any future, framework, presents several challenges. This section discusses the main challenges in terms of: (1) data availability and uncertainty and (2) challenges relating to the final design evaluation. More challenges and research needs can be found in Nasr et al., (2021).

6.5.1 Data availability and uncertainty A main challenge that precludes the consideration of climate change impacts in infrastructure design concerns data availability. Climate change projections, which are essential for the analysis of specific climate change risks, are often unavailable. Even when such data are available, the temporal and/or spatial resolution of the available data may not be suitable for assessing a specific climate change risk for a certain asset, that is, bridge. In the few cases where climate change projections with the necessary temporal and spatial resolution are available, analyzing climate change risks is still subject to considerable uncertainties. Climate change projections are characterized by several interacting uncertainties (as outlined in Section 6.2). Moreover, assessing the three other components of climate change risks on bridges described in Section 6.4.3 (i.e., impact, vulnerability, and consequences) involve considerable uncertainties. For instance, assessing the impact component of the risk of increased corrosion of reinforced concrete bridges is characterized by relatively high uncertainties related to the adopted models as well as uncertainties related to the input parameters in these models (see, e.g., Stewart et al., 2011). This also applies to the other climate change risks described in Section 6.3 [see, for instance, for the risk of increased long-term deformations and Dikanski et al. (2018) for the risk of higher scour rates]. A consistent treatment of climate change related risks to future or existing bridges then requires that these uncertainties are acknowledged and suitably considered in the decision-making process.

6.5.2 Challenges related to final design evaluation Important challenges that impede the application of the proposed conceptual framework in practice relate to the evaluation of the final bridge design solutions. As stated earlier, the final design should be evaluated with regards to: (1) risk acceptance requirements, (2) robustness requirements, (3) resilience requirements, and

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(4) sustainability requirements. Although probabilistic risk acceptance criteria can be found in the literature, there is no clear consensus on these criteria (see e.g., Nasr et al., 2021; Stewart et al., 2013). Risk acceptability in the context of climate change risk assessments is even more problematic and has, to the best of the authors’ knowledge, never been thoroughly investigated. With respect to the other three requirements, it has been highlighted in the literature that probabilistic acceptance criteria for robustness, resilience, and sustainability are missing from current literature and that establishing such criteria is required (Bocchini et al., 2014; Faber et al., 2020). It should be mentioned that the aforementioned issues, which may fall far beyond the scope of traditional structural engineering, exist even for the case of standard bridge design (without consideration of potential climate change impacts). Another relevant issue highlighted in, e.g., Aldunce et al. (2015) and Kim et al. (2019), concern significant problems in communicating resilience from research to practice. It is presumable that this also applies to both robustness and sustainability. Hence, developing practical guidelines that aids in clearly defining these concepts, their relation to one another, and their assessment methods is highly desirable. It is clear that more research and development are necessary to fully realize the potential of viable climate change adaptation strategies and especially in practice; refer to Nasr et al., (2021) for more discussions on these issues.

Acknowledgments The authors gratefully acknowledge the financial support provided by the Swedish Transport Administration [grant numbers 2016-008 and 2019-027], the Swedish Research Council (Formas) [grant number 2015-00451], and the strategic innovation program InfraSweden2030 [grant number 2018-00611], a joint effort of Sweden’s Innovation Agency (Vinnova), the Swedish Research Council (Formas), and the Swedish Energy Agency (Energimyndigheten). Any opinions, findings, or conclusions stated herein are those of the authors and do not necessarily reflect the opinions of the financiers.

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Smith, M.C., Rowshan, S., Krill, S.J., Jr., Seplow, J.E., & Sauntry, W.C. (2002). A guide to highway vulnerability assessment for critical asset identification and protection. Washington, DC: The American Association of State Highway and Transportation Officials (AASHTO). https://trid.trb.org/view/718608. Stewart, M. G., & Li, Y. (2010). Methodologies for economic impact and adaptation assessment of cyclone damage risks due to climate change. Australian Journal of Structural Engineering, 10 (2), 121 135. Available from https://doi.org/10.1080/13287982.2010.11465038. Stewart, M. G., O’Callaghan, D., & Hartley, M. (2013). Review of QTRA and risk-based cost-benefit assessment of tree management. Arboriculture & Urban Forestry, 39(4), 165 172. Stewart, M. G., Wang, X., & Nguyen, M. N. (2011). Climate change impact and risks of concrete infrastructure deterioration. Engineering Structures, 33(4), 1326 1337. Available from https://doi.org/10.1016/j.engstruct.2011.01.010. Svegrup, L., Johansson, J., & Hassel, H. (2019). Integration of critical infrastructure and societal consequences models: Impact on Swedish power system mitigation decisions. Risk Analysis, 39(9), 1970 1996. Available from https://doi.org/10.1111/risa.13272. Thacker, S., Adshead, D., Fay, M., Hallegatte, S., Harvey, M., Meller, H., O’Regan, N., Rozenberg, J., Watkins, G., & Hall, J. W. (2019). Infrastructure for sustainable development. Nature Sustainability, 2(4), 324 331. Tidblad, J. (2012). Atmospheric corrosion of metals in 2010 2039 and 2070 2099. Atmospheric Environment, 55, 1 6. Available from https://doi.org/10.1016/j.atmosenv.2012.02.081. Trivedi, N. S., Venkatraman, M. S., Chu, C., & Cole, I. S. (2014). Effect of climate change on corrosion rates of structures in Australia. Climatic Change, 124(1-2), 133 146. Available from https://doi.org/10.1007/s10584-014-1099-y. USGS. (2012). The Schoharie creek bridge. http://water.usgs.gov/wid/images/NY.figure.id.3.gif. van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., . . . Rose, S. K. (2011). The representative concentration pathways: An overview. Climatic Change, 109(1-2), 5 31. Available from https://doi.org/10.1007/s10584-011-0148-z. Wang, C., & Wang, X. (2012). Vulnerability of timber in ground contact to fungal decay under climate change. Climatic Change, 115(3-4), 777 794. Available from https://doi. org/10.1007/s10584-012-0454-0. Wang, C.-H., Leicester, R.H., & Nguyen, M. (2008). Timber durability technical report. Manual no. 3 Decay in ground contact. Highett, Australia: CSIRO and FWPRDC. https://www.fwpa.com.au/images/marketaccess/ManualNo3-IG%20Decay.pdf. Wang, X., Stewart, M. G., & Nguyen, M. (2011). Impact of climate change on corrosion and damage to concrete infrastructure in Australia. Climatic Change, 110(3-4), 941 957. Available from https://doi.org/10.1007/s10584-011-0124-7. Ward, P. J., Jongman, B., Aerts, J. C. J. H., Bates, P. D., Botzen, W. J. W., Diaz Loaiza, A., . . . Winsemius, H. C. (2017). A global framework for future costs and benefits of riverflood protection in urban areas. Nature Climate Change, 7(9), 642 646. Available from https://doi.org/10.1038/nclimate3350. Yang, D. Y., & Frangopol, D. M. (2019). Physics-based assessment of climate change impact on long-term regional bridge scour risk using hydrologic modeling: Application to Lehigh River watershed. Journal of Bridge Engineering, 24(11). Available from https:// doi.org/10.1061/(asce)be.1943-5592.0001462.

Resilience of concrete infrastructures

7

Davide Forcellini1 and Rijalul Fikri2 1 Department of Civil and Environmental Engineering, University of San Marino, Serravalle, San Marino, 2Department of Civil Engineering, Syiah Kuala University, Banda Aceh, Indonesia

7.1

Introduction

Anthropogenic climate change is expected to impact human and natural systems all over the world. In particular, after the UN Framework Convention on Climate Change, climate change has gained prominence over time since the frequency and magnitude of climate disasters have been increasing (Khan & Munira, 2021; Khan & Roberts, 2013). In this regard, the Intergovernmental Panel on Climate Change Special Report on Global Warming of 1.5 C (2018) assessed that “Warming of 1.5 C is not considered ‘safe’ for most nations and poses significant risks to natural and human systems.” In this regard, climate change is modifying scientific attitudes toward pre- and postevent assessments of natural hazards. Unprecedented levels of destruction need renewed focus on addressing and protecting communities forcing the decisionmakers to change their attention to vulnerability and risk assessment. In particular, society and economy rely heavily on infrastructures, as fundamental links for movement of goods and people, and are extremely vulnerable to multiple hazards (such as droughts, floods, storms, and coastal hazards), as shown in several contributions (i.e., Mortagi & Ghosh, 2020, 2022; Nay et al., 2014; Turner et al., 2016). Moreover, the magnitude and extent of future impacts depends not just on the dynamics of the earth system, but also on socio-economic factors, such as population dynamics, economic development, technological change, social, cultural, and institutional changes, and policies. (Van Vuuren et al., 2014). In this regard, infrastructure is one of the most sensitive sectors that are sensitive to climate impacts which impacts multisectors, such as the environment, civil structures and infrastructures, biology, and economy. These impacts commonly concentrate on the municipal level, facilitated by higher-level government investments, as shown in Ford et al. (2011). In this background, infrastructure vulnerability to natural hazards is an increasing topic in civil engineering (Forcellini, 2021a) with many contributions (such as Dehgani et al., 2014; Eidsvig et al., 2017; Moini, 2015; Nourzad & Pradhan, 2015). In particular, long-term effects (i.e., deterioration and life-cycle loads) need to be considered inside risk-based frameworks in order to include the effects of climate Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00009-3 © 2023 Elsevier Ltd. All rights reserved.

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change. As proposed by Forcellini (2021a), vulnerability of infrastructures can be assessed by applying resilience to include the long-term effects due to climate change. The ultimate objective is to predict how the change of specific environmental variables will impact on the resilience, as a parameter to define the vulnerability of infrastructures. In this regard, this formulation may be applied in long-term assessments that can be useful by several stakeholders, such as public administrators, infrastructure owners, or other decision-makers. Resilience from natural disasters has becoming a relevant issue for civil communities that rely particularly on infrastructures, being significantly exposed to natural disasters and thus quantitative estimations of seismic resilience (SR) are fundamental to define pre- and posthazard decision-making procedures. In particular, risk assessment methodologies become crucial in planning adequate mitigation procedures and recovery activities to minimize the disruptions. (Andrı´c & Lu, 2017). In this regard, resilience quantifies the recovery time (RT) and procedures in order to facilitate and enhance event mitigation and emergency response strategies of transportation systems and entire communities (Argyroudis et al., 2019, 2020a).

7.2

Concrete resilience

Reinforced concrete structures are commonly used for civil infrastructure construction around the world, representing a multitrillion dollar construction investment, where these infrastructures facilities are intended to provide the mobility of goods and people in supporting the economic growth and sustainable development of modern society. In addition, in the postevent emergency response period, these concrete infrastructures are predominantly critical facilities to deploy logistic relief and resources to repair the damaging facilities. The structural durability of reinforced concrete structures may deteriorate over time due to the chemicalphysical attack of aggressive agents, such as sulfates and chlorides, associated with environmental conditions (Bertolini, 2008; Comite´ EuroInternational du, 1992). Generally, this aging concrete exhibited damage mechanism that can critically affect the life-cycle performance of concrete structures. These mechanisms include chemical processes associated with carbonation, leaching, sulfate and chloride attacks, reinforcing steel corrosion, and alkali silica reactions; physical processes because of freeze/thaw cycles and thermal cycles; and mechanical processes, such as cracking, abrasion, erosion, and fatigue (Ellingwood, 2005). Reinforcement corrosion caused by Chloride in concrete structures which are among the most common and detrimental deterioration processes that can affect structural performance of concrete infrastructures over their service life (Biondini & Frangopol, 2016). The reinforcing steel corrosion initiated when carbonation producing a decrease in pH in the carbonated part of the concrete and chloride substance at the reinforcing steel surface exceeded the threshold level of a certain critical chloride substance. The reinforcing steel corrosion can further propagate

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depending upon the properties of concrete, including the concrete cover thickness, and the temperature humidity of reinforcement surface (Nilsson et al., 2016). The service life and deteriorated reinforced concrete infrastructure due to reinforcing steel corrosion can be modeled based on the Tuutti’s model (1982), as presented in Fig. 7.2. Service-life can be defined as the end period of reinforcement corrosion. The service-life simple model of reinforcing steel corrosion presented in Fig. 7.1 consisted of the initiation of carbonation (CO2, CL) when it reached the surface of reinforcing steel. The depth of carbonation (xCO3) can be calculated as: xCO3ðtSLÞ 5 d

(7.1)

where tSL is the service life and d is the concrete cover thickness. Another model considered a certain level of chloride substance at the surface of reinforcing steel C(x 5 d, tSL), that exceeded the chloride threshold level, Ccr, is presented in Fig. 7.2, with the principle of the service model can be calculated using Eq. (7.1) (Nilsson et al., 2016), shown below: C ðx 5 d; tSLÞ 5 Ccr

(7.2)

The deterioration process of aging concrete infrastructures can result in a detrimental performance of these infrastructures under service loadings or unexpected collapse under extreme natural disaster events, including natural hazards, such as: earthquakes, typhoon, and floods, and human-made disasters, such as fire, explosion blast, and vehicular collisions (Ellingwood, 2005; Frangopol, 2011). When concrete infrastructures, such as buildings and bridges, are damaged in the disaster events, they could spread failures to other infrastructure systems, including transportation, and consequently lead to extensive disturbance for infrastructure networks (Guidotti et al., 2016). Thus modeling of the infrastructure networks dependencies is required

Figure 7.1 Service-life model for reinforcing steel corrosion.

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Figure 7.2 The principles service-life model when chloride ingress reinforcing steel corrosion.

to assess the resilience of critical infrastructures, and it is expected to enhance the robustness and resilience of infrastructure networks. Additional studies undertaken by Mortagi and Ghosh (2020, 2022) investigated the impact of aging structural components, including corrosion deterioration within reinforced concrete structure, caused by climate change to resist lateral load and the seismic fragility of these highway bridges under earthquake-imposed loadings. Their studies developed a framework for seismic fragility of highway bridges incorporating earthquake hazard, aging effects, and global warming due to climate change. This proposed framework has been applied to some multispan continuous (MSC) steel girder bridges in the Central and Southeastern United States, with the result showing that the effects of climate change can potentially reduce the seismic performance of aging bridge structures. In addition, a framework for lifetime seismic losses of highway bridges considering the earthquake hazard, aging effects, and global warming was also proposed to inform the decision-maker and investor. This framework was also applied to MSC steel and concrete girder highway bridges, with the results demonstrating that these bridges were seismically vulnerable, and the lifetime seismic losses were forecasted for about 6.7% for the MSC steel bridges and about 13.2% for the MSC concrete girder bridges. The design methods for resilience of deteriorated concrete infrastructure can be categorized into prescriptive design and performance-based concepts. Prescriptive design concept comprises of the concrete material characteristics, including raw materials, mix proportions, batching, mixing, and transport of fresh concrete and the stage of construction from concrete pouring to curing (Torrent, 2016). In addition, this prescriptive design considers exposure conditions and concrete compressive strength specified in current building codes in different countries. The prescriptive design for concrete resilience incorporates the selection of exposure conditions, the compliance of material and concrete cover specifications, and also concrete pouring, compacting and curing methods. Despite the prescriptive design provides a simple methodology to assess the resilience of deteriorated concrete infrastructures through straightforward concrete parameters, there are some other parameters that need to be considered, including the different types of cement and addictive additions to the concrete, types of

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aggregate, and the use of new or recycled materials. The development of performance-based concept is designed to include quantitative predictions for concrete durability (or service life) from existing exposure conditions and material characteristics that are not included in the prescriptive design concept (Beushausen, 2016). The performance of deteriorated of lifetime concrete infrastructure is calculated using durability indicators of the actual concrete adopted the appropriated deterioration model and compared with the environmental actions. The aggressiveness of environmental actions can affect the durability performance of concrete infrastructures. There are important environmental conditions, including temperature, relative humidity, nature and concentration of the aggressive agents and freezethaw cycles, that are commonly classified as exposure conditions (Bastidas-Arteaga & Stewart, 2018). These environmental actions could vary between regions or countries, and they can also vary between various part of the same structures. Consequently, when calculating the durability model of deteriorated concrete infrastructure, the relevant environmental conditions need to be considered and quantified for specific concrete structures. The calculation of concrete durability adopted the performance-based design concept can be proceeded from the prescriptive design concept by using framework proposed by Harrison (1995), as follows: G

G

G

G

G

G

G

Determine exposure conditions based on the mechanism of concrete deterioration; Develop a quantitative design concept, incorporates the determination of the end of service life; Establish test methodology for various input parameters of the design method; Generate conditional compliance criteria and calibrate with traditional design method; Specify the limitations of test applicability; Certify the production control and acceptance of testing; and Undertake full-scale trials and long-term monitoring to ensure compliance requirements.

In addition, the practical application of performance-based design concept in durability requirements, and service life assessment, there are some elements proposed by Walraven (2008) required to be established, as follows: G

G

G

G

G

G

Limit state criteria; A defined service life; Deterioration models; Compliance tests; A strategy for maintenance and repair; and Quality control systems.

It is considered that the performance-based design concrete can be a significant innovation for assessing deteriorated concrete infrastructure, despite this concept having some limitations including the inaccuracy to model the circumstances of various deterioration process that affect the concrete structures. However, this inaccuracy can be overcome by using the physical models that take testing different conditions, including the ageing phenomena and microstructural changes. Note that when the laboratory condition has a large different to site condition, the large uncertainty needs to be considered for the calculation of concrete infrastructure performance (Beushausen, 2016).

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Resilience

Resilience has been defined in several ways during the last decades. Wildavsky (1988) defined resilience as “the capacity to cope with unanticipated dangers after they have become manifest, learning to bounce back,” expressing two important concepts: (1) prevention from damages and (2) learning for future events. Holling et al. (1997) a decade later proposed a more specific definition: “the buffer capacity or the ability to a system to absorb perturbation, or magnitude of disturbance that can be absorbed before a system changes its structure by changing the variables” that expressed the principle of a change of the structural configuration of the system. Horne and Orr (1997) in the same year extended such definition to “individuals, group and organizations, and systems,” generalizing the application of resilience to a bigger scale. Mallak (1998) applied the concept to health care provider organizations, by defining resilience as “the ability of an individual or organization to expeditiously design and implement positive adaptive behaviors matched to the immediate situation, while enduring minimal stress.” The originality of this definition consists of the introduction of recovery inside resilience. Mileti (1999) proposed to consider the possibility of an “amount of assistance from outside the community.” This definition is novel for two points of view: (1) considering an eventual help from the outside and (2) extending the concept of resilience from systems to community. Comfort (1999) extended the concept of resilience to “the capacity to adapt existing resources and skills to new systems and operating conditions.” The key words in this definition are capacity and adaptation, meaning that resilience was intended as the possibility of an effective answer to changes due to an external event. Paton et al. (2000) described resilience as “an active process of self-righting, learned resourcefulness and growth the ability to function psychologically at a level far greater than expected given the individual’s capabilities and previous experiences.” This definition extended considerably the original definition by (1) considering resilience a process, (2) introducing the psychological contribution, and (3) referring to the individuals. In the early 2000s, other definitions were proposed [such as Kendra and Wachtendorf (2003), Cardona (2003), and Pelling (2003)], but probably the most famous was from Bruneau et al. (2003). These authors proposed an interrelated concept of resilience that considers technical, organizational, social, and economic dimensions that may assess the performance of critical systems (i.e., electric power, water, road infrastructures, and critical structures) and the social and economic dimensions of communities. The most comprehensive definition may be considered the one presented by UNISDR (2005) in the so-called Hyogo Framework. Resilience was defined as “the capacity of a system, community or society potentially exposed to hazards to adapt, by resisting or changing in order to reach and maintain an acceptable level of functioning and structure. This is determined by the degree to which the social system is capable of organizing itself to increase this capacity for learning from past disasters for better future protection and to improve risk reduction measures.” This modern definition took into account several contributions from the previous, in particularly, by

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underling the importance to the social dimension and the role of learning from the past and future protection actions. Bruneau and Reinhorn (2007) and Cimellaro et al. (2010) developed an analytical formulation to quantitatively calculated resilience by including RT (the period necessary to restore the functionality of the system to a desired level). Therefore resilience graphically represents the normalized shaded area underneath the recovery function Q(t) that represents the process of recovery from the time of the event (t0E) to the time that is defined as the RT. Such functions depend on two important contributions (1) the loss model to assess the reduction of functionality due to the impact of the event and (2) the recovery model to describe a series of event, actions or changes to enhance the capacity of an affected system or a community, as shown in Forcellini (2021a). Therefore the quantitatively formulation of resilience is defined as: R5

ð t0E 1RT t0E

QðtÞ dt RT

(7.3)

where t0E is the time of occurrence of the event E, RT is the repair time (or recovery time) necessary to restore the functionality, and Q(t) is the recovery function that quantifies the recovery process to return to the preevent level of functionality. Such definition has been applied in different case studies, such as Cimellaro et al. (2009), that applied Eq. (7.3) for the assessment of the SR of a hospital system. Later, Forcellini (2017a, 2020) considered the same theoretical formulation in the study of the SR of isolated bridge configurations with soil-structure interaction. Ranjbar and Naderpour (2020) considered Eq. (7.3) inside the probabilistic evaluation of the SR of buildings by applying vulnerability curves. In particular, as shown in the JOINT RESEARCH PROJECT by the European Commission (Caverzan and Solomos, 2014) resilience calculation depends on two important models: a loss model and a recovery model. (1) A loss model is necessary to assess the reduction of functionality due to the impact of hazards and (2) a recovery model to represent the complex process that comprises a series of event, actions, or changes to enhance the capacity of an infrastructure when faced with events.

7.3.1 Loss model Loss model aims to assess to assess the reduction of functionality due to the impact of events in correspondence with the time of occurrence of the considered events. In infrastructures such losses need to be divided in direct and indirect. As recently proposed by Ranjbar and Naderpour (2020), direct and indirect losses can be divided in the losses directly identified as the economic costs and those related to the casualties. Moreover, Argyroudis et al. (2020b) proposed a methodology based on resilience to assess vulnerability of bridges including direct and indirect losses.

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Direct losses are those connected with the damages of the structural and nonstructural elements. Traditionally expected direct costs were calculated as the sum of the losses associated with all the vulnerable components failure/damage states in all possible conditions. Their calculation is generally based on the implementation of fragility curves, a probability-based approach that has been developed in the last decades in structural engineering. Indirect losses are defined as those associated with system failures by a scenario-based approach regarding the condition states of the components (Saydam et al., 2013). However indirect losses have many consequences and uncertainties that need to be assessed using interdisciplinary approaches. In particular, the assessment of indirect losses is challenging and implementing their calculation in a comprehensive framework may be a difficult issue (Forcellini, 2016, 2019a) because of several reasons. The extreme variability of this typology of losses and the dependency of indirect losses on structures and on network conditions, do not allow a unique definition. In this regard, Meyer et al. (2013) summarized various methods used to assess indirect costs, such as: 1. firm- or household-level surveys relating to past events (e.g., McCarty and Smith, 2005); 2. econometric methods (e.g., Noy and Nualsri, 2007; Skidmore and Toya; 2002; Strobl, 2011); 3. inputoutput models (e.g., Martin-Ortega et al., 2012; Okuyama et al., 2004; Perez y Perez and Barreiro-Hurl’e, 2009); 4. CGE models (e.g., Berrittella et al., 2007; Boyd and Ibarrar’an, 2009; Pauw et al., 2010; Rose and Liao, 2005; Tsuchiya et al., 2007; Wittwer and Griffith, 2010); and 5. intermediary models between CGE models and Input Output models (e.g., Hallegatte, 2008).

In addition, other approaches are used to estimate indirect costs considering the impact of natural disasters on public finances (Mechler et al., 2006) assessing indirect costs in terms of the Government’s capacity to cope with large amounts of expenditure due to natural disasters and their subsequent ability to deliver basic services in the aftermath. In addition, indirect losses were estimated with idealized models that emphasize the role or one or more particular relation(s) or mechanism(s) in economic systems subjected to hazards (e.g., Hallegatte and Dumas, 2008; Hallegatte and Ghil, 2008). Other contributions estimated indirect losses on communities, such as droughts (e.g., Berrittella et al., 2007; Boyd and Ibarrar’an, 2009; Horridge et al., 2005; Islam, 2003; Logar and van den Bergh, 2013; Martin-Ortega et al., 2012; Pauw et al., 2010; Wittwer and Griffith, 2010), coastal hazards due to Hurricane Katrina (Hallegatte, 2008), riverine flooding (Green et al., 2011; Przyluski and Hallegatte, 2011), and alpine hazards (Kletzan et al., 2004; Nothiger, 2003). Moreover, Masiero and Maggi (2009) assessed indirect losses due to the two weeks closure of the north-south Gotthard road corridor.

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Furthermore, transportation infrastructures have some basic traits in common, such as large size, wide-area coverage, complexity, and interconnectedness, but may show significant differences in details. Most of such differences depend on (inter)dependencies that should not be neglected in vulnerability assessments (Kro¨ger and Zio, 2011). Interdependencies are fundamental in the evaluation of connectivity and Rinaldi et al. (2001) provided an overview of how to identify, understand, and analyze them. To provide a detailed description and modeling of interdependent infrastructures, many relevant data are required and often are inaccessible due to, for example, confidentiality and privacy issues and a reluctance to share data (Ouyang, 2014). However, the assessment of indirect costs needs to consider the mutual effect of different infrastructures that can supply each other when the functionality of one of them is reduced or fails. Two typologies of indirect losses are herein considered, as proposed by Adey et al. (2004) (prolongation time and connectivity losses).

7.3.2 Prolongation of travel Indirect losses connected with prolongation of travel (PT) are caused by interventions on the infrastructure and the consequent detours that might be needed. Losses due to PT are important when a network is redundant and there are other alternative networks that can be used to cover the journey. The economic impact of wasting work and leisure time traveling may be considered as the loss of productivity of the users due to time spent traveling (Adey et al., 2012). Hackl et al. (2018) proposed to calculate the indirect costs due to additional travel time, vehicle operating costs, and accidents as the difference between costs at time t and the costs at t 5 0, when the network was totally functional. The authors introduced costs as a function that depends on the traffic flow. Therefore it is fundamental to define the travel time as the amount of time traveling on the road, determined by speed driven which in turn is affected by various factors [such as condition, capacity, and geometry of the road and thus the daily traffic volume (Adey et al., 2012)]. The existing approaches calculate PT losses as the difference between the traffic flow after and before the event, requiring the knowledge of such flows that can be difficult to be estimated in case of preevent assessments and they are affected my many uncertainties. Since these approaches are deterministic, they cannot model the uncertainties related to inputs, such as restoration time and cost (Luna et al., 2011).

7.3.3 Connectivity loss Connectivity loss (CL) is principally due to the loss of economic activity that occurs when travel is not possible or the journey can become prohibitive for commercial and industrial traffic and the entire journey is not covered anymore. In particular, connectivity can be defined as the property of being joined, linked, or fastened together and the purpose of a network is to establish and maintain such

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property to facilitate the movement of valuable goods and services across a system. This intangible nature of CL makes the assessment relatively challenging. In addition, the estimation of CL losses becomes even more challenging since connectivity depends on the way networks are interconnected (Grubesic et al., 2008). In addition, CL quantifies the average decrease of the ability of distribution of movements along the infrastructure and relies on the topological structure of the network and flow patterns, requiring performance measures to capture network RT and longterm reliability after disruptions (Duenas-Osorio et al., 2017). Hackl et al. (2018) proposes a deterministic approach that consists in defining a cost function to assess CL, without considering the uncertainties connected with such definition. On the other side, the formulation by Forcellini (2016) proposed to calculate CL as proportional to repair time, introducing the coefficient c that generally varies from 0 to 1 (but may be bigger than 1, when CLs are bigger than direct costs).

7.3.4 Recovery model Recovery model describes the procedure to recover from the event. In particular, it represents the variation of the functionality of the system over the time. Such curves are particularly challenging to be defined since they present disparities among different geographic areas in the same community or state, showing different rates and quality of recovery. Different types of recovery function can be selected depending on the system and society preparedness response and this article investigates the three possible recovery functions proposed in literature: linear (Fig. 7.3A), exponential (Kafali and Grigoriu, 2005; Fig. 7.3B), and trigonometric (Chang and Shinozuka, 2004; Fig. 7.3C). The parameters in the figures are: G

G

G

QI is the initial functionality at t0; QE is the final functionality at the end of the recovery process and that the system will recover at the repair time; L is total loss that determinates the level of functionality due to the hazards and the first point of the recovery function (at the occurrence time t0E) and calculated with the loss model.

7.4

A case study

The calculation of resilience is herein proposed for a case study, under the assumption that resilience is the best investment decision parameter for a bridge leading to a proposed decision-making framework accounting for posthazard event mitigation, emergency response strategies and recovery investments on bridges. The results may benefit public administrators and transportation asset owners who will be able to establish a list of investments for retrofit options for bridge different configurations. In addition, the responses may prompt new concepts and tools for strategic and operational planning purposes. Stakeholders can assess investment options for potentially vulnerable bridges depending on the predicted losses in terms of costs and time.

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Figure 7.3 Recovery model [(A) linear, (B) exponential, and (C) trigonometric].

In this regard, several functionalitytime curves have been proposed and compared to identify which is the most realistic representation of recovery behavior for bridge configurations. As identified by Cimellaro et al. (2010), quantification of resilience depends on the definition of two issues. First, it is fundamental to define the RT that a bridge need to recover from the instant that a certain event occurs. The quantification of such variable is not object of this paper, since it has already investigated in previous publications

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(Forcellini, 2016, 2017a). In particular, RT are calculated by applying the Pacific Earthquake Engineering Research center (Mackie et al., 2011) methodology implemented inside the platform BridgePBEE (Lu et al., 2011). Peak ground acceleration (PGA) was used as the reference intensity measure for the fragility curves (Mackie et al., 2011). The calculation of RT associated with the calculated limit states is based on the Caltrans Comparative Bridge Costs database (Caltrans, 2003). In particular, RT values are calculated by a probabilistic procedure called the local linearization repair cost and time methodology developed by Mackie et al. (2008), and that comprised of the closed-form “Fourway method” (Mackie and Stojadinovic, 2006), piecewise power-law approach, and Monte Carlo simulations. Second, resilience quantification depends on the analytical functions applied to calculate the recovery of functionality from the reduced to the final one (Fig. 7.4). In this regard, this case study applies the state-of-the-art procedures to calculate RT and several assumptions were considered: 1. the proposal of an analytical formulation for calculating the recovery of functionality; 2. the use of repair time from the PBEE methodology; and 3. the calculation of resilience as the primary parameter used to guide investment decisions for a bridge after an earthquake.

The recovery process is herein described with a continuous function that assess the increase of bridge functionality (Q) in dependence with time (t). Q is defined as the percentage of the preearthquake functionality and its trend is defined as follows: QðtÞ 5 βUðt2t0E Þα 1 Q0

(7.4)

β represents the ratio between the final functionality Q and the original value of functionality (that is assumed equal to one). This ratio can generally vary from 0 to

Figure 7.4 Proposed framework: (1) calculated by applying BridgePBEE (Lu et al., 2011). (2) Recovery functions proposed in the present article [parameters: (a): β 5 1; α 5 1; (b): β 5 0.7; α 5 0.85; (c): β 5 0.5; α 5 0.75].

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1 (0%100%). Sometimes recovery procedures allow an improvement relative to the original functionality, and this value can be higher than 1.0. α defines the exponent of the growth and it is related to the specific strategy applied. It depends on many uncertainties and can be assessed only by statistical approaches, such as optimization procedures. In addition, as previously specified, recovery process after an earthquake is a complex procedure that depends on many factors, such as interdependencies among infrastructure systems (Ouyang and Wang, 2015), the state of the entire network (Miller-Hooks et al., 2012), and the surrounding region (Cimellaro et al., 2010). In particular, in the case study, the three different trends (linear, exponential, and trigonometric) shown in Fig. 7.3 are considered, depending on community preparedness. In this regard, α describes the rate of increase in functionality given by recovery procedures and thus its physical meaning is the speed to reach the final functionality (bigger values of a means quicker recoveries), defining the exponent of the growth. For linear increases, this value is 1 as proposed by Minaie et al. (2017). In general, realistic values of are smaller than 1, to model a less than linear increase in functionality. Q0 is the level of functionality due to the impact of the earthquake in correspondence with the time of occurrence of the event E (t0E) and may be calculated by knowing the losses (L in Fig. 7.3). The proposed formulation (2) is based on a limited number of parameters and a mathematical structure (power function) that can describe restoration procedures more realistically than the linear one. At the same time (2) allows a certain flexibility in the calibration procedures with available data sources to cover various bridge classes, different bridge characteristics and specific recovery procedures. In particular, four parameters (t0E, β, α, and Q0) need to be defined on the basis of existing database that are fundamental in two steps: Step 1: calculation of RT that is obtained by implementing production rates (PR) defined in terms of crew working days (CWD). Step 2: calibration of the analytical curves (2) that need to be consistent with practical experience coming from bridge multisectorial actors (i.e., bridge owners, transportation authorities and public administrators). Fig. 7.5 shows the structural configuration (model 1) that represents ordinary California highway bridges, designed according to the Caltrans Seismic Design Criteria (Caltrans, 2003) and classified as Ordinary Standard Bridges. More details are in Mackie et al. (2012). The deck and the abutments are connected with elastomeric bearing pads that can freely translate longitudinally realizing simple roller connections that allow no resistance in longitudinal direction such that the horizontal movement is permitted. Vertical and transversal directions are restrained (Forcellini, 2017b). The pier and deck are connected with a fixed connection (i.e., translation is restrained in all directions). This scheme was assumed to represent the base conditions of the existing bridge. More details are in Forcellini (2017b, 2018, 2019b). The numerical models have been built up following the assumptions applied in the previous Forcellini (2017a, 2017c, 2021b).

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Figure 7.5 Benchmark bridge (Forcellini, 2018, 2019a).

The study was conducted to explore the effectiveness of the proposed framework as a tool for decision-making procedures. RT were calculated by applying BridgePBEE (Lu et al., 2011). Resilience was quantified adopting the recovery functions proposed in the present article (parameters: t0E, β, α, and Q0), as explained below. In the following, the level of functionality in correspondence with the time of occurrence of the event E (t0E), was considered 0% (Q0 5 0) Three configurations were considered by applying base isolation which has been shown to improve the performance of the bridge, in cases of rigid soils (Forcellini, 2017b). This work considered three isolated configurations that were selected and calibrated in Forcellini (2017b), demonstrating for each of them the vulnerabilities and risks. The framework is able to develop adaptive methods as to evaluate the investments for each of these solutions. Therefore the original configuration (model 1) can be strengthened with three retrofitted configurations (alternative investment options): Model 2: deck—abutments connections using elastomeric bearings while the pier-deck connection is fixed; Model 3: pier—deck connection consisting of elastomeric bearings at the top of the pier, while deck and abutments are free to move (no restraint); and Model 4: a double-isolated configuration with elastomeric bearings atop each abutment and on the top of the pier. In addition, as shown in Forcellini (2016), three retrofit scenarios (named S1, S2, and S3 in the following) were modeled to the define the possibility to consider several indirect costs in terms of loss of connectivity (depending on the network redundancy) and prolongation of down time due to extreme events. The choice of these three retrofit scenarios is not detailed in this article because part of a previous publication (Forcellini, 2016, 2019a). However, it is important here to consider that in the previous work, scenarios were calibrated in order to evaluate the effects of different typologies of losses (direct and indirect) on the performance of the solutions. In the present work, repair time (RT) were calculated for each configurations (investments) and under each scenario. They were quantified by CWD are shown in Figs. 7.67.9. It is worth to notice that the rate of RT to PGA is reduced in scenarios in which the isolation techniques are implemented. In particular, in

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RT (CWD)

70 60

S3

50

S2

40

S1

30 20 10

model 1

0 0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

PGA (g)

Figure 7.6 Model 1—nonretrofitted bridge. 70

RT (CWD)

60

S3

50

S2

40

S1

30 20 10

model 2

0 0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

PGA (g)

Figure 7.7 Model 2—abutments connections.

RT (CWD)

70 60

S3

50

S2

40

S1

30 20 10

model 3

0 0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

PGA (g)

Figure 7.8 Model 3—deck connection.

RT (CWD)

70 60

S3

50

S2

40

S1

30 20 10 0 0.00

model 4 0.10

0.20

0.30

0.40

0.50

PGA (g)

Figure 7.9 Model 4—double-isolated configuration.

0.60

0.70

0.80

0.90

1.00

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correspondence of model 1 (the original) the values of RT stabilize around the ultimate values for a PGA of 0.55 g. For model 2 this trend occurs for higher values of PGA (around 0.65 g). Models 3 and 4 (the ones with the isolation between the pier and the deck) still have a crescent trend in the range of the considered PGA values. For PGA equal to 1 g, these configurations have not still reached any stable value of RT.

7.4.1 Calculation To calculate the resilience, RT needs to be calculated as the interval between the instant of the event (t0E) and the instant when functionality is (fully or partially) recovered. Therefore it is necessary to define a particular level of PGA, in correspondence of which RT can be calculated. Tables 7.17.3 show the values of RT, calculated for values for three levels of PGA—0.25, 0.50, and 0.75 g—were used as reference intensities. Figs. 7.107.18 show the dependence of SR to α in correspondence with the chosen PGA values and all the models and scenarios. It is fundamental to consider that the various values of α represent different recovery functions, as shown in (2). Table 7.1 RT (CWD: crew working days); PGA 5 0.25 g. PGA 5 0.25 g

S1 (CWD)

S2 (CWD)

S3 (CWD)

Model 1 Model 2 Model 3 Model 4

3.25 3.11 0.10 0.10

4.75 4.61 0.20 0.20

9.25 9.11 0.50 0.50

Table 7.2 RT (CWD: crew working days); PGA 5 0.50 g. PGA 5 0.50 g

S1 (CWD)

S2 (CWD)

S3 (CWD)

Model 1 Model 2 Model 3 Model 4

36.45 26.19 11.76 9.55

43.03 32.77 16.70 14.49

62.77 52.51 31.52 29.31

Table 7.3 RT (CWD: crew working days); PGA 5 0.75 g. PGA 5 0.75 g

S1 (CWD)

S2 (CWD)

S3 (CWD)

Model 1 Model 2 Model 3 Model 4

42.65 42.36 22.02 17.86

49.23 48.94 27.36 23.30

68.97 68.68 43.38 39.22

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Figure 7.10 Seismic resilience, S1, PGA 5 0.25 g.

Figure 7.11 Seismic resilience, S2, PGA 5 0.25 g.

Figure 7.12 Seismic resilience, S3, PGA 5 0.25 g.

In particular, Cimellaro et al. (2010) and Minaie et al. (2017) considered linear assumptions. However, both recommended that more realistic recovery functions should be utilized in such resilience assessments. The presented figures demonstrate that many cases considering a linear function leads to overconservative results. The outcomes indicate the importance of calibrating α, as a key parameter in the recovery procedures. Model 3 and Model 4 have the same trend as one another

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Figure 7.13 Seismic resilience, S1, PGA 5 0.50 g.

Figure 7.14 Seismic resilience, S2, PGA 5 0.50 g.

Figure 7.15 Seismic resilience, S3, PGA 5 0.50 g.

(see Figs. 7.107.13) but note the decrease of resilience as α increases which occurs when RT is less than 1 due to the power function producing larger values than are produced using a linear representation. However, in correspondence with low values of PGA (0.25 g), models 3 and 4 have RT less than 1 CWD. Therefore Figs. 7.107.13 show almost constant values of Q (or even decreasing trends). These curves are shown to confirm that for this cases, model 1 functionality was predicted to be good with no need of recovery actions.

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Figure 7.16 Seismic resilience, S1, PGA 5 0.75 g.

Figure 7.17 Seismic resilience, S2, PGA 5 0.75 g.

Figure 7.18 Seismic resilience, S3, PGA 5 0.75 g.

In addition, models 1 and 2 have similar recovery trends for the different scenarios for small values of PGA (0.25 g) and for highest levels (0.75 g). These results show that the presence of the isolation on the abutments does not seem significant in increasing resilience. Therefore the original configuration performs considerably well in correspondence with the abutments and there is no need to isolate them.

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In other words, model 2 is not a convenient investment for recovery purposes, especially for extreme values of PGA. On the contrary, models 3 and 4 show increases in resilience for all the considered scenarios and for all values of PGA. Tables 7.47.6 show the values of SR for the considered values of PGA and for the scenarios. It is possible to assess the increases of models 3 and 4 respect with model 1. Comparing the different scenarios, it is worth to notice that models 1 and 2 seems to have similar trends for all the scenarios. On the contrary, models 3 and 4 are more sensitive to the scenarios. In particular, the biggest values are reached in correspondence with scenario 3. Table 7.4 Seismic resilience, PGA 5 0.25 g. PGA 5 0.25 g

α 5 0.25

α 5 0.375

α 5 0.50 α 5 0.75

α 5 0.875

α51

Model 1—S1 Model 2—S1 Model 3—S1 Model 4—S1 Model 1—S2 Model 2—S2 Model 3—S2 Model 4—S2 Model 1—S3 Model 2—S3 Model 3—S3 Model 4—S3

0.299 0.332 1.000 1.000 0.232 0.257 1.000 1.000 0.148 0.162 1.000 1.000

0.314 0.346 0.960 0.960 0.257 0.280 0.973 0.973 0.178 0.191 0.988 0.988

0.334 0.364 0.934 0.934 0.286 0.308 0.953 0.953 0.215 0.228 0.979 0.979

0.416 0.437 0.894 0.894 0.410 0.426 0.920 0.920 0.397 0.406 0.959 0.959

0.451 0.470 0.889 0.889 0.467 0.480 0.914 0.914 0.491 0.498 0.955 0.955

0.384 0.409 0.903 0.903 0.362 0.380 0.928 0.928 0.322 0.332 0.965 0.965

Table 7.5 Seismic resilience, PGA 5 0.50 g. PGA 5 0.50 g α 5 0.25

α 5 0.375

α 5 0.50

α 5 0.75

α 5 0.875

α51

Model 1—S1 Model 2—S1 Model 3—S1 Model 4—S1 Model 1—S2 Model 2—S2 Model 3—S2 Model 4—S2 Model 1—S3 Model 2—S3 Model 3—S3 Model 4—S3

0.088 0.402 0.837 0.903 0.083 0.362 0.794 0.853 0.071 0.280 0.705 0.749

0.127 0.432 0.852 0.914 0.122 0.393 0.812 0.868 0.110 0.314 0.727 0.770

0.268 0.533 0.894 0.947 0.268 0.505 0.868 0.916 0.265 0.445 0.807 0.845

0.392 0.617 0.925 0.971 0.401 0.602 0.911 0.952 0.415 0.568 0.876 0.908

0.575 0.737 0.965 1.000 0.601 0.745 0.969 1.000 0.652 0.759 0.977 1.000

0.062 0.381 0.826 0.894 0.057 0.340 0.781 0.841 0.047 0.258 0.689 0.734

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Table 7.6 Seismic resilience, PGA 5 0.75 g. PGA 5 0.75 g

α 5 0.25

α 5 0.375

α 5 0.50

α 5 0.75

α 5 0.875

α51

Model 1—S1 Model 2—S1 Model 3—S1 Model 4—S1 Model 1—S2 Model 2—S2 Model 3—S2 Model 4—S2 Model 1—S3 Model 2—S3 Model 3—S3 Model 4—S3

0.061 0.069 0.663 0.784 0.056 0.064 0.630 0.738 0.047 0.052 0.560 0.643

0.088 0.096 0.681 0.799 0.083 0.091 0.648 0.755 0.072 0.078 0.579 0.661

0.129 0.137 0.705 0.819 0.124 0.132 0.674 0.777 0.112 0.118 0.607 0.687

0.283 0.290 0.784 0.882 0.282 0.289 0.763 0.852 0.277 0.282 0.714 0.784

0.422 0.428 0.849 0.932 0.429 0.434 0.838 0.914 0.439 0.443 0.811 0.871

0.632 0.637 0.938 1.000 0.654 0.658 0.945 1.000 0.699 0.702 0.958 1.000

Furthermore, model 4 is shown to be the most resilient model under whatever scenarios and conditions. The difference in SR with model 3 does not appear to be significant. The difference between model 2 behavior and the outcomes of models 3 and 4 (where the pier is isolated) is fundamental. Therefore it is possible to see the importance of isolating the pier in order to improve the seismic performance of the bridge and thus the validity of investment corresponding with model 3. On the contrary, isolating the abutments is not so fundamental when isolation on the pier is present. Overall, the presented framework allows readable findings for a wider range of stakeholders that those resulted by simply considering structural performance. In this regard, the results can be of interest for multisectorial actors, such as bridge owners, transportation authorities and public administrators. Consequently, the framework allows interdisciplinary applications, such as the assessment of recovery techniques and solutions and/or new easy-to-use decision-making approaches.

7.5

Conclusions

Resilience has been here defined by following its historical development with considering several contributions in literature from different fields and disciplines. Several definitions have been discussed and considered with the more developed concept that resilience acquired during the last decades. In particular, the quantification of resilience has become the most interesting aspect in order to be applied in realistic assessments. In this regard, resilience has been discussed in the more specific field of concrete material by considering the main peculiarities in terms of properties, potentialities and limitations. Therefore the application of resilience to infrastructure has been described with the various models and the state-of-the-art

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approach. In particular, it has been presented the definition of recovery functions consisting in analytical functions between time and functionality that can quantify recovery and thus calculate resilience. Several functionalitytime curves have been showed and compared in order to identify which may be the most realistic representation of recovery behavior for infrastructures. Finally, a case study has been presented in order to apply the SRRIB methodology that implements functionalitytime curves in order to calculated the seismic resilience of an existing bridge and three possible scenarios. The results allow to assess the various investments by presenting readable findings for a wide range of different stakeholders, such as infrastructure owners, public administrations and city planners. The main focus was on the multidisciplinary dimension of the proposed SRRIB methodology that makes this approach significant and interesting with many potential developments and applications among bridge decision-makers all over the world.

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Masiero, L., & Maggi, R. (2009). Estimation of indirect cost and evaluation of protective measures for infrastructure vulnerability: A case study on the transalpine transport corridor. NFP54 “Sustainable Development of the Built Environment”. Project founded by the Swiss National Science Foundation. McCarty, C., & Smith, S.K. (2005). Florida’s 2004 Hurricane season: Local effects. Florida Focus, University of Florida. http://www.bebr.ufl.edu/sites/default/files/FloridaFocus1320050.pdf. Mechler, R., Linnerooth-Bayer, J., & Peppiatt, D. (2006). Microinsurance for natural disasters in developing countries: Benefits, limitations and viability. ProVention Consortium. http://www.proventionconsortium.org/themes/default/pdfs/MicroinsurancestudyJuly06. pdf. Meyer, V., Becker, N., Markantonis, V., Schwarze, R., van den Bergh, J. C. J. M., Bouwer, L. M., Bubeck, P., Ciavola, P., Genovese, E., Green, C., Hallegatte, S., Kreibich, H., Lequeux, Q., Logar, I., Papyrakis, E., Pfurtscheller, C., Poussin, J., Przyluski, V., Thieken, A. H., & Viavattene, C. (2013). Review article: Assessing the costs of natural hazards  state of the art and knowledge gaps. Natural Hazards and Earth System Sciences, 13, 13511373. Available from https://doi.org/10.5194/nhess13-1351-2013. Mileti, D.S. (1999). Disasters by design: A reassessment of natural hazards in the United States. National Academies Press. Miller-Hooks, E., Zhang, X., & Faturechi, R. (2012). Measuring and maximizing resilience of freight transportation networks. Computers and Operations Research, 7(39), 16331643. Minaie, E., & Moon, F. (2017). Practical and simplified approach for quantifying bridge resilience. Journal of Infrastructure Systems, 23(4), 0401701. Moini, N. (2015). Modeling of risks threatening critical infrastructures: System approach. Journal of Infrastructure Systems, 22, 04015010. Mortagi, M., & Ghosh, J. (2020). Climate change considerations for seismic vulnerability assessment of aging highway bridges. ASCE—ASME Journal of Risk and Unc. Mortagi, M., & Ghosh, J. (2022). Consideration of climate change effects on the seismic lifecycle cost analysis of deteriorating highway bridges. Journal of Bridge Engineering, 27 (2), 04021103. Nay, J. J., Abkowitz, M., Chu, E., Gallagher, D., & Wright, H. (2014). A review of decisionsupport models for adaptation to climate change in the context of development. Climate and Development, 6, 357367. Nothiger, C. (2003). Naturgefahren und Tourismus in den Alpen—Untersucht am Lawinenwinter 1999 in der Schweiz, Eidgen€ossisches, Institut f€ur Schnee und Lawinenforschung (SLF). Nilsson, L-O., Kamali-Bernard, S., & Santhanam, M. (2016). Durability of reinforced concrete structures and penetrability. In Performance-Based Specifications and Control of Concrete Durability, (pp. 917). Dordrecht: Springer. Nourzad, S. H. H., & Pradhan, A. (2015). Vulnerability of infrastructure systems: Macroscopic analysis of critical disruptions on road networks. Journal of Infrastructure Systems, 22. Noy, I., & Nualsri, A. (2007). What do exogenous shocks tell us about growth theories? Working paper 07-28, University of Hawaii. Okuyama, Y., Hewings, G., & Sonis, M. (2004). Measuring the economic impacts of disasters: Interregional input-output analysis using the sequential interindustry model”. In Y. Okuyama, & S. Chang (Eds.), Modeling spatial and economic impacts of disasters (p. 2004). Springer.

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Innocent Chirisa1,2, Tariro Nyevera3 and Thembani Moyo4 1 Administration, Ezekiel Guti University, Bindura, Zimbabwe, 2Department of Urban & Regional Planning, University of the Free State, Bloemfontein, South Africa, 3 Development Governance Institute (DEGI), Harare, Zimbabwe, 4Department of Urban & Regional Planning, University of Johannesburg, Johannesburg, South Africa

8.1

Introduction

Africa’s development is highly dependent on an adequate, reliable road system. Given emerging trends, climate change is expected to take a heavy toll on the region’s transport infrastructure on roads and bridges (Moretti & Loprencipe, 2018; Piryonesi & El-Diraby, 2021). To address this challenge, the World Bank has outlined the need to develop cost-effective and appropriate adaptation pathways to inform planning and development under various climate scenarios (Epule et al., 2021; Meijer et al., 2018). Sarkodie and Strezov (2019) have also articulated how climate change will affect the African road system. To ensure road spending delivers the best possible return and brings lasting development benefits, investment plans must take into account the consequences of a changing climate, as road assets are particularly vulnerable to climate stressors, such as higher temperatures, increased precipitation, or flooding (Rydge et al., 2015). Virtually all models show that weather extremes will indeed place considerable pressure on Africa’s Road system. The damage and accelerated aging of roads caused by climate change will require increased maintenance and frequent rehabilitation. Aside from higher maintenance and rehabilitation costs, climate-related damage to the road infrastructure will also cause more frequent disruptions to the movement of people and goods with direct consequences on economic productivity (Leal Filho et al., 2019; Markolf et al., 2019; Salimi & Al-Ghamdi, 2020). The chapter seeks to express and explain the challenges associated with climate change on transportation infrastructure. It has been identified that climatic factors, such as rising temperatures, increased flood risk, and other potential hazards, threaten transportation networks’ reliable and efficient operation. The central idea in this chapter is the realization of these challenges and unpacking mitigation measures.

Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00005-6 © 2023 Elsevier Ltd. All rights reserved.

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Conceptual framework

Climate resilience can best be understood through articulating the meaning of resilience. The original meaning of resilience as presented by the Center for Climate and Energy Solutions (2019) is “to bounce back.” The term has through time since Francis Bacon’s reference in the 17th century been redefined but one thing that has stood the test of time is the bouncing back from a particular space. Hence, one has to be resilient to something, after understanding the threats and vulnerabilities of a particular event or phenomenon and the likelihood and consequence of these impacts. People living in coastal areas have to be resilient to water and if they live in dry areas, they have to be resilient to inadequate water. Thus climate resilience focuses on the planning required to bounce back from impacts of climate change (Fig. 8.1). Perera et al. (2021) have articulated how climate change complicates the design problem in urban development projects due to its multidimensional impacts on both the environment and infrastructure. As such, to ensure climate resilience, cities need to consider the frequency of extreme climate events and how existing systems can respond to these, as it becomes essential to resilience planning that enables improving the climate resilience of cities. Transportation infrastructures are complex networks that connect cities and accommodate human activities coupling the social, economic and environmental systems with urbanization and population growth. Wang and Banzhaf (2018) also outline that transportation networks contribute to socioeconomic development and increased quality of life by generating inter- or intracity connections during urbanization. Examples of transportation infrastructures include roads, railways, airports, seaports, bridges, and bus stations (Arbabi, 2019). The discussion of transportation infrastructures will not be adequate without referring to goals, such as low-carbon, resilient, and sustainable development. Thus Wang and Banzhaf (2018) have the understanding that transportation infrastructure among cities leads to urban aggregation and diffusion, boosting regional and national economic development. Also, irrational planning of transportation infrastructure generates negative effects, such as ecological destruction, increased traffic accidents, climate change, carbon dioxide emissions, and lower transport efficiency. Given how transportation infrastructure is essential in the economic development and growth of society (Magazzino & Mele, 2020; Wang et al., 2018), an efficient climateresilient transport infrastructure promotes economic growth at a local and national level. The importance of transportation infrastructure means that for urban development planning to meet its intended needs effectively, the provision of adequate resilience measures should be a top priority. Thus the pressing need for a climate-resilient transportation infrastructure that addresses the socioeconomic needs of the people would influence the nature of urban planning for developing nations. Transportation infrastructure is the backbone of ensuring the functionality and efficiency of cities.

8.3

Literature review

As greenhouse gas (GHG) emissions continue to rise, climate change will continue to accelerate. Emissions can be curbed but, the climate will continue to change for some

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Sustainable resource ulisaon

Low carbon economy

Energy efficiency and conservaon

Reduced Climate impact

Sustainable landscapes and livelihoods

Climate Resilience

Figure 8.1 Climate resilience (Musakwa et al., 2020; Shakou et al., 2019; Vallejo & Mullan, 2017). Source: Adapted from Musakwa, W., Mpofu, E. and Nyathi, N.A., (2020). Local community perceptions on landscape change, ecosystem services, climate change, and livelihoods in Gonarezhou National Park, Zimbabwe. Sustainability, 12 (11), 4610; Shakou, L. M., Wybo, J. L., Reniers, G., & Boustras, G. (2019). Developing an innovative framework for enhancing the resilience of critical infrastructure to climate change. Safety Science, 118, 364 378; Vallejo, L., & Mullan, M. (2017). Climate-resilient infrastructure: Getting the policies right.

time as the Earth’s system responds to the warming already underway. Therefore there is need of anticipating changes and minimizing future economic and social risks. Climate resilience is often associated with acute events—like heat waves, heavy downpours, hurricanes, or wildfires—that will become more frequent or intense as the climate changes (Tyler & Moench, 2012). The evaluation of such direct and indirect costs to critical infrastructure by climate change will lead to the development of systems that are climate-resilient (Asadabadi & Miller-Hooks, 2017).

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Dawson et al. (2018) also noted the increased interdependence between infrastructure systems, from critical infrastructure leading to amplified risks. Current adaption strategies are limited by the lack of coordination of efforts by the public and private sectors due to undefined responsibilities and areas of sharing synergies not being tapped into to ensure climate resilience (Dawson et al., 2018; Sun et al., 2020). Operationalizing resilience of critical infrastructure would call for holistic integration of data from sector-specific infrastructure asset management knowledge, traditional risk-based disaster analysis and emergency management techniques (Yang et al., 2019). However, good resilience planning also accounts for chronic events like rising sea levels, worsening air quality, and population migration. Cities and local communities are responding by investing in infrastructure updates and climate-smart planning to mitigate the impacts of acute and chronic events (Rydge et al., 2015). Understanding the local communities’ relationship with nature is crucial for the well-being and sustainable development in the face of climate change. As such, cities are developing climate change action plans that assist in identifying areas that are highly vulnerable to the effects of climate change (Mi et al., 2019; Reckien et al., 2018). Climate resilience can be introduced to these areas that are susceptible and unable to cope with adverse effects of climate change including climate variability and extremes. Shakou et al. (2019) have proposed a framework for climate resilience critical infrastructure. The strategies for climate resilience are defined for the short, medium, and long terms (Fig. 8.2). In the short term, ensures plans for critical infrastructure that can anticipate risk, become robust, adapt to emergencies, and recover from disasters. While the medium-term plans should be designed to anticipate the effects of climate change, addressing climate change and adaptive by incorporating new technologies and designs. Lastly, plans for the long-term should be robust and anticipate the effects of climate change on critical infrastructure, propose innovative solutions and lastly ensure transformation of critical infrastructure to ensure resilience. Quinn et al. (2018) also proposed a framework for climate-ready transport infrastructure composed of an adaptation strategy and implementation plan. The framework outlines the need to ensure that hazards, vulnerabilities and losses are assessed through a holistic risk appraisal. The framework stages include: (a) (b) (c) (d) (e) (f) (g)

Identification of objectives; Identification of hazards is informed by climate data; Identification of vulnerabilities is informed by risk assessment; Identification of consequential losses; Risk appraisal, that will be led to the development of an adaption strategy; Development of options when defining the scope of work during implementation; and Development of strategic action plans, that also enable a review and evaluation process.

Consequently, Quinn et al. (2018) framework place practical decision-making at the center of strategic decision-making to assist efforts to prevent the stagnation that can arise when making decisions for uncertain futures, given the uncertainty of the extent and impacts of climatic change.

Challenges surounding climate resilience on transportation infrastructures

Long term

• Anticipate - Robust decision-making, adaptation pathways, climate change risk assessment, indicators related to climate change • Innovate - Investment into innovation • Transform - Transformation of Critical infrastructure so they are decentralised, diverse, flexible and able to withstand a variable and unpredictable climate

Medium term

Short term

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• Anticipate - climate change risk assessment, indicators related to climate change • Innovate - Investment into innovation • Adapt - New designs, criteria and methodologies that seek to mitigate and adapt to climate change

• Anticipate - Risk Assessment, Early warning system, and monitoring key ecosystem variables • Absorb - Emergency plans, emergency teams • Recover - Emergency contacts with other Critical Infrastructures

Figure 8.2 Framework for climate-resilient of urban critical infrastructure. Source: Adapted from Shakou, L. M., Wybo, J. L., Reniers, G., & Boustras, G. (2019). Developing an innovative framework for enhancing the resilience of critical infrastructure to climate change. Safety Science, 118, 373.

Building on efforts to ensure climate-resilient critical infrastructure Vallejo and Mullan (2017) utilized case studies to assess the vulnerability of critical infrastructure. The findings from the case studies reveal key factors and challenges in ensuring climate resilience for critical infrastructure namely, a developing need for comprehensive support of system led by the government. There is a need for collaboration between the private and public sectors. The ecological resilience paradigm remains one of the critical infrastructure indicators across the globe (Hayes et al., 2019). This perspective recognizes infrastructure as part of complex socio-eco-technological systems. This has led to increased investment in developing robust critical infrastructure. This has been achieved through regenerative designs for critical infrastructure that are safe-to-fail, emergency responsive with built-in quality control monitoring systems (Hayes et al., 2019; Vallejo & Mullan, 2017). Argyroudis et al. (2019) assessed the impact of climate change on urban critical infrastructure. The findings from the study revealed the following steps as essential when,

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Defining the critical infrastructure; Selection of elements vulnerable to the climate; Development of a model for visualization; Mapping the effects of climate change on the critical infrastructure; and Introducing multiple fragility functions for the quantification of risk.

The assessment of the linkage between the environment, livelihoods, and climate resilience is essential for sustainable development (Chanza & Musakwa, 2021). The key issues in the local communities are air pollution from uncontrolled burning, clearing of land for informal settlements, and littering around areas of economic activities. There is a need for education campaigns and awareness of the adverse impacts and building capacity at key locations, such as community facilities. For example, a combination of nature-based solutions and building improvements like planting street trees and installing green roofs can help mitigate extreme heat (Berman & Sarra, 2021; Pieterse et al., 2018; Sorgho et al., 2020). Actions like these are important in historically marginalized communities, where climate impacts can exacerbate existing inequalities. Literature has revealed ways to cope with global warming with measures to reduce human-caused climate change (climate change mitigation) and measures to increase infrastructure resilience to the impacts of climate change (climate change adaptation) (Frischmann, 2021; Malhi et al., 2020; Williamson et al., 2018). The effects of global warming are already changing natural ecosystems, and the negative ecological impacts of climate change are becoming more apparent and very likely to intensify over the coming decades (Malhi et al., 2020). Transportation infrastructures, such as roads, railways, airports, seaports, bridges, and bus stations, play an important role in the transmission of materials and the flow of population during urban agglomeration and diffusion. OECD (2013) defines transportation infrastructure as a critical ingredient in economic development at all levels of income, supporting personal well-being and economic growth. Wang et al. (2018) also provide that from the perspective of function, transportation infrastructure is a large-scale public work that has an importation influence on countries politics, economy, society, science, technology development, environmental protection, public health, and national security. Pasimeni et al. (2019) articulated that globally, the key challenges for transportation infrastructures are building and maintaining roads given the threat of climate change. Given this threat, literature has revealed investment in green infrastructure, such as greenbelt corridors and integration of green infrastructure in transportation development plans, will lead to a sustainable and more resilient capacity in the face of climate risks to critical infrastructure (Kumar et al., 2021; Pasimeni et al., 2019; Shakou et al., 2020). Moretti and Loprencipe (2018) provide a novel view of transportation infrastructures, describing these as lifelines for goods and commuters in ordinary and emergency conditions. They should therefore be resilient to climate change. Cities have adopted strategies to ensure transportation infrastructures are resilient, these strategies seek to protect structures, limit damage, and continuously monitor the current condition of transportation infrastructures.

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8.4

167

Road transport infrastructure

Road transport infrastructure forms the physical links between regions and nations and is a key facilitator for the exchange of goods, services, and people and countries economic growth. Sahoo (2011) provides that road transport infrastructure has been recognized to significantly impact the overall GHG emissions. Road transport infrastructure can thus be defined as the road network and associated physical infrastructure, such as signage, lighting, and vehicle refueling service (Ness, 2008). Linked to the aspect of climate resilience and climate change, energy consumption, environmental impacts, and costs of a road transport infrastructure refer to three distinct but interlinked areas: the construction of the physical infrastructure and the associated construction materials, the road maintenance over time the road operation or use. Road operation or use is strongly related to the energy supply to vehicles that use the infrastructure and the energy required for infrastructure operation. Sahoo (2011) goes on the say that each area has associated energy use, emissions, and costs.

8.5

Railway transport infrastructure

Railways are defined as terrestrial mass transport systems (Pyrgidis, 2019). Pyrgidis (2019) also provides that trains move on their own (diesel traction) or remotely transmitted power (electrical traction) using steel wheels on a dedicated steel guideway defined by two parallel rails. Railways can extend to cover any distance in any environment be it urban, suburban, peri-urban, regional, or interurban. Pyrgidis (2016) also provides that the most suitable range for passenger transportation is usually suited to approximately 1500 km while for freight, the distances can be greater. Railway transportation by default should comprise of the railway infrastructure, rolling stock and railway operation. Railway infrastructure describes railway tracks and all the civil engineering structures and systems/premises that ensure the railway traffic. The railway track consists of a series of components of varying stiffness that transfer the static and dynamic traffic loads to the foundation.

8.6

Airport infrastructure

Airport infrastructure comprise airports, air traffic control centers and the organizations involved in coordinating their provision and use (Larsen, 2015). Even if one could eliminate carbon emissions, the delay in the atmospheric response would—according to scientific projections—make the future climate significantly different. Although the effects of climate change are prevalent, the main effects will be more evident after three or four decades, and it is worth bearing in mind that airport infrastructure erected in the present-day face new climate. All airports should carry out risk assessments of existing and new infrastructure to reduce risks and costs and ensure future punctuality and regularity in the aviation sector.

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Port infrastructure

Ports are the main industrial and commercial tools for the economic and social development of the countries. The port sector is affected by socioeconomic changes characterized by the requirements development in the countries through commitments by the countries of free trade and the new contexts of globalization to the new constraints and economic, institutional, technological, environmental, and maritime transport development (Monioudi et al., 2018). Therefore the seaports have always been disposed to changes in socioeconomic trends. These developments have created a highly uncertain and complex environment for ports and fundamentally changed the port concept. The seaport is a multidimensional system combined with economical function, infrastructure, geographical space, and trade. In addition, a seaport is managed under a complex legal concept and managed through an organizational model that mostly generates the need for convergence of the public and private sectors (Izaguirre et al., 2021; McIntosh & Becker, 2017). A bridge is a structure built to span a physical obstacle without blocking the way underneath. It is constructed to provide passage over the obstacle that is usually difficult or impossible to cross. Contemporary bridge infrastructure planners are facing several challenges to ensure the resilience of bridges as they seek to improve the availability and serviceability of aging infrastructure, while the maintenance planning is constrained by budget restrictions (Allah Bukhsh et al., 2019; Costin et al., 2018; Nasr et al., 2021). Based on the attributes of scaling factors, bridge infrastructure management in cities is becoming resilient to climate change (Argyroudis et al., 2020; Mondoro et al., 2018). A bus station or a bus interchange is a structure where city or intercity buses stop to pick up and drop off passengers. While the term bus depot can also be used to refer to a bus station, it generally refers to a bus garage. The bus station plays a crucial role in spatial integration as it is central to the principle of connectivity. As various modes of transport can be connected through bus stations, they benefit commuters through increased mobility while boosting the local economy. Therefore bus stations become connector points or activity nodes (Gumbo & Moyo, 2020; Hnatov et al., 2017). Consequently, any transit agency that plans to operate in urban areas should prepare for changes in planning and scheduling, operation and maintenance, fuel procurement, and supporting infrastructure as parts of efforts to ensure transportation infrastructure is resilient to climate change.

8.8

Research methodology

The research methods engaged for the study that informed the writing of this chapter included literature and document review. Published books, journal articles, and conference papers constituted literature and were instrumental in engaging past and current debates on challenges around climate resilience on transportation infrastructures. Document review, known as the archival method, engaged published and

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unpublished reports by government and civil society organizations. The idea was to get a triangulated picture of the reality on the subject matter at hand. The collected data were analyzed through content analysis.

8.8.1 Issues in seeking to achieve climate resilience Infrastructure financing is a perennial problem: the public sector tends to focus on immediate needs and raising funds for current expenditures rather than long-term investments. At the municipal or local authority level, many countries limit or ban independent debt financing by cities. In countries where borrowing is permissible, there is a resistance to debt financing infrastructure investments associated with concerns over creditworthiness. There is thus an “anti-infrastructure bias” (Meyer & Schwarze, 2019) built into the budgeting process that becomes acute when it comes to the incremental costs associated with climate-resilient infrastructure. Such investments, however, can mitigate climate risks and improve urban resilience and adaptive capacity. Financing infrastructure requires the translation of those benefits into measurable returns on investment in the context of emerging risks that capital markets can understand and appreciate (Meyer & Schwarze, 2019). This need is recognized by many international institutions and efforts are underway to encourage capital markets to invest in climate-resilient infrastructure. Public finance can be used to mobilize private finance for climate-resilient infrastructure (Mojafi, 2014). For example, publicly funded analysis of the risks faced by the port of Cartegena, Colombia motivated investment to manage climate risks. Support for project preparation can help to address capacity constraints relating to climate resilience. Blended finance can be used to improve the risk-return profile of investments where appropriate. Investing in infrastructure that serves populations whose climate vulnerabilities are exacerbated by societal inequalities can be impactful. Resilient infrastructure is designed and constructed with consideration of vulnerable populations, such as senior citizens, children, people with disabilities, low-income households, and those with restricted access to cars or public transportation. Infrastructure funding should be prioritized based on the number of homes affected and the potential for preventing loss of life, rather than the financial value of the assets that are at risk or affected. Climate resilience is the ability to anticipate, prepare for, and respond to hazardous events, trends, or disturbances related to climate. Improving climate resilience involves assessing how climate change will create new, or alter current, climaterelated risks, and taking steps to better cope with these risks. Given that infrastructure investments have an economic life expectancy of 30 years or more, it should be realized that it is sensitive to climatic conditions prevailing during its construction and to future climate variations (UNDP, 2011). Infrastructure is vulnerable to climate impacts so climate change concerns must be considered while designing infrastructure. Typically transport infrastructure is designed to withstand extreme events, however, TERI (2018) argues that current design standards do not meet the demands of climate change and emphasize the need to introduce a new design of infrastructure to be in coalescence with the environment. Institutions that design for transportation infrastructure face challenges of using only past climate patterns, that are likely to be altered due to climate change

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(TERI, 2018). Typically, transportation infrastructure is designed based on historic climate data and during their design life, they could be subjected to a varying climate that may be different from past climate trends. It is understood that climate is projected to change rapidly so that long-term climatic averages may be disturbed and the frequency and severity of extreme weather events may be overlooked in the planning and design of transportation infrastructure. TERI (2018) also provides that there are no enabling policies and environment to steer the current and future course of infrastructure management to ensure the mainstreaming of climate change concerns into infrastructure development. Climate proofing infrastructure will require additional financial costs. A World Bank study in 2010 estimates that the price tag between 2010 and 2050 for adapting to an approximately 2  C warmer world by 2050 will be in the range of $70 billion to $100 billion a year. This means that the prioritization of investment decisions for resilient infrastructure needs a comprehensive policy framework to integrate climate resilience, improve risk assessment and information and identify innovative financing mechanisms.

8.9

Case studies

8.9.1 Europe An efficient and reliable transport system is essential for society, for the transport of goods, for employment and leisure. Currently Europe’s transport systems struggle to cope with extreme weather events, and climate change is predicted to increase the frequency and severity of certain weather events (Forzieri et al., 2018). In addition, traffic prognoses show that freight volume transported on roads will increase by approx. 70% until 2030 (prognosis for German motorways). The entire transport infrastructure (road, rail, sea and inland waters) will be significantly impacted by climate change, affecting the way Europe’s transportation sector plan, design, construct and maintain infrastructure in the future (Lamb et al., 2019). On the basis that there will be a significant impact from climate change, and considering that all eventualities cannot be catered for, this roadmap aims to determine how road transport infrastructure shall adapt to the inevitable changes. Facing this situation road authorities need to be supported with appropriate strategies to ensure the reliability, availability, maintainability, and safety of road infrastructure (Sharifi, 2021). While many initiatives will look to mitigate the effects of climate change through the adoption of low carbon technology, some impacts are inevitable, and this roadmap sets out the steps required to maintain, and ideally improve the resilience of the three key transport networks (road, rail, and inland waterways) to extreme weather events, and specifically the key TEN-T European transport networks.

8.9.2 Asia Climate change is a global challenge that threatens sustainable development and places the prosperity and well-being of future generations at risk. As transport demand increases in the South Asia Region (SAR) due to population and economic

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growth, the need to provide sustainable and resilient transport services has become important (Khan et al., 2019; Shaffril et al., 2018). Disaster and climate risks are high in SAR, making infrastructure and communities particularly vulnerable. Flooding, landslides, extreme heat and wildfires are the main risks to be addressed. In specific locations, measures and investments are also critical to increase the adaptive capacity vis-a-vis cyclones, tsunamis along with coastal areas, and earthquakes. Rapid economic growth and urbanization are accelerating and magnifying the impact of climate change and natural disasters (Baruah, 2018; Zhang et al., 2018). Transport infrastructure incurs losses of US$15 billion on average from natural hazards at the global level, with low- and middle-income countries shouldering about 60 percent of the total amount (Shaffril et al., 2018; Reyer et al., 2017).

8.9.3 Africa Roads are a key asset for Africa—they connect villages to economic centers, people to hospitals, children to schools and goods to markets facilitating trade. This study considered 2.8 million km of roads in Sub-Saharan Africa, including new road construction outlined in the Programme for Infrastructure Development in Africa and assessed the impact of climate change on roads and bridges (Yakovleva et al., 2017). Climate change is expected to substantially increase the disruption time of the network, shorten their rehabilitation life cycle, and increase repair and rehabilitation costs. The study evaluates the economics of engineering solutions to build resilience to climate change impacts due to flooding, precipitation, and temperature and develops a methodology to assist decision-makers in identifying the most costeffective adaptation approach, comparing the cost of inaction (reactive response) to the net cost of investments in adaptation (proactive adaptation). Adequate road maintenance is critical and efficient in reducing the impact of a changing climate on the road system (Sharifi et al., 2021; Umar et al., 2020). Proactive adaptation is a cost-effective option in virtually all countries in response to anticipated higher temperatures, and in at least eight countries in response to precipitation (Adenle et al., 2017; Yakovleva et al., 2017). Better information on the benefits of avoiding climate-related disruption can inform decisions on proactive adaptation. Transportation infrastructure, such as roads and railway systems, is one of the sectors most threatened by climate change. Extreme weather events, such as flooding, sea level rises, and storm surges—repeatedly wreak havoc on transport networks. In Africa, extreme weather is a threat that can cause extensive structural damage. It can also accelerate the aging of infrastructure components (Scheffran et al., 2019). This can lead to considerable financial losses. A notable example is the Gautrain a Railway Rapid Transit System (Fig. 8.3), that operates across three metropolitan cities in South Africa with the Gaubus as an extension of the Gautrain service in the form of a bus rapid transportation system (Gumbo & Moyo, 2020). To mitigate the emission as part of efforts of long-term decarbonization of public vehicles, the Gautrain system is adopting new technologies, such as the electrification of services and switching to low-carbon alternatives. Such efforts should

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Figure 8.3 Gautrain a railway rapid transit system. Source: Adapted from Moyo, T., Kibangou, A. Y., & Musakwa, W. (2021). Societal contextdependent multi-modal transportation network augmentation in Johannesburg, South Africa. PLoS One, 16 (4), 12.

provide environmental and social benefits by improving market accessibility, reducing emissions and connecting communities (Moyo et al., 2021).

8.9.4 Latin America Climate change poses an enormous challenge to development, particularly in Latin America and the Caribbean (Reyer et al., 2017). Despite contributing less than 10% of global GHG emissions, the region’s countries already experience the tip of the climate change spear—from slow-onset droughts and floods to sudden-onset disasters—disrupting economic activity and livelihoods. Fig. 8.4 outlines the key elements in response, the region’s countries are leading the way in making the vision of climate-smart development a reality, moving with increasing urgency to develop more sustainable energy and transport systems; to strengthen the resilience of their cities, enhance nature-based solutions to climate mitigation and adaptation in forests, oceans, and agriculture; and to prepare people, public services, and infrastructure for the future climate shocks (Dobbs et al., 2019; Furley et al., 2018; Lattes et al., 2017). These countries submitted climate action pledges with Nationally Determined Contributions in the run-up to the historic Paris Agreement at COP21, and they are now raising their climate ambitions even further by submitting revised NDCs under the same process.

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Figure 8.4 Key elements of addressing climate change.

8.9.5 North America The North American economy and way of life are highly dependent on transportation systems that move goods and people locally, regionally, nationally, and internationally. Major disruptions to transportation networks due to natural hazards, manmade hazards (notably terrorist and cyberattacks), accidents, or infrastructure failure can cause substantial social and economic impacts (Miele et al., 2021). The impacts of climate change present a significant and growing risk to the safety, reliability, and sustainability of transportation infrastructure and operations. As disruptions in any part of the transportation system can trigger cascading delays and economic impacts across multiple systems, building resilience in the transportation sector can help cities recover from a range of events. While existing transportation infrastructure in countries like El Salvador, the United States, Canada, and Cuba was designed to handle a broad range of conditions based on historic climate, the frequency and intensity of some extreme weather events are increasing (Espinet et al., 2016). Transport infrastructure in North America undergoes a variety of climate hazards. The vulnerability differs in various regions and is influenced by the climatic events unfolding. For instance, the vulnerability of the transportation network of New York City, the most populous and crucial urban area in the United States, was underlined in the aftermath of Hurricane Sandy. El Salvador is vulnerable to natural hazards and exposed to a growing number of tropical storms and hurricanes from the Pacific and Atlantic Oceans. For Jamaica, however, the vulnerability is a combination of climatic events and climate change. Jamaica’s transportation system is already affected by weather extremes. Damage to roads, bridges, and supporting infrastructures, such as drains and culverts, is commonplace, both as a result of extreme events as well as outdated design and inadequate maintenance (Monioudi et al., 2018).

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8.9.6 Australia and New Zealand New Zealand’s transport system is interdependent. It comprises a network whose demand is derived from local communities and the wider economy. People use this network for economic and social purposes, such as commuting, shifting freight, and visiting friends and family. Transport also provides critical links during emergencies. Climate change affects the transport network itself. It causes damage, accidents and network disruption (Koetse & Rietveld, 2009). These have wider effects on communities and the economy. Climate change also alters the spatial allocation of activities and consequently leads to changes in derived demand for transport infrastructure (Table 8.1). Climate change is important to consider in transport planning because transport assets are long-lived and the transport system is intertwined with the wider economic and social systems. There are opportunities for adaptation in the normal cycle of infrastructure build and renewal. However, there are also many challenges due to the costs involved, the uncertainties ahead and the need to coordinate the different institutions that make up the transport system. Australia’s infrastructure will have to cope with high temperatures and reduced water availability. As a consequence of climate change, design thresholds for safe and efficient operation may be breached more frequently, or projects may function within tighter margins between “normal” operation and critical thresholds resulting in decreased efficiency of equipment and more frequent periods of restricted operation. This could lead to reduced asset lifetimes, higher running costs and capital expenditures, loss of income, and increased risk of environmental damage (European Commission, 2013a). Damages from climate hazard impact to critical infrastructures in Europe could increase tenfold by the end of the century (Forzieri et al., 2015).

8.10

Discussion

The development of sustainable measures to ensure climate resilience of transportation infrastructure is essential for urban development. This is another lacuna that justifies the current study by advocating for improved monitoring of transportation infrastructure through the life cycle. The term “infrastructure” when used in casual conversation tends to be perceived as hard physical systems—and public—as in roads, bridges, schools, and public offices. But this is a very narrow definition of what needs to be considered in the context of generating more resilient systems in cities. Because the different spheres of government operating in silos efforts to ensure climate resilience are still faced with limitations. This has led to the creation of transportation infrastructure that is not integrated and whose operations are disintegrated. It is evident from the findings that without integrated planning, ensuring climate resilience will be hard to attain. Through building on existing efforts, infrastructure investments will be utilized more effectively to enable comprehensive planning. These investments should address the two elements of transportation infrastructure namely:

Table 8.1 Examples of key vulnerabilities per transportation sector to the climate hazards. Energy

Transport

Economy

Social

Reduced power plant efficiency due to higher water temperature required for cooling Structural damage to distribution lines due to ice and snow loads Reduction in hydropower potential and biofuel production

Material degradation and buckling of roads, rails and bridges due to thermal expansion Buckling of roads, rails and bridges due to thermal contraction Reduced navigability of rivers and channels

Increased cost for cooling and refrigeration

Increased cost for cooling

Water pipes vulnerable to frost/icing

Wildfire

Reduction in biofuel sources

Flood

Structural damages to energy production sites and transport networks

Deterioration of roads, railways and power lines Reduction of the structural integrity of surface and subgrade material

Windstorm

Disruption of transmission and distribution networks

Structural damages to transport facilities

The increased cost of heating during cold episodes Structural damages due to drought-induced subsidence and permafrost thawing Destruction of social infrastructures Structural damage to social infrastructures and reduction in operational services Structural damages to social structures and facilities

Heat

Cold

Drought

Water quality degradation, reduction in usable water and increase in treatment costs Structural damages to industrial sites Structural damages to industrial sites, increasing cost for water treatment Structural damages to industrial systems equipment

Source: From Forzieri, G., Bianchi, A., Herrera, M. A. M., eSilva, F. B., Feyen, L., & Lavalle, C. (Eds.) (2015). The resilience of large investments and critical infrastructures in Europe to climate change. Publications Office.

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G

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Hard measures: for resilient systems in cities are physical interventions, such as the retrofitting of critical and defensive infrastructure, adapting buildings and urban spaces, managing the physical settlement relocation from at-risk areas, and adapting accounting for and promoting ecosystems services to a changing climate. Soft measures: to enhance cities’ resilience encompasses land use and urban planning, community awareness and preparedness, monitoring of hazards and risks, early warning systems, emergency and evacuation plans, and the political will to pursue hard and soft measures.

In the modern age of information technology, infrastructure is inherently a mix of hardware and software that includes the programming. In traditional transportation systems planning, the emphasis on the built roads, rails, and related hardware remains dominant. When people talk about “smart” transportation, however, the softer elements—programming of lighting, coordinating of schedules, on-demand systems—enter the redefinition. All these additions are, arguably, from the world of IT. The soft elements of the “smart city” and hard components of “urban resilient infrastructure” seem to be defined by different metrics, but the true climate-resilient city must combine both elements: “Resilience describes the ability of a system to withstand or accommodate stresses and shocks, such as climate impacts, while still maintaining its function. The resilience of a city depends on both the fragility of the urbansystem and the capacity of social agents to anticipate and to take action to adjust to changes and stresses” (World Bank, 2011). Recognizing this reality, resilience cannot be limited to “infrastructure” physical components, and there is a need to include the social, cultural and legal systems that link those hard elements to each other. Thus the broader conception includes roads, utilities, buildings, and transportation or communication networks, healthcare, education, emergency and support networks, the so-called “safety net,” and other welfare programs, not to mention the legal structures of markets for employment and exchange of goods and services. Neither element, it should be noted, is exclusively public or private; both types of ownership may—and, in most cases, do—coexist and coordinate. Infrastructure refers to the fundamental facilities and systems serving a country, city, or other areas, including the services and facilities necessary for its economy to function. With this broad definition, changes in those facilities and systems are required to promote the resilience. Climate-resilient infrastructure differs from traditional infrastructure as it is less affected by the different impacts that may be associated with climate change. On the one hand, it must be more capable of recovery from climate-related physical impacts associated with extreme weather and/or rising sea levels. In this context, it must be capable of recovery from unexpected short-term shocks, but also capable to respond and adapt to longer-term trends including major changes in precipitation and temperature patterns. Beyond this capacity for climate adaptation, however, it must also be resilient to both local and supra-local regulatory and other measures addressed to mitigating future climate change as the efforts may affect residents’ quality of life, local business continuity and regional economic and social growth potential. Mitigation-responsive infrastructure decisions involve those over the technological and sectoral bases that a local economy should depend (obviously arguing

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against public efforts to support local reliance on fossil fuel extraction, processing or use). But they also include both the choices of technologies used in infrastructure investments and those over regulatory practices and rules including building codes and land use controls. Climate mitigative infrastructure might also include what is often labeled as “nature-based solutions” for urban climatic challenges, for example, urban forests, constructed wetlands, and environmental education.

8.11

Conclusion and future direction

Given the limited availability of public sector funds, developing countries have been increasingly scaling up public contribution with private sector investment and expertise through public private partnerships (PPPs). PPPs have, in the last two decades, emerged as a mechanism to leverage greater private investment participation and most importantly to access specialized skills, innovations, and new technologies associated with infrastructure development, operation and maintenance. Present-day transport systems require highly specialized managerial and operational skills, and cutting-edge technologies, the expertise of private partners for building, operating and maintaining transport infrastructure and services is significant and constitutes an important resource to draw from, in addition, to finance. Over the 1990 2012 period, private sector participation in transport projects is estimated to have increased fivefold. While there is no one universal definition of PPPs, a widely accepted definition refers to PPP in infrastructure as a mechanism for the “creation and/or management of public infrastructure and/or services through private investment and management for a predefined period and with specific service level standards.” As such, PPPs can vary by shape and size, ranging from small service contracts to full-blown concessions, greenfield projects and divestitures.

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A worldwide survey of concrete service life in various climate zones

9

Sara Kalantari1, Rojina Ehsani1 and Fariborz M. Tehrani2 1 Department of Civil and Environmental Engineering, Amirkabir University of Technology, Tehran, Iran, 2Department of Civil and Geomatics Engineering, California State University, Fresno, CA, United States

9.1

Introduction

Natural disasters linked to climate change, such as floods, storms, drought, and wildfires, rise in frequency and severity. Globally, hydrological disasters have quadrupled in the last four decades, meteorological disasters have more than doubled, and geophysical events have risen from an average of 21 events a year to 31 events a year. Climate change continues to cause new challenges to the built infrastructure and environment that are already stressed by overconsumption and pollution (Thomas, 2017). Climate change has certainly had more impact on developing communities (Iskandar et al., 2022). The American Society of Civil Engineers (ASCE) seeks to lower the infrastructure life cycle costs by 50% by 2025. This goal involves two fundamental challenges lowering development footprints and increasing the service life of developed infrastructure. For addressing these challenges, ASCE has four different focuses resilience, life cycle cost analysis, performance-based standards, and innovation. These four pillars require civil engineering projects to focus on long-term environmental factors for infrastructure to withstand. Lifecycle assessment (LCA) is a recognized approach for assessing a project’s total cost and may extend to lifecycle analysis of other measures, such as energy, emissions, waste, and water, with a zero concept goal. This approach is vital to ensure that a project is the most sustainable and cost-effective alternative (Nelson & Tehrani, 2018). As practical solutions, performance-based specifications are vital in specifying how modern infrastructures should be built, operated, and maintained to achieve sustainability and resilience objectives (ASCE, 2011). Resilient structures contribute to the sustainability of infrastructure by optimizing resources and reducing the environmental footprints of disasters over the lifecycle of projects (PCA, 2019). Concrete is a common material for building and transportation infrastructures due to its resilience against fire, flood, storm, and other disasters. However, the environmental footprints of cement production are a sustainability concern for concrete products. These footprints have significant roots in the cement production, aggregate mining, water consumption, and waste management of concrete Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00015-9 © 2023 Elsevier Ltd. All rights reserved.

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materials. These roots justify global attempts to use natural cementitious materials, recycled aggregates, and reclaimed water in concrete production (Nazari et al., 2019, 2022). The application of lightweight aggregates has also been an attractive solution to reduce concrete footprints associated with transportation and construction activities and energy consumption during the operation of buildings (Tehrani, 2019, 2022). Furthermore, extending the service life and enhancing the durability of concrete are essential for the sustainable development of reinforced concrete infrastructure (Kosmatka & Wilson, 2011). The durability of concrete is attributed to the performance of concrete against weathering, chemical attacks, and similar processes leading to the failure of concrete (ACI Committee 201, 2016; INBR, 2020). Exposure of concrete to corrosive and chemical agents and freeze-and-thaw conditions are responsible for the deterioration of concrete materials in various climate zones. Low water-to-cementitious material ratio, application of supplementary cementitious materials, protection of steel reinforcement, and adequate curing are vital for improving the durability of concrete. For instance, internal curing is an established method to mitigate shrinkage cracking and enhance the durability of concrete, as permeability and diffusion are the main factors affecting durability through controlling the transport of chloride ions (Bonyadian et al., 2019; Kosmatka & Wilson, 2011; Tehrani, 2020). Prediction of service life using transport properties facilitates LCA of infrastructure, including pavements, bridge decks, parking structures, and marine infrastructure (Davodijam et al., 2022; Kalantari & Tehrani, 2021; Kalantari et al., 2021; Tehrani, 2019, 2021). These LCAs involve objective evaluation of performance measures, such as cost, energy, and greenhouse gas emissions (Nazari et al., 2019, 2022; Tehrani et al., 2014, 2018, 2019; Tehrani & Dadkhah, 2018). Furthermore, these quantitative parameters form the environmental product declarations based on LCAs of the targeted applications (ESCSI, 2022).

9.2

Backgrounds

The deterioration of concrete is the key parameter responsible for the long-term performance of concrete and premature failure of reinforced concrete structures before reaching the design capacity due to structural demands. The interaction between environmental degradation and structural demands of concrete infrastructure often manifests itself in the early deterioration of exposed systems, such as pavements, bridges, parking structures, and marine systems. The increased demands may stem from the growth of populations, expansion of economic opportunities, environmental disasters, climate change, or other planned and unplanned events. While sustainable measures intend to reduce the environmental footprints and preserve natural resources, resilient measures endeavor to sustain the performance and serviceability of infrastructure subjected to natural and manufactured disasters. Hence, the deterioration of concrete is the critical element controlling the service life of the concrete and therefore the sustainability and resilience of concrete infrastructure experiencing the effects of climate change (Tehran & Nelson, 2022).

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Standard solutions to extend the service life of concrete may involve measures at structural and material levels. Structural design optimization aims to increase concrete elements’ capacity, robustness, redundancy, rapid recoverability, and resourcefulness, leading to a resilient design. Material specifications endeavor to eliminate or reduce environmental factors responsible for concrete deterioration leading to a context-sensitive sustainable design. The latter includes preventive measures during manufacturing, production, and construction phases to placing concrete materials fit for the purpose and corrective measures during operation, maintenance, strengthening, and retrofit to preserve materials through the lifecycle of infrastructure (Nelson & Tehrani, 2018). Extending these solutions to concrete with a service life of 100 years or more demands consideration of climate change consequences on structural and material characteristics (Stewart et al., 2011). These consequences may include variations in humidity, temperature, carbonation, chloride concentration, and other physical and chemical parameters affecting concrete or reinforcing steel (BastidasArteaga et al., 2010; Farah et al., 2014). The corrosion of reinforcing steel is a widespread cause of deterioration in most concrete elements, with an estimated $2.5 trillion damage cost worldwide (Koch et al., 2016). The root cause of steel corrosion is the penetration of chloride ions in corrosive environments and their transport through the body of the concrete due to capillary forces (Bastidas-Arteaga, 2018; Castro et al., 2001). Various parameters, such as shrinkage, creep, thermal deformations, fatigue, and other structural stresses and strains, aggravate chloride penetration through crack initiation and propagation at different concrete ages. Freeze-and-thaw cycles combined with corrosive de-icing agents exacerbate the chloride present in large volumes of placed concrete on horizontal infrastructures, such as roads and bridges. The loss of strength and rigidity due to corrosion typically leads to additional cracking and intensified accumulation of chloride ions in the reinforcement steel resulting in a progressive degradation of the reinforced concrete element (Bastidas-Arteaga et al., 2010, 2018). The interaction between environmental conditions and structural demands scales up due to climate change’s effects on humidity, temperature, and chloride concentrations. It serves as an example of demonstrating the need to survey the performance of concrete infrastructure in various climate zones. The Ko¨ppen classification system offers different environmental characteristics of climate zones globally. For instance, exposed concrete in a tropical climate may show vulnerability to heavy rainfall and direct sunlight, particularly in marine environments that experience additional chloride and dryingwetting cycles (Castro et al., 2001; Farah et al., 2014; Touil et al., 2022). These effects are different for concrete exposed to seawater or low-humidity air. In arid areas, hot climates and wind effects interact to damage the concrete surface, increase the permeability, and reduce the resistance of concrete to transport of corrosive agents. These agents may include combinations of airborne chloride, sulfate in soil, or carbon dioxide in urban areas, even in moderate Mediterranean climates (Mustafa & Yusof, 1991). Design specifications aim to recognize the probability and the severity of concrete degradation and mitigate their impact on the capacity and serviceability of reinforced concrete elements. Identification of durability concerns utilizes climate

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and site data to classify concrete exposure to sulfate and chloride attacks, carbonation, and freeze-and-thaw cycles. Hence, environmental exposure defines the interacting chemical and physical conditions that influence the expected mechanical behavior of concrete, steel, and their bond. Mitigating these interactions endeavors to set minimum concrete cover, maximum water-to-cementitious materials ratio, and other best design practices for the target application, such as reinforcing details for prestressing concrete. In addition, construction specifications control placement, finishing, and curing tasks to maximize the resistance of concrete surfaces to penetration of deteriorating agents (ACI Committee 201, 2016; ACI Committee 318, 2019; EHE,2008; EN 19921-1, 2005; JSCE, 2007). However, like the increased concrete cover to protect reinforcement, each solution has other environmental footprints, including input energy, greenhouse gas emissions, waste, and water consumption associated with their production and implementation. The net values of these footprints indicate the sustainability of the solution, which is a function of the concrete service life (Kalantari et al., 2021).

9.3

Climate

The sensitivity of concrete durability to climate characteristics and environmental exposures is evaluated using the predicted service life of selected concrete applications in various climate zones. Table 9.1 lists 30 different cities selected from the global climate zoning map shown in Fig. 9.1 (Kottek et al., 2006). Selected cities typically represent the most populated cities in each subgroup to capture the highest impact of climate Table 9 1 Selected locations in each subgroup of four major climate zone groups. Group

Subgroup: climate

City

A: Tropical climates

Af: Tropical rainforest

Singapore, Singapore Jakarta, Indonesia Kinshasa, Congo Fortaleza, Brazil Karachi, Pakistan Damascus, Syria Lahore, Pakistan Shijiazhuang, China

Am: Tropical monsoon

B: Dry climates

Aw: Tropical savanna with dry-winter characteristics As: Tropical savanna with dry-summer characteristics BWh: Hot desert BWk: Cold desert BSh: Hot semiarid BSk: Cold semiarid

(Continued)

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Table 9 1 (Continued) Group

Subgroup: climate

City

C: Temperate climates

Cfa: Humid subtropical

Shanghai, China London, UK Reykjavı´k, Iceland Chengdu, China Mexico City, Mexico El Alto, Bolivia Izmir, Turkey Cape Town, S Africa Balmaceda, Chile Chicago, USA

Cfb: Temperate oceanic Cfc: Subpolar oceanic Cwa: Monsoon-influenced humid subtropical Cwb: Subtropical highland or monsooninfluenced temperate oceanic Cwc: Cold subtropical highland or Monsooninfluenced subpolar oceanic Csa: Hot-summer Mediterranean Csb: Warm-summer Mediterranean Csc: Cold-summer Mediterranean D: Continental climates

Dfa: Hot-summer humid continental Dfb: Warm-summer humid continental Dfc: Subarctic Dfd: Extremely cold subarctic Dwa: Monsoon-influenced hot-summer humid continental Dwb: Monsoon-influenced warm-summer humid continental Dwc: Monsoon-influenced subarctic Dwd: Monsoon-influenced extremely cold subarctic Dsa: Mediterranean-influenced hot-summer humid continental Dsb: Mediterranean-influenced warm-summer humid continental Dsc: Mediterranean-influenced subarctic Dsd: Mediterranean-influenced extremely cold subarctic

Moscow, Russia Arkhangelsk, Russia Yakutsk, Russia Beijing, China Heihe, China Yushu City, China Oymyakon, Russia Bishkek, Kyrgyzstan Sivas, Turkey Yellowknife, Canada UstSrednekan, Russia

change on infrastructure development. Hence, no cities represent Group E in polar and alpine climates, where inhabitants are insignificant. Figs. 9.29.5 present the average monthly temperatures for each location (NOAA, 2022).

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Figure 9.1 Ko¨ppen climate classification (Beck et al., 2018). Source: From Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A., & Wood, E. F. (2018). Present and future Ko¨ppen-Geiger climate classification maps at 1-km resolution. Nature Scientific Data, 5, 180214. https://doi.org/10.1038/sdata.2018.214.

Figure 9.2 The average monthly temperature of cities in Group A.

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Figure 9.3 The average monthly temperature of cities in Group B.

Figure 9.4 The average monthly temperature of cities in Group C.

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Figure 9.5 The average monthly temperature of cities in Group D.

9.4

Service life prediction

A common approach to predicting the concrete service life is measuring the total time needed for the surface concentration build-up and transport of chloride ions from the concrete surface to the reinforcing steel bars and the time for steel corrosion to occur. This chapter benefits from the Life-365 program, which models the diffusion of chloride using the Fick’s second law (Ehlen et al., 2009; Ehlen and Kojundic, 2014; Life-365, 2020): dC d2 C 5D 2 dt dx

(9.1)

where C is the chloride content, D is the diffusion coefficient, x is the depth of the chloride intrusion with the maximum value equal to the depth of reinforcing steel or concrete cover, and t is time. Diffusion coefficient varies with time and temperature, benchmarked at the 28-day and 293K referenced time and temperature, respectively (Davodijam et al., 2022): DðT Þ 5 Dref

t m ref

t

   U 1 1 exp 2 R Tref T

(9.3)

where U is the activation energy of the diffusion process (35 kJ/mol) and R is the gas constant (8.3145 J/mol/K).

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The corrosion time for steel bars depends on surface properties and protection, with an assumed value of 6 years for conventional steel materials. However, the initial chloride concentration and the build-up rates are functions of the target application and the surrounding environment, thus considering the climate zone. Climate change also impacts long-term predictions. Table 9.2 lists the chloride build-up rates for parking structures following recommendations in Life-365, 2020. The frequency of freeze-and-thaw cycles is the primary parameter influencing the intensity of chloride build-up rate in each zone; thus, the lowest suggested rate applies to arid and hot regions. This rate drops to 85% of tabulated values for urban bridges considering the higher frequency of exposure to de-icing agents. The suggested value for marine structures located at a 1.5 km distance from the ocean is 0.02% (Kalantari et al., 2021; Kalantari & Tehrani, 2021). Three nonprestressed cast-in-place reinforced concrete applications of the parking garage, urban bridge deck, and marine walls at a 1.5-km distance from the ocean were included in this study with a specified compressive strength of 35 MPa. Each application has been designed using standard practices, as summarized in Table 9.3. Concrete in marine environments tends to have more cover, thickness, and reinforcement to withstand corrosive agents. In contrast, parking garages with smaller spans need less thickness and reinforcement. Urban bridges have larger Table 9.2 Chloride build-up rate in various climate zones. Climate zone

Chloride build-up rate (% per year)a

Very cold Cold Moderate Semimoderate Semiarid to very hot

0.10 0.08 0.03 0.02 0.01

a

Values shown for parking structures; values for urban bridges are 85% of tabulated values; the value for the marine environment at 1.5 km distance from the ocean is 0.02%.

Table 9 3 Input data for the service life prediction. Exposure

Thickness (mm)

Concrete cover (mm)

Reinforcing ratio (%)

w/cm

Maximum chloride concentration (%)

Parking garage Urban bridge Marine

200

25a

0.6

0.45b

0.8c

225

50

1.2

0.45b

0.68d

250

75

1.3

0.4

0.6

a

37.5 mm for corrosive environments. 0.4 for corrosive environments. 1.0% for frigid climate. d 0.85% for the frigid climate. b c

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spans and more exposure to harmful agents than parking garages and, therefore, are designed for thicker slabs and concrete cover. The concrete cover for parking garages in cold regions is slightly higher than usual due to the higher frequency of application of de-icing agents. The same applies to cities next to water bodies with a higher chloride concentration (Davodijam et al., 2022). Service life prediction was performed by Life-365 using the information provided in Figs. 9.29.5 and Table 9.3, following Fick’s second law (Life-365, 2020). Cost analysis included construction and repair activities with breakdowns for materials, labor, and equipment (MPORG, 2019, 2021). Construction cost involves the cost of concrete and rebar with similar unit costs for all applications and locations adjusted for the thickness and reinforcement ratio. The repair cost includes the replacement of damaged areas as scheduled. Fig. 9.6 illustrates the relative unit area costs of construction and repair for each application, indicating a significantly higher repair cost for parking garages. Regardless, total repair costs require further adjustments per frequency and intensity rates of damages (Vosoughi et al., 2017). The frequency of these activities was determined based on the service life for each application and location. Estimating energy and emissions also followed the breakdown for materials and equipment. Input energy and emissions were determined using environmental product declarations by NRMCA (2020), assuming ordinary Portland cement. Further, energy sequestered in machines’ fuel consumption and associated emissions were augmented to calculate total values (Nazari et al., 2019, 2022; Tehrani et al., 2014, 2018, 2019; Tehrani & Dadkhah, 2018). Lifecycle costs have followed an assumption of a 150-year study period and 10-year intervals between repair projects. Repair projects involve the replacement of 10% of the area following suggested practices (ACCO, 2004; Vosoughi et al., 2017).

9.5

Results

Fig. 9.7 provides predicted service life values for different climate zones and applications as calculated by Life-365, 2020. Moreover, urban bridges have shown to be more

Figure 9.6 Relative unit area construction and repair costs for parking garages (left), urban bridges (middle), and marine environments (right) applications.

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Figure 9.7 Predicted service life for three applications in various climate zones.

durable applications than parking structures in all locations due to higher concrete cover and lower build-up rates. Despite the higher build-up date, applicable cases for marine environments show higher service life due to additional concrete cover and lower water-to-cementitious materials ratio. Humidity also enhances the predicted service life of the marine environment when comparing climates in groups Csa, Dfa, and Dwb. Comparing cities in dry climates (BWh) versus humid climates (Dfa) reveals that the humidity increases the service life. The effect of higher temperature on decreasing the service life is also apparent for cases of Cs and Dw zones. These observations align well with expectations based on input data for the service life prediction model. Figs 9.89.10 show the ratio of predicted service life for each location to an assumed referenced value (Af) for parking garages, urban bridges, and marine environments, respectively. These trends confirm that cases with less service life have been associated with higher cost, energy, and emissions. Comparing different measures indicate that emissions are slightly more influenced by the change in the service life than energy or cost. Furthermore, the comparison of trends for different applications reveals that the effect of climate zone is more evident in marine environments followed by urban bridges than parking garages. Fig. 9.11 shows a similar chart normalizing all values to those of parking garage applications. This figure confirms relatively more significant changes for cities in colder climate zones than those in warmer climate zones, say Cs and Dw zones, except for cases in the marine environment, where the level of chloride concentration is more influential than other climate characteristics. The higher costs associated with urban bridges and marine environments compared to parking garages are apparent in this figure. Nevertheless, the sensitivity of emissions and energy to the change in application is considerably higher than the cost index for all locations.

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Figure 9.8 Normalized predicted service life to referenced values for parking garages in various climate zones.

Figure 9.9 Normalized predicted service life to referenced values for urban bridges in various climate zones.

Fig. 9.12 indicates various logarithmic trades for cost, energy, and emissions vs the predicted service life. All calculated coefficients of determination (R-squared values) are above 0.977, indicating the fitness of logarithmic models. Fitted power

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Figure 9.10 Normalized predicted service life to referenced values for the marine environment in various climate zones.

Figure 9.11 Normalized predicted service life to parking structure values for each location in various applications.

functions show that reductions in energy and emissions follow nearly the same trends with logarithmic coefficients of 0.83 and 0.838, respectively. However, the cost does not have a strong relationship with the service life. Instead, the lifecycle cost trend is different for each application. This observation can be correlated to the

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Figure 9.12 Variations of cost, energy, and emissions with service life.

Figure 9.13 Variations of energy and emissions with the cost for each application.

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fact that various prototypes had already been designed based on climate characteristics, that is, more concrete and rebars had been specified in less favorable conditions subjected to freezing or exposure to corrosive agents. Hence, it can be concluded that service life extension has been achieved with additional expenditure, to the point that the overall cost has minor change due to such extension. Nevertheless, the logarithmic coefficients of cost index trends for parking garages, urban bridges, and marine environments are 0.816, 0.79, and 0.759, respectively, all close enough to energy and emissions. Fig. 9.13 clarifies the direct relationship between cost, energy, and emissions as primary performance measures for sustainable development. Separating applications into three clusters allow a valid comparison between changes in energy and emissions as a function of cost for nearly identical prototypes. In this respect, the linear relationship for each cluster is evident, with minor deviations having roots in very cold or corrosive climate cases. The higher slope for parking garages represents a higher increase in energy and emissions than the cost index.

9.6

Conclusions

Service life, cost, energy, and emissions have been assessed for reinforced concrete applications in parking garages, urban bridges, and marine environments in 29 locations with different climate zones. Climate zones included a range of ambient temperatures from very cold to very hot and dry and humid moisture conditions. Each application was designed to withstand environmental exposures as required by the code and hence had different thickness, cover, and reinforcement. Service life prediction indicated the interaction between climate characteristics and chloride exposures specific for each application in determining the overall service life of the concrete. Results indicate that satisfying design procedures directly affect the cost, and therefore, the annualized cost does not show a high-fidelity correlation with the service life. However, trends of energy savings and emissions reductions showed reliable dependency on the extension of service life. The input energy sequestered in construction and repair activities and associated emissions were a linear function of costs.

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Tehrani, F. M. (2021). Service life prediction of internally cured concrete pavements using transport properties. Proceedings of the ASCE international airfield and highway pavements conference. Austin, TX: Transportation & Development Institute of ASCE, June 810, 2021. Tehrani, F.M. (2022). Studies on the deployment of sustainable practices using lightweight aggregates for bridge infrastructures. In Proceedings of the ASCE lifelines conference (p. 97), Los Angeles, February 711, 2022. Los Angeles, CA: University of California. Available from https://doi.org/10.34948/N3QP4X. Tehrani, F. M., Alexandrou, A., Machoney, M., Adhikari, D., & Raymond, M. (2014). Energy inputs and carbon dioxide emissions from construction equipment during construction of a golf course. International Journal of Engineering Research and Innovation, 6(2), 7886. Available from http://www.ijeri.org/issues/fall2014/Z__IJERI %20fall%202014%20v6%20n2%20(PDW-4).pdf#page 5 80. Tehrani, F. M., & Nelson, D. (2022). From sustainability to resilience: A practical guide to envision. In M. Ettouney (Ed.), Objective resilience, Book2: Objective processes. Reston, VA: ASCE Press. Available from https://doi.org/10.1061/9780784415894.ch3. Tehrani, F. M., & Dadkhah, M. (2018). A case study on the analysis of energy and emissions for sustainability rating. International Journal of Climate Change: Impacts and Responses, 10 (3), 1323. Available from https://doi.org/10.18848/1835-7156/CGP/v10i03/13-23. Tehrani, F.M., Farshidpour, F., Pouramini, M., Mousavi, M., & Esfahani, A.N. (2018). Sustainability rating of lightweight expanded clay aggregates using energy inputs and carbon dioxide emissions in lifecycle analysis. In: Proceedings of the sixth international symposium on life-cycle civil engineering, IALCCE (pp. 29892993), Ghent, Belgium, October 2018. Tehrani, F.M., Nazari, M., Truong, D., & Farshidpour, R. (2019). Sustainability of tirederived aggregate concrete: A case study on energy, emissions, economy, and ENVISION. In: Proceedings of the international conference on sustainable infrastructure 2019 (pp. 399408), Los Angeles, CA: ASCE, November 69, 2019. https://doi. org/10.1061/9780784482650.043. Thomas, V. (2017). Climate Change and Natural Disasters: Transforming Economies and Policies for a Sustainable Future. London, UK: Routledge. Touil, B., Ghomari, F., Khelidj, A., Bonnet, S., & Amiri, O. (2022). Durability assessment of the oldest concrete structure in the Mediterranean coastline: The Ghazaouet harbour. Marine Structures, 81103121. Available from https://doi.org/10.1016/j.marstruc.2021.103121. Vosoughi, P., Tritsch, S., Ceylan, H., & Taylor, P. (2017). Lifecycle cost analysis of internally cured jointed plain concrete pavement. Part of IHRB project TR-676. Ames, IA: Iowa Highway Research Board.

Effect of global warming on chloride resistance of concrete: a case study of Guangzhou, China

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Mingyang Hong1, Xinyu Zhao2, Jinxin Chen2 and Tianyu Xie3 1 Civil and Transportation School, South China University of Technology, Guangzhou, P.R. China, 2State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, P.R. China, 3School of Civil Engineering, Southeast University, Nanjing, P.R. China

10.1

Introduction

Reinforced concrete (RC) structures are subjected to environmental actions affecting their performance, serviceability, and safety. In particular, electrochemical reactions between steel bars and their surrounding environment can result in corrosion of an RC member, which possibly engenders worse structural performance (ALAmeeri et al., 2021). But concrete corrosion is not a soon process—it includes corrosion initiation, concrete cracking, structural delamination, and final failure (Li et al., 2007). In general terms, corrosion of bars caused by chloride ion attack is one of the leading causes of premature failure of concrete (Broomfield, 1997). Therefore the development of chloride ion diffusion models has become the focus of research regarding the chloride intrusion issues of RC elements. It is necessary in developing such models to consider a variety of factors. Many studies have been carried out to look into the mechanisms of chloride-induced corrosion of steel in concrete (Glass & Buenfeld, 2000; Liu & Weyers, 1998). Since the main factor affecting chloride attack is free and water-soluble chloride ions in concrete, and the main factor resisting chloride attack is the individual physicochemical properties of an RC member, it can be considered from both perspectives (Haque & Kayyali, 1995). The common factors include the concentration of chloride ion, cement density, water-to-cement ratio, temperature as well as relative humidity (Angst, 2019; Han, 2007; Tang, 1999). Among them, the chlorine ion diffusion coefficient is a dominant one incorporated in many models with various degrees of complexity. On the other hand, climate change arguably represents one of the greatest global threats of our time. It is having major short-run effects with possible serious longrun implications for natural and human systems on all continents and across all oceans, requiring us to adapt to a new reality (Hoegh-Guldberg et al., 2019; Nordhaus, 1991). Seriously, current academic research holds that climate change will even provoke subsistence crises and, occasionally, civilizational collapses Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00013-5 © 2023 Elsevier Ltd. All rights reserved.

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among human societies. For example, rising global temperatures are one of the most visible outcomes of climate change, causing polar ice caps to melt and sea levels to rise. As a result of this phenomenon, ocean water levels have continuously increased and most coastal areas overlooking open seas have suffered from erosive damage and flooding (Vousdoukas et al., 2018). At the same time, these climate and environmental changes are affecting engineering facilities enormously, too (Stewart & Deng, 2015). For this reason, extensive studies have been carried out on the greenhouse effect and its direct and indirect consequences (Berrang-Ford et al., 2011; Gernaat et al., 2021; Mora et al., 2018). Also, there are several projects underway to study the mitigation of the adverse effects of the greenhouse effect, for example through crop residue management, rehabilitation of degraded soils and conservation tillage to enrich CO2 in order to improve soil resilience and quality as well as to minimize the risk of soil degradation (Gernaat et al., 2021; Nandan et al., 2019). In addition to the above research, the prediction of future climate is also of strong interest. In fact, such analyses and future projections are essential for enabling policymakers and stakeholders to achieve climate resilience and sustainable development goals by harnessing the power of meaningful and trustworthy forecasts and insights. With the development of computer technologies, machine learning models have been applied in numerous aspects. Future climate prediction, as a branch of machine learning model applications, has become a hot research topic (Bochenek & Ustrnul, 2022; Huntingford et al., 2019). By choosing the most appropriate machine learning model and its parameters, a high level of accuracy can be achieved in predicting future climate. For example, Chen and Hwang (2000) used the two-factor time-variant fuzzy time series model for temperature prediction and obtained good results. Pal et al. (2007) developed RegCM3 model to simulate the climate of three developing country regions. Ise and Oba (2019) used 30 years of monthly temperature data to predict the rise and fall in temperature over the next 10 years using a neural network model with an accuracy of 97%. These predictions of future climate can allow people to better face the global and regional environmental changes brought about by the greenhouse effect. And as a matter of fact, climate change could also interfere with the degradation of RC structures over time. For example, it is found that increasing atmospheric CO2 emissions will significantly affect the carbonation progress and depth in concrete (Chen et al., 2021). Also, a shortened service life of RC components is inevitable if chloride ion penetration speeds up resulted from greenhouse effects. Using a finite-element model, Shafei et al. (2012) predicted the onset of corrosion of RC structures in an exposed environment and pinpointed that the onset of corrosion was 13.9, 23.2, and 34.8 years for different protective layer thicknesses of 40, 50, and 60 mm, respectively, when considering over a span of 50 years. BastidasArteaga et al. (2020) argued that climate change could accelerate corrosion initiation from 3% to 13%. According to another study (Gao & Wang, 2017), the increased chloride diffusivity rate induced by global warming and sea-level rise could reduce the service lifetime by about 5%. This is understandable because existing experimental evidence has shown that the chloride ingress is highly influenced by weather conditions (Bastidas-Arteaga & Stewart, 2015).

Effect of global warming on chloride resistance of concrete: a case study of Guangzhou, China

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The above initial indications warn us of the possible influence of climate change on the process of concrete deterioration. To more vividly reveal the dire consequences, this study took Guangzhou—a typical coastal metropolis in China—as an example, thereby demonstrating the effects of city-scale heat and moisture variations on concrete’s chloride diffusivity and, hence, its previewed service life. As both temperature and relative humidity are important factors affecting chloride ion erosion, it is urgent and necessary to look at how global climate change affects the durability of RC structures (Adam, 1995; Medeiros-Junior et al., 2015). From both real and simulated data, this chapter contributes to examining the extent to which the service life performance of marine RC structures is influenced over different time periods. The following sections begin with identifying the location of the actual measurement station and understanding their approximate orientation. The collected mean temperature and dew point temperature data from 1980 to 2021 were then fitted to the mean temperature and dew point temperature data from 2022 to 2100 by means of a cubic exponential smoothing model for time series prediction analysis. At the same time, the actual collected and predicted relative humidity data were calculated using the actual collected and predicted mean and dew point temperature data. Subsequently, some typical chloride ion diffusion models with temperature and relative humidity as key factors were used to estimate the effect of chloride ion erosion on the durability of RC structures at different periods of temperature and relative humidity. The changes in structural durability under the greenhouse effect were predicted after comparative analysis.

10.2

Temperatures and relative humidity: past and future

The data for this study were obtained from measurements taken at a meteorological station in Guangzhou from 1980 to 2021. Fig. 10.1 shows the location of the city in China. The weather station is at 113.298786 E, 23.392436 N. It is located in a subtropical coastal region which belongs to an oceanic subtropical monsoon climate with high relative humidity, characterized by warmth and rain, abundant light and heat, long summers, and short frost periods. Temperature can accelerate the penetration of chlorides into concrete. We adopted the annual average temperature as reference data. The projection of the temperature change in the future period 20212100 was made based on the historical temperature data in the past period 19802021. In such a forecast, the cubic exponential smoothing model for time series prediction analysis was followed (Hou & Yang, 2014). Exponential smoothing of time series is an improved version of the moving average method, which is realized by taking the time series item by item and calculating a time series average containing a certain number of items in turn. Exponential smoothing of time series can be seen as a moving average method with a wireless memory and exponentially decreasing weights.

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Figure 10.1 The location of Guangzhou in China.

Exponential smoothing of time series can be divided into primary exponential smoothing, secondary exponential smoothing and tertiary exponential smoothing. Primary exponential smoothing is used for series with no trend or seasonality. Secondary exponential smoothing is used for series with a trend but without seasonality. It takes into account the baseline of the data and includes the trend as an additional consideration, retaining the details of the trend. The triple exponential smoothing method is used for series with both trend and seasonality and adds a seasonal component to the quadratic exponential smoothing method. Similar to the trend component, exponential smoothing is done for the seasonal component. Triple exponential smoothing is also known as Holt-Winters. It consists of a forecasting equation and three smoothing equations (Kalekar, 2004). The three smoothing equations are the baseline smoothing equation si , the trend smoothing equation ti , and the seasonal smoothing equation pi , with the corresponding smoothing parameters α, β, and γ. The specific formulas are as follows: si 5 αðxi 2 pi2k Þ 1 ð1 2 αÞðsi21 1 ti21 Þ

(10.1)

ti 5 β ðsi 2 si21 Þ 1 ð1 2 β Þti21

(10.2)

pi 5 γ ðxi 2 si Þ 1 ð1 2 γ Þpi2k

(10.3)

Effect of global warming on chloride resistance of concrete: a case study of Guangzhou, China

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The final prediction formula reads: xi1h 5 si 1 hti 1 pi2k1h

(10.4)

where si is the smoothed value of the baseline component at the ith time point; ti is the smoothed value of the trend component at the ith time point; pi is the smoothed value of the seasonal component at the ith time point; xi is the actual data at the ith time point; α, β, and γ are the smoothing parameters, which can be any value between 0 and 1; and k is the length of the period. By using the cubic smoothing model for time series predictive analysis, the future average and dew point temperature data we predict can be better fitted to the trend of the data, and periodically fit the oscillations of the deviation of the data relative to the trend line over a period of time cycle. Relative humidity (RH) is another vital factor affecting chloride diffusion. It was calculated according to the model by Castellvı´ et al. (1996). es ðTd Þ  RHð%Þ 5 100  es Tavg

(10.5)

where es ðTd Þ is the saturated vapor pressure (hpa) of the dew point temperature and  es Tavg is the saturated vapor pressure  (hpa) of the annual average temperature. For obtaining the value of es Tavg , the GoffGratch saturation water vapor pressure formula was adopted: lgew 5 10:79586ð1 2T0 =TÞ 2 5:02808lgðT=T  0Þ 0 21Þ 1 1 1:50475 3 10h24 1 2 1028:2969ðT=T i 23 4:76955ð12T0 =T Þ 0:42873 3 10 10 1 0:78614

(10.6)

where ew is the saturated vapor pressure at the water surface (hpa) and T0 is the temperature at the three-phase point of the water, which is equal to 273.16 K; T 5 273.15 1 t, where t is the temperature and the applicable range of temperature is 49.9 C49.9 C. In calculating the RH for the period 19802021, the actual data were directly imported into the formula. While for the period 20212100, the previous cubic exponential smoothing model was used to predict the mean and dew point temperatures, and the predicted values were then substituted into the formula to get the future RH values. Having obtained the temperature and relative humidity data, we need to consider the difference between the temperature and relative humidity in the external environment and the actual internal environment of the structure. As the concrete thickness assumed here is the thickness of the protective layer of concrete, which is thin in relation to the concrete structure as a whole, it has less influence on the temperature and relative humidity. Therefore in this study, it is assumed that the temperature and relative humidity in the internal environment of the RC structure are the same as in the external environment.

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10.3

Chloride diffusion models

Although numerous chloride diffusion models have been proposed, not all of them include the temperature or the RH variables, and their prediction accuracy varies from one to another. For example, Meijers et al. (2005) considered fluctuations in ambient temperature and humidity, chloride binding, diffusion and convection, and carbonation effects and then derived the relationships between a series of factors including the moisture content at saturation and the chloride conductivity. After a thorough review, the chloride diffusion models proposed by Saetta et al. (1993). Bob (1996) and Amey et al. (1998) were selected for the application of this study. Saetta et al. (1993) used the finite-element method to analyze the process of chloride penetration into concrete, and the model can be summarized as: Dc 5 Dc;rif  f1 ðT Þ  f2 ðte Þ  f3 ðRH Þ

(10.7)

where Dc is the modified diffusion coefficient (m2 =s); Dc;rif is the diffusion coefficient (m2 =s) corresponding to 28 days of maintenance under standard conditions (T0 5 23 C, RH 5 100%); and f1 , f2 , and f3 are the correction functions corresponding to temperature, equivalent maturation time, and relative humidity, respectively. Based on the long-term experimental data, Bob (1996) derived an empirical simplified model as follows: xc 5 150

  ck1 k2 d pffiffiffiffiffi tic fc

(10.8)

where xc is the thickness of concrete cover (mm); c presents the cement’s ability to fix chlorides; k1 and k2 are the parameters that are influenced by temperature and relative humidity, respectively; d presents the ratio between the critical concentration and the surface concentration of chlorides; fc is the compressive strength of concrete (N/mm2 ); and tic is the time (years) when chloride ions start to attack the reinforcing steel. Amey et al. (1998) applied the Nernst-Einstein method to obtain a chloride diffusion model:  

  T 1 1 2 Dc 5 Dc;rifU Uexp q T0 T0 T

(10.9)

where Dc;rif is the diffusion coefficient (m2/s) corresponding to 28 days of maintenance under standard conditions (T0 5 23 C, RH 5 100%); T0 is the standard temperature T0 5 296K; T is the actual temperature, which is expressed in  K; and q is a constant obtained from experimental fitting. Finally, we need to get the time of chlorine corrosion. The model by Bob (1996) can get the value of tic directly, while the models of Saetta et al. (1993) and Amey

Effect of global warming on chloride resistance of concrete: a case study of Guangzhou, China

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et al. (1998) can only get the value of Dc . Thus Eq. (10.10) is used to bridge Dc and tic . tic 5

x2c 2Dc

(10.10)

In the calculation process, we need to assume a particular curing time and concrete water-to-cement ratio data and then calculate the equation by means of the values of the parameters corresponding to this data. Thus the concrete durability variation data we obtain by calculation corresponds to an RC structure for a specific curing time and water-to-cement ratio. The data can be adjusted for further calculations if other curing times and water-to-cement ratios corresponding to the durability change of the concrete structure are required, and only one combination of curing time and water-to-cement ratio is calculated here as an example. At the same time, in addition to the influence of curing time and concrete waterto-cement ratio on the time to obtain the reduced service life of RC structures due to chloride ion attack, there are also different factors, such as the nature of the material, the surrounding environment and regional codes that can have an impact on the results. It is important to note that because some of the parameters, such as Dc;rif , are influenced by these different factors, these parameters cannot be generalized. Therefore we consider the ratio of tic for comparative analysis. The calculations were carried out with the same combination of maintenance time and waterto-cement ratio corresponding to each period and each model. According to the Chinese national standard GB 50068-2001 (GB 500682018, 2018), the design reference period adopted for building structures, structural elements and foundations in China is 50 years. For the statistical parameters of loads and time-dependent material properties used in the design of structures, 50 years is generally selected as the time parameter. Therefore in the current analysis, 50 years was chosen as the benchmark to calculate the weakening time of the durability of RC structures induced by chloride ion attack.

10.4

Results and discussion

The data series of the historical annual average temperatures (19802021) and the simulated future data (19802100) using the cubic exponential smoothing model are shown in Fig. 10.2. The projections show an average temperature increase of 2.35 C in 2100 relative to 2000, which is in line with the range of temperature rise, that is, 1.8 C3.5 C for the global surface warming forecast by the IPCC report (IPCC. Climate Change, 2007). The curve presents an overall oscillating upward trend, where the oscillation period is around 12 years. The deviation from the trend line during the rise is relatively small, and the temperature data can be considered by using the average of the temperatures over a period of time. If the actual data at a particular time is used for the calculation, it may happen that the calculated data

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future

Figure 10.2 The variations of the annual average temperatures from 1980 to 2100.

future

Figure 10.3 The variations of the annual RH values from 1980 to 2100.

differs significantly from the overall situation over time, so it is better to use the average value rather than the actual data at a particular time. The changes in the RH obtained from the predictions are shown in Fig. 10.3, which initially presents an overall downward trend, but then gradually increases and flattens. The graph shows that the relative humidity variation has become more oscillating since 2000, but the overall trend is still relatively flat. There is no clear cyclical variation in relative humidity and it tends to oscillate within a certain range. To give a more visual representation of the changes in temperature and relative humidity between past and future time periods, we have summarized and compared the analysis results with the following graph: Fig. 10.4 characterizes the environmental data (temperature and RH) of the past and future due to global warming. These results were substituted into the aforementioned three chloride ingress models, assuming a conservation to concrete maturity time of 28 days and a water-to-cement ratio of 0.5. This represents the combination of curing time and water-to-cement ratio selected for this study. For different combinations of curing time and water-to-cement ratio, the results of substituting the data into the three models will vary and the variation will affect the ratio of the weakening time of the concrete service life in future time periods to that in past time periods. The temperature-related changes in the data are more sensitive when this combination is varied. The average values of the temperature and RH for the period 19802021 were used for the past time period, and the predicted values of

Effect of global warming on chloride resistance of concrete: a case study of Guangzhou, China

Past (1 980 -2021 )

T=22 .8ć

R H=7 0.5%

209

Futu re ( 2100 )

T=2 5 1

RH =72.3 %

Figure 10.4 The environmental characterization of past and future. Table 10.1 Final results of tic predicted by the three models.

Percentual reduction in tic (%) Equivalent reduction for tic 5 50 years (years)

Saetta et al. (1993)

Bob (1996)

Amey et al. (1998)

26 13

38 19

14 7

the temperature and RH for the year 2100 were used for the future time period. The final predicted values for the rate of change of tic were obtained for each of the three selected models for a time span of approximately 100 years. Further calculations were performed to obtain the predicted service life reduction time using 50 years as the design reference period of the structure. The results are shown in Table 10.1. From the above results, it can be seen that under the influence of global warming, there is an overall increasing trend in both annual temperature and RH values in Guangzhou. With these environmental conditions, the diffusion time of chloride ions in concrete will be shortened by about 1438% over 100 years. The corresponding service life of an RC structure would be only 6286% of the design service life. There are still large fluctuations between the results of the different models, for example, a more accurate prediction of future climate and a chloride ion dispersion model that is closer to the Guangzhou environment is needed to derive a more precise change in the durability of RC structures. Further, if a 50-year span is taken as the designed service life, the safe service lifetime of an RC structure is estimated to be reduced by about 719 years, a degradation level that must not be ignored. Clearly, this prediction signifies a considerable influence of global warming on the durability of RC structures, which may lead to serious safety issues if maintenance is not involved in the later years of the service life. It also reminds us that changes in concrete design codes and standards should be made, and this adaption should also change with time and environmental conditions.

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Conclusion

This study collected real mean and dew point temperatures data from 1980 to 2021 of Guangzhou, representing coastal (atmospheric marine) zones of China. By conducting a time series prediction analysis, the mean and dew point temperatures were predicted for the next period 20212100. The annual relative humidity values of this city were also obtained from the available and predicted data. These useful data were input into three typical chloride diffusion models to estimate the changes in the durability of RC structures in this region. And the design base period was set in order to derive the change in service life of RC structures. The results are as follows: (1) An overall upward trend in annual average temperatures is shown for Guangzhou up to 2100, with a temperature change of about 2.35 C (about 10% increase) over 100 years. The change of atmospheric relative humidity is less significant, with a variation of 2.6% over 100 years. (2) In addition to an overall increase, temperature changes are also cyclical, with an oscillation period of about 12 years, and the amplitude of the oscillation is not large. Relative humidity changes can be seen to have become significantly more oscillatory since 2000. However, the reason that the periodicity of RH changes is not obvious is probably due to the fact that RH is influenced by a number of factors, including temperature and some other factors, which make it difficult to visualize the pattern. Therefore the trend of the effect of chloride ion attack on the durability of RC structures is more dependent on the trend of temperature changes. (3) Due to the rises in temperature and relative humidity, an increase in the chloride diffusion rate is resulted, which may lead to a reduction in chloride diffusion time of around 1438% over a 100-year period. This means that the service life of an RC structure is likely to be reduced by about 719 years, a significant alert to the structural safety and durability performance. (4) Changes in chloride corrosion due to global warming are more pronounced over a longer period of time. Therefore regular maintenance should be carried out in the later service life of an RC structure to prevent safety accidents from occurring. In addition, the durability degradation estimated warrants special attention to the changes in building standards over time to adapt to future climate changes. The results calculated in this study are for concrete structures with a curing age of 28 days and a water-to-cement ratio of 0.5. As can be seen from the data results in Table 10.1, there is a degree of variation in the final calculated results from the different chloride erosion models. This variation results in a large fluctuation in the final obtained chloride ion erosion effects on the durability of RC structures and does not provide an accurate basis of reference. To obtain more accurate results for reference, future research could attempt to consider the effects of different ages and water-to-cement ratios on the results, use more accurate future climate prediction methods to predict the data, and choose a chloride ingress model that is more appropriate for the actual area under consideration. The final results obtained from these studies can provide some reference for future maintenance of building facilities and modification of relevant regulations to better ensure the function and safety of building structures.

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Hoegh-Guldberg, O., Jacob, D., Taylor, M., et al. (2019). The human imperative of stabilizing global climate change at 1.5 C. Science (New York, N.Y.), 365(6459), eaaw6974. Hou, Q. H., & Yang, H. (2014). Analysis and forecasting of haze weather based on the cubic exponential smoothing model. Environmental Protection Science, 6, 7377. Huntingford, C., Jeffers, E. S., Bonsall, M. B., Christensen, H. M., Lees, T., & Yang, H. (2019). Machine learning and artificial intelligence to aid climate change research and preparedness. Environmental Research Letters, 14124007. IPCC. Climate Change. (2007). The fourth assessment report. Cambridge: Cambridge University Press. Ise, T., & Oba, Y. (2019). Forecasting climatic trends using neural networks: An experimental study using global historical data. Frontiers in Robotics and AI, 6. Kalekar, P.S. (2004). Time series forecasting using Holt-Winters exponential smoothing. Kanwal Rekhi School of Information Technology. Li, C. Q., Mackie, R. I., & Lawanwisut, W. (2007). A Risk-cost optimized maintenance strategy for corrosion-affected concrete structures. Computer-Aided Civil and Infrastructure Engineering, 22(5), 335346. Liu, T., & Weyers, R. W. (1998). Modeling the dynamic corrosion process in chloride contaminated concrete structures. Cement and Concrete research, 28(3), 365379. Medeiros-Junior, R. A. D., Lima, M. G. D., & Medeiros, M. H. F. D. (2015). Service life of concrete structures considering the effects of temperature and relative humidity on chloride transport. Environment Development & Sustainability, 17(5), 117. Meijers, S. J. H., Bijen, J. M. J. M., Borst, R. D., & Fraaij, A. L. A. (2005). Computational results of a model for chloride ingress in concrete including convection, drying-wetting cycles and carbonation. Materials and Structures, 38(2), 145154. Mora, C., Spirandelli, D., Franklin, E. C., et al. (2018). Broad threat to humanity from cumulative climate hazards intensified by greenhouse gas emissions. Nature Climate Change, 8(12), 10621071. Nandan, R., Singh, V., Singh, S. S., et al. (2019). Impact of conservation tillage in rice-based cropping systems on soil aggregation, carbon pools and nutrients. Geoderma, 340, 104114. Nordhaus, W. D. (1991). To slow or not to slow: The economics of the greenhouse effect. The Economic Journal, 101(407), 920937. Pal, J. S., Giorgi, F., Bi, X., et al. (2007). Regional climate modeling for the developing world: The ICTP RegCM3 and RegCNET. Bulletin of the American Meteorological Society, 88(9), 13951410. Saetta, A. V., Scotta, R. V., & Vitaliani, R. V. (1993). Analysis of chloride diffusion into partially saturated concrete. ACI Materials Journal, 90(5), 441451. Shafei, B., Alipour, A., & Shinozuka, M. (2012). Prediction of corrosion initiation in reinforced concrete members subjected to environmental stressors: A finite-element framework. Cement and Concrete Research, 42(2), 365376. Stewart, M. G., & Deng, X. (2015). Climate impact risks and climate adaptation engineering for built infrastructure. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 1(1)04014001. Tang, L. P. (1999). Concentration dependence of diffusion and migration of chloride ions: Part 1. Theoretical considerations. Cement and Concrete Research, 29(9), 14631468. Vousdoukas, M. I., Mentaschi, L., Voukouvalas, E., Verlaan, M., Jevrejeva, S., Jackson, L. P., & Feyen, L. (2018). Global probabilistic projections of extreme sea levels show intensification of coastal flood hazard. Nature communications, 9(1), 112.

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Shady Attia Department of Urban and Environmental Engineering, University of Liege, Lie`ge, Belgium

11.1

Introduction

Resilience is a central feature of the United Nations (UN) Sustainability Development Goals (SDGs) and is reflected in a range of SDG targets (Jacob et al., 2018). According to the UN General Assembly Resolution 71/276 (United Nations, 2017), the term “resilience” describes “the ability of a system, community or society exposed to hazards to resist, absorb, accommodate, adapt to, transform and recover from the effects of a hazard in a timely and efficient manner, including through the preservation and restoration of its essential basic structures and functions through risk management.” The need for resilient building design and construction is urgent to anticipate climate change and disruptions caused by weather extremes, increasing carbon emissions, and resource depletion (Attia, 2020). Our well-being depends on reducing the carbon emissions in our built environment and other sectors (Attia et al., 2021). While solving the root-cause problem of climate change, we need to address its effects. Avoiding excessive temperatures induced by overheating is one of the most critical challenges that the building industry will face worldwide in the coming decades (Gupta et al., 2017; Kjellstrom et al., 2009). Increasing electricity demand during heat stresses can lead to blackouts and grid failures. This can leave buildings out of thermal comfort range and threaten the lives of vulnerable people at risk, as happened during the 2003 Europe heatwave (De Bono et al., 2004). As building disruptions may have severe and long-term economic impacts, resilient building cooling solutions are an essential strategy to mitigate threats to occupants (Gupta & Kapsali, 2016). There is an urgent need for resilient cooling solutions in buildings to keep comfort despite extreme weather events due to climate change (Holzer & Cooper, 2019). Meanwhile, fuel-intensive mechanical cooling should be reduced to slow climate change (IEA, 2018). Greenhouse gas emissions from buildings’ air conditioning stand at around 210 460 gigatonnes of carbon dioxide equivalent (GtCO2e) over the next four decades, based on 2018 levels (Anderson et al., 2020). It is important to define buildings’ resilient cooling to maintain indoor environmental quality against unexpected events, for example, extreme weather conditions, Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00014-7 © 2023 Elsevier Ltd. All rights reserved.

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heat waves, and power outages. However, the definition of resilience and resilient cooling is challenging and complex (Kelman et al., 2016). Research on resilience associated with human nature interactions is still in an explorative stage with few practical methods for real-world applications (Carpenter & Folke, 2006; Liao, 2012). This chapter presents the main concepts of resilience. It proposes a definition of resilient cooling of buildings based on the discussion taking place in the International Energy Agency (IEA)—Energy in Buildings and Communities Programme research project “Annex 80: Resilient Cooling of Buildings” (Holzer & Cooper, 2019). The essence of this chapter is to define resilience against overheating and power outages. It seeks to answer the following research questions: 1. What are the existing concepts of resilience in the built environment? 2. How to define resilient cooling of buildings?

This chapter presents a definition framework based on reviewing almost 90 studies of resilience, including RELi 2.0 Rating Guidelines for Resilient Design and Construction (USGBC, 2018). One of the challenges of this study is to define resilience on the building scale beyond what is present in literature, which mainly addresses the definition of resilience on an urban scale. This reinforces the importance of resilient cooling as an integral approach for building design and operation concerning comfort (including indoor environmental quality), carbon neutrality, and environmental friendliness (Attia et al., 2021).

11.2

Methodology

The qualitative research methodology relies on literature review, focus group discussions, and follow-up discussions with individuals.

11.2.1 Data collection A literature review aimed to define resilience against different climate changeassociated disruptions in the built environment worldwide. The publications included scientific journal chapters, books, and building rating systems. Our initial Scopus and Web of Science research resulted in almost 90 publications relevant to resilience and resilience criteria in the built environment. To examine the definitions of resilience and the associated resilience criteria, such as vulnerability, resistance, robustness, and recoverability, we surveyed resilience in ecology, resilience in engineering, and resilience in psychology.

11.2.2 Data processing The content of the full text of every identified article was analyzed, and an analysis protocol and coding schema were developed to record its content attributes. The entire text of the full chapter was read multiple times as the coders (authors)

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completed the search for coding words. Coding is a way of indexing or categorizing the text to establish a framework for its themes (Gibbs, 2007). We used the framework method commonly used to manage and analyze qualitative data in health research (Gale et al., 2013; Lacey & Luff, 2001).

11.2.3 Development of a definition For the definition development, we used the framework method, which is the most commonly used technique for managing and analyzing qualitative data in health research (Gale et al., 2013; Lacey & Luff, 2001). The framework method allows systematic analysis of the text data to produce highly structured outputs and summarized data. It can also compare and identify patterns, relevant themes, and contradictory data (Gale et al., 2013). We categorized the codes (resilience concepts) by theme. Our classification resulted in four concepts that define the resilient cooling of buildings.

11.2.4 Focus group and follow-up-discussions Qualitative research is primarily a subjective approach to understanding human perceptions and judgments. However, it remains a solid exploratory scientific method if bias is avoided. The suggested definition was validated through focus group discussions to provide reliable and consistent results. Several validation measures were implemented, including member checking, memo logs, and peer examination following the work of Attia et al. (2021). The study validation allowed emphasizing credibility and strengthening the study’s relevance and results. Focus groups were convened during IEA Annex 80 first expert meeting in Vienna, Austria (October 21, 2019) and during its second expert meeting, held online (April 21, 2020). Each focus group comprised 15 people. The invited experts for the focus-group discussion represented the scientific and professional experts in the field of building performance assessment and comfort. An IEA Annex 80 participants list can be found on the Annex website (Holzer, 2019). The goal of the focus group discussions was to validate the suggested definition and main associated criteria. Follow-up discussions with RELi steering committee members and UN resilience experts helped articulate and validated the framework and included the detailed elaboration of some criteria. The follow-up discussions took place between the first authors and some of the coauthors via teleconference and emails.

11.3

Results

11.3.1 Resilience against what? One critical prerequisite for a comprehensive definition and assessment of resilience is identifying threats (shocks) or disruptions to the stability of these systems. An essential question to answer is “resilience against what?.”

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As shown in Table 11.1, several types of disruptions or emergencies can lead to the systemic failure of buildings to be resilient—for example, air pollution, fires, and earthquakes. Disruptions are increasingly presented by unexpected phenomena outside or inside the building (De Wilde & Coley, 2012). The rate and pace of disturbances that the built environment faces have accelerated significantly over the past three decades (Bull-Kamanga et al., 2003). Understanding and identifying the phenomena that disrupt a building and threaten the well-being of its occupants is fundamental. For our study, we decided to identify heat waves and power outages as the major disruptions that can influence occupant indoor environmental quality conditions on the building scale (Attia et al., 2021). This chapter is focused on the definition of resilient cooling of buildings as part of the IEA Annex 80 activities that aim to define resilience. Crawley (2008) identified heat waves as the significant climate change disruption in buildings. Baniassadi et al. (2018) identified the frequency and duration of power outages as a significant cause of disruption for buildings in the near future. Both studies confirmed that the increase of mean outdoor temperatures and the frequent and intensive nature of heatwaves disrupt power and degrade comfort. Disruptions are shocks or events that have an origin, nature, incidence, scale, and duration. Therefore we define disruptions in buildings as shocks that degrade the indoor environment and require resilient cooling strategies and technologies to maintain it (De Wilde & Coley, 2012).

11.3.2 Resilience: at which scale? And for how long? The resilience of a system cannot be studied without examining the scale of the system and the relation between the shock cause and its effect(s). Resilient systems function through the interaction of complex processes operating at different scales and times frames (Bull-Kamanga et al., 2003). Therefore it is essential to characterize the scale of the system that is expected to be resilient in a time-bound way. The definition of resilience should always reflect whether the disturbance affects the performance or operation of a single building element, building service, or the entire building (Crawley, 2008). As shown in Fig. 11.1, the definition of resilience should always characterize the resilience to disturbance of a system concerning its scale within a specific time frame for the disturbance. For our study, we define heat waves and power outages as the primary disruptive events addressed by resilient cooling for buildings. Our proposed definition considers the indoor environmental conditions on the building scale for long periods. Climate scenarios represent historical and future outdoor conditions and consider short-term and long-term heat waves. Resilience in the building engineering field is strongly associated with long-term climate projections that encompass the increase in the average temperature due to a global warming effect and a further temperature rise due to the urban heat island effect (Palme et al., 2017). Defining and identifying disruptions and specifying their associated events that impact healthy and comfortable buildings is the first step to determining a building’s resilience. As shown in Fig. 11.1, heat waves and power outages are events that may impact the thermal conditions in buildings. The identification of heatwave

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Table 11.1 Different types of disruptions affecting the built environment. Description Air Pollution

Fire

Earthquakes

Wind storms hurricanes Flooding

Heatwaves

Power outages

Water shortages

Pandemic

- Outdoor air pollution refers to the air pollution experienced by populations living in and around urban and rural areas. Air pollution derives from poor combustion of fossil or biomass fuels (e.g., exhaust fumes from cars, furnaces, or wood stoves) or wildfires. Buildings require efficient air filters and ventilation systems that mitigate the impact of air pollution. - Wildfires are sweeping and destructive conflagrations, especially in a wilderness or a rural area, that cause significant damage. Most building codes address common fire hazards with mandatory fireresistant stairwells, fire-resistant building materials, and proper escape methods. - Earthquakes are the most common disruptions covered in all building codes. Trembling of the ground is caused by the passage of seismic waves through the earth’s rocks. This natural disaster can damage a building by knocking it off its foundations and harming the occupants. Seismic testing should be used on components of buildings to determine their resilience to earthquakes. - Hurricanes have the potential to harm lives and property via storm surge, heavy rain, or snow, causing flooding or road impassibility, lightning, wildfires, and vertical wind shear. - Flooding is the inundation of land or property in a built environment, particularly in more densely populated areas, caused by rainfall overwhelming the capacity of drainage systems, such as storm sewers. - Heatwaves are a period of excessively hot weather, which may be accompanied by high humidity. They cause overheating in the building and intensify the urban heat island effect. This event can potentially risk the health and lives of occupants if no measures are taken. - Power outages and blackouts are common occurrences that can be caused by natural disasters cited earlier, like floods or hurricanes. It can lead to overheating in buildings when air conditioners do not operate. - Water shortage is the lack of freshwater resources to meet water demand. Lack of water significantly impacts irrigation and urban use, degrading food security, public health, and overall stability. - Pandemics can impact the built environment of societies is how spatial and social aspects are intertwined to constitute everyday lives mutually. Minimizing the risk of disease spread in buildings during active outbreaks starts with keeping people out of them. For those who occupy a building, increasing the ventilation and filtration of the inside air is essential.

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Figure 11.1 Time, Scale and Disruption as boundary conditions for systems’ resilience.

events is based on their intensity, duration, and frequency coupled with power outages (Laouadi et al., 2020). A building with a resistant cooling design (strategy) is expected to withstand short and extensive heat waves. A building with a robust cooling design can withstand short, intense, and prolonged lengthy heatwaves. The performance of a building with a resilient cooling design could surpass that of a robust building by reacting to power outages and longer intensive heat waves. The literature review confirms that resilience must be associated with a response to system failure (Gale et al., 2013). A system is robust when it can continue functioning in the presence of internal and external challenges without a system failure. However, a system is resilient when it can adapt to internal and external challenges by changing its method of operations while continuing to function. The ability of the building to recover after disruptive events is a fundamental feature of resilience. Therefore the ability to model the occurrence and consequences of discrete heatwave events is crucial to preparing the building for the response. The interviewed experts agreed that climate change should be defined as a longterm disruptive event and that heatwaves and power outages should be designated short-term disruptive events. Based on our literature review and following Fig. 11.2, we distinguish four major events categories that can challenge resilient cooling (Laouadi et al., 2020): Event 1: Observed and future extreme weather conditions (extended, spanning years). Event 2: Seasonal extreme weather conditions (long, spanning months). Event 3: Short extreme weather conditions (short, spanning days). Event 4: Power outages (spanning hours).

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Across the literature, several studies identified extended and long climate change-associated temperature increase events (events 1 and 2) (Hamdy et al., 2017; Moazami et al., 2019). Other studies investigated the impact of short-term heat waves and power outages on thermal conditions and cooling systems’ resilience (MacKenzie & Barker, 2012; Sailor, 2014). For example, the RELi rating system requires thermal safety during emergencies (events 3 and 4) by maintaining indoor air temperature at or below outdoor air temperature for up to 7 days (Gale et al., 2013). Schu¨nemann et al. (2022) investigated the heat resilience (overheating intensity) and energy efficiency (cooling demand) of two representative apartment buildings in Germany and Korea. Through thermal zoning and modeling, designers need to demonstrate that the building will maintain safe temperatures during a blackout that lasts four days. During a power outage, buildings must provide backup power to satisfy critical loads for 36 hours. We define four major event categories that need to be tested and addressed in any resilience assessment for comfort in buildings. The following section provides a further detailed explanation for Fig. 11.1 associated with Fig. 11.2.

11.3.3 Definition of “resilient cooling for buildings” Resilient cooling is used to denote low-energy and low-carbon cooling solutions that strengthen the ability of individuals and our community as a whole to withstand and also prevent the thermal and other impacts of changes in global and local climates—particularly concerning rising outdoor temperatures and the increasing frequency and severity of heatwaves (Burman et al., 2014). Resilient cooling for buildings is a concept that was not approached thoroughly in previous studies. Therefore we developed the following definition based on the

Figure 11.2 The difference between resistance, robustness and resilience in relation to disruption events intensity and frequency.

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literature review and validated it through the focus group discussion with members of IEA Annex 80: The cooling of a building is resilient when the capacity of the cooling system integrated into the building allows it to withstand or recover from disturbances due to disruptions, including heat waves and power outages, and to adopt the appropriate strategies after failure (robustness) to mitigate degradation of building performance (deterioration of indoor environmental quality and /or increased need for space cooling energy (recoverability). Resilience is a process that involves several criteria, including vulnerability, resistance, robustness, and recoverability (Martin & Sunley, 2015). Therefore we include those four criteria in the definition formulation shown in Fig. 11.1. The vulnerability involves the sensitivity or propensity of the building’s comfort conditions to different disruptions. It is vital to define disruptions at this stage, as discussed in Section 3.1 (see Figs. 11.1 and 11.2). A resilient building must be conceived based on a vulnerability assessment that considers future climate scenarios and prepares the building system, including occupants, to adapt against failures. The vulnerability assessment should test the building’s performance against long-term disruptions using average weather conditions, extreme weather conditions, future weather conditions, and worst future weather conditions. It should also test the building against short-term disruptions, including brief heat waves and power outages. A vulnerability assessment stage should be part of the design process. A building cooling system is prepared for different disruption scenarios engaging different thermal conditions. The building cooling system should withstand short-term and long-term disruptive events. As shown in Fig. 11.3, resistance involves the ability and the depth of reaction to the shock. Under disruptive events, the building may use performance dropbacks to achieve the predefined minimal thermal conditions. After the failure of the building cooling system, the building’s resilience process moves to the most

Figure 11.3 The buildings resilience timeline and performance (for higher resolution, see Attia, 2020).

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crucial stage—robustness, meaning reaction to failure. Robustness requires the building to be prepared to survive an otherwise-fatal shock by adapting its performance. The survivability of the system relies on its ability to ensure the critical thermal conditions to maintain the functional activities of occupants during a crisis. As shown in Fig. 11.3, a robust building will first fail and then adapt its performance conditions to meet critical or minimum thermal requirements to achieve a degree of survivability for occupants depending on the vulnerability assessment decisions made during design. The significant distinction between a resistant building system and a robust building system is that the latter is prepared to adapt based on a backup plan and ecosystem. Robustness involves how the building, including its services and occupants, adjusts and adapts to shocks. The final stage of resilience involves the recoverability of the system. Recoverability consists of the extent and nature of occupants and the building’s services to recover and returns to its equilibrium state and its speed to come back. As shown in Fig. 11.3, recovering has a duration, performance, and learnability. The necessary speed for recovery and the recovery performance curve should be planned during the vulnerability assessment stage. The ability of the users, buildings, and systems to learn from the event is an integral part of this stage. While the diagram in Fig. 11.3 is linear, the resilience process is cyclic and iterative. Resilient cooling of buildings is a continuous process involving the commissioning and retro-commissioning of building elements and systems over the building’s life cycle. It also includes the continuous education of occupants and the preparation for adaptive measures during unforeseeable disruptions. Fig. 11.4 provides a complementary definition framework that includes the main resilience criteria. It presents an example of the factors that influence building

Figure 11.4 Influencing factors of resilient cooling of buildings (for higher resolution, see Attia, 2020).

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cooling performance under the four resilience criteria. Depending on the overheating definition and exposure risk, a resilient cooling design for buildings assures that the designed indoor environmental conditions are secured before the disruption. The risk factors should be identified during the design stage to assess vulnerability. Examples of risk factors include climate change scenarios, heat waves combined with power outages, or urban heat island effects. As shown in Fig. 11.4, the resistance stage depends mainly on the building’s design features and technologies and their ability to keep the building performing under severe overheating exposure until reaching failure. The failure is the essential disruption to start the third stage of resilience, namely robustness. The robustness of the cooling system the building must adapt to cover the critical thermal conditions temporarily until reaching the recovery stage. The ability to respond, in an adaptive way, that implements fundamental changes to the original thermal conditions involved occupants and systems adaptability. The energy system backup and an emergency control possibility are part of the building’s robustness. This is finally followed by a recovery stage and a shift in the building performance to achieve before designed thermal conditions that adapt to the normal.

11.4

Discussion

The review of the main concepts of resilient cooling for buildings and the proposal for a definition and assessment framework indicates the complexity of the idea. We found varying and inconsistent definitions of resilience in the context of building comfort and in the context of the overall built environment. The following sections discuss possible questions that we answered in this study. 1. What are the existing concepts of resilience? 2. How to define resilient cooling for buildings?

Few studies and case studies succeeded in defining resilience and applying its principles on a building scale. Across our review, we found some studies that focus mainly on robustness as a proxy for resilience (Homaei & Hamdy, 2020, 2021; Kotireddy et al., 2018; Miller et al., 2021). However, none of those reviewed studies embraced a multicriteria approach for resilience that involves vulnerability, resistance, robustness, and recoverability. Therefore based on our literature review and focus group discussions, this study’s suggested definition and framework are a step forward. The following recommendations can be helpful for designers and building operators that seek to achieve resilient cooling of buildings in a holistic way: 1. Any definition of resilience must be based on identifying a specific shock or disruption. In the case of resilient cooling of buildings, heat waves and power outages are considered the main shocks (extreme events). Designers should prepare buildings against those shocks.

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2. Any definition of resilience should specify and distinguish, at the same time, the resistance and robustness conditions against heat waves and power outage events. The resistance period involves the building’s ability to resist shock(s) with the same preshock operation conditions. However, robustness requires failure and adaptation after failure. The robustness mechanism involves building users and building systems adaptation and their ability to adjust after a shock. 3. Thus the definition of resilient cooling for buildings involves four critical criteria, mainly vulnerability (preparation), resistance (absorption), robustness (adaptation after failure), and recovery (remedy). The building design, construction, and operation processes should address these criteria. 4. Resilient and passive cooling design is an urgent requirement for future-proof buildings (Silva et al., 2022). Weather extremes must be anticipated to assume well-being. The choice of comfort models is elementary in preparing buildings. Resilient cooling design involves the combination of passive and active cooling design measures (Zeng et al., 2022), on-site renewable production, and coupling to storage capacities. Our suggested definition for resilient cooling of buildings can help to develop future resilience performance indicators that account for the impacts of global warming for long and short assessment periods. This can allow comparing the carbon emissions and primary energy use at different stages of the building life stages. As part of the activities of IEA—Annex 80, there is a need to assess the performance of conventional and advanced cooling technologies. Without a multistage definition, it will be challenging to develop universal indicators that assess the active and passive cooling technologies listed above. 5. Building operation systems and building management systems will play a significant role in applying the adaptation strategies and risk mitigation plans in collaboration with buildings users. HVAC systems and envelope features are a prime target for real-time optimization for resilient cooling. Different dynamic control strategies with predictive algorithms should be embedded in building operation systems using a deeply coupled network of sensors. The smart readiness of buildings is part of resilience because it considers that buildings must play an active role within the context of an intelligent energy system ¨ sterreicher, 2019). (M¨arzinger & O 6. Resilience is a process, and its criteria should be addressed following a circular, iterative approach. Extracting learned lessons and integrating user experience during shocks is essential to increase the emergency learnability and feed the preparedness loop.

11.5

Conclusion

A definition of resilient cooling for buildings is developed and discussed in this chapter as part of the IEA Annex 80 research activities. The definition’s main concepts and criteria are based on qualitative research methods. This chapter presents a set of recommendations to adopt the definition in practice and research. Future research should build on our findings and create more consistent frameworks (Rahif et al., 2022) with useful quantifiable indicators (Zhang et al., 2021), quantitative metrics, and performance threshold limits. Additional definitions of overheating and modeling of overheating events are required for different building types and climates. The research should be extended to identify benchmarks and case studies (Sun et al., 2021) with reference values and threshold ranges and seek tools and

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reporting mechanisms for the resilient cooling of buildings. The suggested framework should evolve as research and experience build a greater understanding of resilient and sustainable buildings.

Acknowledgments The Walloon Region partially funded this research under the call “Actions de Recherche Concerte´es 2019 (ARC)” and the project OCCuPANt, on the Impacts Of Climate Change on the indoor environmental and energy PerformAnce of buildiNgs in Belgium during summer. The authors would like to gratefully acknowledge the Walloon Region and Liege University for funding.

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Gibbs, G. R. (2007). Thematic coding and categorizing. Analyzing Qualitative Data (pp. 38 56). Sage. Gupta, R., Barnfield, L., & Gregg, M. (2017). Overheating in care settings: magnitude, causes, preparedness and remedies. Building Research & Information, 45(1 2), 83 101. Gupta, R., & Kapsali, M. (2016). Empirical assessment of indoor air quality and overheating in low-carbon social housing dwellings in England, UK. Advances in Building Energy Research, 10(1), 46 68. Hamdy, M., Carlucci, S., Hoes, P.-J., & Hensen, J. L. (2017). The impact of climate change on the overheating risk in dwellings—A Dutch case study. Building and Environment, 122, 307 323. Holzer, P. (2019). Annex 80 participants. Available from https://annex80.iea-ebc.org/participants, Accessed 1 April 2022. Holzer, P. & Cooper, W. (2019). IEA EBC Annex 80 on resilient cooling for residential and small non-residential buildings, IEA, https://doi.org/10.13140/RG.2.2.33912.47368. Homaei, S., & Hamdy, M. (2020). A robustness-based decision making approach for multitarget high performance buildings under uncertain scenarios. Applied Energy, 267, 114868. Homaei, S., & Hamdy, M. (2021). Thermal resilient buildings: How to be quantified? A novel benchmarking framework and labelling metric. Building and Environment, 108022. IEA. (2018). The future of cooling: Opportunities for energy-efficient air conditioning. IEA. https://www.iea.org/reports/thefuture-of-cooling. Jacob, A. et al. (2018). Transformation towards sustainable and resilient societies in Asia and the Pacific. Kelman, I., Gaillard, J. C., Lewis, J., & Mercer, J. (2016). Learning from the history of disaster vulnerability and resilience research and practice for climate change. Natural Hazards, 82(1), 129 143. Kjellstrom, T., Holmer, I., & Lemke, B. (2009). Workplace heat stress, health and productivity—an increasing challenge for low and middle-income countries during climate change. Global Health Action, 2(1), 2047. Kotireddy, R., Hoes, P.-J., & Hensen, J. L. (2018). A methodology for performance robustness assessment of low-energy buildings using scenario analysis. Applied Energy, 212, 428 442. Lacey, A., & Luff, D. (2001). Qualitative data analysis. Trent Focus. Laouadi, A., Gaur, A., Lacasse, M. A., Bartko, M., & Armstrong, M. (2020). Development of reference summer weather years for analysis of overheating risk in buildings. Journal of Building Performance Simulation, 13(3), 301 319. Liao, K.-H. (2012). A theory on urban resilience to floods—A basis for alternative planning practices. Ecol. Soc., 17(4). MacKenzie, C. A., & Barker, K. (2012). Empirical data and regression analysis for estimation of infrastructure resilience with application to electric power outages. Journal of Infrastructure Systems, 19(1), 25 35. Martin, R., & Sunley, P. (2015). On the notion of regional economic resilience: Conceptualization and explanation. Journal of Economic Geography, 15(1), 1 42. ¨ sterreicher, D. (2019). Supporting the smart readiness indicator—A methM¨arzinger, T., & O odology to integrate a quantitative assessment of the load shifting potential of smart buildings. Energies, 12(10), 1955.

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Miller, W., Machard, A., Bozonnet, E., Yoon, N., Qi, D., Zhang, C., & Levinson, R. (2021). Conceptualising a resilient cooling system: A socio-technical approach. City and Environment Interactions, 11, 100065. Moazami, A., Nik, V., Carlucci, S., & Geving, S. (2019). Impacts of the future weather data type on the energy simulation of buildings—Investigating long-term patterns of climate change and extreme weather conditions. Palme, M., Inostroza, L., Villacreses, G., Lobato-Cordero, A., & Carrasco, C. (2017). From urban climate to energy consumption. Enhancing building performance simulation by including the urban heat island effect. Energy and Buildings, 145, 107 120. Rahif, R., Hamdy, M., Homaei, S., Zhang, C., Holzer, P., & Attia, S. (2022). Simulationbased framework to evaluate resistivity of cooling strategies in buildings against overheating impact of climate change. Building and Environment, 208, 108599. Sailor, D. J. (2014). Risks of summertime extreme thermal conditions in buildings as a result of climate change and exacerbation of urban heat islands. Building and Environment, 78, 81 88. Schu¨nemann, C., Son, S., & Ortlepp, R. (2022). Heat resilience of apartment buildings in Korea and Germany: Comparison of building design and climate. International Journal of Energy and Environmental Engineering, 1 21. Silva, R., Eggimann, S., Fierz, L., Fiorentini, M., Orehounig, K., & Baldini, L. (2022). Opportunities for passive cooling to mitigate the impact of climate change in Switzerland. Building and Environment, 208, 108574. Sun, K., Zhang, W., Zeng, Z., Levinson, R., Wei, M., & Hong, T. (2021). Passive cooling designs to improve heat resilience of homes in underserved and vulnerable communities. Energy and Buildings, 252, 111383. United Nations. (2017). 71/276. Report of the open-ended intergovernmental expert working group on indicators and terminology relating to disaster risk reduction. United Nations, UN General Assembly 71/276 Resolution. USGBC. (2018). RELi 2.0 rating guidelines for resilient design and construction. U.S. Green Building Council. Zeng, Z., Zhang, W., Sun, K., Wei, M., & Hong, T. (2022). Investigation of pre-cooling as a recommended measure to improve residential buildings’ thermal resilience during heat waves. Building and Environment, 210, 108694. Zhang, C., Kazanci, O. B., Levinson, R., Heiselberg, P., Olesen, B. W., Attia, S., & Zhang, G. (2021). Resilient cooling strategies—A critical review and qualitative assessment. Energy and Buildings, 251, 111312.

Climate change and building performance: pervasive role of climate change on residential building behavior in different climates

12

Cristina Baglivo1, Paolo Maria Congedo1 and Domenico Mazzeo1,2 1 Department of Engineering for Innovation (DII), University of Salento, Lecce, LE, Italy, 2 Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria, Rende, CS, Italy

12.1

Introduction

Numerous data agree on an inexorable overall rise in air temperature due to climate change (Dias et al., 2020; Haddad et al., 2020). Buildings are largely responsible for global energy consumption and are among the largest contributors to global warming (Rabani et al., 2021). The energy needs of buildings are principally for heating, cooling, domestic hot water, and lighting consumption (Salata et al., 2018). Climate change is expected to have an even greater impact on heating and cooling requirements in buildings. Until 2050 building energy needs are expected to increase by ¨ rge-Vorsatz et al., 79% in residential buildings and 84% in commercial buildings (U 2015). Therefore a prior assessment of the future climate in the design and retrofit phases cannot be ignored if the energy requirements of buildings are to be reduced over the years (Baglivo et al., 2022) and thus ensure building resilience to climate change. Several actions have already been launched and adopted both locally and globally to mitigate the change that is already occurring while trying to avoid the deterioration of the environment (Congedo & Baglivo, 2021). The European Commission proposes that from 2030, all new buildings must be zero emission (https://ec.europa.eu/commission/presscorner/detail/en/IP_21_6683) (visited on 29 march 2022) and toward decarbonization and reduction of current energy consumption. Moreover, crises, such as the one caused by the very recent SARS-CoV-2 pandemic, have greatly changed people’s habits, leading to new needs and a different way of living. Today smart working has changed the way of perceiving residential buildings, which in part also play the role of offices; on the other hand, in public buildings, it is necessary to ensure high levels of healthy air through proper ventilation. Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00003-2 © 2023 Elsevier Ltd. All rights reserved.

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Indeed, the link between heavy air pollution and the spread of SARS-CoV-2 is well known (Filippini et al., 2020). Ventilation allows the removal of toxic air pollutants and guarantees high levels of indoor air quality, providing comfort and health to occupants (Ng et al., 2015). Well-designed buildings can play a central role in controlling the spread of infectious diseases (Awada et al., 2021); but, if air exchanges are improper and undersized, occupants may experience respiratory problems, especially if indoor environments are highly insulated and sealed. There are different types of ventilation: natural, mechanical, or combined. Under these circumstances, it can be expected that controlled mechanical ventilation systems will increase in the future, including in residential buildings, resulting in increased energy consumption (Congedo et al., 2019). In addition, the use of buildings for work also leads to increased consumption of the buildings themselves, as people use residential buildings as work environments most of the time. Even the high-performance buildings that have been designed to date may, in the long run, lead to further negative impacts due to increased energy consumption and emissions. Even if best design practices are widely adopted and implemented, this will only mitigate global warming, and not necessarily be able to stop the impending climate change that is underway. First and foremost, rising outdoor temperatures will inevitably cause a decrease in the indoor comfort of buildings, but it will also lead to shortened device life, higher energy consumption, and greater operating costs. This would result in a shift toward a greater electricity supply with considerable implications for national and international energy and environmental policies. Zero-energy buildings (ZEBs) have captured interest worldwide because they consume less energy than traditional buildings (Lin et al., 2020). ZEBs are expected to lead to a new way of designing toward a major reduction in energy consumption and CO2 emissions and thus act at the forefront of the fight against climate change (Liu et al., 2019; Nasser Al-Saadi & Shaaban, 2019). Many studies use optimization as an important step in building design to address climate change and reduce greenhouse gas emissions (Baglivo & Congedo, 2019; Nguyen et al., 2021). Designing renewable energy systems for near-ZEBs is a complex optimization problem that can also be computationally time-consuming (Ferrara et al., 2021). Energy optimization of buildings is typically conducted under current climate conditions (Congedo et al., 2015), it is critical to also consider a predictive analysis of possible future scenarios in the optimization steps, as climate change can affect the optimized design. Given these assumptions, designing resilient buildings today means predicting at the design stage the possible influence of climate change to enable the building to provide indoor comfort conditions. Climate-responsive buildings, such as ZEBs, should always be designed using long-term simulations (Congedo et al., 2015). In fact, due to climate change, actions taken today to improve building performance may result in missing the net-zero goal for most future years. Therefore it is critical to make design choices characterized by a greater awareness of future climate scenarios, so that design efforts made in the present are not in vain 50 years later. The purpose of this study is to illustrate the effects of climate change on a building designed in four very different climates. The goal is to identify how the

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231

conditions of well-being and distress inside a hypothetical building change over the years across climate zones. The building is the same for all locations to allow easy comparison. A residential apartment has been dynamically simulated in a freefloating regime. The choice to disregard the air-conditioning system is on the basis that a building with an optimized envelope will certainly have less need for airconditioning systems. To monitor comfort within the building, the indoor operative temperature (TOP) was plotted on an hourly and annual basis. TOP values were analyzed in the short, medium, and long term, considering the years 2020, 2050, and 2080 at all selected cities.

12.1.1 Effects of climate change on building behavior: summary results from the literature Climate change is driving the world toward higher outdoor temperatures (Congedo et al., 2021), resulting in an expansion of arid zones and the warming of polar areas (Chen & Chen, 2013). Although several actions have been conducted to improve the performance of existing buildings designed in the current climate (D’Agostino et al., 2017), in the future the effect of climate change will result in less energy use for winter heating and more use for summer cooling (Ciancio et al., 2020). The degree of this impact will vary by region and climate, as energy demand is closely linked to the climatic conditions of the building location (Ciancio et al., 2018). Implications of global warming were conducted in eight major cities in India characterized by different climates, the results indicate that the cooling needs of buildings will increase, and on the contrary, heating demands will decrease (Ukey & Rai, 2021). A study conducted on commercial buildings located in the Middle East determined that the most effective passive cooling solutions are natural ventilation, efficient glazing, and shielding devices (Fereidani et al., 2021). Shortly, buildings located in different climatic regions of Southeast Asia will experience an increase in total energy consumption along with a significantly longer overheating period, therefore it is necessary to undertake a potential adaptation and mitigation path through a multiobjective optimization strategy to minimize its impact. The optimal models show significant superiority in energy-saving and overheating prevention over the baseline model and its variants (Nguyen et al., 2021). The study (Hwang et al., 2018), conducted on a building in Taiwan, highlighted the limitations of the energy conservation index of the building envelope, which needs to be adapted over time to accurately respond to climate change. Climate change could increase the intensity of energy consumption for buildings located in different climate zones in the United States. It is expected that cities with hot and humid climates should experience high growth rates in building energy use, while in cold climates energy use could be reduced. The comparison of different uses shows that commercial buildings could increase their energy use at a faster rate than residential ones (Fonseca et al., 2020). The behavior of commercial buildings located in different Australian climate zones was tested in the current and future climate scenarios. It is found that

232

Adapting the Built Environment for Climate Change

buildings with optimized configurations built in the subtropical climate are less affected by changes in the load scenario than those built in the cool temperate climate (Bamdad et al., 2021). From the analysis conducted on a residential building located in a hot-humid climate in Turkey, considering the short- and long-term climate conditions until 2080, it was found that the choices of solar heat gain and heat transfer coefficients of transparent surfaces have a great influence on the energy and environmental performances of the building (Gercek & Arsan, 2019). It is estimated that the energy consumption of a prefabricated building located in the United Kingdom, compared to 2017, could decrease by 12% in 2030 and 34% in 2080 (Ismail et al., 2021). A question that arises is whether the actions taken today to design highefficiency buildings also through incentives, applied by various countries around the world, will be effective in the future due to climate change and therefore if, in the long run, the buildings will be able to adapt without too much additional expense and ensure comfort to users (Baglivo, 2021). For example, although in Switzerland, there is a transition from old to new buildings, the national goals of a 60% reduction in energy demand and net-zero GHG emissions by 2050 may not be met, as a decrease of only a quarter is expected in 2060 (Streicher et al., 2021). The impact of global warming has been addressed by analyzing residential buildings’ energy requirements located in 19 European cities. In Southern Europe, an overall decrease in thermal energy demand for heating and an increase in electricity demand for cooling are expected, resulting in increased CO2 emissions (Ciancio et al., 2020). This overview highlights the strong correlation between climate and buildings, and the resulting impact on energy use; improper design assessment could lead to unexpected and undue energy losses, under or oversized energy sources, and underperforming building envelopes (Tu¨kel et al., 2021). In addition, impending climate change will lead to different building performance over time, compared to when it was designed, in terms of energy requirements and the number of system operating hours (Andri´c et al., 2017). It will be necessary to outline large-scale future scenarios, through a reorganization of the energy production sector and the energy market, based on the new energy needs of the building sector (Salata et al., 2017), the costs of energy sources, and electricity production in each nation.

12.2

Methodology

The study involves the simulation of a building, chosen as a prototype, in very different climates. The building was modeled on Termolog Epix 12, and the results were plotted in terms of indoor operative temperature (TOP) on an hourly and annual basis, in a free-floating regime. The operative temperature can be defined as the uniform temperature of a fictitious environment in which a subject inside would exchange by radiation and convection the same energy that he/she exchanges in the real environment, generally

Climate change and building performance

233

not uniform. It is determined by the combination of the air temperature and the average radiant temperature. For all locations, simulations were performed considering climate data for 2020, 2050, and 2080 exported from World Climate Change Weather File Generator.

12.2.1 Climate data generator World Climate Change Weather File Generator (CCWorldWeatherGen) (Jentsch et al., 2013) is a widely used climate change weather file generation tool. It returns climate data for each location in the world for three-time intervals: 2020 (includes a range from 2011 to 2040), 2050 (from 2041 to 2070), and 2080 (from 2071 to 2100), in terms of dry bulb temperature, dew point temperature, direct normal radiation, horizontal diffuse radiation, and wind speed. The CCWorldWeatherGen uses model data from the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report of the HadCM3 A2 experiment set. The climate file generation routines are based on the “morphing” methodology. Four locations in different nations around the world, characterized by very different climates, were selected. The international Ko¨ppen-Geiger climate classification (http://koeppen-geiger.vu-wien.ac.at/shifts.htm; Mazzeo et al., 2020) was used to select the locations, which are divided into macrogroups that are in turn divided into further microclimates. The choice was made by taking one city per macrogroup. As shown in Table 12.1, the locations chosen are Miami with a tropical—tropical monsoon climate (Am), Damascus with arid—cold desert climate (Bwk), Izmir with temperate—hot summer Mediterranean climate (Csa), and Yakutsk with continental—extremely cold subarctic climate (Dfd). For each of these cities, the hourly climate data for the years 2020, 2050, and 2080 have been extrapolated from CCWorldWeatherGen. The minimum, average, and maximum values of outdoor temperatures are plotted in the table for each year considered and for all locations. Looking at the annual minimum outdoor temperature peaks of Table 12.1, it can be seen that going from 2020 to 2080 there is a major temperature increase in Yakutsk of about 5.4 C, followed by Miami with an increase of 2.7 C, and Izmir and Damascus both seeing an increase of 1.8 C. On the other hand, in terms of maximum outdoor temperature peaks, going from 2020 to 2080, the largest increase is in Izmir with 6.7 C, followed by Yakutsk and Damascus with 3 C and Miami with 2.5 C.

12.2.2 Energy software for dynamic building simulation Termolog EpiX 12 is an energy software approved by the Italian Thermotechnical Committee (CTI) for the calculation of the building performances using hourly dynamic energy simulations. It is software widely used in Italy (Congedo et al., 2020; Fregonara et al., 2017). The hourly dynamic engine allows performing the energy balance, returning the real behavior of the building to the climate and the internal conditions, according to UNI EN ISO 52016 (UNI EN ISO 52016 1:2018, 2018). Once the building has been modeled including all its components, that is, defining the envelope, the plants, and the renewable sources, it allows to import the

Table 12.1 External temperature ranges across the Ko¨ppen-Geiger climate classification of Miami, Damascus, Izmir, and Yakutsk. Cities

Code

External temperatures ( C)

Description Minimum

Miami ( Florida, United States) Damascus (Syria)

Am Bwk

Izmir (Turkey)

Csa

Yakutsk (Sakha Republic, Russia)

Dfd

Tropical—tropical monsoon climate Arid—cold desert climate Temperate—hot summer Mediterranean climate Continental—extremely cold subarctic climate

Average

Maximum

2020

2050

2080

2020

2050

2080

2020

2050

2080

3.9

5.1

6.6

25.1

26.1

27.5

34.7

35.6

37.2

25.4

24.7

23.6

17.6

18.6

20.3

44.5

45.6

47.5

22.3

21.7

20.5

17.9

19.2

21.3

42.6

45.3

49.3

245.2

242.9

239.8

27.5

25.5

23.2

33.9

35.5

36.9

Climate change and building performance

235

climatic data generated by other software, such as CCWorldWeatherGen, and to evaluate on an hourly basis the trends followed by the internal operative temperature. Hourly calculations can be made both in a free-floating regime with the heating and cooling system generator switched off and considering the operation of the plants as scheduled. This study provides the analysis in a free-floating regime.

12.2.3 The case study An isolated building with exposed walls was considered according to the main orientations. The perimeter walls border the outside environment. The case study analyzed is a small apartment belonging to a three-storey apartment building, located on the second floor. All the apartments in the condominium have the same internal distribution, thus only one apartment has been chosen for analysis. As shown in Fig. 12.1, the apartment has a useful floor area of 73.57 m2 and a net interfloor height of 2.7 m. It consists of two bedrooms, kitchen, bathroom, and hallway. Table 12.2 shows the stratigraphy details of the opaque envelope, specifically for external walls, floor against the ground, intermediate floor, and roof. Table 12.2 presents the single material properties in terms of thickness (d), specific heat (C), conductivity (λ), and density (ρ), selected from the commercial data sheets of the building materials. In addition, Table 12.2 shows the total thickness (dtot) of the opaque element and the thermal characterization in terms of phase shift (t), stationary thermal transmittance (U), dynamic thermal transmittance (YIE), and decrement factor (Fd), calculated according to UNI EN ISO 13786 (EN ISO 13786, 2017). The total thickness (dtot) is the sum of all single thicknesses (d) that compose the element.

Figure 12.1 Internal distribution of the second floor.

Table 12.2 Details of the opaque envelope stratigraphy with individual material properties and thermal characterization of the envelope element. Elements

External walls

Floor against the ground

(Inside to outside)

Layer 1 Layer 2 Layer 3 Layer 4 Layer 1 Layer 2 Layer 3 Layer 4 Layer 5 Layer 6 Layer 7 Layer 8

Layer 9 Layer 10 Intermediate floor

Layer 1 Layer 2 Layer 3 Layer 4 Layer 5 Layer 6

Layers

Plaster Stone blocks Polystyrene Plaster Tiles Cement mortar Concrete screed Steam barrier Polystyrene Bituminous membrane Reinforced concrete Under-floor cavity with ventilated cavity-type Iglu Lean concrete Coarse gravel without clay Tiles Cement mortar Concrete open structure Polyester fibers Attic block Plaster

d

C

λ

ρ

dtot

t

U

YIE

Fd

(mm)

[kJ/ (kgK)]

[W/ (mK)]

(kg/ m3)

(mm)

(h)

[W/ (m2K)]

[W/ (m2K)]

[ ]

10 250 80 10 10 10 80 5 30 5

1 1 1.45 1 0.84 1 1 1.5 1.45 1

0.7 0.55 0.03 0.7 1 1.4 1.06 0.4 0.03 0.17

1400 1600 24 1800 2300 2000 1700 360 24 1200

350

12 h 07’

0.325

0.03

0.088

650

15 h 48’

0.623

0.03

0.052

80

1

1.91

2400

200

1

1.39

1200

80 150

1 0.84

1 1.2

2200 1700

12 10 100

0.84 1 0.88

1 1.4 0.32

2300 2000 600

400

14 h 55’

0.799

0.06

0.072

8 260 10

0.96 1 1

0.04 0.74 0.7

125 1800 1400

Roof

Layer 1 Layer 2 Layer 3

Layer 4 Layer 5 Layer 6 Layer 7 Layer 8

Plaster Attic block Bituminous waterproofing membrane Polystyrene Concrete Sheets of synthetic material Dry sand Stone blocks

10 260 4

1 1 1

0.7 0.74 0.17

1400 1800 1200

100 50 2

1.45 0.88 1.5

0.03 0.94 0.23

24 1800 1100

100 40

0.84 1

0.6 0.55

1700 1600

566

19 h 15’

0.259

0.01

0.025

238

Adapting the Built Environment for Climate Change

Phase shift (t) is the difference in time between the time when the maximum temperature is recorded on the external surface of the element and the time when the maximum temperature is recorded on the internal surface, in other words, it is a period of time between the maximum amplitude of a cause and the maximum amplitude of its effect. Stationary thermal transmittance (U) measures the amount of heat that in a given unit of time passes through an element with a surface area of 1 m2 when there is a temperature difference of 1K between the inside and outside environments. Dynamic thermal transmittance (YIE) is defined as the ratio of the change in heat flux entering one environment held at a constant temperature to the change in temperature over the other environment. The decrement factor (Fd) is the ratio of the modulus of the periodic thermal transmittance to the steady-state thermal transmittance U. The choice to report these values is determined by the awareness that U is the thermal property that most influences the behavior of the building envelope in the winter season, while the parameters that best represent summer performances are YIE, t, and Fd (Baglivo & Congedo, 2016). All windows are 160 cm 3 150 cm in size, with the following characteristics: G

G

G

G

low emissivity glass 4 15 4 with argon, glass transmittance of 1.522 W/(m2K), frame of double chamber PVC, frame transmittance of 2.2 W/(m2K), window transmittance of 1.765 W/(m2K), and solar heat gain coefficient of 0.32

All windows have white exterior shutters and opaque transparency, made of wood and plastic with no foam and high air permeability. Although these values are not identifiable to a specific location, the envelope characteristics were left unchanged for each simulation to be able to analyze the same building in each climate zone and decrease the problem variables. The goal is not to create an optimal building for a location, but to understand how the behavior of the same building differs in different locations as climatic conditions change. The building has been analyzed considering the thermal systems off, as it is assumed that if the building envelope is well designed then it will be possible to implement the thermal system, allowing the achievement of comfort inside the spaces without an overuse of the systems.

12.3

Results and discussions

Once the building was modeled in Termoloig Epix 12, and climate data from CCWorldWeatherGen was imported for the three-time frames, indoor operative temperature values were calculated on an hourly and annual basis and in the freefloating regime. Fig. 12.2 shows the temperature trend in Miami (climate code— Am). The blue line represents the outdoor temperature trend, while the gray one represents the indoor operative temperature trend. The trends were calculated on an

Figure 12.2 External air temperature and indoor operative temperature (TOP) trends in Miami, for the years 2020, 2050, and 2080. Please refer the online version to view the color image of the figure.

240

Adapting the Built Environment for Climate Change

hourly and annual basis, for the 8760 hours of the year. Values are shown for the years 2020, 2050, and 2080. Similarly, operative indoor temperature values were plotted by locating the same building at the other selected locations. Fig. 12.3 shows the annual hourly temperature trend in Damascus (climate code—Bwk), Fig. 12.4 displays the temperature trend in Izmir (climate code—Csa), Fig. 12.5 presents the temperature trend in Yakutsk (climate code—Dfd). Table 12.3 shows the operative temperature of the chosen localities for the years 2020, 2050, and 2080. The values are the maximum, the minimum peaks, and the average TOP during the years. As observed the maximum temperature peak in 2020 is in Izmir and Damascus, reaching a value of 35.8 C in Izmir and 35.7 C in Damascus. Maximum peaks also result in 2050 and 2080 in these two cities, but temperatures tend to differ, reaching an absolute maximum in Izmir. A maximum value of 41.6 C is reached in Izmir in 2080 while 38.9 C is reached in Damascus. As far as the minimum peaks are concerned, the city that reaches the lowest operative temperature is Yakutsk, which reaches a minimum of 26.2 C in 2020 and 22  C in 2080. Three indoor operative temperature ranges have been considered, namely: TOP , 20 C, in which it is necessary to turn on the heating system, 20 C , TOP. 26 C, comfort range, and therefore it is not necessary to turn on the heating system, TOP . 26 C, in which it is necessary to turn on the cooling system.

Assuming that the building is the same for all cities, Table 12.4 shows the number of hours, and Fig. 12.6 graphically reports the percentage of hours, in which the TOP falls in the three ranges, for the 3 years considered, and for the four selected locations. Figure during the year when the operating temperature falls into one of the three ranges considered. Among all the cities considered, Miami is the city that has a lower percentage of hours in which it is necessary to turn on a heating system, a percentage that tends to decrease over the years. The number of hours when it is necessary to turn on the cooling system will increase at the expense of the comfort hours when the optimum temperature is reached without turning on the system. In Damascus, the number of hours when TOP is below 20 C dominates in 2020; the number of hours when TOP is below 20 C and above 26 C is basically the same in 2080, that is, 3643 hours when TOP is below 20 C and 3655 hours when TOP is above 26 C. The number of hours in which a heating system is not required in a building tends to increase with time. Specifically, the number of hours of thermal comfort tends to increase and the number of hours when heating is not needed decreases, while the number of hours when a cooling system needs to be used increases. In Izmir, the number of hours when TOP is below 20 C prevails in 2020, and the number of hours when TOP is below 20 C (3809 hours) is closer to the number of hours when the temperature is above 26 C (3539 hours) in 2080, although the number of hours when the temperature is below 20 C is higher. Over the years, the number of hours when it is not necessary to turn on a cooling system and the comfort hours tend to increase, decreasing the number of hours when it is necessary to turn on the heating system.

Figure 12.3 External air temperature and indoor operative temperature (TOP) trends in Damascus, for the years 2020, 2050, and 2080. Please refer the online version to view the color image of the figure.

Figure 12.4 External air temperature and indoor operative temperature (TOP) trends in Izmir, for the years 2020, 2050, and 2080. Please refer the online version to view the color image of the figure.

Figure 12.5 External air temperature and indoor operative temperature (TOP) trends in Yakutsk, for the years 2020, 2050, and 2080. Please refer the online version to view the color image of the figure.

Table 12.3 Internal operative temperature (TOP) ranges of Miami, Damascus, Izmir, and Yakutsk, for 2020, 2050, and 2080. TOP ( C) Miami

MAX MIN AVERAGE ST. DEV.

Damascus

Izmir

Yakutsk

2020

2050

2080

2020

2050

2080

2020

2050

2080

2020

2050

2080

32.8 14.3 26.8 3.3

33.8 15.4 27.7 3.3

35.1 16.7 29.1 3.3

35.7 3 20.2 8.1

37.1 3.8 21.3 8.3

38.9 5.1 23 8.4

35.8 4.7 20.5 7.7

38.4 5.4 21.8 8.1

41.6 6.9 23.9 8.7

26.7 241.9 26.2 22.2

28.6 239.4 24.2 21.7

30.4 236.5 22 21.3

Table 12.4 Number of hours of each year when the internal operative temperature falls in the three ranges (TOP , 20 C, 20 C , TOP . 26 C, TOP . 26 C) for Miami, Damascus, Izmir, and Yakutsk. Temperature ranges

Number of hours Miami

TOP , 20 C 20 C , TOP . 26 C TOP . 26 C

Damascus

Izmir

Yakutsk

2020

2050

2080

2020

2050

2080

2020

2050

2080

2020

2050

2080

183 3360 5217

96 2693 5971

35 1787 6938

4357 1306 3097

4161 1305 3294

3643 1462 3655

4553 1287 2920

4218 1347 3195

3809 1412 3539

7548 1194 18

7132 1320 308

6727 1183 850

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Figure 12.6 Percentage of hours of each year (8760 h) when the internal operative temperature falls in the three ranges (TOP , 20 C, 20 C , TOP . 26 C, TOP . 26 C) for Miami, Damascus, Izmir, and Yakutsk. Please refer the online version to view the color image of the figure.

In Yakutsk, the number of hours when the temperature is below 20 C clearly prevails over the years. Among the selected cities, Yakutsk has the highest number of hours during which it is necessary to turn on the heating system (TOP is below 20 C), although this number has decreased slightly over the years, the number of hours in which the cooling system must be turned on increases, while the number of hours of comfort remains mostly constant over the years.

12.4

Conclusion

Climate change is leading to new challenges, especially in the construction sector, which is considered one of the most energy-intensive sectors. This study aims to highlight the performance of the same building located in different climates, under climate change considering the years 2020, 2050, and 2080.

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The locations chosen for the analysis are Miami, Damascus, Izmir, and Yakutsk, falling within the locations defined by the international Ko¨ppen-Geiger climate classification as tropical, arid, temperate, and continental. The building analyzed is a newly constructed residential apartment. The prototype model is kept the same to decrease the variables of the problem. The objective is not to find an optimal building per location, but to investigate how the operative temperature inside the building varies with changing climatic conditions. The analysis was performed by plotting the operative temperature on an annual and hourly basis for each location and for each time range. The calculation was performed in a free-floating regime, focusing on the building envelope as it asserts that a building with an optimal envelope will need significantly less demand for air-conditioning systems. The results show a clear increase in temperatures and therefore a need to implement cooling systems, even where they are not required today. Over the years, comfort conditions only increase in Damascus. In Miami, the number of hours when it is necessary to turn on a heating system decreases even more. In Yakutsk in 2080 a number of hours in which cooling needs to be turned on also emerge. Izmir sees an increase in the number of hours when it is necessary to turn on a cooling system. This study confirms that climate change will have an even greater impact on building heating and cooling requirements. Therefore a prior assessment of the future climate in the design and retrofit phases is essential. This phase cannot be ignored if the energy requirements of buildings are to be reduced over the years and thus ensure the resilience of buildings to climate change by reducing consumption and CO2 emissions, and higher operating costs. Given these assumptions, designing resilient buildings today means predicting at the design stage the possible influence of climate change to enable the building to provide indoor comfort conditions.

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Climate-responsive architectural and urban design strategies for adapting to extreme hot events

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Sheng Liu1,2, Shi Yin2,3, Junyi Hua4 and Chao Ren2 1 School of Architecture, Southwest Jiaotong University, Chengdu, P.R. China, 2 Faculty of Architecture, The University of Hong Kong, Hong Kong, P.R. China, 3 School of Architecture, South China University of Technology, Guangzhou, P.R. China, 4 School of International Affairs and Public Administration, Ocean University of China, Qingdao, P.R. China

13.1

Introduction

13.1.1 Climate change and extreme hot events It is widely acknowledged that human-induced climate change has various adverse influences on the ecosystem, agriculture, human health, built environment, etc. According to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) (Lynn & Peeva, 2021), there is evidence of increased intensity of extreme weather events, such as heatwaves, droughts, and tropical cyclones, during the most recent decade (2011 20). Human influence and the observed increase in anthropogenic greenhouse gas concentrations contributing to these observed extremes has strengthened since the Fifth Assessment Report (IPCC, 2010). In the near future more frequent and severe extreme climate events can make built and nature systems more vulnerable when their performance falls outside the typical range. However, if buildings and cities are better designed for the atypical or extreme conditions, humans and built environment are able to adapt to short-term as well as long-term changing conditions due to climate change. The climate-responsive design strategies for buildings and cities are required to maintain their performance under the extreme weather conditions. Among the different extreme weather conditions, extreme hot events are causing many problems for the society and built environment. For instance, higher building energy demand can be attributable to the higher ambient temperature and intense solar radiation during the heat wave days. At the same time, electricity generated by renewable energy systems are highly susceptible to the unexpected climatic variations, which might lead to blackouts across the city or the regional grid failures. To maintain the energy security during extreme hot events, it is necessary to design urban energy systems and our built environment to be more adaptive to the unexpected climatic conditions. On the other hand, it is well known that extreme hot Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00002-0 © 2023 Elsevier Ltd. All rights reserved.

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events can trigger significant health risks for vulnerable populations. For example, the extreme heat events in Chicago (1995) and western Europe (2003) exacerbate the excess death (Johnson et al., 2005). In recent years the prolonged summer with the higher temperature and humidity are observed in some subtropical cities (Huang et al., 2021). Prolonged extreme hot events are found to be significantly associated with the excess mortality risks in Hong Kong (Wang et al., 2019). Failure to address the adaptation designs of buildings and cities could lead to serious and costly consequences, including energy supply disruptions and excess death among vulnerable populations. Therefore understanding how to design our cities and buildings for adapting to extreme weather conditions, such as extreme hot events, is critical to mitigating their potential impacts on human health and energy security.

13.1.2 Necessary to use climate-responsive design strategies for adapting to extreme hot events Various design strategies used by architects and urban designers can physically intervene the built environment at different scales. Instead of arbitrarily designing the urban and buildings’ features, evidence-based design can not only inform designers with scientific solutions but also address the design issues from many other perspectives, such as the environmental impacts, economic cost, and social aspects. Architectural and urban design strategies backed by evidence about the climatic factors can create the comfortable and sustainable urban built environment for humans without compromising the other aspects. Measures for adapting buildings and cities to climate change can be generally categorized into several types: (1) urban microclimate interventions; (2) passive design measures for buildings; (3) adopting renewable energy technologies; and (4) energy saving in heating, ventilation, and air-conditioning systems (see Fig. 13.1). Among them, climate-responsive architectural and urban design measures at the early design stage are the most fundamental and effective methods (Tian et al., 2018). Proper climate-responsive designs can be only implemented by architects or urban designers at the early design stage to achieve resilient buildings and cities to extreme weather conditions. Climate-responsive architectural design strategies include, but are not limited to,

Figure 13.1 Main categories of measures for buildings and cities adapting to climate change

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the building layout design, shading devices, envelope thermophysics, fenestration and infiltration, and airtightness (Rodriguez-Ubinas et al., 2014). Climate-responsive urban design strategies include but are not limited to, urban morphology design, urban landscapes, and urban cooling materials. Understanding the cooling effects of different climate-responsive design strategies can help design professionals to find the most effective ways to make our urban built environment more adaptive to extreme hot events. Moreover, providing architect and urban designer with some feasible design solutions can help finding relevant evidence for their designs and thus bridging climatology research and design practice gaps.

13.2

Climate-responsive architectural design strategies for extreme hot events

13.2.1 Effectiveness of climate-responsive architectural design strategies in different climates The increasingly frequent extreme heat events not only cause the warmer outdoor environment but also jeopardize the health of vulnerable populations. The building envelope essentially works as a buffer zone to moderate the outdoor hazardous environment for creating comfortable indoor spaces for livability. When buildings without proper climate-responsive designs are confronting extreme hot events caused by climate change, the overheated and hazardous indoor environments may result due to the higher ambient temperature, solar heat inputs, and convective and conductive heat gains through the building envelope (Lapisa et al., 2018). In buildings with proper climate-responsive design strategies, the comfortable indoor spaces can be achieved by designing appropriate external shading devices, nocturnal crossventilation, reducing the convective and conductive heat gains through the windows and walls, etc. (Macintyre & Heaviside, 2019). In buildings with a good climateresponsive design, a comfortable and healthy indoor space can therefore considerably decrease the usage of mechanical cooling, that is, energy consumption in buildings, and the risks of heat exposure of residents. More importantly, some buildings’ lifespan is expected to be about or over 100 years due to the progress of building materials and technologies. Thus both the existing and new buildings would need to be prepared for the worsening future climatic conditions and increasingly frequent extreme hot events, which would inevitably increase future energy demands and the frequency of overheated days. To counteract the impacts of the increasingly frequent extreme hot events, various climate-responsive architectural design strategies were appraised by researchers worldwide. In the Netherlands, van Hooff et al. (2015, 2016) investigated six design measures, including thermal mass, increased thermal capacity, higher albedo of exterior surfaces, green roofs, solar shading protections, and high ventilation flow through windows, for a Dutch terraced house. They found that the application of green roof cannot significantly improve the thermal performance of studied houses.

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By contrast, the application of operable external shading panels and lowering them when the solar radiation is above some limits is significantly useful for mitigating overheating hours. Another useful measure for reducing overheating hours is providing additional natural ventilation for terraced house during the entire day. In UK dwellings, there is a need for existing buildings with low thermal performance to adapt the more frequent and severe heatwaves. Porritt et al. (2012) evaluated the effectiveness of different climate-responsive architectural design interventions for UK dwellings, such as adding insulation for external walls and lofts, replacement of existing glazing with low-e triple glazing, adding high-performance solar reflective paint for external walls, adding 1.0 m deep overhangs for windows, adding external window shutters, etc. They found that interventions relating to external wall surface, such as adding insulation or replacement of external solar reflective paint, are most effective ways to mitigate the impacts of extreme hot events. The other effective but controversial design strategies are using of shutters, blinds, curtains and adding external fixed shading devices for south-facing rooms, because they are facing some practical issues with loss of landscape view and potential use of artificial lighting. In Australia, Ren et al. (2011) investigated the effectiveness of several climate-responsive architectural design measures for residential buildings to adapt to the future warmer climate. They suggested that in the mild temperate cities, such as Melbourne and Mildura, improving building envelope performance from 5 (the most new house designs) to 7 (the likely future energy efficient houses) stars is sufficient to counteract the effects of future extreme hot events, while the building envelope improvement is not applicable for some cities, such as Darwin and Alice Springs, with cooling dominated climates. In Iran, Roshan et al. (2019) adopted Givoni’s bioclimatic charts for visualizing the climatic variations and the impacts of climate change on several climate-responsive architectural design recommendations. In the architectural design recommendations, they presented the use of solar passive heating and cooling is still an important strategy for most of cities in Iran. Also, they found that the fuel poverty in Iran can be alleviated during winter seasons. In hot summer cold winter climate region of China, Chow et al. (2013) investigated the effects of architectural retrofitting design measures for existing public buildings in the face of climate change. It was found that the most effective design measures to mitigate the effects of climate change is simply improving U-Values of the building envelope to the new local building codes. Further improvement of building envelope to higher standards is not a cost-effective way. It can be seen from the above literature review that different regions with different climates have their different preference of using climate-responsive architecture design strategies to adapt to the local extreme climates.

13.2.2 Effectiveness of climate-responsive architectural design strategies in the subtropical climate In subtropical cities with hot and humid climates, extreme hot events can cause the increased indoor overheating and needs of mechanical cooling. Free-running buildings

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could not be comfortable for the most time of the summer and then the energy demand could be significantly raised. The Building Bio-Climatic Chart (BBCC) is used by Liu et al. (2020) to quantify the significance of each bioclimatic design strategy. The freerunning simulated indoor air temperature and relative humidity from a public housing building model was used to plot the BBCC in subtropical Hong Kong, as shown in Fig. 13.2. After counting the points falling in the different design zones in BBCC from Fig. 13.2, the number of hours using different bioclimatic design strategies is compared in Fig. 13.3. Overall, the time of using solar protections and air-conditioning strategies is increased in the future climatic scenarios, while the time of using other design strategies is decreasing over time. In Hong Kong, solar protections of windows are still the most significant strategy for residential buildings in the changing climate in the 21st century. Another remarkable characteristic is that the cooling potential of night natural ventilation (0.5 m/s of air speed) decreased significantly from 1087 in Typical Meteorological Year (TMY) to 506 in RCP8.5 2090s and the ventilation with a range of 0.5 1.0 m/s is of less importance (364 and 206 hours in TMY and RCP8.5 2090 s, respectively) for occupants. This might show that nocturnal natural ventilation is not constantly effective for cooling residential buildings in the future warmer climatic conditions. On the other hand, the passive heating strategies including passive solar heating and internal heat gains is expected to be decreased considerably to a negligible level in the future extreme weather conditions. Although the other passive strategies, for example, passive solar heating and dehumidification, have a negligible significance for passive cooling, a similar decreasing trend of their effectiveness can be observed. The bioclimatic potentials of different climate-responsive design strategies in the BBCC can help the local architects to select proper design strategies combating the future changing climate.

Figure 13.2 The complete Hong Kong Building Bio-Climatic Chart under the TMY (left) and future 2090s (right) climate scenarios. Source: From Liu, S., Kwok, Y. T., Lau, K. K.-L., Ouyang, W., & Ng, E. (2020). Effectiveness of passive design strategies in responding to future climate change for residential buildings in hot and humid Hong Kong. Energy and Buildings, 228. https://doi. org/10.1016/j.enbuild.2020.110469.

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Figure 13.3 The number of hours requiring different climate-responsive design strategies over time. Source: From Liu, S., Kwok, Y. T., Lau, K. K.-L., Ouyang, W., & Ng, E. (2020). Effectiveness of passive design strategies in responding to future climate change for residential buildings in hot and humid Hong Kong. Energy and Buildings, 228. https://doi. org/10.1016/j.enbuild.2020.110469.

Figure 13.4 The value of significance (left) and relative change of significance (right) of passive design parameters for the cooling load under different future climatic scenarios in radar chars. Source: From Liu, S., Kwok, Y. T., Lau, K. K.-L., Ouyang, W., & Ng, E. (2020). Effectiveness of passive design strategies in responding to future climate change for residential buildings in hot and humid Hong Kong. Energy and Buildings, 228. https://doi. org/10.1016/j.enbuild.2020.110469.

In the same study, Liu et al. (2020) further used global sensitivity analysis to quantify the significance of each passive design parameter for building cooling load. The sensitivity coefficient of each passive design parameter under different future climate scenarios is identified and plotted in radar chart of Fig. 13.4. Their relative percentage change

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is also plotted taking the sensitivity coefficient of TMY as the reference value. The most remarkable observation is the deceasing significance of almost all design parameters over the 21st century, except for infiltration air flow coefficient for cracks (IFAC). This means that almost all passive design parameters will become relatively less significant for mitigating the energy consumption in the future compared with the TMY climate scenario. In contrast, the significance of IFAC is expected to increase by 329% for RCP8.5 in 2090s. This reveals that the importance of better airtightness for buildings which require a significantly increased amount of air-conditioning in the future warmer climates. Amongst the building design parameters evaluated, the solar heat gain coefficient (SHGC) of glazing emerges as the most significant design consideration with sensitivity coefficient, while the solar absorptance of external walls and overhangs shading projection factor appear as the second and third most important factors. However, the significance of solar protection strategies has a more dramatic decreasing trend compared to the parameters related to insulation, such as window U-value and wall U-value. In another similar study, Chen et al. (2017) quantified the effectiveness of several selected passive design parameters related to the building layout, envelope thermophysics, building geometry and infiltration and airtightness for energy savings in Hong Kong public housing buildings. The most influential strategies for energy use of buildings are reducing solar heat gain coefficient of glazing, using smaller window to ground ratio, and increasing overhang shading projection for windows, whereas the window U-value has a nonlinear effect on the building energy performance. Another study in subtropical Taiwan, Huang and Hwang (2016) explored the energy saving effects for five passive design strategies, including achievable envelope design, reducing U-value and SHGC of glazing, reducing U-value of external walls and roof, adding external shading device. They pointed out the combination of improving walls’ insulation, adding external shading, and reducing SHGC of glazing, can significantly decrease the cooling load in the warming weather conditions in hot and humid Taiwan.

13.2.3 Shading and ventilation design strategies for buildings in subtropical high-density cities Apart from consideration of effectiveness of each climate-responsive design strategies, the urban context for each building in subtropical high-density cities is important for selecting proper design strategies. For instance, external shading devices have been proven to be one of simplest and most efficient passive strategies in subtropical residential buildings (Liu et al., 2020); however, they are not applicable for every residential building under the high-density urban forms. If residential buildings are located in the compact urban forms, such as the terraced houses (see Fig. 13.5), where the daytime solar radiation can be mainly blocked by the surrounding buildings, shading panels attached on the windows and the smaller windows sizes which are originally designed for the daytime shading could be detrimental for the nocturnal ventilation. Therefore if most of fac¸ades can be shaded by the surrounding buildings during the daytime, the operable windows with a bigger area which can improve the

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Figure 13.5 The irradiated solar radiation of each fac¸ade during summer time in Hong Kong compact urban residential forms.

nocturnal ventilation should be encouraged to be implemented in buildings under such high-density urban forms. By contrast, the stand-alone buildings or the high-rise tower buildings with less shading effects from surrounding buildings should be cautious about the window-to-wall ratio and the window areas. When we change the window-to-wall ratio of buildings, there is a trade-off between cooling effects of nocturnal ventilation and solar heat gains through windows. This means that the sophisticated design of external shading devices and windows can not only help to avoid the heat gains through the transparent fac¸ades, but also improve the efficiency of nocturnal ventilation. In the complex high-density built environments, solely using one single advanced solution, such as using the high-performance glazing materials (Fang et al., 2015) or cooling walls (He & Hoyano, 2011), could not be a cost-effective solution. Another limitation of using external shadings or low-e windows is sacrificing the indoor visual comfort. For this reason, chromogenic glazing, characterized by the property of variable transmittance, can be easily used in building fac¸ades to reduce the energy consumption and increase the visual comfort for occupants. The integrated design of buildings’ different components and consideration of urban contexts might be more critical for the design of high-performance buildings under the high-density urban forms. In addition to solar radiation, the effects of high-density urban morphology on wind speeds around buildings should be not be ignored for assessing building thermal or energy performance, especially under the extreme weather conditions. Regarding to urban design strategies, creating “urban ventilation corridors” throughout the cities can removal the anthropocentric heat in the city center areas, which can be beneficial to urban microclimate, that is, lower temperatures and elevated air speed, and to cool the buildings (Ren et al., 2018). In recent years, many Chinese cities have adopted this strategy at the early planning stage to analyze the wind characteristics of different planning scenarios (Ng & Ren, 2018). He et al. (2019) further adopted “precinct ventilation zones” classification approach which assesses the urban ventilation performance of urban forms based on urban compactness, street structure, building morphology, etc., to enhance the ventilation performance-based planning. In high-density Hong Kong, an air

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ventilation assessment (AVA) system (Ng, 2009) was established to facilitate sustainable urban planning and building designs through creating air paths in high-density urban areas, proposing the proper street orientations and building permeability. These implementations of sustainable urban design approaches in high-density cities can not only contribute to the pedestrian-level ventilation and thermal comfort, but also create cooling potentials for improving the overall building thermal performance. The detailed elaboration of urban morphology and ventilation design will be discussed in Section 15.3.2. Although the air-conditioning is now widely used in residential buildings in subtropical cities, utilizing the outdoor natural ventilation and lower temperatures during the nighttime is still an efficient and commonly used way to cooling the indoor space. But when the elevated ambient temperature due to the exacerbated extreme hot events during the nighttime exceeds the upper limits of indoor thermal comfort, the use of natural ventilation through opening windows could be a counter-productive strategy for indoor thermal comfort. Therefore the frequency and severity of extreme heat events cannot be ignored when the nocturnal ventilation is used as a potential mitigation strategy to the high temperatures.

13.3

Urban adaptive design strategies in responding to extreme hot events

In urban level, the process of urbanization changes the underlying surface type and has an important influence on local temperature. The phenomenon of urban heat island (UHI) might increase the temperature of cities up to 10 C accompanying with global climate change. Especially under the extreme heat events, the outdoor thermal environment might jeopardize the health of residents and raising the energy consumption in a further step. As interpreted by Oke (1988), the urban thermal environment is featured by the characteristics of urban morphological elements, including surface material, geometry layout, and landscapes. Adopting proper design strategies for these elements demonstrate potentials on mitigating the thermal stress in urban areas. This section summarizes the effective design strategies and corresponding mitigation capacity of material, geometry, and landscapes from state-of-art studies as scientific supports for design practitioners.

13.3.1 Effectiveness of cooling materials for mitigating urban heat island Materials used in the building and urban fabric, including roofs, facades, and pavements, affect the urban thermal balance which highly relate to the performance of outdoor thermal environment. Especially, the opaque urban surfaces can significantly absorb incident solar radiation, emit thermal radiation, and transfer heat via convective and conductive processes with the atmospheric air simultaneously. Therefore the UHI can be mitigated by maintaining the surface temperature in low level and reducing the sensible heat release.

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The concept of “cool surfaces,” referring to the surfaces with reflective materials and coatings that reflect the solar energy radiation, is emerged as a viable solution for responding urban overheating. The thermal performance of a material is mainly evaluated by the albedo (solar radiation) and emissivity (long-wave radiation). The solar reflectance potential of cool materials initially relied on their whiteness, which promoted the use of white paints and light-colored aggregates. The cooling capacity of replacing surface materials to high albedo is profoundly proven. In Canada, increasing surface albedo from 0.2 to 0.45 can achieve a reduction of 1 C 2 C in air temperature, a decrease of 0.2 0.5 C in dew point temperature, and a slight increase up to 0.4 m/s in near-surface wind speed (Jandaghian & Akbari, 2021). Santamouris and Yun (2020) reviewed the recent innovative mitigation materials, including light color reflective coatings, retro-reflective materials, thermochromic materials, fluorescent materials and so on. Despite the beneficial effect on air temperature, increase of inter-reflections in an urban street canyon leading to a higher mean radiant temperature for pedestrians and damaging the human thermal comfort. As suggested by Salvati et al. (2022), reducing the reflectivity of the bottom part of fac¸ade and pavement zone for pedestrian can demonstrate a positive impact on both outdoor thermal comfort and UHI mitigation. Therefore employing cooling materials and designing the suitable area of application are critical strategies for enhancing urban thermal environment.

13.3.2 Urban geometry design for ventilation and shading The characters of urban geometry closely relate with urban ventilation and shading performance, which are essential for thermal environment in urban area. On one hand, the natural ventilation can motivate cool and fresh air moving in urban area. The wind over human bodies increases heat lost and reduces heat stress significantly, especially in the hot and humid urban condition. On the other hand, shadings for pedestrians prevent the incident solar radiation damaging human thermal comfort and overheating urban surface. Except the ambient air temperature, the radiant heat determinate human thermal sensation which relate with human health closely. Organizing the configurations and profiles of urban geometry in a proper way demonstrate potentials on enhancing the quality of urban climate and responding on extreme heat events.

13.3.2.1 Urban geometry and ventilation The permeability of urban geometries is the key indicators for evaluating ventilating performance in built environment and can be enhanced in different spatial scale levels. In regional and urban scale, developing urban ventilation corridors is the most effective strategy to improve wind environment in the whole urban area. As firstly defined in the German national guideline “Environmental meteorology climate and air pollution maps for cities and regions (VDI 3787-Part 1),” the ventilation corridor is the “Area for the mass transport of air near the ground which is preferred owing to direction, nature of the surface and width. Air-directing tracks, also termed ventilation or aeration tracks

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are intended to facilitate horizontal air exchange processes by means of low roughness (no high buildings, only individual trees), an alignment which is as far as possible rectilinear or only slightly curved, and a relatively large width (as far as possible more than 50 m)” (VDI, 2015)., the open space, such as road network, river channels, parks, greenery areas, and built-up areas, with low development intensity but high permeability in urban space are predominant elements for creating ventilation corridors (Fig. 13.6). Nowadays, many nations, such as Japan and China, have published their own technical standard for guiding the integration of ventilation corridors in the planning and design. Ren et al. (2018) summarized the workflows and methods applied in

Figure 13.6 Schematic design on urban ventilation corridors at different spatial scale level, (A) on regional level, (B) on city level, (C) on district level, and (D) on building level. Source: From Ren, C., Yang, R., Cheng, C., Xing, P., Fang, X., Zhang, S., Wang, H., Shi, Y., Zhang, X., Kwok, Y. T., & Ng, E. (2018). Creating breathing cities by adopting urban ventilation assessment and wind corridor plan—The implementation in Chinese cities. Journal of Wind Engineering and Industrial Aerodynamics, 182, 170 188. https://doi.org/ 10.1016/j.jweia.2018.09.023.

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proposing urban ventilation corridors plan and corresponding control measures as below: (1) collect historical meteorological data and analysis wind condition; (2) conduct mesoscale numerical modeling, local wind circulation system, and ventilation volume calculation; (3) classify potential wind dynamics, UHI intensity, and cool fresh air sources; and (4) finally, detect and visualize major and secondary urban ventilation corridors.

In site and building level, increasing the porosity of building clusters or building volumes benefits on pedestrian thermal comfort and energy efficiency. For achieving better urban living, the AVA System was officially proposed by Hong Kong government in 2006 as technical guide for improving permeability in the early phases of design. As show in Fig. 13.7, in total 10 qualitative urban design guidelines were provided for practitioners and project developers, including: creating breezeway or air path, aligning main street in parallel to prevailing wind, linking open spaces, avoiding blockage of sea/land breezes and prevailing wind, introducing nonbuilding areas, improving the building height variation, adopting terraced podium design in large development sites, providing wide gaps between building blocks, removing obstructions, etc.

Figure 13.7 Yes no design strategies for enhancing permeability in site and building levels. Source: Modified from Ng, E. (2009). Policies and technical guidelines for urban planning of high-density cities—Air ventilation assessment (AVA) of Hong Kong. Building and Environment, 44 (7), 1478 1488. https://doi.org/10.1016/j.buildenv.2008.06.013.

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13.3.2.2 Urban geometry and shading Shading is an indispensable strategy to reduce human exposure to solar radiation in outdoor environment. Except shading by tree canopy, varying the street canyon height width ratio, adding open-semi arcade for pedestrian, and adjusting orientation of canyon axis are effective shading strategies of urban geometry. From a geometrical perspective, shadings mainly moderate thermal environments by adjusting the level of exposure to the sky, which can be evaluated using the sky view factor (SVF) to demonstrate the situation of a point from completely obscured to open to the sky. The negative correlation between the SVF and human thermal comfort has been extensively verified (Ahmadi Venhari et al., 2019; Chatzipoulka et al., 2016). Additionally, the axis orientation of the canyon determines solar access to the canyon and effects on the cooling efficiency of shading facilities. Some researchers have reported that pedestrian thermal comfort is much worse in east-to-west oriented streets than that in north-to-south oriented streets, and it is difficult to improve by increasing canyon height width ratio. Yin et al. (2022) compared the cooling performance among different shading facilities in a subtropical city by numerical simulations (Fig. 13.8). The physiologically equivalent temperature (PET) was employed for assessing human thermal comfort. The SVF reduced significantly with increasing the canyon height width ratio in all street canyons. The SVF in arcades and boulevards is was 0.1 to 0.3 lower than that in the street without special shading facilities (AL) at the same canyon height width ratio. The cumulative PET load at an observing point (cPETL) in the street with arcades and trees were much lower than that in AL. The peak value of cPETL was 166.10 C in AL with CHW 5 1 and SVF 5 0.45, while, the maxima cPETL in the street with shading facilities were less than 140 C. However, both the max PET and cPETL demonstrated a huge difference in the canyon with same SVF, which implied the impact from varying orientation of streets. Therefore combining different shading strategies in the process of urban design properly is necessary to achieve a comfortable thermal environment.

13.3.3 Urban greenery design for cooling city At the city level, greenery contributes to cooling urban environments. The cooling effect of urban greenery has been widely acknowledged, and therefore greenery has been applied as an effective strategy to respond to the increasing extreme heat events in urban areas intensified by the UHI effect. At the micro scale, there are three cooling mechanisms: evapotranspiration, shade provision, and increased albedo (Wong et al., 2021), and they are often combined to elevate the cooling effect. Plants, particularly trees, block a large proportion of short-wave and long-wave solar radiation. According to previous reviews (Lai et al., 2019; Wong et al., 2021), only 10% 30% of solar radiation can shine through tree canopies. The mechanism helps buildings and ground surfaces absorb less heat and therefore reduce air temperature and surface temperature. Reduced temperature and solar radiation improve people’s thermal comforts. Vegetation consumes solar energy through evapotranspiration by transferring sensible

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Figure 13.8 Scatter matrix among canyon height width ratio, sky view factor, maximum physiologically equivalent temperature, and cumulative physiologically equivalent temperature load at an observing point of all simulated street canyon cases/ Source: From Yin, S., Wang, F., Xiao, Y., & Xue, S. (2022). Comparing cooling efficiency of shading strategies for pedestrian thermal comfort in street canyons of traditional shophouse neighbourhoods in Guangzhou, China. Urban Climate, 43, 101165. https://doi.org/ 10.1016/j.uclim.2022.101165.

heat to latent heat and hence reduces surrounding air temperature. Greenery can also function by increasing albedo on impervious surfaces to lower the heat absorbed by buildings or ground surfaces. While at the mesoscale, as suggested by Gunawardena et al. (2017), canopies of green spaces increase surface roughness that further increase convective heat dissipation for boundary layer cooling. Urban greenery in different types work in different scenes at different scales for cooling. Main types of urban greenery include urban parks, street trees, and greenery on buildings. Urban greenery can not only cool a specific location at a micro scale but also contribute to mitigate the UHI effect at a meso or macro scale for a whole urban area. According to the review by Wong et al. (2021), at a micro scale, urban green spaces reduce air temperature by 2 C 4 C and reduce remotely-sensed

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land surface temperature (LST) by 1.9 C 6.7 C and reduce field-measurement LST by 9.2 C 19 C. Such previous findings show that green spaces substantially cool urban environments, but the cooling effect greatly varies with their configurations and compositions, and distance decay of cooling effect outside green spaces is enhanced by ventilation. Street trees as another main system form a large component of greenery in cities. Tree patterns influence the cooling effect with interactions with the impervious surface coverage. Daytime tree-height air temperature can be reduced by 4 C, and the effect extending to higher level further contributes to urban heat island mitigation. In addition to greenery on ground, vegetation can also be arranged on building surfaces for indoor cooling and therefore energy saving. Due to the three cooling mechanisms, vegetation reduces indoor temperature through thermal insulation, and similar to green spaces and street trees, the cooling effect depends on climate and design. Green roofs and green walls are main types of greenery on buildings. Peak surface temperature can be reduced by about 17 C (Wong et al., 2021). Design strategies of urban greenery design depend on a series of factors including climate, scale, greenery mode, configuration, and plant. It is clear that greenery’s cooling capacity is strongest in summers and the daytime, and the capacity is clear in different climatic regions. Previous research has demonstrated vegetation’s effect at the city (meso) scale to mitigate urban heat island intensity and at the site (micro) scale to reduce temperature and improve thermal comfort. Compared to rural areas, urban areas are more compact, and there has been limit space for greenery. Hence, scientific design strategies are necessary to not only create new green spaces on either ground or buildings but also optimize the current ones. Norton et al. (2015) presented a framework to implement greenery (green infrastructure) to mitigate thermal conditions from a trans-scale perspective. As shown in Fig. 13.9, the five-step workflow is comprised a neighborhood-scale process to optimize existing urban green infrastructure in identified areas based on various factors including thermal exposure, urban morphology, greenery, and even social conditions, and follow-up implementation of new greenery based on street canyon geometry and orientation, site features, and cooling potential of greenery systems. At the site scale, green parks, street trees, and greenery on buildings have specific design strategies, and scenario simulation based on response variables and characteristics and design of greenery systems can be an initial step of greenery design (Liu et al., 2021). Regarding park size, too large or too small parks may not be efficient in cooling. One-hectare large parks regularly shaped can be scattered in cities with spacing below 1 km to better cool spaces inside and among the parks, and large-canopy trees should be arranged with understory shrubs and grass to increase the cooling effect. Urban morphology should also be considered into tree design. Trees are highly needed in areas that are featured with low SVF (Tan et al., 2017) and tree species, tree height, tree crown, and tree interval are all important factors of the cooling effect (Rahman et al., 2020). Different types of vertical and rooftop greenery on buildings, such as green fac¸ade, modular green wall, extensive green roof, and intensive green roof, have different cooling effects and design principles (Seyam, 2019). Overall, integration of various types of greenery on ground

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Figure 13.9 The steps in the prioritization operate at the neighborhood scale (Steps 1 3), where the physical environment and people’s vulnerability are characterized for the area; and the street (Step 4) and microscales (Step 5), at which scales urban green infrastructure that is fit for place is selected and implemented. Source: From Norton, B. A., Coutts, A. M., Livesley, S. J., Harris, R. J., Hunter, A. M., & Williams, N. S. (2015). Planning for cooler cities: A framework to prioritise green infrastructure to mitigate high temperatures in urban landscapes. Landscape and Urban Planning, 134, 127 138. https://doi.org/10.1016/j.landurbplan.2014.10.018.

and buildings can help reach a higher cooling effect. All factors related to greenery systems and their cooling effects mentioned in this section should be considered in simulation of heat mitigation with built environments at either micro or mesoscale.

13.4

Conclusion

When buildings and cities are confronted with the worsening extreme weather conditions caused by climate change, climate-responsive strategies for architectural and urban designs have been proved to be effective for maximizing the indoor and outdoor thermal comfort and reducing hazards for humans. This study has reviewed the climate-responsive design strategies for adapting to the extreme hot events from the perspectives of architectural and urban designs, especially in subtropical cities. It should be noted that the impacts of extreme weather conditions caused by climate change on the effectiveness of different climate-responsive design strategies are not trivial issues for architectural and urban designs. Understanding the cooling effects of different climate-responsive design strategies can help architects and urban planners to find the most effective ways to adapt to extreme hot events. Failure to address the climate-responsive designs of buildings and cities for extreme weather adaptations could lead to serious and costly consequences of human health and energy security. In the future, compound extreme events, such as the compound extreme hot and humid events, are becoming more frequent and severe in

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subtropical cities. Providing evidence-based design solutions for design professionals is critical to mitigating their potential impacts on built environment and human society.

Acknowledgments This work has been supported by the Seed Fund for Basic Research of the University of Hong Kong (Project title: Investigating subjectively perceived accessibility of urban green spaces in a high-density city and the effect of urban density; 202011159063). Supports were also received from the Hong Kong Scholars Program and Fellowship of China Postdoctoral Science Foundation (No. 2020M672633).

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Resilience of green roofs to climate change

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Cristina S.C. Calheiros1,2 and Sofia I.A. Pereira3 1 Interdisciplinary Centre of Marine and Environmental Research (CIIMAR/CIMAR), University of Porto, Novo Edifı´cio do Terminal de Cruzeiros do Porto de Leixo˜es, Matosinhos, Portugal, 2Institute of Science and Environment, University of St. Joseph, Macao, P.R. China, 3Universidade Cato´lica Portuguesa, CBQF - Centro de Biotecnologia e Quı´mica Fina Laborato´rio Associado, Escola Superior de Biotecnologia, Porto, Portugal

14.1

Introduction

14.1.1 Built environment and urban transition Built environment is the baseline infrastructure of cities that comprises land-use, specifically buildings, transportation, and roadways. The global share of energyrelated CO2 emissions from buildings and construction in 2020, compared to other sectors, stands at 37% and the global final energy consumption stands at 36% (United Nations, 2021). It is thus important to have in consideration the design, planning, and development of the built environment, especially the building envelop, since it can contribute to the mitigation of climate change, support adaption and promote environment and public health, toward sustainable cities. This approach determines the patterns of exposure, social and physical vulnerability, and capacity for resilience. For example, the interventions in the morphology of a city-built environment can contribute to the reduction of the urban heat island effect and minimize the impact of heat waves (IPCC, 2022). At the level of the buildings, there is a great need to implement effective low-carbon policies and decarbonization through costeffective investments having in consideration the life span and considering the issue of resilience. This latter issue, concerning resilience, is of outmost importance since a building of today will still be in use in 2070, although facing significant differences in climate (United Nations, 2021). Cities should pave the way to consider programs providing retrofitting, disaster reconstruction and urban regeneration, following a strategic direction toward low-carbon and high-resilience urban form and function, to counteract the costs for maintenance and reconstruction of urban infrastructure that are predicted to increase with global warming (IPCC, 2022). In the context of global development urban settlements are of great importance since they will further urbanize over the next decade, from 56% today to 60% by 2030 (United Nations, 2020). They contribute with about 85% of global GDP (gross domestic product), but on the other hand they (1) consume about 70% of global Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00008-1 © 2023 Elsevier Ltd. All rights reserved.

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resources and 70% of all energy generated, (2) generate about 50% of all waste, and (3) emit 70% of all greenhouse gases (European Investment Bank, 2021). Unplanned and unmanaged urbanization pose a threat to sustainable development being does fulcra well-planned territories that can curb excessive land consumption and all that is implied, toward sustainable urbanization that is a generator of inclusive prosperity. This highlights the relevance to consider the environment footprint to accommodate growing populations (United Nations, 2020). Thus the successful management of cities growth will rely in part on how to maximize the benefits for the settlement while minimizing the environmental degradation and other potential adverse impacts (United Nations, 2019). Having that in consideration it is stated that an environmental transition is needed underpinning by a circular economy approach where not only resources conservation is attained but also the reduction of environmental and climate impacts (European Investment Bank, 2021). Cities have unique features that allow them to be cradles and catalysts for circular change, since they (European Investment Bank, 2021): (1) (2) (3) (4) (5) (6)

have density and scale of citizens, business, materials and resource flows, can connect stakeholders and promote a culture of collaboration, can lead by example offer/procure circular solutions/services, have autonomy to regulate/incentivize, can define and communicate circular vision and strategy, and can embed circular principles in city infrastructure and services.

Considering the Proposal for the European Partnership Driving Urban Transitions four priority themes have been identified as crucial to support urban transition (JPI Urban Europe, 2020): (1) digital transitions and urban governance, (2) from resilience to urban robustness, (3) sustainable land-use and urban infrastructure, and (4) inclusive public spaces. Following this alignment, it is crucial to consider the Green-Blue Infrastructures and nature-based solutions (NBS) toward urban transitioning (JPI Urban Europe, 2020).

14.1.2 Nature-based solutions toward circular cities The inclusion of NBS in the urban landscape can contribute to a circular economy, to different extents, and through the provision of ecosystem services can counteract the impact of climate change and urbanization (Calheiros & Stefanakis, 2021; Pearlmutter et al., 2020). According to the European Commission (European Commission, Directorate-General for Research and Innovation et al., 2020, p. 4), “Nature-based Solutions to societal challenges are solutions that are inspired and supported by nature, which are cost-effective, simultaneously provide environmental, social and economic benefits and help build resilience. Such solutions bring more, and more diverse, nature and natural features and processes into cities, landscapes and seascapes, through locally adapted, resource-efficient and systemic interventions. Nature-based solutions must benefit biodiversity and support the delivery of a range of ecosystem services.” Embedding the concept of circular cities, the COST Action CA17133 Circular City has proposed that “NBS are defined as

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concepts that bring nature into cities and those that are derived from nature. NBS address societal challenges and enable resource recovery, climate mitigation and adaptation challenges, human well-being, ecosystem restoration and/or improved biodiversity status, within the urban ecosystems. As such, within this definition we achieve resource recovery using organisms (e.g., microbes, algae, plants, insects, and worms) as the principal agents. However, physical and chemical processes can be included for recovery of resources (as discussed in WG3 Resource Recovery), as they may be needed for supporting and enhancing the performance of NBS” (Langergraber et al., 2020). Stefanakis et al. (2021) further discussed the potential of NBS to stimulate economic growth through a circular model, their contribution to new circular strategies for climate change adaptation and mitigation, and key actions necessary to increase the awareness and attract more investments for their implementation. To shift to circular management of resources the following urban circularity challenges can be addressed with NBS (Atanasova et al., 2021): (1) restoring and maintaining the water cycle (by rainwater management), (2) water and waste treatment, recovery and reuse, (3) nutrient recovery and reuse, (4) material recovery and reuse, (5) food and biomass production, (6) energy efficiency and recovery, and (7) building system recovery. According to Katsou et al. (2020) the success for adoption and implementation of NBS in circular cities require four main steps: (1) planning, (2) design, (3) assessment, and (4) communication. Besides that, implementation of NBS may be considered at the scale of green building: (1) materials that are nature-based materials (raw or processed) used in the construction of the bulti environment, (2) systems that are systems for the greening of buildings, and (3) sites that are considered the open spaces directly adjacent to buildings for nature establishment, playing a role in the blue-green network of the city, intending to promote outdoor comfort, healthy living environments, and well-being. Green roofs are an example of NBS that can be implemented at a building scale, in new or existing buildings, coping with the societal challenge of “Climate action, environment, resource efficiency and raw materials,” identified by European Union. They thus play a pivotal role in the Water-Energy-Materials-Food-Ecosystem nexus (Calheiros & Stefanakis, 2021). The present chapter aims at giving an overview on the role of green roofs as NBS toward climate change resilience, highlighting the provision of ecosystem services and the mitigation and adaptation capacity.

14.2

Green roof as engineered system

The space in the top of the buildings in urban context is generally unused, although is a considerable area extension since accounts for approximately 40% 50% of the impermeable urban surface (Stovin, 2010). The inclusion of green roofs in new buildings or retrofitting the existent ones, is a solution that contributes to cities resilience and adaptation to climate change to different extents.

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Green roofs are systems that use vegetation as top layer and are installed on a constructed structure regardless the type of construction, meaning that they can be implemented on a top of a building or at the ground level, for example covering an underground parking, being excluded green walls built with climbing plants or vertical gardens systems. Typically, they are arranged in several layers that play different functions to assure effective performance. Modern green roofs are thus engineered systems that follow standard guidelines to assure the compliance with the best practices and avoid malfunctioning (Calheiros et al., 2022).

14.2.1 Green roof classification Green roofs are classified as extensive, semiintensive and intensive (ANCV, 2019). The differentiation relies mainly on the substrate depth and type of vegetation, and the maintenance associated (Table 14.1). Briefly, extensive roofs are characterized by having low growing vegetation that can go from grass varieties to meadows and sedum (Fig. 14.1A). The substrate is thus adequate for the growing need of such plants with low thickness. This category is not adequate for frequent stepping. Only periodic maintenance is needed, mostly to verify the drain pipes, inspection pit and overall aspect. It can be considered four annual visits after the installation period (source: https://www.greenroofs.pt/en/faq, assessed May 21, 2022). Compared to the other green roofs a minimal capital and maintenance cost is associated (ANCV, 2019). Intensive roofs are characterized by Table 14.1 Green roofs typical classification and characteristics. Characteristics

Maintenance

Substrate layer

Vegetation Weight of the system Accessibility

Green roofs classification Extensive

Semiintensive

Intensive

After installation of the vegetation the maintenance is low Typically, mineral substrate and porous. 8 15 cm thickness

Periodic/moderate

High maintenance

Mineral substrate. 15 25 cm thickness

Different substrates may be used according to the type of plants. Thickness .25 cm Trees, shrubs, lawn .350 kg/m2 (3.43 KN/m2 ) In general, without limitation

Succulent (sedum), mosses, grass 80 180 kg/m2 (0.59 1.77 kN/m2 ) Unless for maintenance

Grass-herbs, shrubs 150 350 kg/m2 (1.47 3.43 kN/m2 ) Limited stepping

Source: Adapted from ANCV. (2019). Coberturas Verdes: Guia Te´cnico para projeto, construc¸a˜o e manutenc¸a˜o. ANCV-Associac¸a˜o Nacional de Coberturas Verdes. ISBN: 978 989 33 0039 8 (in Portuguese).

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Figure 14.1 (A) Left side: extensive green roof and (B) right side: intensive green roof (Porto, Portugal).

having different levels of vegetation, meaning that can include for instance trees, shrubs, and other ornamental plants (Fig. 14.1B). The substrate topographically is variable, with a greater weight than the extensive, having in consideration the substrate thickness and plants. This category is conceived for frequent stepping and use. Maintenance is adapted to plant requirement, but similar to a garden. Higher implementation capital and maintenance costs need to be attained. Semiintensive green roofs may have plants that can go from small plants and shrubs to grass, with a moderate substrate thickness, being partially accessible. As seen, maintenance is applied to all categories but at least once a year the green roofs should be checked concerning: (1) drainage: verify if there is any obstruction in the drain pipes and inspection pit, (2) invasive plants: removal of invasive plants is recommended that may jeopardize drainage or supporting structure, tending to became dominant, (3) fertilization: depending on the species there may be requirement of fertilization or organic matter addition, and (4) irrigation system: must be adequately programed of the climacteric conditions and plants species watering needs, being kept to minimum (source: https://www.greenroofs.pt/en/faq, assessed May 21, 2022). Beside the above-mentioned categories, there are other typologies available in the market, with different designs, with specific purposes, such, biosolar roofs, agrisolar roofs, productive/farm roofs, biodiverse roofs and blue-green roofs. Briefly, biosolar green roofs combine green roofs with photovoltaic (PV) panels delivering renewable energy. Plants increase the efficiency of the PV panels at the same time that provide other ecosystem services (Chemisana & Lamnatou, 2014; Nash et al., 2015). Agrisolar roofs or agrivoltaics are a general term for combination between agriculture and PVs, delivering both benefits at the level energy and food production (Fraunhofer, 2020). Food production on roof tops as a way to do urban agriculture and access local products is gaining interest (Harada & Whitlow, 2020) (Fig. 14.2).

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Figure 14.2 Food production in a city green roof (Rotterdam, Netherland).

Biodiverse roofs are designed to promote diversity at the level of the building envelop but also in the surroundings (Ko¨hler & Ksiazek-Mikenas, 2018). Bluegreen roofs combine vegetation and elements of stormwater management in the roof structure (Busker et al., 2022). Independently of the design and purpose of the green roof implementation it is important that follows standard guidelines. In general, they may not be mandatory but the recommendations, knowledge, and expertise embed allow for a successful implementation (Calheiros et al., 2022).

14.2.2 Green roof layers Depending on the systems design, a green roof can comprise different layers. The selection of these layers is fulcra to achieve the best performance, cost-effective solution and in use of ecofriendly materials (Calheiros & Stefanakis, 2021). In relation to materials, they should be locally available, recycled or compatible with biological cycles having in consideration their durability, structural integrity, and energy dependence (Pearlmutter et al., 2020). Briefly, these are the main layers that constitute a green roof, although it may vary according to the design and purpose of implementation and use, from top to bottom: (1) Vegetation: this layer is the interface of the green roof being thus a visible indicator of the health status of the system. Selection of plants should be careful undertaken and considering the climacteric conditions, substrate thickness and irrigation requirements. They

Resilience of green roofs to climate change

(2)

(3)

(4) (5)

(6)

279

can be also chosen based on their function, such as biodiversity promotion, engaging pollinators, productive, or fully covered green carpet benefiting other ecosystem services. Irrigation system: should be always considered even if kept to a minimum use. Usually, a drop-by-drop system is adequate for most of the green roofs. It will be more valuable at the installation phase to assure plant establishment. Tap water is usually considered for this purpose. Technical substrate: except some specific situations that may use soil applied to green roofs, the technical substrate is by far the most used approach to support successful plant development and allow for a favorable system hydrodynamics. Filter layer: main function is to prevent fine substrate to pass on to drainage layer in order to avoid blockage and system saturation. Usually is geotextile based. Drainage layer: main purpose is to assure an effective water flow preventing substrate saturation or overflow of the system. They are in general polyolefin based, although recently other materials have been put is commercialization such the Green Urban Living (Tadeu et al., 2019). Protection layer: addresses the question of protecting the green roof from mechanical pressures being usually made of extruded polystyrene.

Resilience of green roofs to climate change can be achieved through the selection of the adequate layers and materials to the situation under consideration. When having in mind to optimize and boost green roof resilience, as foster the ecosystem services, it is important that the supporting system for the vegetation is assure and aligned with the understanding of natural cycles.

14.3

Buildup green roof resilience through value

Evidence-based outcomes have shown already the wide range of ecosystem services that NBS can delivered at the level of contributing to a transition to circular economy as to climate change mitigation and adaptation (Stefanakis et al., 2021). It is considered that “Ecosystem services are the benefits people obtain from ecosystems. These include provisioning, regulating, and cultural services that directly affect people and the supporting services needed to maintain other services” (MEA —Millennium Ecosystem Assessment, 2005, p. 40). These benefits are translated in the value that green roofs bring at the level of environment, social and economic aspects. So, the resilience of green roofs to climate change is influenced by the selection of the adequate layers and materials which translates into the extension of ecosystem services delivered. The green roof values below mentioned, in the next sections, will have to consider that the green roof performance will always vary according to different locations (latitudes), local climates, green roof structure, including pant species and the physical environment. It is also important to mention that the values of green roofs have different extensions of impact, meaning that one green roof has a neglectable influence on a site scale or even city scale, but if they are replicated, their benefits will be amplified and can be thus measured and accountable. Nevertheless, one green roof will always have impact at the scale of the building envelope itself.

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To promote green roofs, and other NBS, inclusion in cities it is important to proceed with: (1) identifying barriers and overcoming it, (2) setting guidelines and standardization, (3) establishing policies, incentives, and strategies, (4) leveraging organizations delivering related services, and (5) promoting awareness, dissemination, and investment in education (Calheiros & Stefanakis, 2021).

14.3.1 Environmental value 14.3.1.1 Air quality enhancement Air pollution is typically associated to heavily urbanized areas and city centers being a major concern due to the threat that poses to health and life of the citizens, and environmental degradation. Originated from several sources, the air pollutants often present are: CO2, O3, NOx, SO2, metals, and suspended particulate matter. Green roofs can reduce air pollution does promoting a better air quality (e.g., Currie & Bass, 2008; Nguyen et al., 2022; Suszanowicz & Wiecek, 2019; Yang et al., 2008). Increasing green roof areas in cities is a way to reduce the impact of air pollution. For instance, even 10 20% of increase would already make a substantial contribution (Currie & Bass, 2008).

14.3.1.2 Carbon sequestration Carbon dioxide (CO2) is the primary greenhouse gas emitted through human activities and the increase of its emission has been related to global warming. There is thus an urgent need to capture and store it. Green roofs are considered a technology that can contribute to carbon sequestration (Getter et al., 2009; Nguyen et al., 2022; Shafique, Xue et al., 2020). It can be highlighted direct and indirect impacts of green roofs in relation to carbon sequestration. Direct impact refers to the carbon capture by plants through photosynthesis and consequently storing it in plants and roots and carbon storage in the substrate. The plant species and substrate properties (depth and composition) have a great influence on the amount of carbon stored. Indirect impact refers to the long-term effect, being green roofs good insulators, which reduces heating and cooling needs, translated in building energy consumption, and consequently leading to a reduction in fossil fuel consumption (Shafique, Xue et al., 2020).

14.3.1.3 Biodiversity promotion In cities, the intensification of urbanization tends to cause an increase of soil sealing and impermeabilization, loss of green spaces and habitat fragmentation, thus leading to biodiversity decrease, habitat loss and general environmental degradation. With green roofs conditions are created for biodiversity establishment, habitat creation and enhancement of urban ecology, allowing natural colonization of plants, birds, insects, and small animals and spots for feeding and nesting. They are also very important as enablers to promote connectivity between green spaces, as green corridor, acting as stepping stones for several species (Calheiros et al., 2022; Ko¨hler & Ksiazek-Mikenas, 2018). Besides that, they attract pollinators, supporting thus diverse pollinator communities at the urban scale (Dusza et al., 2020).

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14.3.1.4 Stormwater management The impermeabilization of surfaces in urban context brings consequences to different extents on urban water cycle. As the soil sealing increases, the stormwater infiltration area decreases and the surface runoff and the stress on existing gray infrastructure increases, often resulting in cities flooding. With the climate change, in certain areas, there is a frequency increase of precipitation events which exacerbates the pressure on infrastructures and more severe floodings occur (Berndtsson, 2010; Calheiros et al., 2022). The roofs of the buildings are the first surface to interact with rainwater, being typically directed to drainage (ca. 85%) (Pearlmutter et al., 2020). A green roof has a direct effect on stormwater runoff quantity and quality. In terms of quality, it is expected that varies according to some leaching of nutrients but also there is an enhancement of the quality through filtration and adsorption associated with the substrate and plants. Although, rainwater is generally considered as nonpolluted there may be other pollutants, for example, heavy metals and pesticides depending on the local pollution sources and prevailing winds (Berndtsson, 2010; Zhang et al., 2015). It has been suggested that the water coming from green roofs has sufficient quality for nonpotable uses in buildings, such as irrigation, flushing toilets, or pavement cleaning, regarding its physicochemical parameters, coupled with an adequate rainwater harvesting system, with first flush discharge (Monteiro et al., 2016). In terms of quantity, the green roof attenuates and delays peak runoff (time lag between the peak from a hard roof and a green roof for the same rain event) preventing. Nevertheless, different studies report a high range of quantitative performance. Green roofs retention capacity maybe affected by: (1) green roof characteristics (e.g., substrate thickness, substrate composition, type of layers and materials, vegetation cover and slope of the roof) and (2) weather conditions (e.g., rainfall intensity and duration rainfall, antecedent dry weather period, air temperature and wind conditions) (Berndtsson, 2010). The stormwater management in cities facing climate change is being looked deeply through the concept of “sponge city” approach that includes NBS with the intention to promote “an urban environment that is devoted to finding ecologically suitable alternatives to transform urban infrastructures into green infrastructures so these could capture, control and reuse precipitation in a useful, ecologically sound way” (Liu et al., 2017).

14.3.1.5 Acoustic insulation and noise reduction Activities producing noise that influence human health and well-being are considered to cause noise pollution. The limits of noise may differ from country legislation although is commonly origins are: heavily traffic roads, airports, industrial facilities, and some recreational activities (Nguyen et al., 2022). Green roofs have shown to have a positive performance in reducing the sound exposure near or inside a building. The green roof layers influence the sound absorption to different extents having impact on how the diffraction of sound waves over (parts of) roofs occurs and how the transmission of sound develops through the roof system (Renterghem, 2018).

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14.3.2 Social value 14.3.2.1 Esthetic integration Green roofs have an important esthetic landscape integration value, since results from greening a gray surface. Although is an intangible benefit, it has implications on the perception of how a green roof integrates on a building and also the acceptance by the public (Calheiros et al., 2022; Kotzen, 2018; Sutton, 2014). They soften the artificial urban landscape and provide visual relief, besides enhancing architectural designs and often create iconic landmarks in the city (Rahman & Ahmad, 2012).

14.3.2.2 Well-being and life quality Green roofs can improve the health and well-being of people. They can either be of private use or publicly available with the possibility of access to social amenities such cafe’s, bars, restaurants, and swimming pools (Kotzen, 2018). They allow for recreational activities and pleasant leisure areas (Mesim¨aki et al., 2019; Shafique et al., 2018). Furthermore, the access to green space in an hospital context increases both patients’ and staffs’ overall satisfaction. It has been shown that they contribute to reduction of emotional distress, improvement of mental health, increase of socialization and community connection, increase physical activity, decrease cardiovascular and respiratory diseases, and decrease pain management needs (O’Hara et al., 2022).

14.3.2.3 Rooftop gardens Gardening can promote social cohesion and cultural activity. When considering rooftop gardens they can improve household livelihood through enhanced income, being considered for urban food production (Khan et al., 2020; Nugent, 2000). The receptivity of rooftop gardens can be attributed to the proximity to the people’s living and working spaces, delivering social interaction, passive recreation, education, and self-achievement. Social values have been pointed out as the most important benefits of urban rooftop farming, compared with economic and environmental values (Wang & Pryor, 2019).

14.3.3 Economic value 14.3.3.1 Life span extension Roofs are subject to mechanical damage (e.g., direct stepping and dirt), direct solar radiation, and wide range of temperatures variation (suffering daily expansion and contraction of the roof materials). Having that in consideration when considering a green roof for a building it will allow for a longer lifetime than conventional roofs, because of the lessen exposure of the roof membrane. While increasing life expectancy of the building the cost of building maintenance is reduced. When compared to conventional roofs, it is expected that the green roof life span may increase up to 40 years. This aspect is of great importance when doing a life cycle assessment (Calheiros et al., 2022; Shafique et al., 2018).

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14.3.3.2 Energetic efficiency Green roofs contribute to reduction of energy consumption by reducing the roof temperature of the building, with repercussion indoors, with savings for cooling and heating demand and improvement of thermal comfort, and outdoors, leading to the reduction of the heat island effect and microclimate. With green roofs the thermal insulation on the building is thus improved providing a more balanced temperature within and having impact on reducing the carbon footprint (Mutani & Todeschi, 2020; Nguyen et al., 2022; Suszanowicz & Wiecek, 2019).

14.3.3.3 Energy production Local energy production can be enhanced through PV green roofs, thus promoting renewable electricity production. The benefits of this type of production could offset the construction cost of the green roof on the building. Nevertheless, more studies are needed to fully cover the outcomes of electricity production against different latitudes and PV panels performance (Arenandan et al., 2022; Shafique, Luo et al., 2020; Shafique, Xue et al., 2020).

14.3.3.4 Real-state valorization The roofs are often underestimated in terms of their use and versatility. By turning into green roofs there is an increment in the property value due to benefits that they can bring in terms of ecosystem services delivered, but also in becoming a usable space for instance for leisure or recreational activities (Kotzen, 2018). The values for apartments rentals tend also to be higher when having green roofs (Ichihara & Cohen, 2011). Green roofs may be considered short-term investments in terms of net returns and with low-risk investment (Bianchini & Hewage, 2012).

14.3.3.5 Business development Given the limitation of space in the cities for in-ground agriculture, the rooftop farms are not just becoming a trend but also a business. Besides that, there are already policy support and public funding from green building and green infrastructure initiatives, which underpins this business. Thriving urban agriculture contributes to food security and equity, efficient food supply chains, waste management using compostable waste and job creation (Harada & Whitlow, 2020; Nguyen et al., 2022; Walters & Midden, 2018).

14.4

How to increase green roofs’ resilience to water scarcity?

Green roofs have been installed in temperate and cold climates without need of irrigation. However, their implementation in arid and semiarid regions, as well as in the Mediterranean zone is more challenging. To increase the resilience of green

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roofs to dry climates the selection of efficient and sustainable components for its installation is extremely important. In the following sections it is summarized how the main green roofs’ components, including the vegetation and substrates may improve the resilience of green roofs undergoing dry conditions.

14.4.1 Vegetation Green roofs often face more extreme weather conditions than natural habitats on the ground. Therefore the survival and development of plants in green roofs depends on their tolerance to several abiotic factors, including solar exposure and radiation, temperature, rainfall intensity, drought, and salinity, among others. It is also important to consider the constraints associated to the substrate depth that influence the development of plant root system and water retention, as well as substrate pH, salinity, and nutrient deficiency that may affect plant survival and growth. Thus the selection of plants well adapted to the local edaphoclimatic conditions is crucial for the success of any green roof (Vijayaraghavan, 2016; Xie et al., 2018). Several authors advise the use of native species, especially because they are well adapted to the local environment and may attract native wildlife contributing to boost the biodiversity in urban areas, while they are blended into the natural landscape which is esthetically pleasant (Butler et al., 2012; Li & Yeung, 2014; Pac¸o et al., 2019). Despite the benefits, green roofs with native plant community are susceptible to colonization by invasive or exotic species, which will greatly increase the cost of maintenance if the strategy was to maintain only the original plant species (Aloisio et al., 2019; Li & Yeung, 2014). Semiarid and Mediterranean climate zones are characterized by hot and dry summers with growing occurrence of extreme events, such as heat waves and long drought periods (IPCC, 2019). Plants colonizing green roofs in that regions often experience harsh growth conditions, as such the need for irrigation is unavoidable, as plants may fail to survive (Dvorak & Volder, 2013; Razzaghmanesh et al., 2014; Savi et al., 2016). However, since water is one of most limiting natural resources in the world, its utilization in urban green areas is limited since this is often considered a low-priority use (Van Mechelen et al., 2015). Therefore it is crucial to make an adequate selection of plant species to cope with water scarcity in green roofs, by using: native plant species adapted to local climatic conditions and with physiological traits related to drought and/or heat resistance (Caneva et al., 2015; Dvorak & Volder, 2013; Gioannini et al., 2018; Pac¸o et al., 2019; Van Mechelen et al., 2014); non-native plants colonizing natural habitats with growth conditions similar to those found in green roofs, including scree slopes, limestone pavements, grasslands on nutrient poor soils or annual and perennial wildflowers from agricultural systems (Lundholm, 2006; Rayner et al., 2016; Van Mechelen et al., 2014); and polycultures or mixtures of vascular plants and mosses (Gioannini et al., 2018; Pac¸o et al., 2019).

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Succulent plants (e.g., Sedum) are generally considered the most appropriate ones to use in green roofs (Dvorak & Volder, 2013; Rayner et al., 2016; Vasl et al., 2017), as they present high tolerance to extreme drought conditions resulting from the succulence of their leaves, shallow root systems, and high water use efficiency due to physiological adaptations as the Crassulacean acid metabolism (Cascone, 2019; Farrell, Szota et al., 2013; Starry et al., 2014). Indeed, a green roof exposed to semiarid climatic conditions and colonized by Sedum sediforme showed minimal irrigation demands since plants were able to survive without irrigation for 14 months (Nektarios et al., 2014). Azen˜as et al. (2018) compared the performance of five Mediterranean species, Asteriscus maritimus L. Less., Brachypodium phenicoides (L.) Roem. Et schultes, Crithmum maritmun L., Limonium virgatum (Willd.) Fourr, Sedum sediforme (jacq.) Pau, and Sporobolus pungens (schreber), planted in experimental modules under well-watered and water-limited conditions and concluded that S. sediforme was the plant that better performed under water-limited conditions followed by B. phenicoides. Despite their good performance under drought conditions, succulents may not be the best choice for green roof installation in Mediterranean region which is characterized by hot and dry summers but also by rainy and cold winters, as they have a low water use making them not effective to reduce runoff and increase building cooling effect (Farrell, Ang et al., 2013; Li et al., 2018; Vaz Monteiro et al., 2017). Hence, there is a growing interest in exploring alternative plant species, including herbaceous, shrubs, and grasses, as well as other native species adapted to water shortage. Indeed, Du et al. (2019) recommended the use of the scrubs Correa glabra and Calytrix tetragona in green roofs experiencing hot and dry climates. It has also been reported that Cotinus coggygria and Prunus mahaleb plants have high drought and heat resistance being suitable for green roof installation in warm and dry climates. Several authors have reported the importance of using polycultures to enhance plant resilient to severe environmental stresses and consequently improve the green roofs’ performance and ecosystem services (Butler & Orians, 2011; Lundholm et al., 2010; Pac¸o et al., 2019), while contributing to increase biodiversity in urban areas. According to Lundholm et al. (2010) and Lundholm (2015), the use of mixtures of plant species improves green roofs’ ecosystem services, outperforming monocultures. Butler and Orians (2011) also reported the importance of combining Sedum sp. with and non-succulent plants to reduce the negative effects of abiotic stress on green roofs. In a study performed by Nagase and Dunnett (2010), 12 species of forbs, sedums and grasses were planted, as monocultures and as mixtures of 4 and 12 species, in extensive green roofs. Under dry conditions, it was observed a higher survival in the green roofs with mixtures of species, while sedum plants showed higher drought tolerance than forbs and grasses. In addition, Pac¸o et al. (2019) recommended a mixture of vascular plants and mosses to increase the resilience of green roofs to drought. The success of this approach stems from the high water holding capacity and drought tolerance of mosses, which allows plants to be hydrated for longer periods, improving their performance. Plants in natural ecosystems in the ground are in close connection with a variety of microbial communities that foster their development and resilience to a plethora

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of climate change-related abiotic stresses, as well as underpin biodiversity (Inbaraj, 2021; Kumar & Verma, 2018; Pereira et al., 2020). However, plant microbe interactions in newly installed green roofs are limited since substrates are usually sterilized prior to installation to prevent spontaneous weed seedlings (Fulthorpe et al., 2018). In fact, only a narrow number of studies have evaluated the plant-associated microorganisms in green roofs systems. John et al. (2014) monitored the colonization of arbuscular mycorrhizal fungi (AMF) and dark septate endophyte (DSE) in plants grown for 4 years in a green roof. All plant species were colonized by both AMF and DSE with exception of Sedum acre which roots were not colonized by AMF. More recently, Hoch et al. (2019) reported that green roofs planted with Sedum sp. or with a mixture of succulents, grasses, and wildflowers showed distinct bacterial and fungal communities, suggesting that microbial communities are closely linked to the type of vegetation. The application of commercial bioinoculants, comprising AMF and/or the plant growth-promoting bacteria (PGPB) can be a good strategy to foster microbial communities in green roofs. However, despite their importance for biological systems only a few studies have considered the use of microbial inoculants and their potential to foster the resilience of plants to abiotic stresses in green roofs. Molineux et al. (2014) showed that the addition of AMF and compost tea (a live mixture of beneficial bacteria) increased the biomass of bacterial groups in subplots with a narrower layer of substrate. Likewise, Molineux et al. (2017) observed significant improvements on plant performance and on AMF root colonization of plants single and/or mixed inoculated with a commercial AMF inocula and compost tea. On the other side, Rumble and Gange (2017) did not observe a significant improvement on plant diversity and coverage by application of microbial inoculants. Schro¨der et al. (2019) reported the effect of AMF inoculation in 11 native grassland species growing under moderate and severe drought conditions. Despite the benefits observed in AMF-inoculated plants regarding aboveground biomass (2.5 times higher than noninoculated plants), under severe drought inoculated plants shriveled on average 2 days earlier than noninoculated ones. Despite the promising results reported so far, the application of microbial inoculants in green roofs needs to be deeper analyzed. Future research should address the use of PGPB and AMF to enhance plant resilience, as well as the improvement of key ecosystem services of green roofs, particularly in areas prone to drought.

14.4.2 Substrates Unlike humid regions where precipitation occurs throughout the year, underpinning plant growth, in dry regions it is necessary to irrigate green roofs, which increase the cost of maintenance (Dvorak & Volder, 2013; Razzaghmanesh et al., 2014; Savi et al., 2016). However, several strategies can be used to maintain/increase moisture and decrease temperature in the root zone, including: (1) deeper layers of substrate (Reyes et al., 2016; Zhang et al., 2014); (2) use of substrates with higher water retention capacity; and (3) addition of water retention materials to substrates (Cao et al., 2014; Chen et al., 2018; Savi et al., 2014; Werdin et al., 2021; Young et al., 2017).

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The substrate guarantees the proper establishment and stability of plants in green roofs as it can retain water and provides nutrients and physical support to plants (Cascone, 2019). Hence, increasing the depth of substrate layer will improve moisture and reduce temperature in the roots (Chenot et al., 2017; Reyes et al., 2016). Zhang et al. (2014) evaluated the effect of different substrate depths (10, 15, and 20 cm) on survival and performance of 18 nonsucculent species in nonirrigated extensive green roofs. Plant survival increased with substrate depth during water stress period. A similar trend was observed for growth index and visual rating which were higher in plants growing in deeper substrates (20 cm). Only one species, Allium senescens, showed ability to grow in nonirrigated green roofs with the shallower substrate (10 cm). Likewise, Reyes et al. (2016) showed that substrates depths of 10 and 20 cm provide a better water content if compared to a shallower layer (5 cm), while contributing to reduce the temperature in the root zone. Despite the undeniable benefits for plants, increasing substrate depth impacts installation cost, as well as the weight charge for the building structure. Therefore the use of substrates with different compositions tailored to thrive plant development under dry conditions could be a successful alternative. Growing media usually comprise several components with different characteristics mixed at different rates (Cascone, 2019; Vijayaraghavan, 2016). Low-density inorganic materials are the main constituents of green roofs’ substrates and may include pumice, zeolite, scoria, vermiculite, expanded clay, perlite, peat, sand, coco-peat, and crushed brick, among others (Farrell et al., 2012; Ondon˜o et al., 2015; Sandoval et al., 2017). Moreover, it is important to incorporate organic constituents, such as mulch, recycled organic waste, and compost to supply nutrients to the plants and increase biodiversity (Lata et al., 2018). Recently, Jusselme et al. (2019) showed that amending a commercial substrate with a mixture of earthworms and vermicompost significantly increased plant biomass and plant-pollinator interactions. The ability of substrates to retain water can be enhanced by changing the composition of growing media and by decreasing the particle size of inorganic materials, since the increase of pore space favor the retention of water (Graceson et al., 2013; Raimondo et al., 2015). Chenot et al. (2017) showed that a 15-cm-depth substrate composed by fine and coarse elements (75% clay silt and 25% pebble sand) is the best option to achieve an optimal vegetation colonization under a Mediterranean climate. It has also been reported that substrates containing bottom ash foster plant survival under severe drought conditions, probably due to its higher ability to retain water (Farrell et al., 2012). Ondon˜o et al. (2015) evaluated the effect of different artificial substrates: green compost and clay-loam soil, green compost and expanded clay and green compost and crushed bricks, on the development of 6 native Mediterranean species—Silene vulgaris, Silene secundiflora, Crithmum maritimum, Lagurus ovatus, A. maritimus, and Lotus creticus. It has been observed that the substrates containing expanded clay and bricks showed better aeration conditions than the loam soil containing-substrate. Despite the higher retention capacity of the latter, the germination rate and plant growth were better in lightweight and highly porous substrates.

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The amendment of substrates with water retention additives, such as hydrogels and biochar, can also enhance the moisture retention properties of green roofs in dry regions and their application is gaining ground in the last decades. There is evidence that adding increasing doses of sludge biochar (0 20%, v/v) significantly increased water holding capacity of substrate and the availability of water to the plants, while reducing roof substrate temperature (Chen et al., 2018). Cao et al. (2014) also demonstrated that biochar significantly improved water holding capacity and plant available water. Similar results were obtained by Savi et al. (2014) by adding a polymer hydrogel to the green roofs’ substrate to increase the amount of available water to the plants. The addition of this hydrogel enhanced plant performance and allowed the reduction of substrate depth. Farrell, Ang et al. (2013) evaluated the ability silicate granules and hydrogel to increase the substrate water holding capacity, the plant available water and growth in two substrates based on scoria and crushed terracotta roof-tiles. Silicates best performed regarding water holding capacity and plant growth for both substrates. However, the ability to increase plant available water by both additives is depended on plant species and substrates.

14.5

Conclusion

Green roofs, as NBS, have been proven to contribute with multiple environmental, social, and economic benefits in the built environment, toward cities resilience. They can enhance biodiversity, support stormwater management, and provide benefits in terms of energy reduction on consumption, thermal human comfort, with positive impact on outdoors microclimate and heat urban effect. Resilience of green roofs to climate change can be achieved through the selection of the adequate layers and materials to the situation under consideration. There is a need for an holistic view of the territories in order to optimize the flow of resources and materials having a circular economy as baseline. It is important that they integrate the built environment embracing the existing gray infrastructure, toward circular, resilient, and resourceful cities. To amplify their impact new buildings should integrate these systems as the retrofitting of existing ones. Innovative approaches have been addressed for green roofs in order to cope with high dry climates.

Acknowledgments This research was supported by National Funds from FCT-Fundac¸a˜o para Ciˆencia e Tecnologia within the scope of projects UIDB/04423/2020, UIDP/04423/2020, and UIDB/ 50016/2020 projects. Authors are thankful for the support of ANCV—Associac¸a˜o Nacional de Coberturas Verdes.

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Permeable concrete pavements for a climate change resilient built environment

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Alalea Kia Department of Civil and Environmental Engineering, Imperial College London, London, United Kingdom

15.1

Introduction

Climate change, growing urban populations (United Nations, 2019), and more widespread use of impermeable surfaces are all contributing to increased surface water runoff during heavy rainfall and the potential for localized flash flooding. Permeable pavements are one of the most promising mitigation strategies for urban flooding, as they rapidly drain stormwater through otherwise impermeable infrastructure into the underlying soil or drainage network. The most commonly used permeable pavement surfaces are permeable concrete (also known as pervious concrete), permeable asphalt and permeable interlocking block paving. Permeable concrete (Fig. 15.1), and permeable asphalt (Fig. 15.2A) have open structures with typically 1535% volume of interconnected voids that

Figure 15.1 Cross-section of a typical permeable concrete with porosity of 22%. Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00006-8 © 2023 Elsevier Ltd. All rights reserved.

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Figure 15.2 Typical (A) permeable asphalt and (B) permeable interlocking block pavements.

Figure 15.3 Schematic cross-section of a typical permeable pavement system incorporating a permeable concrete layer.

allow for stormwater drainage. Permeable interlocking blocks (Fig. 15.2B) are installed in an interlocking manner with their joints filled with crushed gravel for water drainage. They are laid in patterns that increase the structural strength and integrity of the pavement surface (Imran et al., 2013; Mullaney & Lucke, 2014; Scholz & Grabowiecki, 2007). This chapter solely focuses on permeable concrete pavements. A typical permeable pavement system consists of a top permeable concrete layer placed above a subbase coarse aggregate layer and subgrade soil (Fig. 15.3). In practice, there are many variations in the number, thickness, and composition of each layer, but all with the purpose of storing stormwater runoff until it infiltrates into the underlying soil or the existing drainage network. Permeable pavement systems can be designed for full, partial or zero infiltration depending on the site

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soil conditions. In the full infiltration system, the rainfall passes through subbase into the underlying soil. In the partial infiltration system, the proportion of the rainfall that exceeds the soil’s infiltration capacity flows into the drainage system. The zero infiltration system has an impermeable membrane between the subbase and the subgrade, with the water going through the subbase into the drainage system via perforated pipes. Partial and zero infiltration systems are best suited for sites with poorly draining soils, contaminated soils or in groundwater sensitive areas (CIRIA, 2015; Crookes, 2015; Drake et al., 2013). Permeable concrete is primarily used in low load-bearing environments, including car parks, pedestrian footpaths and cycle paths. The hydrologic benefits of permeable pavements for reducing run-off volume and peak flow rates are well documented (Abbott & Comino-Mateos, 2003). For example, annual run-off volume reductions of 50100% have been observed (Dempsey & Swisher, 2003; Legret & Colandini, 1999; Stenmark, 1995). Even if the underlying soil is poor draining, permeable pavement systems can reduce peak flows by over 90% and surface run-off volumes by 43% (Drake et al., 2014). As such, permeable concrete pavements are well suited to existing urban areas that lack conventional stormwater management facilities. In new urban areas, they can decrease development costs by limiting the need for other stormwater management infrastructure (ACI, 2010; Ferguson & Ferguson, 2005; Tennis et al., 2004). It has also been reported that permeable concrete captures suspended solids, P, N, Zn, Cu, and motor oil, improving stormwater and groundwater quality (Brattebo & Booth, 2003; Calkins et al., 2010; Sansalone et al., 2008; Scholz & Grabowiecki, 2007; Schueler, 1987; Welker et al., 2013). It is also reported to improve skid resistance and minimize heat island effects in cities (Amde and Rogge, 2013; Schaefer et al., 2006; Tennis et al., 2004). The latter is due to a change in pavement color (black asphalt to grey concrete) and its ability to absorb stormwater, reducing the pavement temperature. While permeable concrete has many benefits, it is susceptible to clogging that leads to serviceability problems and premature degradation (Coughlin et al., 2012; Deo et al., 2010; Kia et al., 2018; Mata & Leming, 2012; Tong, 2011; Yong et al., 2013). Physical clogging, which is the most common clogging mechanism, is caused by debris build-up on the surface and in the pore structure. Biological clogging can also occur, which is caused by algae and bacteria, and penetration of plant roots (Mishra et al., 2013; Ye et al., 2010). Addressing this challenge will substantially improve the durability, long-term performance, and service life of permeable concrete, while optimizing its application as a sustainable drainage system. However, clogging is not well understood and there are inconsistencies between the published studies due to the differences in the clogging material, the pore structure, exposure conditions, and testing methods used. Furthermore, predicting the effect of clogging on the long-term performance of permeable concrete is challenging. This chapter focuses on the properties of permeable concrete and factors that influence its performance. Clogging and methods to unclog permeable concrete as well as the current state of the art are also detailed in this chapter.

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Properties of permeable concrete

15.2.1 Composition and mix design Materials used in permeable concrete are the same as in normal concrete, but the mix proportioning is different. The aim in permeable concrete mix design is to achieve a balance between voids, strength, paste content, and workability. Fine aggregate content is significantly reduced or in most cases omitted (Obla & Sabnis, 2009; Tennis et al., 2004). A number of mix proportioning methods have been recommended, with the most important requirement being to provide sufficient cement paste to bind aggregates in order to achieve the required strength and a high void content. Absolute volume method is often used in permeable concrete mix design (ACI, 2010; Deo & Neithalath, 2011; Kevern et al., 2009; Sumanasooriya & Neithalath, 2011; National Ready Mixed Concrete Association (NRMCA), 2009). Other approaches have also been suggested. Nguyen et al. (2014) developed a mix proportioning method based on excess paste theory. Yahia and Kabagire (2014) proposed a method based on the volumetric ratio of paste to interparticle voids. A repeated trial-and-error approach to mix design and field testing was recommended by (ACI, 2010) until the desired properties are achieved. A typical range of permeable concrete mix proportions, compiled from literature, are summarized in Table 15.1 (Crouch et al., 2006; Ghafoori & Dutta, 1995; Ibrahim et al., 2014; Mata & Leming, 2012; Meininger, 1988; Montes & Haselbach, 2006; National Ready Mixed Concrete Association NRMCA, 2009; Sonebi & Bassuoni, 2013; Sumanasooriya et al., 2012; Wang et al., 2006). This shows a large variation in the mix composition of permeable concrete. This is partly due permeable concrete having different performance requirements coupled with the absence of no single universally accepted mix design method.

15.2.2 Pore structure The pore structure of permeable concrete consists of large, interconnected voids with sizes ranging from 2 to 8 mm depending on mix proportion, aggregate used Table 15.1 Typical permeable concrete mix proportions. Reported range Cementa Coarse aggregate Fine aggregateb Water/cement ratio Aggregate/cement ratio Fine/coarse aggregate ratio

150700 kg/m3 11002800 kg/m3 0100 kg/m3 0.20.5 212 00.07

a Portland cements and blended cements containing supplementary cementitious materials, including fly ash (565% wt. cement replacement), ground granulated blast furnace slag (2070% wt. cement replacement) and silica fume (512% wt. cement replacement) can be used in permeable concrete. b Fine aggregate content is typically limited to 07% wt. coarse aggregate content.

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(e.g., type, size, gradation), and degree of compaction (Low et al., 2008; Tennis et al., 2004). These pores are important as they control the performance of permeable concrete (Ghafoori & Dutta, 1995; Meininger, 1988). The volume fraction, size distribution, and topological structure of these pores are the critical parameters controlling the behavior of permeable concrete (Sansalone et al., 2008). Similar to impermeable concrete, permeable concrete also contains very fine capillary and gel pores that are inherent features of the cement paste, with their characteristic size ranging from several microns to nanometers. However, as these pores make insignificant contribution to water percolation, they are far less important. The void content of permeable concrete, typically 1535%, depends on a range of variables including cement paste fraction, aggregate content, gradation and particle shape, water/cement ratio, and compaction effort (ACI, 2010). These dependencies will be further examined in Section 15.3. In general, permeable concretes with porosity ,15% have very low permeabilities due to insufficient interconnected voids (Meininger, 1988). Porosities .35% result in highly permeable but very weak concretes (see Fig. 15.6).

15.2.3 Permeability Permeability is a property that describes the relative ease with which a porous medium transmits liquid under a hydraulic gradient. It is dependent on the pore structure, but the exact relationship is complex. The permeability of permeable concrete varies widely, from 0.003 to 3.3 cm/s (Coughlin et al., 2012; Crouch et al., 2006; Debnath & Sarkar, 2020a; Deo et al., 2010; Haselbach, 2010a,b; Ibrahim et al., 2014; Kant Sahdeo et al., 2020; Kevern et al., 2010; Kia et al., 2018; Lian & Zhuge, 2010; Mata & Leming, 2012; Meininger, 1988; Montes & Haselbach, 2006; National Ready Mixed Concrete Association NRMCA, 2009; Sonebi & Bassuoni, 2013; Sumanasooriya & Neithalath, 2011; Sumanasooriya et al., 2010, 2012; Taheri et al., 2021; Wang et al., 2006). The compiled permeability data are plotted against porosity in Fig. 15.4. Although a general trend of increasing permeability with increasing porosity is observed, there is a large scatter and weak correlation, in contrast to the strength-porosity data shown in Fig. 15.6. This is because permeability is not only dependent on the total pore volume but also on other pore characteristics including pore size distribution, shape, degree of connectivity, and tortuosity. Another reason for the scatter is the differences in the testing method (e.g., falling head or constant head permeability tests) that will influence the results. An interesting observation from Fig. 15.4 is that some permeable concretes display near zero permeabilities despite having very high porosities ( . 15%). These concretes were probably affected by “paste drain down” that causes localized pore blockage (see Fig. 15.5 and Section 15.3.1). Permeability can be calculated theoretically using the KozenyCarman equation that relates permeability (k) to porosity (φ) (Bear, 1988; Carman, 1939; Kozeny, 1927). It was found that when the α factor is equal to 19, there is a good correlation between the experimental and theoretical permeability values (Kia et al., 2018; Montes & Haselbach, 2006; Wang et al., 2006). This suggests that this equation can

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Figure 15.4 The correlation between permeability (cm/s) and porosity (%) for a wide range of permeable concretes reported in the literature.

Figure 15.5 Permeable concrete (A) as cast and (B) rotated, showing the bottom is completely blocked by paste drain down, which is due to excessive cement paste content, water/cement ratio and/or compaction. The sample is a 100-mm cube.

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be used as a simple guide for designers to estimate initial permeability of permeable concrete from measured porosity. k5α

φ3 ð12φÞ2

(15.1)

15.2.4 Strength The 28-day compressive strength of permeable concrete ranges from 1 to 28 MPa, increasing to 46 MPa with addition of silica fume, fine aggregates and superplasticisers (Ibrahim et al., 2014; Lian & Zhuge, 2010; Tennis et al., 2004). A design strength of 13.8 MPa would be required for pavements and footpaths not exposed to vehicles (ACI, 2010; Crouch et al., 2006). Pavements exposed to traffic require strengths greater than 20.7 MPa, and these are usually limited to low speed and/or infrequent usage (Hager, 2009). The strength of permeable concrete is mainly determined by total porosity, which in turn is influenced by a range of factors including cement content, water/cement ratio, aggregate characteristics and extent of compaction during placement. The compiled compressive strength against porosity data for a wide range of permeable concretes is shown in Fig. 15.6 (Debnath & Sarkar, 2020a; Ibrahim et al., 2014; Kant Sahdeo et al., 2020; Kevern et al., 2010; Kia et al., 2018; Li et al., 2021; Lian & Zhuge, 2010; Meininger, 1988; National Ready Mixed Concrete Association NRMCA, 2009; Sonebi & Bassuoni, 2013; Sumanasooriya

Figure 15.6 The correlation between compressive strength (MPa) and porosity (%) for a wide range of permeable concretes reported in the literature.

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& Neithalath, 2011; Sumanasooriya et al., 2012; Taheri et al., 2021; Wang et al., 2006). As expected, a strong correlation is observed and on average, strength decreased by about 3% for every 1% increase in porosity.

15.2.5 Durability The service life of permeable concrete ranges from 6 to 20 years and end-of-life is usually caused by clogging (discussed in Section 15.4), freezethaw degradation or excessive surface raveling (Chopra et al., 2007). Similar to impermeable concrete, freezethaw degradation of permeable concrete increases at higher degree of saturation. The voids in permeable concrete can offer some resistance to freezethaw degradation provided they empty before freezing, and therefore placing permeable concrete over drainable subbase is recommended (Gunderson, 2008; Tennis et al., 2004). However, clogging prevents draining and exacerbates degradation as trapped water and soil particles expand when they undergo freezing (Guthrie et al., 2010; Izevbekhai & Akkari, 2011; Tennis et al., 2004; Yang et al., 2006). This leads to cracking and debonding of the thin cement paste layer from the aggregate particles. Addition of fine aggregates, polypropylene fibers, and rubber improves strength and enhances resistance to freezethaw degradation, but it reduces porosity and permeability, which are the main contributors to permeable concrete pavement’s overall drainage performance (Amde & Rogge, 2013; Bilal et al., 2021; Bonicelli et al., 2015; Geso˘glu et al., 2014; Huang et al., 2012; Kevern et al., 2008a,b, 2010; Kevern, 2008; Liu et al., 2018a; Mondal & Biligiri, 2018; Schaefer et al., 2006; Yang & Jiang, 2003; Yang, 2011). Adding silica fume (up to 5% wt. cement) improves workability and enhances F-T resistance, but it reduces porosity (Kevern et al., 2008b; Yang, 2011). However, increasing the replacement rate ( . 5% wt. cement paste) will lead to a dry mixture that is difficult to compact, resulting in increased porosity and reduced F-T durability (Kevern et al., 2008b). Increasing compaction improves resistance to F-T degradation and surface raveling, but this reduces porosity and drainage performance (Bilal et al., 2021; Henderson & Tighe, 2012; Kevern et al., 2008a,b; Schaefer et al., 2006). Permeable concretes with porosity ,15% are durable, but those with porosity .30% exhibit poor F-T resistance (Kevern et al., 2008a,b; Liu et al., 2018b). Air entrainment is also known to improve F-T resistance of permeable concrete pavements by decreasing the hydraulic pressure that develops during freezing of pore water (Henderson & Tighe, 2012; Kevern et al., 2008a,b, 2010; Schaefer et al., 2006). However, the presence of entrained air voids can lead to further reductions in compressive strength.

15.3

Factors controlling the performance of permeable concrete

15.3.1 Cement content and water/cement (w/c) ratio The lack of fine aggregates coupled with a thin layer of cement paste to bind the aggregates, lead to an open pore structure permeable concrete that allows water infiltration but suffers from low compressive strength and tendency to cracking,

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raveling, and spalling. Increasing the cement content has a significant effect on mechanical properties of permeable concrete; however, excessive cement fills the open pores resulting in reduced porosity. Conversely, insufficient cement results in poor aggregate coating and low compressive strength. The optimum cement content is dependent on the aggregate size distribution (ACI, 2010). The optimum w/c ratio is typically between 0.26 and 0.45. Ghafoori and Dutta (1995) determined that the optimum w/c ratio was 0.370.42 for an aggregate/cement (a/c) ratio of 46. Smith (2004) reported that w/c ratio of 0.270.31 was necessary for permeable concrete with good performance. ACI (2010) recommends w/c ratio of 0.260.40 for good aggregate coating and paste stability. Lower w/c ratios cause balling and sticking of the concrete during mixing, while higher w/c ratios produce a thin cement paste that run-off the aggregates during placement, blocking the pores (Meininger, 1988). A high cement paste content causes localized clogging when the paste drains down the permeable concrete, resulting in a dense paste-rich lower layer (Fig. 15.5). Permeable concretes affected by paste drain down have poor infiltration capacity even if they have a high porosity. The conventional inverse relationship between w/c ratio and compressive strength does not apply to permeable concrete. At constant aggregate and cement content, increasing w/c ratio increases strength due to the excess cement paste filling the open voids. In contrast, reducing w/c ratio increases void content and infiltration rates (Schaefer et al., 2006).

15.3.2 Aggregates The aggregates used in permeable concrete are either single-sized or narrowly graded between 9.5 and 19 mm (ACI, 2010). The larger particle size and narrow grading lead to development of larger pores, improving the permeability but reducing the strength (Xie et al., 2020). While blending aggregates of different sizes improves the mechanical properties, it is not recommended for permeable concretes as it reduces their porosity and infiltration rates (Schaefer et al., 2006). Rounded aggregates (e.g., gravel) produce lower void content and increase the compressive strength. Angular aggregates tend to be oriented in one plane during compaction, adversely affecting the contact area and bonding. Flaky and elongated aggregates are avoided (Jain & Chouhan, 2011; Kevern et al., 2010; Lian & Zhuge, 2010; Maguesvari & Narasimha, 2013; Tennis et al., 2004). Fine aggregates are usually excluded from permeable concrete, but addition of a small fraction (up to 7% wt. coarse aggregate) increases compressive and flexural strengths, density and freezethaw resistance, while maintaining sufficient infiltration capacity (Henderson & Tighe, 2012; Kevern et al., 2008a; Schaefer et al., 2006; Wang et al., 2006). Increasing the a/c ratio beyond its typical range of 4.04.5 leads to an increase in permeability but decreases its compressive strength as less cement paste binds the aggregates (Ghafoori & Dutta, 1995). Aggregate moisture content plays an important role in the permeable concrete mix design, with dry aggregates reducing the workability, while wet aggregates contribute to paste drain down causing clogging (ACI, 2010). Therefore it is important for the aggregate moisture content to be accounted for in the mix design, with batch water adjusted to compensate for aggregate absorption or excess water from the wet aggregates.

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15.3.3 Additives Several studies investigated the effect of utilizing supplementary cementitious materials, including fly ash and silica fume as partial cement replacements, on permeable concretes’ compressive strength. Saboo et al. (2019) reported a 3554% increase in compressive strength when using 515% of fly ash replacement. A 30% increase in compressive strength and a 3% decrease in porosity were achieved with fly ash replacement of up to 20%. While the inclusion of fly ash was found to increase the compressive strength and durability, the permeability and porosity were reduced. This is due to fly ash’s pozzolanic reaction improving the aggregatepaste bonding, affecting the pore structure (Amornsrivilai et al., 2017; Wang et al., 2019). An addition of 515% silica fume was also reported to improve the compressive strength and freezethaw durability, while reducing the void content and permeability, due to the effect of the pozzolanic reaction on the pore structure (Adil et al., 2020; Amornsrivilai et al., 2017; Bilal et al., 2021; Mondal & Biligiri, 2018).

15.3.4 Chemical admixtures Similar to impermeable concrete, chemical admixtures used in permeable concrete improve the fresh and hardened properties (ACI, 2010). The water-reducing admixtures increase the workability at low w/c ratios. The retarders extend the workability during placement by decreasing the rate of cement hydration and reducing the excessive heat of hydration during early ages. Retarders also act as lubricants to help discharge stiff mixes from the mixer, improving the handling and performance of permeable concretes (ACI, 2010). The viscosity modifying admixtures lead to more cohesive mixes, preventing the paste drain down. Air-entraining admixtures are used in permeable concretes susceptible to freeze/thaw degradation in cold climates (Kevern et al., 2010; Kevern, 2008; Schaefer et al., 2006). As no reliable methods exist to quantify the entrained air voids in permeable concretes, ensuring adequate air entrainment (volume, spacing) for frost protection in field permeable concretes is difficult (ACI, 2010).

15.3.5 Compaction and placement As the freshly mixed permeable concrete contains little excess water, it should quickly be placed in its final position to prevent drying out, which can lead to low strength and surface raveling. Compaction is very important for permeable concrete, with insufficient compaction causing low-strength and surface raveling, while overcompaction leads to paste drain down, reduces void content and the ability to drain stormwater (Meininger, 1988; Schaefer et al., 2006; Sumanasooriya & Neithalath, 2011). Permeable concrete pavements are usually roller compacted. The roller consolidates near surface aggregates, resulting in a stronger bond but decreasing the surface permeability, with excessive rolling pressure causing void collapse. Permeable concrete pavements are not finished in the same way as impermeable concrete

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pavements as floating and troweling operations close surface voids (ACI, 2010; Obla, 2010; Tennis et al., 2004). Permeable concrete pavements, due to their high surface area and open void structure, are more susceptible to damage from improper curing than impermeable concrete pavements. Permeable concrete pavements are typically cured using a plastic sheeting cover within approximately 20 minutes after placement that lasts for 710 days or longer, if placed in cold climates. Permeable concretes that are not sufficiently cured will ravel if the cement paste dries out before achieving an adequate strength (Smith, 2004; Tennis et al., 2004). While the method of construction is regarded as most critical for permeable concrete pavements, many variations exist and their impact on long-term durability is not well understood. Furthermore, field quality control and ensuring sufficient compaction and curing is difficult.

15.4

Clogging

Permeable concrete pavements are prone to clogging, which is caused by build-up of debris on the surface or within the pore structure. Stormwater runoff carries a range of particles that fill and block permeable concretes’ voids, reducing their infiltration rates and causing surface overflow and ponding when the infiltration rates become less than the rainfall intensity. Materials that cause clogging include sediments (sand, silt, clay) that may have eroded from surrounding areas, debris from road surfaces or other areas carried and deposited by vehicles, small particles originating from the pavement itself due to surface wear or other degradation, and organic matter from surrounding vegetation (Ferguson & Ferguson, 2005). Welker et al. (2013) analyzed the material removed from the voids of permeable asphalt and permeable concrete pavements in a car park, which contained little fine sediments and were mainly from pavements’ deterioration. The permeable concrete was found to have greater surface raveling, and details of this work together with other relevant research are summarized in Table 15.2. Kayhanian et al. (2012) reported that the majority of the sediments removed consist of particles .38 μm from the surrounding vegetation.

15.4.1 Laboratory studies A number of studies investigated the effect of sediment type on clogging potential under controlled laboratory conditions. Some observed that coarse sand particles did not significantly reduce permeability as these large particles were prevented from entering the surface pores (Coughlin et al., 2012; Deo et al., 2010). However, Schaefer and Kevern (2011) found sand to cause significant reductions in permeability, with fine-grained silty clay producing almost no effect as it was washed through the sample with no concentration in the pore structure. The combination of silty clay and sand caused the highest reduction in permeability, with complete

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Table 15.2 Summary of selected studies on clogging of permeable concrete, arranged according to publication date. Study

Exposure method

Findings

Deo et al. (2010)

Fine (0.10.84 mm) and coarse (0.841.8 mm) grained river sands were used as the clogging material. For each clogging cycle, 25 g of sand was spread evenly on the specimen surface and permeability was measured. This was repeated until the flow rate was very slow or when further sand additions did not result in noticeable changes in the permeability.

Haselbach (2010a)

Cored samples were exposed to different clay sediments mixed in water: 0.167 g/L and 0.233 g/mL of kaolin, 0.03 g/mL of bentonite, and 0.01 g/mL, 0.025 g/mL and 0.1 g/mL of red clay. After each clogging cycle, samples were dried in an oven for at least 24 h. After the clogging cycles were completed, the excess clay was swept off with a brush from the top of the sample after drying. The sample was then exposed to rinsing cycles.

Guthrie et al. (2010)

Assessed the effects of clogging and water saturation on freezethaw resistance of permeable concrete. Carried out field measurements of stiffness and compressive strength on slabs subjected to the following conditions: (1) unclogged, soaked, and completely submerged in water; (2) unclogged, soaked, drained, and sealed; and (3) clogged, soaked, drained, and sealed.

Permeability decreased with increasing sand addition due to blocking of the pore channels, porosity reduction and tortuosity increase. Samples with higher porosity showed greater residual permeability at the end of testing due to larger pore sizes and pore connectivity. Coarse sand did not result in significant permeability reductions compared to fine sand as larger particles were prevented from entering the sample. Full clogging occurred after 410 cycles. Very little clay infiltration was observed with most of the clay accumulated on the sample surface, creating an impermeable layer. Samples appeared to have vertical porosity distribution with smaller pores near the top. The cores that were clogged with less cohesive clays tended to restore part of their permeability after exposure to 58 rinsing cycles. Results showed that samples that were clogged or fully saturated or both, deteriorated at a faster rate than those that remained unclogged and unsaturated.

(Continued)

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Table 15.2 (Continued) Study

Schaefer and Kevern (2011), Tong (2011)

Coughlin et al. (2012)

Mata and Leming (2012)

Kayhanian et al. (2012)

Welker et al. (2013)

Exposure method Clogging was performed using poorly graded sand (,0.297 mm) collected from the site. Three sediments (sand, clayey silt, and clayey silty sand) were applied over 20 cycles, with 5 or 40 g of each sediment type spread evenly on each sample per cycle. Clogged samples were cleaned using three different techniques and permeability was measured to determine recovery rate.

Samples were exposed to eight clogging cycles: one without sediments, three with increasing sand content (20, 60, and 140 g), three with increasing clay content (2, 6, and 14 g) and 140 g of sand per cycle, and one after pressure washing. The clogging material was uniformly distributed on top of the sample. Clayey silt and clayey silty sand was applied on top of the sample at 0.53 g/L each. Following permeability measurement, sample was drained and air dried for 24 h. Sample was cleaned, pressure washed and the permeability remeasured. This procedure was conducted three times for each sample. The collected sediments (particularly clay and inorganic form) from the 20 permeable concrete cores were ranging in particle size from 1000 to 38 μm.

Clogging material from permeable concrete and asphalt pavements,

Findings

Clayey silty sand caused the highest (9396%) permeability loss. Samples with higher porosity had higher residual permeability after clogging. A significant quantity of sand and clayey silty sediments remained on the sample surface, with clay adhered to sand particles forming a mud layer on the surface. Both sand and clay caused clogging, but clay produced approximately ten times more clogging per unit mass compared to sand. Pressure washing was ineffective at restoring infiltration capacity because of the subgrade clogging. Clayey silty sand produced the highest permeability loss and lowest recovery. Sediment deposits were observed retaining on top or in the specimen. Significant quantities of clayey silt were deposited at the bottom of the sample, retained by the filter fabric. The combined image analysis and porosity profile of the majority of the cores showed that most of the clogging occurred near the surface of the pavement, but some cores showed reduced porosity up to 100 mm below the surface. Most of the collected material was large particles from (Continued)

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Table 15.2 (Continued) Study

Exposure method installed side by side in a car park was analyzed. The pavements’ initial porosity was 27% and 25%, respectively, and was maintained every 6 months by vacuum sweeping.

Hein et al. (2013)

Nguyen et al. (2017)

Kia et al. (2018)

Tested the effectiveness of power blowing, pressure washing, and vacuuming in recovering the infiltration capacity of 6 m 3 18 m permeable concrete parking slabs (18.527% porosity) subjected to storm-water runoff containing silt, clay, and organics. Samples were exposed to 253 g of sediments (75% silty clay, 25% of sand, mixed in water per cycle for five cycles). After each clogging cycle, the samples were rinsed with water and permeability was remeasured. Four different sample types of varying particle size (1.2514 mm) and porosity (736%) were tested (glass spheres, gravel, laboratory prepared and commercially available permeable concretes). Samples were exposed to two clogging methods: (1) combined “sand and clay” and (2) alternate “sand or clay.” The permeability of all samples were measured at different hydraulic gradients (0.33 up to 5) to determine the effect of the applied pressure on permeability. Three methods were used to define clogging potential based on measuring the initial permeability decay, half-life cycle and number of cycles to full clogging.

Findings pavement deterioration (surface raveling). Permeable concrete had greater surface raveling, with 66% of the collected material coming from permeable concrete and 34% from permeable asphalt. Vacuuming followed by pressure washing was found to be most successful in improving infiltration rates. Pressuring washing was more effective than power blowing, but no improvements were achieved by combining the two. Permeability was reduced to lower than 95% of the initial value. The blended material was believed to be the most damaging clogging agent, leading to complete clogging after a small number of cycles. Substantial permeability reductions were observed in all samples, particularly when exposed to sand and clay simultaneously. Samples with lower porosity showed more rapid clogging, complete clogging occurred after 213 cycles, depending on the sample porosity and exposure method. It was found that the measured permeability decreased by 15%30% with increase in the hydraulic gradient due to the increased friction associated with increase in the fluid velocity. The clogging potential methods could be used for service life modeling.

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clogging after a small number of cycles. This was due to the wider particle size distribution increasing the probability of retention coupled with the cohesive nature of clay, leading to more surface interaction and particle adhesion. Nguyen et al. (2017) and Sandoval et al. (2022) found the silty clay and sand to cause the most rapid clogging. Kia et al. (2018) found the combined sand and clay (0.8 g/cm2 of sand and/or 33.3 g/L of clay in each cycle) to lead to a more rapid reduction in permeability compared with alternate sand or clay, with the deposition pattern dependant on the exposure and particle size relative to the pore size. Sand particles and bentonite clay clumps larger than the pores were retained on the top surface, forming a blanket like deposition layer, while finer sand particles were trapped within the pore structure with fine bentonite clay slurry being carried through, unless it was flocculated and deposited at pore constrictions. Coughlin et al. (2012) concluded that clay caused approximately ten times more clogging per unit mass than sand. Haselbach (2010a) found very little clay infiltration in sectioned cores, samples exposed to bentonite clay clogged the most with particles accumulating on the top surface creating a low permeability layer. The findings from such studies are not consistent, and this can be attributed to differences in the clogging material, the pore structure of the tested samples, exposure conditions and other variables. Kevern (2015) measured the permeability of permeable concrete slabs (350 mm 3 350 mm 3 150 mm) clogged with silty soil slurry (34% ,0.074 mm), landscaping compost (15% ,0.074 mm) and a combination of soil slurry and compost. Although the samples were prepared by a single operator using the same procedure, the initial permeability of unclogged samples were highly variable and ranged from 140 to 1380 cm/h. Following the clogging tests, the samples were washed with a standard hand-held hose and cleaned with an industrial vacuum cleaner to determine the extent of permeability recovery. Samples clogged with compost had higher postclogging permeability and recovery rates than samples clogged with soil slurry. The greatest clogging effect was caused by a combination of soil slurry and compost. Samples with high initial permeability also showed high recovery rates, but significant infiltration capacity was permanently lost as the recovery was only around 50% of the initial capacity. Some studies have observed that clogging usually occurs on the surface or in the upper layer of the permeable pavement (Kayhanian et al., 2012; Yong et al., 2013), while others found that particles are just as likely to clog within the permeable concrete or the underlying soil (Chopra et al., 2007; Mata & Leming, 2012; Siriwardene et al., 2007). These findings highlight the complexity of the clogging mechanism and suggest that there is no single location within the permeable concrete where clogging occurs. The actual deposition pattern will depend on the size of the clogging particles relative to the pore size in permeable concretes, as shown schematically in Fig. 15.7. Particles that are much larger than the pores will be retained on the top surface (Fig. 15.7A), forming a blanket like deposition layer. Finer particles tend to trap within the permeable concrete away from the surface (Fig. 15.7B). Very fine particles, such as silt and clay, are carried through but may still clog when deposited at pore constrictions or at the bottom of the pavement, at the interface with the

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(A)

(B) Figure 15.7 Schematic diagrams showing the clogging patterns of different sized particles in permeable concretes: (A) large particles relative to the pore size are predominantly caught at the top surface or migrate only a short distance into the permeable concrete and (B) fine particles travel deeper into the permeable concrete.

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aggregate subbase or subgrade soil (Kia et al., 2018; Mata, 2008; Mata & Leming, 2012; Nan et al., 2021). A geotextile fabric (Fig. 15.3) can be used between the layers to prevent transfer of the fines and as a filter to improve the water quality (Scholz, 2013), but accumulation of solids on the fabric increases the clogging risk and reduces the infiltration rates (Boving et al., 2008; Brown et al., 2009; Kayhanian et al., 2012). Another factor influencing clogging is the exposure to different climatic conditions. Yong et al. (2013) investigated clogging in permeable asphalt, block pavers, and resin bound paving, and although these are not permeable concrete, the findings are relevant. Each permeable pavement type was exposed to either constant inflow of actual stormwater with no drying periods or variable inflow rates with drying periods, with the flow containing sediments with 10% wt. particles ,5 μm and 10% wt. particles .147 μm. Each run was continued until the pavements were clogged, defined as when ponding was 30 mm above the surface or outflow decreased to 10% of the initial rate. It was found that irrespective of the pavement type, clogging was delayed in systems exposed to variable flow and drying periods, having almost twice the lifespan of the pavements receiving continual wetting. The earlier onset of clogging is believed to be caused by biological growth, which occurs faster in continuous wet conditions (Mackey & Koerner, 1999; Watson-Craik & Jones, 1995). Clogging accelerates the freezethaw degradation. The freezethaw resistance of permeable concrete has been evaluated when exposed to different levels of soil clogging (poorly graded sand ,0.297 mm collected from the vicinity of an actual permeable concrete slab) and water saturation (Guthrie et al., 2010). It was found that permeable concrete samples that were clogged or fully saturated or both, deteriorated at a faster rate than those that remained unclogged and unsaturated. The average number of freezethaw cycles to failure was 93 for clogged specimens compared to 180 for unclogged specimens and 80 for saturated specimens compared to 193 for unsaturated specimens. However, as only the upper 2550 mm of the 180 mm sample was clogged, there was no significant differences in the structural properties (strength and stiffness) between the clogged and unclogged specimens.

15.4.2 Field investigations Large variations were observed in the properties of field permeable concretes. The permeability of 20 permeable concrete pavements, aged 18 years, located in car parks in California was measured at the main entrance, an area with no traffic and within the parking spaces (Kayhanian et al., 2012). A large variability in permeability measurements (0.00021.82 cm/s) was observed within each and between all parking spaces, attributed to differences in the traffic volume, inconsistencies in pavement construction and pavement damage in the testing area at each site. The permeable concrete age and the amount of accumulated sediments were the most important factors influencing permeability, with older samples showing lower permeability due to increased clogging. The permeable pavement application type is believed to influence the permeability, with traffic lanes having lower infiltration capacity as larger quantities of

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sediments fall onto them compared with parking spaces (Henderson & Tighe, 2012). This is consistent with the findings of Kumar et al. (2016), who measured the in-situ permeability of three different permeable pavement types (asphalt, concrete, and block pavers) in a car park over a 4-year period. The highest permeability was observed in permeable asphalt, followed by permeable concrete and permeable block pavers, with the infiltration rate in traffic areas being at least 50% lower than in the parking spaces due to their higher surface wear causing increased pore clogging. The long-term field performance of permeable concrete pavements has been reported in a number of studies. Radlinska et al. (2012) examined the porosity, compressive strength and clogging of samples taken from the Stormwater Research and Demonstration Park, Villanova University, that was constructed in 2002 and demolished in 2012 due to degradation. Significant variations were observed in the strength values (15.643.0 MPa) due to inconsistencies in placement and curing of permeable concrete. The porosity, examined using image analysis, was found to range from 1% to 26%, with only a fifth of the samples having values .15%, which is the lower limit for permeable concrete. The top surface porosity was consistently lower than that in the deeper sections, indicating loss in surface infiltration capacity. Moreover, the sediments in the pore structure resembled hardened cement paste, indicating freezethaw induced spalling and clogging by loose particles. In addition, some samples had reduced surface void content due to excessive compaction at the time of construction. Field infiltration tests indicated that the top surface was sealed, preventing infiltration into the pavement, which were consistent with the porosity profiles obtained from image analysis. Improper construction has led to irregular pore distribution, variable strength and sealed pavement surfaces, preventing infiltration. The permeability of 55 permeable pavements from Australia and the Netherlands, aged 112 years, was evaluated using a double ring infiltrometer (Boogaard et al., 2014). The permeable pavements were compared in terms of their ability to infiltrate either a 3-month average recurrence interval storm event for the Australian pavements, or to satisfy the minimum European infiltration rate of 97.2 mm/h for the Dutch pavements. Over 90% of the 55 pavements, were able to satisfy these standards, however the infiltration capacity of the permeable pavements decreased with increase in the pavement age due to cumulative clogging by sediments, poor installation of the older pavements and poor maintenance. The Urban Drainage and Flooding Control District (UDFCD) has extensive experience in installation, testing and monitoring of permeable concrete pavements in Colorado. By 2008 a number of installations have suffered from extensive surface raveling and erosion, leading to UDFCD issuing a temporary moratorium on permeable concrete until further investigation (MacKenzie, 2008). Subsequently, UDFCD collaborated with Colorado Ready Mix Concrete Association to develop new design guidelines for permeable concrete (Colorado Ready Mixed Concrete Association, 2010) and lifted the moratorium. A permeable concrete demonstration pad was constructed at the National Renewable Energy Laboratory (NREL) using the new design specifications, but was heavily deteriorated after two years of service in 2011. As a result of the failure at the NREL site and poor structural

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performance at other sites, UDFCD removed permeable concrete as a possible sustainable stormwater quality best management practice from their urban storm drainage criteria manual (MacKenzie, 2013).

15.4.3 Unclogging maintenance methods Permeable concrete pavements require regular unclogging maintenance to remove sediments, recover permeability and preserve performance. Pressure/power washing with water and vacuum sweeping (or a combination of these) are the most recommended methods in rehabilitating clogged permeable concrete (Drake et al., 2013; Environmental Protection Agency EPA, 2004; Golroo & Tighe, 2012). Pressure washing uses a power head cone nozzle to weaken the bond between the clogging particles and the pavement and to remove them. Vacuum sweeping, sucks out the clogging particles, re-opening the blocked pores. The recommended maintenance frequency ranges from at least once a year (Drake et al., 2013) to two to four times a year (Gunderson, 2008; Henderson & Tighe, 2012), depending on the site and weather conditions, with more frequent maintenance required in areas subjected to higher debris concentrations and deposition rates. The effectiveness of pressure washing, vacuum sweeping, and a combination of these techniques for restoring the infiltration capacity of clogged permeable concretes has been investigated in a number of studies, with the findings varying between different studies and sometimes within a single study. These variations can be attributed to the differences in the permeable concrete (e.g., mix design, construction technique, homogeneity, age), pavement application, clogging material and the process, test procedure, and history prior to the maintenance. Overall, the results suggested that these maintenance techniques can often partially restore the permeability, but the economic and practical viabilities are questionable. The combination of vacuuming and pressure washing was found to result in the highest permeability recovery, with pressure washing being more effective than vacuuming (Chopra et al., 2010). However, the findings were based on laboratory experiments with samples being washed with an open base, as opposed to being than mounted on a subbase. Furthermore, high pressure washing dislodges the particles, pushing them into the pavement and causing further clogging. Coughlin et al. (2012) found pressure washing to be ineffective in restoring the permeability of samples clogged with sand and clay as most of the head loss occurred in the subgrade rather than the permeable concrete layer. Similarly, Haselbach (2010a) reported improvements after drying, brushing and water flushing clay (bentonite, kaolinite, and red clay) clogged permeable concrete samples but found limited success in restoring infiltration rates due to the difficulty in cleaning samples where the clogging materials accumulated below the pavement surface. Field tests conducted by Henderson and Tighe (2012) found pressure washing and vacuuming ineffective in rejuvenating permeable concrete pavements. They reported sweeping the pavement with a stiff broom followed by rinsing it with a garden hose to be effective in agitating debris present in the surface voids. However, mechanical sweeping is not recommended as it pushes the particles further into the pavement

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rather than removing them. Restoring the initial permeability in pavements with low initial infiltration rates (due to poor mix design and/or improper construction), was observed to be extremely difficult (Henderson & Tighe, 2012). Similarly, Schaefer and Kevern (2011) found the maintenance methods to be more effective on samples with high porosities, but had a negligible effect on specimens with ,15% porosity. This is also consistent with the findings of Tong (2011) who found samples with higher initial porosities to achieve improved permeability recoveries. Therefore the pavement recovery rate is strongly influenced by its porosity, pore size distribution and connectivity. Although vacuum sweeping is faster than pressure washing, it was found to only extract particles that are close to the pavement surface (Chopra et al., 2010; Schaefer & Kevern, 2011; Vancura et al., 2012). While Mata and Leming (2012) found vacuum sweeping to partially restore permeable pavement’s infiltration capacity, Drake et al. (2013) concluded that it was only effective at one of the investigated sites and not the other. The porosity profile of permeable concrete cores was measured, using X-ray tomography, to assess the effect of pavement age on the nature and extent of clogging (Manahiloh et al., 2012). Vacuum sweeping was found to increase the average porosity of 1-year-old samples from 26.0% to 29.0% and from 18.1% to 19.1%. for 8-year old samples. The lower porosity and recovery rates of the old samples were associated to the extent of clogging. The most effective cleaning method is found to be vacuum cleaning followed by pressure washing (ACI, 2010). Chopra et al. (2010) found that combining vacuuming and pressure washing produced the highest permeability recovery. Schaefer and Kevern (2011) showed vacuum sweeping and pressure washing to approximately give the same permeability recovery, while combining vacuum sweeping and pressure washing produced higher recoveries. Hein et al. (2013) also found pressure washing and vacuuming to be effective initial cleaning methods, but vacuuming followed by pressure washing and a second round of vacuuming was reported to be even more effective. However, it should be noted that such maintenance practices do not fully recover the initial infiltration rates, in fact the recovery rates are fairly low. For example, the recovery rates were ,15% when pressure washing or vacuuming was applied on samples clogged with sand and clayey silty sand, but combining vacuum sweeping and pressure washing increased the recovery rates to 2025% (Tong, 2011). Similarly, pressure washing or vacuum sweeping resulted in 1020% of the initial permeability to be recovered in samples clogged with sand, while combining these methods produced 30% recovery (Schaefer & Kevern, 2011). For samples clogged with silty clayey sand, pressure washing or vacuum sweeping recovered 1020% of the initial permeability, while the combined method produced 20% recovery. The effectiveness of the maintenance methods also depends on the extent and location of clogging. When pavements are clogged with coarse sand particles that are mainly deposited on the surface, vacuum sweeping, pressure washing, or a combination of both improves the permeability. However, if the permeable concrete is clogged with silty clayey sand particles that are deposited within the bulk or toward the base of the sample, traditional cleaning methods are not effective (Mata, 2008). Mata and Leming (2012) exposed a 20% porosity permeable concrete to two cycles

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of sediment loading with washing after each cycle. Results showed that the majority of sand was trapped at the top surface, while clayey silt and clayey silty sand significantly penetrated and deposited at the bottom, retained by the filter fabric. Washing largely removed the sand particles, achieving 30% of surface permeability recovering by using either pressure washing or vacuum sweeping; however, it was less effective for clayey silt (recovery rates ,20%) due the difficulty in recovering material settled at the bottom. The samples subjected to clayey silty sand showed the highest permeability loss and lowest recovery (,10%). Sandoval et al. (2020) evaluated the effectiveness of three different cleaning methods, surface cleaning with a broom, air cleaning using an air compressor, and pressure washing, in recovering the permeability of a field permeable concrete pavement. It was found that when permeable concrete is exposed to sand and clay, the most effective cleaning method is pressure washing (35% permeability recovery rate), followed by air compressor (9% recovery rate) with surface cleaning having no effect. Vancura et al. (2012) compared the performance of a vacuum truck, vacuum street sweeper, and regenerative air street sweeper in removing clogging material from filed permeable concrete pavements. All three machines were only effective at removing clogging material within approximately 3 mm of the surface. It was found that some test locations required maintenance every month to sustain a functional level of permeability, and despite this, clogging material remained in the void structure. Drake et al. (2013) evaluated the effectiveness of several small- and full-scale maintenance equipment including pressure washers, street sweepers, and low/high suction vacuuming in restoring permeable interlocking concrete pavers and permeable concrete in eight car parks. The results suggested that these techniques were effective to some extent in clearing near surface clogging, but the improvements were not consistent throughout as the fines that migrated too far into the pavement were impossible to extract, permanently affecting the permeability. These results show that even with regular maintenance, a degree of clogging in permeable pavement systems is unavoidable. The above review highlights the importance of conducting regular unclogging maintenance to avoid failure of permeable concrete pavements in infiltrating stormwater. This maintenance has to be regular or else clogging will occur to such an extent that maintenance is no longer effective, and the pavement becomes fully impermeable. Maintenance does not fully restore the initial infiltration rates, even if carried out regularly, and the performance of permeable concrete pavements will decrease over time to unacceptable levels due to the cumulative effects of clogging leading to premature degradation.

15.5

Current state-of-the-art in permeable concrete pavements

This chapter has identified several unresolved issues concerning the performance of permeable concrete pavements that need further investigation in order to optimize their application. Poor understanding of mix composition and proportioning as well as the construction techniques contributes to large variabilities in the pore structure

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and properties of field permeable concretes. Paste drain down is a major defect in permeable concretes that exacerbates degradation, but it is difficult if not impossible to detect. Therefore on site quality control and quality assurance remains a major challenge for permeable concrete pavements. An improved understanding of clogging, the decrease in permeability over time and long-term degradation mechanisms occurring in the field are required. In addition, development of longterm performance and clogging predictions are critical in facilitating more accurate life-cycle analysis and the development of improved designs. The problem with current permeable concrete pavements is that they are highly susceptible to clogging, which means it is essential to conduct periodic maintenance/ cleaning in order to retain their performance. Research has focused on different methods to restore the permeability of permeable concrete pavements. However, the maintenance methods used are not particularly effective for clogging particles that accumulate below the surface. New improved maintenance methods that are more effective are needed. A better understanding of which methods are effective on different pavement types and service environments, and how frequent maintenance should be carried out, is needed to optimize permeable concretes’ performance. This chapter also highlights the need to develop new permeable concretes that are more resistant to clogging with no frequent maintenance requirements. The pore network in permeable concretes is highly complex and heterogeneous, containing tortuous pore channels with variable cross-section and random interconnectivity. Tortuosity is an intrinsic property of a porous material defined as the ratio of actual flow path length to the straight distance between the ends of the flow path (Bear, 1988) and is related to the inverse of connectivity. Different flow paths through permeable concrete have different tortuosity as shown schematically in Fig. 15.8. Particles moving in pores that are more tortuous and heterogeneous have greater probability of retaining and accumulating within narrow constrictions (pore necks), with the clogging potential increasing with increased tortuosity. Therefore a clogging resistant permeable concrete will require uniform pore structure with low tortuosity. Solving the clogging problem will make permeable concretes more efficient, resilient and cost effective, promoting their widespread adoption. New types of permeable pavements have been developed to overcome the previously discussed limitations in permeable concrete pavements. Jones et al. (2010) developed concrete beams with drainage holes, 12.5 mm in diameter with 50 mm spacing and porosity of 3.1%. The splitting tensile strength and modulus of rupture of these precast concrete beams, were compared with equivalent beams without drainage holes. It was reported that the strength ratio between the beams with and without drainage holes was approximately 0.71. Jones et al. (2010) highlighted a number of issues in preparing these test specimens, including breakage of the vertical dowels. Kia et al. (2019) have recently developed a high-strength clogging resistant permeable pavement (CRP, also known as Kiacrete), which improves the strength, drainage performance, and clogging resistance observed in conventional permeable concretes. This was achieved by engineering a uniform pore structure of low tortuosity (direct pore channels of 36 mm diameter) in self-compacting mortar.

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(A)

319

(B)

Figure 15.8 Schematic showing (A) the different pathways through a conventional permeable concrete with tortuosity .1 and (B) CRP with direct channels and tortuosity of 1.

Rigorous lab testing supported by modeling confirmed its enhanced strength, durability, and drainage performance (Kia et al., 2019, 2022). The new material is highly resistant to freezethaw degradation, has high strength (twice as strong as conventional pervious concrete pavements, .50 MPa) and high permeability (ten times more permeable than conventional pervious concrete pavements, .2 cm/s), yet does not clog despite extensive cyclic exposure to sand and clay sediments. CRP was found to be at least twice as strong and ten times more permeable than conventional permeable concretes of equal porosity, which completely clogged after just a few cycles of sediment exposure (Kia et al., 2018, 2019). The superior permeability and clogging resistance of CRP is due to the homogenous pore structure of constant cross-section and tortuosity of 1 (see Fig. 15.8), allowing the water and sediments to flow through without being trapped within the pore structure. The challenges of scaling up the innovation for flood prevention were addressed by developing a novel interlocking tile system (Kia et al., 2020) which was recently deployed at scale as cast in-situ slab at the new White City Campus of Imperial College London in the United Kingdom (Fig. 15.9). This system was shown to be easier to construct at scale on site as it uses self-compacting cementitious material and does not require specialist contractors for placing it to avoid overcompaction or closing off of the surface pores observed in conventional permeable concrete pavements (ACI, 2010; Debnath & Sarkar, 2020b; Kevern et al., 2009; Kia et al., 2017). A structural and hydrological design methodology for this system has also been reported in (Kia et al., 2021), enabling widespread adoption of permeable concrete pavements.

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Figure 15.9 Large-scale delivery of CRP at Imperial College London’s White City Campus.

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Building design in the context of climate change and a flood projection for Ankara

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˙ Ayc¸am ˘ and Idil Pelin Sarıcıoglu Faculty of Architecture, Department of Architecture, Gazi University, Ankara, Turkey

16.1

Introduction

Rapid industrialization and urbanization that have occurred in various locations of the world in the last decades have resulted in severe effects on the climate. International organizations have made efforts to respond to these changes by founding the Intergovernmental Panel on Climate Change (IPCC) which holds a significant place in this regard (Shaw et al., 2010). According to a report by IPCC, high temperatures have been observed inn certain global areas in the current decade. For instance, the temperature recorded for the entire year of 2015 was so high that 2015 was accepted as the warmest year of the last decade. According to certain researchers, the mean temperature of the period between 2081 and 2100 is estimated to be 0.3 C 4.8 C higher than that of the period between 1986 and 2005 (IPCC et al., 2014). The recent concept of global warming is a result of humans’ effect on nature. One of the aforenoted anthropogenic effects is related to built environments. As the construction sector is one of the factors creating the largest amount of greenhouse gas (GHG), it has a key role in worsening the global warming (Nematchoua et al., 2019). Constituting a significant part of the built environments, buildings are among the primary reasons for CO2 emission. Although energy efficient designing methods and sustainable approaches are important for controlling this issue in the buildings to be constructed and despite the energy efficiency being a significant metric for sustainable development, operation performance should also be ensured against the climate change. Buildings are designed in a specific form so that they will preferably serve for 40 50 years. Furthermore, the initial designs of buildings should largely ensure the proactive adaptation. Accordingly, how the future incidents of extreme temperatures and floods will affect buildings is a significant parameter (Wang & Ramakrishnan, 2021). Impact of extreme climate events on buildings and the concept of thermal comfort, effect of flood, durability of construction materials and changing climate conditions were primarily discussed. According to the literature, changes in heat waves will affect the indoor comfort conditions first. Therefore the indoor thermal comfort conditions that depend on the weather conditions should be adapted to the changing climate conditions (Koˇsir, 2019). Studies on this topic indicate that ensuring the thermal comfort conditions will be challenging during summer months and that the need for cooling the Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00001-9 © 2023 Elsevier Ltd. All rights reserved.

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buildings will increase due to the temperatures expected to increase in the upcoming years, although the dimension of change varies by building type and characteristics. The change in the energy consumption of buildings depends on the fluctuations seen in external climate conditions. The temperature increase expected for the upcoming ten years is believed to increase the demand for the cooling energy. Many studies have shown that buildings’ need for heating will decrease while the need for cooling will increase, based on the future climate scenarios. These changes in energy demands mean more electricity consumption by buildings, resulting in higher electricity costs and extra loads on urban grid. Accordingly, alternative energy efficient solutions should be generated to prevent all these issues. As an another effect of climate change, changes in water availability, particularly reductions in the summer, may result in less reliable supplies, more frequent restrictions, and potential water shortages in the long run, unless additional measures to reduce demand and develop supplies are implemented. Climate change flooding effects on the built environment include: drier summers and droughts; reduced water availability/shortages, reduced water quality, reduced soil moisture content/increased subsidence, changes in biodiversity, and sea temperature rise; and sea level rise, increased sea surge height, increased precipitation or more rainfall in heavier form, increased river flooding, increased urban drainage flooding, and higher wind speeds (Bello et al., 2018). The projections conducted by General Directorate of Meteorology (GDM) indicate that Turkey will face comparable results. According to the results of these projections, heating degree days will increase while the cooling degree days will decrease in Turkey, meaning more energy consumption to cool buildings. Therefore energy efficiency will be more important considering these phenomena that will change in time. The effects of climate change on building envelope which will arise from extreme temperatures and precipitation include distortions in material resistance and facade envelope materials. To solve these issues, alternative and modern technology materials that have a low rate of carbon emission that are not based on plastic and that will contribute to energy generation should be primarily preferred. Measures to reduce or adapt to the climate changes become important to minimize the adverse effects on buildings and built environments. With the climate change risk analysis, it is easy to determine the relevant risks, the dimension of damage as well as necessary measures can be specified. Accordingly, this study discussed the effects of climate change on buildings, mentioned the climate change risk analysis, and included the flood risk analysis regarding recent periods for Ankara. The reason for selecting Ankara is that the city is located in the Central Anatolian Region of Turkey with continental climate and that Ankara is believed to be affected by climate change more than other Turkish cities according to the data from the relevant literature. However, due to the inability to obtain sufficient amount of data, the study was limited and assessed on the street scale. This study is believed to serve as a basis for the future climate change analyses and assessment for Ankara. In an analysis performed for a short period of time, the precipitation rate of 2020 is found to be lower that of 2019 for Ankara, proving the effect of climate change on precipitation.

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16.2

329

Climate change and its effects

American Meteorological Society defines climate as the slowly changing directions of the atmosphere-hydrosphere-land surface system. Considering the variability of these factors in time, climate is characterized by the mean figures of the climate system covering a prolonged period. The most popular trait of the climate change is the changes seen in seasonal cycles. Moreover, seasonal cycles grow, and mean figures regarding seasonal temperatures change. American Meteorological Society defines climate change as follows: the systematic change seen in the long-term statistics of climate elements (temperature, pressure, or wind) that exist or continue for a couple of decades or longer (Dessler, 2012). Studies on climate change benefit the data regarding the global climate and weather models. The climate models reflect atmosphere, geosphere, biosphere, hydrosphere, and cryosphere as the totally integrated aspects of climate. Weather models predict the weather of tomorrow and probably further days or weeks. Climate models are global and regional. However, weather models are regional and local. Therefore the temperatures that have been globally rising since 1750 and 1880 are related to the climate, rather than the weather conditions. Storms, tornadoes, and daily temperatures are related to weather conditions (Farmer, 2015). There are many reasons for climate change including increased GHG effect arising from the changes in atmospheric gas rates, changes in sunlight, melting glaciers, continental movements, and increased CO2 arising from human-triggered factors. These changes are related to one another and result in extreme temperatures and precipitation by affecting the climate. As a result of observing the climate changes, IPCC was founded as nations started to accept the severity of the climate change issue. IPCC does not conduct any research or follow any data or parameters regarding the data. Founded by World Meteorological Organization (WMO) and United Nations Environment Programme, IPCC targets presenting assessments to governments and policymakers about the scientific grounds, effects, and future risks regarding the climate change and to inform authorities about the options of adaptation and reducing climate change (Da¸sc¸ıo˘glu, 2021). In its third and fourth assessment report (AR3 and AR4), IPCC developed four different scenarios named B1, B2, A2, and A1 for future GHG emissions based on different assumptions, such as future global population development, technological practices, economic growth, resource use, and social equality. In AR5, these emission scenarios were replaced with four new scenarios named Representative Concentration Pathway (RCP) and based on GHG concentrations (Bamdad et al., 2021). An RCP scenario consists of a large digit cluster. RCP data are offered in tables resembling to an electronic table. For each emission category, an RCP includes a series of initial values and emission figures estimated for upcoming years until 2100, based on the assumptions regarding economic activities, energy resources, population increase and other socio-economic factors (Farmer, 2015). These estimated emission scenarios are utilized to predict the climate changes within general (also known as global) circulation models (GCMs). GCMs are the digital, computer-controlled models simulating the physical processes in

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the global atmosphere and oceans. GCMs predict the climate conditions at a high spatial resolution (indicating a few hundreds of kilometers), which does not make them suitable for direct use within the building simulation software (Bamdad et al., 2021). The data obtained from global climate models should be shrunk regionally. Following this process, the data will become suitable for the relevant assessments in building simulation software. In conclusion, the climate continues changing and this change can be digitally proven according to IPCC reports, other scientific studies and projections. Temperatures are increasing globally while CO2 emissions are also increasing, resulting in precipitation anomalies. Earth surface continues getting warmer significantly, as understood from the current global temperatures being the highest in the last 2000 years. Fig. 16.1 shows the alteration in global surface temperature compared to the average temperatures of the period between 1951 and 1980. Since 2000, there have been 19 years which were the warmest, excluding 1998 helped by a severe tornado named El Nin˜o. 2020 was a match for 2016 in terms of being the warmest year as the activity of record-keeping started in 1880 (source: NASA/GISS). This study is extensively consistent with the examinations and studies conducted by the Climatic Research Unit and the National Oceanic and Atmospheric Administration (URL 1, 2022). According to the projections, certain sections of Northern Africa, Middle East, Southern America, Southern Asia and Australia will be affected by increased temperatures, and three billion people will live under high temperatures in the event that temperature increases 1.5 C until 2070. Global sea levels are rising due to global warming caused by human-triggered factors, which is another impact of climate change, with the current rates being the highest for the last 2000 years. Sea level rise arises from two reasons associated with global warming: melting ice blocks and glaciers providing extra water and seawater expanding after getting warmer. Fig. 16.2 reflects the alterations in sea level from 1993 as displayed by satellites (URL 2, 2022).

Figure 16.1 Changing global surface temperature (URL 1, 2022).

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Figure 16.2 Satellite sea level observations (URL 2, 2022).

Other global results of climate change indicate that the glaciers in Greenland and Antarctica lose significant amount of ice due to global warming arising from humantriggered reasons which also paved the way for 70% increase in CO2 emission levels. According to the data of National Aeronautics and Space Administration, the level measured in December 2021 was 417 pm (URL, 2022). In addition to these impacts, climate change effects can be observed in different sectors that concern the social and human aspects of built environments. These results regarding the built environment are divided into direct and indirect effects; direct effects concern the cities following the changes in climatic variability, while indirect effects yield results including environmental and social changes in sectors related to the financially known built environments of the urban or rural areas. Global climate change affect people and environment from various aspects. Potential effects are observed in various sectors, agriculture and food safety, ecosystems, forests, waterworks, health, shores, flood areas, and tourism, energy, and economy sectors (Aboulnaga et al., 2019). When assessed from the perspective of Turkey, more challenging conditions are the case in each of four scenarios determined for Turkey. In the event that the mean temperature rises 1.5 C, it is estimated that the annual mean temperature of Turkey, especially the Southeastern Anatolia region, will be higher than the annual global mean temperature. As the value of increase gets closer to 4 C, the annual mean temperature values will increase more extensively (Da¸sc¸ıo˘glu, 2021; IPCC, 2021). Climate change also affects precipitation events. Annual precipitation is expected to increase in high latitudes and certain sections of Monsoon regions, and to decrease in the Mediterranean Belt which covers Turkey. In the event that the mean temperature increases by 1.5 C, the precipitation rate in Turkey is believed to decrease 1% 10%. However, if the mean temperature increases by 4 C, precipitation rate is thought to decrease 20% 30% in the Southern Aegean Region and western-central sections of the Mediterranean Region, and 10% 20% in the southern sections of the Central and Northern Aegean Region, Southern Marmara Region, internal sections of the Central Anatolia and the majority of the Southern

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Anatolia. The Black Sea Region is expected to be affected by the precipitation decrease the least. Soil structure is also thought to be affected severely by the increased mean temperature. Furthermore, according to expectations, the land in Turkey will lose more moisture and drought will increase in Turkey, especially in Southern Aegean and Western Mediterranean Region. In the scenario where the mean temperature increases by 4 C, the entire Turkey will witness moisture loss in its land at the highest rate (IPCC, 2021). Although the precipitation projections conducted by GDM for Turkey estimate the occurrence of the aforenoted effects, the precipitation events will happen as anomalies as understood from Fig. 16.3 (URL, 2022). According to RCP 8.5 scenario, the change in annual precipitation anomalies regarding Turkey is expected to range from 13% to 212% for the period between 2016 and 2099. The mean change in precipitation anomaly is believed to range between 15% and 21% for the first half of the century and 11% and 218% for the second half of the century (URL, 2022).

16.2.1 Climate change effects on buildings One of the climate change elements that has often been neglected is built environments. Construction activities and buildings mean using excessive amount of raw materials. Global resources are limited, and it is not possible for these resources to supply the construction sector at the same rate of consumption for an indefinite period of time. Raw materials for construction activities should be received, processed and transported before the phase of installation. Energy supply is necessary for each of these phases, which results in CO2 emissions (Booth et al., 2012). Accordingly, buildings are among the primary reasons for climate change, being responsible for 33% of global GHG emissions. To sum up, a vicious circle exists between buildings and climate change since buildings’ energy consumption contributes to climate change and as changing climate conditions result in more energy

Figure 16.3 Turkey’s annual total precipitation percentage change range (URL, 2022).

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use. Many studies have examined the effect of climate change on buildings’ energy performance. The contrast between buildings’ heating and cooling demands is believed to be more important due to climate change, despite depending on the location where the relevant building is located (Bamdad et al., 2021). However, the effect of climate change on buildings and building systems is not solely related to energy consumption/use. Extreme weather events will affect user comfort including the indoor comfort conditions, material and durability of the building envelope, and operation of the building systems [such as heating, ventilation, and air conditioning (HVAC)]. Future events that will arise from climate change may weaken buildings’ structures, increase the collapsing risk for some buildings, reduce buildings’ mean lifespan and therefore risk the dwellers and decrease buildings’ values. The effects of climate change on buildings are expected to increase with the risks and other impacts that will increase in time. Additionally, probability of collapsing will increase for certain buildings due to increased storm severity and danger of erosion and salty water penetration in the coastal locations below the sea level (Alfraidi, 2015). Also, the other effects of climate change is flooding. The future increase in damages is due to both a projected increase in the frequency of (climate-driven) hazards (in the case of floods) and increased exposure in vulnerable areas. Elevating buildings, elevating door and window openings, creating floodable buildings, and improving the structure and material of the walls, foundation, and frame are all common approaches recognized in the literature for increasing the structural resilience of buildings to fluvial flood damages. Also, the material of a building is an important factor in determining its physical vulnerability to flood damage. For example; using of soil makes the buildings extremely vulnerable to flooding (de Ruiter et al., 2021). According to literature a lot of studies highlights the climate change flood risk by means of how affecting the building systems, which precautions should have taken etc. One of these studies is show a first global database of FLOod PROtection Standards, FLOPROS, which comprises information in the form of the flood return period associated with protection measures, at different spatial scales. FLOPROS consists of three layers of information that are combined into a single consistent database. The design layer contains empirical information about the actual standard of existing protection; the policy layer contains information on protection standards from policy regulations; and the model layer calculates protection standards using a validated modeling approach. The policy and model layers can be considered adequate proxies for the actual protection standards included in the design layer, and they serve to increase the database’s spatial coverage (Scussolini et al., 2016). Bello et al. (2018) presented a literature investigating the impact of climate change-induced flooding around buildings in Nigeria. At the end of the study, they suggest the efforts of all stakeholders in the built environment to cooperate among themselves in order to achieve the achievements of the climate change flood adaptation approach in Nigeria to achieve a sustainable built environment. The main flood adaptation strategy includes using built defenses to prevent and mitigate the impact of floods on the built environment, raising river banks and flood walls, creating adequate storage reservoirs and channeling the flood passage, and installing standard drainage system

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on roads (Bello et al., 2018). In another study, Claudia (2014) stated that flooding, coastal erosion, subsidence, and drainage systems necessitate new building techniques and materials in order to withstand adverse weather conditions (Claudia, 2014). One of these techniques is “boardwalk.” This connects the homes, rises and falls with floodwaters, and acts as the spine to which the houses are connected has been designed as a flood adaptation technique in residential buildings. The boardwalk creates a continuous circulation network and serves as a literal and symbolic representation of what people require in a time of crisis—access to one another. A shared raised foundation between two buildings creates a protected area above the prescribed flood level, protecting vehicles and gardens from floodwaters (Anthonia et al., 2021; Claudia. 2014). Creach et al. (2020) aims in their study comparing the different adaptation strategies in terms of cost of implementation and efficiency in order to reduce the vulnerability of houses to flooding. The strategies are classified as; (1) protection, (2) relocation, (3) architectural adaptation of housing, and (4) preventive warning and evacuation. This work is applied to La Gue´rinie`re, an Atlantic coastal town at risk of coastal flooding despite the fact that Storm Xynthia did not affect it. The preliminary findings indicate that the most effective strategy for reducing housing vulnerability to coastal flooding is also the most expensive. The strategies are as follows, ranked from most efficient and expensive to least efficient and expensive: (1) relocation, (2) housing architectural adaptation, (3) protection, and (4) preventive warning and evacuation. Until now, these strategies have been limited because they do not account for human behavior in coastal flooding scenarios. As a result, this study investigates the role of human behavior in relation to various mitigating measures (Creach et al., 2020). In another study, Shahid et al. (2017) examined the effects of climate change risks on buildings to help the shareholders in Malaysia give the necessary reactions to reduce the adverse effects in this regard. Accordingly, increased temperatures may affect buildings’ paint and external polish, which will result in the need for frequent maintenance. As increased temperature and moisture will result in higher precipitation rate, the concentration of the indoor pollutants will increase. Pressed wooden and similar materials will have changed formaldehyde emission rates which will decrease in time. Increase in main temperatures will result in the buildings getting heated extremely, which will cause increased electricity demand for artificial cooling. Accordingly, operation building expenses will increase. Along with the urban heat island effects, increased temperatures arising from climate changes will worsen the case in metropolises (Shahid et al., 2017). The intense precipitation events predicted by climate change models may have direct effects on properties. The risk of water penetration from external walls will increase, affecting the buildings’ surface integrity. Intense precipitation will affect the plastered buildings more than coated ones (Lisø et al., 2003). The cavity wall insulation, which is often recommended to increase buildings’ thermal efficiency, may actually make buildings more vulnerable to rain penetration under intense weather conditions. To solve this problem, more cavities may be needed in the insulation structure (Sanders & Phillipson, 2003), all of which may increase the capital and maintenance costs. In addition to higher precipitation and temperature, extreme precipitation and temperature may worsen the circumstance. The combination of

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increased temperatures and changed precipitation events may change the humidity levels, which may result in mold stains, harmful organism growth, paint-related issues (such as peeling), eroded plaster joints and faulty plaster, etc. (Shahid et al., 2017). Another effect of heavy precipitation is triggering the wind so it causes heavy damages on building facades and elements. One of the related studies is conducted by Lacasse et al. (2020). The study discussed the effects of climate change on buildings and presented an examination of the studies on the materials and durability of building envelopes considering the potential effects of climate change on the longevity and durability of these products in time. The assumptions regarding the sustainability of buildings were also discussed taking into account the potential impacts of climate change on the durability of buildings and building components. In that study conducted for Canada, the frequency and intensity of future precipitation events, severity of peak wind loads and extreme wind frequency will increase, which will affect buildings’ external facades; moreover, facades will be exposed to more intense climate loads lasting for a longer time, which will increase the risk of early distortion for building elements, such as roof, wall, and window systems, and increase the risk of failure due to moisture-related issues arising from water penetration to building elements (Lacasse et al., 2020). Also, the increased salt rate in land due to the rises in sea level, which is another impact of climate change, may harm the houses, buildings, and other structures in the coastal regions as the bricks, plaster, and concrete elements get distorted due to the salty water crystallized in these components. In addition to the metal elements, pipes, cables, and other infrastructure elements in the structural underground concrete elements may be corroded. Moreover, the building foundation may move or even go down, resulting in structural cracks, damages, or collapses. In addition to the aforenoted suggestions, this study recommends renewing the current HVAC climatization designs as they will be insufficient in climate change scenarios. In the case of climate change, the new risk maps may suggest that the properties that were considered to be risk free are actually exposed to potential risks. Therefore while planning and developing new properties, the regions under flood risk and coastal flood regions should be mapped within different climate change scenarios (Shahid et al., 2017). From the differences of energy demand point of view, in the literature many research can be seen. Moazami et al. (2019) examined the effects of prospective extreme conditions on building performance in Geneva, Switzerland. Results indicated that the relative peak cooling load increase may reach 28.5% under extreme conditions when compared to typical weather conditions (Moazami et al., 2019). Another study conducted by De Masi et al. (2021) considered different emission scenarios for a housing case study simulated in the southern Italian city of Benevento and created certain future climate projections in the medium (2050 s) and long (2080 s) term. In the long-term projection, the heating degree days will decrease 21%, while the cooling degree days will increase more than twofold, suggesting a significant transition to dominant cooling climate for Benevento. In addition, considering the climate change, insulation interventions as well as double-glazed and

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low-emission window installation are not flexible actions because heating energy demand decreases by 56% while the cooling energy demand increases by 162% (2080 s). If the efficiency measures also include cool roof and external shading elements, cooling demand may decrease as much as -33% in certain cases (De Masi et al., 2021). The same study mentioned the efforts by Gonza´lez et al. (2020) for the historical buildings. According to that study, annual energy consumption is expected to increase approximately 15% until 2050 to conserve the historical artworks due to increased relative humidity concerning the historical buildings (Gonza´lez et al., 2020). Verichev et al. (2020) analyzed the changes in climate regions for the buildings in three regions of southern Chile under two prospective climate scenarios (RCP 2.6 and RCP 8.5). According to that study, heating energy consumption for a house hosting a family will decrease by 13% and 27% on average for the scenarios RCP 2.6 and RCP 8.5. In addition, studies on assessing the changes in climate regions were presented on a smaller scale, and it was understood that the buildings’ heating load would decrease and cooling load would increase along with the increased indoor thermal discomfort for all geographical regions (Verichev et al., 2020).

16.3

Climate change flood risk analysis and effects on buildings

The economic risk associated with flood and earthquakes increased significantly on the global scale. “United Nations Office for Disaster Risk Reduction” (UNISDR, 2009) defines this risk “as the probability of harmful results or expected losses (deaths, injuries, properties, means of living, disruption of economic activities or environmental damage) arising from natural or human-triggered dangers and interactions under sensitive conditions (UNISDR, 2009). Climate change risks affect the built environments, and as the built environments are connected to many systems, all these risks emerge in different forms in different areas. Flood is one of the natural disasters caused by climate change that occurs as a result of human activity and poses a risk to human life, property, and the built environment. While such risks cannot be entirely removed, climate change adaptation can help to limit extreme climate exposure and vulnerability while also preserving the built environment. The main causes of floods generally are intense and/or long-lasting precipitation, dam break (e.g., glacial lakes), reduced conveyance due to landslides, or by an intense local storm (Bello et al., 2018). According to the international disaster database, flooding occurs more frequently than all other types of natural hazards worldwide, accounting for 39% of all natural disasters since 2000, affecting over 94 million people worldwide each year (Guha-Sapir et al., 2018). According to the WMO, while economic losses from flooding have increased over the last 50 years, loss of life has decreased significantly due to improved monitoring and forecasting of hydrometeorological hazards. (Wu et al., 2020). Flooding and windstorm events around the world have raised awareness of the importance of better planning and designing buildings and infrastructure to reduce vulnerability to climate extreme

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events. To address the risks of climate change, Aliyu (2010) advised that building professionals (architects, planners, builders, and engineers) should collaborate with climatologists/meteorologists. Clearly, the built environment and its infrastructures have been identified as vulnerable to climate change due to higher temperatures, erratic and variable precipitation, rising sea levels, and wind actions, all of which have impacts on the environment’s surface as well as varying impacts on the built environment. (Anthonia et al., 2021). The ability of a city built on a prairie wetland’s politicians, policymakers, and citizens to adapt to climate change will necessitate holistic approaches to water management, land regulation, and the ecosystems of its lake and rivers (Platt, 2018). In this context, climate change risk analysis, which ensures the important information for preventing area/building against an extreme event, such as flood, is crucial. For a risk analyzing by means of climate change factor, climate change projections, data, and risk maps are used in general. The literature indicates that the risk studying intensify on the effect of flood, which is an immediate event, in the scope of climate events. Also, building-level flood preventing measures are frequently designed with the base flood elevation in mind (de Ruiter et al., 2021). By examining the literature, many studies highlight the flood damages on building facades and elements. In the one of these studies, Shah et al. (2013) examined the severe floods that occurred in Pakistan in 2010 and reported that the housing stock affected the most was the collapsed adobe houses that resulted in the highest number of human and animal deaths. The adobe houses damaged by the floods in the relevant regions were analyzed, and the main reasons for the collapse of such houses were determined based on the field studies and observations. Authors recommend raising the level of houses, terminating the cavities within walls, increasing wall thickness, and using soil, sand, and clay to reduce the risks arising from floods (Shah et al., 2013). Balasbaneh et al. (2020) analyzed the sensitivity of construction materials toward flood risk in Malaysia, aimed to reveal the degree of loss for each building, and assessed the vulnerability of the materials. The following materials were assessed the most: brick, concrete block, steel wall panels, wooden wall, and precast concrete frame. The lowest and highest flood depth figures affecting wall construction were 25 and 150 cm, respectively (Balasbaneh et al., 2020). Escarameia and Tagg (2021) developed the flood management frame based on the INTACT project and presented a frame consisting of the basic and substeps of risk analysis, risk assessment, and risk management. The authors examined three different methods for risk assessment within this frame. Called “quick scan,” the first method, as its name suggests, is the process of “first transition” that helps determine the buildings or elements which are under the greatest damage risk and which are easy to cope with and that results in affordable interventions. The second method is related to the provision of the information and instruments necessary for selecting and assessing the flood resistance and durability options to be used in critical buildings. The third method or instrument (to be more specific) is the Individual Building Flood Damage tool utilized to predict the damage in detail (Escarameia & Tagg, 2021). Buildings along Turkey’s coast will be vulnerable to flooding. Buildings that have been damaged by coastal flooding often have wind damage as well. Water

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driven by hurricane-force winds may enter a building through particularly sealed openings, and rain penetrating through a damaged roof can damage the indoor area and, in some cases, expose the building to dangerous water-borne pathogens. All sources of damage, particularly those related to water penetration into the building envelope, should be considered during the planning process. It is worth noting that coastal flooding is not the only cause of direct physical damage caused by tropical cyclones and other weather events. As a result of all weather hazards identified during the design and planning stages, all building projects have adequate risk management (Sarıcıo˘glu & Ayc¸am, 2021). To sum up, risk analysis direct the attention to the greatest risks or the areas where the risks are distinctive the most, helping determine the relative importance of the risks that are not associated with climate. In conclusion, when risk analyzing are spatially performed, they may be more helpful for decision makers in prioritizing the climate risk and developing relevant adaptation strategies related to spatial planning (Connelly et al., 2018).

16.4

Case study about a “flood” risk analysis in Ankara

As noted in the previous section, a flood risk analysis is performed for Ankara. The reason for selecting Ankara is that it is the capital city of Turkey with continental climate and that Ankara is believed to be affected by climate change more than other Turkish cities according to the data from the relevant literature. For that purpose, the “flood” risk present in the climate change projections of GDM for Turkey was selected in the risk determination phase. The reason for selecting the flood risk is that precipitation anomalies will occur for Turkey as noted by GDM (URL 4). ArcGis was used first within the borders of Ankara to determine the riskiest region/neighborhood/building group through the risk analyses, and the riskiest region was found using the mean monthly precipitation data that was obtained from GDM and covered the period between 2019 and 2020 (Table 16.1). Table 16.1 only reflects the mean values regarding Ankara. Furthermore, the data regarding the districts (or currently neighborhoods) of Ankara which are Akyurt, Altında˘g, Aya¸s, Balˆa, Beypazarı, C¸amlıdere, C ¸ ankaya, C ¸ ubuk, Elmada˘g, Etimesgut, Evren, Go¨lba¸sı, Gu¨du¨l, Haymana, Kahramankazan, Kalecik, Kec¸io¨ren, Kızılcahamam, Mamak, Nallıhan, Polatlı, Pursaklar, Sincan, Sereflikoc ¸ ¸ hisar, and Yenimahalle were obtained, and a general risk mapping was performed for Ankara using all of the data. Due to the absence of sufficient building data set, the building scale could not be utilized at this step, and therefore the assessments were conducted at the neighborhood scale. Fig. 16.4 displays the flood risk map that was analyzed in line with the precipitation data regarding Ankara and covering the period between 2019 and 2020, and that was formed using ArcGis. As the building data set was limited in the study, relevant buildings were added to the legend. According to the analysis result, the districts facing the highest risk were C ¸ amlıdere and Kızılcahamam. Mean values as well as the slope and elevation figures, geological characteristics and soil traits

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Table 16.1 Monthly precipitation data of Ankara as obtained from General Directorate of Meteorology. Station_no

Station_name

Year

Month

Total_monthly_ precip._mm

17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130 17130

Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region Ankara region

2019 2019 2019 2019 2019 2019 2019 2019 2019 2019 2019 2019 2019 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020

1 2 3 4 5 6 7 8 9 10 11 12 13 1 2 3 4 5 6 7 8 9 10 11 12

40.8 36.1 38.1 29.3 31.5 37.8 30.9 27.2 0.3 6.7 20.4 58.6 357.7 20.6 64.7 21.2 22.1 65.2 103.3 5.3 0.0 4.5 27.8 5.1 16.0

were considered for the flood risk. To be more specific, re-weighting should be conducted and analysis should be repeated using the analytical hierarchy process for a better quantitative analysis. In the second phase of the risk mapping, risk analysis was performed for Kızılcahamam and C¸amlıdere districts based on the results from the flood risk map of Ankara, and downscaling efforts were made, as seen in Figs. 16.5 and 16.6. When compared, precipitation rate of 2020 was lower than that of 2019 as understood by comparing two random data sets. Although not much difference was present between two maps, feature-related data showed the precipitation rate decreased in 2020, and analysis was performed accordingly (Fig. 16.7). The same analyses and comparisons were also performed for C¸amlıdere district, and efforts were made to determine the building group, but downscaling efforts were limited due to insufficient data. Also, as seen in Figs. 16.8 and 16.9, the result is as same as Kızılcahamam. It can concluded that precipitation rate for C ¸ amlıdere tends to decrease when comparing 2019 and 2020.

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Figure 16.4 Flood risk analysis regarding Ankara and covering the period between 2019 and 2020.

Figure 16.5 2019 flood risk map created with ArcGis for Kızılcahamam.

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Figure 16.6 2020 flood risk map created with ArcGis for Kızılcahamam.

Figure 16.7 Comparison of risk maps for Kızılcahamam for the period between 2019 and 2020.

According to the analysis results, the mean precipitation rate of 2019 was higher than that of 2020. Moreover, the number of areas that seemed risky due to precipitations decreased to a certain degree in 2019 because the precipitation rate also

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Figure 16.8 2019 Flood risk analysis and building groups for C¸amlıdere.

Figure 16.9 2020 Flood risk analysis and building groups for C¸amlıdere.

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decreased. The eastern sections of the buildings (the east of the study setting) indicate a shrinkage in the intensity of the areas seeming risky in 2019 compared to 2020 because the precipitation rate also decreased. A better result can be obtained when the building set is established. If the number of criteria is increased, analysis through weighted superposition method will yield different results. Although the result from the analyses covered the recent era (2019 20), the precise effect of climate change is still clear. The present study showed that the precipitation rate fell and would fall in future. The projections and adverse effects of climate change on buildings can be summarized as displayed in Fig. 16.10. As noted in Fig. 16.10, high temperature, which is one of the climate change parameters, will affect buildings’ air conditioning and cooling systems, as well as how these systems work and the capabilities of these systems. The need for cooling will increase and the buildings’ energy demands will change with the increased temperatures. Moreover, the need for natural and artificial shading will also increase. Another impact of temperature increase is the change in indoor comfort conditions which may require more cooling and suggest the use of air conditioning and other alternative solutions. Precipitation anomalies and increased humidity, which are the other effects of climate change, will particularly affect the facades and facade systems. Building envelope materials will be adversely affected by extreme humidity, in the form of corrosion and fungi growth, meaning their lifespan and durability will decrease. Similarly, extreme temperatures will distort the structure of plastic-based facade materials, shortening their lifespan. As one of the regional or local results regarding precipitation anomalies, flood effect will particularly affect and damage the buildings on the coastal regions and their foundations.

Figure 16.10 Climate change effects on buildings and building equipment.

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Although precipitations decrease in the predetermined regions as understood from the result of the Ankara projection, analyses should be performed in the regions which are found to be risky on the building scale. Other than that, it is safe to state that the adverse effects arising from the extreme temperatures will also apply to the buildings in Ankara because the temperatures are expected to increase in the city. Energy and humidity analyses should be performed with various scenarios on the building scale for a more detailed risk analysis.

16.5

Future trends

Climate change will affect the building systems, building and operation systems. As noted above, most of the scientific studies bear the objective of analyzing buildings’ cooling and heating demands based on the idea of increased temperatures seen in prospective scenarios. Therefore future studies should focus on innovative materials and technologies to decrease the need for cooling energy. In addition, increased temperature and precipitation anomalies will alter certain parameters regarding building designs, according to estimations. For instance, design parameters, such as building location, as well as the amount of receiving solar radiation, facade clearance rate, thickness, and durability values regarding the layers of facade materials, adequacy of natural-superficial ventilation, needs regarding the indoor comfort conditions, presence, and dimensions of shading elements should be analyzed separately for climate scenarios, and design should be planned later. Furthermore, setting new threshold values and promotion strategies is important and necessary for the designers, researchers, and construction sector in terms of the most effective energy renewal assessments. In conclusion, changes in climate conditions will make the current design strategies insufficient. This study demonstrated that the spatial risk analyzing is important for targeting the adaptation responses and that it is beneficial for spatial planning. However, finding spatial data to follow a risk-based approach is challenging, and there is an information deficiency regarding the risks arising from climate change for the cities and regarding the potential adaptation reactions (Connelly et al., 2018). Using climate change scenarios and performing risk analyzing will be necessary for architects and engineers to ensure the adaptation of buildings to prospective climate risks and to determine the measures to be taken in the buildings to be constructed. In addition, various states have begun to take actions to reduce and limit CO2 emission and other substances harming the atmosphere. To play a key role in reducing or mitigating disasters, the future of construction sector should adopt sustainable development by using less, utilizing available resources efficiently by reusing and recycling. Production of sustainable construction materials can have a significant role in terms of neutralizing the adverse effect of climate change. Furthermore, to cope with the immediate results of flooding, current housing stock should be kept, new houses should be planned and constructed to be more durable to climatic events, and the selection of convenient construction materials may be key in fulfilling this goal (Booth et al., 2012).

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Acknowledgments We are grateful to “General Directorate of Meteorology” for ensuring the necessary information and permission for this article.

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Amphibious housing as a sustainable flood resilient solution: case studies from developed and developing cities

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Iftekhar Ahmed Department of Architecture, BRAC University, Dhaka, Bangladesh

17.1

Climate change and flood vulnerability

The effects of climate change are already visible; it is beyond argument now. The exigent question has already shifted from “whether” and “if” climate change is taking place, to “how much” and “to what extent.” It transcends mere regional boundaries and is affecting the global socio-economic-political systems altogether. Climate change has both active and passive attributes. It is imperative to find out the possible areas/grounds that are to be affected and in which way. Climate change impacts, ongoing and future, both in global and local contexts, should be examined in a cross-disciplinary manner; considering the sociological, economic, and technological fields. A better understanding of the climate change issues will essentially help to plan a sustainable future embracing the future changes. Various studies have confirmed that severe climate change impacts, such as increased and varied precipitation, along with related factors, such as temperature and sea level rise, will highly impact and make infrastructure in the world more vulnerable in the future (Balica et al., 2012; Neumann et al., 2015; Wilbanks & Fernandez, 2014). In some regions, climate change has altered precipitation patterns (i.e., intensity, frequency, and duration of rainfall), leading to an increased frequency of extreme rainfall events (Christensen et al., 2007). These extreme rainfall events are the major triggers of flash floods, which can impact important urban infrastructure systems, such as storm water systems and dam. These destructive rainfall-induced flooding events are among the deadliest and most expensive weather-related disasters. The vulnerability of flooding in terms of exposing population and assets has increased dramatically over the last few decades. Flood as a natural disaster and its destructive impact has reached a new high. Flood vulnerability triggers economic, environmental, and social effect in floodplain area (Gad-el-Hak, 2008). It implies that people, society, property, and the environment are suffering more and more from the dangers of flooding (Dang et al., 2011). This study aims to explore amphibious housing as a sustainable flood resilient solution with case studies from developed and developing cities. Adapting the Built Environment for Climate Change. DOI: https://doi.org/10.1016/B978-0-323-95336-8.00011-1 © 2023 Elsevier Ltd. All rights reserved.

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Research methodology

To measure the comparative performance of amphibious housing as a sustainable flood resilient solution in the selected developed and developing cities, the study uses a set of selected indicators from the components of Baseline Resilience Indicators for Communities (BRIC). The BRIC is generally used to measure impact of projects on communities and adopt a refined version of the Disaster Resilience of Place model developed by the Department of Geography and Hazards and Vulnerability Research Institute, University of South Carolina, United States, in 2008 (Winderl, 2014). The BRIC analyzes community level resilience to natural hazards using a comprehensive set of indicators under broad categories, such as ecological, social, economic, institutional, infrastructure, and community competencies (Winderl, 2014). This study uses the selected BRIC indicators to determine the specific elements of resilience in the three case study cities. This study selected case studies of amphibious housing from developed to developing cities to get a comprehensive grasp of the relevant issues under various flooding conditions. The aim was to explore whether the level of development; economic condition and technological advancement in particular, had a role to play on the performance of the amphibious housings. Only a selected few indicators from each category were selected for the study a measuring all the indicators were beyond the scope of the study. In addition, a few new physical components were added for its relevance to the projects as they sheds light on the physical elements of the amphibious housing projects in the three cities. Primary data from field studies conducted in 2018 19 were complemented by secondary data where primary data was found to be inadequate to reach a conclusion. Qualitative methods, such as unstructured interviews and focus group discussions, were used to find out the community response to the selected indicators where possible. Qualitative methods suited the purpose of the study better as they facilitated addressing the core issues with more complex questions compared to quantitative methods. Focus group discussion in particular facilitated a sense of ownership for the relatively new living conditions and allowed for a deeper understanding of the situation. Unstructured interview facilitated more relaxed, and thus more forthcoming and resulted in in depth understanding of the issues. It also had the added advantage of pursuing an issue not included in the formal list of questions but was crucial apparently. In case of few indicators, this was complemented with secondary data from case studies and archival research. A limitation of the comparative study was the various degree of flood hazards happening in the three selected cities. This was overcome by complementing the community responses with secondary and archival data to come to better conclusions.

17.3

Adaptive techniques to combat flash floods: a comparative analysis

People lived near the edge of water for millenniums for convenience of trading, fishing, etc. They considered the local climate and tidal conditions during

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construction. The fighting and mitigating flood vulnerabilities dates back to the origin of species and it is one of the most important attributes of human species. Forecasting the occurrence of flash floods is often seen as one of the most challenging tasks in hazard forecasting for meteorological researchers (Doswell et al., 1996). Resilience to extreme flooding events has various related issues rather than only about physical exposure. Two cities may face identical physical exposure to a climate-related hazard but show widely differing characteristics of vulnerability because of their network’s topological and physical characteristics, therefore potentially impacting their resiliency and coping capacity substantially (Solomon, 2007). There is a wide array of strategies to fight, prevent or mitigate the destructive impacts of floods in urban and peri-urban areas. Through typological comparative analysis, this section illustrates the various choices that people made to live near or over water and their comparative advantages and disadvantages (Table 17.1). All of the five techniques discussed have their comparative advantages and disadvantages. One recent factor outweighs the advantages for the first four techniques; the unpredictable rising water level during flash floods. Turner and Overland (2009) stated that Global warming greatly contributes to inconsistency in rise of sea level, inconsistency in flood height. As a result, elevated houses with a static design becomes inefficient to combat an extreme flood event with unusual flood level. This can be an example of the inadequacy of the existing techniques to combat floods. Comparatively floating or amphibious buildings offer a more flexible approach to combating flash floods.

17.4

Amphibious housing: origin and development

Amphibious living existed in vernacular cultures since time immemorial (Hack et al., 2010). With the advent of climate change, there has numerous contemporary cases of amphibious housing in countries, such as the Netherlands, Thailand, and Jamaica, and in several other countries of North America (English et al., 2021). The amphibious living has been proven to be more sustainable, reliable and more convenient compared to more conventional houses with permanent static elevation (Penning-Rowsell, 2020). More recently, disasters, such as the Hurricane Katrina, have forced the architect community to think “out of the box” to design for disaster struck areas. Morphosis Architects designed the prototype prefabricated affordable float house for the “Make it Right” Foundation in the Hurricane Katrina struck flood prone lower Ninth Ward of New Orleans. The amphibious house has a flexible design with a floating foundation. It can float with rising water levels so that it remains afloat and can withstand the most severe floods. The prototype design can be used in any flood zone throughout the world (English et al., 2016; ergodesk, 2009). The “amphibious house,” a recent innovation in hydrological living, has the potential to play a critical role in the future of flood adaptation. Although people have lived near the edge or over water through the ages in various forms, the design

Table 17.1 A comparative analysis of adaptive techniques to combat floods. Adaptive techniques

Features

Dry-proofed and wet-proofed buildings

They anticipate temporary floodwaters and protect buildings from flooding using low-tech strategies. Both methods require knowledge of potential flood levels and flood frequencies. Dry proofing methods work to keep water completely out of the building, making the building watertight. Wet proofing strategies enable water to enter the buildings, raising ground’s elevation above the flood datum. In both of these cases, structural walls, which will receive additional water loads during a flood, must be waterproof and capable of handling anticipated unbalanced forces; without additional structure (Kreibich et al., 2005).

Shore-side buildings

These buildings are located near waterways and uses a variation of dry proofing. They must anticipate changing water elevations; their structure must consider changing water pressures and building details must prevent water infiltration. Rather than protecting all four sides, these buildings usually focus on protecting the side facing the water. All openings are placed above flood datum level. Water proofed exterior materials are used.

Illustration

Sites with high water tables

A water table in between 60 and 70 cm below grade is maintained. This depth helps prevent the water table from suddenly rising above grade causing nearby buildings to flood. This technique fails when the elevation is below sea level, there is a lack of necessary storage capacity or inadequate pumping capabilities.

Elevated buildings

These buildings replace a typical slab-on-grade or pile foundation with a column foundation, raising the structure above either dry ground or an existing water body. The elevation is above the predicted high water levels. The use waterproofed foundation, all gaps to be sealed and friction piles to take the water pressure.

Floating buildings

There are two basic types: floating buildings that constantly float and amphibious buildings that rest on riverbed or land, floating only in high water conditions (Vermeer, 2022). Both require a buoyant and waterproof foundation. They are typically tethered to stationary moorings and remain at a particular location only moving vertically with rising water level.

Source: author.

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and development of amphibious housing is rather contemporary, with cases spanning over the last two or so decades. They were primarily developed to tackle the problem of flooding, especially flash flooding and create opportunity to live in a place with a high risk of water damage. Primarily pioneered by the Dutch architects, the key idea was to convert crisis into opportunity by living with water and not against. This innovation in hydrological living challenges the “accepted” norm of living on dry land during floods (leaving the property vulnerable) and creates opportunity to live in a place with a high risk of water damage and overcomes the traditional threats that flooding poses (English et al., 2017). From the conception, the idea was to live with water and not against it. To tackle the recurring problem of flooding in the Netherlands, which impacts the low-lying areas in every few years; the Dutch architects converted crisis into opportunity through this innovation. Forty six floating houses were developed on a Governmentdesignated flood-overflow plane in the Maasbommel area near the Maas River of the Netherlands. They were designed by architect Chris Zevenbergen of Factor Architecten, a design firm based in Amsterdam, with the Dutch construction company Dura Vermeer, a pioneer in hydrological constructions (npr, 2008). The project envisioned a future where hydrological living can become a reality for places highly vulnerable to flash floods. The amphibious houses were designed with option to sit on the ground for most of the time, with the capacity to float on the floodwater, and then returning to its exact original position while the flood recedes. The amphibious houses allow an otherwise-ordinary structure to float on the surface of and with the rising floodwater while the amphibious foundation retains the connection with an anchor to the ground by resting firmly on the soil under usual circumstances. The key principle of amphibious houses is that any house that can be elevated can be made amphibious. The key idea of floating architecture is to coexist with nature, not to fight it (Nekooie et al., 2018). A typical Dutch amphibious house is designed from single to double storied, having a split-level design with a living room facing the water on the lower level along with kitchen and other utilitarian spaces and bedrooms at the upper level. The houses are generally made of wood to reduce self-weight so that they are easier to float during floods. In common terms, they are not floating per se, rather their innovative foundation enables them to float and rise with the changing flood level (Varkey & Philip, 2022). The amphibious houses have a low ceiling basement generally constructed with a seventy watertight-hollow concrete box that works as an underwater air buoyancy chamber, just like the hull of a boat; helping the house to keep afloat during a floods and ensuring stability (Urkude et al., 2019; Varkey & Philip, 2022). During normal climates, the foundation sits on dry land. When the water level of the rivers rises to flood level, the house can gradually float up with the water table and withstand a rise of up to 5.5 m, which covers beyond the normal flood conditions in Netherlands. When the floodwater subsides, the houses return to their original position. Six 5.5-m-long heavy iron posts are rooted into the ground below water to withstand the strong currents of the water under various conditions and secure the house which are approximately 300 m2 in plan. The iron posts are outfitted with shock-absorbent materials to minimize the feeling of movement from nearby waves in the living areas. Flexible pipes adapted to

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move with force of water, keep the house connected to building services and utilities, such as electrical, water, and sewer lines. This solved the issue of maintaining uninterrupted energy supply for the houses to remain habitable during floods (INHABITAT, 2007). The Dutch floating houses are often prefabricated, square-shaped, two to threestoried townhouses built offsite. Conventional materials, such as steel, timber, and glass, are used (Rubin, 2022). There have been other special approaches to amphibious and floating housing. Waterstudio (2022), a Dutch firm specializing in floating architecture, has recently constructed a floating housing development in Male the very low lying capital of the Maldives. As almost 80% of the country sits barely less than 1 m above sea level, the housing adopts a simple and affordable design for 20,000 people. To help support marine life, underneath the hulls will be artificial reefs. In addition, to aid airconditioning systems, the floating houses will pump cold seawater from the deep sea. The impacts of climate change are a reality and people must prepare for it. To get a better understanding of the development of amphibious living thus far under various socio-economic conditions, the experiences from the Netherlands, Thailand, and Jamaica are presented here followed by a comparative analysis.

17.5

Amphibious living: the Dutch experience

The Netherlands (Dutch word neder means “low”) is a small densely populated land area with low elevation, and a major part of it, located in the north and west, is either at the same or even below the sea level (less than 1 m above sea level). About half of its land mass is only 1 m above sea level and much of it actually below (home-l2.tiscali.nl). In places, such as the Netherlands, that are highly vulnerable to storm floods and storms, amphibious living offers a lifestyle in flood defense that allows vulnerable communities to better withstand impacts of climate change. Many countries with worsening floods are seeing growing interest in amphibious living as a solution. While some of them are highly flood-prone nations, such as the Maldives, others have various low lying flood zones. Recent floods and heavy storms show that floating communities of Netherlands, such as Schoonschip, have a better capacity to withstand the natural hazards. During recent events, the residents stored sufficient food and water and endured as their neighborhood floated up and down the anchored steel foundation pillars. Once the rising water receded, they descended back to their original position with little or no effect on their everyday lifestyle. As part of the climate change adaptation, the Dutch government undertook “Room for the River” program in 2006, strategically allowing certain areas to inundate during heavy rain. It was a paradigm shift that seeks to embrace, rather than resist, flooding and rising water levels. Rotterdam, a Dutch delta city 90% below sea level has been promoting floating buildings as one of the pillars of its Climate Proof and Adaptation Strategy. The city promotes water as an opportunity instead of as an enemy (Fig. 17.1).

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Figure 17.1 Dutch amphibious house: top—during flood; bottom—in normal condition. Source: Author.

According to Nienke van Renssen, an Amsterdam city councilor, the Dutch municipalities are expanding the concept of amphibious living as it is a sustainable way forward with multifunctional use of space for housing (Rubin, 2022). Inspired by the success of floating housing projects, the Dutch engineers are aspiring to go for larger-scale multifunctional floating projects, such as small floating cities. Another potential benefit of amphibious living is it offers a solution to shortage of land for housing, especially in coastal areas or on riverbanks where floating houses can significantly expand buildable land to combat climate change (Fig. 17.1). Floating houses could potentially alleviate pressure on the shortage of land available for housing. According to Koen Olthuis (Rubin, 2022), the founder of Waterstudio, a Dutch architectural firm specialized exclusively on floating architecture, one of the key advantages of floating houses is they are relatively low tech and do not require high level of specialization or training to build. This makes the construction cheaper as well. With his experience of designing more than 300 floating houses, offices, schools and healthcare centers, Olthuis goes on to compare the opportunity presented by floating architecture to expand cities on water with that of vertical expansion of cities with the invention of the elevator (Rubin, 2022). Previously neglected neighborhoods are gaining newfound property value with the advent of floating houses, creating opportunities for sustainable urban forms. Schoonschip, a floating community of 30 houses on a canal in a dilapidated manufacturing area, was designed by Space & Matter, a Dutch firm. The residents use ferries to commute to central Amsterdam. They share resources, such as transportation and food. Each building is self-sufficient with heat pump and a third of the roofs devoted to greenery and solar panels. Community members even sell their surplus power to the national grid. Amphibious living has its own set of challenges. The Dutch architects and engineers faced numerous challenges in creating amphibious architecture. The floating buildings rock significantly during strong wind and rain, or even the passing of large cruise ships in the coastal projects. Most residents shared that they got used to the discomfort

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eventually. In terms of utilities, such as connection to electricity grid and sewer system, floating houses requires more infrastructure and effort than regular houses. As they are below the level of regular municipal services, they require special waterproof cords and pumps to link to municipal infrastructure on higher ground. In cases where there is no existing infrastructure, new microgrids had to be built from scratch (Rosso et al., 2020). Despite the challenges, most specialists are optimistic about the future of floating houses. Rutger de Graaf, the director of Blue21 (Rubin, 2022), thinks the growing number of storms, floods and other natural disasters has spurred the policymakers, urban planners and residents to search the water for solutions. He feels that billions of dollar could be saved globally when amphibious living becomes more widespread and eventually the benefits may outweigh the costs. He is optimistic that more and more people will opt to choose expansion onto the water rather than leaving the property and moving to higher ground during disasters. Especially with the grim forecast for the second half of the century, when hundreds of millions of people will be displaced by rising sea level; there is an urgent need to increase the scale of floating developments.

17.6

Amphibious living: the Thai experience

17.6.1 Flash floods in Thailand Southern Thailand, with a low elevation (5 10 m on an average) from the sea level, is a part of a narrow peninsula with a distinctive local climate and terrain. The region has been highly vulnerable to flash floods throughout its history. The main factors behind are the topography of the region, increased rainfall due to La Nina and land uses located in historically flood prone areas. In March 2011, a severe active low pressure cell caused intense rainfall over the region resulting in a series of unprecedented flash floods in Chumphon, Trang, Phang Nga, Krabi, Surat Thani, Nakhon Si Thammarat, Songkhla, Patthalung, Narathiwat, Yala, and Satun. Landslides and mudslides happened in the surrounding areas (OCHA, 2011a). This resulted in 20 deaths and 842,324 people being affected at various degrees by the disaster (OCHA, 2011b). In other areas of Thailand, flood occurred in communities with no history of floods or floods occurred unseasonally in flood-prone areas. The recent floods were much higher and hit the communities with far greater intensity than in the past. To manage floods and flood disasters in future, the government of Thailand developed the National Water Resources Management Strategies. Strategy 3 aims to reduce the damage from flood disasters in urban communities and significant economic areas, relieve the damage and support the adjustment in agricultural areas, reduce the damage from the landslide, and flash flood (ONWR, 2018). As a part of the strategy, a series of amphibious houses were developed.

17.6.2 Amphibious houses of Thailand History shows that settlements of Siam (former name of Thailand) has always been situated along the rivers. It was not a coincidence that western merchants who

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visited the region called both Ayutthaya and Bangkok “Venice of the East” (Iamtrakul & Thongplu, n.d.). To combat floods, these riverine communities built their houses either with stilts or as rafts. Two significant changes make this natural choice challenging. First, modern communities developed primarily on land with roads which means that solutions had to found where houses sit on ground and survive the floods. Second, even for the communities that live by the river till now, building houses on a fixed level with stilts or as rafts may not work due to the greater intensity and suddenness of the floods that came with the recent climate change. There has been many cases where flood exceeded the fixed level of stilts or the houses on rafts were washed away by floods (Morita, 2016) (Fig. 17.2). A permanent solution had to be found to help the communities to be able to live with the rising water level during floods. Few communities of Southern Thailand had been building their houses on rafts or short pilings. The idea was embraced by Thai architects as a starting point. Site-specific company limited, a Thai firm specializing in amphibious houses, designed some of the first amphibious houses of Thailand in the Ban Sang village in 2013 using prefabricated steel floatation system. The floatation system sits in the trench under the house so that the entire system remains hidden during normal conditions and the houses look usual in their surroundings. Another advantage of the trench is that it can collect water during rain. During flood, as the water level rises, the depressed area gets inundated first and gradually the house becomes prebuoyant (WordPress, 2021) (Fig. 17.2). The houses are constructed using prefabricated panels with steel framing; allowing a strong construction yet being much lighter than traditional houses (Fig. 17.3). To survive floods, the amphibious houses have built-in back-up systems for power generation, rain water and food storage. A lattice system has been used to tie 5 to 10 houses together to a form a mini community during floods so that they can selfsustain for a longer period without depending too much on external help. The amphibious houses were tested in flood conditions. The spaces below the foundation were filled with water and they rose 8.5 cm (WordPress, 2021) (Fig. 17.4).

Figure 17.2 Amphibious house in Ban Sang village, Thailand. Left—normal condition; right —during flood. Source: Author.

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Figure 17.3 Thai amphibious house, exploded axonometric drawing showing various parts. Source: Author.

The Thai amphibious houses were designed to be cost effective and can be built in various types of flood prone areas of Thailand. They do not interfere with the everyday life of the residents. Another advantage (compared to traditional Thai houses built on stilts) is that the guide posts are not visible in the landscape and thus not disruptive. As floating units, more sustainable and economic materials, such as large gallon jug to expanded polystyrene (EPS), were used. The frame holding the buoyancy EPS is attached to floor structure of the houses. The flexible mooring poles not only help the houses rise up with water but also keep the houses in their place. The residents have the freedom to choose the structure type depending on whether the houses are located in rural or urban areas according to their convenience (Nilubon et al., 2016).

17.7

Amphibious living: the Jamaican experience

17.7.1 Flood prone areas of Bliss Pastures and Port Maria Jamaica, the small island state with a large vulnerable low-lying coastal areas and river deltas, ranks 20th in the 2016 World Risk Report (Garschagen et al., 2016) as a country exposed to multiple disasters. Some of the most common disasters are

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Figure 17.4 Thai amphibious house, exploded axonometric view when inundated. Source: Author.

tropical storms, hurricanes, and floods. Jamaica has the second highest economic risk exposure to two or more hazards according to the 2008 update of the Natural Disaster Hotspot study by the World Bank (Dilley et al., 2005). Historical record confirms that the recent greater frequency of flooding in Jamaica is associated with impacts of changed climate. The four most common types of floods affect Jamaica: flash flood, riverine flood, tidal flood, and ponding. In Jamaica, common techniques to combat floods are either to build walls to keep the water out, build elevated structures, or evacuate, none of which is a sustainable solution in the context, as seen in recent floods of Jamaica (Gleaner, 2010) where the failed once floodwater crossed the estimated limit, resulting catastrophic consequences. Amphibious housing takes a completely different approach. They adapt a nondefensive, affordable, and proactive flood mitigation strategy, which considers the historic data of flooding and work in sync with nature (Treehugger, 2009). A shift of attitude is required to adapt, the shift of attitude from conquering or dominating

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nature to the attitude of adapting to it. Olthuis and Keuning (2010) explain that compared to all the common approaches to flood mitigation (such as building barriers or houses on stilts), the key advantage of amphibious housing is that sustainability comes naturally being on water. It treads lightly on the site, leaving very little footprint. Case study was conducted in Bliss Pastures and Port Maria, two small cities with a few rivers. Both communities are highly vulnerable to flooding, especially flash flooding in its low-lying and flood prone areas. During the heaviest rainfalls 10- to 20-cm water accumulates in these areas according to Jamaica’s National Meteorological Office. In both the areas, floodwater collects in the community after passing through other areas. During floods, residents need to evacuate their houses and take shelters in governmental facilities, such as schools. There have been serious dangers to public health in the form of occasional casualties during the heaviest floods, buildings tumbling when water reaches roof level and pit latrines overflow causing serious health hazards. These communities are some of the most floodprone areas of Jamaica. Unfortunately, the residents are not solvent enough to leave and continue to inhabit in these areas. Compared to the uncertainty of relocating to flood shelters or higher grounds, the community members welcome the prospects of retrofitted or newly built amphibious houses. However, the construction or retrofitting is challenging due to the accompanying administrative corruption, ambiguous land ownership pattern, etc.

17.7.2 Amphibious houses of Jamaica As new construction (as attempted in Netherlands) would be too expensive for the local communities, retrofitted amphibious houses were considered an alternate. Target was to come up with a prototype design solution to retrofit existing houses at an affordable price below US$5000 (Turner & English, 2015). A team of researchers led by Scott Turner and Elizabeth English from University of Waterloo, Canada, collaborated with CARIBSAVE, an NGO with long background of working with several low-income communities across the Caribbean to find a sustainable solution for amphibious houses. The first phase of the field study explored the communities that were highly vulnerable to flooding and their existing capacity to handle floods were identified. An extensive survey was conducted to find out Jamaica’s existing housing typologies, neighborhood patterns, life style, social system, and cultural preferences in communities. The methods of construction and construction materials used were also explored (G’meiner, 2012; Turner & English, 2015). The second phase of the field study was to develop strategic design strategies for amphibious housing that would be suitable for the local communities. The two main parts of the study were, first to understand the design, technical and social issues, such as existing social capital in communities, and second to understand architectural, engineering, and overall urban planning issues. As part of the design stage of the second phase, the Buoyant Foundation Project team (buoyantfoundation, 2018) made several notable refinements were required to suit the local

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conditions with consultation with a local civil engineering consultant who had a better understanding of the conditions and construction possibilities. Local vernacular building typologies and construction techniques were integrated with the floating technologies already used in Louisiana post-Hurricane Katrina. As new construction would be too expensive, prototypes were to be developed to retrofit existing houses. Target was to adapt the already practiced buoyancy strategies of Louisiana to find the most economically and technologically suitable option for the local context. After a vetting process by the expert of hydrology and fluid dynamics, the team decided on a sustainable vertical guidance system that could resist any lateral horizontal movement of the houses during severe floods. Finally, a set of design solution were developed based on the data and analysis provided by the local engineering consultants. It was decided from the inception of the project that the proposed solution had to be low-cost, sustainable, and replicable for and by the local communities. The retrofit solution was cost-effective as it used local construction practices and locally available materials to convert existing regular houses of various conditions to amphibious houses in both the communities. The typical vernacular Jamaican houses are built with pier-and-beam construction system with wood joists and beam platforms. On the foundation piers, either a standard size rectangular block of timber or concrete masonry unit is used. One limitation was that the retrofit was only possible in the regular houses with a minimum level of elevation above ground where assembling a buoyant foundation was possible. Houses with slabs on grade was omitted in the process as it was not possible to retrofit (Fig. 17.5).

Figure 17.5 Jamaican retrofitted amphibious houses of Bliss Pastures and Port Maria when flooded. Source: Author.

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In the retrofitted assembly of the buoyancy elements below the floor structure, a tie of structural substrate to the floor with a vertical guidance system is used to reinforce the structural system and restrict lateral movement during floods or high tides. Marine plywood strapping was placed perpendicular to the floor joists to secure the buoyancy elements. The existing structural joists of the houses were secured with sill beams with galvanized steel hurricane ties (Turner & English, 2015). The existing timber telephone poles where used to stabilize lateral movements. This provides enough stability and enabled the houses to rise, float, and descend during floods. Depending on availability and convenience, wire mesh “cages” containing recycled jugs or EPS were used. In places where labor cost is higher for the first process, the type of buoyant technology adopted should be context sensitive. Construction technique with EPS is relatively simpler. Study showed that while the first technique is ecologically sustainable, the second one is 65% less expensive (Fig. 17.6).

Existing house New steel channel reinforcement for sill beam Existing sill beam

Steel double-angle “T” beam Secondary steel framing to support buoyancy blocks Diagonal bracing Coated EPS buoyancy blocks Telescoping vertical guidance post

Sleeve for VGPs Screen for water-borne debris Existing pier

Figure 17.6 Top—schematic drawing of components of a retrofitted amphibious house in Jamaica; bottom left—during dry and bottom right—during flood conditions. Source: Author.

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Two different approaches of constructing the retrofitted buoyant foundation were used in Bliss Pastures and Port Maria. As the communities of Bliss Pastures were more economically challenged, cost effective, safe, and structurally sound materials and construction techniques were used. Comparatively, in Port Maria, more traditional yet cost-effective methods were used. From the outset, using Styrofoam was out of question as they are expensive. Five gallon jugs were used in lieu for buoyancy as they are recycled and easily available, inexpensive, and most importantly; the residents could fit it by themselves (Turner & English, 2015). Cages of galvanized steel “chicken wire” were created to frame and hold the jugs in repetitive modules of 3 wide and 4 deep. They were attached to the marine plywood strapping connected below and vertical to the floor joists. The houses of Bliss Pastures approximately 370 jugs, giving 6990 kg of buoyancy. This exceeded the buoyancy calculation by more than 30% (Turner & English, 2015). Comparatively, in Port Maria, common buoyancy blocks of EPS were retrofitted below the existing floor structure. The retrofitted amphibious foundations (including labor and materials) and other construction cost varied in the two communities. The average cost was US$2414 ($90.24/m2) in Bilss Pastures. In Port Maria, it was US$3765 ($93.81/m 2) on an average. A significant saving in cost was possible where voluntary labor was available. In Bliss Pastures, the reduced cost was US$1199 and in Port Maria, it was US $2064. Overall, the costs seemed affordable for the communities for permanent houses. Especially in comparison with the hassle of flood damage repair, cost and safety issues of relocation, the retrofit approach to amphibious houses proves a low-environmental impact and economically sustainable solution (Turner & English, 2015). From the outset, the key goal was to make sure that the construction was not complicated so that the residents can replicate the process in future. Capacity building in the communities was crucial for future flood-resilient housing. The NGO and other agencies were only involved for a limited period, ultimately handing over the responsibility to the local communities. Findings of field study show that there have been other successful cases of postdisaster intervention by the agencies. Amphibious housing technology is becoming an acceptable, innovative, and sustainable flood mitigation solution gradually.

17.8

Comparative analysis

This section makes a comparative analysis of the three cities using the BRIC indicators to analyze the performance of amphibious houses. The comprehensive set of indicators are arranged under broad categories, such as ecological, social, economic, institutional, infrastructure, and community competencies, responsibility to the local communities. The results are shown here in Table 17.2.

Table 17.2 A comparative study of amphibious houses. Netherlands

Thailand

Jamaica

Compatible. Highly connected.

Compatible. Moderately connected. Walkable. Mixed. Clustered and detached in cases. Safe. Adequate for most of the aspects.

Detached.

Either a watertight-hollow concrete box that works as an underwater air buoyancy chamber or buoyancy EPS used. Hidden by submerged level and landscape. Prefabricated. Vacation house. Not flexible.

Recycled barrels and galloons tied together in a frame.

Physical components Compatibility with existing urban fabric Walkability between buildings Clustering of the structures

Walkable. Highly organized and clustered.

Safety of housing infrastructure Adequacy of water supply, sanitation, first aid, sleeping, food storage, electric power, latrine/W.C., per 20 persons Foundation

Highly safe. Adequate for all aspects.

Visibility of Foundation

Hidden by submerged level and landscape.

Prefabricated versus Retrofitting Use as home Flexibility

Prefabricated. Primary home and vacation house. Highly flexible to be used as other functions.

Either a watertight-hollow concrete box that works as an underwater air buoyancy chamber or buoyancy expanded polystyrene (EPS) used.

Not walkable. Detached. Moderately safe. Inadequate.

Visible in cases. Retrofitted. Primary home. Not flexible.

Infrastructural components Shelter capacity

Maintains standard shelter capacity.

Evacuation potential (arterial miles/mi2) Housing age (built since 1970 94)

Easy to evacuate. Well connected with existing fabric. Mostly built after 1990s.

Maintains standard shelter capacity. Easy to evacuate. Well connected with existing fabric. Mostly built after 1990s.

Exceeds shelter capacity. Not easy to evacuate. Rescue required in some cases. Mostly built during the 1970s and 1980s.

(Continued)

Table 17.2 (Continued) Netherlands

Thailand

Jamaica

Each building is self-sufficient with heat pump and a third of the roofs devoted to greenery and solar panels. Uninterrupted.

Have solar panels on roof.

Not energy self-sufficient.

Interrupted.

Interrupted.

Recent hazard mitigation plan (yes/no) Flood ready participation (yes/no) Municipal expenditures (fire, police, emergency services)

Yes.

Yes.

No.

Yes. Fully municipal supported expenditures.

Yes. Not supported.

Resilience during flood

Highly resilient.

Yes. Partially municipal supported expenditures, especially fire, and police. Resilient.

Effect on livelihood

Uninterrupted.

Moderately interrupted.

Savings in construction

None.

None.

Affordability

Highly expensive costs in the range of US $300,000 400,000 (Mestemaker, 2012). Another study shows a 120 m2 of living space costs in the range of US$295,500 354,600 (pencil-roving. blogspot.com).

Moderately expensive

Disrupted. Need external assistance. Significant savings as the houses are retrofitted. Affordable. A 200 m2 house with recycled materials costs in the range of US$2000 3500.

Energy self sufficiency

Energy supply during flood

Institutional components

Resilient.

Economic components

Social components Quality of life Safety, health and well-being Social order, cohesion and community interaction

Highest. Highest. Highest. Highest level of community support in the form of cluster living.

Medium. Medium. Medium. Limited cohesion and community interaction exists.

Poor. Poor. Poor. Houses are sporadic, especially the retrofitted ones, making cohesion and community interaction challenging.

No.

Yes.

Yes.

Yes. Yes.

No. No.

No. Yes.

High. Full support from community during emergencies.

Moderate. No support.

High. No support.

Accepted as a permanent living solution. Cluster houses possible. It offers the advantages of group survival. Cluster houses support each other in case of individual houses fall short of supply.

Tentative. Cluster houses possible

Tentative. Individual houses

Built-in back-up systems for power generation, rain water and food storage

Not available.

Community components Previous disaster experience (PDD, yes/no) Social connectivity (yes/no) Sense of place (born in state and still live here) Social capital Community emergency response from its own resources Community acceptance Community living Community support

Source: Author.

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17.9

Adapting the Built Environment for Climate Change

Conclusion

The comparative study shows that one of the main advantages of amphibious living is that it gives the residents opportunity to cope with flood, instead of evacuating (which can be cumbersome and unsafe) or being devastated. The study shows that amphibious houses offer flexibility and mobility. They are not permanent in nature and do not scar the site permanently, offering more dynamic planning opportunities. An amphibious house is highly sustainable as it can make way for a new building when required; it decreases the need for demolition. Amphibious architecture can tackle changing water levels by rising and falling with the high and low tide, making a more sustainable water management a possibility. One of the key challenges for amphibious living to be accepted more widely is the affordability. There is a high contrast of construction cost depending on whether the houses are prefabricated or retrofitted. The current cost of a retrofitted house seems much lower as seen in Jamaica. The cost of a new prefabricated house, as seen in the Dutch examples, seems beyond reach for the economically challenged population of developing countries. As the construction technology, especially that of foundation, is further developed and refined, the overall cost can be expected to fall significantly. Another challenge is to ensure stability. Not only the elements, such as strong wind, rain, and waves, even the passing of large boats, can make the buildings rock, making living uncomfortable. This is more acute in smaller structures. When the footprint of the building is smaller compared to its height, the amphibious houses become highly unstable during flood hazards. This issue must be resolved for them to be more acceptable socially. Amphibious houses require extra infrastructure and effort to connect to the main electricity grid and sewer system and other municipal services on higher ground. They require special waterproof cords and high capacity pumps, making operation expensive in most cases. In some areas, new micro grids have to be built from scratch. To reduce the load on traditional utilities, many amphioxus design partly rely on renewable energy sources. Polystyrene is the most commonly used material for floating foundation. Unfortunately, it is considered a hazardous material for health during both production phase and use. Further research is required to invent more sustainable materials for amphibious structures. Overall, if one compares, the benefits of amphibious living outweighs its challenges. Especially, in the advent of climate change and unprecedented number of storm and flood related disasters around the world, when in the second half of the century, hundreds of millions of people will be potentially displaced by the rising seas level; amphibious living may offer a sustainable solution for urban thinkers and residents. It has the potential to save billions of dollars in disaster mitigation otherwise required. As the solution works both for coastal and inland cities, amphibious houses offer a dynamic array of living solutions.

References Balica, S. F., Wright, N. G., & Van der Meulen, F. (2012). A flood vulnerability index for coastal cities and its use in assessing climate change impacts. Natural Hazards, 64(1), 73 105.

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