Green Infrastructure in Chinese Cities (Urban Sustainability) 9811691738, 9789811691737

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Urban Sustainability

Ali Cheshmehzangi Editor

Green Infrastructure in Chinese Cities

Urban Sustainability Editor-in-Chief Ali Cheshmehzangi , Architecture & Built Environment, University of Nottingham Ningbo China, Ningbo, Zhejiang, China

The Urban Sustainability Book Series is a valuable resource for sustainability and urban-related education and research. It offers an inter-disciplinary platform covering all four areas of practice, policy, education, research, and their nexus. The publications in this series are related to critical areas of sustainability, urban studies, planning, and urban geography. This book series aims to put together cutting-edge research findings linked to the overarching field of urban sustainability. The scope and nature of the topic are broad and interdisciplinary and bring together various associated disciplines from sustainable development, environmental sciences, urbanism, etc. With many advanced research findings in the field, there is a need to put together various discussions and contributions on specific sustainability fields, covering a good range of topics on sustainable development, sustainable urbanism, and urban sustainability. Despite the broad range of issues, we note the importance of practical and policyoriented directions, extending the literature and directions and pathways towards achieving urban sustainability. The series will appeal to urbanists, geographers, planners, engineers, architects, governmental authorities, policymakers, researchers of all levels, and to all of those interested in a wide-ranging overview of urban sustainability and its associated fields. The series includes monographs and edited volumes, covering a range of topics under the urban sustainability topic, which can also be used for teaching materials.

More information about this series at https://link.springer.com/bookseries/16930

Ali Cheshmehzangi Editor

Green Infrastructure in Chinese Cities

Editor Ali Cheshmehzangi University of Nottingham Ningbo China Ningbo, China

ISSN 2731-6483 ISSN 2731-6491 (electronic) Urban Sustainability ISBN 978-981-16-9173-7 ISBN 978-981-16-9174-4 (eBook) https://doi.org/10.1007/978-981-16-9174-4 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

I dedicate this book to Mr. Brownie. I wish him a full life, health, and happiness. Also, I devote this to all those sustainability educators who genuinely aim to make a difference—may their journey and achievements be fruitful.

Preface

There is no doubt about our manifold blunders and the enduring interference in global changes, such as climate change and its impacts on our daily lives. As we are moving quite rapidly towards a more urbanised world, we are expected to face new challenges. In return, we need to be more critical, innovative, and reflective so that our challenges are not mounted up, and we can choose the right pathways for contemporary and future planning and design paradigms. Unfortunately, the start of more sensible concepts such as resilient cities coincided with more popular movements/concepts such as smart cities. If this did not happen, we could have invested more in policies and practices that are more human-environment-centric than those that have developed towards digitalised and technological directions. Yet, we believe we still have time to speed up our progress to enhance the resilience and sustainability of cities and communities worldwide. In light of these recent trends in urban development, we see many opportunities emerging to see how we can first mitigate and not adapt and then reflect on and address issues and not neglect them. We ought to give more room for innovation so that we would intervene more holistically, more reflectively, and with a more technical understanding of the current and forthcoming conditions. The growing number and intensity of natural disasters worldwide remind us of an alarming point where we see the need to do more before it is too late. The valuable lessons and promising technical tools we have in hand could equip us more smartly, rather than just relying on machines. By now, we must know (as common sense) that best practices could be enhanced, our standards could increase, and our genuine sustainability targets could be achieved. Hence, we reflect on these points very cautiously and aim to see how we can utilise green infrastructure more effectively and achieve the ultimate goals of urban sustainability. Under this overarching goal, this edited volume brings together a selection of excellent research work conducted by leading researchers in areas related to GI practices. As you will see throughout the book, we have brought together a range of disciplines, sectors, and viewpoints to ensure our views are not biased and our pathways are informative, integrated, and interchangeable. We hope the case study examples in this edited volume would inform future planning and design directions. We hope integrated solutions could highlight the need to utilise scientific-technical solutions and consider multiple ways vii

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of innovation, improvement, and sustainable progression. We also hope that interchangeability between various viewpoints, sectors/disciplines, contexts, and spatial scales could have in the healthiest possible way, allowing us to innovate new sustainability pathways, or else enhance what we have at present, and reverse some of the recent unsustainable trends. You will see that GI is considered as the central point in this book. And by using China as the case study example, we hope to reflect on some of the ongoing sustainability transitions, policies, practices, and scientific-technical directions for the benefit of cities, communities, and the built environments. Although this book focuses on the context of China, our arguments, findings, and suggestions apply to other contexts, too. The balance that we urge to have been the natural and built environments is not something that can only be relevant to one particular context but is surely something that we need to consider at the global level. If this balance is recreated healthily and maintained to ensure sustainable development is not just human-centric but also an earth-centric approach, we can fulfil the sustainability goals and targets in the right way. If we continue to consider humans at the centre of our sustainability pathways, we are just delaying the end result of decayed environments and a deteriorated planet. Our unjust urbanisation processes and callous urban development have caused immense damage to the environment that needs our care and attention. Our focus on rapid (and presumably never-ending) economic growth has led us to fulfil our never-ending greed while witnessing the many exploitations, degenerations, and exacerbations that are no longer rescindable. Yet, we believe we can do better in the future to avoid repeating the mistakes, to avoid continuing the unsustainable trends, and to avoid embittering where we belong. This book covers a comprehensive range of topics on the topic of green infrastructure in cities, particularly in the context of China. The book includes a diverse range of approaches or ideas, from methodological solutions and advances to policy recommendations and guidelines. We intentionally divide this volume into four interrelated parts: policies, planning, design, and technicality of GI integration in cities and built environments. A scientific approach to better understanding ecological values and enhancing urban ecologies would enable us to investigate our current urban problems with a wider eye and think beyond current practices and guidelines. We are yet to witness impactful development modes and policies that are more than just some generic sustainability ideas, and we believe these can become a reality if we put our minds together and set our hearts on the genuine values of living a healthy and sustainable life. This volume provides us with an inspiring set of chapters, a collection that could help us study GI more holistically and scientifically. Some of the chapters highlight the importance of dynamic interdisciplinary and transdisciplinary approaches to studying GI and its integration in cities and the built environments. Although different from each other, the positions of ecological values and urban ecologies should be considered the heart of environmental sustainability movements and pathways towards achieving urban sustainability. This is particularly relevant to contexts where urbanisation is ongoing and environmental deterioration is unavoidable. The manifestation of innovative and integrated methods could lead us to a more holistic

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urban science and urban studies approach. In doing so, we could find a balance between the natural and the built environments and avoid repeating the same mistakes that resulted in many extinctions, polluted environments, inhabitable conditions, etc. We have to wake the mass by finding ways that sustainability is part of our education, and green infrastructures are not just green spaces where people can play and enjoy their lives. They are places that matter the most in cities, with much more value than any business districts or financial quarters, cultural centres, and commercial/retail zones. They are where we belong, and we are part of those green and blue environments that help us have better and healthier living environments. If we opt to have any other type of living environment, then we are a curse to ourselves and the next generations. We hope this edited volume could benefit future researchers, decision-makers, and practitioners. Therefore, we believe the nexus between academia, government, and practice should become stronger, and our approaches should become more precise, holistic, and respectful to the environment. Our suggestion is to consider scientifictechnical approaches more seriously and understand the values of the environment beyond just living spaces for us, the humans. We have to consider more visionary concepts, long-term plans, and promising pathways to achieve sustainable development and urban sustainability. Thus, we believe green infrastructures and utilising them in our planning and design could help us achieve these. This volume is just a starting point where we could see more innovative and visionary directions than quixotic and unthoughtful directions. We hope this book serves many with new ideas, lessons, and best practices of GI for urban sustainability. To those who do not care, we urge them to stop their obnoxious behaviour. And to those who do care, we encourage them to do more and do not give up! Prof. Ali Cheshmehzangi Head of Department of Architecture and Built Environment (ABE) Director of Urban Innovation Lab (UIL) Director of Centre for Sustainable Energy Technologies (CSET) Network for Education and Research on Peace and Sustainability (NERPS) University of Nottingham Ningbo China (UNNC) Ningbo, China Hiroshima University (HU) Hiroshima, Japan

Acknowledgements

I would like to sincerely thank all the authors and contributors for their hard work and dedication in writing their chapters. So far, I have not had a chance to meet most of the authors here, but I hope we get the opportunity to meet up and collaborate on future research studies. They are all excellent researchers who I wish could become leaders in their respected research fields. I also thank the publishing team for their continuous support. I acknowledge the National Natural Science Foundation of China (NSFC) for funding project numbers 71850410544 and 71950410760, used for material purchase and recruitment of local research interns in China. I also send my appreciation to the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) for the provision of funding for further studies on peace and urban sustainability. Lastly, I thank those who remain as our genuine friends during the hardest times. They know who they are, as one once said so almost 21 years ago.

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About This Book

Since 2014 and the start of the New-type Urbanisation Plan (NUP), we see a turning point in China’s sustainability agenda. One of the main indicators is greening cities and the built environments, which is covered holistically in this edited volume. From the perspective of green infrastructure, in particular, the book approaches key areas of ‘forest city development’, ‘sponge city program’, ‘green roofing’, ‘naturebased solutions’, ‘urban farming’, ‘eco-city development’, etc. This is the first time that such important areas of research come together under the perspective of green Infrastructure and in the context of China. Green Infrastructure in Chinese Cities is beneficial to policymakers, practitioners, and researchers in China and worldwide. The comprehensive set of findings from this book will benefit other countries, as we aim to highlight some of the best practices of the current age. The book’s main aim is to put together an excellent group of scholars and practitioners from the field, focusing on the topic of ‘Green Infrastructure in Chinese Cities’. In doing so, we cover some of the main ‘best practices’. Divided into four parts, the book covers four key areas of (1) Policy Interventions, (2) Planning Innovation, (3) Design Solutions, and (4) Technical Integration. In doing so, we cover an array of best practices related to green infrastructures of various types and their impacts on cities and communities in China. This volume is a valuable resource for researchers in the areas of sustainability, urbanism, urban planning, urban geography, urban design, geographical sciences, environmental sciences, landscape architecture, and urban ecology. The book covers essential factors such as policy, regulations, and programs (in part “Policy Interventions”), planning paradigms and their impacts on urban development (in part “Planning Innovation”), integrated design solutions that suggest sustainable urbanisation progression (in part “Design Solutions”), and technical knowledge that would be utilised for the future development of green infrastructure practices in China and beyond (in part “Technical Integration”). Lastly, this edited book provides a collaborative opportunity for experts and researchers of the field, who could contribute to the future pathways of sustainable urbanisation in China. Lessons extracted from these contributions could be utilised for other contexts, which will benefit a wider group of stakeholders. xiii

Contents

Green Infrastructure and Urban Sustainability: An Editorial . . . . . . . . . . Ali Cheshmehzangi

1

Policy Interventions Policy Intervention on Green Infrastructure in Chinese Cities . . . . . . . . . Jinjun Zhou, Qi Chu, Hao Wang, and Ying Tang

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Urban Forest Planning and Policy in China . . . . . . . . . . . . . . . . . . . . . . . . . . Wendy Y. Chen, Cheng Wang, and Yining Su

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Analysis of Policy and Regulatory Landscapes for Green Roof Implementation in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bao-Jie He, Xin Dong, and Ke Xiong

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The Transformation of the Green Infrastructure Intervention Under the Case of Sponge City Program: Positions, Challenges, and Prospects in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Faith Ka Shun Chan, Lei Li, Ali Cheshmehzangi, Dimple R. Thadani, and Christopher D. Ives

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Planning Innovation Does the National Forest City Policy Promote Haze Pollution Control? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 Chang Xu, Yueming Li, Xinfei Li, and Baodong Cheng Greening by Self-organised Urban Farming: A Productive Paradigm for Urban Green Space in China . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Longfeng Wu Changes of Urban Greenspace Coverage and Exposure in China . . . . . . . 173 Bin Chen and Yimeng Song

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Building Green Infrastructure: Eco-Cities and Sustainable Development Zones in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Bing Wang and Shining Sun Design Solutions Green Exposure as a People-Centered Metric for Green Infrastructures: A Shanghai Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Fabien Pfaender, Francesca Valsecchi, Xiulin Sun, and Wei Chen Comprehensive Evaluation of Green Infrastructure Restorative Practices for High-Quality Transitional “Sponge Node” Renewal Programs in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 Jing Sun, Ali Cheshmehzangi, and Sisi Wang Countermeasures and Empirical Research on GI Network Construction of Coal Cities in the Eastern Plain . . . . . . . . . . . . . . . . . . . . . . 299 Xiangxu Liu and Linlin Wei Strategies and Tactics for the Design of Green Infrastructure in the Public Realm of Chinese Cities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323 Fin Church, Siyan Zhang, and Yu Ye Technical Integration Smart Technologies for Urban Farming and Green Infrastructure Development: A Taxonomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379 Saeid Pourroostaei Ardakani, Hongcheng Xie, and Xinyang Liu Integrated Decision Support System for Sponge City Management: A Case Study of the National Demonstration Area of Guangming District, Shenzhen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 Yan Wei, Jiping Jiang, Jingxian Lai, and Yunlei Men Applying Multiple Nature-Based Solutions (NBS) with Regional Flexibility in Bio Building Design in Southeast China . . . . . . . . . . . . . . . . . 431 Minjia Fan and Ali Cheshmehzangi Nature-Based Solutions for Transforming Sustainable Urban Development in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469 Linjun Xie Towards Sustainable Urban Green Infrastructures . . . . . . . . . . . . . . . . . . . 495 Ali Cheshmehzangi Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 507

Editor and Contributors

About the Editor Ali Cheshmehzangi is a Professor of Architecture and Urban Design with a Ph.D. Degree in Architecture and Urban Design, a Master’s Degree in Urban Design, a Graduate Certificate in Professional Studies in Architecture, and a Bachelor’s Degree in Architecture. He is an urbanist and urban designer by profession and by heart. He studies cities and city transitions, sustainable urbanism, and integrated urban design strategies. Ali is Head of the Department of Architecture and Built Environment, Director of the Centre for Sustainable Energy Technologies (CSET), and Director of Urban Innovation Lab at the University of Nottingham Ningbo China (UNNC). He is also a Specially-Appointed Professor at Network for Education and Research on Peace and Sustainability (NERPS), Hiroshima University (HU), Japan. Currently, he works on two research projects on ‘Integrated Urban Modelling Framework’, and ‘ICT-based smart technologies for resilient cities’. Some of his previous projects are ‘smart eco-cities in China and Europe’, ‘low-carbon town planning in China’, ‘green infrastructure of cities’, ‘nature-based solutions in China’, ‘toolkit for resilient cities’, ‘sponge city program’ and ‘green development in China’, ‘low carbon and climate-resilient planning’, and other urban transition studies. So far, Ali has over 125 published journal papers and nine other published books. His books are titled Designing Cooler Cities (2017, with Chris Butters), the

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award-winning Eco-Development in China (2018, with Wu Deng), Sustainable Urban Development in the Age of Climate Change (2019, with Ayotunde Dawodu), Identity of Cities and City of Identities (2020), The City in Need (2020), Urban Memory in City Transitions (2021), Sustainable Urbanism in China (2021, with Ayotunde Dawodu and Ayyoob Sharifi), China’s Sustainability Transitions (2021, with Hengcai Chen), and Urban Health, Sustainability, and Peace in the Day the World Stopped (2021). His most recent book is focused on the nexus between Urban Health, Sustainability, and Peace. He is currently writing on ICTmediated platforms for smart-resilient cities.

Contributors Saeid Pourroostaei Ardakani School of Computer Sciences, University of Nottingham Ningbo China, Ningbo, China Faith Ka Shun Chan Faculty of Science and Engineering, School of Geographical Sciences, University of Nottingham Ningbo China, Ningbo, China; Water@Leeds Research Institute, University of Leeds, Leeds, UK; School of Geography, University of Leeds, Leeds, UK Bin Chen Division of Landscape Architecture, Faculty of Architecture, University of Hong Kong, Hong Kong SAR, China Wei Chen Center for Data and Urban Sciences (CENDUS), Shanghai University, Shanghai, China Wendy Y. Chen Department of Geography, University of Hong Kong, Hong Kong, China Baodong Cheng School of Economics and Management, Beijing Forestry University, Beijing, China Ali Cheshmehzangi Faculty of Science and Engineering, Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, China; Network for Education and Research On Peace and Sustainability (NERPS), Hiroshima University, Hiroshima, Japan Qi Chu Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing, China Fin Church Planet Earth Ltd, Ningbo, China; Planet Earth Ltd, Grantham, England, UK

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Xin Dong School of Architecture and Urban Planning, Chongqing University, Chongqing, China; Key Laboratory of New Technology for Construction of Cities in Mountain Area, Ministry of Education, Chongqing University, Chongqing, China Minjia Fan Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, China Bao-Jie He School of Architecture and Urban Planning, Chongqing University, Chongqing, China; Key Laboratory of New Technology for Construction of Cities in Mountain Area, Ministry of Education, Chongqing University, Chongqing, China Christopher D. Ives School of Geography, University of Nottingham, University Park, Nottingham, UK Jiping Jiang Shenzhen Municipal Engineering Lab of Environmental IoT Technologies, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China Jingxian Lai Shenzhen Howay Technology Co., Ltd., Shenzhen, China Lei Li Faculty of Science and Engineering, School of Geographical Sciences, University of Nottingham Ningbo China, Ningbo, China Xinfei Li School of Economics and Management, Beijing Forestry University, Beijing, China Yueming Li School of Economics and Management, Beijing Forestry University, Beijing, China Xiangxu Liu School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China Xinyang Liu School of Computer Sciences, University of Nottingham Ningbo China, Ningbo, China Yunlei Men Shenzhen Zhishu Enviornmental Science and Technology Co., Ltd., Shenzhen, China Fabien Pfaender Shanghai University, Université de Technologie de Compiègne, UTSEUS, Costech, Compiègne, France Yimeng Song Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China; Smart Cities Research Institute, The Hong Kong Polytechnic University, Hong Kong SAR, China Yining Su Department of Geography, University of Hong Kong, Hong Kong, China Jing Sun School of Civil Engineering and Architecture, Zhejiang University Ningbo Institute, Ningbo, China;

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Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, China Shining Sun Graduate School of Design, Harvard University, Cambridge, MA, USA Xiulin Sun Center for Data and Urban Sciences (CENDUS), Shanghai University, Shanghai, China Ying Tang Urban Construction School, Beijing City University, Beijing, China Dimple Thadani Nottingham University Business School China (NUBS), University of Nottingham Ningbo China, Ningbo, China Francesca Valsecchi College of Design and Innovation, Tongji University, Shanghai, China Bing Wang Graduate School of Design, Harvard University, Cambridge, MA, USA Cheng Wang Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China Hao Wang Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing, China Sisi Wang Key Laboratory of Urban Stormwater System and Water Environment, Ministry of Education, Beijing, China; Beijing University of Civil Engineering and Architecture, Beijing, China Linlin Wei School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China Yan Wei Shenzhen Howay Technology Co., Ltd., Shenzhen, China Longfeng Wu College of Urban and Environmental Sciences, Peking University, Beijing, China Hongcheng Xie School of Computer Sciences, University of Nottingham Ningbo China, Ningbo, China Linjun Xie Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, China Ke Xiong School of Architecture and Urban Planning, Chongqing University, Chongqing, China; Key Laboratory of New Technology for Construction of Cities in Mountain Area, Ministry of Education, Chongqing University, Chongqing, China Chang Xu Anhui University of Finance and Economics, Anhui, China Yu Ye Beijing Forestry University, Beijing, China

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Siyan Zhang Ningbo University, Ningbo, China Jinjun Zhou Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing, China

Green Infrastructure and Urban Sustainability: An Editorial Ali Cheshmehzangi

Abstract Green infrastructure and urban sustainability are correlated in existing scholarly research. In fact, the two cannot be separated from each other. In recent years, China has focused on fast-forwarding achieving sustainable development goals (SDGs), carbon neutrality, and urban greening. These (sustainability) pathways have led to major initiatives such as sponge city development, developing healthier and more resilient cities, enhancing urban green infrastructure, waste management, food security, and finding a harmonious development between the built and natural environments. This chapter is an introduction to this amazing collection, which is very important in urban sustainability. This book focuses mainly on urban green infrastructure, using China as an example for future research, policy development, and practice. Keywords Green Infrastructure; Urban Sustainability; Cities; China; Sustainable Development; Planning

1 Prologue: Green Infrastructures in the Urbanising World In our earlier published work, we only partially discussed the position of Green Infrastructure (GI) in achieving urban sustainability. Nonetheless, we believe GIs could play a much more central role in the journey of sustainable development in cities and the built environment. Thus, we intend to have this volume precisely focuses on GI in cities, using China as an example as a younger leader in this area. Nonetheless, we verify that some of the existing traditional practices and guidelines suggest that China is not necessarily young in this area but perhaps only lost its direction in the process of rapid urbanisation. This is the same trend for any other A. Cheshmehzangi (B) Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, China e-mail: [email protected] Network for Education and Research On Peace and Sustainability (NERPS), Hiroshima University, Hiroshima, Japan © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_1

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rapidly-developing country or context, where we see large-scale urban developments, rapid deforestation, and a lack of concerns for the natural environments. Lessons could be learned before it is too late, and we believe China aims to put itself back to its pathway of finding a balance between the built and natural habitats and humans and nature. This fact, narrated as part of the more recent ‘ecological civilisation’, enables China to rethink its urbanisation plan, find new pathways or innovations for sustainable development, and consider cutting-edge and novel methods in planning and design practices. As noted in our earlier studies on green infrastructures for urban sustainability (Cheshmehzangi et al. 2021a), there is a general concern about the rapid urban development of various types, from urban expansion models to intense in-fill urban development cases around the globe. There are common challenges in every context, where we see growing pressure on energy, climate, societal wellbeing, and the natural environments. We also verified the absence or lack of green infrastructures in developing cities, something that we note very clearly that requires investment, long-term vision and planning, and comprehensive frameworks to ensure GI integration could happen healthily in cities and communities. This concern also touches on other factors such as urban health and environmental sustainability measures. We note that rapid urbanisation methods or rapid urban development scenarios usually lead to unhealthy living environments. We report the significant impacts of careless and unplanned urbanisation on people and the environment, something that for long has shown to be a major concern for urban and environmental specialists worldwide. The adverse impacts on energy use increase, climate emissions, decaying natural environments, polluted habitats, and unhealthy living environments, are only a very few issues that concern us in our journey towards not just a pseudo-sustainability but a genuine one that is not just focused on us, the human beings. Previously, we opted for more integrated methods and directions, which could become healthier pathways for urban sustainability or sustainable development as a whole. We suggested, “approaches that integrate environmental and human/social goals and offer win– win outcomes…[through]…infrastructural requirements, amenities, and qualities: water, sanitation, energy, ventilation, indoor and outdoor urban environment, health, and community” (Cheshmehzangi et al. 2021a). Many advantages of such infrastructural solutions could be summarised in many practices of green infrastructure integration in cities and the built environment. In light of the current progress in technological advancement and ecological science, we note many possibilities are remained to be exploited, tested, and scaled up in the near future. We are hopeful, mainly because we can see new integrated ideas are emerging. More than before, we welcome innovation and critically assess our wrongdoings. With such a mindset, we may set a new mark in human history unless we ignore the mistakes and repeat them. This edited book covers a good range of policies and guidelines that one can use for various purposes. They could be seen as experimental examples for scaling up processes or scenarios, or could be simply become the starting point for policy development or establishing planning guidelines. The nexus between ecological and built environment factors help us reflect on significant micro-climate changes caused by rapid urbanisation and urban development (Makvandi et al. 2019). We could also

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respond to urban health conditions, and avoid unguided urbanisation (Cobbinah et al. 2015) becoming the common practice of many cities and communities worldwide. The examples covered here could also shed lights on the multiplicity and multiobjectivity of the GI practices (Sun et al. 2020). Multiple factors such as governance (Mulligan et al. 2020; Li et al. 2021), accessibility and practical implications (Girma et al. 2019), and social conditions (Cheshmehzangi and Griffiths 2014; Ramyar et al. 2020) could help us consider better pathways for policy development and management solutions (Norton et al. 2015; Cheshmehzangi et al. 2021a). We could opt for more nature-based solutions as planning and design strategies (Li et al. 2021), rather than as experimental small-scaled projects. We also see opportunities for institutional arrangements (Raven et al. 2019) or rearrangements, where it seems to be possible for transferring urban experimentations to reality. Furthermore, we could opt to integrate advanced green technologies in current practices (Cheshmehzangi et al. 2021a), which has been missing or progressing slowly in recent years. Afterward, the book also brings together a range of planning and design practices, particularly important to achieving urban sustainability. We evaluate a range of aspects, such as environmental amelioration, microclimate, and macro-climate issues. Some of these could be addressed by extended GI development and integration in cities and communities and in between them. The continuity of GI in the built environments would help us to enhance urban comfort, health, and wellbeing. These could ultimately improve the quality of outdoor environments and help to enhance amenities and social/community qualities. With many changes occurred from urban growth, we see many pressures on sustainable development (Cohen 2004; Cheshmehzangi and Butters 2017; Butters et al. 2021). Our earlier work highlighted six key issues directly and indirectly linked to the lack of or misapplication of GI in cities and urban environments. These were included in an earlier technical report (Cheshmehzangi and Butters 2015) and later in a published article on GI and urban sustainability (Cheshmehzangi et al. 2021a). These six key issues are summarised as: A. B. C. D. E. F.

Deteriorating urban microclimates with rising temperatures and pollution; Dysfunctional layouts and networks due to rapid and poorly planned development; Piece-by-piece development in large, unconnected and low quality master planning projects; Loss of green/blue urban areas with deteriorating social and recreational services; Massive increases in transport-related land, time, fuel and resource use and climate emissions; and Rapid increase in energy needs (and associated emissions) especially for space cooling.

These are highlighted as problematic trends in urban development in many cities of developing contexts. For many years, such trends have also become the bottleneck to sustainable urban development progression, with often lead to “a lack of planning regulations and support, political willingness, institutional structures, and

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poor management of urbanisation patterns” (Cheshmehzangi et al. 2021a). Therefore, our solutions should better understand the nexus between the environment, health factors, amenities, and community values. These are essential for any practice of GI through considerable planning and comprehensive design solutions. Down the line, we may also be able to find solutions for microclimate, meso-scale challenges, and macro-level issues, through which we could then address multiple global problems. Some of these common issues are the impacts of the urban heat island effect (UHIE) (Stavrakakis et al. 2012; Wong et al. 2015) on cities and living habitats, thermal and climate change (Barrera 2014), and reducing environmental sustainability in cities and the built environments. Other factors, such as GI provision for environmental justice (Zhu et al. 2019), tailoring better progress for enhancing our political ecology (Xie et al. 2020), and achieving more suitable urban transitions towards sustainable development, could also be the by-products of GI consideration, development, and integration in future urban innovations, strategies, and design. Thus, this book covers a range of examples, hoping that some of them could be extended for future sustainable pathways and directions, using GI as the essential but central point of developing healthy cities and communities worldwide. The examples of China’s GI development in cities and/or in various built environments help us to see how urban transitions could occur, how healthy cities can be achieved, and how we can help to reverse some of our unsustainable trends.

2 The Aim and Objectives of the Book This edited book aims to put together a selection of GI-focused studies and case study examples from both industry and academia. The focus is on China’s context but with potential applicability and transferability of ideas to other contexts. In particular, we hope some of these ideas could develop as future directions in other developing countries or emerging economies, where we currently see the absence or lack of GI in planning and design practices. In light of this aim, the book’s objectives are threefold: (1) To demonstrate a range of policy interventions, planning innovation, design solutions, and technical integration of the GI in achieving urban sustainability; (2) To provide a set of guidelines and case study examples for policymakers, practitioners, and researchers in China and worldwide; and (3) To highlight some of the best practices and excel the positon of green infrastructure in sustainable development in cities and communities. Based on these objectives, the book is intentionally structured in the most comprehensive way to cover a range of policies, practices, and directions to ensure we could develop more ideas and visions for integrating GIs in planning and design practices.

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3 Structure of the Book The book is intentionally divided into four parts, each addressing key aspects related to green infrastructures, urban sustainability, and best practices. Each part includes four chapters, including various examples, case studies, or specific frameworks, guidelines, and policies. The selection is made based on the aim and objectives of the book mentioned in the previous section, highlighting the position and direction(s) of green infrastructures in Chinese cities. Each part is important in its own position, and we believe the interchangeability between them will be beneficial to future practices or even for forthcoming policy development. They do not only apply to China’s context and could be related to other developing nations or cities, as well. The beauty of such work is that we could learn from best practices that could become tailor-made or contextualised to speed up the process of sustainable development in other contexts. This is something that China also benefitted from while looking up to global best practices and reflecting on mistakes that caused adverse effects on achieving urban sustainability. The book is a response to how GI could help us achieve urban sustainability, and for this reason, it covers a comprehensive view of GI policies, practices, and directions. Divided into four parts, these factors will be covered to ensure GI development and integration are utilised smartly for future practices and sustainable development pathways. These four parts are structured as (1) Policy Interventions, (2) Planning Innovation, (3) Design Solutions, and (4) Technical Integration (Fig. 1). Fig. 1 Four key areas to study Green Infrastructure (GI) as part of this book’s structure

(1) Policy Interventions

(4) Technical Integration

GI (3) Design Solutions

(2) Planning Innovation

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PART I: Policy Interventions The first part looks into four case study examples of ‘policy interventions’, exploring four key policy areas in Chinese cities, including green infrastructure in general, urban forestry, green roofs, and sponge city programme. These cases are highlighted from the policy intervention narrative. Below is the summary of the four chapters included in this part. Chapter “Policy Intervention on Green Infrastructure in Chinese Cities” By: Jinjun Zhou, Qi Chu, Hao Wang, and Ying Tang The concept of green infrastructure (GI) was first proposed by the United States and gradually developed and applied globally. In China, GI has laid the foundation for green development and related policies, which helped solve the ecological and environmental problems in urban development in China. Many ministries and commissions in China have put forward guidelines related to GI from different professional perspectives and implemented policy intervention in urban planning and development. The relevant policies issued by the Ministry of ecological environment protection and the Ministry of natural resources are more specific and detailed. China’s leader Xi Jinping’s scientific thesis that Green is Gold is the best evidence of GI development in China. China’s Belt and Road strategy and the construction of Xiong’an New Area involve apparent GI policy intervention. However, compared with the top-three global GI systems, China’s GI theory is relatively weak, and the public’s awareness of participation in GI is relatively low. In urban planning, designing, and construction in China, the practical application of GI is limited, especially in conflict with the short-term social and economic interests in urbanisation’s rapid development. Fragmentation and one-sidedness are primary problems in constructing China’s GI. Given these problems, we suggest that China’s GI policymaking should adhere to government-led, encourage multi-party participation, and improve public participation awareness. The goal is to build a perfect GI network and improve the GI service efficiency. Chapter “Urban Forest Planning and Policy in China” By: Wendy Y. Chen, Cheng Wang, and Yining Su Urban forests, in various forms and sizes, have been recognised as an important component of urban landscapes for millennia. Being produced and managed by governmental authorities, they manifest how various policy and planning initiatives have been implemented. This chapter delineates the history, experience, and characteristics of policy guidance pertaining to urban forests and urban green spaces (being an early and still co-existing form) in the People’s Republic of China since its founding in 1949. The chronological roadmap of China’s urban forest can be roughly divided into four phases: (1) piecemeal urban greening and massive deforestation (1949–1979), (2) urban gardening and peri-urban afforestation for landscape beautification (1980–2000); (3) urban forests as a countermeasure to environmental stresses

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(2000–2010), and (4) urban forests as a visual manifestation of ecological civilization (post-2010). It is unquestioned that China is strongly committed to promoting ecological civilization as an innovative paradigm for its sustainable development and a new vision for the global future. The transformation of this political discourse into expected outcomes in urban forest development requires policymakers, scholars, and practitioners to construe urban forests as an integral component in urban transition, a stronghold of civic responsibility, and a key dimension of the nature of human flourishing. Chapter “Analysis of Policy and Regulatory Landscapes for Green Roof Implementation in China” By: Bao-Jie He, Xin Dong, and Ke Xiong Green roofing is a nature-based solution to urban environmental problems and an alternative for urban designers to provide additional spaces for outdoor activities and entertainment under the trend of urban open space reduction. However, several barriers hinder green roofing implementation, including lack of government policy, unsound technological development, high initial cost and long payback period, and individual unwillingness. Governmental policy is the most effective strategy for sustainable initiative implementation by overcoming their barriers. Therefore, this chapter aims to reveal policy and regulatory landscapes for green roofing. In particular, the analysis is conducted in China, a country undergoing rapid urbanisation and severe environmental, economic and social challenges in cities. In particular, this chapter presents an overall picture of policy and regulatory landscapes for green roofing in mainland China across the national, provincial, and city scales, considering mandatory and guiding terms. The analysis indicates that there is no specific national document for roof greening promotion. Nevertheless, in the central government’s guide, opinion, notice, and technical standards and specifications, roof greening is advocated in other projects, such as environmental protection, green building, sponge city, and urban landscaping. Roof greening is mostly mentioned for green space or landscape benefits, but other functions have not been particularly defined. Roof greening has been more clearly framed in province-level technical guide/specification, legislated regulations, governmental opinion, provincial plan, and economic support. The results indicate that the provincial policies and regulations are uneven in geographical distribution, mainly in the east part of mainland China. Technical guide/specification is the main approach to promoting green roofs, followed by the legislated specification, governmental opinion, and provincial plan and economic support. However, among the 25 provinces that have suggested green roof implementation, only ten provinces have clarified the specific requirements of intensive and extensive green roofs. In addition, incentives for green roof implementation have been analysed, indicating that urban greening conversion is the most common way to green roofing promotion at both province and city scales, followed by the fiscal subsidies and then awards. City-level incentives are more inspiring, sounder, and

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more comprehensive than province-level incentives. In addition, the results indicate that while the Urban Greening Ordinance exhibits a strong top-down impact on provincial legislated specifications, the policy and regulatory landscapes for green roof implementation show a strong bottom-up pattern from cities to provinces and then to mainland China. Overall, this chapter is of significance to the understanding of the policy and regulatory landscapes for green roof implementation and provides a reference to the next-step reform of the current policy system. Chapter “The Transformation of the Green Infrastructure Intervention under the Case of Sponge City Program: Positions, Challenges, and Prospects in China” By: Faith Ka Shun Chan, Lei Li1 , Ali Cheshmehzangi, Dimple Thadani, and Christopher D. Ives “Sponge City Program” (SCP), initiated in 2013, is the term in the Chinese interpretation of tackling urban stormwater and surface water management. The concept acts like a “Sponge” to absorb urban runoff and conduct the purification and storage via the restored natural hydrological processes via vegetation, soil, and water interactions. There were frequent and severe urban flood impacts and damages that affect the country during the recent decades after the “Open Door Policy” revealed and rapid urbanisation and developments occurred which see the country. Urban transformation occurs that witnesses their success, but urban surface water floods similarly occurred due to the interruption of the urban hydrological cycle. The current land drainage system cannot cope with climatic extremes. The SCP is similar to Green Infrastructure (GI) that has been commonly adopted in the UK and elsewhere by the practices such as sustainable drainage systems (SuDs) and Low-impact development (LID). The Central National Government (CNG) is ambitious and committed to achieving the major target for reducing urban flood risk. Indeed, there were selected 30 pilot “Sponge Cities” have been adopted the GI measures for the last few years at the first and second stage of SCP. This chapter shares and discusses recent progress, transformation, interpretation, and future development of SCP. In particular, we would like to adopt Ningbo, East China, one of the SCP major pilot cities that is an affluent and rapidly expanding coastal city, as the case for implying the positions, challenges, and prospects of SCP. Lastly, the chapter offers recommendations and foresight that the SCP and GI development further in the third stage (up to 2030s) and beyond, to mitigate future urban water issues in Chinese cities. PART II: Planning Innovation In the second part, we focus more on ‘planning innovation’, particularly specific strategies that help implement and achieve best practices in urban planning. Divided into four chapters, these include forest city planning for pollution control, urban farming, urban greenspace coverage, and application of green infrastructures in ecocity development. Below is the summary of the four chapters included in this part. Chapter “Does the National Forest City Policy Promote Haze Pollution Control?”

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By: Xu et al. Air pollution is a significant issue with global impacts. The implementation of China’s national forest city policy may provide some valuable references for air pollution control. First of all, this chapter introduces the main content of China’s national forest city policy selection. Then, under the condition of considering the time lag effect, spatial lag effect, and space–time hysteresis, it uses the unique and comprehensive panel data of 276 cities in China from 2003 to 2016. In doing so, we use the difference in differences method (DID) and the dynamic SAR model to estimate the policy effects of the implementation of national forest cities on the control of haze pollution. We find that there is an apparent spatial spillover effect in China’s smog pollution. In addition, there is a strong positive correlation between the local smog pollution between the local areas and the surrounding areas in the same period. In this period, the higher the local smog pollution is, the higher the smog pollution in the next period of the local area is. In contrast, the next period of smog pollution in the surrounding is lower. The national forest city policy has improved the level of urban greening and can significantly reduce urban smog pollution. Whether in the long-term or short-term, if a city is selected as a forest city, it will substantially promote the smog pollution of the city and surrounding cities. However, the impact of the national forest city policy on smog pollution also shows cyclical fluctuations, like after each review by the central government, the effect of the national forest city policy to reduce haze pollution will be significantly improved. Chapter “Greening by Self-organised Urban Farming: A Productive Paradigm for Urban Green Space in China” By: Wu China is currently urbanising the largest agricultural population to turn areas of cultivatable land into the urban territory. This has led to many urban issues such as dense community, lack of food security, and limited access to green spaces. Chinese urban dwellers, especially the older generations who lived in rural areas, often deal with the problems in their ways by planting flowers, fruits, and vegetables on any possible grounds within their communities. Such bottom-up, dispersive, and non-institutional activity is defined as self-organised urban farming and is a common - yet overlooked phenomenon—in Chinese cities. The study assumes that urban farming will have great social and ecological potentials if properly guided by designers and will become a new paradigm for urban greening. By investigating Beijing’s self-organised urban farming activities, this chapter aims to provide regulatory recommendations and planning strategies to turn self-organised urban farming into a new urban greening paradigm that engenders more benefits. Three major questions were addressed: What is self-organised urban farming? Why can self-organised farming have the potential to be a productive greening approach? How could self-organised farming green the city by integrating it into current urban greening? Chapter “Changes of Urban Greenspace Coverage and Exposure in China”

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By: Chen and Song Urban greenspace, as an essential component of green infrastructure, is particularly important in the urban environment that maintains the function and sustainability of urbanities. With the rapid economic growth over recent decades, China has been experiencing unprecedented urbanisation processes, at the same time, led to dramatic changes in urban land use and living environment. Therefore, understanding the spatiotemporal changes of urban greenspace coverage and how they impact on population’s exposure to urban greenspace is a critical requirement for supporting urban planning and healthy city development. Although a number of studies have attempted to evaluate urban greenspace changes in China, a comprehensive and multidimensional assessment of urban greenspace coverage and exposure is still lacking. Meanwhile, the emerging geospatial big data provides unique opportunities to quantify the interaction between human activities and the green environment, which has been limitedly addressed. In this chapter, we retrospect some of our recent works on leveraging multi-source remote sensing and social big data to estimate the dynamics of greenspace coverage and exposure change for Chinese large cities. The expected findings will advance our understanding of the following questions in a more systematic way: (1) What is the spatiotemporal pattern of greenspace changes over the past two decades? (2) What is the temporal dynamic and heterogeneity in greenspace exposure? (3) How does urban expansion impact on greenspace exposure experience? (4) Are there any inequalities in greenspace exposure among Chinese cities? Chapter “Building Green Infrastructure: Eco-Cities and Sustainable Development Zones in China” By: Wang and Sun Historically, environmental degradation has often been the cost of concomitant urbanisation and industrialisation. China is no exception. Although China’s GDP has maintained the fastest average growth worldwide over the past four decades, the country has encountered multifaceted environmental challenges, with its ecosystems and biodiversity undergoing large-scale disruption. Since the 1990s, the central government has ushered in a series of campaigns, policies, and regulations focusing on an environmental agenda at different levels. This chapter tracks the shifting propositions of green infrastructure in China’s efforts during the eco-cities movement at the beginning of the 2000s and under the most recent Sustainable Development Zones (SDZs) initiative in 2016. This chapter analyzes the various planning principles, design approaches, and environmental, economic, and social considerations involved in the development of green infrastructure, both conceptually and through the lens of practice, in China’s search for a sustainable urban development model. Case analyses, comparative studies, and data analytics from social media are employed as research methods to examine how the concepts of environmental sustainability and green infrastructure have been evolving under the influence of locational dynamics and temporal characteristics in China.

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PART III: Design Solutions In the third part, we delve into ‘design solutions’ at multiple scales, particularly some urban design strategies that include green infrastructure as part of design thinking or design solutions. Divided into four chapters, this part includes studies on people cantered metrics for green infrastructures, sponge-node renewal programmes, green infrastructure networks, and high-performing green infrastructures. Below is the summary of the four chapters included in this part. Chapter “Green Exposure as a People-Centered Metric for Green Infrastructures: A Shanghai Case Study” By: Pfaender et al. Green Infrastructures refers to components of the built environment, encompassing various shapes and functions from leisure to utilitarian through aesthetics, including elements entirely natural to entirely artificial. In this spectrum of intrinsic natures, purposes, and sizes, green infrastructures are mainly defined as static objects placed into an environment. As such, the definition fails to depict the influence such infrastructures exert on urban dwellers. In this chapter, we propose the concept of "exposure" as a metric that considers green infrastructures not as static outcomes of planning and design but rather as a component of a dynamic relationship involving the citizens. Exposure recognises how many and which kind of infrastructures exist, and, most importantly, how accessible they are and where they are placed in ordinary commuting and living patterns. To validate the concept of exposure, we use a twofold data-driven methodology that combines a Quantitative space analysis approach (from the domain and the tools of urban data science) and a Qualitative Space observation approach (from the field and tools of design and planning). The chapter details the methodology and the quantitative and qualitative data used for the analysis, considering Shanghai as a proof of concept: we provide exposure assessment of 5,000 communities in Shanghai, integrated with fieldwork to detail the nature of each infrastructure and their capacity for interaction. Through this twofold exposure concept and assessment method, we look at the green infrastructures, their presence, and meaning, and understand their role for the community to better inform planning and design solutions from a dynamic perspective. Chapter “Comprehensive Evaluation of Green Infrastructure Restorative Practices for High-quality Transitional “Sponge Node” Renewal Programs in China” By: Sun et al. In general, Green Infrastructure (GI) is described as part of nature-based solutions (NBS). It is not only recognised as a driver in sustainable water management and water resilient city construction, but also for promoting urban ecosystem restoration, climate change adaptation, and enhancing urban liveability and well-being. Due to their multi-objectives and multi-benefits, GI practices and GI-guided land use

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policies have gained attention in China’s Sponge City Program (SCP). Hence, the assessment of hydro-environmental performance is recognised as the foundation of SCP; however, there is a lack of a comprehensive quantitative evaluation system and a design and assessment process model including this evaluation system for high-quality SCP at neighborhood scale. Taking the GI planning of the Liangnong Town, Siming Lake sponge node restoration as an example, this chapter applies the Storm Water Management Model (SWMM) to examine key indicators of hydroenvironmental performance. The findings utilise ten design scenarios to compare the effectiveness of each facility and their combinations in practice. Furthermore, based on Analytic Hierarchy Process (AHP) system, other benefits are quantitatively evaluated through a comprehensive performance analysis of the ten GI scenarios. The final results suggest the most suitable GI general plan for the transitional regeneration of Liangnong Siming lakeside area. Finally, a comprehensive evaluation system is developed to highlight key sustainability indicators and design pathways for high-quality GI design for the neighborhood scale SCP. The chapter’s findings provide a useful reference for similar program’s decision-making and GI design. Chapter “Countermeasures and Empirical Research on GI Network Construction of Coal Cities in the Eastern Plain” By: Liu and Wei The coal cities in the eastern plains have made a significant contribution to China’s economic development. However, the explosive economic growth has severely impacted the environment. The integrity of the green infrastructure has been terribly threatened by the mining activities with the damaged surface and unexpected urban spatial pattern. This paper analyses the existing problems of the green infrastructure in the coal cities in the eastern plain and proposes some countermeasures to build the green infrastructure network. At last, this paper takes Yongcheng as an example, building a GI network based on MSPA, landscape pattern index, and MCR model, aiming at providing a scientific guarantee for the sustainable development of coal cities. Chapter “Strategies and Tactics for the Design of Green Infrastructure in the Public Realm of Chinese Cities” By: Church et al. Core to Green Infrastructure (GI) concept is multi-functionality serving manifold benefits across the environment and society. This chapter presents current design strategies and tactics, mainly spatial strategy, to establish multifunctional green infrastructure in the public space of Chinese cities. The spatial strategy will be used to determine the overall planning and spatial integration of the scheme. It will provide a framework throughout the planning and design process for the sub-strategies and tactics to be considered and executed in parallel with a cross-reference. It is noted that the associated spatial and material qualities of each service category are often interlinked and overlapping. The chapter

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examines the spatial strategy and takes a look at sub-strategies with selected case studies. The findings help develop strategies and tactics for the design of GI in the public realm of Chinese cities. The concluding remarks could be utilised as planning and design guidelines for future GI integration projects in public realms. PART IV: Technical Integration Lastly, in part four of the book, we highlight some ‘technical integration’ opportunities and examples, explicitly looking into newer technical areas that could help fast-forward the inclusion, enhancement, and integration of green infrastructure in Chinese cities. These examples include smart technologies for urban farming, integrated decision support system, integrating nature-based solutions to the built environment, and micro-scale green infrastructure integration in cities. Below is the summary of the four chapters included in this part. Chapter “Smart Technologies for Urban Farming and Green Infrastructure Development: A Taxonomy” By: Pourroostaei Ardakani et al. The need for urban farming and green infrastructure is quickly growing due to the increased population and rapid urbanisation during the past decades. They have the capacity to increase urban farm productivity, enhance fresh food quality, optimise farming resource conservation (i.e., soil and water) and boost the economy. Urban farming and green infrastructure applications can be enriched by advanced smart technologies such as Artificial Intelligence, Machine learning, Telecommunication, and Big data analysis. In China, cities have a great opportunity to benefit from smart technologies in farming to enhance urban sustainability, and life quality as this country rapidly moves on the edge of advanced technologies. This chapter surveys state-of-the-art smart technologies, particularly in the domain of farming and green infrastructure. It outlines the technologies’ advances, benefits, and superiorities and highlights their distinct features, potential trends, and challenges in agriculture applications. Chapter “Integrated Decision Support System for Sponge City Management: A Case Study of the National Demonstration Area of Guangming District, Shenzhen” By: Wei et al. China is currently entering a post-sponge-city era. Determining how to effectively present and manage the construction and operation of green infrastructures is one of the critical issues arising. Decision support systems (DSSs), which combine advanced information technologies such as the Internet of Things (GIS) with environmental models, provide intelligent solutions for integrated management. This chapter presents a state-of-the-art DSS platform of Guangming District, Shenzhen, one of the best national sponge city demonstration regions. In this platform, seven subsystems are integrated according to the requirements of stakeholders, including the big data centre, data mining and comprehensive simulation systems, a 3D sponge city display system, a project lifecycle management system, a performance appraisal

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system, a monitoring system of black and odorous water, and a flood control and drainage management system. The focus of this chapter is the system architecture, monitoring campaign, data processing, model intergradation, and workflows of supervision. The system has been online for one year. The advantages and drawbacks of the DSS are also summarised herein, and the future trends of integrated management in the post-sponge-city era are discussed. This chapter can provide a good engineering reference for smart sponge city management in other cities. Chapter “Applying Multiple Nature-Based Solutions (NBS) with Regional Flexibility in Bio Building Design in Southeast China” By: Fan and Cheshmehzangi With the global population increase, satisfying the quality of living of urban citizens has become a major challenge in urban design and planning. In addition, the environmental damage intensifies rapidly, land sources have been limited, and species diversity is failing. On account of urbanisation expansion, construction is growing to higher levels and underground development, both intensifying density of the built environment. In both cases, we continuously face the reduction of space used for green and blue infrastructures. As a result of living stress, human beings’ physical and mental behaviour are increasingly affected by buildings. The idea of bio building combines ecology and architecture. Based on the local condition, architects/designers and planners can apply buildings with biological characteristics, such as living materials or vegetation and plants. This is one of the common ways close to nature-based solutions and can be utilised for various planning and design projects at multiple scales. China has been one of the fastest populations growing countries. Eco building design has been developed in China since the 1980s. As the increase of sustainable consciousness, experts have considered the relationship between architecture and ecology. Eco building design aims to connect nature with building design, reduce energy consumption and reuse the existing energy. This chapter will discuss the strategies of eco-building design and figure out a feasible ecological cycle in a rural area in China at the micro-level. The chapter focuses on applying multiple naturebased solutions (NBS) for bio building design in Southeast China. The feasibility study benefits from modelling and simulation, demonstrating the benefits of NBS integration at the micro-level, specifically for building energy performance, users’ satisfaction, and sustainable strategies for building refurbishment design. The findings will benefit future research that aims to include NBS as their strategies for refurbishment. Chapter “Nature-based Solutions for Transforming Sustainable Urban Development in China” By: Xie Urban sustainability transitions imply the co-evolution of the integrated social, ecological, and technical systems and can be driven by innovations initiated by

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different urban actors, both public and private. Drawing insights from sustainability transitions and urban governance literature, this chapter explores the potentials of nature-based solutions in transforming urban sustainable development in China, which has been characterised by a state-dominated top-down steering mechanism and a technocratic planning and development pattern. Currently, state-led and modernisation-guided urban sustainability programs and their pilot projects dominate both public and academic discourses on the efforts and promises for a sustainable urban future in China. This chapter argues that with few actual changes in the governance system that largely excludes the civil society and private sector organisations in decision-making and practices, these efforts often fail their promises in advancing transformational changes in urban China. The rush to build ‘eco’, ‘low-carbon, ‘smart’, or ‘green’ cities even generated unintended and negative outcomes on local ecology and community. The rising concept of naturebased solutions encompasses multi-actor dynamics, various forms of interventions, and multiple benefits for people and nature. Its inclusiveness and multi-functionality could draw wider attention and support for non-state-led innovations across Chinese cities, and thus, open up a great opportunity for promoting urban sustainability transitions in China. Lastly, Chap. “Towards Sustainable Urban Green Infrastructures” serves as a summary chapter, concluding with some extracted lessons for sustainable urban green infrastructures (SUGIs). It also highlights selected potential new directions in future research and practice of green infrastructure development in China and elsewhere. China’s progress (to date) is discussed as an emerging model, where we see a larger capacity for more investment, innovation, and opportunities that could lead to more sustainable planning and design solutions. So far, China has proven to be a country that invests and progresses in sustainable developments with a long-term vision (Cheshmehzangi and Chen 2021; Cheshmehzangi et al. 2021a, b), and has gone through a three-decade-long journey in just a decade. From the start of the resilient city movement to the emergence of the sponge city programme and other similar programmes, China has focused on developing many experimental projects, pilot cities, and new policies and practice paradigms. While we believe the journey has just started, we see that China has already developed a solid foundation to what could become a successful model for sustainable development, green infrastructure development, and achieving urban sustainability. Its eagerness to lead on sustainability is something that should not be neglected. Nonetheless, China needs to support North–South and South-South cooperation, developing platforms for knowledge transfer, technology sharing, and a potential shift to global solidarity in sustainable urbanism. While green infrastructure is only a small part of sustainable development, particularly in cities and the built environment, we see it can play a central role in bringing together various disciplines, ideas or innovation, and integrated solutions. Hence, this book brings together a range of ideas from different disciplines, with leading

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experts from both industry and academia. These ideas, policies, and practices set good examples of GI development and its integration in contemporary and future urbanism, particularly to achieve urban sustainability and develop sustainable built environments. For us, China could be recognised as an emerging global leader in the sustainability arena. We expect to extract some lessons from the following 16 chapters in four parts, allowing us to demonstrate strength and opportunities for future development of GIs in China and elsewhere. The following examples would help us to notice the importance of (1) policy interventions prior to any development, (2) planning innovation for integrated and cutting-edge methods, (3) design solutions for successful implementation, and (4) technical integration to think beyond the existing and current policies and practices. This volume helps considering GI to be central in achieving urban sustainability and sustainable development in cities and communities around the globe.

References Barrera LP (2014) Evaluation of prototype “eco-efficient resting place with a bio-climatic design for urban spaces, sede-u version 5” winter and summer efficiency. Energy Procedia 57:2976–2983 Butters C, Cheshmehzangi A, Sassi P (2021) Cities, energy and climate: seven reasons to question the dense high-rise city. J Green Build 15(3):197–214 Cheshmehzangi A, Chen H (2021) China’s sustainability transitions: low carbon and climateresilient plan for carbon neutral 2060. Springer, Singapore Cheshmehzangi A, Butters C (2015) Urban green infrastructure: for cities of developing countries. Technical Report, Part of the ELITH project, pp 1–26 Cheshmehzangi A, Butters C (eds) (2017) Designing cooler cities: energy, cooling and urban form– the asian perspective. Palgrave Macmillan, Singapore Cheshmehzangi A, Butters C, Dawodu A, Xie L (2021a) Green infrastructures for urban sustainability: issues, implications, and solutions for underdeveloped areas. Urban For Urban Green 59(127028):1–18 Cheshmehzangi A, Dawodu A, Sharifi A (2021b) Sustainable urbanism in China. Routledge, New York Cobbinah PB, Erdiaw-Kwasie MO, Amoateng P (2015) Rethinking sustainable development within the framework of poverty and urbanisation in developing countries. Environ Develop 13:18–32 Cohen B (2004) Urban growth in developing countries: a review of current trends and a caution regarding existing forecasts. World Dev 32:23–51 Cheshmehzangi A, Griffiths CJ (2014) Development of green infrastructure for the city: a holistic vision towards sustainable urbanism. Archit Environ 2(2):13–20 Girma Y, Terefe H, Pauleit S, Kindu M (2019) Urban green infrastructure planning in Ethiopia: the case of emerging towns of Oromia special zone surrounding Finfinne. J Urban Manag 8(1):75–88 Li L, Cheshmehzangi A, Chan F, Ives CD (2021) Mapping the research landscape of nature-based solutions in urbanism. Sustainability 13(7):3876. https://doi.org/10.3390/su13073876 Makvandi M, Li B, Elsadek M, Khodabakhshi Z, Ahmadi M (2019) The interactive impact of building diversity on the thermal balance and micro-climate change under the influence of rapid urbanization. Sustainability 11:1662 Mulligan J, Bukachi V, Campbell Clause J, Jewell R, Kirimi F, Odbert C (2020) Hybrid infrastructures, hybrid governance: new evidence from Nairobi (Kenya) on green-blue-grey infrastructure in informal settlements. Anthropocene 29:100227

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Norton BA, Coutts AM, Livesley SJ, Harris RJ, Hunter AM, Williams NS (2015) Planning for cooler cities: A framework to prioritise green infrastructure to mitigate high temperatures in urban landscapes. Landsc Urban Plann 134:127–138 Ramyar R, Saeedi S,Bryant, M Davatgar A, Hadjri GM (2020) Ecosystem services mapping for green infrastructure planning–the case of Tehran. Sci Total Environ 703:135466 Raven R, Sengers F, Spaeth P, Xie L, Cheshmehzangi A, de Jong M (2019). Urban experimentation and institutional arrangements. Eur Plann Stud 27(2):258–281 (Urban experimentation and sustainability transitions) Stavrakakis GM, Tzanaki E, Genetzaki VI, Anagnostakis G, Galetakis G, Grigorakis E (2012) A computational methodology for effective bioclimatic-design applications in the urban environment. Sustain Cities Soc 4:41–57 Sun J, Cheshmehzangi A, Wang S (2020) Green infrastructure practice and a sustainability key performance indicators framework for neighbourhood-level construction of Sponge City programme. J Environ Prot 11(2):82–109. https://doi.org/10.4236/jep.2020.112007 Wong P, Lai P-C, Hart M (2015) Temporal statistical analysis of urban heat islands at the microclimate level. Procedia Environ Sci 26:91–94 Xie L, Mauch C, Cheshmehzangi A, Tan-Mullins M (2020) Disappearing reeds on Chongming Island: an environmental microhistory of Chinese eco-development. Environ Plan E Nat Space. https://doi.org/10.1177/2514848620974375 Zhu Z, Ren J, Liu X (2019) Green infrastructure provision for environmental justice: application of the equity index in Guangzhou, China. Urban For Urban Green 46:126443

Policy Interventions

Policy Intervention on Green Infrastructure in Chinese Cities Jinjun Zhou, Qi Chu, Hao Wang, and Ying Tang

Abstract The concept of green infrastructure (GI) was first proposed by the United States and gradually developed and applied globally. In China, GI has laid the foundation for green development and related policies, which helped solve the ecological and environmental problems in urban development in China. Many ministries and commissions in China have put forward guidelines related to GI from different professional perspectives and implemented policy intervention in urban planning and development. The relevant policies issued by the Ministry of ecological environment protection and the Ministry of natural resources are more specific and detailed. China’s leader Xi Jinping’s scientific thesis that Green is Gold is the best evidence of GI development in China. China’s Belt and Road strategy and the construction of Xiong’an New Area involve apparent GI policy intervention. However, compared with the top-three global GI systems, China’s GI theory is relatively weak, and the public’s awareness of participation in GI is relatively low. In urban planning, designing, and construction in China, the practical application of GI is limited, especially in conflict with the short-term social and economic interests in urbanisation’s rapid development. Fragmentation and one-sidedness are primary problems in constructing China’s GI. Given these problems, we suggest that China’s GI policymaking should adhere to government-led, encourage multi-party participation, and improve public participation awareness. The goal is to build a perfect GI network and improve the GI service efficiency. Keywords Green infrastructure (GI) · Chinese cities · Policy · Green development · Sustainable development

J. Zhou (B) · Q. Chu · H. Wang Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China e-mail: [email protected] Y. Tang Urban Construction School, Beijing City University, Beijing 100083, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_2

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1 Green Infrastructure (GI) Development in China 1.1 The Background to the GI Concept Since the 20th Century, most countries have experienced rapid urbanisation with the emergence of megacities. At the same time, the problems of extreme weather, air pollution, soil erosion, water pollution, environmental pollution, and ecological environment damage caused by urban sprawl and rapid expansion have become increasingly prominent. In order to deal with the above problems in urban development, in the mid-1990s, the United States put forward the concept of GI based on the dual goals of smart land conservation and smart economic growth. In May 1999, the U.S. President’s Council on Sustainable Development identified GI as one of the five strategies for sustainable community development. They pointed out that GI is an active strategic measure to guide sustainable land use, economic development, and ecosystem protection by evaluating different functions of natural resource systems. Subsequently, as an efficient and sustainable development strategy and the national natural life support system, GI has gradually developed and applied globally. The first definition of GI appeared in August 1999. It was proposed by the GI working group organised by the United States Conservation Foundation and the Forest Administration of the Department of Agriculture. They defined GI as an interconnected green space network system composed of natural and artificial spaces to enhance biodiversity, maintain natural ecological processes, protect air and water resources, and improve the quality of life of cities and people. This green space network system covers natural areas such as waterways, wetlands, forests, wildlife habitats, and protected areas such as greenways and parks, farms, pastures, forests, and wilderness. As one of the essential concepts to guide urban development, the core of the GI is that the natural environment determines land use, highlighting the ‘life support’ function, integrating community development into nature, and establishing a systematic ecological function network structure. Although China introduced the GI concept only around the late 20th Century, many experiential practices similar to GI in ancient Chinese engineering have already existed. For example, the ancient roads of the Zhou Dynasty (Jia and Dai 2015), the pond system in the hilly southern area (Gao et al. 2015), the canal network in the Yangtze River Delta, and the pond flood storage system in the Yellow River floodplain (Yu and Zhang 2007; Wu et al. 2013; Chen and Yu 2015). They all embody the idea that urban development adapts to nature and has played the ecological, social, and economical service function since their completion.

1.2 China’s GI Research Development This study selected the CNKI database as the data source for analysis to comprehensively reflect China’s GI research development. The literature collection scope of the

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Fig. 1 Number of papers on GI published in Chinese journals from 1995 to 2020 (Source The Authors’)

CNKI database was limited to Chinese literature, and the literature collection time was up to December 31, 2020. Based on the theme of ‘green infrastructure,’ this study excluded invalid literature such as newspapers and periodicals and retrieved a total of 1195 Chinese works of literature, covering the period from 1995 to 2020. Among them, 361 papers were published in Chinese Core Journals (EI, CSCD, and PKU) covering 1996–2020. Based on literature review and investigation, this paper analyses the development trend, subject distribution, frontier hot spots, research weakness, and development trend of GI research with the help of the CNKI database and the literature analysis function of CiteSpace software. As shown in Fig. 1, the development of GI research in China can be divided into two periods: exploration period (1995–2008) and rapid development period (2009–2020). Based on the works of literature, China introduced the concept of GI around the late 20th Century. It was mainly used to guide the planning and construction of ecological and environmental protection facilities such as urban parks and greenways (see Table 1) in the early stage. In this period, ecological environment protection in land development has been highlighted in the National Tenth Five Year Plan and the Western Development. It was not until 2004 that Zhang Qiuming systematically introduced the concept, origin, planning methods and principles, functions, and benefits of GI for the first time. He also pointed out the key points China should pay attention to when using the GI concept for urban planning and construction. Many researchers like Liu et al. (2005) have summarised the connotation and essential characteristics of GI-related concepts at home and abroad. They further put forward their understanding and views on the role and function of GI in human settlements, ecological environment protection, society, and economy. Since then, the number of GI research in China has continued to increase, focusing on the overview of GI’s concept and theoretical development and the discussion of GI planning and evaluation methods. The rapid development period starts with the

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Table 1 Top 15 keywords with the strongest bursts in Chinese GI literature from 2000 to 2020 Keywords

Burst strength

Burst start year

Burst end year

Public open space

5.08

2000

2009

GI planning

4.71

2000

2008

Park City

4.52

2000

2009

Environmental infrastructure

2.80

2001

2010

Green Olympics

3.49

2002

2008

Ecological infrastructure

3.7

2007

2010

Sustainable development

3.35

2007

2010

Landscape architecture

5.76

2009

2015

Landscape planning

3.19

2010

2015

Stormwater management

3.57

2014

2020

Sponge city construction

6.09

2016

2017

Green development

5.55

2017

2020

Green Finance

4.98

2017

2020

Xiong’an new area

2.47

2017

2020

Ecosystem services

4.22

2017

2020

Burst timeline (2000–2020)

46th IFLA (International Federation of Landscape Architects) conference in 2009. The theme of this conference is ‘green infrastructure high-performance landscape,’ which redefines the function of contemporary landscape architecture as GI.

1.3 Evolution of the GI Concept in China In China, the development of GI is the result of the joint promotion of parks, park systems, open spaces, greenways, ecological networks, biological corridors, and stormwater management (see Fig. 2), which can be summarised into three contexts. First, from the perspective of the human settlement environment, taking the service of human settlement needs as the starting point (Stephan 2019). Second, taking biological protection as the starting point (Liu et al. 2005; Li et al. 2014). Third, from

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Fig. 2 Keyword cloud picture of references on GI in China (Source The Authors’)

the perspective of green technology, taking the greening of municipal engineering facilities as the starting point (Shen 2005; Tang and Zhao 2015). The independent development and mutual influence of the three contexts promote the formation and development of GI concept consensus. The idea of ecosystem services in ecological economics provides a clear and comprehensive ideological basis for the connotation and function of GI. After the development and integration of various fields, the connotation of GI is gradually clear and convergent, with the following core characteristics: (1) in function, GI provides comprehensive ecosystem services; (2) in space, GI is a cross-scale, multi-level, interconnected green network structure, which is the fundamental spatial framework of urban development and land protection; (3) In terms of components, GI includes three levels: national natural life support system, urban and rural green space based on infrastructure and municipal engineering infrastructure based on green. GI is the national natural life support system on the macro scale, carrying the ecological services of water conservation, drought and flood regulation, climate regulation, soil and water conservation, desertification control, and biodiversity protection to maintain national ecological security. GI is a green space with infrastructure on a medium-scale, different from the traditional urban green space system. It has a wide range of essential ecological services, such as alleviating urban flood disasters, controlling water pollution, restoring urban habitat, improving air quality, and alleviating urban heat islands. Moreover, it provides human settlements services such as recreation, aesthetic, cultural, and spiritual inspiration. At the microscale and technical level, GI uses green technology to carry out the comprehensive design of

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the human settlement environment of the site to restore and improve the ecosystem services.

1.4 Main Research Area of GI in China Domestic research on GI mainly focuses on the following four aspects: (1)

Research on the concept review and theoretical framework of GI

Yu Kongjian and others conducted a systematic study on the theory and method of ecological infrastructure (Yu et al. 2001; Liu et al. 2005). Liu Binyi and others focused on combining GI and China’s green space system (Liu et al. 2013; He and Liu 2011; Liu and Jiang 2002). In addition, many scholars have reviewed the concept of GI in foreign countries (Zhang et al. 2017; Du and Yu 2010; Zhou and Yin 2010; Wu and Fu 2009; Hou and Guo 2012), and some scholars have summarised the development of GI in China (Fu 2012; Jia and Dai 2015). (2)

Research on GI technology approaches and methods

Many domestic research studies reviewed foreign GI planning methods (Li 2009; Pei 2012). Yu Kongjian and others explored a complete method system with landscape security patterns as the technical approach to construct EI (Yu et al. 2009a, b; Li and Huang 2016). Some scholars applied GI principles in green space system planning (Liu and Wen 2007; Liu et al. 2012a; Meng and Wang 2013). Others explored new methods such as morphological spatial pattern analysis and ecological performance of spatial utilisation in GI construction (An and Shen 2013; Qiu et al. 2013). (3)

Introduction of practice cases at home and abroad

A large number of domestic articles introduced foreign practice cases, including cases in Seattle (Liu et al. 2012b), Maryland (Zhang 2009; Li and Wang 2010), Canada (Shen 2005; Tang and Zhao 2015), the UK (Huang and Liu 2010), and other places. Some research studies sorted out the domestic GI practice cases (Qiao et al. 2013). There are also some studies on the concept and method of site scale construction projects, such as Liupanshui Minghu Wetland Park (Yu 2014), Jinhua Yanweizhou Park (Yu et al. 2015), Harbin Qunli Yuhong Park (Yu 2015). (4)

Studies on the subdivided research area

At present, there are more applied studies in the research area of stormwater management in GI research in China (Che et al. 2010, 2015; Li et al. 2011; Zhang et al. 2011; Wang et al. 2012; Fu and Wang 2013; Jiang 2013; Li and Wang 2015). In addition, a few studies evaluated the effect of implementing GI (Lu 2013; Fu et al. 2015) on the mitigation of climate change (Chen 2015), air quality (Du 2013a, b; Cao et al. 2018), and human health (see Table 2).

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Table 2 The top 20 keywords by number of papers published in Chinese journals Ranking

Keywords

Number of papers published

First appearance year

1

Green infrastructure

588

1999

2

Landscape architecture

160

2008

3

Infrastructure

118

1995

4

Sponge city

106

2014

5

Stormwater management

82

2010

6

Landscape planning and design

78

2006

7

Greenspace

77

1995

8

Low impact development

59

2008

9

Green rainwater infrastructure

53

2010

10

Ecosystem services

49

2005

11

Greenway

43

2005

12

Green development

42

2011

13

Ecological civilization construction

32

2009

14

Climate change

32

2009

15

Sustainable development

31

2003

16

Ecological infrastructure

24

2003

17

Green finance

24

2015

18

Environmental infrastructure

20

1996

19

Bio-diversity

15

2005

20

Rain garden

15

2010

1.5 Problems in China’s GI Research Generally speaking, the understanding of GI research in China is still vague regarding connotation and denotation. The studies mainly focus on the conceptual theory and method framework at the urban and regional levels. The research method is mainly qualitative research from the perspective of a single discipline. Although the theoretical system represented by ecological infrastructure has been initially formed, the development of GI is still in its infancy. The main problems are as follows. (1)

The subdivision degree of the research area is low, and the degree of approximation is high

The research on GI in China is still in the primary stage of exploring theoretical methods, and the subdivision degree and depth of research are not high. GI research in China mainly comes from Architecture Science and Engineering, Economics and

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Management Science, Environmental Science and Resource Utilisation, and other disciplines. In addition, there are a few works of literature in Water Conservancy and Hydropower Engineering, Meteorology, Biology, and other fields (see Table 3). The research mainly focused on summarising GI’s concept and development process, introducing the theory and practice at home and abroad, and exploring spatial planning and evaluation methods. There is still a lack of in-depth research in the international frontier, such as human health, climate change, air quality, and public participation. (2)

Insufficient cross cooperation among science, engineering, and design disciplines

GI is a multi-scale and multi-functional application field evolved from different disciplines. Therefore, the close relationship between scientific research, engineering technology, and design application is significant for GI. So far, there are still some deficiencies in this research area in our country, such as the lack of response to real problems in scientific research, the lack of overall planning of comprehensive objectives in engineering technology, and the lack of professional technical support in design and application. Due to the lack of interdisciplinary cooperation, although GI research in China has distinct characteristics, it also has obvious bottlenecks. Urban planning, landscape architecture, and other human settlements mainly use qualitative methods to coordinate space implementation’s human and ecological value while lacking relevant quantitative research. Research on landscape ecology mainly focuses on judging and constructing a complete and continuous macro network pattern through a spatial Table 3 Top 15 subject categories by number of papers published Ranking

Subject categories

Number of papers published

1

Architecture Science and Engineering

687

2

Economics and Management Science

306

3

Environmental Science and Resource Utilisation

153

4

Water Conservancy and Hydropower Engineering

81

5

Forestry

68

6

Finance

52

7

Tourism

18

8

Meteorology

14

9

Biology

13

10

Library and Information

7

11

Higher Education

7

12

Transportation

7

13

Resource Science

6

14

Aerospace Science and Engineering

6

15

Gardening

6

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model. However, the attention to the internal quality of the pattern is insufficient, and the theoretical model still lacks empirical support (Ted et al. 2005; Theodore et al. 2008; Pei 2012). Research on environmental science mainly uses experiments and models to study specific problems quantitatively, but it lacks spatial coping strategies. Research on ecological restoration, environmental engineering, municipal engineering, and other fields are good at green engineering technology and lack understanding and overall planning of GI’s multiple values and comprehensive objectives. (3)

Few studies on comprehensive performance evaluation and its standards

At present, there are two tendencies in GI practice in China. One is applying single green technology that lacks humanistic value, such as the environmental engineering of constructed wetland, which only focuses on the effect of sewage purification, often lacks aesthetic value and participation. The other is the ‘ecological vase,’ which is challenging to evaluate the environmental benefits. For example, some beautiful urban wetland parks are likely to be water consumption projects of water diversion, causing damage to the ecosystem. It is the core characteristic of GI to have the total value of ecology and humanity, which is not in line with its connotation. So far, few studies comprehensively measure the comprehensive performance of ecosystem services in supply, regulation, support, culture, and health and well-being of GI. Regarding the source of construction funds of GI, the investment model of pubicprivate-partnership (PPP) is the primary trend in the future. The current obstacle is the lack of quantitative evaluation methods and standards of government pay for performance. Therefore, it is a crucial link to comprehensively evaluate the performance of GI in the whole life cycle of raw state, material acquisition, construction, and operation, and to establish quantitative, measurable standards for government purchasing ecosystem services. So far, the domestic research in this area is still minimal. (4)

The research on public participation, operation mode, and system guarantee needs to be strengthened

GI is not a simple green project. Its cultural value, social value, and economic value on the technical level are its essential attributes. So far, there is little research on GI in China, such as cultural identity, public participation, operation mode, management policy, and system guarantee. GI research is mainly in natural science and engineering, and the intervention in humanities is not enough. However, GI is not a simple green project. Its cultural value, social value, technical and economic value are its essential attributes as well. Regarding GI’s economic operation and social participation, the foreign practice represented by New York’s Highline park has adopted a new model of cooperation among government, community, social organisations, or enterprises. It provides a new vision for GI’s construction and operation, investment and financing mode, community participation, management policy, and property rights. Firstly, it solves operation and sustainable income and achieves economic benefits through franchising activities and projects. Secondly, it solves social participation, shortening

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the distance between community residents and GI through activities and strengthening interaction and participation. Thirdly, government finance and management cost is lower, and it only needs to buy green services on schedule. The current PPP mode in China is only a single way of investment and financing, which needs further research from more perspectives.

2 Construction of GI in Chinese Cities After introducing GI and other related concepts, China gradually paid attention to urban GI in urban planning and construction. According to the concept of GI, any natural, ecological, green-related facilities or underlying surface structures belong to GI. From a professional and academic perspective, GI refers to an interconnected green space network. Here, we divided GI construction into conventional GI elements and a particular GI system in urban construction and development. Urban public green land is an essential element of urban GI. In the past urbanisation process in China, every city has carried out the construction of urban green space/land, which is also the main content of the GI construction in Chinese cities. Some cities have adopted the concept of GI in urban development and construction. Government departments in these cities have formulated specific plans for GI construction and organised particular construction work. GI special planning and construction in these cities also focused on urban unit scales, such as green campus infrastructure construction and green industrial infrastructure construction. This study analysed the overall construction of urban GI in China according to the per capita green space area of each province in China. Then, Guangdong Province and Shandong Province were selected to analyse the unique construction of GI in crucial provinces. At last, we briefly introduced the construction of green campus infrastructure and green industrial infrastructure in China.

2.1 Construction of Public Green Land in China Cities Public (Park) green space is a kind of green space open to the public in the city. It has comprehensive functions such as ecological maintenance, landscaping, disaster reduction, and shelter. In urbanisation in the past few decades, public (park) green space is the main element of China’s urban geographic information system. From 2001 to 2010, the green coverage of China’s urban built-up areas increased from 28.4% to 37.37%; the per capita public (park) green space area increased from 4.6 m2 to 9.71 m2 . By 2019, the green space rate and green coverage of urban built-up areas have reached 37.34% and 41.11%, respectively. Urban per capita park area has reached 14.11 m2 , and the number of national forest cities has reached 194.

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Fig. 3 Per capita green area of provinces and cities in China from 2004 to 2019

Figure 3 shows the per capita public green space in cities in 31 provinces of China from 2004 to 2019. The data comes from China Urban Statistical Yearbook (2005– 2020). Due to restrictions of data access, Hong Kong, Macao, and Taiwan are not shown in the figure. As can be seen from the figure, Chinese cities’ per capita green space area has shown an apparent growth trend in the past 15 years. In 2004, each province’s maximum and minimum per capita green areas were 10.49 m2 and 4.51 m2 , respectively. In 2019, the maximum and minimum per capita green areas were 21.05 m2 and 8.71 m2 . The per capita public green space area of 14 provinces in 2019 is twice that of 2004, such as Shanxi, Inner Mongolia, and Jilin. The per capita green space area of Chongqing and Ningxia in 2019 is even four times that of 2004.

2.2 Representative Cases of Urban GI Construction in China Over the past few decades, not all cities in China have carried out special planning and construction related to GI. In terms of GI planning and construction, Guangdong Province and Shandong Province are representative. The two provinces’ government departments have issued relevant GI construction policies to guide and intervene in local urban development and construction. (1)

Urban GI construction in Guangdong Province

Since the 1990s, Guangdong Province has done much work in exploring ecological environment protection. With the popularisation of the ecological environment

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protection concept and the accumulation of practical experience, the protection of the ecological environment in Guangdong Province has experienced the evolution of ‘point-line-network,’ and the protection scope has gradually expanded from a single and isolated element to the whole ecosystem. Figure 4 showed the development process of GI Policy in Guangdong Province. In 1995, the Guangdong provincial government formulated the ‘Coordinated Development Plan of the Pearl River Delta’ and put forward the “Eco-Sensitive Zone” concept for the first time. In 2005, they formulated the ‘Coordinated Development Plan for Towns in the Pearl River Delta’ (2004–2010), put forward an ecological support system, and constructed a regional green space frame. In 2009, they formulated the ‘Integrated Planning for the Pearl River Delta’ (2009–2020) and proposed the ‘PRD (Pearl River Delta) Regional Greenway Construction Scheme.’ In the ‘Greenway Network master plan outline for the Pearl River Delta’ released in 2010, it was proposed to build six regional greenways, with a total length of 1,690 km of the main greenway line and a total area of 4,410 km2 of the green buffer zone. In 2013, the Guangdong Provincial Housing and Construction Office issued the ‘key points of greenway network construction,’ pointing out that the province’s GI construction project would start, and greenways would upgrade to GI. In 2014, Guangdong Province released the ‘New Urbanisation Plan of Guangdong Province’ (2014–2020) (Liu and Xie 2011). The guideline defined and classified the ecological control lines, which provided a reference for GI construction to clarify the distribution and pattern of the ecological network. The urbanisation plan focused on harmonious coexistence and coordinated development of people, nature, and cities, which was the core concept of GI construction. In 2015, the Guangdong Provincial people’s Government issued opinions on accelerating urban infrastructure construction. In the same year, Guangdong Province took the lead in constructing China’s first ‘Forest City Cluster,’ a practice of Regional Forest Wetland Ecological Construction on a macro scale with Chinese characteristics. (Li et al. 2021). It was the inevitable requirement of ecological construction for the development of urbanisation and clustering in China. It can be seen that GI is not only a new stage of ecological protection practice in Guangdong Province but also a new way to solve the ecological and environmental problems in Guangdong Province from the pattern and system-level (Liu and Chao 2016).

Fig. 4 Development and evolution of GI policy in Guangdong Province

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(2)

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Urban GI construction in Shandong Province

Since the 18th National Congress of the Communist Party of China (CPC) report in 2012, Shandong Province has included constructing a ‘modern eco-livable city’ into the development outline (Tang and Anna 2018). The outline pointed out that all localities and cities should implement the five development concepts of “innovation, coordination, green, openness, and sharing.” Moreover, they should fully implement the ‘Construction Plan for Ecological Civilization in Shandong,’ solidly promote the construction of ecological civilization, and build a livable city with a beautiful environment and comfortable life. In May 2016, the CPC Shandong Provincial Party Committee and the Shandong Provincial People’s Government issued the ‘Implementation Plan on Accelerating the Construction of Ecological Civilization.’ In the same year, the Guangdong Provincial Housing and Construction Office allocated special funds to support sponge city construction projects, renovation of old residential areas, building energy conservation and green buildings, and building characteristic towns. Under the policy intervention, in 2016, 18 green ecological demonstration towns in Shandong Province focused on promoting green buildings, comprehensively promoted green planning, green energy, green transportation, and GI as a whole, and promoting the construction of green urbanisation. Among them, the constructions of GI in some cities are as follows. Laixi City of Qingdao has carried out construction around the goals of “green city, water town” and “pastoral ecological city.” Sishui City has initially formed a three integrated eco-tourism pattern of the natural landscape, human landscape, and tourism agriculture, focusing on the construction of ‘new highland of eco-cultural tourism city.’ Tai’an City has formed an urban garden green space system by integrating urban park green space and ecological green space from points, lines, and surfaces. Jining City changed the traditional construction model, started sponge city construction all-around way, and compiled the ‘Jining City Sponge City Special Plan (2016–2030).’ Weifang City has compiled the ‘Water Network Ecological Greening Plan for Weifang’ (Tang and Anna 2018), with the primary goal of building a national forest city.

2.3 Other Forms of GI Construction in China Other GI constructions include Tianjin China-Singapore Eco-City construction, Chengdu-Chongqing urban agglomeration construction, sponge city construction, green campus infrastructure construction, and green industrial infrastructure construction. Tianjin China-Singapore Eco-city is a demonstration project of green development and the first international cooperative development of the eco-city to realise ecological restoration and protection (Liu et al. 2016). Its purpose is to establish a symbiotic ecosystem between the natural and artificial environments and realise the harmonious coexistence of humans and nature. During the Chengdu-Chongqing

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urban agglomeration construction, the GI concept is introduced into the collaborative planning of ecological cyberspace (Xieet al. 2019). Xining is a pilot city for sponge city construction in China, which aims to explore the technical approach of constructing a sponge city water system with GI system optimisation and provide ideas and references for similar urban water system construction in Northwest China (Wang et al. 2021). The theory of green industrial infrastructure is the practice of restricting industrial land to meet the needs of the ecological environment, social masses, and economic health while considering the needs of humans and nature. It can be described as the perfection and enrichment of the GI concept. For green campus infrastructure construction, Tsinghua University, Harbin University of Technology, and other schools began to explore in the late 1980s. Followed by Tongji University, Zhejiang University, Jiangnan University, and Shandong Construction University, which began to explore at the beginning of the 20th Century, according to Zhou (2018).

3 GI Policy Interventions in China For China, GI is a concept introduced from abroad, which coincides with China’s concept of green development. In most urban planning practices in China, GI is usually regarded as constructing urban public green land (space) systems. The results of the literature analysis showed that since 2009, the research on GI in China had gradually increased. Integrated searches and surveys showed that since 2010, China’s central government and ministries and commissions had successively put forward GI-related policies and documents. This section will analyse the development and evolution of GI-related policy from China’s central government’s perspective and the China State Council ministries’ perspective.

3.1 GI Policy Interventions from China Central Government In August 2005, Xi Jinping, then the Party Secretary of Zhejiang Province, concluded that ‘Lucid waters and lush mountains are invaluable assets’ in Anji, Huzhou, Zhejiang Province. In 2012, the 18th CPC National Congress report pointed out that GI, as an essential part of the construction of ecological civilization, played a vital role in promoting the construction of ecological civilization. It usherd in a good policy opportunity for the urban GI construction in China. The Central Economic Work Conference held in December 2012 proposed integrating the concept and principles of ecological civilization into the urbanisation process. In September 2013, Chairman Xi Jinping put forward ‘China development requires both clear water and green mountains, gold and silver mountains’ at Nazarbayev University in Kazakhstan. He clarified that China’s ecological civilization construction should respect nature, conforms to nature, and protects nature. In December 2013, the Central

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Conference on Urbanisation for China called for ‘building a sponge city with natural accumulation, natural infiltration, and natural purification.’ In March 2014, the ‘National New Urbanisation Plan (2014–2020)’ (also known as the ‘New-Type Urbanisation Plan’ or ‘NUP’) was released. As a programmatic document guiding China’s new urbanisation, the NUP took ‘ecological civilization and low green carbon’ as essential principles in urban planning. In November 2014, the Ministry of Housing and Urban–Rural Development issued the ‘the Technical Guide for Sponge City Construction—Construction of Rainwater System for Low Impact Development (Trial).’ In December 2014, the Ministry of Housing and Urban–Rural Development, Ministry of Finance, and Ministry of Water Resources jointly launched the application of the first batch of China’s sponge city pilot cities. In October 2015, the Fifth Plenum of the 18th CPC Central Committee proposed the 13th Five-Year Plan for Economic and Social Development, which combined green development with innovation, coordination, openness, and sharing to form a new development concept. In December 2015, the Central Urban Work Conference held in Beijing pointed out that China’s urban development has entered a new development period. It was necessary to respect nature, conform to nature, protect nature, strive to improve the urban ecological environment, and improve the sustainability and livability of urban development. In February 2016, the CPC Central Committee and the State Council issued several opinions on Further Strengthening the management of urban planning and construction, firmly establishing and implementing the development concept of innovation, coordination, green, openness, and sharing. By the end of 2016, China had established 30 pilot sponge cities in two batches (The first batch of 16 pilot sponge cities established in 2015, and the second batch of 14 pilot cities in 2016). In October 2017, the scientific conclusion that ‘Lucid waters and lush mountains are invaluable assets’ began to be implemented throughout the country. In April 2019, China’s GI Professional Committee was officially established in Beijing to build a future, robust, intelligent, green modern infrastructure system. In May 2019, the General Office of the State Council and the General Office of the CPC Central Committee issued the ‘National Ecological Civilization Experimental Zone (Hainan) Implementation Plan,’ which proposed to promote green urbanisation. In 2021, the proposal of ‘the 14th Five-Year Plan for National Economic and Social Development and the Long-time goal of 2035’ proposed building a GI system to help the highquality development of the city. In February 2021, the State Council of China issued the ‘Guiding Opinions on Accelerating the Establishment and Improvement of a Green Low-Carbon Circular Development Economic System’ and deployed tasks such as accelerating the green upgrading of infrastructure (Fig. 5).

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Fig. 5 Development and Evolution of GI Policy in the central government in China

3.2 GI Policy Interventions from the Chinese Ministries (1)

Ministry of Housing and Urban–Rural Development of the People’s Republic of China (MoHURD)

In October 2014, the MoHURD issued the ‘the Technical Guide for Sponge City Construction—Construction of Rainwater System for Low Impact Development (Trial).’ Subsequently, it issued relevant government documents and guidelines for sponge city construction every year. ‘The Key Points of the Work of the Department of Building Energy Conservation and Science and Technology of the MoHURD in 2014’ pointed out that we should continue to implement the demonstration of green ecological urban areas, strengthen the promotion of green buildings and GI construction, and strengthen quality management. In 2015, the MoHURD added Low-Impact Development (LID) content to the revised ‘Standard for Urban Green Space Design’ and put forward the specific requirements that the planning and construction of greenway should be combined with the construction of sponge city. In December 2016, the MoHURD and Ministry of Environmental Protection jointly issued the ‘National Urban Ecological Protection and Construction Plan (2015–2020).’ It called for the implementation of GI construction to achieve multiple objectives of ‘ensuring water security, restoring water ecology, conserving water resources and improving the water environment.’ In 2018, the General Office of the MoHURD pointed out that the green space system was the only vibrant GI in the city. In 2020, the General Office of the MoHURD adopted the ‘Special Planning and Design Standards for Sponge City Construction (Draft)’ by using green facilities and gray infrastructure according to local conditions. In 2020, the General Office of the MoHURD adopted the ‘Special Planning and Design Standards for Sponge City Construction (Draft for comments),’ which proposed to adopt the concept of systematic governance and made use of green facilities and gray infrastructure according to local conditions. (2)

Ministry of Natural Resource of the People’s Republic of China (MoNR)

In March 2018, the MoNR was established with the approval of the State Council at the first session of the National People’s Congress based on the suggestions

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promoted in the third plenary session of the CPC Central Committee on deepening the reform of the decision, deepening the reform of the party and state institutions. In May 2020, the MoNR implemented the natural resources management practice of land and space control according to ecological priority and green development requirements. The specific contents included strengthening ecological protection and restoration, enhancing biodiversity and ecosystem function, promoting harmonious symbiosis between humans and nature, and ensuring sustainable economic and social development. (3)

National Development and Reform Commission (NDRC)

In November 2016, the NDRC solicited public opinions on the circular development leadership plan. By 2020, a green, circular and low-carbon industrial system has been preliminarily formed: the resource utilisation level of typical urban waste has been significantly improved; the symbiotic system linking production and living systems has been basically established; the household garbage classification and renewable resources recycling has been effectively connected; and the construction level of GI and green buildings has been significantly improved. (4)

Ministry of Ecology and Environment of the People’s Republic of China (MoEE)

In May 2013, the MoEE issued the ‘National Pilot Demonstration Zone Index for Ecological Civilization Construction (Trial).’ Since 2017, the MoEE has implemented the Green Silk Road Messenger Plan and jointly strengthened environmental capacity building with ‘the Belt and Road’ countries. It has trained more than 2000 environmental protection officials, experts, technicians for 120 countries, covering ecosystem assessment and management and GI construction.

4 GI Policy Interventions in the Belt and Road Initiative (BRI) The Belt and Road is the abbreviation of ‘Silk Road Economic Belt’ and ‘21st Century Maritime Silk Road’, proposed by Chinese President Xi Jinping in September 2013. From May 14 to May 15, 2017, the first ‘Belt and Road’ International Cooperation Summit Forum was held in Beijing. On this forum, the ‘Guiding Opinions to Promote Green Belt and Road Construction’ was issued to promote GI construction and enhance the quality of the ecological environment. From April 25 to April 27, 2019, the second ‘Belt and Road’ International Cooperation Summit Forum was held. China’s President Xi Jinping stressed at this forum that ‘we must take green as the background, promote GI construction, green investment, green finance, and protect the common home we live on.’ On June 18, 2020, the ‘Belt and Road’ international cooperation high-level video conference was successfully held in Beijing. The theme was “strengthening the ‘Belt and Road’ international cooperation and join hands to

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Fig. 6 Main green development roads of the Belt and Road

fight the 2019-nCov”. Up to January 30, 2021, China has signed 205 cooperation documents with 171 countries and international organisations to build the ‘Belt and Road’ (Fig. 6). After China put forward the ‘Belt and Road’ Initiative (BRI), to eliminate international concerns about the ecological environment that the ‘Belt and Road’ Initiative may bring, several ministries have put forward relevant opinions and specific plans for the green BRI. On March 28, 2015, the National Development and Reform Commission, the Foreign Ministry, and the Ministry of Commerce jointly issued the ‘Vision and Action to Promote the Co-construction of the Silk Road Economic Belt and the Maritime Silk Road in the 21st Century.’ This document highlighted: ‘emphasise the concept of ecological civilization in investment and trade; strengthen cooperation in ecological environment, biodiversity, and climate change; and build a green Silk Road.’ In May 2017, the Ministry of Environmental Protection, the Ministry of Foreign Affairs, the National Development and Reform Commission, and the Ministry of Commerce jointly issued the “Guiding Opinions on Promoting the Construction of Green Belt and Road” (Xia 2019). The ‘Opinions’ pointed out that promoting China’s experience in green development and ecological civilization construction through the construction of the green ‘Belt and Road’ could help improve the ecological environment protection capabilities of the economies along the route, prevent ecological, environmental risks, and achieve sustainable development. The Ministry of Environmental Protection also proposed the ‘Belt and Road’ Ecological Environmental Protection Cooperation Plan. The ‘Plan’ further focused on 25 key projects to promote ecological and environmental protection cooperation,

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including policy communication, facility connectivity, unimpeded trade, financing, people-to-people, and the capacity construction category projects, aiming to promote the countries along the BRI to achieve the 2030 countries’ sustainable development agenda environmental goals (Cheng et al. 2017). Moreover, the ‘Opinions’ and ‘Plan’ put forward two construction directions regarding infrastructure construction. One was to implement the ecological and environmental protection requirements of infrastructure construction standards and norms, promote environmental protection standards and practices in green transportation, green buildings, green energy, and other industries, and improve the green and low-carbon level in the process of infrastructure operation, management and maintenance. The second was to strengthen environmental management in industrial parks, strengthen environmental protection infrastructure, and promote centralised sewage treatment and recycling and demonstration in industrial parks (Lu and Wei 2017) (see Fig. 7). As the concept of green development has been widely accepted, the development of green finance has attracted more attention. In 2016, ‘the Outline of China’s 13th Five-Year Plan’ proposed for the first time ‘Develop green finance and establish

Fig. 7 The belt and road initiative’s ecological and environmental cooperation framework

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green development funds.’ In the same year, seven ministries, including the People’s Bank of China, the Ministry of Finance, and the National Development and Reform Commission, jointly issued the ‘Guiding Opinions on Building a Green Financial System.’ In October 2017, the 19th CPC National Congress took ‘developing green finance’ as one of the paths to promote green development, and building a green financial system has become a national strategy. The green financial system is a highlight of China’s green development system, and it is an essential guarantee for promoting ‘GI investment’ and ‘green trade’ (Wang et al. 2017). The ‘Belt and Road’ cooperation covers infrastructure construction, trade interoperability, and financial cooperation. It is the key and priority area of the ‘Belt and Road’ construction and also an important foothold for green finance to play an important role. In order to cope with climate change and resource and environmental issues, the demand for GI is rising. Investment in GI construction can increase productivity and bring various benefits to human health, the environment, and the economy. It is estimated that a cumulative investment of $36 trillion to $42 trillion in GI between 2012 and 2030 will cost about $2 trillion, accounting for 2% of global GDP. On September 24, 2019, the International Alliance for Green Development of Belt and Road and the Boao Forum for Asia jointly released “Beijing’s Belt and Road Green Development Case Report.” The report selected 13 successful projects in 8 aspects: biodiversity and ecosystem protection, clean energy, clean water, sustainable transportation, solid waste treatment, sustainable consumption and production, green building, and corporate social responsibility, which had made positive contributions to the economic and social development of the host country. For example, the Cabinda Water Supply Project in Angola not only provides safe and sanitary drinking water for residents of Cabinda Province through the construction of a high-quality and complete water supply system but also effectively improves people’s livelihood. It has actively promoted the improvement of local environmental quality and community well-being through various sustainable infrastructure construction and operation methods and social service measures. It has also solved insufficient water supply for seven local water plants and delivered safe and clean drinking water to nearly 110,000 residents in the urban area. Although the construction of the ‘Belt and Road’ has played a good role, the construction is still facing some practical problems: (1) (2) (3) (4)

Insufficient funds: asset scale expansion is restricted. Institutional challenges: difficult to introduce evaluation standards. Risk factors: affecting implementation costs and effects. Environmental issues: hindering the implementation of green finance.

5 GI Policy Interventions in Xiong’an New Area Xiong’an New Area is located in the hinterland of Beijing, Tianjin, and Baoding, covering Xiong County, Rongcheng County, Anxin county, and some surrounding

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Fig. 8 Schematic diagram of the urban and rural spatial layout structure of Xiong’an New Area

areas, including Baiyangdian Lake (People’s Government of Hebei Province 2018a) (see Fig. 8). It has obvious regional advantages, convenient transportation, stable geological conditions, an excellent ecological environment, and a robust carrying capacity of resources and environment. Baiyangdian Lake, the largest freshwater lake in North China Plain, is rich in water resources, meeting the regional ecological water demand. The current development level of the region is low, and the development space is abundant. The above conditions make Xiong’an New Area suitable for high starting point planning and high standard construction. The government work report of the 19th CPC National Congress formally proposed for the first time that ‘Xiong’an New Area should be planned from a high starting point and constructed with high standards’ (The 19th Central Committee of the Communist Party of China 2017). The establishment of Xiong’an New Area has its precise goals. (1) (2) (3) (4)

Focus on relieving Beijing’s non-capital functions; Explore new models for optimising the development of densely populated areas; Adjust and optimise the urban layout and spatial structure of Beijing, Tianjin, and Hebei; and Cultivate a new engine of innovation-driven development.

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Among the New Area construction tasks, ‘adhere to the basic principles of ecological priority and green development’, ‘create a beautiful ecological environment’, and ‘strive to build a green ecological livable city with blue-green interweaving and urban green symbiosis’ are the primary strategic tasks (People’s Government of Hebei Province 2018b). As a national sample to promote high-quality green development, Xiong’an New Area adheres to the principle of planning before construction. According to the city’s orientation of high-quality green development, Xiong’an New Area draws lessons from the GI and other international urban development and planning concepts, technical methods, management mode, and guarantee mechanism. China’s President Xi Jinping stressed that every inch of land in Xiong’an New Area should be clearly planned before construction. The New Area planning should be formulated at high standards, high quality, and high level. Only in this way can we ensure that the development of Xiong’an New Area and the protection of the ecological environment can be taken into account and make the city scale adapt to the carrying capacity of resources and environment. Since its establishment in April 2017, Xiong’an New Area has successively issued several special planning projects (See Fig. 9). These planning projects include ‘the Outline of Xiong’an New Area Planning in Hebei Province’ (People’s Government of Hebei Province 2018a), ‘the Master Plan of Xiong’an New Area in Hebei Province’ (People’s Government of Hebei Province 2018b), ‘the Ecological Environment Protection Planning of Xiong’an New Area’ (People’s Government of Hebei Province 2018c), ‘the Ecological Environment Treatment and Protection Planning of Baiyangdian Lake’ (People’s Government of Hebei Province 2019a). ‘The reply of the Central State Council on the Outline of Xiong’an New Area planning in Hebei Province’ (The State Council of the People’s Republic of China 2018) pointed out that the development boundary, population scale, land scale, and development intensity of the New Area should be scientifically determined. They should be determined with the resources and environment carrying capacity as the rigid constraint condition. The proportion of blue-green space in Xiong’an New Area should be stabilised at 70%. The intensity of long-term development should be controlled at 30%. The forest coverage rate should reach 40%, and the green coverage rate in the starting area should get 50%. After more than two years of planning, construction,

Fig. 9 Development and evolution of GI-related policy in Xiong’an new area

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and exploration, based on the above specific planning, each district of Xiong’an New Area has successively compiled the regional regulatory detailed planning (People’s Government of Hebei Province 2019b, c; 2020a, b, c), which provides guidance and construction basis for the planning and construction of Xiong’an New Area. According to the requirements of the above-mentioned specific planning and detailed regulatory planning, Xiong’an New Area gives priority to strengthening ecological construction, strictly protecting the regional environment, strictly delimiting the ecological red line, permanent basic farmland and urban development boundary, strengthening the protection of cultivated land, and strengthening afforestation and wetland restoration. Since the establishment of Xiong’an New Area, the government has taken the lead in implementing a series of planning and construction measures for ecological environment control and protection, including ‘Baiyangdian ecological restoration project’, ‘Millennium Xiulin urban forest project’, ‘investigation and treatment of sewage pits and ponds’, ‘gas instead of coal, electricity instead of coal’, ‘harmless treatment of domestic waste’. In the completed ‘Citizen Service Center’, ‘green data center’, and other projects, the concept of ecological priority has been fully implemented. Moreover, ecological and environmental protection plans have been taken as the primary construction goal throughout the planning, construction, management, and operation of Xiong’an New Area. Green finance is an important measure to support the implementation of green development construction projects. To explore the green finance support mode with local characteristics and support the high-quality green development of Xiong’an New Area, Ma Jun, chief economist of the Research Bureau of the central bank, released the green finance planning report of Xiong’an New Area at the second ‘Tianjin Green Finance Forum’ in December 2017 (Green finance professional committee of China Financial Society 2017). The report put forward three specific ideas for Xiong’an New Area to develop green finance: ‘one center, one demonstration, and one system.’ ‘One center’ refers to the establishment of a green technology innovation investment center. Attract green technology industry and investment funds to settle in Xiong’an New Area, and build a green technology innovation and investment center with technology bank and capital market resources. ‘One demonstration’ refers to establishing GI and green building investment and financing demonstration zone. Innovate the green financial support mode. Ensure that the funds provided by green credit, green bonds, green industry development fund, and other channels will be used to focus on supporting low emission, low energy consumption GI, and green building projects. ‘One system’ refers to the construction of a green financial system with local characteristics. By the end of 2020, Xiong’an new area has accumulated more than 10 billion yuan of direct government investment and green financial investment. After more than four years of planning and construction, the construction of Xiong’an new area has achieved initial results. The afforestation area of ‘Millennium show forest’ has exceeded 273 km2 . Baiyangdian Lake’s ecological water supply exceeded 1.29 billion cubic meters, and its water area recovered to 290 km2 . The ecological environment of Baiyangdian Lake has been significantly improved, and the biodiversity has been significantly restored. The water environment continued to improve, and the

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chemical oxygen demand concentration of primary pollutants was 23.7 mg/l, which decreased by 9.5% compared with the same period in 2019. The water quality of the lake area has achieved the goal of ‘global class IV, local class III, and elimination of class V’. The air quality composite index of Xiong’an New Area was 5.73, 8.90% lower than that in 2019. PM 2.5 concentration was 52 µ g/m3 , 7.14% lower than that in 2019. The average number of days with good air quality was 226, 29 days more than in 2019. In addition, to ensure the high-quality and orderly development of Xiong’an New area, the planning requirements, significant measures, and successful experience of Xiong’an New Area were summarised and upgraded into regulations. Xiong’an New Area actively tried to solve the considerable problems of environmental governance, ecological protection, and flood control safety by the rule of law to ensure the high-quality development of Xiong’an New Area on the track of the rule of law. On February 22, 2021, Xiong’an New Area issued the first local regulation, ‘Baiyangdian Ecological Environment Governance and Protection Regulations’ (People’s Government of Hebei Province 2021). For the first time, the rules confirmed the relevant plans approved by the state, highlighting the leading and authoritative nature of the plannings. In the ‘Regulations on the control and protection of the ecological environment of Baiyangdian Lake’, the contents mentioned in the planning, such as the formulation of the plan for the control task to reach the standard within a time limit, and the improvement of the ecological environment standard system, have all been upgraded to the contents of the regulations. In addition, the rules strictly set up legal responsibilities to ensure the orderly and effective implementation of the plan following the law. Generally speaking, Xiong’an New Area is an exploration practice with great symbolic significance to grasp its characteristics and the actual development of the city at this stage. The planning and construction of Xiong’an New Area draw on the planning concept of ‘giving priority to natural ecological functions’ of GI and draws on GI’s technical methods and normative guidelines. On this basis, combined with the characteristics of China’s urban and rural structure, land ownership, and administrative system, a feedback evaluation and management mechanism with local features is formed to ensure the benefits of GI planning and construction on the urban development Xiong’an New Area.

6 Problems and Solutions for GI in China Based on the literature review and investigation, it is found that the research results of Chinese scholars on GI focus on the early planning stage, and the research on the technical route and spatial strategy needs to be deepened. The theoretical research on GI is still in its infancy. The practice and exploration of the implementation of GI are basically carried out in macro places such as cities and fixed areas. China’s urban GI is rarely discussed in policy and management mode and lacks quantitative data support. Many cities in China still have several GI construction problems, such as limited land

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distribution, insufficient capital investment, insufficient publicity, and promotion, which restricts the construction and development of urban GI and the construction of urban ecological civilization. The following summarises the problems existing in China’s urban GI construction from the following aspects and gives countermeasures and suggestions.

6.1 Problems in Urban GI Construction in China (1)

Unreasonable planning of urban GI

The layout of urban GI is unreasonable, and an ecological network has not yet been formed. The planning of the urban green space system still needs to be improved, especially since the distribution of green space in some old cities is uneven, and even the lack of green space in some cities. In addition, the layout of the parks and green spaces are scattered and unsystematic. The GI of urban–rural integration should include all kinds of gardens and green spaces in the city, including forests and lakes outside the city, rural farmland, forest networks, and orchards. Due to administrative zoning and other reasons, the green space ecological network is often cut off. This cuts off the connection between urban and rural areas and is detrimental to the continuity and integrity of the ecological networks. The total amount of urban green space is insufficient, and the building density is high. The central urban area usually retains only less green space. The urban shelterbelts lack comprehensive planning, with only a single tree species, and the number of nurseries is shrinking year by year. The urban greening form is single, and the landscape quality needs to be improved. Urban green space lacks a design with national characteristics. The greening form of urban roads is relatively single, mainly regular planting trees, lack of Qiao irrigation grass group landscape, cannot play green belt rich road landscape. The structure, function, and stability of the urban green space landscape need to be improved urgently. (2)

Insufficient awareness of GI and public participation

Residents, as the private owner of community property and also the specific executors of disaster reduction policies and measures, whose participation is crucial to the construction of GI. At present, Chinese urban residents have insufficient GI, low construction, operation, and management of urban GI, lack of adequate public participation mechanism, and weak supervision over urban environmental construction. (3)

Fragmentation and dispersion of urban GI construction

The greenway construction of GI construction in cities with particular GI, such as China, Guangdong Province, Chengdu—Chongqing, have achieved good GI construction results. For most cities in China, GI construction mainly constructs public green spaces in urban parks and green space on both sides of roads. The main

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problem is the lack of specific planning and construction of GI. Urban GI is fragmented and decentralised. The plot ratio of GI is low, the distribution of resources is uneven, and it is not easy to form a large-scale development. Poor connectivity between GI creates no green network-like infrastructure. (4)

Poor policy system for GI

Since 2010, the Chinese central government, various ministries and commissions of the State Council, and local governments have put forward many targeted policies and issued relevant documents, standards, and guidelines centered on urban ecological civilization and GI. These actions play an essential role in guiding the development of China’s urban GI. For example, the Chinese government put forward the concept of green ‘Belt and Road’ construction, and the Xiongan New Area of China implemented green development and construction. However, developing these GI policies lacks continuity and extension and an overall system and organisation. Under the background of insufficient policy intervention and guidance, there are also related problems such as insufficient capital investment, social organisations failing to play their role fully, and excessive pursuit of GDP, ignoring the construction of urban GI.

6.2 Countermeasures and Solutions for Urban GI Construction in China (1)

We should include GI in regional and local plans and policies, do an excellent job in the top-level design of urban GI construction, and continue to improve the layout of the green space system. The layout of green space shall be optimised and improved within the planning scope of the plan. The planning structure and spatial layout of the green space system in the planning area shall be scientifically determined. A green space system integrating urban and rural areas shall be formed. Build a scientific, reasonable, and multi-scale GI planning system. Investigate the urban green space system, analyse the current urban green indicators, including green space rate, green coverage rate, and per capita public green space, and find out the main restrictive factors affecting the development of urban green space. Determine the overall planning objectives, including short-term, medium, and long-term goals, and establish the corresponding green space planning index system. Under the guidance of green space planning, we will constantly improve and optimise the urban green space system, improve the total amount and quality of urban green space, and maintain biodiversity. Urban GI planning is a huge planning system, including data collection and the implementation between multiple departments, organise personnel from different professional backgrounds to participate in planning and construction. It also breaks administrative barriers, strengthens cooperation between various departments and involving regions and urban governments, and establishes a diversified urban

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(3)

(4)

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GI planning participation mechanism. The urban planning department shall organise planning, determine the key areas and facilities that need to prioritise planning, formulate reasonable planning objectives, and carry out scientific management by land construction management and other departments in the implementation process. Based on the overall urban planning, specific plans for the green space system will be formulated. We need to improve the public participation system for urban GI. Improve the awareness of GI to enhance public participation, enhance citizens’ recognition and belong of urban GI, and gradually realise the openness of information and the legalisation of public participation procedures to ensure GI development. Implement relevant supportive land policies to encourage more people to participate in the construction of GI. Encourage scientific and technological innovation, vigorously promote scientific research and exchanges; strengthen professional education, and promote talent team construction. Basic research should combine the natural ecosystem of urban green space based on correlation and connectivity. Build a low-carbon city, integrate the green space system with an overall developing and innovative vision, and build a green ecosystem at different levels. Combine green space with other infrastructure in the city organically to establish a comprehensive green network. We will further increase the construction of supporting facilities such as sewage treatment, environmental sanitation, and energy consumption and promote GI development. From the central government to departments to governments at all levels, we should continue to improve supporting policies for GI construction and strengthen institutional and institutional innovation. Urban governments at all levels shall incorporate the construction of urban GI into their urban development policies. Implement the corresponding incentive policies for GI construction to make the urban GI construction more comprehensive and perfect. Preferential policies for GI construction should be implemented. Such as rigid provisions that land development must ensure a specific green space area and the construction of related GI, and reduce the corresponding tax revenue, to encourage developers to develop and build green buildings, to reduce the burden of developers to a certain extent, and to encourage the construction of urban GI facilities. At the legislative level, the public’s environmental participation right is stipulated to provide a legal basis for the public’s participation in environmental management to democratise environmental policies, protect the environment, promote the construction of ecological civilization, and realise the sustainable development of human and nature. On the other hand, the government should broaden communication channels, increase promotion efforts, and make reasonable and practical use of various media to publicise the urban GI. The public can better access information and participate in the construction of the team. Government departments have led the establishment of public welfare

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social organisations to construct GI for exchanges and cooperation. Establish and improve the industry management system and constantly improve the industry regulations and standard system.

7 Summary of GI Policy Interventions For China, GI is an imported concept or development model, which coincides with the concept of green development that China has been adhering to. The research on GI in China started 10–15 years later than in other countries. Urban public green space construction is an essential element and content of urban green technology facilities construction in Chinese cities. In the construction of special GI, Guangdong Province is an early start of GI-related particular construction provinces. Shandong Province vigorously develops the ecological civilization construction related to GI throughout the whole province. Green industrial infrastructure, green campus, green ecological demonstration area are also typical demonstrations of GI construction on the unit scale of Chinese cities. The policy related to the green foundation in China began in 2010, especially after the 18th CPC National Congress report in 2012, which proposed to vigorously promote the construction of ecological civilization. The central government and all ministries put forward policies and guidance documents related to GI. The representative GI policies at the central government level mainly include the development concepts of ‘clear waters, and green mountains are gold and silver mountains’, the urban ecological civilization construction, the sponge city construction concept, the ‘Belt and Road’ plan, and the construction plan of the Xiong’an New Area. The MoHURD Department put forward the most relevant GI policies and documents. It is also the most relevant ministry related to the construction of urban GI. Other relevant ministries and commissions have proposed their targeted policy documents based on their departmental functions. GI construction in China should develop in policy, institutionalisation, priority, planning standardisation, comprehensive evaluation, and verification. We believe that the concept and practice of urban GI construction in China will become more perfect and mature.

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Urban Forest Planning and Policy in China Wendy Y. Chen, Cheng Wang, and Yining Su

Abstract Urban forests, in various forms and sizes, have been recognized as an important component of urban landscapes for millennia. Being produced and managed by governmental authorities, they manifest how various policy and planning initiatives have been implemented. This chapter delineates the history, experience, and characteristics of policy guidance pertaining to urban forests and urban green spaces (being an early and still co-existing form) in the People’s Republic of China since its founding in 1949. The chronological roadmap of China’s urban forest can be roughly divided into four phases: (1) piecemeal urban greening and massive deforestation (1949–1979), (2) urban gardening and peri-urban afforestation for landscape beautification (1980–2000); (3) urban forests as a countermeasure to environmental stresses (2000–2010), and (4) urban forests as a visual manifestation of ecological civilization (post-2010). It is unquestioned that China is strongly committed to promoting ecological civilization as an innovative paradigm for its sustainable development and a new vision for the global future. The transformation of this political discourse into expected outcomes in urban forest development requires policymakers, scholars, and practitioners to construe urban forests as an integral component in urban transition, a stronghold of civic responsibility, and a key dimension of the nature of human flourishing. Keywords Urban forest · Policy · Beautification movement · Ecological civilization

W. Y. Chen (B) · Y. Su Department of Geography, University of Hong Kong, Pokfulam Road, Hong Kong, China e-mail: [email protected] C. Wang Research Institute of Forestry, Chinese Academy of Forestry, No. 1 Dongxiaofu, Xiangshan Road, Haidian District, Beijing, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_3

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1 Introduction Urban forests, a term coined by Professor Erik Jorgensen (University of Toronto, Canada) in 1965, are generally considered to include all woodlands and tree resources and associated vegetation inside of and close to urbanised cities, regardless of whether they are naturally developed or artificially planted (Grey and Deneke 1986; Konijnendijk 2003; Jones and Davies 2017). They are integral components of urban ecosystems, providing a full spectrum of ecosystem services (Jim and Chen 2009) and safeguarding natural, biological, environmental, cultural, and recreational processes across urban landscapes that are essential to sustain human society (Staddon et al. 2018). This innovative conceptualisation of urban forest signifies a transition from seeing individual trees (like street trees, shade trees, ornamental trees, etc.) that are established and maintained for satisfying individually separated needs of the city to an ecological community of vegetation connected with the wider natural and built world (Dean 2009) and addressing various needs of the city coordinately and holistically. In the following decades, this concept has evolved and caught on amongst professionals and policy-makers across North America and Europe. It was also introduced into China after the 1990s (Liu et al. 2004; Li et al. 2005), offering new perspectives and constituting the foundation upon which modern urban forests have been gradually established in the world’s most populous country (Chen and Wang 2013). A monumental event is the first symposium on urban forests held in Tianjin in 1992, which attracted more than 50 scholars who discussed extensively about the theoretical concepts, content, planning, and development measures pertaining to urban forests (Li et al. 2005), ushering in a new age of urban greening and landscaping in the unique context of China. With the gradual advancement of scholarly understanding of urban forests in the following decade, they came to be understood as an integrated form of urban gardens/parks (usually dominated by decorative vegetation) and countryside forests (usually dominated by woody stands) (Xu and Zhu 2017), a multi-functional infrastructure (Shanfeng et al. 2011; Zhu et al. 2019) and a naturebased solution for addressing and mitigating the grand and diverse social, economic, environmental, as well as ecological challenges facing human society (Chen et al. 2021), and have thus become an important part of municipal planning, upheld by a series of statutory instruments (such as Urban Green System Plan), and non-statutory greening campaigns (such as National Garden City and National Forest City) (Syrbe and Chang 2018). As a typical form of urban commons in human-dominated and dynamic urban ecosystems, urban forests have been established and managed by municipal governments (mainly the Landscape Garden Bureau and the Forestry Bureau). Thus they are subject to changing contemporaneous societal attitudes towards nature and political will, manifesting how various policy and planning initiatives have been constructed and implemented (Chen and Hu 2015; James et al. 2009). Under China’s complete top-down political system (Syrbe and Chang 2018), the official ideology has played a decisive role in all social activities, with the development of urban green spaces and

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urban forests being no exception. This chapter tracks the transitions in the development of urban green spaces and, more recently, urban forests, delineates the history, experience, and characteristics of urban forest planning in the People’s Republic of China since its founding in 1949, and points future directions of China’s urban forest led by ecological civilization, a new paradigm envisioned by China for the sustainable development across the globe.

2 1949–1979: Piecemeal Urban Greening and Massive Deforestation After the 1949 liberation when Chairman Mao Zedong (1893–1976) came to power, there existed 112 urban parks, with a total area of 2,961 hectares, in entire China (Li 1987; Liu 1999). The scarcity of material goods was one of the main characteristics of the first few decades; thus, the top priority was given to a full-scale reconstruction to regain economic and social strength. Even though there was a serious lack of amenities and recreational facilities, little progress was made to create new urban green spaces (public parks), restrained by the grave economic circumstances and lack of resources and professionals. Existing green spaces and parks constructed before 1949 as aesthetically pleasing environments for recreation were transformed into vegetable fields and/or livestock farms, and waterbodies (a key component of traditional Chinese gardens, according to Shi et al. 2018). For instance, the waterbodies were converted into fish ponds in pursuit of production, i.e., economic gain to make the socialist nation economically powerful, which was believed of great importance not only for building the economic base for socialism but also for upholding Mao’s political ideology of self-reliance (Zhao and Woudstra 2012). Urban greening inspiration and design model originated from the former Soviet Union was introduced into China in 1952 (Yu and Padua 2007; He and Zhao 2019), which emphasised tree planting in tandem with built structures for various functions, including publicity, exhibitions, sports activity, and entertainment. Unfortunately, this initial greening effort was soon abandoned after the split with the Soviet Union in the late 1950s. The political pressure caused an immediate urgency to show the nation’s progress in the socialist undertaking, including urban construction and associated green spaces establishment (Zhao and Woudstra 2012). To establish China’s own vision of a socialist landscape, Mao issued the slogan “Greening the Motherland” in 1956. Two years later, the National Gardening and Afforesting Movement was launched, which specified that “we should turn all the lands of our country green, create garden-like places, make it beautiful everywhere, and change the face of China”, and “natural and beautiful landscape should be restored to beautify people’s working, learning and living environment”. This laid the foundation of urban greening in cities and afforestation in countryside areas (Jim and Chen 2009). Responding to this initiative, by the end of 1959, the total number of urban parks had increased to 509

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in the whole country, with a total area of 16,581 hectares (Liu 1999). For example, Taoranting Park (Joyous Pavilion Park) in Beijing was created in the 1950s, reflecting a mixture of functional divisions (emphasised by the Soviet model) and scenic spaces (highlighted in the traditional Chinese gardens). Guided by the policy to “combine greening with production”, fruit trees, such as apple, pear, peach, and hawthorn, were extensively planted along with willow (Salix spp.), poplar (Populus spp.), as well as shrub species (such as Sorbaria kirilowii and Amygdalus triloba) in Taoranting Park. However, the dire economic conditions in the following years (the Great Leap Forward from 1958 to 1961, and the Great Proletarian Cultural Revolution from 1966 to 1976) had pushed large scale deforestation in countryside areas (even on sloping, low-yielding land), aiming to seek grain from the lakes, grassland, and mountain tops (Démurger et al. 2009). In connection with this, forest tracts were cleared and burnt in order to enlarge the cultivated land area (Shapiro 2001). According to Smil (1983), about 24% of China’s forest cover was felled by the end of the 1970s. While in urbanised cities, amenities and recreation were conceived as a “reactionary viewpoint” of feudalism and denounced as “bourgeois lifestyle”, greening/gardening related to recreation and beautification was completely rejected. A majority of the existing urban parks had been destroyed and demolished, the total green area in all cities declined to less than 50% of the amount in 1959 (Zhao 2009). The remaining ones suffered from neglect or misuse, and very few new urban green spaces were created (Zhao and Woudstra 2012). Overall, during this Maoist era dominated by the communist ideology in pursuit of a pure revolutionary vision, public parks and other green spaces for amenities and recreation (as early forms of urban forests) had experienced significant regression. Even though the State Ministry of Construction Engineering (renamed as China State Construction Engineering Corporation in 1982) published “Several Provisions on Urban Greening and Landscaping” in March 1963 as the very first legislation concerning urban greening in contemporary China, the development of urban and peri-urban landscapes has been severely constrained by the leftist ideology and limited economic capability. This fact resulted in an exploitative use of existing forests and stagnant growth of urban greening.

3 1980–2000: Urban Gardening and Peri-Urban Afforestation for Landscape Beautification The Third Plenum of the 11th Central Committee of the Chinese Communist Party convening in Beijing between 18 and 22 December 1978 is a significant turning point of national policies. This meeting basically reversed the tendency toward the increasingly autarkic state of the country since 1949, preparing the way for the rapid development of China. Tree planting regained considerable attention, especially when the National Congress in 1981 officially assigned 12th March as the “Tree Planting Day”. Every year on this date since then, government officials at all levels

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appear on TV and other media to call for planting trees along roads, in parks, and along rivers (Yu et al. 2006). The major theme of urban greening and landscaping during these two decades of rapid development and urbanisation focused on an areal increase to replenish the shortage of green spaces and landscape beautification. In February 1981, the National Administration of Urban Construction (renamed as the Ministry of Construction in 1988 and then the Ministry of Housing and Urban–Rural Development in 2008) issued the Notice on the Work Plan for Urban Greening. The Notice clarified that green park area per capita should be increased to 4 m2 and green coverage ratio should achieve 30% in 1985. A more comprehensive statutory policy, Provisional Regulations on the Administration of Urban Greening, was published by the Ministry of Urban and Rural Construction and Environmental Protection in December 1982. After ten years of trial, the Regulations on Urban Greening was enacted In August 1992. This policy, serving as an umbrella for the development of urban green spaces, consists of 31 Articles covering multiple aspects of urban green spaces, such as planning, construction, and management. It legitimised that the green coverage ratio in new urban areas should not be less than 30%, and in old urban renewal areas should not be less than 25%. It also highlighted that the main purpose of urban tree planting is to improve the environment and beautify the city. In the same year, the National Administration of Urban Construction promulgated the Program of the National Garden City. In August 1997, the Evaluation Standards of the National Garden City was established; one of the most important variables is the ratio of urban green spaces. By the end of 1999, five badges covering 19 cities and one district had won this prestigious accolade. When in 1987 the first handbook on public parks and urban green spaces appeared in China, green landscapes were referred to as ‘the face of the city’ (Li 1987), a Chinese metaphor emphasizing the external appearance reflecting a city’s social and economic status. A major task thus for many municipal governments was to improve the aesthetic potentials of the urban environment, urban landscaping like forest parks, over-sized boulevards and squares as “window project”, “image-building project” to serve as symbols of status, wealth, and urbanity (Yu and Padua 2007; Junfeng 2016) and name card of the city (He and Zhao 2019). Visual quality was attached with great importance. Ornamental exotic species and human-made structures have replaced natural terrain and native vegetation, and they have become dominant showpieces of urban green spaces. Additionally, old and big trees were preferred and transplanted to achieve better and quicker visual effects, without appropriate and scientific posttransplantation maintenance (Yang and McBride 2003; Liu et al. 2004; Kong 2011). As a result, the survival rate of peculiarly shaped, feeble old trees tended to be very low, which in turn undermined the tentative aesthetic effects (Yang and McBride 2003; Da and Song 2008). Overall, this period is regarded by some scholars as a “city cosmetic movement” (Yu and Padua 2007) or “city-image campaign” (Wang 2018), in which urban green spaces have been eagerly promoted and extensively applied for beautifying the urban landscape, which was threatened by industrial and urban expansion invasiveness. Yet, the development of urban green spaces had been constrained by a low priority

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in policy agenda and a lack of financial resources and professional knowledge. It was not uncommon for urban parks to be transformed into commercial or residential buildings (O’Connor and Liu 2014; Chen and Hu 2015). In 1992, the first symposium on urban forests was convened in Tianjin, which signified that urban forest, as an innovative concept, made its way into the academic domain. In March 1995, the urban forest was mentioned in the Action Plan of Forestry: Agenda for the 21st Century (China) as an integral part of sustainable urban development (Ministry of Forestry 1995), which established the basis and goal for urban forest development (Zhang and Wang 2006; Zhang 2020). However, there had been little progress in urban forest planning and construction until November 2004 when the “Program of the National Forest City” was launched in the first China Urban Forest Forum held in Guiyang.

4 2001–2010: Urban Forests as a Countermeasure to Environmental Stresses At the beginning of the twenty-first century, rapid industrialisation and urbanisation since 1980 had resulted in a tense relationship between humans and nature, and severe environmental degradation and pollution, such as sand storm, acid rain, air pollution, urban flooding, and urban river contamination, and urban heat island (Li et al. 2004; Fu et al. 2007). For example, the monitoring report suggested that in 2002, more than 80% of 340 Chinese cities (with monitoring systems) were suffering from high levels of suspended particles (State Environmental Protection Administration 2003). Between 2008 and 2010, 62% of Chinese cities experienced frequent flooding due to the large-scale replacement of urban green areas with impervious surfaces (Zheng et al. 2016). In the wake of ecological and environmental crises, the 5th Plenum of the 15th Central Committee of the Chinese Communist Party issued the 10th Five Year Plan (2001–2005) in October 2000, emphasizing developing urban green spaces to improve urban environmental quality along with economic growth targets. Guided by this national strategic development plan, the State Council published the Notice on Strengthening Urban Greening Construction in May 2001, which served as a programmatic document guiding the direction and development of urban green spaces in China (Available from http://www.gov.cn/gongbao/content/ 2001/content_60905.htm). It emphasised green spaces’ environmental benefits and practical effectiveness, signifying a shift from solely pursuing aesthetic effects to addressing various environmental concerns. This document also highlighted forest belts’ construction as buffer zones to prevent sand storms and other environmental problems and preserve forest patches for ecological functions in peri-urban and rural areas. For the first time, the entrenched urban–rural dichotomy in China (Ye et al. 2013) was bridged (at least in greening/afforestation). The administrative barrier was attempted to be removed between traditional forests (i.e., mainly for commercial

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products and managed by the Ministry of Forestry, which was renamed as the State Forestry and Grassland Administration in 2018) and urban green spaces, parks and gardens, street trees (i.e., mainly for aesthetic and recreational benefits and managed by the Ministry of Housing and Urban–Rural Development). In September 2002, an international symposium on urban forest and eco-city was held in Shanghai. More than 80 scholars from 10 countries (such as the US, UK, Germany, Japan, South Korea, etc.) were attracted (Yang 2002). In this symposium, five key aspects of urban forests were discussed, focusing on scholarly understanding and best practices, roles of urban forests in eco-city construction, case studies of urban afforestation, urban tree management, and assessment of urban forests (Li et al. 2005). A key scholarly publication founded by the State Forestry and Grassland Administration, Journal of Chinese Urban Forestry, was inaugurated in 2003. It marked the maturation of urban forest as a scholarly concept in China’s socioeconomic context. The following year, the “Program of the National Forest City” was initiated by the State Forestry and Grassland Administration. It was successfully launched, transforming urban forest from focusing on scholarly understanding and knowledge advancement to practical implementation and performance evaluation (Xu and Zhu 2017). By the end of 2010, a total of 22 cities had been crowned with the title of the National Forest City. During this time, the multiple functions of urban forests (and urban green spaces) have been increasingly recognised, particularly air pollution mitigation (Wu et al. 2004). In line with this view, they were elaborately designed to counter environmental stresses facing many Chinese cities. In June 2002, the Classification Standards of Urban Green Spaces (CJJ/T85-2002) divided all urban greenery into five categories, mainly based on their functions, including public parks (for aesthetics and recreation), productive green spaces (nurseries for seedlings and saplings), protective green spaces (such as green buffers for various environmental benefits), attached green spaces (such as community gardens, street trees, and green spaces distributed within other municipal facilities), and other green spaces (such as forest parks and scenic forests located in peri-urban areas). This standard highlighted the multiple functions of urban green spaces and integrated urban green spaces and peri-urban green spaces into one holistic and systematic management and assessment framework (Shi and Woolley 2014). In October 2002, the Ministry of Construction (today renamed as the Ministry of Housing and Urban–Rural Development) issued the Urban Green Space System Plan Outline (Trial Version). And the Urban Green System Plan was regarded as an independent and legally binding part of the Master Plan of Urban Development (comprehensive planning of urban economic and social development, land use, spatial layout, and urban management). The spatial functions and associated vegetation composition and structure were directly guided and strictly controlled by the Urban Green System Plan (Syrbe and Chang 2018). Urban forests and urban green spaces were designed, constructed, and managed for multiple purposes, so that they can fulfill their potential roles in recreation, water source protection, biodiversity conservation, atmospheric carbon sequestration, air pollutant removal, urban heat island mitigation, and so forth (Liu et al. 2004; Yuwei and Jiangyun 2015). An example is the

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Fig. 1 Newly established urban forest in the peri-urban area of Beijing

newly established urban forest in Beijing under the Beijing Afforestation Scheme (Fig. 1), which aimed to not only satisfy residents’ recreation/leisure and aesthetic needs but also serve as a green buffer to mitigate soil erosion and prevent sand storms (Yao et al. 2019). However, an over-emphasis on the quantitative indices of the average park area and the green space ratio (the compulsive standards requested by the relevant national regulations), and a mismatch between green space layout and morphological as well as social-demographic characteristics of a city has been noticed (Xiao-Jun 2009). A comprehensive theorisation of urban forests largely characterised this decade as an independent research subject and an explorative implementation of urban forests as countermeasures to diverse environmental problems arising from unprecedented urbanisation and industrialisation. Underpinned by a series of statutory instruments and non-statutory campaigns, urban greening and urban forest construction have successfully secured political support and mass involvement and thus become an integrated part of short-term and long-term urban development planning.

5 Post 2010: Urban Forests as a Visual Manifestation of Ecological Civilization A key milestone in urban forest development, and an overall green development of all sectors of society, is an innovative paradigm, ecological civilization, introduced in the 17th National Congress of the Chinese Communist Party in 2007 to reverse and avert the enduring environmental and ecological problems/threats arising from

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previous prioritisation of economic growth and industrialisation-oriented urbanisation in China. And later on, it was elevated to a prominent position in the constitution in the 18th National Congress in 2012. It is promoted in the global arena as a new imaginary of a society featured by ecological sustainable modes of natural resource utilisation, production, and consumption, inhabited by environmentally conscious and responsible citizens (Hansen et al. 2018). Resonating with this innovative political discourse, the potential roles of urban forests have been extensively promoted in pursuing ecological progress and building a beautiful China to realise rejuvenation of ancient China’s Confucian philosophy and achieve an intrinsic harmonious relationship between humankind and nature (Hu 2018; An 2021). Firmly embedded in the context of an ecological civilization, urban forests, underpinning a full spectrum of benefits (from environmental, ecological, to sociocultural ones) and therefore sustainable urban development (Bush 2020), is increasingly understood as a critical component of urban ecosystems and ecological construction of cities (Zhang et al. 2016), as well as a nature-based solution (Chen et al. 2021), become popular in government rhetoric and policies. In 2016, the State Forestry and Grassland Administration published the Guidelines for Enhancing Urban Forest City Construction (for further details, see http://www.forestry.gov.cn/zlszz/5354/201 90517/145245055889993.html). This major national policy highlighted several key tasks and directions of urban forest development. The first task was an expansion from the National Forest City program, which primarily focuses on a target of achieving forest area per capita, to the National Forest City Cluster campaign, which emphasises the maintenance and preservation of the connectivity of forest patches across neighboring cities and the establishment of an integrated urban forest management scheme to improve the connectivity urban and peri-urban landscape, improve ecological resilience, and minimise habitat fragmentation during the process of extensive urban expansion (Wang 2016). By the end of 2019, there are 194 National Forest Cities and six National Forest City Clusters are under construction. Another key component of this policy is to strengthen the quality of urban forest, showing an important shift from quantitative to qualitative criteria in the performance assessment of the National Forest City and the National Forest City Cluster. For example, in the new town of Xiong’an (southwest of Beijing, Hebei province), an afforestation project of more than 13,000 hectares (the Millennium Forest endorsed by President Xi Jinping) has been planned, for which a mixture of more than 100 tree species would be used, signifying a change from monocultures to ecological restoration of the high-quality zonal forest. Particularly, the country’s Forest Law (2019 revision), which came into force in July 2020, for the first time, includes explicitly the term of urban forest, being a way leading to homeland beautification and ecological civilization (Article 42). In 2019, the Ministry of Ecology and Environment issued the “Indicators for Ecological Civilization Construction Demonstration Cities”, in which forest/grassland coverage is incorporated as a key index for assessing a city’s ecological safety and urban park area per capita is regarded as an index for a city’s ecological living. Clearly, articulating urban forests (as an integrated system combining traditional urban green spaces constructed for aesthetics and recreation, with peri-urban

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woodlands constructed for various environmental and ecological functions) in this national guiding policy is still lacking. It urges relevant policymakers, scholars, and practitioners to construe urban forests as building block of the urban ecosystem, an integral component in urban transition, a stronghold of civic responsibility, and a key dimension of the nature of human flourishing.

6 Concluding Remarks Reforesting urbanised cities and constructing urban forests could bring radical changes towards ecological civilization and readily visible changes to where most of the population are residing and what they come into contact with every day. Figure 2 illustrates the chronological roadmap of urban greening and urban forest development in contemporary China, from sporadic urban greening to extensive landscape beautification, followed by a shift from environmental outcome-driven urban forest construction to treating urban forests as an integral framework and visual showcase of the subtle ecological civilization ideology. As such, urban forests should be treated as important policy components amidst the institutionalisation of ecological civilization. Preserving and constructing multifunctional urban forests will symbolise the successful ecological civilization of the urban landscape, enlighten citizens about what constitutes ecological civilization. It also entails achieving ecological civilization and essentially mitigating various environmental and social pressures during the process of China’s rapid urbanisation and growth. It is unquestioned that China, the most populous country and the second-largest economy across the globe, is strongly committed to promoting ecological civilization as an innovative paradigm for its sustainable development and as a new vision for the global future. The successful transformation of this political discourse into expected outcomes covers multiple dimensions, including green economy, innovative technology, and eco-civilized ways of life (Hansen et al. 2018). The concept of ‘urban forest’ is situated in the center of transformative actions towards urban transition, is an inseparable part of an intrinsic harmony between humankind and nature, and is a key dimension of human flourishing. Undoubtedly, the importance of urban forests has been fully recognised in several statutory policies and non-statutory instruments issued by the state and local authorities, demonstrating China’s leading role in urban forestry and urban greening across the globe. Nevertheless, some necessary prerequisites for effective urban forest planning include (1) a solid knowledge base about the dynamic and multi-faceted characteristics of urban forests and comprehensive criteria for evaluating the performance of urban forests for evidence-informed planning, (2) institutional coordination and synchronisation, which can generate complementarities (instead of duplication) for effective intersectoral planning, and (3) an enhanced citizen awareness and appreciation for public–private collaborative planning (Sipilä and Tyrväinen 2005). With these prerequisites being met, holistic, systematic, and participatory urban forest development and management plans can be adequately

Fig. 2 Roadmap of urban greening and urban forest development in China

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established (Hu 2017), and thereupon a green, resilient, and self-maintaining way could be paved for an eco-civilized future of all humanity.

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Analysis of Policy and Regulatory Landscapes for Green Roof Implementation in China Bao-Jie He, Xin Dong, and Ke Xiong

Abstract Green roofing is a nature-based solution to urban environmental problems and an alternative for urban designers to provide additional spaces for outdoor activities and entertainment under the trend of urban open space reduction. However, several barriers hinder green roofing implementation, including lack of government policy, unsound technological development, high initial cost and long payback period, and individual unwillingness. Governmental policy is the most effective strategy for sustainable initiative implementation by overcoming their barriers. Therefore, this chapter aims to reveal policy and regulatory landscapes for green roofing. In particular, the analysis is conducted in China, a country undergoing rapid urbanisation and severe environmental, economic and social challenges in cities. In particular, this chapter presents an overall picture of policy and regulatory landscapes for green roofing in mainland China across the national, provincial, and city scales, considering mandatory and guiding terms. The analysis indicates that there is no specific national document for roof greening promotion. Nevertheless, in the central government’s guide, opinion, notice, and technical standards and specifications, roof greening is advocated in other projects, such as environmental protection, green building, sponge city, and urban landscaping. Roof greening is mostly mentioned for green space or landscape benefits, but other functions have not been particularly defined. Roof greening has been more clearly framed in province-level technical guide/specification, legislated regulations, governmental opinion, provincial plan, and economic support. The results indicate that the provincial policies and regulations are uneven in geographical distribution, mainly in the east part of mainland China. Technical guide/specification is the main approach to promoting green roofs, followed by the legislated specification, governmental opinion, and provincial plan and economic support. However, among the 25 provinces that have suggested green roof implementation, only ten provinces have clarified the specific requirements of intensive and extensive green roofs. In addition, incentives for green roof implementation have been analysed, indicating that urban greening conversion is the most B.-J. He (B) · X. Dong · K. Xiong School of Architecture and Urban Planning, Chongqing University, Chongqing 400045, China Key Laboratory of New Technology for Construction of Cities in Mountain Area, Ministry of Education, Chongqing University, Chongqing 400045, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_4

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common way to green roofing promotion at both province and city scales, followed by the fiscal subsidies and then awards. City-level incentives are more inspiring, sounder, and more comprehensive than province-level incentives. In addition, the results indicate that while the Urban Greening Ordinance exhibits a strong top-down impact on provincial legislated specifications, the policy and regulatory landscapes for green roof implementation show a strong bottom-up pattern from cities to provinces and then to mainland China. Overall, this chapter is of significance to the understanding of the policy and regulatory landscapes for green roof implementation and provides a reference to the next-step reform of the current policy system. Keywords Green roof · Policy · Roof greening · Regulations · Regulatory landscape

1 Introduction The world expects an increase in urbanisation to accommodate people in cities with extensive and sound infrastructures like houses, transportation, sanitation, health care, communication, utilities, etc. Fortunately, the global urbanisation rate had witnessed a rapid increase from about 33% in 1960 to about 57% in 2017. Moreover, it is projected that 68% of the global population will live in cities by 2050 (UN-DESA 2018). Nevertheless, the fast population migration towards cities is also a mega challenge of the world, with a series of associated challenges such as economic development, environmental quality, climate change, health, and well-being. To address such challenges, there is an urgent need to take actions by all professions of the society to ensure the cities and human settlements are inclusive, safe, resilient, and sustainable, according to the United Nations Sustainable Development Goals (SDGs) (UN 2015). One of the critical problems, along with urbanisation, is reducing urban greening since the originally natural landscapes have been extensively modified for housing and pavements. In particular, the reduction of urban greening leads to several problems of urban flooding, urban heat island (UHI) effects, water and air pollution, biodiversity reduction, and the deterioration of human physiological and psychological health (He 2019). While it seems simple to deal with such problems through planting vegetation, limited land availability for urban green infrastructure is a prominent problem for urban planners and designers in practice. Alternatively, rooftop spaces have been increasingly recognised as valuable land resources for green infrastructures (Zhang et al. 2020). Rooftop spaces are also achievable since (building) rooftop spaces account for at least 20% of the urban spaces for sparse cities and even more than 40–50% for compact cities. The adoption of rooftop spaces for urban greening is known as the practice of planting vegetation overgrowing medium on the building roofs wholly or partially with the inclusion of additional layers such as substrate, waterproofing, root barrier, insulation, drainage and retention, and filter layers (Fig. 1). According to the growing medium, there are two types of green roofs: extensive green roofs and intensive

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Fig. 1 The configuration of extensive green roofs (left) and intensive green roofs (right)

green roofs. The former is lightweight with the typical vegetation of drought-tolerant sedums and grasses, which are accessible for installation and maintenance on singlefamily and multi-family residential roofs. In contrast, intensive green roofs, all known as the traditional roof gardens, plant with small trees and shrubs in growing medium with large depths over commercial buildings. It is more labor-intensive and requires more maintenance compared with extensive green roofs. Apart from studies of technical requirements, there have been various studies on green roof performance in terms of outdoor thermal environment improvement, urban flooding alleviation, energy efficiency, air and water purification, noise prevention and reduction, biodiversity improvement, etc. For instance, existing studies revealed the green roofs could help reduce indoor temperature and reduce the reliance on airconditioning (AC) systems, where the energy usage for AC systems could be reduced by 25–80% in summer (Wong et al. 2003) and particularly the cooling load reduction in hot climates could be reduced by 32–100% (Alexandri and Jones 2008). The use of green roofs could help reduce the temperature within communities by 0.2–1.4 °C, and the cooling areas could be extended under windy conditions (Morakinyo et al. 2017; Zhang et al. 2019). Green roofs are capable of filtering and absorbing vehicular and industrial pollutants. A study estimated the air purification capacity of a green roof (19.8 ha in area) in Chicago, U.S., indicating that the green roof could remove annual air pollutants by 1.675 tons (Yang et al. 2008). Green roofs could also insulate and reduce noise by 5–13 dB at low and mid transmission frequencies and 2–8 dB at high frequencies (Connelly and Hodgson 2008). Moreover, green roofs are considered the ‘fifth surface’ beauty to provide recreational, aesthetic, and psychological values to cities (Mesimäki et al. 2019). Green roofs are conducive to people’s mental health who are working under significant stresses by providing psychological rehabilitation (Feng and Hewage 2018).

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Fig. 2 Prefabricated and lightweight green roofs. (Source Photos taken by the authors at Chongqing University, China)

Given the environmental, economic, and social benefits of green roofs, we can verify that green roofs have been gradually implemented. However, the adoption of green roofs in cities is still limited in pace and size because of several barriers such as a lack of governmental policy, unsound technological development, high initial cost, long payback period, and individual reluctance (Zhang and He 2021). In particular, most existing buildings have not been constructed with a green roof structure, making it challenging to build a green roof well. Only prefabricated and lightweight green roofs with a shallow soil depth are allowed (Fig. 2). There is a need to retrofit existing buildings in the pursuit of better green roof performance. To overcome such barriers to green roof adoption, governmental policies and support are essential. Governmental actions can provide robust environments and stringent enough for driver developers, planners, designers, engineers, and others to adopt green roofs. At the same time, the propaganda offered by the government can effectively inform end-users of green roof information and improve their awareness and acceptance of green roofs (Zhang and He 2021). In particular, the governmental policies could be implemented in either compulsory or voluntary ways, where the compulsory ways such as regulations, specifications, and standards are capable of promptly promoting green roofs towards the market. These could also lead to strategies such as incentives and guidance that are conducive to guide stakeholders to adopt green roofs voluntarily (Zhang and He 2021). For instance, states and cities in the U.S. and Canada have released various programs on tax credits, density bonuses, financial grants, sewer fee reduction, below-market-rate loans, and green building assessment to incentivise different stakeholders to adopt green roofs (Savarani 2019). Accordingly, the analysis of policy and regulatory landscapes of green roof adoption in cities, states, and nations is meaningful to understand how green roof adoption is framed and to identify the gap between green roof adoption and present policy and regulatory landscapes. In recognition of such significances, this chapter aims to review green roof adoption’s policy and regulatory landscapes. The study is conducted in China, a developing country undergoing the reduction of urban greening due to fast urbanisation and suffering severe urban environmental problems like urban

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flooding, air pollution, water pollution, UHI effects, etc. This study is of significance to provide an overview of the policy and regulatory landscapes of green roof adaption in China and provide a reference for the next-step reform of the green roof policies and regulations. The remainder of this chapter includes five sections. Section 2 presents the structure of green roof policies and regulations at the national level of mainland China. Section 3 analyses the province-level policy and regulatory landscape for green roof promotion, followed by the provincial requirements and incentives for green roofing in Sect. 4. Section 5 further analyses the city-scale incentives for green roof promotion. Afterward, Sect. 6 summarises and concludes this chapter.

2 Framing Green Roof Adoption by the National Policies and Regulations National policies and regulations can be regarded as the top-level design through considering all possible elements and causes at different levels of a specific problem for comprehensive solutions. National policies and regulations are the most powerful to guide lower-level policies and regulations and the approaches to achieving the targets. Accordingly, this section is designed to analyse how China’s national policies and regulations frame green roof adoption through examining the expected benefits of a green roof to society and analyzing the plans for green roof implementation, as shown in Table 1. Table 1 Policy and regulation landscape of green roof implementation at the national scale in China No. Type

Name

Content relevant to green roof

Agency/ministry

1

Regulation

Urban greening ordinance (implemented on 01/08/1992, revised on 01/03/2017)

Requirements for urban greening planning and construction, protection and management

State Councils

2

Guidance and Opinions on the opinion construction of conservation-oriented urban landscaping (30/08/2007)

Key measures to develop conservation-oriented urban landscaping: promote vertical greening in all available places, and promote roof greening in areas where conditions suitable (suggestions)

Ministry of construction

(continued)

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Table 1 (continued) No. Type

Name

Content relevant to green roof

Agency/ministry

3

Guidance and Measures for the management administration of national sports training bases (23/12/2013)

Landscape National Department environment: greening of Sport area does not include roof greening, vertical greening, and land with a cover of less than 2 m (requirements)

4

Notice

Notice of the “13th five-year” ecological environment protection plan (05/12/2016)

Maintain and restore State Councils the urban natural ecosystem: expand ecological spaces such as green spaces and water areas, rationally plan and construct various types of urban green spaces, and promote vertical greening and roof greening (suggestion)

5

Guidance and Guiding opinions on opinion promoting the construction of sponge city (16/10/2015)

Promote sponge-type State Councils buildings and related infrastructure. Promote sponge-type buildings and communities, adopt roof greening …, according to local conditions (suggestion)

6

Guidance and Guiding opinions on opinion accelerating the development of agricultural circular economy (01/02/2016)

Encouragement of the adoption of green roof for enhancing the ecological function of adsorbing air pollutants, alleviating the urban heat island effect, and expanding the urban green space (brief suggestions)

National Development and Reform Commission, Ministry of Agriculture, National Forestry and Grassland Administration

7

Guidance and Opinions on further opinion strengthening the management of urban planning and construction (21/02/2016)

Restore the natural ecology of the city: Encourage the development of roof greening and vertical greening (suggestions)

Central Committee of the Communist Party of China, State Councils

(continued)

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Table 1 (continued) No. Type

Name

Content relevant to green roof

Agency/ministry

8

Notice

Notice of the application for the 2012 science and technology plan projects in MOHURD (09/11/2011)

Land saving and underground space development and utilisation technique system: roof space utilisation technology (rooftop parking lot construction technology, roof greening technology, etc.)

Ministry of Housing and Urban–Rural Development

9

Standard

Assessment standard for green building (GB/T 50378-2006/2019)

Measures to Ministry of Housing counterbalance urban and Urban–Rural heat island intensity: Development The ratio of roof greening area, the horizontal projection area of solar panels, and the roof area with a solar reflectance of at least 0.4 should reach 75% (suggestion)

10

Code

Code for the design of urban green space (GB 50420-2007)

Provisions on structural load and waterproofing, medium, location and species (brief specifications)

Ministry of Housing and Urban–Rural Development

11

Code

Code for construction and acceptance of landscaping engineering (CJJ82-2012)

Drainage layer and aquifer: If the pebbles are used for drainage in roof greening, the particle size should be 3–5 cm (requirement)

Ministry of Housing and Urban–Rural Development

12

Standard and supplement

Technical rules for evaluation of green super high-rise buildings (May 2012)

Reasonably adopt vertical greening methods: possibly use the roof greening and vertical greening on attached podium of super high-rise buildings

Ministry of Housing and Urban–Rural Development

(continued)

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Table 1 (continued) No. Type

Name

Content relevant to green roof

Agency/ministry

13

Specification

Technical specification for planted roof (JGJ 155-2013)

Provisions on green roof materials, design, construction, quality acceptance, maintenance and management (comprehensive specifications)

Ministry of Housing and Urban–Rural Development

14

(Technical) guide

Construction guideline of Sponge City in China—low impact development of stormwater system (trail) (October 2014)

Controlled detailed Ministry of Housing planning: Green roof and Urban–Rural ratio is one of the Development control objectives and indicators (suggestion) Technique selection: green roof is a kind of techniques for runoff control via water infiltration, reducing pollutants by 70–80% and having good landscape effects (assessment)

15

Standard

Assessment standard for green retrofitting of existing building (GB/T 51141-2015)

The ratio of the total Ministry of Housing green area and roof and Urban–Rural greening area over the Development public building site to the site area reaches 25% (suggestion) The ratio of roof greening area, the horizontal projection area of solar panels, and the roof area with a solar reflectance of at least 0.4 should reach 75% (suggestion)

16

Notice

“12 five-year” development plan for building materials industry

Development of Ministry of Industry materials and products and Information relevant to green roof Technology

Document type, agency, and view: 16 documents relevant to the green roof techniques and adoption have been released at the central government and ministry level. Seven out of the 16 documents are in the form of guidance, opinion, and notice, and another seven are in the form of code, standard, specification, and technical guide. The national documents are mainly delivered by the Central Committee of the

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Communist Party of China, State Councils, Ministry of Housing and Urban–Rural Development (MOHURD), etc. Overall, most agencies and ministries promote the use of green roofs. The MOHURD suggests using green roofs in green building construction, sponge city development, and urban landscaping through a series of national codes, standards, specifications, and technical guides. Moreover, the MOHURD is the only agency or ministry legislating green roof adoption. In comparison, the Central Government and State Council have suggested green roof adoption in the form of notice, guidance, and opinion. However, such suggestions are relatively brief without specific instructions. The Ministry of Construction (MOC), National Development and Reform Commission (NDRC), Ministry of Agriculture (MOA), National Forestry and Grassland Administration (MFGA) have also contributed to green roof adoption. Nevertheless, the National Department of Sport (NDS) does not recognise roof greening as an approach to improving landscape environments in training spaces. Document release timeline: Overall, the green roof has been advocated in three stages. The first stage is in 2006–2007 for urban green construction, in terms of green building and urban green space. In particular, the Assessment Standard of Green Building firstly suggested the green roof adoption, with the suggestion of using vertical greening and roof greening properly for land saving and outdoor environment around public buildings, in 2006. In 2007, the green roof was suggested to improve the urban green space and conservation-oriented landscaping. The second stage is in 2011–2013, with the financial support to the research projects on the green roof, the requirements of green roof construction in landscaping engineering, the development of green roofing materials and products, the use of green roof in super high-rise buildings. Afterward, the third stage is in 2015–2016, focusing on the sponge city development and natural ecology in urban planning and design. In addition, while the Urban greening ordinance released by the State Council in 1992 did not consider green roofing initially, it was thought to be a guideline for later urban greening (including roof greening) development at the provincial scale (Also see Sect. 4).

2.1 Green Roof Benefits Green roofs can potentially generate multiple benefits across energy-saving, urban heat island mitigation, roof longevity prolongation, air and water purification, runoff control, noise reduction, etc. However, such benefits have not been fully valued in existing national documents. In particular, the development of agricultural circular economy, collaboratively suggested by the NDRC, MOA, and NFGA, has been the only document that highlights several aspects of benefits of green roof including air pollution reduction, urban heat island mitigation, and urban green space expansion. The notice, suggestion, and guidance suggested by the State Councils and Central Committee have primarily concerned benefits of urban greenery improvement, the direct effects of ecological environment protection, and sponge city construction.

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This is highly related to the national strategies of ‘the construction of ecological civilization’ and ‘sponge city’ advocated by the 18th National Congress of the Communist Party of China in 2012. The MOC suggested originally pursued urban landscape improvement through green roofing, and the NDS also focused on the urban landscape while it holds an opposing view. The MOHURD has indicated various benefits such as land saving and underground technology (No. 8), urban heat island mitigation (No. 9), urban green space or landscape improvement (No. 10 and No. 11), and runoff control (No. 14) in different codes, standards, and specifications. It should be particularly noted that green roofing has been one of the critical technologies in codes, standards, and specifications relevant to green buildings (No. 9, No. 12, and No. 15). Nevertheless, the technical specification for a planted roof (JGJ 155-2013) has not well documented the benefits of a green roof (No. 13). Overall, the analysis indicates that the recognition of green roof benefits in existing national documents is limited. Provisions and function: The release of these national documents on green roof adoption has mostly been voluntary and promoted (nine out of 14 documents), except for the exclusion of green roofs as an approach to improve landscape environments of training sites. Such conclusions are made based on the words ‘promote’, ‘possibly use’, and ‘encouragement’. The standards relevant to green building (No. 9, No. 12, and No.15) could be more critical than the guide, notice and opinion, to suggest the green roof adoption, as these standards suggest green roof is an option to improve green building recognition. Nevertheless, the technical guide on the sponge city (No. 14) suggests that a green roof is one of the control objectives and indicators of the control detailed planning. The technical specifications (No. 13), technical rules (No. 12), and codes (No. 10 and No. 11) play a role in providing techniques on how to construct a green roof, such as the structure, substrate materials, medium, location, and species. However, the Code for construction and acceptance of landscaping engineering (CJJ82-2012, No. 11) and the Technical Rules for Evaluation of Green Super High-rise Buildings (May 2012, No. 12) have only mentioned briefly green roof location and substrate materials through one term, respectively. In comparison, the Code for the design of urban green space (GB 50420-2007) indicates the provisions on structural load and waterproofing, medium, location, and species partially. The Technical specification for a planted roof (JGJ 155-2013, No. 13) indicates a series of provisions on green roof materials, design, construction, quality acceptance, maintenance, and management. Nevertheless, the existing documents have not provided a sound and detailed instruction or catalogue about green roof construction.

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3 Framing Green Roof Adoption by Provincial Policies and Regulations Compared with national policies and regulations, province-level policies and regulations could be more feasible for local implementation as they fit into local characteristics of different provinces, including climatic conditions, economic development, and social demands. Accordingly, this section presents the provincial policies and regulations on green roofs adoption. The province-level policies and regulations considered in this section are composed of those that directly promote green roof development rather than the ones indirectly suggesting green roofing as one of the solutions to urban environmental problems such as urban heat islands, urban flooding, and noise, air, and water pollution. The province-level policies and regulations are considered in terms of technical guide/specification, legislated regulations, governmental opinion, provincial plan, and economic support, as shown in Figs. 3, 4, 5, 6, 7. Figure 3 presents provincial policies and regulations on green roof adoption in mainland China. In total, there are 82 pieces of provincial policies and regulations. The release and distribution of such policies and regulations are highly uneven. Provinces in the east part of mainland China are the prominent place of origin. In comparison, the west part, including Xinjiang, Tibet, Qinghai, Ningxia,

Fig. 3 Number of provincial policies and regulations on green roof adoption in mainland China (by April 2021)

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Fig. 4 Technical guide and specification in different provinces in mainland China (by April 2021)

Fig. 5 Distribution of provincial legislated specifications on green roof adoption in mainland China (by April 2021)

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Fig. 6 The governmental opinions on urban greening for green roof promotion in mainland China (by April 2021)

Fig. 7 Provincial plan and economic support relevant to green roof promotion in mainland China (by April 2021)

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and Gansu, has not relevant released policies and regulations. Beijing, Shanghai, Zhejiang Province, and Hainan Province are the four that have released six pieces of policies and regulations. Following this, Chongqing and Henan Province are also leading in releasing policies and regulations for green roof promotion, with five pieces of policies and regulations. Tianjin and Guangxi Province present four pieces of policies and regulations. In addition, provinces like Heilongjiang and Liaoning have not presented effective policies and regulations for roof greening, with only one piece—Urban Greening Regulations (Fig. 5)—in order to follow national urban greening regulations (Table 1). The results also show that the four municipalities and provinces in the southeast part of China are more active. Figure 4 presents the technical guides and specifications for green roofing. The guides and specifications include the information of green roof categories, construction materials, design and construction techniques, maintenance requirements, waterproofing, green roofing area measurement, calculation, and special Atlas. In particular, the number of technical guides and specifications reaches 30, higher than that of legislated specifications (25), governmental opinion (16), provincial plan (9), and economic support (2). The technical guide system in mainland China is not sound. First, the geographic distribution is uneven, where most provinces in the west and northeast part of China have not published technical guides. Such phenomena are partly because of the lack of governmental advocations, such as Xinjiang, Tibet, Qinghai, Ningxia, and Gansu. Many provinces, such as Hebei, Jilin, Hubei, Guizhou, and Inner Mongolia, have not released technical guides, while they have released the governmental opinions and legislated specifications. This result indicates that the technical guide is delayed to scientifically support governmental promotions. Second, amongst provinces that have released technical guides and specifications, such technical guides are mostly limited to the technical specifications for roof greening (including green roofing definition, materials, species, design, construction, and maintenance). In comparison, the green roofing area calculation and measurement are only available in Zhejiang (measurement), Henan (measurement), and Guangxi (special Atlas). Such results indicate an urgent need for measurement methods and a special Atlas to improve developers’ interest and readiness for green roofing design. It should be noted that although many Provincial People’s Governments have not released a governmental opinion on green roof promotion, provinces like Tianjin, Chongqing, Zhejiang, Fujian, Jiangxi, Hunan, Guangdong, and Shaanxi are active to set up technical guide and specifications spontaneously. Such results indicate the bottom-up development of the green roof technical guide at the provincial level. For instance, Tianjin released the Technical specification for constructing the urban greening project in Tianjin (DB29-68-2004) and the Technical specification of greening buildings for Tianjin (DB29-220-2013). Chongqing released the Technical specification for planted roofs (DBJ/T50-067-2007) and the Technical standard for application of vertical planting on civil building (DBJ50/T-313-2019), as shown in Fig. 4. Figure 5 presents the legislated specifications on green roof adoption. Overall, the provinces that have published legislated specifications are mainly in the east part of

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mainland China, except for Shandong, Jiangsu, Anhui, and Guangxi. Most provinces have only published only one specification, of which the legislated specifications are mostly released in the form of Urban Greening Regulations, following the requirements of the State Council (Table 1). Such results indicate that the national urban greening regulations are forceful to enable provincial governments to legislate the top-down pattern for urban greening improvement. The results further indicate that only three provinces, including Chongqing, Hebei, and Zhejiang, have published two legislated specifications. Based on the Urban and Rural Planning Law of PRC and the Urban Greening Regulations, Chongqing has published the Technical regulations on green space management for construction projects to locally legalise the planning, construction, protection, and management of urban landscaping in both urban and town planning areas in Chongqing. Similar to Chongqing, Hebei has implemented the Measures for the administration of urban landscapes on March 1, 2012, for the planning, construction, protection, supervision, and management of urban landscaping. For the same purpose, Zhejiang implemented the Measures for the Administration of Urban Greening on March 13, 2014. It should be noted the provincial specifications of roof greening is mainly to improve urban greening and promote urban ecological environments. Figure 6 presents the governmental opinions in different provinces that have mentioned the intention of promoting roof greening. The distribution suggests that provinces that have released governmental opinions are in the east part of mainland China. However, in the southeast parts, the provincial governments, including Hunan, Jiangxi, Zhejiang, Fujian, and Guangdong, have not indicated their province-wide opinions, while such provinces are active in formulating and legislating the technical guide specifications (see Fig. 4). This pattern suggests the spontaneous policies and regulations development of green roofs, namely bottom-up pattern, by specific industries. Moreover, Heilongjiang and Liaoning are delayed in terms of governmental opinions relevant to the green roof adoption. In addition, the advocation of roof greening adoption is one of the strategies for improving urban greening. Nevertheless, several provinces have advanced the development of vertical greening, such as Beijing, Shandong, Henan, and Shanghai. This is an important transition from the general advocation of the improvement of urban greening to highlight the adoption of roof greening particularly. In particular, the Guiding opinions on strengthening the urban vertical greening released by Shandong Province on May 16, 2019, have suggested extensive benefits of green roofing by expanding green space, reducing dust and noise pollution, improving air quality, alleviating the heat island effect, and reducing building energy consumption, marking an accurate and comprehensive definition and recognition of green roof. Shandong’s governmental opinions also make a compulsory requirement that new public buildings, including government, school, hospital, cultural and sports buildings, should at least build 60% of the accessible green roofing areas. In addition, Guangxi also released the Guiding opinions on pilot work in park city on March 4, 2020, with the concept of the garden city, in which the annual increase of vertical greening should be at least 20,000 sqm.

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Figure 7 presents the provincial plan and actions that can potentially promote green roof adoption. Seven provinces, including Beijing, Tianjin, Henan, Shanghai, Zhejiang, Anhui, and Jiangxi, have provincial plans relevant to green roofs. Such eight provinces are in the east part of mainland China. In particular, Henan issued two provincial plans for pollution prevention and control, and forest ecological construction in 2018. Tianjin and Shanghai set up plans for cityscape, while Beijing launched the plans for urban environment improvement. Innovatively, Zhejiang is committed to green communities to implement the Scheme of Green Community Construction proposed by the MOHURD and NDRC. In addition, Anhui is implementing new urbanisation development, and Jiangxi focuses on improving urban function and quality. Figure 7 presents economic support that can be potentially suitable for green roof development. Shanghai launched special support for its building energy-saving projects, where the green roof is one of the approaches for energy use reduction. Chongqing is launching the measures for encouraging 3D urban greening (awaiting approval without implementation, not included in Sect. 4) to save land, expand green space, beautify the urban landscape, improve the ecological environment, and highlight the characteristics of Chongqing’s mountainous city. Moreover, the Chongqing case suggests that new, rebuilt, and expanded public buildings with flat roofs shall implement roof greening. The proportion of roof greening area shall not be less than 50% of the accessible roof greening area. It also sets the incentive measures by converting the roof greening areas into urban affiliated green areas, societal investment projects, economic subsidies, and other forms of awards.

4 Provincial Requirements and Incentives for Green Roofing This section further analyses provincial instructions on green roofing (Table 2) and the compulsory requirements and incentives (Table 3) for green roof adoption. Whist 25 provinces have advocated green roof adoption (see Fig. 3), only ten provinces have well-defined the green roof types for implementation (Table 3). In comparison, seven provinces, including Tianjin, Jiangsu, Anhui, Guangxi, Sichuan, Shanxi, and Henan, have not presented requirements of garden roof, simple roof, or combined roof. Such instructions are presented in the technical guide/specification of roof/vertical greening. In general, a garden roof should have a green roofing area of more than 60% of the building roof area in Beijing, Chongqing, Jiangxi, Shandong, Hubei, Hunan, and Guangdong. In Fujian, comparatively, the thresholds of both garden roof and simple roof are only 50%. However, Shanghai and Chongqing have not presented the green roofing threshold for a garden city based on the building roof area. Moreover, Beijing, Jiangxi, Hubei, and Hunan have similar instructions for the proportion of green planting area (Agpt ≥ 85% Agrf ), pavement area (Apave ≤ 12% Agrf ), and

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Table 2 Requirements of garden roof and simple roof in technical guide and specifications Province

Intensive (garden)

Beijing

Agrf ≥ 60% Arf Agrf ≥ 80% Arf Agpt ≥ 85% Agrf , Apave ≤ 12% Agrf , Asgo ≤ 3% Agrf Agpt ≥ 90% Agrf

Extensive (simple)

Shanghai

Garden roof greening: hsd ≥ 60 cm Agpt ≥ 70% Agrf , Ats ≥ 70% Agpt Apave ≤ 25% Agrf Asgo ≤ 5% Agrf

Chongqing

Agrf ≥ 60% Arf Agpt ≥ 80% Agrf , Apave+sgo ≤ 20% Agrf

Agrf ≥ 80% Arf Agpt ≥ 90% Agrf , Apave ≤ 20% Agrf

Zhejiang

Agpt ≥ 70% Agrf , Ats ≥ 70% Agpt Apave ≤ 25% Agrf Asgo ≤ 5% Agrf

Agrf ≥ 80% Arf Agpt ≥ 90% Agrf

Fujian

Agrf ≥ 50% Arf , Apave ≤ 10% Agrf , Asgo ≤ 7% Agrf

Jiangxi

Agrf ≥ 60% Arf Agrf ≥ 80% Arf Agpt ≥ 85% Agrf , Apave ≤ 12% Agrf , Asgo ≤ 3% Agrf Agpt ≥ 95% Agrf

Shandong

Agrf ≥ 60% Arf

Hubei

Agrf ≥ 60% Arf Agrf ≥ 80% Arf Agpt ≥ 85% Agrf , Apave ≤ 12% Agrf , Asgo ≤ 3% Agrf Agpt ≥ 95% Agrf , Apave ≤ 10% Agrf

Hunan

Agrf ≥ 60% Arf Agrf ≥ 85% Arf Agpt ≥ 85% Agrf , Apave ≤ 12% Agrf , Asgo ≤ 3% Agrf Agpt ≥ 90% Agrf

Guangdong

Agrf ≥ 60% Arf Agrf ≥ 80% Arf Agpt ≥ 65% Agrf , Apave ≤ 12% Agrf , Asgo ≤ 5% Agrf Agpt ≥ 95% Agrf

Combined roof greening: hsd ≥ 30 cm Agpt ≥ 80% Agrf Ashb ≥ 50% Agpt Apave ≤ 20% Agrf

hsd ≥ 10 cm Agpt ≥ 90% Agrf Apave ≤ 10% Agrf

Agrf ≥ 80% Arf

Note Arf denotes roof area, Agrf denotes green roof area, Agpt denotes green planting area, Apave denotes paved area, Asgo denotes small garden ornament area, Ats denotes tree and shrub covering area, Ashb denotes shrub covering area, hsd denotes average soil depth

small garden ornament area (Asgo ≤ 3% Agrf ). Shanghai and Zhejiang suggest a green planting proportion of ≥70% Agrf , a pavement proportion of ≤25% Agrf and a small garden ornament proportion of 5% Agrf . Guangdong suggests a green planting proportion of ≥65% Agrf , a pavement proportion of ≤12% Agrf , and a small garden ornament proportion of 5% Agrf . Their sum could be lower than 100%, giving the spaces for building facilities (e.g., HVAC, lift). Fujian suggests a threshold of pavement proportion of ≤10% Agrf and a small garden ornament proportion of 7% Agrf . In comparison, Shandong does not present a sub-requirement on the green planting area, pavement area, and small garden ornament area. It should be noted that Shanghai has also suggested the requirements for combined roof greening, which could allow developers or owners to construct green roofs flexible. The requirements for a simple green roof are different from those for a garden roof, except for the case in Fujian. The green roof area should be at least 80% of the building roof area in Beijing, Chongqing, Zhejiang, Jiangxi, Shandong, Hubei, and

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Guangdong. Shanghai does not have a requirement for a green roofing area based on the building roof area. Hunan issues a higher proportion of roof greening, at least 85% of the building roof area. The green planting area should be at least 90% of the roof greening area, in which Jiangxi, Hubei, and Guangdong suggest 95%, while Shandong has not set sub-requirements. Table 3 presents the methods that ten provinces, including Beijing, Shanghai, Chongqing, Hebei, Shanxi, Jiangsu, Zhejiang, Shandong, Hainan, and Guangxi, Table 3 Incentives for green roof adoption in different provinces Provinces

Urban greening (with a specific conversion coefficient)

Fiscal subsidies

Award

Beijing

A coefficient of 20% (soil depth 0.6–0.8 m), and the maximum conversion ratio could reach 50% of the auxiliary green area

Flood control fee reduction and exemption (the auxiliary green area could meet the urban planning requirements without the inclusion of roof greening Garden style roof: 100–150 RMB/sqm Simple-style roof: 50–100 RMB/sqm

An important indicator of Municipal garden-style unit, Greening and beautifying advanced units and individuals Compensation with awards

Shanghai

The coefficient depending on building base-roof height difference (roof height) and the maximum conversion ratio could reach 20% of the auxiliary green area: 12 m: 0

Garden-style roof: 200 RMB/sqm Combined-style roof: 100 RMB/sqm Simple-style roof: 50 RMB/sqm

Chongqing A coefficient of 20% 50 RMB/sqm for specific (suitable for low-rise districts building and multistorey buildings with a maximum height of 24 m and 8 storeys, soil depth > 0.3 m, width > 4 m and greening area > 80 sqm) and the maximum conversion ratio could reach 10% of the auxiliary green area: Hebei

A coefficient of 20%

Shanxi

A coefficient of 20%

Municipal garden-style units (continued)

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Table 3 (continued) Provinces

Urban greening (with a specific conversion coefficient)

Jiangsu

A coefficient of 15% and the ratio could reach 10% of the auxiliary green area (soil depth 0.3–0.6 m, area > 200 sqm and well-maintained) A coefficient of 30% and could reach 15% of the of the auxiliary green area (soil depth 0.6 m, with a garden function)

Zhejiang

The coefficient depending on soil depth d (m) and the ratio could reach 20% of the auxiliary green area: 10%: 0.1 ≤ d < 0.3; 30%: 0.3 ≤ d < 0.5; 50%: 0.5 ≤ d < 1.0; 80%: 1.0 ≤ d < 1.5; 100%: d > 1.5

Shandong

Converted according to relevant regulations (vague)

Hainan

The coefficient depending on soil depth d (m) and the ratio could reach 15% of the auxiliary green area: 50%: 0.6 ≤ d < 1.0; 100%: d > 1.0

Guangxi

The coefficient depending on soil depth d (m) and the ratio could reach 15% of the auxiliary green area: 20%: 0.3 ≤ d < 0.6; 30%: 0.6 ≤ d < 1.5; 50%: d > 1.5

Fiscal subsidies

Award

Set out special funds (vague)

− Municipal garden-style units − One and two-star green buildings

adopt to promote green roof adoption. Overall, the ways such ten provinces adopt generally include converting into the green area, fiscal subsidies, and awards. Beijing and Shandong set all three aspects of incentive methods, while the regulation in Shandong is currently going, resulting in a vague incentive landscape. All these ten provinces have prioritised the methods of converting roof greening into urban greening according to a specific coefficient, with a maximum conversion ratio.

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Beijing makes it the most inspiring as the roof greening could be 50% of the auxiliary green area. For other provinces, the conversion ratios are about 10–20% of the auxiliary green area. It is uncertain that if Hebei and Shanxi have set the maximum conversion ratio, and Shandong makes it vague by specifying ‘roof greening can be converted according to relevant regulations, given the condition that Shandong has not released further regulations. Nevertheless, soil depth is a common indicator determining the value of the conversion coefficient. For instance, when the soil depth ranges between 0.6 and 0.8 m, the coefficient in Beijing is a fixed value of 20%. However, the conversion coefficient varies significantly across different provinces. A soil depth of 0.3–0.6 m results in a coefficient of 15%, and a soil depth of >0.6 m results in a coefficient of 30% in Jiangsu Province. The coefficient could reach 100% when the soil depth reaches 1.5 m in Zhejiang Province. In Guangxi, when the soil depth reaches 1.5 m, the coefficient reaches its maxima of 50%. Shanghai presents a different method for deciding conversion coefficient by the height difference between building base and roof height. When the height difference is less than 1.5 m, the coefficient could be 100%; namely, roof greening can be totally considered as urban greening. However, when the height difference reaches 12 m, the coefficient is zero, meaning roof greening is not a part of urban greening. In addition, Chongqing has a comprehensive requirement for urban greening conversion of 20% by considering soil depth, greening width and area, and maintenance conditions. These could be sound to ensure that roof greening is well constructed and avoid the roof greening washed buildings for higher urban greening areas. Chongqing provides fiscal subsidies with 50 RMB/sqm. Shanghai provides subsidies depending on the roof styles, where the subsidies for garden roofs could be 200 RMB/sqm. Beijing has also set up direct payment according to roof greening style, with 100–150 RMB per square meter of garden-style roofing and 50–100 RMB per square meter of simple-style roofing over public buildings. In addition, Beijing has also offered payment for green roof maintenance. In addition, the flood control fee could be reduced and even waived in Beijing according to the roof greening area because the auxiliary green area could already meet the urban planning requirements. Shandong makes a commitment to set out special funds, but it is still vague at present. Beijing suggests that roof greening is an important indicator for selecting the Municipal garden-style unit and greening and beautifying advanced units and individuals. This is currently a method to provide awards (with bonus) as compensation. Hebei and Shandong also adopt such ways, the properties in selecting Municipal garden-style units, to promote green roof adoption. In addition, Shandong lists the green roof as an item for one- and two-star green building labelling. In addition, Beijing suggests that every square meter of green roofing can be equivalent to the duty of planting three trees.

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5 Framing Green Roof Adoption by City-Scale Policies and Regulations While cities generally follow the provincial policies and regulations for green roof promotion, some cities could release the specific policies and regulations, especially given the condition that some provinces have not well-developed policies and regulations. Therefore, this section further analyses the policies and regulations released for green roof promotion at the city scale, as shown in Table 4. In Table 4, only the representative cities such as the capital cities and economically advantaged cities (e.g., Shenzhen, Xiamen). Accordingly, the policy landscape of the green roof of 15 cities has been summarised in Table 4 for subsequent analysis. Akin to the provincial incentives for green roof adoption, city-scale policies and regulations are mainly urban greening, fiscal subsidies, and awards. The awards are limited to the ‘recognition and title’ from the government, such as Excellent Roof Garden, Excellent Vertical Greening, Most Beautiful Balcony Garden, Most Beautiful Gardening Home in Hefei, Anhui Province, the Governmental Recognition and Title in Shijiazhuang, Hebei Province, and Outstanding Individuals and Units in Zhengzhou, Henan Province. In addition, there are some other incentives such as ‘two sqm of roof greening equivalent to one tree’ in Guangzhou, Guangdong Province, and ‘one sqm of roof greening equivalent to two trees’ in Hangzhou, Zhejiang Province. The conversion of green roofing area into the urban greening area is a common incentive, suggested by 12 cities among the 15 cities. In comparison, only five cities, including Nanjing, Hangzhou, Zhengzhou, Shenzhen, and Xi’an, have set up direct payments for green roof areas. In contrast, the provinces such cities are affiliated to have not set up fiscal subsidies. More inspiringly, the fiscal subsidies released by such cities are much higher than the provincial ones. For instance, the payment for the garden-style roof could reach 300 RMB/sqm in Hangzhou, Zhengzhou, and Shenzhen, and the one in Xi’an is 285 RMB/sqm (Table 4), higher than the 200 RMB/sqm in Beijing (Table 3). Hangzhou and Zhengzhou specify a green roof maintenance or management fee of 6 RMB/sqm and 10 RMB/sqm, respectively, indicating a more active effort to promote green roof development. In addition, Nanjing does not suggest a specific payment per square meter of roof greening, but it reports a maximum value of 300,000 RMB for a roof greening project. Such phenomena indicate the bottom-up pattern from cities to provinces in promoting green roof development and implementation. The conversion of roof greening area into the urban greening area in such 12 cities is mainly dependent on the criteria of soil depth (Jinan, Wuhan, Changsha, Shenzhen, Haikou, Chengdu, Kunming, Yinchuan), building base-roof height difference (Hefei, Xiamen, Changsha), roof greening area (Chengdu) and building height (Nanchang, Jinan). Moreover, several provinces have used more than one indicator to specify green roof construction. For instance, Xiamen, a city that successfully adopts green roofs, has a set of requirements for green roof construction and then incentives. The conversion coefficient is at least 20% for such cities, except for the case in Jinan. The conversion coefficient is only 10% when the construction projects are higher

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Table 4 Incentives for green roof adoption in different cities City

Urban greening (with a specific conversion coefficient)

Nanjing (Jiangsu)

Fiscal subsidies Roof greening of office buildings (>1000 sqm) and residential buildings (>300 sqm) can be financially supported with a maximum of 3000,000 RMB

Hangzhou (Zhejiang)

Same with provincial policy landscape

Hefei (Hefei)

The coefficient depending on building base-roof height difference (H, m) and each roof greening area should be at least 100 sqm: 30%: 1.5 < H ≤ 24; 100%: H ≤ 1.5

Xiamen (Fujian)

The coefficient depending on building base-roof height difference (H, m) 40%: H > 15.0; 50%: 5 < H ≤ 15; 80%: 1.5 < H ≤ 1.5; 80%: H ≤ 1.5 Based on the following requirements: (i) The first ground is fully greened; (ii) Soil depth no less than 0.2 m; (iii) Water and drainage facilities are well-constructed for green roof maintenance; (iv) Hard surface of each roof should be less than 40%; (v) Shrubs and small trees should be planted with at least 0.3 plant/sqm

Nanchang (Jiangxi)

The coefficient depending on building height (storeys) and the soil depth should be at least 0.3 m: 30%: 1–3 storeys; 20%: 4–6 storeys; 10%: higher than 6 storeys but lower than 40 m; Well-maintained roof green greening could have a coefficient of 50–60%; High-quality garden-style roof could have a conversion coefficient of 80%

Garden-style roof: 300 RMB/sqm; Combined-style roof: 200 RMB/sqm; Simple-style roof: 100 RMB/sqm; Maintenance fee is 6 RMB/sqm when roof greening area is larger than 100sqm

(continued)

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Table 4 (continued) City

Urban greening (with a specific conversion coefficient)

Jinan (Shandong)

The coefficient depending on soil depth d (m): 30%: 0.5 ≤ d < 1.0; 40%: 1.0 ≤ d < 1.5; 50%: d > 1.5 The ratio could reach 20% (construction projects lower than 12 m) of the auxiliary green area and 10% (construction projects higher than 12 m) of the auxiliary green area

Zhengzhou (Henan)

Fiscal subsidies

300 RMB/sqm for all green roofs. 10 RMB/sqm for green roof management

Wuhan (Hubei)

A coefficient of 20% and the ratio could reach 20% of the auxiliary green area (soil depth 0.4 m)

Changsha (Hunan)

The coefficient depending on base-roof height difference H (m) and soil depth d (m) for accessible roof greening (>100 sqm): 80%: 0.3 < H ≤ 3.0, d ≥ 1.2; 50%: 3.0 < H ≤ 6.0, d ≥ 0.9; 20%: 6.0 < H ≤ 12.0, d ≥ 0.6;10%: H > 12.0, d ≥ 0.6

Shenzhen (Guangdong)

The coefficient depending on soil Garden-style roof: 300 RMB/sqm depth d (m) and the conversion Least payment: 180 RMB/sqm ratio could reach 50% for commercial and service building and 20% for other buildings: 10%: 0.1 ≤ d < 0.3; 30%: 0.3 ≤ d < 0.5; 50%: 0.5 ≤ d < 1.0; 60%: 1.0 ≤ d < 1.5; 80%: 1.5 ≤ d < 3.0; 90%: d > 3.0

Haikou (Hainan)

A coefficient of 50% and the ratio could reach 15% of the construction area (soil depth ≥ 0.6 m) (continued)

than 12 m, indicating the more robust support for roof greening implementation. Nevertheless, many cities have not specified the maximum conversion ratio, which should be further clarified if they follow the provincial requirements. Overall, the city-scale requirement of roof greening area is sounder, more inspiring, and more comprehensive than provincial incentives of green roof promotion.

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Table 4 (continued) City

Urban greening (with a specific conversion coefficient)

Chengdu (Sichuan)

Underground or semi-underground building and the outdoor ground elevation is the same as the elevation of the adjacent city road: 100% when d ≥ 0.6 m; 20%, when d < 0.6 m Other non-residential buildings with a building height less than 40 m: 20% of roof area if d ≥ 0.4 m, roof green area ≥ 60%; 20% of roof greening area if roof greening area less than 60%

Kunming (Yunnan)

A coefficient of 20% (soil depth ≥ 0.6 m, building height less than 24 m)

Xi’an (Shaanxi)

Yinchuan (Ningxia)

Fiscal subsidies

Garden-style roof: 285 RMB/sqm; Combined-style roof: 220 RMB/sqm; Simple-style roof: 180 RMB/sqm Roof greening can be included in the urban greening area when the green roofing area is accessible, lower than 1 m, and soil depth larger than 1.2 m

6 Summary and Conclusions This chapter analyses the policy and regulatory landscape of green roof implementation in mainland China, according to the five ways of sustainability implementation in the New Urban Agenda: national urban policies, urban legislation and regulations, urban planning and design, local economy and municipal finance, and local implementation (United Nations 2016). Accordingly, the green roof is increasingly a critical approach in the urban planning and design by energy efficiency improvement, urban heat island mitigation, roof longevity extension, air purification, water runoff control, water purification, urban infrastructure improvement, noise reduction, biodiversity improvement, recreation, and aesthetics, property value increase, and employment improvement. The other four pillars frame the policy and regulatory landscape of green roof implementation. This chapter analyses the policy and regulatory landscape of green roof implementation at the national, provincial, and city scales. The results indicate that the policy and regulatory landscape is far from mature to promote green roof implementation. On the national scale, there are no specific documents for roof greening, and roof greening has only been mentioned in the guide, notice, opinion, legislation,

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technical specification and standards of environmental protection, green space, urban landscape, sponge city, and green building. Moreover, the green roof benefits have not been well clarified in existing national documents, where urban greening is a mere benefit, and the associated benefits have been mostly neglected. In addition, there is a lack of financial support from the central government, which may make the whole circumstance uncertain (He et al. 2018). Compared with the national policy and regulatory landscape, the provincial one is much sounder, indicating a clear bottom-up green roof development pattern in mainland China. In particular, there are specific documents for green roofing development in aspects of technical guide/specification, legislated regulations, governmental opinion, provincial plan, and economic support. The provincial governments are actively formulating green roof guides and technical specifications in order to instruct the green roof design, construction, maintenance, measurement, and species selection. Legislated regulations generally follow the Urban Greening Ordinance in many provinces, showing a top-down green roof development pattern. More inspiringly, the governmental opinions of several provinces have directly expressed the intention of developing vertical greening and roof greening. Provincial plans and economic support have also been proposed while they are not used directly for roof greening. In addition, 25 provinces have issued relevant documents for green roof implementation. However, an analysis of the geographic distribution of provincial policies and regulations indicates an uneven distribution pattern, mainly in the east part of mainland China. Moreover, only 10 of the 25 provinces have well-defined green roof types based on planting structures, even though the definitions are primarily different across various provinces. Ten provinces have released incentives for green roof implementation in aspects of urban greening conversion, fiscal subsidies, awards, and others. Among these aspects, the urban greening conversions are the most common way, followed by the fiscal subsidies and awards. In particular, the conversion coefficient generally ranges between 10–20%, except for the case in Beijing that a coefficient of 50% is suggested. In addition, Beijing and Shandong have adopted the most comprehensive methods, but the case in Shandong is awaiting next-step progress to implement such incentives. Nevertheless, there is a need to release more incentives to promote green roof implementation, such as land planning, floor area ratio, taxation, credit, enterprise qualification, scientific research, consumption guidance, approval, and city supporting fees. The case of city-scale policy and regulatory landscape, in aspects of incentives, is similar to the case of province-scale one, with urban greening conversion, fiscal subsidies, awards, and others. Nevertheless, the city-level incentives are more inspiring, sounder, and more comprehensive than province-level incentives. For instance, the prerequisites of offering green roofing incentives are more comprehensive with more than one criterion. Moreover, the fiscal subsidies released by such cities are much higher than the provincial ones, with a payment for the garden-style roof of 300 RMB/sqm in Hangzhou, Zhengzhou, and Shenzhen. The city-scale policy and regulatory landscape of green roof implementation indicate a clear bottom-up development pattern in mainland China. However, there is a need to develop the incentivizing

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system of green roofs further. Overall, this chapter reveals the policy and regulatory landscapes for green roof implementation in mainland China, which provides a reference to the next-step reform of the current policy system. Acknowledgements This work is financially supported by the startup fund from Chongqing University (NO.: 02170011044116).

References Alexandri E, Jones P (2008) Temperature decreases in an urban canyon due to green walls and green roofs in diverse climates. Build Environ 43:480–493. https://doi.org/10.1016/j.buildenv. 2006.10.055 Connelly M, Hodgson M (2008) Sound transmission loss of extensive green roofs-Field test results. Can Acoust 36:74–75 Feng H, Hewage KN (2018) Chapter 4.5—Economic Benefits and Costs of Green Roofs. In: PéREZ G, PERINI K (eds) Nature Based Strategies for Urban and Building Sustainability. ButterworthHeinemann He B-J (2019) Towards the next generation of green building for urban heat island mitigation: zero UHI impact building. Sustain Cities Soc 50:101647. https://doi.org/10.1016/j.scs.2019.101647 He B-J, Zhao D-X, Zhu J, Darko A, Gou Z-H (2018) Promoting and implementing urban sustainability in China: an integration of sustainable initiatives at different urban scales. Habitat Int 82:83–93. https://doi.org/10.1016/j.habitatint.2018.10.001 Mesimäki M, Hauru K, Lehvävirta S (2019) Do small green roofs have the possibility to offer recreational and experiential benefits in a dense urban area? A case study in Helsinki, Finland. Urban Forest Urban Green 40:114–124. https://doi.org/10.1016/j.ufug.2018.10.005 Morakinyo TE, Dahanayake KWDKC, Ng E, Chow CL (2017) Temperature and cooling demand reduction by green-roof types in different climates and urban densities: a co-simulation parametric study. Energy Build 145:226–237. https://doi.org/10.1016/j.enbuild.2017.03.066 Savarani S (2019) A review of green roof laws & policies: domestic and international examples. NYU. https://guarinicenter.org/wp-content/uploads/2019/03/A-Review-ofGreen-Roof-Laws-Policies.pdf UN-DESA 2018 (2018) Revision of world urbanization prospects. Department of Economic and Social Affairs, United Nations, 16, 2018. https://www.un.org/development/desa/en/news/popula tion/2018-revision-of-world-urbanization-prospects.html UN (2015) Goal 11: make cities and human settlements inclusive, safe, resilient and sustainable. Department of Economic and Social Affairs, Sustainable Development, United Nations. https:// sdgs.un.org/goals/goal11 United Nations (2016). New Urban Agenda. United Nations Conference on Housing and Sustainable Urban Development (Habitat III), 16. https://unhabitat.org/sites/default/files/2019/05/nuaenglish.pdf Wong NH, Tay SF, Wong R, Ong CL, Sia A (2003) Life cycle cost analysis of rooftop gardens in Singapore. Build Environ 38:499–509. https://doi.org/10.1016/S0360-1323(02)00131-2 Yang J, Yu Q, Gong P (2008) Quantifying air pollution removal by green roofs in Chicago. Atmos Environ 42:7266–7273. https://doi.org/10.1016/j.atmosenv.2008.07.003 Zhang G, He B-J (2021) Towards green roof implementation: drivers, motivations, barriers and recommendations. Urban Forest Urban Green 58:126992. https://doi.org/10.1016/j.ufug.2021. 126992

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Zhang G, He B-J, Dewancker BJ (2020) The maintenance of prefabricated green roofs for preserving cooling performance: a field measurement in the subtropical city of Hangzhou, China. Sustain Cities Soc 61:102314. https://doi.org/10.1016/j.scs.2020.102314 Zhang G, He B-J, Zhu Z, Dewancker BJ (2019) Impact of morphological characteristics of green roofs on pedestrian cooling in subtropical climates.Int J Environ Res Public Health, 16.https:// doi.org/10.3390/ijerph16020179

The Transformation of the Green Infrastructure Intervention Under the Case of Sponge City Program: Positions, Challenges, and Prospects in China Faith Ka Shun Chan, Lei Li, Ali Cheshmehzangi, Dimple R. Thadani, and Christopher D. Ives Abstract “Sponge City Program” (SCP), initiated in 2013, is the term in the Chinese interpretation of tackling urban stormwater and surface water management. The concept acts like a “Sponge” to absorb urban runoff and conduct the purification and storage via the restored natural hydrological processes via vegetation, soil, and water interactions. There were frequent and severe urban flood impacts and damages that affect the country during the recent decades after the “Open Door Policy” revealed and rapid urbanisation and developments occurred which see the country. Urban transformation occurs that witnesses their success, but urban surface water floods similarly occurred due to the interruption of the urban hydrological cycle. The current land drainage system cannot cope with climatic extremes. The SCP is similar to Green Infrastructure (GI) that has been commonly adopted in the UK and elsewhere by the practices such as sustainable urban drainage systems (SUDS) and Low-impact development (LID). The Central National Government (CNG) is ambitious and committed to achieving the major target for reducing urban flood risk. Indeed, there were selected F. K. S. Chan (B) · L. Li Faculty of Science and Engineering, School of Geographical Sciences, University of Nottingham Ningbo China, Ningbo 315100, China e-mail: [email protected] F. K. S. Chan Water@Leeds Research Institute, University of Leeds, Leeds LS29JT, UK School of Geography, University of Leeds, Leeds LS29JT, UK A. Cheshmehzangi Faculty of Science and Engineering, Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo 315100, China Network for Education and Research On Peace and Sustainability (NERPS), Hiroshima University, Hiroshima, Japan D. R. Thadani Nottingham University Business School China (NUBS), University of Nottingham Ningbo China, Ningbo 315100, China C. D. Ives School of Geography, University of Nottingham, University Park, Nottingham NG72RD, UK © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_5

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30 pilot “Sponge Cities” have been adopted the GI measures for the last few years at the first and second stage of SCP. This chapter shares and discusses recent progress, transformation, interpretation, and future development of SCP. In particular, we would like to adopt Ningbo, East China, one of the SCP major pilot cities that is an affluent and rapidly expanding coastal city, as the case for implying the positions, challenges, and prospects of SCP. Lastly, the chapter offers recommendations and foresight that the SCP and GI development further in the third stage (up to 2030s) and beyond, to mitigate future urban water issues in Chinese cities. Keywords Sponge City Program (SCP) · Green Infrastructure · Sustainable stormwater management · Sustainable development

1 Introduction 1.1 Chinese Urban Floods and Implications Cities are facing tough challenges and are exposed to extreme climatic conditions. Thus, we see more chances of frequent and significant climatic extremes, such as urban floods, droughts, and heatwaves (Hamin et al. 2019). Urbanisation and rapid developments in cities brought more risks and threats to the current urban ecosystem due to land-use changes. Such an approach has gradually diminished natural ecosystem functions that interconnect with a large reduction of green and blue-green spaces and soil sealing by infrastructure (roads, buildings, etc.) (Sandström et al. 2006). Evidently, more than 26% of green spaces were lost in the Pearl River Delta (PRD), South China, from the late 1970s when the “Open Door” policy was adopted by rapid urbanisation among these cities. The urbanisation rate in Shenzhen and Guangzhou as examples reached over 70% to 90% in the latest decades (Yeung 2011). Nevertheless, the success of urban transformation in Chinese cities is witnessed and the status of Chinese coastal cities and core cities established to top world cities for trading, finance, port logistics, and technology (Tang et al. 2015; Yeung 2009; Zhang et al. 2012). Whilst, such rapid and intensive land-use changes and urban transformation enhance the shift of the hydrological cycle, as increasing impermeable artificial surfaces interrupt the natural habitat, biodiversity, and vegetation-soil–water interactions. For example, 30–40% of stormwater (rainwater) originally goes to vegetation (e.g., trees, grassland, and crops), and another 20–30% of stormwater goes to soil (and vertical via through-flow goes to the groundwater level) in the natural hydrological process (Gao et al. 2016). However, because of urbanisation, almost 80–90% of urban stormwater now goes to urban runoff and highly relies on land drainage to offload the peak discharge (Griffiths et al. 2017; Todd et al. 2009). In this case, most Chinese cities rely on hard-engineering control measures on urban flood protection (e.g., ditches, canals, urban drainage systems, and pumping stations) to alleviate the urban peak discharge during the rainstorms (Cheng 2005). However, the land drainage and urban flood

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protection standard remains inadequate, only reaching at 1-in-1 year to 1-in-5 year return period at 1st Tier (major) cities, such as Shenzhen, Guangzhou, Shanghai, and Beijing (Chan et al. 2013; Griffiths et al. 2017; Yang et al. 2020; Yin et al. 2021). As a result, among the current (almost all) 654 Chinese cities, there are 641 cities currently exposed to frequent urban floods. There were 150 cities inundated by severe urban floods that caused the direct flood damages at about 160 billion RMB in 2015 (Xia et al. 2017). That said, the drivers by climate change and human-induced urbanisation have escalated urban flood risk via surface water floods and pluvial floods (i.e., urban surface floods that also connect with the fluvial and coastal floods, such as drainage backlashes by riverine freshwater or coastal water or both if cities are located on coastal area) (Griffiths et al. 2019; Meng et al. 2019). More examples miserably occurred, such as the Beijing flood in 2012 that caused 79 causalities, Ningbo 2013, Guangzhou 2014, 2015, 2018, Shenzhen 2013, 2014, 2015, 2018; and Wuhan 2016 and 2020 (Chan et al. 2021; Griffiths et al. 2020a; Tang et al. 2015; Yang et al. 2020). That said, current urban areas are lacking sufficient hydrological retention capacity to allow peak discharge offload through the hydrological cycle (allowing rainwater to absorb by sufficient vegetation, going through the soil–water infiltration processes, and retention of stormwater during rainstorms/downpours) back to rivers, lakes, and coastal estuarine areas or shorelines, and surface water floods and waterlogging frequently occurred especially during the wet season (from May to September) annually (Wang 2019). Additionally, urban developments and expansions will continue pushing forward Chinese cities. Such pressure implies these cities have not conserved their indigenous/originated natural water infrastructures (e.g., lakes, ponds, wetlands, canals, peri-urban forest, grassland) (Xia and PahlWostl 2012; Zhao et al. 2014), eventually resulting in a large reduction on these water storage capacities. If policies and practices remain unchanged, the projected urbanisation will continue rising in Chinese cities (among all tiers/levels) in the future, and the increasing flood risks are expected because of climate change and cumulative consequences.

1.2 Aim and Objectives This chapter reviews the current surface water management strategies in Chinese cities and illustrates the development of green infrastructure (GI) in the global and Chinese context. The chapter critically reviews the development of surface water management via the Sponge City concept associated with the Central National Government (CNG) guidelines. In this chapter, we review current national policy and guidelines and provide examples of municipal implementation by municipality authorities to demonstrate the progress of GI development in the Chinese context. Current and upcoming challenges will be discussed in this chapter.

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2 Green Infrastructure and Implications In the early 2000s, Fleming (2002) emphasised that civil engineers should be transformed and more focused on social-economic and ecological perspectives on urban water and flood management. There were strong trends on urban river restoration in the UK and other European countries that have been undertaken. Examples include “Making Space for Water” (UK) (Defra 2007) and “Room for Rivers” (the Netherlands) (Hudson et al. 2008). Such projects helped push ecological solutions of urban stormwater management that merge with the Catchment Management Plan in the UK (Wheater 2006) and Water Framework Directive in the EU (Carter and Howe 2006). Indeed, there are several incentives that we can see the transformation of ecological approaches on urban water management instead of only focusing on traditional or engineering approaches compared to several decades before. These are a good sign for the urban transformation delivering urban sustainability after Brundtland’s motto on sustainability in 1987 (Hjorth and Bagheri 2006). Urbanism and urban development trends focus more on building upon nature and social capitals, which aligns with stakeholders (urban planners, water engineers, civil engineers), experts, and scholars (practitioners). Green infrastructure (GI) is the strategy to mitigate problems caused by rapid urbanisation (Everett and Lamond 2019) that is popular in the UK and USA, examples of GI for the greenbelts in the UK and urban open-space networks in the USA (CohenShacham et al. 2016). GI provides multi-benefits, which include revitalising soil and vegetation, restoring hydro-ecological processes destroyed by urban developments and urbanisation, and naturally managing urban stormwater. GI is a strategically planned network of natural and semi-natural areas designed with green spaces (or blue-green aquatic ecosystems are concerned) and other environmental features (e.g., green roof, rainwater garden, bio-swale to deliver better urban ecosystem services. Whilst, GI also provides multiple benefits underpin urban sustainability, including promoting a healthy living environment and social well-being, supporting a green economy, improving biodiversity and ecological resilience, and enhancing ecosystems’ ability. The main purpose is still to deliver more sustainable stormwater management practices to deliver services such as flood protection, water purification, air quality improvement, and climate change mitigation and adaptation (O Donnell et al. 2021). GI is used at both an urban and a landscape scale compared to only a landscape scale of natural infrastructure. At the same time, the research applications of GI tend to associate with the urban context and improve sustainable water management. GI is useful to deliver multiple benefits that are similar to Nature-Based Solutions (EU), Low-Impact Developments (USA), Water Sensitive Urban Design (Australia), Sustainable Urban Drainage Systems (UK) or Low Impact Developments Urban Design (New Zealand), and other global practices (UN-WATER 2018). Liu and Jensen (2018) argued that GI is transforming the global sustainable water management practices of five forerunner cities (city-state Singapore, Berlin in Germany, Melbourne, Australia, Philadelphia in the US, and Tianjin Eco-city in China). They demonstrated the potential of GI in these cities are successfully delivered their role

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of enhancing more ecological-focused urban stormwater management practices and planning strategies in the future.

2.1 Green Infrastructure Opportunities and Progress in China—Sponge City Program (SCP) SCP progress and development Interestingly, the term “Sponge City” was not innovated and originated in China, but was found by scholars in Australia. They developed the “Sponge City” concept to metabolise the urban migration trend and movement from smaller towns towards cities (Argent, Rolley and Walmsley 2008), not related to water issues, but about population trends and demographic changes. Other researchers used the term “Sponge City” to describe the potential of rainwater runoff from Hyderabad city in India to evaluate the city’s potential impacts of water demand coping with the agricultural water supply (Van Rooijen et al. 2005). The Sponge City concept was proposed in China in 2013 and was officially launched by President Xi. The concept means that “Sponge” practice is similar to GI principles. The detailed plan included an overarching idea that cities absorb excess water from excessive precipitation, enhance the soil–water infiltration function through the soil layers, then conduct the purification and maximise infiltration (through the throughflow and intersection flows inside soil). The concept enables the reuse of absorbed water (via storage outlets) of groundwater, ponds, lakes, wetland, urban runoff, etc. It also recycles the urban water resources during wet and dry seasons (Xia et al. 2017). The CNG promotes SCP to encourage municipal authorities to build more urban flood resilient measures such as Sponge measures and mimic the natural hydrological cycle in the urban environment rather than relying on traditional drainage systems. That aims to increase current drainage protection standards by the application of SCP. According to the Sponge Construction Guideline, the required Sponge facilities can reach up to 1-in-30 years return period to protect the urban areas exposed to rainstorms. This flood protection standard (at 1-in30 years return period) aligns with other major Asian cities such as Tokyo, Singapore, and Hong Kong Special Administrative Region (HKSAR) (Chan et al. 2021). The SCP practices and approaches are similar to GI by encouraging the adoption of the Nature-Based Solutions (NBS) and Low-Impact Development (LID) practices that offset peak discharges and reduce excess stormwater (O Donnell et al. 2021). The SCP concept encourages multi-functions delivery that addresses urban stormwater management and promotes urban ecosystem services by increasing artificial water bodies and blue-green spaces, and water bodies. It offers better amenity value, recreational functions, improving air quality, reducing carbon emissions, carbon neutralisation, and reducing urban heat island effects for the communities in China (Wang et al. 2018).

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The CNG established the SCP at the end of 2014 and launched the “Construction guidance of Sponge City Program” by the Ministry of Housing and Rural– Urban Development (MoHURD) and affiliated with the Ministry of Finance and the Ministry of Water Resources. Chan et al. (2018) argued that the SCP could implement urban flood management and stormwater management into the urban planning practices and designs. The SCP indeed requires to restore and transform urban spaces into “Green” or “Blue-Green” infrastructures (e.g., swales, parks, ponds, wetlands, forests, gardens, grasslands). That also includes retrofitting and refurbishing communities and neighbourhoods, such as revitalisation and urban green renewal or river restoration projects with the Sponge measures. Undertaking these practices involves multi-governmental sectors (e.g., Ministry of Housing and Urban–Rural Development (MoHURD), Ministry of Planning, Ministry of Water Resources, Ministry of Environment, Ministry of Forestry, Ministry of Finance). Such departments collaborate and align with interventions required to transform the SCP guidance needed to transform the urban areas (Tang et al. 2018; Wu et al. 2020). According to the SCP guidance, the CNG first established the introduction and pilot program of SCP construction and development concepts. It then enhanced the demonstrated Sponge construction sites for stakeholders and the public to be familiar with the program by using small-scale urban pilot projects (or site-specific size such as parks) at the first stage of SCP (from 2015 to 2018). At the second stage (2018– 2020), the CNG established the SCP standards on stormwater management and freshwater management criteria and assessment (that also published the supplementary SCP assessment guidance on urban stormwater management in 2018). It aimed to achieve 20% of the urban areas (municipal districts/zones) of selected Sponge Cities should absorb, retain and reuse about 70% of the stormwater by 2020s. It then raised the bar up to 80%, where municipal areas should be able to recycle 70% of incident rainfall by 2030s at the third stage (2020s–2030 onwards) (Griffiths et al. 2020b; Qi et al. 2021). The MoHURD is responsible for implementing SCP and construction projects (Zevenbergen et al. 2018) that have estimated the required financial investments of about 100–150 million RMB per square kilometer. SCP pilot cities The CNG identified 16 out of 30 candidate Sponge City pilot cities that are under the selection criteria. Each city has to have a strong case for urban drainage infrastructure renewal, plus the potential to achieve the targets within the projected life of the initiative (see Fig. 1). Table 1 illustrates that the first batch of SCP pilot cities consisted of one municipality, three sub-provincial cities, and 12 prefecture-level cities. The distribution of cities across various rainfall and climatic zones have different topographic and demographic conditions (e.g., mountainous, valley, coastal, lowland, dryland, temperate forest, grassland, and tropical forest). The CNG and MoHURD aimed to make the sponge measures to improve the stormwater intakes from urban runoff. The first batch of pilot cities consisted of various sizes of Chinese cities,

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Fig. 1 Geographical distribution in Mainland China (excluding Taiwan, Macao SAR, and Hong Kong SAR) with the indication of 30 SCP pilot cities that cities number—Geographic location of the first (dark circles) and second (light circles) batch of Sponge City pilot cities (Source James Griffiths and Faith Chan)

including the municipality (i.e., Chongqing), three sub-provincial cities (e.g., Jinan, Wuhan, and Xiamen), and prefecture cities (e.g., Baicheng Zhenjiang, Jiaxing, etc.). In this regard, the CNG targeted to evaluate the hydrological patterns and the performance of “Sponge” facilities and measures for the proposed guidelines. The aim was to assess adequate progress through various size and meteorological patterns of these cities. Later on, the CNG has selected another 16 cities that similarly represent a diverse range of hydrological, meteorological, topographic, and demographic factors that supplement the first batch (see Table 2 and Fig. 1). Stakeholders of SCP: the duties and legislated guidance The SCP stakeholders are committed to the implementation of SCP, for example, ensuring the construction and progress are well pushed forward. Their duties and responsibilities are explicit and varied of urban planning, design, and road construction and highway agency departments in the local (district) and municipal government and CNG level and coordinate Sponge City administrative and institutional functions

Chongqing

Jinan

Wuhan

Xiamen

Baicheng

1

2

3

4

5

City

Prefecture

Sub-provincial

Sub-provincial

Sub-provincial

Municipality

City level

Jilin

Fujian

Hubei

Shandong

–

Province

Mongolian steppe, Tao’er River floodplain

Coastal, humid sub-tropical

Yangtze River floodplain

Yellow River floodplain

Confluence on the Yangtze and Jialing Rivers

Environment

Drought and the only city to be selected for the sponge city program in the NE China

Water-logging Pluvial flooding (urban surface water floods) Coastal flooding

Water-logging Pluvial flooding (urban surface water floods)

Water-logging Pluvial flooding (urban surface water floods)

Waterlogging Pluvial flooding (urban surface water floods)

Hydrological issues

(continued)

Jilin Government (2018) Guidelines for planning and design of sponge city in Baicheng. (http://www.jl.gov.cn/hd/zxft/ szfzxft/zxft2018/20180224ft_123315/ ftzy/201811/t20181109_5228720.html)

Xiamen Government (2018) Guidelines for planning and design of sponge city in Xiamen. (http://www.xm.gov.cn/zwgk/ flfg/sfbwj/201808/t20180801_2081407. htm)

Wuhan Planning and design institute (2017) Guidelines for planning and design of sponge city in Wuhan. (http://www. wpdi.cn/academic-research-i_11398.htm)

Jinan Government (2015) Guidelines for planning and design of sponge city in Jinan. (http://www.jinan.gov.cn/art/2015/ 11/12/art_1862_230391.html)

Chongqing planning and design institute (2018) Guidelines for planning and design of sponge city in Chongqing. (http://www. cqghy.com.cn/index.php?s=/articles/174. html)

Citation/source (in Chinese)

Table 1 First batch of nominated pilot “Sponge Cities” and relevant sources (adopted after Qi et al. 2021; Qi et al. 2020; Griffiths et al. 2020; Chan et al. 2018)

104 F. K. S. Chan et al.

Zhenjiang

Jiaxing

Chizhou

Hebi

Pingxiang

Changde

6

7

8

9

10

11

City

Prefecture

Prefecture

Prefecture

Prefecture

Prefecture

Prefecture

City level

Table 1 (continued)

Hunan

Jiangxi

Henan

Anhui

Zhejiang

Jiangsu

Province

Yuan River floodplain

Mountainous floodplain

Qi river flood plain

The Southern bank of the Yangtze River

Drained land

The Southern bank of the Yangtze River

Environment

Hydrological issues

Pluvial flooding(urban surface water floods)

Pluvial flooding (urban surface water floods)

Pluvial flooding (urban surface water floods)

Pluvial flooding (urban surface water floods)

Water-logging (urban surface water floods)

Water-logging Pluvial flooding (urban surface water floods) Coastal flooding

Citation/source (in Chinese)

(continued)

Changde Government (2017) Guidelines for planning and design of sponge city in Changde. (http://zfjsw.changde.gov.cn/art/ 2017/3/13/art_5254_1034945.html)

Pingxiang Government (2018) Guidelines for planning and design of sponge city in Pingxiang. (http://xxgk.pingxiang.gov.cn/ fgwj_1/qtygwj/201805/t20180514_172 6051.htm)

Hebi Government (2017) Guidelines for planning and design of sponge city in Hebi. (https://fgw.hebi.gov.cn/zghb/436 364/436368/2029120/index.html)

Anhui Government (2017) Guidelines for planning and design of sponge city in Chizhou. (http://www.ah.gov.cn/Use rData/DocHtml/1/2017/6/13/697254727 4419.html)

Jiaxing Government (2018) Guidelines for planning and design of sponge city in Jiaxing. (http://www.njszgl.com/szgh/257. html)

Zhenjiang Government (2017) Guidelines for planning and design of sponge city in Zhenjiang. (http://jsj.zhenjiang.gov.cn/ xxgk/zcfg/dfxfg/201708/t20170816_187 9146.htm)

The Transformation of the Green Infrastructure Intervention … 105

Nanning

Suining

Qian’an

Gui’an

Xixian

12

13

14

15

16

City

New Area

New Area

Sub-prefecture

Prefecture

Prefecture

City level

Table 1 (continued)

Shannxi

Guizhou

Hebei

Sichuan

Guangxi

Province

Mountainous

Mountainous

Luan River Floodplain

Fu River Basin

Yong River floodplain

Environment

Pluvial flooding (urban surface water floods)

Pluvial flooding (urban surface water floods)

Drought

Pluvial flooding (urban surface water floods)

Pluvial flooding (urban surface water floods)

Hydrological issues

Citation/source (in Chinese)

Xixian Government (2016) Guidelines for planning and design of sponge city in Xixian (http://www.fcfx.gov.cn/xwzx/ mbjj/20706.htm)

Guian Government (2019) Guidelines for planning and design of sponge city in Gui’an (http://www.gaxq.gov.cn/zwgk/ xxgkml/zdlyxxgk/cxgh/201901/t20190 115_2214467.html)

Tangshan Government (2016) Guidelines for planning and design of sponge city in Qian’an (http://www.tangshan.gov.cn/zhu zhan/zwgkgcztbzbgg/20161130/368216. html)

Suining Government (2016) Guidelines for planning and design of sponge city in Suining (http://gk.suining.gov.cn/t.aspx? i=20170104163744-845752-00-000)

Nanning Government (2018) Guidelines for planning and design of sponge city in Nanning. (http://www.nanning.gov.cn/ xxgk/xxgkml/jcxxgk/zcwj/zfwj/t756426. html)

106 F. K. S. Chan et al.

Beijing

Tianjin

Shanghai

Dalian

Ningbo

Qingdao

Shenzhen

1

2

3

4

5

6

7

City

Municipality

Sub-provincial

Sub-provincial

Sub-provincial

Municipality

Municipality

Municipality

City level

–

Shandong

Zhejiang

Liaoning

–

–

–

Province

Coastal floodplain

Coastal city

Coastal floodplain

Coastal Peninsular

Costal megacity

Costal megacity

Capital megacity

Environment

Waterlogging Pluvial flooding (urban surface water floods) Coastal flooding

Waterlogging Pluvial flooding Coastal flooding

Waterlogging Pluvial flooding (urban surface water floods) Coastal flooding

Pluvial flooding (urban surface water floods) Coastal flooding

Waterlogging, pluvial flooding (urban surface water floods), Coastal flooding

Pluvial flooding (urban surface water floods) and coastal flooding

Pluvial flooding (urban surface water floods)

Hydrological issues

(continued)

Shenzhen Government (2018) Guidelines for planning and design of sponge city in Shenzhen. (http://www.sz. gov.cn/sswj/ztzl/bmzdgz/hmcsjs/zhyw/201808/P02018 0820364500062887.pdf)

Qingdao Government (2018) Guidelines for planning and design of sponge city in Qingdao. (http://www.qin gdao.gov.cn/n172/n24624151/n24626395/n24626409/ n24626423/180524152516531751.html)

Ningbo Government (2018) Guidelines for planning and design of sponge city in Ningbo. (http://zfxx.nin gbo.gov.cn/art/2018/7/12/art_2447_2350366.html)

Dalian Government (2018) Guidelines for planning and design of sponge city in Dalian. (http://www.dl. gov.cn/gov/detail/file.vm?diid=101D05000180910260 518093009&lid=3_4)

Shanghai Government (2018) Guidelines for planning and design of sponge city in Shanghai. (http://www. shanghai.gov.cn/nw2/nw2314/nw2319/nw12344/u26 aw56510.html)

Tianjin Government (2019) Guidelines for planning and design of sponge city in Gui’an. (http://zfcxjs.tj. gov.cn/

Beijing Government (2018) Guidelines for planning and design of sponge city in Beijing. (http://www. ccgp.gov.cn/cggg/dfgg/zbgg/201812/t20181206_112 84932.htm)

Citation/source (in Chinese)

Table 2 Second batch of nominated pilot “Sponge cities” (adopted after Qi et al. 2021; Qi et al. 2020; Griffiths et al. 2020; Chan et al. 2018)

The Transformation of the Green Infrastructure Intervention … 107

Fuzhou

Zhuhai

Sanya

Yuxi

Qingyang

Xining

Guyuan

8

9

10

11

12

13

14

City

Prefecture

Prefecture

Prefecture

Prefecture

Prefecture

Prefecture

Prefecture

City level

Table 2 (continued)

Ningxia

Qinghai

Gansu

Yunnan

Hainan

Guangdong

Fujian

Province

Mountainous

Mountain floodplain

mountain plateau

Mountainous floodplain

Coastal city

Coastal city

Coastal floodplain

Environment

Pluvial flooding (urban surface water floods)

Pluvial flooding (urban surface water floods)

Pluvial flooding (urban surface water floods)

Pluvial flooding (urban surface water floods)

Pluvial flooding (urban surface water floods) Coastal flooding

Pluvial flooding (urban surface water floods) Coastal flooding

Waterlogging Pluvial flooding Coastal flooding

Hydrological issues

Citation/source (in Chinese)

Guyuan Government (2018) Guidelines for planning and design of sponge city in Guyuan. (http://www. nxgy.gov.cn/zwgk/szfwj/201708/t20170808_384666. html)

Xining Government (2018) Guidelines for planning and design of sponge city in Xining. (http://www.xin ing.gov.cn/html/171/373685.html)

Gansu Government (2018) Guidelines for planning and design of sponge city in Qingyang. (http://www. gansu.gov.cn/art/2018/3/28/art_48_359212.html)

Yuxi Government (2018) Guidelines for planning and design of sponge city in Yuxi. (http://www.yuxi.gov. cn/zxdt/20170525/571123.html)

Hainan Government (2018) Guidelines for planning and design of sponge city in Sanya. (http://www.sanya. gov.cn/sanyasite/fgwj/201609/715518bb75694b46ad 12297dfdcb8fd2.shtml)

Zhuhai Government (2018) Guidelines for planning and design of sponge city in Zhuhai. (http://www. zhzgj.gov.cn/xxgk/tzgg/201801/t20180105_25444461. html)

Fuzhou Government (2018) Guidelines for planning and design of sponge city in Fuzhou. (http://fzjw.fuz hou.gov.cn/zz/zwgk/tzgg/201804/t20180428_218 9253.htm)

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between them. The MoHURD is responsible for designing and issuing guidelines and standards and assisting in the supervision of pilot projects. The MoHURD also establishes the “Sponge City Office” (SCO) that governs by them to liaise and coordinate all governmental ministries, departments, and bureaus accordingly in all 30 SCP pilot cities. The SCO organises meetings and workshops to cooperate with the Ministry of Finance, allocates and manages investments, and also liaises with the Ministry of Water Resources to deal with the urban hydrological and flood issues for monitoring and guidance in new projects. Lastly, the SCO also works with the National Development and Reform Commission, responsible for interpreting national-scale policy and delivery standards to the regional and local scale, which approves and evaluates all SCP delivery and progress. Tables 3 and 4 provide the detailed policies and standards related to the implementation of the SCP. The “Sponge City Construction Guidance” indicates that drainage of surface water runoff should be integrated with the “Code of Design of Outdoor Wastewater Engineering” (GB 50,014–2006). Other relevant urban drainage and waterlogging control and planning and design standards include the “Urban Drainage Facility Planning Code” (GB50318-2000); the “Outdoors Drainage Design Code” (GB50014-2016); and the “Urban Flood Control Facility Design Code” (CJJ50-92). These legislated guidance and protocols are helpful to improve current land drainage urban flood protection standards largely increase to 1-in-30-year (24 h) rainfall events. Previously, most Chinese cities account only for 1-in-1 to 1-in-5-year (24 h) events (Chan et al. 2018a). With the implementation of SCP, new towns and development areas (that selected in the SCP construction plan in these Sponge cities) will move closer to levels of flood protection in other Asian cities, such as Tokyo, Hong Kong, and Singapore (which designed for 1-in-50-year events) (Chan et al. 2021). In December 2018, the MoHURD published the “Assessment standards for Sponge City construction” (GB/T 51,345–2018), which all pilot cities were required to use by August 2019. The standards provide assessment guidelines for (1) Improving volume control of urban runoff; (2) Increasing stormwater source control and implementation effectiveness; (3) Promoting road surface flood control; (4) Improving urban water quality; (5) Ensuring ecological conservation and ecosystem services; (6) Improving groundwater depth and condition; and (7) Reducing urban heat island effect. These new standards allowed the MoHURD to address issues omitted from the earlier 2014 guidance. These included benchmarking the effectiveness of new infrastructure on stormwater control, suggestions for improving the ecosystem services and ecology conservation, describing groundwater effects, and reducing urban areas heat island effects.

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Table 3 National planning and policy relevant to the implementation of Sponge City guidelines (adopted after multiple sources, includingGriffiths et al. 2020; Chan et al. 2018; Xia et al. 2017) National policy

Aims

Source (in Chinese)

The Communist Party of China’s State Council policy on urban drainage storm water drainage facility construction notice (April 2013)

Transform water drainage and sewage control systems (by 2023) • Promote sustainable drainage construction methods • Permeable surfaces area ratio minimum of 40% in new developments • Convert impermeable surfaces to permeable surfaces, to store rainwater and reduce hydrograph peak

The State Council of the Peoples’ Republic of China (2013) The Communist Party of China’s State Council policy on urban drainage stormwater drainage facility construction notice. Notice No. 23 of the State Council. (http://www. gov.cn/zhengce/content/201304/01/content_5066.htm)

The Communist Party of China’s State Council policy on promoting the sponge city-building guidance and aims (October 2015)

Increase implementation of sponge city approach • Rehabilitate urban water ecology • Increase stormwater drainage capacity • Increase public investment in drainage projects • Reduce the impact of urban development on ecology • Infiltrate 70% of rainfall within the development areas • By 2020 reach at 20% of urban areas should achieve the above objectives; by 2030 reach at 80% of urban areas should achieve the above objectives

The State Council of the Peoples’ Republic of China (2015) The Communist Party of China’s State Council policy on promoting the sponge city-building guidance and Aims. Notice 75 of the State Council. (http://www. gov.cn/zhengce/content/201510/16/content_10228.htm)

The Communist Party of China’s State Council on further strengthening the urban planning and construction management (February 2016)

Draft sponge city construction guidance • Utilise natural landscape: topography, wetlands, farmlands, woodlands, Grasslands, and existing rivers and lakes • Develop synergistic eco-spaces to promote water conservation; recycling; improving flood and waterlogging resilience • Encourage households to install rainwater collection devices and reduce urban impermeable surfaces

The State Council of the Peoples’ Republic of China (2016) The Communist Party of China’s State Council on further strengthening the urban planning and construction management. 6th Feb 2016. (http://www.gov.cn/zhengce/ 2016-02/21/content_5044367. htm)

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Table 4 National standards for the prevention of waterlogging (adopted after multiple sources, including: Griffiths et al. 2020; Chan et al. 2018; Xia et al. 2017) National standards

Specification

Source/citation (in Chinese)

Outdoor drainage design code • Guidance on rainwater (GB50014-2006) harvesting, transportation, storage, discharge, processing and utilisation of natural and artificial facilities • Medium-sized cities and small urban waterlogging prevention schemes to design for return periods of 10–20 years • No more than 15 cm of runoff depth on road surfaces • Engineering and non-engineering measures • Used to prepare for and respond to urban waterlogging

Ministry of housing and urban rural development of the People’s Republic of China (2016). “Code for design of outdoor wastewater engineering (GB 50,014–2006)”, 2016 edition. China Planning Press, Beijing, China

Sponge city construction technology guide—Low impact development storm water systems construction

• Volume runoff objectives: The total annual runoff rate is limited to 15–20% Annual runoff control of 80%-85% of incident rainfall • Peak runoff objectives: City storm sewer and pumping stations to be designed with respect to outdoor drainage design code (GB50014-2016) • Stream pollution control targets: Classification system for runoff pollutant and to control the total amount of combined sewer overflow

Ministry of Housing and Urban–Rural Development (2014). The construction guideline of Sponge City in China. Ministry of Housing and Urban–Rural Development, China Planning Press, Beijing, China

The city flood control engineering design code (GBT50805-2012)

• Relates to flood control including storm surge, flood tide and related impacts • Flood control and engineering design standards • River flood engineering for 200-year events • Urban flood design for 20-year events

Ministry of housing and urban rural development of the People’s Republic of China (2012). “Code for design of urban flood control project (GB/T 50,805–2012)”, 2012 edition, China Planning Press, Beijing, China

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3 Discussion: Local Case of GI Movement: Ningbo, East Coast China Progress and implementation Ningbo locates on the East Coast of China. It is a coastal city and one of the major ports in China and worldwide (Tang et al. 2015). The city is included in the second batch of SCP. The city has been exposed to typhoons, enhanced-storm surges, and led coastal floods, but cyclonic weather usually bringing intensive rainstorms, as a result, also led to urban surface flooding. For example, the city was heavily flooded (and the waterlogging/surface water flood depth was reached 1–1.5 m) during the typhoon Fitow during 7–14 October 2013 (Fig. 2). Another town, Yuyao, has been inundated with more than 10,000 households affected (Griffiths et al. 2017). Ningbo was ranked at the top 10 global coastal port cities exposed to flood risk by the OECD (Nicholls et al. 2008). The municipal and local governments of Ningbo fully understand the importance of improving urban flood resilience and management practices and putting substantial efforts into tackling flood issues. Earlier in the 2010s, Ningbo became one of the champion cities in China that adopted the GI even before the SCP was established. The municipal government has been highly concerned and responded afterwards that aligns with the CNG joint the SCP and also promoted the “Five Water Management” strategy in 2013 to deal with major urban water issues, including coastal and surface water floods in Ningbo (Griffiths et al. 2020a; Tang et al. 2015). The authorities have improved the land

Fig. 2 Urban flooding event in Yinzhou district, Ningbo Municipal area on 7th October 2013 during the Typhoon Fitow (Source Photo taken by Faith Chan)

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Fig. 3 Cicheng Central Lake, an artificial wetland project in Cicheng New Town, Ningbo (Photo Source Taken by Lei Li and Faith Chan)

drainage systems with some implemented large artificial water storage measures. Such measures included artificial wetlands and pond systems connected with most rivers and channels in Cicheng New Town. This plan ensures the area reaches a 1-in-30 year return period for stormwater and urban runoff and provides adequate storage for the peak discharge, especially during the rainstorms and typhoon period (see Fig. 3). These practices have been gradually and successfully mitigated and reduced urban flood risk. The authority has also adopted various GI measures, such as bioswales on roadsides to absorb and purify the urban stormwater during rainstorms and road wash materials (e.g., suspended solids). Such an approach allows vegetation to absorb water and allows excess rainwater to be infiltrated and purified. It finally discharges the water via soil interception flow and through a flow to the artificial wetland and ponds for storage and preparation in the dry season (e.g., irrigation and recreation) (see Fig. 4) (Chan et al. 2020a). The potential benefits of the Cicheng example demonstrated the Ningbo municipal authorities committed to delivering SCP accordingly with increasing potential hydrological performance for more urban runoff discharge storage. It also increases infiltration capacity and maintains a good groundwater level, thus yield measurable results multiple benefits. Tables 3 and 4 above provide in-depth information about the implementation plan established by the CNG on SCP and the guidelines in 2014. They illustrate the detailed national standards and mechanisms to guarantee the professional standards and criteria on urban land drainage, urban hydrological cycle, water engineering, road

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Fig. 4 Bio-swale at the roadside of Cicheng New Town, Ningbo as the Sponge City measures (Source Lei Li and Faith Chan)

design coping with the SCP, and water quality relevant aspects. That illustrates the National, Municipal, and District level of good governance (in terms of high standard quality) on SCP delivery, especially on urban stormwater management that collaborated at multi-sectoral governmental institutions, as discussed previously. That is a breakthrough and transformation on urban planning practice that CNG usually and commonly operates as the hierarchy governance system with decentralisation mechanism. Thus, the SCP has initiated a breakthrough and transformation in China’s urban water management and planning practices, as argued by Griffiths et al. (2020b) and Chan et al. (2020a). Tables 5 and 6 further demonstrate Ningbo municipal authorities and their commitments to cope with the CNG and translate the National policy on SCP to implement in the city with the local concerns and adopted with the National Standards. For example, adoption of the stormwater drainage guideline from the National standard required by the CNG to the municipal areas in Ningbo (i.e., The Ningbo city center drainage and stormwater drainage planning guidelines (July 2017) implemented by the MoHURD of the People’s Republic of China). Ningbo local authorities try to achieve the expected standards by the CNG. These standards are set to improve the drainage standard, water environment, rainwater collection and reduce flood risk up to the mandatory standard (e.g., reduce downtown total annual runoff control rate by 75% for design rainfall event; in 80% of the urban area by 2030). They also follow legislation in the SCP guidelines and affiliated legal protocols.

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Table 5 Ningbo Municipal policy relevant to implantation of Sponge City (adopted after O’Donnell et al. 2021; Griffiths et al. 2020; Chan et al. 2020) Local Guidelines

Aims

Source/citation (in Chinese)

The Ningbo city centre • Improve existing stormwater drainage and stormwater drainage drainage planning guidelines • Establish water-storage (July 2017) that implemented • Promote low-impact by the Ministry of housing and development and urban rural development of construction including the People’s Republic of China buildings, community rainwater collection, and permeable areas • Support strengthening of flood risk assessments in new urban developments

Ministry of housing and urban rural development of the People’s Republic of China (2017) “Code for Urban wastewater and stormwater engineering planning”GB50318-2017, 2017 edition. China Planning Press, Beijing, China

Ningbo city - Five water treatments programme (May 2015)

• Aims to improve the water environment, protect water resources, and improve people’s livelihood • Secure fortification of city flood protection measures to meet the state standards, (50 Years events) by 2020; urban built-up area drainage standards (20 Year events)

Ningbo Municipal Bureau of Ecology and Environment (2015) Ningbo city - Five water treatments programme. Ningbo Municipal Bureau of Ecology and Environment, Ningbo, China. (http://sthjj.nin gbo.gov.cn/art/2015/3/13/art_ 19571_3095282.html)

Ningbo Municipal People’s Government: Implementation of upgrading urban and rural quality to build a beautiful Ningbo action plan guidelines (October 2015)

• Short-term (2015–2018): Combined with “Ningbo City promotion, beautiful quality construction” project to promote sponge city construction projects (2015–2018) • Medium-term (2018–2020): establish Sponge city support standards, management systems and monitoring • Long-term (2020–2030): Urban planning, construction, management, and implementation of the sponge construction concept to 80% of the city’s built-up area

Ningbo Government (2015) Ningbo Municipal People’s Government: Implementation of upgrading urban and rural quality to build a beautiful Ningbo - action plan guidelines (October 2015). Ningbo Government, Ningbo China. (http://gtog.ningbo.gov. cn/art/2015/10/20/art_692_ 297911.html)

Upcoming challenges From 2014 to the present time (2021), the SCP has become widely recognised as one of the global successes on GI promotion in cities and urban environments. The SCP indeed has addressed the local stormwater issues in the selected “Sponge Cities” in

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Table 6 Ningbo Municipality standards relevant to the implementation of Sponge City guidelines (adopted after O’Donnell et al. 2021; Griffiths et al. 2020; Chan et al. 2020) Municipal Standards

Specifications

Citation/source (in Chinese)

Eastern Ningbo city planning • Prevent flooding for 20-year area 24-h events in the river-basin planning standards, new town planning in the region targeted at 20-year design flood water level for 2.6 cm (Yellow Sea datum), 100-year flood water level 2.95 cm • Drainage system: using rainwater diversion system • 1. Discharged into the river nearby • 2. Network design parameters: storm intensity. Design return period 1 year, the initial concentration time: 10-15 min; the composite runoff coefficient 0.4–0.6. Sponge city Ningbo city planning guide (2016–2020) (March 2016)

Ningbo Planning Bureau (2017) Master plan of Ningbo East New Town (July 2017). The Eastern New Town (NET), Ningbo Government, Ningbo, China. (http://www.nbent.cn/ site/detail/id/95550/catId/481)

Sponge city Ningbo city planning guide (2016–2020) (March 2016 first published and updated May 2019)

Ningbo Municipal Bureau of Housing and Urban Rural Development (2019) “Ningbo urban planning and design guideline for sponge city” Code 2019 DX-08. Ningbo Municipal Bureau of Housing and Urban Rural Development, Ningbo, China

• By construction guidelines relating to the development of the city water system using “Green-grey design combination “ and belowground water-storage strategies • Aim to reduce downtown total annual runoff control rate by 75% for design rainfall events; in 80% of the urban area by 2030

China. That act as the role model and example for other Chinese cities to follow. We also understand there are several challenges ahead to hold the future success of SCP. Firstly, the SCP’s main aim is to address urban flood issues. We can argue that while most urban drainage infrastructure is improving in terms of increased flood protection and resilience, it is still designed only for up to 1-in-30 year events. However, if the threshold is exceeded, the infrastructure will continue to operate with sub-optimal efficiency. That said, it is expected that the MoHURD will aim to address this type of inconsistency after the latest guidance documents on urban land drainage standards (GB/T 51,345–2018). The CNG will have to address how SCP practice will be fully equipped to the city’s land drainage system, which is an important message. Otherwise, even the CNG pushes all Sponge Cities to achieve 80% of Sponge measures, but without an excellent urban runoff (include adequate drainage)

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system, the GI can only do their job on absorbing and purifying a certain amount of stormwater, as they are not designed for hydraulic flow and enhancing flow pathway to collect excess stormwater and offload to the storage points. Municipalities must be considered among several that cope with their own land use, geography, topography, and demographic factors. Extensively, the SCP should align with the catchment system. Otherwise, “Sponge” measures and facilities are only operating at the sitespecific level and challenging to cope with the urban runoff and peak discharge from a wider catchment scale to work effectively as addressing the urban water issues at a municipality level. While it would be unfair to use such occurrences to measure the initiative’s success (most pilot projects take at least three years to be completed), even when the concepts are extended across 80% of the city by 2030. There are some potentials in some “Sponge Cities” projects, such as Wuhan, Chongqing, which are also likely affected by large-scale fluvial floods. Some of these impacts are based on wider catchment/large rivers (e.g., 1998 Yangtze River flood) or storm surges from coastal areas (e.g., 2017, 2018 in Shenzhen, Zhuhai, and Guangzhou after typhoons Hato and Mangkhut), which will continue to influence city-wide flood risk (Chan et al. 2021). Indeed, in designing for 1-in-30 year (24 h) events only, the current Sponge City guidance may be failing to prepare adequately for typhoon-enhanced rainstorms. This is because current SCP standards on flood protection are purely not designed to mitigate large-scale catchment floods, coastal floods, or flash floods, where generated by topographical factors (e.g., hilly or mountainous areas and coastal shorelines) or even storm-enhanced intensive rainstorms/rainfalls urban floods. Secondly, current public and stakeholders’ participation in SCP has positively started. For example, communities and the public support the SCP development in the case of Ningbo (Chan et al. 2020b). However, Li et al. (2020) found that the SCP delivery of public participation and perception is still limited in Chinese cities compared with the GI development in the UK. This is partly due to the continued flooding in high-profile urban areas, where the public response to the implementation of Sponge City infrastructure has been mixed (Wang et al. 2017). Also, logically, if people suffered and were exposed to floods, the perception of flood risks is high than that experienced by flood threads and impacts (Lamond et al. 2009). Increasing perception to improve the communities’ preparedness and awareness is the smart approach as always, not only to increase the resilience but also reduce their flood impacts, consequently for their flood risks. The municipal government may consider that the SCP measures will increase flood resilience and fit with the Sponge City concept. It promotes a higher level of public participation, such as enhancing more communications with the communities, listening to their voices, and improving consultations and engagements before achieving better responses and feedback mechanisms. That can adapt better with the popularity of social media and new media channels via mobile phone (e.g., smart apps) that align with the mobile network to improve the communication between the stakeholders, public, and communities that expose urban floods and interest SCP in Sponge Cities. That also helps the authorities enhance better planning policies to conduct adequate response and recovery processes of urban floods. As a result, to improve the urban flood resilience (Zevenbergen et al. 2020).

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While looking at another example of SCP measure, the primary remit of the Ningbo’ Eco-Sponge City Construction programme is to improve flood management and mitigation within urban areas by adopting low-impact development technologies. The primary aim is to enhance the quality of water that is released downstream of urban areas. The 1.3 km’ Eco-Corridor’ hat forms part of the 205-acre New East City development area in Ningbo that combines with the eco-friendly bluegreen landscape design for bio-processing of pollutants (e.g., reducing nutrients level in urban runoff via local vegetation by constructed wetland and ponds with SCP measures). That showed the positive outcomes with reduced water pollution issues (e.g., eutrophication and other urban water problems) (Tang et al. 2015). This program has an opportunity to produce significant benefits on social-economic and environmental improvements (e.g., improving well-being, ecosystem services, recreational and leisure experiences.) (See Fig. 5). In this project, the local authority transformed old building stock (i.e., retrofitting perspectives) and surrounding areas. That could be another challenge for the long-term SCP delivery as required for complicated land-use arrangements (as land use space scarcity in Ningbo and other Chinese cities—such as a high price on lands, land use ownership), further restoration and conversion of urban-BGI/GI will be an expected challenge especially following the ambitious SCP guidelines by 2030s and beyond. Lastly, future financing of SCP is also vitally important as smoothly undergoing the Public–Private-Partnership (PPP) schemes for the program will also be a tough challenge. In particular, the CNG aims to push all 30 Sponge cities to transform about 80% of municipality land-use for Sponge functions and measures. That will

Fig. 5 Artificial wetland, Eco-corridor, Ningbo New East Town (Source Lei Li)

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require integration with objectives from related sectors (such as housing, sanitation, gardening, health, urban planning, transportation, civil services). On the plus side, attaining Sponge City goals may be aided by further rapid materials innovation, management and governance, urban planning, and technological support (e.g., bluegreen infrastructure constructions, building materials). Understandably all 30 pilot cities enjoyed the first three years (2015–2018) of roll-out (primarily direct investment from CNG) and into cities has been financed by the government, subsequent years have to develop PPP or anyway with their financial arrangements. No doubt that will require suitable interest from investors (e.g., private developers, funders) that have the same belief in the potential lifestyle and thus economic benefits of this type of investment. It has to attain both initial construction and subsequent maintenance costs on the sponge infrastructures. That eventually set up the long-term goals for the development plans that will benefit all parties and potentially will be made difficult (Griffiths et al. 2020b) by the continuing up-risen in real estate prices in the future.

4 Conclusions Nevertheless, SCP is a success story so far for the GI progress and development in China. It is complicated address the SCP can address all urban stormwater and flood issues because the program is continuing up to the 2030s and beyond. However, taking the positive sides after seven years initiated by the CNG, the SCP successfully demonstrated the ambitions to transform the Chinese cities to be more green and resilient in light of climate change and rapid urbanisation. We can see the affiliated urban water legislation on land drainage, stormwater runoff and discharge, water quality, conservation of soil and groundwater, and urban planning guidance has been revealed in this chapter. The progress of GI development in China via SCP addresses the urban water issues, but that is the priority that the CNG and municipal governments understand. The SCP targets to deliver multiple benefits to address ecological, social-economic, and urban sustainability scopes forward, which is encouraging and should be supported. Indeed, the SCP is not a panacea and currently still faces several significant challenges, including financing, proper hydrological engineering, and management adjustment (that merges with the catchment management plan, for example), public perception and participation (the adequate level of participation that should be taken in SCP or Chinese cities), the governance system that suits for SCP future delivery. These challenges cannot be solved in one day, and we still need time to “wait and see”. Now Chinese cities are up to the standard, and the governments and public are also seeking better living conditions. The aims of the SCP ticks some boxes as the practice is not only to prevent flood but also to improve water quality and potentially water supply (in water-supply limited areas), which are essential for the public and communities in Sponge Cities. As for those other factors for improving the living

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conditions and standards, these perhaps take precedence depending on the priorities identified within the future urban planning process (e.g., located in the Master Plans). That means that the resulting designs will depend on the CNG’s future vision and the local delivery from the selected Sponge Cities’ municipal governments. As from our case, the Ningbo government has done as a champion example among all other 29 cities and successfully transformed the National legislations and standards locally and adopted in their districts to serve the communities. For example, undertaking the composition of the better design (in hydrological effectiveness, level of purification, amount of storage, the level of ecosystem services, etc.) and planning team and the institutional arrangements (i.e., the balance of hydrologists, flood engineers, environmentalists, civil engineers, economist, etc.), so far Ningbo has done well that witnessed by the success stories for the “New Town Development” coping with the SCP in Cicheng New Town and Eco-corridor in East Ningbo New Town. Back to the basics, GI in SCP is mainly dealing with the urban hydrological issue. That said, factors that contributed to the SCP date back to China’s rapid urbanisation process in the early 1990s. Many Chinese cities have not been equipped with adequate land drainage systems but factually experienced increased waterlogging in densely populated areas. Urban floods occurred because of low-level land drainage convergence and capacity and massive flooding of new urban areas with large upstream catchments because of lacking integration of long-term hydrological issues in the urban Master Plans. These stories do not only occur in Chinese cities but are common in many countries. That is a part of urban parcel transformation when the cities are targeted for survival at the stage focusing on the financial development spectrum (McPhearson et al. 2016). It is not exclusive for Chinese cities to experience urban floods due to urbanisation and related human-induced factors. The CNG thinks that is the right time to promote GI and SCP. The initiative aims for up to 70% of rainfall excess to be recycled on greenery since 2014 seems appropriate and encouraging for pushing the SCP and GI forward at this third stage up to 2030s and beyond, which will benefit the next generations in Chinese cities.

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Planning Innovation

Does the National Forest City Policy Promote Haze Pollution Control? Chang Xu, Yueming Li, Xinfei Li, and Baodong Cheng

Abstract Air pollution is a significant issue with global impacts. The implementation of China’s national forest city policy may provide some valuable references for air pollution control. First of all, this chapter introduces the main content of China’s national forest city policy selection. Then, under the condition of considering the time lag effect, spatial lag effect, and space–time hysteresis, it uses the unique and comprehensive panel data of 276 cities in China from 2003 to 2016. In doing so, we use the difference in differences method (DID) and the dynamic SAR model to estimate the policy effects of the implementation of national forest cities on the control of haze pollution. We find that there is an apparent spatial spillover effect in China’s smog pollution. In addition, there is a strong positive correlation between the local smog pollution between the local areas and the surrounding areas in the same period. In this period, the higher the local smog pollution is, the higher the smog pollution in the next period of the local area is. In contrast, the next period of smog pollution in the surrounding is lower. The national forest city policy has improved the level of urban greening and can significantly reduce urban smog pollution. Whether in the long-term or short-term, if a city is selected as a forest city, it will substantially promote the smog pollution of the city and surrounding cities. However, the impact of the national forest city policy on smog pollution also shows cyclical fluctuations, like after each review by the central government, the effect of the national forest city policy to reduce haze pollution will be significantly improved. Keywords National forest city policy · Haze pollution · DID · Dynamic SAR model

C. Xu (B) Anhui University of Finance and Economics, No. 962 Caoshan Road Bengbu, Anhui, China e-mail: [email protected] Y. Li · X. Li · B. Cheng School of Economics and Management, Beijing Forestry University, No. 35 Tsinghua East Road Haidian District, Beijing, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_6

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1 Introduction The living environment of human beings is deteriorating with the accelerating changes in economic development and industrial technology. In recent years, air pollution has become one of the most concerning environmental problems. Most developed countries have experienced severe air pollution in history, such as Los Angeles photochemical smog event in 1943, the London poison fog incident in 1952, Ruhr air pollution in Germany in the 1960s, and Milan smog pollution in the 1980s. Some developed countries in Asia, such as Japan, experienced severe smog pollution from the 1950s to the beginning of the twenty-first century. In 1961, the annual dust and sulfur dioxide emissions in Yokkaichi of Japan reached 130,000 tons, and toxic gas and toxic metal dust were floating in the 500 m thick smoke. After the mid-1980s, the number of victims of air pollution suddenly increased sharply, especially in Tokyo. These countries control air pollution by controlling industrial emissions, strengthening environmental legislation, encouraging citizens to pursuit green commuting, and using clean energy (Bessou et al. 2011; Conti et al. 2015; Yamineva and Liu 2019). Now developing countries are also experiencing similar air pollution. The haze in New Delhi, the capital of India, is the worst among the world’s largest cities, with PM2.5 values sometimes approaching 1000 µg per cubic meter. In the past three years, air pollution in cities like Mumbai and Cairo has been five times more than the World Health Organization’s safety standard. The air pollution in Mongolia is also severe. And the PM2.5 level in a shantytown in Ulaanbaatar, the capital of Mongolia, reached 1985 µg per cubic meter on December 16, 2016, due to the overloaded power plant spewing smoke into the air. As the world’s largest and fastest-growing developing country, China is also facing severe air pollution. More than 500 million Chinese urban residents (14% of the global urban population) suffer from PM2.5 (Du et al. 2018). Despite the existence of a certain degree of meteorological factors, scholars attribute the source of China’s haze pollution to extensive economic development, unbalanced industrial structure, high-polluting energy structure, and inefficient environmental management (Wang et al. 2020). Scholars also propose governance ideas, such as transforming the economic development model, adjusting the industrial and energy structures, and strengthening environmental regulations (Ahmad et al. 2020; Wang et al. 2021). Consistent with most developing countries, China’s fast-growing development has also brought about the rapid advancement of urbanisation. Therefore, some scholars have studied the relationship between urbanisation and smog pollution. In addition, they pointed out that how to plan and build cities is a current problem, which the government should consider carefully in China. They believe that a green and sustainable urbanisation development model is a better choice for China to resolve the contradiction between urban construction and environmental pollution (Du et al. 2018). The idea of a forest city provides a new path for coordinating economic growth and environmental protection. The forest city is a green infrastructure network composed of urban forest ecosystems. As an ecosystem, it is based on forest land, includes urban

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waters, orchards, grasslands, nurseries, and other components, and is closely related to urban landscape construction, park management, and urban planning. At present, China is actively and extensively promoting the construction of forest cities. In the process of building forest cities, the most worthy of expectation is the construction and selection of “National Forest Cities” launched by the National Afforestation Committee of China and the State Forestry Administration. China implements the “National Forest City” construction project to repair urban ecology and improve the city’s regional climate and environmental quality. In 2004, China officially started the “National Forest City” construction project. Then the Chinese government issued the “National Forest City Evaluation Index” (for further details, refer to: http://www. forestry.gov.cn/portal/xby/s/1277/content-126969.html) and the forest city evaluation methods have been strictly regulated from dozens of aspects. These aspects include but are not limited to urban forest coverage rate, forest ecological network, public leisure, management system, special fund financial budget, and so forth, and formulated a detailed review strategy. Thus, the construction of forest cities has been directed to a scientific way. In the decades since the construction of national forest cities have been implemented, more than 200 cities across the country have carried out forest city activities, of which 165 cities have been awarded the title of National Forest City. In July 2018, the Chinese government released the “National Forest City Development Plan (2018–2025)”, pointing out that it will focus on the coordinated development of Beijing-Tianjin-Hebei and the national strategy of the Yangtze River Economic Belt. The plan takes into account factors such as forest resource conditions and urban development needs. By the end of 2020, six national forest urban agglomerations were built. These included Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta, Changsha-Zhuzhou-Xiangtan, Central Plains, and Guanzhong-Tianshui, along with 200 national forest cities. Moreover, 300 national forest cities are expected to be built by 2025. In the published studies, scholars also recognise the value of forests in reducing smog pollution. National forest cities have become a meaningful way to increase China’s forest area and improve the urban ecological environment (Xu et al. 2020). The existing research still has considerable research gaps on whether forest cities can reduce haze pollution. Therefore, it is of great significance to study the impact of forest city construction on urban smog pollution and evaluate the effect of national forest city construction projects from a macro perspective. By comparing the changes in the smog pollution index of the project implementation cities, it is possible to estimate the overall effect of the project implementation. It can provide a reference for the adjustment and improvement of the policy system and provide good ideas for other developing countries plagued by haze. We use the difference in differences method DID to evaluate the impact of China’s national forest city project implementation on haze pollution from 2003 to 2016. Because of the time-lag effect and the spatial lag effect of haze pollution, we use a dynamic space SAR model to ensure the consistency of estimation results. We use unique data and nighttime lighting data to measure economic development. The structure of this chapter is as follows. The second part first introduces the main contents of China’s national forest city policy and the criteria of evaluation and

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review. The third part presents the methods, the variables, and the data sources. The fourth part gives the regression results of the dynamic SAR model under the difference in differences method. It calculates the short-term and long-term direct effects and indirect effects of the variables on haze pollution. Furthermore, we test the impact mechanism of the selection of national forest city policies on haze pollution and the periodicity of national forest city policies on the effect of reducing smog. The fifth part discusses the implementation effect of the national forest city policy and the impact of various variables on haze pollution and explains the reasons. Finally, we present conclusions and recommendations on policies in the sixth part.

2 Policy Background Faced with the grim situation of tight resources, severe environmental pollution, and degraded ecosystems, the Chinese central government has increasingly attached importance to ecological construction. As an essential part of ecological civilization construction, forest city construction has been written into the “Thirteenth FiveYear Plan for National Economic and Social Development of the People’s Republic of China”. At present, the State Council has listed the approval of the title of the National Forest City as an internal government approval item and listed the forest city project in 165 major projects of the “Thirteenth Five-Year Plan”. The construction of forest cities is a bright spot in urban forestry and ecological construction. Cities are eligible to apply for the title of “National Forest City” only if they have officially started constructing forest cities for more than two years. The structure of forest city construction plans has been officially implemented for more than two years. Each year, the National Forestry and Grassland Bureau of China will award the title of “National Forest City” among the cities that have built forest cities. The National Forestry and Grassland Bureau has also developed an assessment method consisting of four steps: (1)

(2) (3)

(4)

Submitting an application by the city, submitting a report on the creation of the applicant city, reporting on the implementation of the overall plan for the construction of the city’s forest city, and the reports on self-examination of the applicant city; Organising experts to conduct closed-door audits of reports submitted by applicant cities, and submit preliminary review opinions; Conduct on-site verification of suspected indicators based on preliminary review opinions of experts, and put forward verification of experts opinions; and According to the evaluation opinions of experts, the National Forestry and Grassland Bureau will publicise the list of public notices to be approved for the title of the National Forest City in the media, such as the website of the State Forestry Administration.

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According to the publicity situation and the review by the National Forestry Administration, cities are decided whether they can be awarded the title of “National Forest City”. Although the construction of forest cities has strong autonomy under the national forest city policy, local governments will still try their best to apply for construction and obtain the title of “National Forest City” because the construction of demonstration cities is related to the governments’ achievements. After three years, the National Forestry and Grassland Bureau will also conduct a dynamic assessment of the “National Forest City” and organise experts to conduct a comprehensive review and verification after granting the “National Forest City” title. If the review and verification meet the requirements, the “National Forest City” title shall be retained; if the review fails to meet the requirements, it shall be warned and rectified within a time limit. If the review fails to meet the requirements after five years, the “National Forest City” title will be revoked. Checked against the national forest city review policy, the demonstration cities may release a series of mandatory measures to ensure the review. Because for cities that have obtained the title of the “National Forest City”, if the target evaluation index cannot be achieved, it will be difficult for them to obtain support from the central government in the future. According to the relevant announcements of the central government, the national forest city policy has operated well. And the national forest cities that have been rated as model cities have an annual increase of more than 13,300 hectares of green forest area, which realise the ecological functions related to human well-being and environmental improvements, like beautification, recreation, health functions, air purification, cooling, and energy conservation. (For more details, see the primary governmental source at: http://www.china.com.cn/newphoto/news/2016-04/08/con tent_38200694.htm). However, according to the relevant person in charge of the national forest city policy of the National Forestry and Grassland Bureau, it is similar to the problems encountered by most countries in the early stage of a forest city. Thus, China’s forest city construction is still a government-led project. The time of planning construction and operating is short. It faces the problems of insufficient resources and management experiences such as funding sources, technical support, and personnel training. National forest city construction is a top-down policy, and the construction effect is likely to change due to the intensity of the central government’s review. Lastly, it is difficult to understand and determine the effectiveness of the policy without relevant empirical analysis to assess national forest city policies. Therefore, we construct this research to add more insights into the construction of forest cities and provide some reference for future national forest city policies.

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3 Model and Data 3.1 Model To assess the impact of forest city construction on haze pollution, we used the difference in differences method (DID) for assessment. We take cities rated as a national forest city as a treatment group, and cities not rated as a national forest city are taken as a control group. The change in the degree of smog pollution in the control group reflects the influence of other synchronic factors other than the national forest city selection policy. When the changes in smog pollution before and after being rated as a national forest city minus which not being rated as a national forest city, the net effect of rating national forest cities on reducing the degree of smog pollution can be determined. Since the time cities are rated as national forest cities is different, we control the fixed effects of time and city in the model. W then set the virtual variable D, which the city I already rated as national forest cities in the t period was set as 1 and 0 for the city that was not rated as the forest city during the t period. D indicates whether the city is a forest city in the year. The net effect of the national forest policy on reducing the degree of smog pollution is determined by estimating the coefficient of D. It should be pointed out that we cannot accurately identify the year in which the city started construction of the forest city in reality. Still, it can be confirmed that after the city is rated as a national forest city, it will be equipped with relevant management systems in accordance with relevant regulations. Forest construction will also be strictly implemented according to the plan and be reviewed by the central government. Therefore, we can assume that the reduction effect of rating the national forest city can be reflected in the year of implementation. However, forest construction is also a relatively long-term process. The construction of public leisure places also needs to be accumulated in the early stage. Only when the city reaches a certain standard in forest construction, green coverage, and public leisure places can it be rated as a forest city, so whether it is selected as a national forest city is strongly correlated to the city’s forest construction, green coverage, public leisure venue construction, etc. Therefore, the variables that can reflect the degree of forest city construction should not be missed. Otherwise, no consistent estimate will be obtained, and the net effect of the policy will not be measured. According to the evaluation criteria of forest cities, we use the green area of the built-up area (Green), the average park area (Park), and the urban maintenance construction expenditure (Investment). These are used to measure the degree of forest city construction and put it into the regression model as an explanatory variable. We expect that the ecological function of the cities rated as a forest city will be better played, and the degree of smog pollution will be reduced. We use the STIRPAT framework proposed by Rosa and Dietz (1998) as the basis for selecting control variables. The STIRPAT model is widely used to analyse environmental pollution influencing factors (Shao et al. 2011; Luo et al. 2018). The STIRPAT model considers environmental pollution levels as a function of economic development, population, and skill levels. Combining the STIRPAT model with the

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subject of this chapter, in our study, the indicators and explanations for the explanatory variables used to analyse the smog pollution level are as follows: (1) Based on the STIRPAT model framework, we use the population density to measure the population size and population density. The calculation method is the total population at the end of the year divided by the administrative area. Under normal circumstances, the more people’s production and life gather, the greater the ecological pressure of the city, the more serious the smog pollution may be (Ma et al. 2016). (2) Wealth levels are usually measured by GDP per capita. However, the authenticity of China’s official national economic statistics is often questioned. Many scholars believe that there is a strong correlation between nighttime lighting data and economic growth, and night lights are used as an alternative indicator of economic growth (Wen et al. 2012). Thus, we also use nighttime light intensity data as a measure of wealth level (A) concerning this approach. Studies have shown that (the level of) economic development is closely related to smog pollution (Xu and Lin 2016). The classic EKC hypothesis suggests that environmental quality will show an inverted U-shaped trend with improved economic growth. Still, existing research indicates environmental variables and economic growth may also have a U- or N-shaped curve relationship (Diao et al. 2009). Therefore, we also add a quadratic term for the light intensity data in the model (A2) to test the relationship between economic growth and changes in smog pollution. (3) The improvement of technology level (T) has an essential impact on environmental pollution control. This study uses energy efficiency to measure the progress of energy-saving and emission reduction technologies. The calculation method of energy efficiency is the GDP of the region divided by the region. The greater the value of electricity consumption, the less electricity is consumed per unit of GDP, and the higher the energy-saving and emission reduction technology. It is important and needed to emphasise that the basis of most quasi-experimental methods (including the DID model) is the Stable Unit Treatment Value Assumption (SUTVA), which requires no spatial “interference” between units. This is the treatment state of one observation does not affect the outcome of another observation. However, an important assumption that underlies the majority of quasi-experimental methods, including the DID model, is the Stable Unit Treatment Value Assumption (SUTVA) that Requires there to be no spatial “interference” among units; i.e., the treatment status of one unit does not affect the outcomes of another (Rubin 1990). Due to the natural flow of the atmosphere caused by weather factors such as wind direction, temperature difference, and precipitation, the degree of smog pollution between adjacent areas will affect each other, and the spatial conduction effect of smog is obvious (Hao and Liu 2016; Wang et al. 2013; Chen et al. 2017). The spillover effect makes the level of smog pollution spatially dependent. The degree of smog pollution in a city is closely related to the degree of smog pollution in the neighboring area. The unbiased regression coefficient can only be considered when using the spatial lag model to consider this spillover effect generation (Anselin 1988). Existing research has generally affirmed the existence of spatial effects (Xu et al. 2020). However, the spatial dependence of smog pollution is reflected in the relevant impacts of the current region and may be affected by the previous corresponding behaviors between regions. In recent years, the Chinese government is actively changing its extensive

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economic development mode. The central government has emphasised ecological civilization construction and has set stricter standards for emission reduction and pollution control for local governments. The assessment of green GDP has been incorporated into the assessment criteria for the promotion of local government officials. Due to the promotion competition among local officials, the public’s pressure on public opinion and the supervision and inspection of environmental protection departments, the level of smog pollution in the immediate vicinity of the region or the region may also affect the local government’s current reduction decision, which means that smog pollution has a dynamic dependence in both time and space. These spillover effects constitute a violation of the SUTVA hypothesis, and a standard DID model that ignores these spillover effects will produce biased and inconsistent estimates. We modified the time and space dependence characteristics of smog pollution into expressions and constructed the full dynamic SAR model (DSAR): ln P Mit =τ W ln P Mit−1 + ψ ln P Mit−1 + ρW ln P Mit + ζ Dit + β X it + αi + γt + μi

(1)

In formula (1), the dependent variable lnPMit is the level of the logarithm of smog pollution and is used to measure environmental pollution. lnPMit-1 represents the smog pollution level of one phase lag. W is the spatial matrix for the autoregressive component. We use the adjacency matrix of the queen standard. τ is the time and space hysteresis effect coefficient, which is used to reflect the influence of smog pollution in the vicinity of the lag phase on the smog pollution in this area. ψ is the time lag coefficient, reflecting the impact of the previous smog pollution on the current period, indicating the magnitude of its time lag effect. ρ indicates the current space lag effect coefficient, reflecting the impact of smog pollution in the immediate vicinity on the smog pollution in this area. D is a dummy variable indicating whether it is rated as a national forest city, ζ indicates the net impact of the national forest city policy on urban haze pollution. X denotes an explanatory variable, β represents the coefficient of the explanatory variable. Since the key explanatory variables may also exhibit spatial correlation, this study also uses dynamic space Dubin to analyse the spatial spillover effect of the explanatory variables, and set the following full dynamic SDM model (DSDM): ln P Mit =τ W ln P Mit−1 + ψ ln P Mit−1 + ρW ln P Mit + ξ W Dit + θ W X it + ζ Dit + β X it + αi + γt + μi

(2)

In (2), ξ W Dit is used to measure the spatial spillover effect of policy variables, θ W X it is used to measure the spatial spillover effect of explanatory variables. Other settings are the same as (1).

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3.2 Data Sources Considering the availability of data and the representativeness of the sample, we selected China’s prefecture-level cities from 2003 to 2016 as research objects. A total of 276 sample cities were excluded from the sample of administrative divisions and missing data during the survey year. These cities cover most of China’s prefecturelevel cities, as well as cities in key forest urban agglomerations in the National Forest Urban Development Plan. The samples are highly representative. The PM2.5 concentration data used herein is based on the global PM2.5 concentration 2003–2016 mean raster data provided by Columbia University’s Center for Social and Economic Data and Applications. Compared with the ground field detection data, the data is based on satellite monitoring and belongs to the surface source data, which can reflect the change of PM2.5 concentration in a region more comprehensively and accurately (Shao et al. 2016), meeting the research needs of this study. Nighttime lighting data comes from the 2003–2013 DMSP/OLS stable lighting data and the 2013–2016 synthetic lighting data released by the National Oceanic and Atmospheric Administration (NOAA) (https://ngdc.noaa.gov/Eog). 2013 is the coincidence year of DMSP/OLS and NPP/VIIRS satellite data. Based on this year’s DMSP/OLS image, the VIIRS image is corrected, vectorised, and reduced the observation error by internal observation and data integration to obtain continuous nighttime lighting data from 2003 to 2016. Data for the National Forest City Policy implementation comes from the National Forestry and Grassland Bureau of China (http://www.forestry.gov.cn/). The data on the green coverage area, the average park area, and the urban maintenance and construction expenditures of the built-up areas used by other explanatory variables are derived from the China Urban Statistical Yearbook and the statistical yearbooks of each region.

4 Empirical Analysis 4.1 Spatial Econometric Regression Results As shown by the global Moran’s I test results in Table 1, the Moran’s I index is positive under the W matrix and passes the significance test at the 1% level. It shows that the spatial distribution of smog pollution indicates positive correlation characteristics of Table 1 Global Moran’s I test Variables

I

E(I)

sd(I)

z

p-value

Moran MI

0.828

0

0.011

75.629

0.0000

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high and low concentration. It also suggests that it is necessary to consider the spatial spillover effect of smog pollution in empirical test, and use a spatial measurement model to analyse data (Anselin 1988). Before estimating the model parameters, we first need to compare the two competitive models of the dynamic SAR model and the dynamic SDM model. The first and second columns of Table 2 are the decomposition results of the short-term total effect and the long-term total effect of the dynamic SAR model. The third and fourth columns are the decomposition results of the short-term total effect and the long-term total effect of the dynamic SDM model. The Wald test cannot significantly reject the null hypothesis of θ = 0. The Lratio test rejects the null hypothesis only at the 4.9% significance level, indicating that the spatial effects of the explanatory variables are not very significant, and SDM can be converted to the SAR model. Further reference is made to the model selection criteria of Akaike information criterion (AIC) and Bayesian Information Criterion (BIC) (Akaike 1973; Schwarz 1978). The AIC and BIC of the dynamic SAR model are −7205.844 and −7131.62, respectively, which both smaller than the dynamic SDM model. Therefore, the study finally selects the dynamic SAR model with the lowest AIC value and BIC. The next analysis is based on the regression results of the dynamic SAR model. It can be seen from Table 2 that the spatial lag term coefficient of smog pollution level is positive and pass the significance test at 1% level, which proves that there are obvious spatial agglomeration characteristics of smog pollution in Chinese cities. For every 1% increase in smog in the immediate vicinity, the smog in the region will increase by about 1.02%. From the time dimension alone, the time lag coefficient of smog pollution is significantly positive at the level of 1%. For the current smog pollution increased by 1%, the next smog pollution will increase by about 0.28%, indicating that smog The pollution change has obvious path dependence characteristics. When the current smog pollution is at a high level, the next smog pollution level will likely continue to rise. From the perspective of time and space, the space– time lag coefficient of smog pollution is significantly negative at the level of 1%, indicating that the higher smog pollution level in the adjacent area in the previous period may promote the current smog pollution in the region to reduce. Figure 1 shows the mean of smog pollution degree change trend of the control and treatment groups before being rated as a forest city. It can be seen that the two are more consistent in the time fluctuation trend. However, due to the impact of the treatment group’s selection of national forest city policies, this Parallel Trend has changed since the city was rated as a national forest city. As shown in the first column of Table 2, from the short-term total effect of being rated as a national forest city, the treatment group was significantly reduced compared with the control group after being rated as a national forest city, and reached a significant level of 1%. In the long run, as shown in the second column of Table 2, the selection of national forest cities still has a significant role in promoting urban smog pollution. The absolute effect of the long-term total effect of the treatment group after being rated as a forest city is also greater than the short-term total effect, which indicates that the selection of forest cities has far-reaching long-term effects on reducing smog pollution.

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Table 2 Short-term total effects and long-term total effects The dynamic SAR

Rated as a forest city this year

(2)

(3)

(4)

SR_Total

LR_Total

SR_Total

LR_Total

−0.0368*** −0.0522*** −0.0370*** −0.0518*** (0.0137)

ln (green coverage of built-up area) ln(average park size)

The dynamic SDM

(1)

(0.0195)

(0.0139)

(0.0198)

−0.0711*** −0.1009*** −0.0216

−0.0303

(0.0124)

(0.0183)

(0.0244)

(0.0342)

0.0086

0.0122

0.0156

0.0219

(0.0068)

(0.0097)

(0.0183)

(0.0257)

ln (expenditure of urban maintenance −0.0118*** −0.0167*** −0.0288*** −0.0403*** and construction) (0.0045) (0.0064) (0.0104) (0.0146) light1

0.0172***

0.0243***

0.0228***

0.0319***

(0.0057)

(0.0081)

(0.0075)

(0.0106)

light12

−0.0003*** −0.0004*** −0.0003*** −0.0004*** (0.0001)

(0.0001)

(0.0001)

(0.0001)

ln population density

0.0100*

0.0142*

0.0144

0.0201

(0.0060)

(0.0085)

(0.0129)

(0.0181)

−0.0018**

−0.0026**

−0.0029

−0.0040

(0.0008)

(0.0012)

(0.0023)

(0.0032)

Energy efficiency Wlnpm25

1.0157*** (0.0329)

(0.0333)

L.lnpm25

0.2755***

0.2780***

(0.0164)

(0.0164)

−0.2655***

−0.2764***

L.Wlnpm25

1.0088***

(0.0458)

(0.0460)

Time

Controlled

Controled

City

Controlled

Controled

Wald test P

0.1526

Lratio test P

0.0493

AIC

−7205.844

−7202.552

BIC

−7131.62

−7091.215

AR (2) P

0.391

0.417

Observations

3,588

3,588

R-squared

0.6004

0.8022 (continued)

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Table 2 (continued) The dynamic SAR

Number of id

The dynamic SDM

(1)

(2)

(3)

(4)

SR_Total

LR_Total

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Note Robust standard errors in parentheses, ***p < 0.01, **p < 0.05, *p < 0.1 50 40 30 20 10 0 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Fig. 1 Changes in smog pollution in forest cities and non-forest cities before being rated as forest cities

The green coverage area of the built-up area has a significant effect on smog pollution. In the short term, the mulch pollution will decrease by 0.07% for every 1% increase in the green coverage area of the built-up area, and the smog pollution will decrease by 0.1% in the long run. The increase in urban maintenance and construction capital expenditure is conducive to reducing smog pollution. For every 1% increase in urban maintenance and construction funds, the degree of smog pollution will decrease by about 0.01% in the short term, and the smog pollution will decrease by 0.02% in the long run. As another measure of forest cities, the average park size has no significant effect on the effects of smog pollution. The economic growth measured by nighttime lighting data has a significant positive impact on smog pollution, and its quadratic term is negative, and pass significance test at 1% level, indicating the inverse U-shaped relation between economic growth and smog pollution exists, that is, smog pollution will experience a process of rising first and then falling in economic development. In the short term, population density has a significant positive impact on smog pollution, and as time goes by, the population density will further worsen smog pollution. The long-term and short-term total effects of energy efficiency on smog pollution are significantly negative, indicating that advances in energy-saving and emission-reduction technologies can significantly reduce smog pollution.

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4.2 Forest City Construction Improves the Effect of Urban Greening and Its Periodicity From the regression results of spatial measurement, we can see that the forest city policy has a strong positive impact on reduction. The National Forest City Policy has strict regulations on urban forest coverage and green area, requires urban forest construction to be strictly implemented according to the overall urban forest construction plan, and has a corresponding inspection and assessment system. Active selection policies may promote the ecological functions of forest cities and thus enhance their declining effects. However, this top-down selection policy is likely to change as the central government’s review cycle changes. The concentration of smog pollution is one of the key measures in China’s current assessment of air pollution levels. The China Environmental Bulletin (2017) shows that the number of days with PM2.5 as the primary pollutant has accounted for 74.2% of the heavy and above pollution days. In order to observe the improvement effect of the air quality of the cities in the treatment group after being selected as national forest cities, we used the concentration of smog pollution to characterise the degree of air pollution and fitted the changes in the degree of air pollution with the length of the forest city selection. As shown in Fig. 2, it can be seen that the degree of air pollution in the cities in the treatment group is declining after being

Fig. 2 Smog fluctuation cycle after the treatment group being rated as the national forest city (the line segment represents the 95% confidence interval)

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rated as a national forest city. Still, the national forest city selection policy shows a significant cyclicality in the fluctuation of the treatment effect of the air pollution level. Specifically, the degree of air pollution in the first year after being rated as a national forest city declined rapidly. Still, after three years, the degree of air pollution in the fourth year showed a clear sign of rising, and then it will enter a downward state, and it will fall. More quickly. During the ten years of Fig. 2, the degree of atmospheric pollution fluctuated in a four-year cycle. It should be pointed out that after the seventh year, the estimated confidence interval is increasing because the number of cities selected as national forest cities is less. Still, the trend is basically consistent with the first two.

5 Conclusions and Suggestions Taking 276 cities in China as an example, this study uses DID method to evaluate the impact of implementing national forest city selection policies on haze pollution. We first combed the concept of a forest city and the main content of China’s national forest city policy. Then according to the basic theoretical framework of the STIRPAT model, the dynamic SAR model with a two-way fixed effect is used to empirically test the impact of China’s forest city construction on haze pollution. This research is based on unique and comprehensive panel experience data from 2003 to 2016. Specifically, the smog pollution data used in this study is derived from the raster data of the global average PM2.5 concentration based on satellite monitoring published by Columbia University’s Center for Social and Economic Data and Applications. The national forest city selection data is derived from China National Forestry and Grassland Bureau; we also use the nighttime lighting data released by NOAA to measure economic growth. We find that China’s haze pollution showed obvious spatial spillover effects and high-emission “club” agglomeration characteristics. The main factor leading to the formation of this pattern is the atmospheric circulation and the economic circulation between the adjacent regions. The haze pollution shows a certain evolution law in time, space, and space–time two-dimensional evolution: The local smog pollution in the current period is positively related to that in the surrounding area. The higher the local smog pollution in the current period, the higher the local smog pollution in the next period, but the smog pollution in surrounding areas in the next period is lower. The national forest city policy significantly reduces urban haze pollution. Whether in the long-term or short-term, implementing the national forest city policy significantly reduces the smog pollution of the demonstration city and surrounding cities. The establishment of a national forest city policy promotes the growth of urban forest green space. Also, it improves the ecological benefits of urban green space so that it can play the role of reducing urban forest and preventing smog. However, the impact of the national forest city policy on haze pollution also shows cyclical fluctuations, which is consistent with the time point of the central government’s review every three years. After each review, the forest city’s reduction effect will be

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significantly improved. Our research also finds that the green coverage rate of the built-up area and the increased expenditure of urban maintenance and construction can help reduce smog pollution both in the locality and surrounding areas. In the long run, this reduction effect is still obvious. The increase in population density will increase smog pollution in the locality and surrounding areas. And an increase in energy efficiency will reduce haze pollution in the locality and surrounding areas. In addition, our research also finds that the level of economic development and haze pollution shows an inverted U-shaped relationship, and the EKC hypothesis is verified by using data from Chinese urban levels. Based on the above conclusions, we can get some useful enlightenment to control the haze pollution: from the characteristics of the smog pollution in the time, space, and space–time two-dimensional evolution. We believe that haze pollution control must adhere to joint defense and joint control strategies between regions. This will form a regional synergy to effectively control the haze and maintain the sustainability of the haze control policy to prevent the level of haze pollution from rebounding. In view of the fact that the national forest city selection policy can better reduce urban haze pollution, we believe that the Chinese government should continue to expand the construction of forest cities. From Shanshui City (1990), Garden City (1992), Environmental Model City (1997), Health City (1999), Livable City (2000), Green City (2001), Eco City (2003), National Forest City (2003), and now to the smart city. There are too many urban construction concepts and urban selection activities. Each city’s evaluation activities also have their own standards, which promote urban construction to some extent, but it brings confusion to urban construction. Urban construction ignores the direction it should have and falls into the chaos that cities compete with their awards. What kind of city is the ideal urban model. The chaos of these concepts makes forest cities’ construction practices fall into confusion and even go into misunderstandings. Therefore, the correct position of urban construction goals is particularly important. We should combine with relevant laws and regulations’ requirements and incorporate the development concepts, industrial policies, technical norms, and decision-making methods. They contribute to the promotion of urban forest development into the framework of an urban plan for development and the policy for management, based on the existing urban planning index system and the framework of urban planning management system policy. It will establish long-term mechanisms and institutional guarantees for forest cities. In addition, as a typical public good, urban forests cannot be separated from the government’s construction funds. Local governments should play a leading role in the construction of forest cities. Still, it also needs to cultivate the citizens’ awareness of protecting the ecological forest and guide the citizens and non-profit organisations to participate. It can enhance people’s forest construction and protection awareness by educating and guiding people’s ecological transformation of ideas and behaviors, thus forming an ecological and cultural atmosphere of society. This is the only way to build an ecological civilization. The promotion of ecological education cannot rely solely on people’s self-conscious introspection. It must be promoted through institutionalisation. This has become the consensus of all countries. And the developed countries are at the forefront of the institutionalisation or legalisation of ecological

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education. For example, the developed countries represented by the United States and Japan have enacted the Environmental Education Law. Domestic urban areas such as Tianjin and Ningxia have also promulgated local environmental educational regulations, which have laid an important practical foundation for the institutionalisation of environmental education at the national level. With the popularisation and deepening of ecological education, the process of ecological culture construction will also accelerate, and the concept of harmonious coexistence between human beings and nature will surely be engraved on the people’s hearts. Eco-education also has an important task, which is to promote public participation. In this aspect, the Chinese government has made some useful efforts, such as publicising propaganda for citizens and guiding citizens to recognise and adopt green spaces. Promoting ecological culture will drive people to actively participate in the construction of forest cities, which is also an important driving force for the construction of forest cities. On this basis, the Chinese government should not neglect the role of local environmental protection associations, green associations, and other environmental protection civil organisations, widely rumor, carry out social supervision, actively promote the construction and maintenance of forest cities, and ensure the sustainable operation of forest cities. Although we have always focused on China, this research has certain positive implications for other countries in the world. Governments often need to weigh and consider a balance between pollution reduction and economic growth (Chen et al. 2017). While we emphasise the transformation of development models and the adjustment of industrial structure to reduce pollution, we should not ignore the pollution control effect that urban construction may bring. The ecological service function of forest city construction can release the pollution problems caused by rapid industrialisation and urbanisation to some extent, such as improving urban microclimate, preventing soil erosion, reducing sandstorm and urban heat island effect. Then it can create a suitable urban habitat. We believe that these ecological functions of forest cities will provide a new path for mitigating and controlling environmental pollution problems in the region.

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Conti ME, Ciasullo R, Tudino MB, Matta EJ (2015) The industrial emissions trend and the problem of the implementation of the industrial emissions directive (ied). Air Qual Atmos Health 8(2):151– 161 Diao XD, Zeng SX, Tam CM, Tam VW (2009) EKC analysis for studying economic growth and environmental quality: a case study in China. J Clean Prod 17(5):541–548 Du Y, Sun T, Peng J, Fang K, Liu Y, Yang Y, Wang Y (2018) Direct and spillover effects of urbanization on PM2.5 concentrations in China’s top three urban agglomerations. J Clean Prod 190:72–83 Hao Y, Liu YM (2016) The influential factors of urban PM2.5 concentrations in China: a spatial econometric analysis. J Clean Prod 112:1443–1453 Luo K, Li G, Fang C, Sun S (2018) PM 2.5 mitigation in China: Socioeconomic determinants of concentrations and differential control policies. J Environ Manage 213:47–55 Rosa EA, Dietz T (1998) Climate change and society: speculation, construction and scientific investigation. Int Sociol 13(4):421-455 Rubin DB (1974) Estimating causal effects of treatments in randomized and nonrandomized studies. J Educ Psychol 66(05):688-701 Schwarz GE (1978) Estimating the dimension of a model, [J]. Ann Stat 6(2):461–464 Shao S, Li X, Cao J, Yang L (2016) China’s economic policy choices for governing smog pollution based on spatial spillover effects (in Chinese). Econ Res J 9:73–88 Shao S, Yang L, Yu M, Yu M (2011) Estimation, characteristics, and determinants of energy-related industrial CO emissions in Shanghai (China), 1994–2009. Energy Policy 39(10):6476–6494 Wang KL, Ding LL, Wang JM, and Yang M (2020) Analysis of provincial total-factor air pollution efficiency in china by using context-dependent slacks-based measure considering undesirable outputs. Nat Hazards 104(9) Wang T, Peng J and Wu L (2021) Heterogeneous effects of environmental regulation on air pollution: evidence from china’s prefecture-level cities. Environ Sci Pollut Res (1) Wang YS, Yao L, Liu ZR, J DS, W LL, Z JK (2013) Formation of haze pollution in Beijing-TianjinHebei region and their control strategies (in Chinese). Bull Chin Acad Sci 28(3):353–363 Wen WA, Hui CA, Li ZB (2012) Poverty assessment using dmsp/ols night-time light satellite imagery at a provincial scale in china. Adv Space Res 49(8):1253–1264 Xu B, Lin B (2016) Regional differences of pollution emissions in China: contributing factors and mitigation strategies. J Clean Prod 112:1454–1463 Xu C, Dong L, Yu C, Zhang Y and Cheng B (2020) Can forest city construction affect urban air quality? The evidence from the Beijing-Tianjin-Hebei urban agglomeration of china. J Clean Prod Yamineva Y, Liu Z (2019) Cleaning the air, protecting the climate: policy, legal and institutional nexus to reduce black carbon emissions in china. Environ Sci Policy 95:1–10

Greening by Self-organised Urban Farming: A Productive Paradigm for Urban Green Space in China Longfeng Wu

Abstract China is currently urbanising the largest agricultural population to turn areas of cultivatable land into the urban territory. This has led to many urban issues such as dense community, lack of food security, and limited access to green spaces. Chinese urban dwellers, especially the older generations who lived in rural areas, often deal with the problems in their ways by planting flowers, fruits, and vegetables on any possible grounds within their communities. Such bottom-up, dispersive, and non-institutional activity is defined as self-organised urban farming and is a common—yet overlooked phenomenon—in Chinese cities. The study assumes that urban farming will have great social and ecological potentials if properly guided by designers and will become a new paradigm for urban greening. By investigating Beijing’s self-organised urban farming activities, this chapter aims to provide regulatory recommendations and planning strategies to turn self-organised urban farming into a new urban greening paradigm that engenders more benefits. Three major questions were addressed: What is self-organised urban farming? Why can self-organised farming have the potential to be a productive greening approach? How could self-organised farming green the city by integrating it into current urban greening? Keywords Urban green space · Self-organised urban farming · Greenspace planning innovation · Beijing

1 Introduction As one of the largest agricultural countries in the world, China’s urbanization is accommodating millions of people from rural areas while turning massive areas of arable land into concrete territories. The majority of land acquired for urban expansion comes from flat, accessible farmland on the outskirts of core city areas. During 1990 and 2010, the trend of urban built-up areas in China expanded significantly and occupied more croplands (Wang et al. 2012). More than sixty percent of urbanised L. Wu (B) College of Urban and Environmental Sciences, Peking University, Beijing, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_7

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areas are transformed from farmland (Wang et al. 2012). Along with the rapid expansion of urban territory, industrialization drives many farmers to work and live in towns and cities (Pan 2015). As a result, the urban population surpassed the rural population in 2010 for the first time (National Bureau of Statistics of China 2011). However, the quality of urbanization is far behind the quantity of newly built urban areas. Lagging urban management and services cannot deal with the explosive emergence of complex urban issues. Critical issues include air pollution, densification, traffic, food security, and accessibility to various public services. Though decision-makers propose many solutions to these problems, some of the problems remain challenging. Urban residents, therefore, find their means for dealing with undesirable issues such as food safety as well as inadequate recreation in public green spaces. Urban farming is one of the most salient activities, especially in these areas where proper management lags during the process of urban expansion (Fig. 1). Urban farming is primarily bottom-up, self-organised by individual residents to make the use of untended areas through planting vegetables either for fun or food supply.

Fig. 1 Mapping the self-organised urban farming reported by on-line news across China (Source The Author)

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Unfortunately, China’s current regulations and planning of urban green spaces are largely in a top-down manner leaving little room for such self-organised urban farming. Most greening projects are invested and led by the public sectors regarding design, construction, and maintenance. Although top-down urban greening can effectively improve the overall volume of green space in cities, it limits diverse types of urban green space and local people’s participation in greening and the subsequent varying ecological and socioeconomic benefits. In this context, by investigating the self-organised urban farming activities in Beijing, this chapter explores how to integrate urban farming in current urban greening practice in terms of regulation, planning, and design, and discusses what benefits urban farming could bring to the city and society at large. This chapter is structured as follows: Sect. 2 addresses the current statuses of self-organised urban farming in China and the potentialities as a way of greening urban areas. Section 3 introduced presents urban greening activities and the challenges in study area— Beijing. Section 4 proposed potential revenues to integrate self-organised urban farming concerning national and local regulations, organizational frameworks, and potential locations. Section 5 envisioned three scenarios of how self-organised urban farming could be integrated into Beijing with detailed local examples.

2 Self-organised Urban Farming in China 2.1 What is Self-organised Urban farming? Self-organised urban farming in China is similar to practices found throughout the world, although it embodies unique characteristics in the context of recent Chinese urbanization. Self-organised urban farming can be considered a subcategory of urban agriculture, which is defined as the production of fruits and vegetables, raising livestock, and cultivating fish for local sale and consumption (Hodgson et al. 2011). In addition, the bottom-up nature of urban farming in China also has similar features of “guerilla gardening”, which is defined as unauthorised appropriation and cultivation of food-producing or ornamental plants on untended, abandoned, or vacant private or public land by an individual or group (Hodgson et al. 2011). Yet, in China, planting activities also happen on the planters’ land or collectively-owned land, such as green spaces in gated communities. In this case, farming is similar to a private garden that was popular in England and Wales (Kellett 1982). Self-organised urban farming in this research can be defined as a farming activity within the core area or periphery of a city by the residents to cultivate agricultural plants. These include fruit, vegetables, even crops in private, collectively owned, or less tendered public lands close to their communities without regulatory, organizational, or technique support. It is a bottom-up activity raised by the people by intervening in the existing urban pattern in various ways. Most self-organised urban farming is conducted by older generations who had been working on farmland for

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most of their lives, only moving into the cities in recent decades. The major purposes of these farming are for entertainment and food supply.

2.2 Why Are People Farming in the City? Import of agrarian techniques in the city As urban–rural migrant accounts for more than half of the new urban population since the 1990s (Chen and Song 2014), China’s urbanization is turning millions of rural villagers into urban dwellers and bringing agrarian techniques to the city in two ways. The first is by attracting migrant villagers from remote rural areas to work in the city. And the second way is urbanizing the local villagers by expanding urban territories into the periphery rural areas. More and more young rural residents choose to work in the city and invite their parents to live with them when they settle down. Megacities like Beijing, Shanghai, and Guangzhou are more attractive to the younger people because there are more work opportunities as well as better public services such as education, recreation, and medical care than the second or third-tier cities. Young generations often find that involvement in agricultural production yields less profit than working in the cities (Lu and Chen 2014). The gap between rural and urban salaries drives young people to seek jobs in cities (Zhao 2013). When younger couples find work and settle down in the city, they often invite their parents to live with them. As a part of Chinese tradition, families living together is still common today in most Chinese cities. The older generations spend most of their time helping take care of the young couples’ children so that they could devote more time to their work. These older generations are mostly villagers who have been living on farmland for most of their lives and only recently moved to the city. Agricultural activities such as planting crops, fruits, and vegetables composed a considerable part of their daily lives trained them to be experts in planting and growing crops. For those who live periphery of an expanding city, the villagers are turned to be urban residents during the expansion. While a city is expanding its footprint, it acquires space from the vast, flat, and easily accessible cropland (Huang, Du, & Castillo, 2019). Villages and the farmlands are reclaimed for urban development. The local residents would then move to subsidised housing in the urban areas as a replacement for their village homes. Those farmers similarly have been cultivating crops for their whole lives before relocating to the city area, which again increased the population that is well known about agrarian techniques in urban areas (see Figs. 2, 3, and 4). Lacking diverse green spaces The designs of green spaces in the city fail to predict the rapid change of demographical structure and hence cannot accommodate the diverse needs along with it. Particularly, in old communities, the original design and planning are no longer

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Fig. 2 City is expanding its footprints into the periphery rural areas, Zhengzhou East New Town Project. Source The Author

Fig. 3 The elderly hardly find many outdoor programs but sitting on the bench to enjoy the ornamental landscapes, Chengdu. Source The Author

suitable for today’s users. The unaccommodated designs of green spaces in the early communities are mostly less usable “window-dress” style with limited areas and programs (Miao 2011). Few proper green space programs could meet the diverse needs of urban citizens, typically the older people who constitute a large segment of the population recently. From affiliated green spaces in the residential community to public parks and plazas, it is hard to find many interactive programs that could allow the public’s involvement with the surrounding environment and nature.

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Fig. 4 Lagging urban management of green belts left many spaces for self-organised farming in peripheral Beijing. Source The Author

Lagging management of the urban public space By doubling the urbanisation rate in less than four decades, urban land use is expanding drastically, making the urban management sector incapable of looking after all the developing lands. Vast areas of untended lands left spaces for the people’s bottom-up intervention. In the fast-growing areas, typically in the periphery of large cities such as Beijing, the municipalities are not ready for the boom of the population and built infrastructures. The city’s expansion left some land uncapped or vacant temporarily to be developed in some time in the future. These lots sometimes have high potentials to be planted with crops by the residents nearby. Without regular maintaining and inspection, those spaces can easily be “intruded” by the people’s transforming activities for their purpose. Additionally, some green spaces covered by

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trees, shrubs, and grass for beautification are gradually out of quality without regular irrigation and pruning, which are not enjoyable for the urban residents. In extreme cases, the plants in the green belts are dying and turning gradually into wild spaces. The residents often find it is a waste of land resources and start to plant the space on their own.1 Concerning food safety The concern for food security is another motivation for people to farm in urban areas (Kozak 2015). Though both national and local governments struggle to maintain the food supply for the city, they are unable to maintain a stable supply throughout the year, which causes food price fluctuation as well as increased food safety incidents (Holtkamp et al. 2014). The inefficient food distribution system cannot establish accessible revenue for every resident, typically in a mega-city like Beijing. For instance, the vegetable supply for Beijing has been increasingly relying on the farms outside of its metropolitan region since 1990 (Guo et al. 2012). The external vegetable supply of Beijing from the hinterland constitutes more than eighty-five percent of the entire vegetable market.2 More than eighty percent of vegetable supply comes from the area within 600 km of Beijing core city. Long-distance transportation and intra-city distribution are subject to extreme events, including the above-mentioned seasonal flux of workers, bad weather, and so on. Moreover, the excessive use of pesticide spray and chemical fertilizers for maintaining productivity is less controlled, leaving the fruits and vegetables sold in the market unsafe. The problem of pesticide residues widely exists in China. It has become worse as farmers are using an everincreasing amount of pesticides and shortening the non-spray time before harvest to avoid infestations of insects from neighboring farms (Yan 2012), thus creating a vicious cycle of pesticide residuals to urban tables.

2.3 Potentials of the Self-organised Urban farming as Urban greening While the municipalities, in most cases, disallow self-organised urban farming typically in the public spaces, urban farming engenders multiple benefits to the residents. If properly guided, self-organised urban farming could contribute to the current urban greening in China in multiple ways. Self-organised urban farming embodies the following advantages and disadvantages that need to be considered in integrating into formal urban green space planning.

1 2

Interview with local residents in peripheral in Beijing, 2015. http://www.bjstats.gov.cn/, 2011.

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Advantages • Entertaining and exercising Self-organised urban farming serves as an interactive program designed and maintained by the residents. Residents, including both younger and older generations, find planting fruits and vegetables an exciting outdoor activity that produces fresh food and serves as physical exercise. “(Farming) is my interest. It is just for fun,” mentioned Mr. Zhang, a retiree, in Tsinghua University (Guo 2012). Planting as a hobby is common in small-scale farming in the intra-city area, typically for those retired people who have plenty of time to cultivate plants. • Community connection It is admitted that urban farming connects the community residents, few of whom have contacted each other (Meharg 2016). When one starts to cultivate the land outside and harvest food, it attracts the neighbors to talk with each other. Mr. Zhang’s farming activities on the private land in the residential community in Tsinghua University foster a connection between different residents (Guo 2012). By sharing crops and exchanging planting skills, the unfamiliar neighbors started to get together around the planted space. • Public education The educative function of farming involves plant recognition, experience farming, food harvesting, promoting food value, academic research, and field tests. Urban farming as an educational tool is associated more with academic facilities such as schools, universities, and research institutions. Some elementary schools start to farm on the rooftops or near campus to teach pupils agricultural knowledge in Beijing. For example, Shijia Hutong elementary school, located in the dense intra-city (Xi Cheng District), farms the rooftop to exhibit the changes of crops in the year. In the university, student groups, with the guidance of teachers, cultivate existing vacant spaces on campus. Such as the Beijing Forestry University’s rural support society (Ao Xiang She) plants vegetables to make use of an abandoned plot on campus. • Increase green volume The scalable and bottom-up farming fills vacant spaces with plenty of green areas from the rooftop to vacant land and the under space of overpass (Meharg 2016). Temporary farming activities on the transit land could take full use of the valuable urban spaces. Due to the lagging management in the urban expansion, some plots might be left unused and gradually turned to barren land, undermining the nearby community’s air quality. Allowing temporary cultivating of the space by the people is a low-cost strategy to cover the temporary vacant lots with greens. In addition, encouraging permanent planting green-leaf vegetables on the private spaces such as first-floor balcony, community-owned vacant spaces, and rooftops gain possible green in the dense city communities where adding green spaces is challenging in a format way.

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• Safe and fresh food supply Though the original purpose of farming is to provide food, self-organised farming is often limited in its scale and constrained by the environment. Food production becomes a subordinate outcome. However, in properly managed cases in large urban periphery areas, some experienced urban residents can grow organic fruits and vegetables. Urban farmers cultivate the food for themselves, and they would be cautious about the excessive use of chemical fertilizers or pesticides. Growing fruits and vegetables close to the community also decreases the “food miles” and promotes sustainability. • Increase diverse forms of green space Urban farming as an interactive green space provides participants an opportunity to know more about nature. On the contrary, the main purposes of formal urban green as beautification and ecological protection limit the interactive opportunities for the public. The main function of the current green spaces in Beijing is providing comfortable outdoor spaces for recreation and sightseeing. There is little revenue to allow people to interact with nature in the city. • Generating profits and lowering maintaining costs Traditional greening practice is largely dependent on the municipals, which invest the most and supervise the process of design, construction, and maintenance. The private sectors and the residents have less revenues to participate the urban greening. The municipal and national financial support could not sustain all the public green spaces, and many need to seek outside funding for maintenance. Poorly funded public parks have to develop profitable recreation programs, which inhibit the accessibility to the public to some degree. Urban farming, however, relies on participants to maintain the sites, who are often retired older residents working as volunteers and ultimately can reduce labor and maintaining cost. Disadvantages Self-organised farming is entirely depending on the residents’ skills and experience in farming. Without standardization and technical support, self-organised farming might misappropriate public properties, harm public health, pollute the environment and cost certain resources for cultivation. • Unauthorised occupation of public property When groups or individuals grow plants on public or community-owned lands such as collectively owned green space in a residential community or municipal/nationowned green belts, it is considered as unauthorised use of the public property. Even though some farming may not alter the original functions of the public space, gaining profit alone is unfair for those who are not engaged in farming. Self-farming often replaces the original functions of designed spaces that limit other potential usages without proper guidance and management. For instance, if individuals are farming in the garden of a residential community, they are occupying the public property that

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reduced useable common spaces. It is more often in the public spaces that have a poor property management. • Threats to the environment and public health The various sources for irrigating and fertilizing the crops in the urban context might include polluted materials that threaten the public’s health and harms the environment (Meharg 2016). Some “urban farmers” still adopt chemical fertilizers and pesticide sprays to keep their plants alive and more productive as villagers do in rural farmland. Without guidance of professionals, the sprays, typically in residential public green space, might harm the residents’ health. Excessive use of pesticides makes the vegetables unsafe for consumption as well. Another concern about pollution derives from the use of untreated wastewater or runoff water directly from urban drainage systems. Irrigated vegetables or fruits could absorb the contained heavy metals or chemical materials, harmful to our health. Plants close to busy motorways also take in pollutant emissions and remain in the edible parts. • Undesirable smell Those who use organic fertilizers such as waste meals are a sustainable approach to the farm since it helps improve productivity without bringing additional pollutants to the city. Yet, most of the homemade organic fertilizers are collected from dish waste or pet excretion without professional treatments. The untreated organic waste release unpleasant smells that are undesirable for the public. • Damage original building structures Urban farming also changes the physical environment of the buildings. Common cases indicate that if high arbors or dense plants are planted on the ground close to the first floor affects the daylighting condition of the upper-level units. Without professional inspection of the buildings, self-farming on the rooftop might not be suitable for the building. Even though the planting space might be physically suitable at first, long-term farming could damage the roof structure whose original design and construction did not consider specific conditions for farming. • High cost of irrigation Even though the urban farmers are encouraged to use wastewater such as gray water collected from vegetable wash to irrigate their plants, the main source of watering comes from tap water. In northern China, the water resource is constraint and costs much more than the well-watered south area. The self-organised urban farmers often lack water-saving irrigation equipment and methods to increase watering efficiency. • The danger of planting in movable containers on rooftops Urban farming in vessels for rooftop and balcony planting might be unsafe if not installed firmly in high-rise buildings. The containers for planting in many selforganised urban farming cases come from self-recycled vessels with no specific

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fixing measures when placed on the rooftops or open balconies. For the high-rise buildings, without enough fixation measures, the strong wind might blow off the planting vessels from the top threatening the safety of pedestrians.

3 Urban Greening in Beijing 3.1 Greening Efforts of Beijing Beijing has a long history of building green spaces for the residents. During the urban expansion, urban agriculture had been considered a component of greening. As a capital city of many dynasties, Beijing was left with several private, imperial, and temple gardens after the collapse of the Qing Dynasty in the early 1900s. Many such gardens and palaces were conserved for the high history values and opened to the public as major parks since the Republican era and continued at a greater scale in the new China after 1949 (Beijing Local Chronicles Compilation Committee 2000; Zhao 2008). Later, urban greening had a difficult time due to political upheavals and natural disasters in the early 1950s, during which greening mainly aims at improving quantity for environmental protection. Encouraged for a short period, urban agriculture was used as a supplementary component for urban green space during the 1960s, due to productive functions they bear in making public green spaces (Beijing Local Chronicles Compilation Committee 2000). After the open and reform policy in the late 1970s, the country started to recognise the multiple benefits of urban greening, which contributes to environmental protection and economic and aesthetic values, and public health (Beijing Local Chronicles Compilation Committee 2000). More diverse types of green spaces were proposed and built, such as wetlands, countryside parks, green boulevards, and commercial integrated green spaces (Beijing Municipal Institute of City Planning and Design 2007).

3.2 The Current Condition of Beijing Urban Green Resources and Problems Quantity and spatial distribution of the green spaces With a green coverage rate of 47.40%, Beijing is among the greenest cities in China regarding the quantity and quality of green space (Beijing Bureau of Statistics 2015). The spatial distribution of the green space is unbalanced: the outskirt of the city has more green spaces, but the inner city is less covered by green. In the outskirt of the city (out of 5th ring), dense forests cover the mountainous areas of western and northern Beijing, and the east and south is a vast plain area with a lower forest coverage rate. The inner city has numerous large historical heritage such as royal

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gardens and palaces, that serve as public green spaces with many newly built large modern urban parks such as the Olympic Forest Park. The infrastructure-affiliated green spaces connect the large patches of parks dispersed in the city. Problems of urban greening in Beijing • Green volume needs to increase After decades of endeavor, by the end of 2014, Beijing’s green coverage rate and greening rate have reached 47.40 and 45.34%, respectively, in the municipal region, which is among the most greened cities in China (Beijing Bureau of Statistics 2015). However, the greening rate per capita and park area per capita is 39.84 and 15.90 m2 , respectively (Beijing Bureau of Statistics 2015), which is still at the medium level among similar scale cities in the country. To reach a mandatory quantity of green space per capita, Beijing Gardening and Greening Bureau suggested “insert green in any possible spaces (见缝插绿Jian Feng Cha Lv). The strategy encourages the grassroots to adopt a possible piece of vacant space to plant greens. • Uneven distribution and limited accessibility to the public While the Beijing government has been struggling to increase the green volume in recent decades, the quality and quantity of green space remain unsatisfied considering the increasing population and the changing needs of the public. The uneven spatial distribution inhibits the accessibility of public green spaces. Because the greens concentrate in some parts of the city in the form of huge parks such as Olympic Forest Park, with an area of more than 1200 ha, such concentration spatially inhibits the accessibility to the public. Some have to walk several kilometers to get to the public park since it is the closest park to their community. The municipal is still striving to build enough spaces to allow all citizens to “visit greens within 500 m from their community (Beijing Municipal Institute of City Planning and Design 2007). Another issue of uneven distribution is related to the residential communities and institutions affiliated with green spaces owned by and opened only to the residents who live inside. The green space in residential communities typically those highend communities do not allow outside people to use these green spaces contributing to the uneven availability of the green space. It is common to see the public green spaces such as parks are full of visitors, but large areas of green spaces in the luxury residential communities are less used. • Limited participatory opportunity Most urban green spaces are more for aesthetic and ecological functions than interacting with nature, as mentioned. Even though the Beijing Municipal has established projects such as “Voluntary Tree Planting (首都全民义务植树)” to encourage the public to participate in tree planting activities, the forms of activity could be more inclusive and diverse regarding the cost and interactivity. Current tree planting or “adopting a tree” programs require residents or units to cover the entire cost of tree planting and management, which might harm the motivation of activities. Some

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farmlands in Beijing start to offer rentable land slots to allow the urban residents to experience farming and produce fresh food. However, they are mostly located in the outskirt of the city, and long transportation makes the most adoption difficult for those who live in the inner city. • Relying on costly ornamental plants The ecological protection and aesthetical functions of present green spaces require professional operations as well as numerous resources to maintain. For instance, the “Million Mu3 forestation” project to reforest the south and east plain reclaimed the croplands to plant green vegetation, which needs a lot of investment from the municipals. The reclaiming process also leads to many villagers’ unemployment. • Constraints on-site design Urban planners and landscape architects are constrained to make more diverse land use and design solutions since they need to follow national and local regulations related to the design practice. Professionals involved in the urban greening practice have limited chances to provide design solutions to include interactive landscapes that can integrate self-organised farming in the urban greening practice. Due to the blockage of urban agriculture in urban development, planners have no legal support to take into account urban agriculture when drafting city plans. At a design scale, though some landscape architects could allow agriculture as landscape design elements when making a park or a piece of green space, the cases are too rare to be influential at the city level.

4 Where to Intervene: Regulations, Players, and Spaces To integrate self-organised urban farming into current urban greening, a series of modifications are needed with regards to planning laws and regulations, organizational framework, and current plans and land use. This section identified three potential aspects that are critical for introduction and guidance for self-organised urban farming as follow: • Release regulation barrier: modify possible regulations associated with urban greening to allow and encourage farming in the urban area. • Participatory organizational framework: recommend organizational framework of urban greening to include self-organised urban farming. • Find the space to integrate: combine urban farming in the current urban greening plan and project.

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Chinese area unit: 1 Mu equals to 0.06667 hectare.

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4.1 Regulations Associated with Urban Greening Though self-organised urban farming is becoming an increasingly common phenomenon citywide, it still catches less attention from the decision-makers. Current policies and regulations remain “blank” in dealing with the public’s passion for farming the ground. A review of existing national and local regulations on urban farming indicates that there are few related to the role of urban farming exclusively. The regulations should first recognise and define urban agriculture as a form of urban green space to include the urban agricultural land use in the urban development land classification system. Upon the revised definition, the local regulations have legal support to include urban farming in the city planning and related code for the design and construction. National regulation The procedure to modify some of the national laws and regulations are complex and effort-consuming. At the national level, introducing urban farming is recommended but not urgent. Some of the recently modified regulations might not change again in a short period. But, the government could consider the recommendation to pay attention to the benefits of urban farming in the long run. The following are related to national regulations that can be modified for integrating urban farming with current urban greening. First, Regulations on Urban Landscaping (城市绿化条例) (State Council of the PRC, 2017) needs specific articles on how to identify the green space and to allow the introduction of urban agriculture to the existing urban green space classification. With the residents’ increasing passion for farming, the regulation should not neglect the trend but encourage proper guidance and policies. To integrate selforganised urban farming in the city, the Code for Classification of Urban Land Use and Planning Standards of Development Land GB50137-2011 (城市用地分类与规 划建设用地标准GB50137-2011) (Ministry of Housing and Urban–Rural Development 2012) needs to define urban farming and to allow urban farming as a landuse of the city. In addition, the current Standard for Classification of Urban Green Space CJJ/T 85—2002 (城市绿地分类标准CJJ/T 85—2002)” (Ministry of Housing and Urban–Rural Development 2017) should define urban farming and include it into the green space land classification. Although the classification system includes productive green space, its function is to nurse plant seedlings. The Code for Design of Urban Green Space (城市绿地设计规范GB 50,420— 2007) (Ministry of Housing and Urban–Rural Development 2007) and the Code for Design of Parks (公园设计规范CJJ48—1992)” (Ministry of Housing and Urban– Rural Development 2016) could define the urban farmland as a green space and provide detailed design regulations. The Code for Planting Planning and Design on Urban Road (城市道路绿化规划与设计规范 CJJ75—1997) (Ministry of Housing and Urban–Rural Development 1997) could allow using the agricultural plants for roadside greening and portable planting beds for pedestrian greening with code specifications. The Plant Materials for Urban Green Space—Tree Seedlings (城市绿化

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和园林绿地用植物材料木本苗CJ/T 24—1999)” (Ministry of Housing and Urban– Rural Development 1999) does not consider the agricultural materials as greening plants. Some urban greening plants are domesticated from agricultural plants that are used to produce food or herbs. The list of urban greening could be updated to recognise the greening effect of some agricultural plants as well as additional values they might provide when adopted properly for urban farming. Local regulation Upon the modified national regulation, the local municipalities could add encouraging articles or policies to foster the development of urban farming based on local conditions. As a basic regulation on the urban greening practice, the Regulations of Beijing Municipality on Greening (北京市城市绿化条例 2009) (Beijing Gardening and Greening Bureau, 2010) need to include the urban farming that plants vegetables, fruits, and other edible vegetations for production as well as supportive nursery facilities in the urban green space. The regulations should encourage establishing supporting infrastructures that promote urban farming development. The Regulations of Beijing Municipality on Park (北京公园条例2002)” (Capital Greening Office 2002) again needs to define the edible landscapes as a subcategory of the park so that landscape designers could have more design options. The codes for design and planning are recommended to set the technical norms to standardise self-organised farming. For example, “ Code for Roof Greening (北京屋 顶绿化规范 2005)” (Beijing Gardening and Greening Bureau, 2005) could include the urban farming on the rooftop by providing reference and guidance. The Code for Planting Planning and Design on Attached Green Space in Beijing 2014 (北京城市 附属绿地设计规范 2014)” (Beijing Gardening and Greening Bureau, 2014a) needs to include the edible plants as a component of green belts or sidewalk greens when the conditions allow modified agricultural plants. “Specification for Maintenance and Management of Urban Green Space in Beijing (北京城镇绿地养护管理规范 2014)” (Beijing Gardening and Greening Bureau 2014b) also should include sections addressing how to maintain and manage the urban farming.

4.2 Potential Players of Promoting Urban farming The integration of self-organised urban farming requires a joint effort of the public sectors as well as individuals and groups that used to farm informally. The governance basis shall include both the top-down and bottom-up approaches to motivate public and private resources. Based on the recommended update of current urban green management regulation—the Regulations of Beijing Municipality on Greening (北 京市城市绿化条例 2009) (Beijing Gardening and Greening Bureau 2010), the urban farming space could be potentially categorised into three operational types per land ownership. The first is municipality-owned urban farming, the second is communityowned space for urban farming, and the third type is private-owned urban farming.

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The owners of land should act as a leader for promoting urban farming through facilitating participants, instructional/technical supports, and planting resources. The instructional and technological supports could come from public institutions, non-profit organizations, and private companies of the urban farming industry. Academic and research institutions such as universities that focus on gardening, landscape architecture, forestry, agriculture, and horticulture fields can help educate and organise the potential urban farming activities and provide planting techniques. Non-profit volunteer groups for the public service could also educate and instruct the public and help organise urban farming. Private companies that promote urban farming, such as “Xiao Mao Lv Urban Farm”, could sell or rent necessary resources such as seedlings, fertilizers, farming tools, and instructions to the urban farmers. The traditional seedlings might include urban farming-related services to offer basic materials for farming. Public facilitated urban farming Beijing Municipal and Beijing Gardening and Greening Bureau are responsible for the management of public urban green space to establish the revenue for residents and nonprofit organizations to involve in urban farming in the public green space and provide them with sources of technological support. For instance, the public parks or green belts maintained by the municipal sectors could rent the residents part of the green spaces to grow edible vegetables. With proper design and farming guidance, the edible landscape could not only retain the aesthetic value but also increase productivity. Nearby urban residents’ involvement could reduce the labor cost exclusively for maintaining the green space. Community facilitated urban farming The forms of community-led urban farming vary according to different community types. In general, the community is more than residential and includes commercial and business sectors, schools, research, and academic institutions. They could help form sub-organizations such as student groups, residential committees for community farming, and volunteer research teams to support farming activities in the attached green spaces. Private facilitated urban farming Private-owned urban farming is providing both on-site service and fresh products for the locals. On-site service includes the forms of agro-tourism, which is the most common urban farming practice nowadays. The urban farm for production involves small or middle-scale urban farms at the community level in the peri-urban region. Current private-owned urban farming is located in the outskirt of the core cities. It is also possible to develop small-scale farming hubs to foster urban farming in the city center with more instructional and material supports.

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4.3 Potential Spaces to Integrate Self-organised Urban farming Current Beijing city plans have many possible opportunities to integrate urban farming in contemporary greening. At the city plan level, targeting to build an “Ecologically Greened City”, the most Beijing green system plan tends to increase the green volume in any possible spaces the citywide (Beijing Municipal Institute of City Planning and Design 2007). Suppose urban farming is considered as part of urban green space. In that case, it might be accepted and allowed to exist in certain conditions to increase the overall volume and the diversity of green spaces. Article 24 of the Beijing Urban Green System Plan (2004–2020) depicts the urban green layout to be built before 2020. The space for the urban green system in the city region could derive from renovated communities, factory relocation (brownfields), affiliated green for public buildings, and peripheral farmlands (Beijing Municipal Institute of City Planning and Design 2007). Urban farming could be part of the expanded green spaces such as attached residential communities, institution-affiliated spaces, special parks, and roadside greening. During the urban renewal, many vacant spaces and brownfields could invite urban farming as a resource-reducing approach for greening. The large existing farmland for afforestation projects needs not to turn to aesthetic green space or protective buffer but can leave spaces for urban farming.

5 Three Scenarios to Integrate Self-organised Urban farming into Urban Greening 5.1 Infrastructure Affiliated Green Spaces Infrastructural-affiliated green spaces include green belts for highways, railroads, airports, and rivers. The green belts are either regulated by the administrative units who are in charge of maintaining the infrastructures or by the Beijing Gardening and Greening Bureau. The main function of these green spaces is environmental protection serving as a buffer around infrastructures (Fig. 5). Regulatory and organization basis For the infrastructure unit-owned green belts, current national and local regulations have no specific definition of the forms of green spaces, and administrations who own the infrastructures are responsible for the greening according to the related codes. As the Code for Planting Planning and Design on Urban Road (城市道路 绿化规划与设计规范 CJJ75-1997)” defined in article 4.3.1: “The green belts of the road could design according to the adjacent land use, protection, and landscape demand. The landscape design should follow the consistency and integrity along the road (Ministry of Housing and Urban–Rural Development 1997)”. Suppose the

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Fig. 5 Green buffers of the highway in Beijing. Source The Author

green belts are wide enough to be sufficient to plant part of protective vegetation for the entire space. In that case, productive vegetations could be introduced to mind the left spaces in the form of farmable areas. However, given the limited area of some green buffers for infrastructure-owned green belts, most spaces are covered with dense protective vegetation. In a few cases, when the green belts are wider than eight meters, as the Code for Planting Planning and Design on Urban Road (城市道 路绿化规划与设计规范 CJJ75-1997) illustrates, the green belt could be open green space accessible to the people. Such design has a higher potential to be developed into cultivatable spaces (Ministry of Housing and Urban–Rural Development 1997). For the protective green spaces between the infrastructures, the responsible administration is the Beijing Gardening and Greening Bureau, which initiated many key projects to increase the green volumes in the periphery of infrastructures. They are heavily vegetated areas along key roads and rivers, most of which were existing agricultural lands. The large size of these afforestation projects have more rooms and potentials for integrating urban farming. For instance, the “Million Mu Forestation Project on Plain Area of Beijing (北京平原地区百万亩造林工程)” demands: “The key greening projects include greening outskirt area and aviation corridors of Capital International Airport. The green belts of key corridors such as the Beijing-Shanghai Highway, Yong Ding River shall be enhanced to build a largescale ecological network of forest in the region. The purpose is to create a wind corridor, increase biodiversity, and reducing heat island effect in the city (Beijing Gardening and Greening Bureau, 2012b)”. Following codes, such as the “Code for key green corridor construction 2012 (重点绿色通道建设工程技术规范 2012)”, describe specific guidelines to enhance the green areas as: “the key green corridor includes adding and increasing the green volume along both sides of main rivers, trunk road, and railroad. A thousand meters of the outer flank and five hundred meters

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of the inner flank of Sixth Ring Road shall be forested. No less than two hundred meters shall be on both sides of other roads, rivers, and railroad (Beijing Gardening and Greening Bureau 2012a)”. The most financial investment for infrastructure-affiliated green space comes from the public sector, including National Government, Beijing Municipal, and County or District Government. The funding distributes to the relative departments, for instance, Beijing Gardening and Greening Bureau funds for public green space construction management, whilst infrastructural administrations, such as Beijing Water Authority, are responsible for different kinds of infrastructure-affiliated green spaces attached to rivers or lakes. Various landscape design and planning companies are hired to design green spaces. After the design phase, professional construction teams and management groups are necessary to keep the vegetation alive and thrive. Based on the original green space practice, self-organised urban farming could fit into the design and maintenance phases. Upon the agreement of Beijing Gardening and Greening Bureau as well as related administrative sectors, landscape design and planning company could propose urban farming as a component of the site design and rent the arable land to the relocated farmers who serve as a construction and maintaining group with the supervision of professional teams (Figs. 6 and 7). Potential sites to integrate self-organised urban farming Both the municipal-owned green buffer and infrastructure-affiliated green spaces have the potential to integrate self-organised urban farming. More preferably, selected sites need to be located in the lower dense urban environment at the peripheral

Fig. 6 Organization framework to integrate urban farming in municipal buffer green spaces managed by Beijing Gardening and Greening Bureau (the green shaded text indicates the integration of self-organised urban farming, the yellow shaded text is for current urban greening, similarly hereinafter in Figs. 7, 8, 9, 10, 11, 12, 13 and 14)

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Fig. 7 Organization framework to integrate urban farming in the infrastructure-owned green buffers

Fig. 8 Post-even land use in Garden Expo, Fengtai District, Beijing. Source The Author

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Fig. 9 The organizational framework of integrating urban farming with post-event site, the Beijing Garden EXPO Park as an example

Fig. 10 The organizational framework of integrating urban farming with vacant land

or have a minimum width of eight meters to integrate urban farming effectively. The main target of a large-scale municipality-led greening plan is to preserve the regional environment and provide recreational spaces for the residents. Certain green agricultural vegetation can preserve the ecological environment as the mere forest does. The current landscape typology of the agricultural areas to be forested between infrastructures can support farming activities. The urban territory gradually extends

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Fig. 11 Nursery in Beijing. Source The Author

Fig. 12 The organizational framework of integrating urban farming with a nursery

Fig. 13 From left to right: residential community green space, business center green space, and university campus green space in Beijing. Source The Author

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Fig. 14 The process of integrating urban farming in residential community affiliated space

into the periphery of Beijing that used to be farmland. Turning the farmland into an artificial forest needs to change the entire landscape, but introducing urban farming takes advantage of the existing configurations of the farmland. On the contrary, cultivated forest upon the farmland requires a large investment of seedling cultivation and subsequent plant and maintenance. In addition, the greening projects’ reclaiming of the croplands in the periphery of Beijing also lead to the unemployment of local farmers. Self-organised urban farming can provide employment opportunities for the local farmers and reduce the financial burden for the municipality. Similar activities were conducted for forestation projects that hired displaced farmers but only in the afforestation works (Li 1997).

5.2 Transitional Land Use Transitional land use refers to the sites that serve as temporal functions and could be developed for new uses in the future. Among the transitional land use, the post-event land, temporary vacant land, and productive green spaces are most suitable to be associated with self-organised urban farming. Regulation and organization basis Though there is no specific regulation to guide the usages of the transitional land during the urban expansion, many relative ones encourage planting trees or other greening activities to decrease the barren lands in the city. For instance, the “Volunteer tree planting” by “Resolution on launching national voluntary tree-planting (关于

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开展全民义务植树运动的决议 2012)” states that “every liable person should plant two to five trees each year… Consider the complexity of planting and the different planting conditions between urban and rural areas… Alternative greening tasks are acceptable as well…”. For the sites hosting temporary events, some local regulations encourage adopting productive urban agriculture to release heavy costs for vegetation maintenance. For instance, Beijing Fengtai District Government suggests the post-event utilization of the Beijing Garden EXPO that: “…taking advantage of the green space to develop herb garden… The plants could not only sell to the Chinese herbal medicine company but also have ornamental values…the large area of water body in the site can support aquacultural production to decrease the maintaining fee of the ornamental garden…”. The introduction of urban farming in those transitional land uses needs approvals from the property owners as well as related administrative units. In this process, the government must play a role in facilitating the transformation by adopting specific regulations and policies to encourage urban farming as a tool to increase green volume and diversity. Upon the agreements, the landscape design and planning sectors redesign the site to be further developed. Urban farming is often combined with additional industries and activities other than merely producing food.

5.3 Potential Sites to Integrate Self-organised Urban Farming Post-event land use Many national and international events, such as the 2008 Olympic, Beijing Garden Exhibition, need exclusive land use for the event activities. Though the event sites often host a large number of visitors and gain sufficient income to sustain the operation cost, municipal funding is the main source after the event, given the decreased number of visitors after the event. In most cases, the sites have to shut down some sections or seek financial support from external sources. One approach is inviting profitable activities based on the current infrastructure of the site. Introducing selforganised urban farming has a high possibility to integrate the garden or agriculturerelated event sites whose original infrastructures are suitable for the farming activity. One example is the Beijing Garden EXPO4 hosted in 2013. The garden is designed to exhibit gardening art, cultural landscape, ecological and sustainable technologies. Constituted by a large water space and various small gardens, the site turns to be a new public park in the southwest of Beijing after the event. However, the ornamental gardens and ancillary facilities depend entirely on municipal funding to maintain. The huge financial burden forces garden to seek outside funding or more profits to reduce the maintenance cost. 4

Beijing Garden Expo Park is located at the west bank of Yongding River, Fengtai District, and occupies an area of 513 hectares. It is a large city garden integrating garden art, cultural landscape, ecological recreation, and science popularization education.

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The urban farming that yields higher profit than traditional production-oriented farming is suitable given the similar spatial configurations and sustaining infrastructures of the garden that demands little alteration. The recommended transformation of the garden to a productive urban farming space includes three approaches: Chinese herbal planting for sightseeing and production, edible gardens associated with on-site restaurants, and synthetic farming based on the large pond area (Fig. 9). Targeting the function of production and decoration, Chinese herbal planting could take advantage of the park’s original design. Herbals with both high economic and ornamental values could replace the resource-cost plants merely for aesthetic value. Grown herbals could also sell to the medicine companies and reduce the maintenance cost. The edible landscape is proposed in the garden space of Beijing EXPO to replace the inaccessible yet decorative landscapes. The edible gardens remain the ornamental value and could bear additional social benefits such as recreation, education, and production. It could either be picking a garden for visitors, serving fresh food for the garden restaurants, or rentable land slots for the nearby residents. The maintaining works are still responsible for the professional teams who used to look after the gardens. When the residents rent plots for regular farming, the professional teams would serve as technical support to teach farming skills and provide necessary resources and tools. The profits of edible gardens could reduce maintenance costs. Multiple urban farming activities can be combined into synthetic farming, in which the waste of one product could fuel the other to form a sustainable production circle. The Beijing Garden EXPO Park has large areas of both water and ground, which provide spacious areas for synthetic farming. The introduction of aquaculture crops in the pond combines with plants on the gardens as synthetic agriculture to boost the productivity and sustainability of the site, which also presents a high educational function. Temporary Vacant Land With the rapid urban expansion, Beijing is leaving many temporary lands and often out of proper care. The residents often fill in the vacant spaces with vegetables. As being introduced, self-organised farming in such vacant land is illegal and should be removed. But leaving the vacant land unused is a waste of resources, and temporary urban farming could increase the productivity of the land by inviting nearby residents to reclaim the empty spaces before the land is being developed. With the approval of landowners and related administrative departments, the landscape designers could provide selected plants suitable for temporary urban farming. The nearby residents are main farming participants who could apply to rent and produce fresh food and provide green space. In the process, the government needs to adopt specific policies to encourage such greening activities (Fig. 10). For instance, the landowners who leave land uncovered shall be responsible for providing farming and greening methods and maintenance.

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Productive Green Space The productive green space serves as a plant nursery providing seedlings for urban greening (Fig. 11). However, the demand for seedlings will gradually decrease when Beijing urban greening achieves a higher amount. The nursery greens might seek alternative development rather than keep producing seedlings for the local greening. It is highly possible to include urban agriculture as a productive green space in nursery land use. Since the nursing infrastructures, spatial configurations, and environmental conditions are suitable for agricultural vegetation and farming activity. During the integration process, the nursery owner and relevant municipal department shall lead the renovation of the site to involve urban farming through turning the site into a picking garden or rented urban farming lots for residents (Fig. 12). The new integrated urban farming in the nursery can provide both economic outcomes (e.g., producing plants and services for urban agriculture) and recreation function.

6 Community Affiliate Space The community-affiliated green space is the attached green areas of the residential community, business and commercial center, and university campuses. The community owns and manages the green spaces with the guidance of professional groups as well as other related municipal departments concerning green management. Having more complicated spatial and organizational conditions than the periphery or intracity large-scale urban farming, the function of community-based farming is less than production and stresses more on the social benefits to the community and the public. Regulation and organization basis The regulation on greening gives more autonomy to the community to manage the community-owned property, including the green spaces. The Regulations of Beijing Municipality on Greening requires that “Grassroots mass organizations of self-government and schools shall, by taking into account their situations, educate residents as well as students and teachers to perform the obligation of greening, protect the achievements of greening and bring success to the greening work within their communities and their institutions” (Beijing Gardening and Greening Bureau 2010). The government also encourages any forms of greening achievements. The municipality shall acknowledge and reward institutions and individuals with prominent achievements in greening work (Beijing Gardening and Greening Bureau 2010). Many local plans also echo the government’s guidelines to motivate all kinds of greening practice such as the Beijing Municipal Institute of Urban Planning and Design proposed in 2006: “In 2010, green all the possible rooftops in Beijing… (Beijing Municipal Institute of City Planning and Design 2007).” Even though the regulations associated with urban greening do not specifically illustrate how farming could be adopted in the urban setting, the community could manage the use of green space independently, collaborating with professional teams

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and various municipal administrations. Plenty of potential farming participants and social agencies could help facilitate the introduction of urban farming into the community.

6.1 Potential Sites to Integrate Self-organised Urban farming Residential affiliated space The residential attached spaces have the largest group of potential participants in farming. Indeed, most self-organised urban farming observed during the field trip is happening in residential communities in Beijing. However, not all residential communities are suitable to introduce urban farming. According to a survey, self-organised urban farming is more frequent in low-rise and middle-rise multi-floor residential communities in Beijing (Xiao 2014). The high-rise blocks are too dense in terms of the population to adopt urban farming. Considering the property owners in residential communities are more complicated than others, there are two general spaces to integrate urban farming into private and public spaces. The private lands include the courtyard and affiliated private yard of first-floor residents and the rooftop owned by the top-floor residents. The public space is owned by all the community collectively, including the public open space, roads, and plazas. The physical environment needs inspection first to confirm whether space is physically feasible for farming in the private space. If the environment is viable, two-thirds of residents in the community or residential buildings have to agree to conduct the farming. When the majority agree, and the environment is available for farming, the private space owners could invite landscape designers to offer planting solutions as well as operating instructions. The owner could either farm themselves or rent the space to the resident who would like to farm.5 The farming on the private land is responsible by the owners who could select the plants and productions themselves, which makes the private farming highly customised. The farming type is recommended to use container planting for a small number of green vegetables. For the public spaces, the ownership belongs to all residents in the community, and property management teams employed are responsible for maintenance. If the public space is to be farmed, two-thirds of residents have to reach an agreement. The planting solutions provided by landscape design need approval from related municipal administrations. The property management committee consisting of resident representatives, landowner representatives, and community committee representatives could organise the cultivation of public open spaces regarding types, techniques, and participation of urban farming with the consultation of professional management teams and landscape designers. The type of planting method could be either 5

It is only feasible for the rooftop spaces since the first floor yard is often not physically open the public.

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container planting for temporary occupation, soil planting for long-term farming, and even planting on pavilions. Commercial and business community affiliated space The commercial and business community-affiliated green space are owned collectively by the community users. The process of integrating urban farming is similar to the collective public space in residential communities. Changing green space or greening the vacant public space needs approvals from the property owners and management department. The landscape designers could find proper spaces and plant solutions to integrate urban farming. If the residents have time and energy, they could participate the farming. Otherwise, the property management groups help to cultivate the plants. Restaurants, typically the high-end ones in which the affiliated spaces are sufficient for greening, are recommended to adopt urban gardening to provide local food as a special service to the menu. In most cases, the space of growing is not able to engender enough production to fulfill the restaurants’ need for food. Therefore, the main purpose of introducing urban gardening to the restaurant is recreation and advertisement rather than food production. Business districts often have high-quality urban green spaces and are well maintained, but the usability of such spaces is low. The decorative spaces have great potential to be redeveloped into edible landscapes so that the space’s productivity and usability increase. There are mainly two strategies to integrate urban farming into the business center district. One is to turn the original green spaces into semifarmland by embedding agricultural plants into existing green spaces. The other is to replace the original greening species with agricultural plants. Both temporary and long-term farming are applicable. Edible plants could also increase the green volume by filling into spaces such as rooftop and pavement areas temporarily or permanently. The high mixed groups, including professional management teams and staff working in the district, would allow diverse participating models. Those who are working in the district could choose to participate in farming with support from the professional property management team. The property management team can also be fully responsible for maintaining the farming and provide fresh food to the employment restaurant. The purpose of farming in the business center district is multiple. The integrated urban farmland as a green space could produce fresh food for the local staff. The staff working in the center could take part in the farming activity as recreation by “signing up” their slots. Academic and research institution affiliated space Academic and research institutions, typically in agriculture-related institutions, often have more professionals who possess knowledge and skills in agriculture. The organization also has a higher possibility to integrate urban farming. Since the open spaces are owned and managed by the institutions, they could introduce urban farming upon approval by the municipal administrations. The green spaces on campus used for farming spaces are recommended in universities with professions such as landscape architecture, agriculture-related majors,

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and gardening. The function of urban farming in the university campus is to focus on academic use. Though it is common for the university to develop pieces of green space for outdoor arboretum experiments, few cases use green space for a productive or edible landscape. The small, cultivated farmland serves as experiencing space to teach students about farming and vegetables. Experiment-based courses require outdoor spaces for students to do botany experiments. Integrating urban farming on-campus needs approval from the school management groups. The organization to facilitate farming on campus involves various student groups with the professional guidance of faculties in the related field and staff responsible for the technical and material support. The students in the major of landscape architecture can even design and plant on their own.

References Beijing Bureau of Statistics (2015) Beijing Statistical Yearbook 2015. In (pp. 574). Beijing, China: China Statistical Press Beijing Gardening and Greening Bureau (2005) Code for Roof Greening. In. Beijing Beijing Gardening and Greening Bureau (2010) Regulations of Beijing municipality on greening. Beijing Beijing Gardening and Greening Bureau (2012a) Code for key green corridor construction. In. Beijing Beijing Gardening and Greening Bureau (2012b) Million Mu forestation project on plain area of Beijing. Beijing Beijing Gardening and Greening Bureau (2014a) Code for planting planning and design on attached green space. In (pp. 21). Beijing Beijing Gardening and Greening Bureau (2014b) Specification for maintenance and management of urban green space In (pp 26). Beijing Beijing Local Chronicles Compilation Committee (2000) Beijing annals. Municipal administration volume. Garden greening annals (1st Edition ed. Vol. 49). Beijing: Beijing Press Beijing Municipal Institute of City Planning and Design (2007) Beijing Green Space System Planning (2004–2020). In. Beijing, China: Beijing Municipal Institute of City Planning and Design Capital Greening Office (2002) Regulations of Beijing Municipality on Park. 10 Chen Q, Song Z (2014) Accounting for China’s urbanization. China Econ Rev 30:485–494. https:// doi.org/10.1016/j.chieco.2014.07.005 Guo H, Cai J, Wang D (2012) Analysis of tempo-spatial patterns of beijing external vegetable supply and its effects under massive logistical system. Econ Geogr 32(3):96–101 Guo S (2012) Study of urban farming space. Master dissertation Hodgson K, Campbell MC, Bailkey M (2011) Urban agriculture: growing healthy, sustainable places. American Planning Association Holtkamp N, Liu P, McGuire W (2014) Regional patterns of food safety in China: What can we learn from media data? China Econ Rev 30:459–468. https://doi.org/10.1016/j.chieco.2014.07.003 Huang Z, Du X, Castillo CSZ (2019) How does urbanization affect farmland protection? Evidence from China. Resour Conserv Recycl 145:139–147. https://doi.org/10.1016/j.resconrec.2018. 12.023 Kellett JE (1982) The private garden in England and Wales. Landscape Plan 9(2):105–123. https:// doi.org/10.1016/0304-3924(82)90002-8

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Kozak AE (2015) Envisioning a self-sustaining city: the practice and paradigm of urban farming in Shanghai. University of Colorado Denver Li M (1997) Development of green space in Beijing. Ekistics 64(385–387):255–261 Lu M, Chen Z (2014) Urbanization, urban-biased policies, and urban-rural inequality in China, 1987–2001. Chin Econ 39(3):42–63. https://doi.org/10.2753/ces1097-1475390304 Meharg AA (2016) Perspective: city farming needs monitoring. Nature 531(7594):S60–S60. https:// doi.org/10.1038/531S60a Miao P (2011) Brave new city: three problems in Chinese urban public space since the 1980s. J Urban Des 16(2):179–207. https://doi.org/10.1080/13574809.2011.548980 Ministry of Housing and Urban-Rural Development (1997) Code for planting planning and design on urban road. In (Vol. CJJ 75—97, pp. 16). Beijing Ministry of Housing and Urban-Rural Development (1999) Plant materials for urban green space— Tree seedlings. In (Vol. CJ/T 24—1999, pp. 12). Beijing Ministry of Housing and Urban-Rural Development (2007) Code for design of urban green space In (Vol. GB 50420—2007, pp 42) Ministry of Housing and Urban-Rural Development (2012) Code for classification of urban land use and planning standards of development land. In (pp 75). Beijing Ministry of Housing and Urban-Rural Development (2016) Code for design of Parks. In. Beijing Ministry of Housing and Urban-Rural Development (2017) Standard for Classification of Urban Green Space. In (pp 13). Beijing National Bureau of Statistics of China (2011) China city statistical yearbook. In: China Statistics Press Beijing Pan J (2015) Overall strategy for promoting the citizenization of rural migrant workers. In Annual Report on Urban Development of China 2013 (pp 1–46) State Council of the PRC (2017) Regulations on Urban Landscaping (2017 Revision). In. Beijing Wang L, Li C, Ying Q, Cheng X, Wang X, Li X, … Gong P (2012) China’s urban expansion from 1990 to 2010 determined with satellite remote sensing. Chinese Sci Bull 57(22):2802– 2812.https://doi.org/10.1007/s11434-012-5235-7 Xiao B (2014) A survey of self-planting activities in urban centers: implications for planning and design. (Master ), Peking University Yan Y (2012) Food safety and social risk in contemporary China. J Asian Stud 71(3):705–729. https://doi.org/10.1017/s0021911812000678 Zhao J (2008) Thirty years of landscape design in China (1949–1979): the era of Mao Zedong. In: University of Sheffield Zhao P (2013) Too complex to be managed? New trends in peri-urbanisation and its planning in Beijing. Cities 30:68–76. https://doi.org/10.1016/j.cities.2011.12.008

Changes of Urban Greenspace Coverage and Exposure in China Bin Chen and Yimeng Song

Abstract Urban greenspace, as an essential component of green infrastructure, is particularly important in the urban environment that maintains the function and sustainability of urbanities. With the rapid economic growth over recent decades, China has been experiencing unprecedented urbanisation processes, at the same time, led to dramatic changes in urban land use and living environment. Therefore, understanding the spatiotemporal changes of urban greenspace coverage and how they impact on population’s exposure to urban greenspace is a critical requirement for supporting urban planning and healthy city development. Although a number of studies have attempted to evaluate urban greenspace changes in China, a comprehensive and multidimensional assessment of urban greenspace coverage and exposure is still lacking. Meanwhile, the emerging geospatial big data provides unique opportunities to quantify the interaction between human activities and the green environment, which has been limitedly addressed. In this chapter, we retrospect some of our recent works on leveraging multi-source remote sensing and social big data to estimate the dynamics of greenspace coverage and exposure change for Chinese large cities. The expected findings will advance our understanding of the following questions in a more systematic way: (1) What is the spatiotemporal pattern of greenspace changes over the past two decades? (2) What is the temporal dynamic and heterogeneity in greenspace exposure? (3) How does urban expansion impact on greenspace exposure experience? (4) Are there any inequalities in greenspace exposure among Chinese cities? Keywords Greenspace change · Urbanisation · Dynamic exposure · Remote sensing · Social sensing · Inequality B. Chen (B) Division of Landscape Architecture, Faculty of Architecture, University of Hong Kong, Hong Kong SAR, China e-mail: [email protected] Y. Song Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China Smart Cities Research Institute, The Hong Kong Polytechnic University, Hong Kong SAR, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_8

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1 Introduction Urban greenspace, typically including open and undeveloped land with natural vegetation, such as parks, gardens, street plantation, lawns, crops, and forests in urban contexts (Mitchell and Popham 2008), is critically important to the function and sustainability of urban environments (Benton-Short et al. 2019; Chen et al. 2017; De Ridder et al. 2004; Irvine et al. 2009; Schipperijn et al. 2013). Extensive studies have highlighted the contribution of urban greenspace to healthy built environments such as modulating microclimate (Deng et al. 2019b; Sun et al. 2017), mitigating heat island intensity (Peng et al. 2012), purifying air pollutants (De Ridder et al. 2004; Xing and Brimblecombe 2019), and reducing noise pollution (Ow and Ghosh 2017; Van Renterghem 2019). In addition, urban greenspace has been widely recognised to promote resident’s outdoor activities and social networks and improve the public’s physical and mental health as well as life satisfaction (Ernstson 2013; Wolch et al. 2014; Wu et al. 2021). However, dramatical changes have occurred in the quantity and quality of urban greenspace over the past decades due to the rapid urbanisation from regional to global scales (Chen et al. 2017). For example, in Europe, nine out of 13 highly urbanised cities in England have experienced a net decrease of urban greenspace from 2000 to 2008 (Dallimer et al. 2011), and most of the Eastern European cities have witnessed a consistent declining trend of urban greenspace over the past three decades (Kabisch and Haase 2013). Survey-based results in 20 cities across the United States reported that 17 out of the sampled cities experienced significant declines in urban tree covers (Nowak and Greenfield 2012). All these challenges have increased the urban vulnerability to potential threats from environment and health problems, which requires timely and accurate monitoring of urban greenspace changes to support a better understanding of our living urban environments. Satellite remote sensing has greatly facilitated the monitoring and extraction of urban environments by providing spatially and temporally explicit information (Chen et al. 2017). A variety of remote sensing observations with different spatial resolutions have been used for mapping urban greenspace coverage and changes. For example, optical data with medium spatial resolution (10–100 m) such as Sentinel-2, Landsat, and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), have been widely used in monitoring the spatiotemporal dynamics of urban greenspace (Chen et al. 2017; Deng et al. 2019a; Fung et al. 2008; Su et al. 2019). National and continental changes in urban greenspace coverage have been monitored using remote sensing data with coarser spatial resolution (>100 m), such as the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (AVHRR) (Sun et al. 2011), and Moderate Resolution Imaging Spectroradiometer (MODIS) (Dallimer et al. 2011). Among the remote sensing based estimates, the widely recognised discrepancies are partially due to (1) different levels of accuracy in extracting greenspace coverage; and (2) different definitions of urban greenspace across different studies (Chen et al. 2017). Multi-scale remote sensing and crowdsourcing observations have advanced our understanding of spatiotemporal patterns and dynamics of urban greenspace.

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However, knowledge of population exposure to urban greenspace across different spatiotemporal scales remains unclear. In particular, the majority of existing environmental assessments are unable to quantify how residents enjoy their ambient greenspace during their daily life (Song et al. 2018). In reality, people living in cities are constantly moving over different locations. For example, daily routines from home to education, work, shopping, exercise, and other places will make people get exposed to different ambient green environments. Compared with the widely used indicators such as greenspace coverage in total or per capita levels, the interaction of human activities and urban greenspace is a more important process that should be quantified to reflect the suitability of urban greenspace settings. Urbanisation is highly linked with changes in urban greenspace environments. In addition to the spatiotemporal alteration of greenspace coverage and distribution, the real experience change concerning the individual-level ambient green environment with the rapid urbanisation is another important issue for promoting optimal urban planning and landscape design (Song et al. 2020). For example, does urbanisation exert unformed negative or positive impacts on urban greenspace exposure experience? Compared with new urban areas, are those urbanised old urban areas more likely to have worse greenspace exposure experience? To answer these questions, a more comprehensive analysis that incorporates the spatiotemporal difference of both urban greenspace and human activities is required. Given the important role that the greenspace environment plays in public health, the inequality in urban greenspace exposure has also aroused a growing attention (McConnachie and Shackleton 2010; Wendel et al. 2012; Wüstemann et al. 2017). The question of whether greenspace, as a critical natural and social component in urban environments, has been equally provided to residents has triggered a number of studies focusing on the greenspace disparities. For example, greenspace accessibility for vulnerable population groups such as low-income neighborhoods and minority communities (Heynen et al. 2006; Wendel et al. 2012; Wüstemann et al. 2017). However, few comparative studies are available for the cities across a country to provide a comprehensive understanding of the county’s urban residents’ ambient green environment. Besides, commonly used inequality measures still remain uncertain, hindered by the simplification without accounting for human mobility in greenspace exposure assessments. If we dive into the spatial contexts of urban greenspace exposure regarding the balance between greenspace supply and demand, we may have a clear picture of the spatial pattern in environmental justice. Addressing the issues above mentioned, we will focus on the spatial context in China and retrospect to some of our recent works on leveraging multi-source remote sensing and social big data to estimate the dynamics of greenspace coverage and exposure change for Chinese large cities, with the aim to provide an overview of answers to the following questions: (1) What is the spatiotemporal pattern of greenspace changes over the past two decades? (2) What is the temporal dynamic and heterogeneity in greenspace exposure? (3) How does urban expansion impact on greenspace exposure experience? (4) Are there any inequalities in greenspace exposure among Chinese cities?

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2 Data and Methods 2.1 Measurement of Urban Greenspace We have witnessed a variety of remote sensing data sources being used to track multi-scale vegetation coverage and dynamics. In particular, greenspace as a critical component of urban landscape, of which its amount, distribution, density, and phenology has been quantified through the lens of remote sensing as well, according to different scopes of spatial details, sample size, and temporal coverage. To eliminate the classification errors among intra-class green vegetation, we adopt the general definition that urban land completely covered by live green vegetation is regarded as greenspace, which is named as urban greenspace in our studies (Chen et al. 2017). Here we summarised our previous efforts of measuring urban greenspace into the following two types. First, hard-classification based approach (Fig. 1a). The Normalised Difference Vegetation Index (NDVI) defined in Eq. (1) is often used as an indicator to assess whether the observed target contains live green vegetation or not. NDVI = (NIR − red)/(NIR + red)

(1)

where NIR and red represent the reflectance of near-infrared and red bands, respectively. Theoretically, NDVI values range from −1 to 1 with negative and zero values representing impervious area, bare soil, or water, and a higher value above zero representing healthier and denser vegetation. For example, with a group of random reference samples of four land-cover types across different places in China, the threshold of Landsat-based NDVI values larger than 0.1 was adopted to differentiate green (i.e., cropland and forest) and non-green (urban and water) areas (Chen et al. 2017). With the support of high-resolution

Fig. 1 Urban greenspace measurement using a hard-classification based and b soft-classification based approaches

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Google Earth red–green–blue composite imagery, the Normalised Difference Greenness Index (NDGI) defined as Eq. (2) was used to measure urban greenspace of each pixel (Song et al. 2018). NDGI = (G − R)/(G + R)

(2)

where G and R are digital values of green and red bands, respectively. Similarly, with trial-and-error experiments of thresholding sensitivity to the classification performance, the optimal threshold of NDGI values greater than 0.2 was adopted to extract urban greenspace areas. Second, soft-classification based approach (Fig. 1b). Given the difficulty in quantifying sub-pixel greenspace amount from the hard-classification approach, the unmixing based approach was able to eliminate this issue to derive proportional greenspace coverage. Specifically, the linear spectral mixture analysis (SMA) defined in Eq. (3–5) was adopted to unmix the 10-m Sentinel-2 imagery to calculate the greenspace percentage for each 10 m x 10 m pixels (Song et al. 2020). M=

n 

f i · ri + 

(3)

i=1 n 

fi = 1

(4)

0 ≤ fi ≤ 1

(5)

i=1

where M is the mixed surface reflectance, i = 1, 2, n denotes the endmember, i.e., impervious area, water, and vegetation in this study. r i is the surface reflectance of each endmember, and f i is the corresponding fraction of each endmember, and  is residual. In the process of spectral unmixing, the selection of endmembers is the most critical step in ensuring the fidelity of models and producing fractional greenspace with high quality. Regarding this concern, we should balance both the quality and quantity of endmembers (“pure” pixel from the Sentinel-2 imagery).

2.2 Quantification of Dynamic Human Distribution The popularisation of smartphones over the past decade and its resultant rapid growth of mobile apps (applications designed for social networking, shopping, dining, navigation, and payment) produces large amounts of geotagged information, thus providing us unprecedented opportunities to characterise the spatiotemporal pattern of human activities. Here we introduced the Tencent mobile phone location-based service (LBS) data, which has been used for quantifying the dynamic of population

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Fig. 2 Hourly dynamics of population distribution in the Beijing-Tianjin-Hebei region for an example

distribution in a series of our previous studies (Chen et al. 2020, 2018a, b; Song et al. 2020, 2018). All of the geotagged data is produced by Tencent through retrieving real-time locations of active mobile phone users when they are using Tencent Apps and Tencent’s LBS invoked by other mobile Apps. As one of the world’s largest Internet service providers for ethnic Chinese, Tencent’s service and Apps (e.g., Wechat, QQ, etc.) have been widely used. The daily location records have reached 38 billion from more than 450 million users globally in 2017. We collected this dataset using the application program interface (API) from the Tencent location big data website (http://heat.qq.com), with a spatial resolution of 0.01 degree and a temporal resolution of 5 min. To eliminate the short-term variability of population distribution caused by random biases, we normally aggregate the Tencent-based dataset into hourly or daily, weekly, and monthly scales (Fig. 2). All the information regarding users’ identities and privacies were removed from the public released dataset.

2.3 Dynamic Human-Greenspace Exposure Assessment Given the location of individuals is spatially and temporally changed (Fig. 3a), a dynamic human-greenspace exposure assessment model in the population-weighted form has been proposed (Chen et al. 2018a; Song et al. 2018), with the sim to quantify population exposure to their ambient greenspace during daily life. The dynamic exposure assessment model is defined as below.

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Fig. 3 Conceptional diagram of changes in people’s exposure to ambient greenspace environment in daily life (a) and greenspace exposure zones with different buffered sizes (b)

n GE =

i=1 ( pi × G i ) n i=1 pi

(6)

where pi is the relative amount of population in the ith grid, Gi represents the greenspace area around the ith grid, and n is the total number of grids. GE denotes the average greenspace exposure of the corresponding study area. We used the greenspace coverage rate within a specific size of people’s surrounding area to quantify the magnitude of greenspace exposure (Fig. 3b). To calculate the greenspace coverage rate in the surrounding areas, a centroid point of each grid was assigned with the assumption that all people (i.e., it is represented by the location-based service (LBS) request records) within the grid were clustered at the center. Buffers with a specific scale were then generated from the center point to define the spatial context of greenspace exposure (Song et al. 2018). For example, three buffered scales of 0.5, 1, and 1.5 km from the center point were adopted to comprehensively evaluate greenspace exposure levels at different scales and detect the scale effects on evaluation results (Fig. 3b).

3 Urban Greenspace Coverage and Exposure 3.1 Spatial and Temporal Changes of Urban Greenspace The urban greenspace has been dramatically changing over the past decades. Our previous study using Landsat imagery from 2000 to 2014 revealed that the majority of China’s populous cities underwent a rapid urban greenspace loss (Chen et al. 2017). Specifically, in terms of the administrative boundary of different cities, only 18 of the 98 selected cities witnessed increasing trends in urban greenspace, and they are mainly distributed in Northeast China, partially attributed to the continuous effort of the Three North Shelterbelt Forests Program initiated and executed by the Chinese

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government (Wang et al. 2010). In contrast, the remaining cities experienced urban greenspace loss with different extents from 50 to 1000 km2 , especially for large cities, for example, urban greenspace losses of 1004.67 km2 in Beijing, 206.57 km2 in Shanghai, and 349.62 km2 in Guangzhou. The widespread urban greenspace loss is mainly driven by the unprecedented urbanisation process, especially for the intensified clusters in Beijing-Tianjin-Hebei region, Yangtze River Delta region, and Pearl River Delta region. The rapid urbanisation was at the expanse of considerable land use/land cover conversions, for example, greenspace loss (vegetation to impervious areas, and cropland to impervious areas), and idle land loss (bare land to impervious areas, and fallow land to impervious areas). Given the certain amount of greenspace areas within the administrative boundaries of different cities are located in suburban areas or outside the urbanised core, our studies further compared the refined urban core greenspace changes during the period 2000–2014 (Chen et al. 2017). Results reinforced that with the rapid urbanisation driven urban core area expansion, the urban core greenspace area also shrank in the majority of China’s populous cities, and only 14 of the 98 selected cities showed an increasing trend of urban core greenspace areas, including Wuxi, Changsha, Hong Kong, Zhuhai, Jiamusi, Urumqi, Suzhou, Hengyang, Zhuzhou, Benxi, Anshan, Tianshui, Dalian, and Liupanshui. As the policy-driven reforestation projects were mainly distributed in the suburban areas, those cities in Northern China did not show considerable greenspace gain trends regarding the urban core boundary division, which was different from the spatial distribution of urban greenspace changes regarding the administrative boundaries. By linking the urban core expansion and urban core greenspace change, our results revealed that with the expansion of urban core areas, urban greenspace areas of China’s populous cities concurrently shrank (R2 = 0.28, p < 0.001). Additionally, the larger cities had been experiencing larger expansion of urban core areas and larger greenspace loss.

3.2 Dynamic Greenspace Exposure The introduction of LBS data-based population distribution provides rich and multidimensional information on green space exposure, as well as uncovers differences in greenspace exposure at different temporal scales. Hourly exposure assessment provides almost real-time information regarding the interactions between greenspace and urban residents, helping detect how people’s diurnal activities contribute to greenspace exposure dynamic. Our study of 30 major Chinese city assessment indicates that obvious variation is common in terms of hourly greenspace exposure during both weekdays and weekends, but the patterns are different among cities (Song et al. 2018). For example, in the city of Huizhou on weekdays (Fig. 1a), the relative high exposure levels occur in some specific periods, e.g., 6:00–7:00 am (0. 223–0.23), 12:00 noon (>0.227), 5:00–6:00 pm (>0.22), and 10:00–11:00 pm (> 0.22). But the rest periods show relative low exposure levels, especially at 2:00 am when the exposure level is just about 0.2, which is 13.04% lower than the highest period at 7:00 pm.

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Besides, in cities like Guilin and Tianjin on weekdays (Fig. 1b, c), even without the obvious fluctuations similar to Huizhou, the exposure level during daytime and nighttime are also significantly different. For the city of Guilin, people are enjoying a better green environment during nighttime than daytime, and the greenspace exposure level becomes higher than 0.215 during 2:00 am–7:00 am. However, Tianjin has the opposite situation where the exposure level is higher during daytime but lower at night. The hourly change of greenspace exposure presents the people’s ambient green environment during their daily activities, reflecting the appropriateness of greenspace distribution within a city (Song et al. 2018). Using Huizhou as an example, the high-exposure periods basically coincide with the outing activity time of urban residents (Fig. 4a). Specifically, people usually leave home for work and school around 7:00 pm, start to rest or eat around 12:00 at noon, go home or do something non-work related (e.g. shopping, gathering, fitness) after 6:00 pm, and basically go home and get ready for bed by 11:00 pm. The high exposure levels during these periods indicate better ambient green environments when people are doing corresponding activities. On the other hand, those hours with lower exposure are exactly when people are at home or at work and school, indicating the relatively poor green environment in these locations in Huizhou. The exposure pattern of Guilin or Tianjin suggests a better green environment when people are at home or work (or school) (Fig. 4b, c). Daily average exposure assessment provides comprehensive insight into urban China in terms of people’s ambient green environment, uncovering the similarities and disparities among cities. The 303 Chinese cities assessment conducted by our study shows that the daily average greenspace exposure levels among Chinese cities present noticeable spatial clustering and heterogeneity pattern (Song et al. 2018) (Fig. 5). For example, cities located in provinces like Yunnan, Liaoning, Jilin and around the Shandong-Hebei border generally have a high greenspace exposure level. In contrast, cities belonging to provinces like Xinjiang, Gansu and Inner Mongolia tend to have poor exposure levels. Statistically, the top three regions with the highest daily greenspace exposure level (calculated by averaging all the cities’ daily exposure values) are southwest region (0.194), northeast region (0.152) and east region

Fig. 4 Hourly urban greenspace exposure (within a 0.5-km scale) within a day in cities of a Huizou, b Guilin, and c Tianjin

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Fig. 5 Greenspace exposure of 303 major cities in China

(0.145), followed by south central region (0.132), north region (0.096) and northwest region (0.066). The general distribution pattern of cities’ greenspace exposure levels suggests that climatic features play a crucial role in determining potential levels of greenspace exposure. In particular, a humid and warm climate provides favorable conditions for the growth of vegetation, while a dry and cold climate reduces the amount of vegetation and the length of the green period. However, spatial heterogeneity in terms of greenspace exposure do exists in cities in the same or similar climate zones, such as some low-exposure cities located in southeast coastal region, which suggests that supply and accessibility of green spaces within cities are also key determinants of the greenspace exposure level. The difference in greenspace exposure between daytime and nighttime reveals the inconsistency between the residential and working areas within a city and provides a scientific basis for the planning and improvement of the urban green environment. The comparison of daytime and nighttime exposure for 303 cities in China from our previous study illustrates that the population distribution change combined with the spatially uneven greenspace supply leads to noticeable variation in people’ ambient green environment (Fig. 6). A higher daytime exposure level, as the cluster of cities located in Pearl River Delta, can be considered as people having a relatively good green environment around their workplaces. On the other hand, the higher exposure level at night can either indicate a better green environment in the people’ residential area, or it can be the result of people’s active proximity to the natural environment during non-working hours. The comparison of people’s exposure levels at different times can provide a good indication of their environmental quality in different living scenarios, and this information can therefore provide city managers, decision makers and planners with effective information to improve the rationality and fairness of urban greenspace provision.

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Fig. 6 Differences in greenspace exposure between daytime and nighttime among 303 major cities in China

The comparison between weekdays and weekends in terms of greenspace exposure can help to investigate whether residents’ activity features on different days of a week have effects on exposure. Our results show that even though the differences are general, they are not significant, and the range of variation is within 2%. For some highly urbanised cities like Shanghai, Beijing, Chengdu and Hangzhou, people tend to have fewer greenspace in their surroundings during weekdays, but the exposure level would rise during weekends. This fact suggests that high-intensity urban construction in these cities has weakened the availability of greenspaces, especially for areas where people live and work during weekdays, consequently prompting people to seek more opportunities to access natural environment on weekends. Besides, people living in cities like Tianjin, Wuhan, Kunming and Zhengzhou have higher greenspace exposure on weekdays, which may benefit from the proper greenspace distribution within the urban areas of these cities.

3.3 Impact of Urban Expansion on Greenspace Exposure China’ rapid urbanisation process has reshaped the land-use types within and around urban areas as well as the corresponding natural environment. Our previous study therefore investigated how urban expansion impact people’s exposure to green environment, by comparing the differences in greenspace exposure between old and new urban areas of 290 cities in China (Song et al. 2020). The results indicated that,

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for most of Chinese cities, old urban areas (existed before 1992) are usually worse than new urban areas (merged by urban expansion between 1993 and 2015) in terms of greenspace exposure. Specifically, 276 out of the 290 selected cities’ residents have better ambient green when they are living in new urban areas and the average greenspace exposure level of all the cities is 0.356, but the value of old urban area is only 0.254. From a geographical perspective, northeast cities have a much better green environment in new urban areas compared with old urban areas, followed by cities in the central region, east coast region and western region of China. The numerous “greener” new urban areas are considered to be the result of a number of factors, such as lower urban development intensity, more rational planning schemes, as well as favorable natural endowment. Moreover, the huge difference between new and old urban areas in China is also an issue that needs to be seriously addressed, as it may accelerate the decline of old urban areas. In addition to the large number of cities with “greener” new urban areas, cities having “greener” old urban areas are also be found, and most of them are located in western region of China with a dry and low rainfall climate. These results illustrate that urbanisation can not only destroy the natural environment within urban areas, but for cities in harsh natural conditions, its effect is rather positive. That is, the willingness to enjoy natural vegetation prompts the improvement of the green environment during urbanisation which enhances the quality of the city’s living environment.

3.4 Inequality in Greenspace Exposure The unequal provision of urban greenspace, as an essential social resource, is also an important issue which should be fully considered in today’s urban China. Leveraging each city’s average daily greenspace exposure level and Gini index, our study made a comprehensive assessment of inequality in greenspace exposure for 303 cities in China. The results reveal that the vast majority of Chinese cities face high inequality in greenspace exposure (Fig. 7), and the overall average Gini index in greenspace exposure is as high as 0.669, with 207 out of 303 cities’ Gini indexes larger than 0.6. Besides, spatial heterogeneities in exposure inequality are also obvious among Chinese cities. For example, more than 66% northwest cities’ Gini indexes are larger than 0.8, while only 30% southwest cities’ Gini indexes are greater than 0.8. The study identified a number of spatial clusters in terms of greenspace exposure inequality. Specifically, a cluster of cities located in west region of China (i.e., the border area of Inner Mongolia, Ningxia, Gansu and Shaanxi) is found to have a high Gini index, but a cluster of cities located along the Yangtze River are having relatively low Gini index (Fig. 7). A series of climate, environmental, and socioeconomic factors are also selected to uncover the potential associations between exposure inequality and different factors. By leveraging geographical detector models, climate and environment factors such as greenspace coverage rate, annual precipitation, are found to have relatively strong and significant associations with exposure inequality, which suggests that adequate

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Fig. 7 Gini index of greenspace exposure among 303 major cities in China

greenspace provision and precipitation play a positive role in mitigating greenspace exposure inequalities. Moreover, in terms of the interaction effect of a pair of factors, the interaction of greenspace coverage and temperature are found to have the strongest association among other selected factor pairs. In summary, adequate greenspace provision could be considered as a prerequisite for reducing inequality, and humid and hot environments promote vegetation growth which increases greenspace supply and contribute to improving inequality.

4 Discussions Compared with the previous widely used indicators such as greenspace coverage in total or per capita levels, the proposed dynamic exposure model considered the spatiotemporal variability of population distribution and explicitly uncovered the interaction between humans and their ambient greenspace environment, thereby contributing to a better exposure assessment. The temporal variation of greenspace exposure reveals the changes in people’s surrounding greenspace environment, which is mainly determined by the characteristics of greenspace distribution in urban areas. Besides greenspace, the assessment of people’s exposure to air pollutants such as PM2.5 , PM10 , SO2 , NO2 , and O3 , noise pollution, and heat stress can be also conducted in this manner to well incorporate the spatiotemporal interaction between humans and urban environment factors. Greenspace measurement is critically important to support and facilitate the monitoring, management, and planning of the urban green environment. Although we

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have hard and soft oriented classifications to quantify urban greenspace coverage, the accuracy of greenspace measurement is still largely influenced by the scaling effect. For example, urban features normally have scale lengths ranging from 10 to 70 m (Small 2003), consequently direct uncertainty results from the insufficiency of spatial resolution in supporting urban greenspace measurement. Phenology difference in greenspace is another factor that impacts a lot on people’s exposure to the ambient green environment across different geographic locations, whereas broadscale urban studies always treat urban greenspace as constant or static within a year. In reality, vegetation species and climatic conditions lead to dramatic differences in vegetation phenology (e.g., evergreen and deciduous trees). As an essential urban environment component, urban greenspace is expected to provide equal exposure opportunities for all citizens. However, our results revealed that the majority of Chinese cities are facing high inequality in greenspace exposure, with 207 cities having a Gini index larger than 0.6. Given the widely recognised health and social benefits from a greenspace environment, the issue regarding environmental justice in Chinese cities is more likely to exacerbate human’s health and social inequality. Additionally, our results also revealed that the spatial distribution of greenspace exposure inequality presents obvious geographic heterogeneity. Generally, cities located in Northwest China (e.g., Xinjiang, Gansu, and Ningxia) and North China (e.g., Inner Mongolia) tended to have a much higher Gini index with serious greenspace exposure inequality, which was partially due to the harsh environmental conditions characterised by arid and semi-arid climates. In 1992, the Ministry of Housing and Urban–Rural Development of China launched an incentive scheme and started to grant the title of “National Garden City” to cities with increased greenspace to meet specific national standards (Wolch et al. 2014). From 1992 to 2019, 235 of the 303 selected cities in this study have met the established standards (http://dwz.date/cHsf)). Nevertheless, as 156 out of the 235 “National Garden City” have a Gini index larger than 0.6, it is clear that they have not fully resolved the issues of usability and equity in the context of securing the growth of the quantity of greenspace. A strategic balance between quantity and equality of urban greenspace coverage is highly required in the future development of green and healthy cities. Meanwhile, some potential caveats need to be addressed in the practices of urban greenspace exposure assessment. First, social sensing big data such as mobile phone data and social media check-in records are non-representative, they may omit some population groups of society such as children, the elderly, and the poor, which are less-frequent active users (Chen et al. 2018a). Nevertheless, the massive volume of big data is still a good lens for delineating real-time population dynamics from local to regional scales. Second, the extractions of urban greenspace conducted in our previous studies are based on empirical thresholds or unmixing analysis of remote sensing observations in certain temporal slices, which will limit the accuracy of greenspace coverage and temporal dynamic mapping. Therefore, how to integrate multi-source remote sensing and social sensing data to better map the higher spatiotemporal greenspace dynamic will be our next-step endeavor in this direction.

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5 Conclusions This chapter provides an overview of our recent works on leveraging multi-source remote sensing and social big data to estimate the dynamics of greenspace coverage and exposure change in China. The key findings and insights can be concluded into the following four aspects: (1) With the rapid urbanisation process, a consistent decline of urban greenspace coverage was identified in the majority of China’s cities. (2) The proposed dynamic model by quantifying the interaction between human movement and urban environment provides a better way to understand how people expose to their ambient greenspace environment across different spatial-temporal scales. (3) Urban expansion process directly led to differences in green environments between old and new urban areas. These differences were not only observed by the green coverage rate but also captured using a dynamic assessment of people’s exposure to greenspace. Generally, for most of China’s large cities, people could enjoy more greenspace in new urban areas than in old urban areas, except for a few cities located in Western China. (4) Urban residents in most Chinese cities face severe inequality in terms of greenspace exposure. We suggest that the government agencies in China should implement more ambitious and effective greening programs based on the balance between greenspace supply and demand across local and regional circumstances, to reduce environmental injustices and promote healthy and sustainable urban development. Acknowledgements This study is supported by The University of Hong Kong HKU-100 Scholars Fund and the National Natural Science Foundation of China (Grant NO. 42001385).

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Building Green Infrastructure: Eco-Cities and Sustainable Development Zones in China Bing Wang and Shining Sun

Abstract Historically, environmental degradation has often been the cost of concomitant urbanisation and industrialisation. China is no exception. Although China’s GDP has maintained the fastest average growth worldwide over the past four decades, the country has encountered multifaceted environmental challenges, with its ecosystems and biodiversity undergoing large-scale disruption. Since the 1990s, the central government has ushered in a series of campaigns, policies, and regulations focusing on an environmental agenda at different levels. This chapter tracks the shifting propositions of green infrastructure in China’s efforts during the eco-cities movement at the beginning of the 2000s and under the most recent Sustainable Development Zones (SDZs) initiative in 2016. This chapter analyzes the various planning principles, design approaches, and environmental, economic, and social considerations involved in the development of green infrastructure, both conceptually and through the lens of practice, in China’s search for a sustainable urban development model. Case analyses, comparative studies, and data analytics from social media are employed as research methods to examine how the concepts of environmental sustainability and green infrastructure have been evolving under the influence of locational dynamics and temporal characteristics in China. Keywords Environmental planning · Eco-Cities · Sustainable development zones · Sustainable development goals (SDGs) · Green infrastructure · Design approaches · GDP

1 Introduction 1.1 Background Since the initiation of its economic reform in 1978, China has undergone rapid urbanisation, concomitant with extensive industrialisation. The country’s urbanisation rate B. Wang (B) · S. Sun Graduate School of Design, Harvard University, Cambridge, MA, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_9

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increased from 17.9% in 1978 to 60.6% in 2020, and its GDP rose from 0.09 trillion USD in 1970 to 14 trillion USD in 2020 (The World Bank 2020). As the histories of many nations attest, urbanisation and industrialisation have often come at the cost of environmental degradation and social challenges. These challenges have ranged from the large-scale destruction of the existing urban fabric, pollution of the environment, and damage to ecosystems to increased social displacement and inequality. China was no exception. The quality of urbanisation in China, especially in its early years of reform, suffered from a complex array of environmental issues rooted in its industrial structure, rural–urban policies, and weak enforcement of environmental regulations (Yusuf and Saich 2008). Since the 1990s, China’s central government has ushered in a series of campaigns, policies, and regulations at different scales focusing on the environmental agenda (Fig. 1). The government’s efforts intensified especially after the 2000s, paying increasing attention to the quality of growth and stressing the need to construct a “resource-conserving and environmentally-friendly society” and “ecological civilization” (The World Bank 2009, p. 27). With frequently established policies and directives reflecting its awareness of the importance of environments, China’s pursuits in constructing an environmentally friendly society have never been linear. The ever-changing agenda in the headline wording of the policy focuses, from the “Environmental Protection Model City” in 1997 to “Ecological Garden City” in 2004, “Ecological City” in 2001, “Livable City” in 2005, “Sponge City” in 2014 and the latest “Sustainable Development Zones” in 2019, reflected not only the evolving actions of China’s collective efforts in improving environmental quality but also the ambiguities and inconsistency embedded in the various concepts and practices of the environmental movements, both in China and worldwide. China’s environmental initiatives under the diverse rubrics were implemented with different levels of success. Some failed to generate the intended impacts, some existed for only a short period before morphing into an upgraded version under a different name, and others yielded positive results in alleviating damages to environmental quality. Among these initiatives, three were carried out with far-reaching governmental efforts and intensive financial investments, involving multiple actors in the process—namely, the ecological city movement, the sponge city, and the sustainable development zones initiatives. Given that the sponge city initiative often had a specific and narrower goal relating to urban water management of the locale, this chapter focuses on the ecological city (the “eco-city”) and the sustainable development zones (SDZs) initiatives. In particular, this chapter examines how green infrastructure has served as a consistent guiding principle and an integral component penetrating these two environmental initiatives. The eco-city and SDZs initiatives were both aimed at the construct of sustainability agenda at the urban scale in an effort to forge a symbiosis of urban ecology and economic growth. Both were initiated using pilot projects to test the effectiveness of the guiding policies before being largely expanded to wide applications at the national scope. The two most well-known eco-city pilot projects were the Dongtan Eco-City project located on the Chongming Island of Shanghai, launched in 2005, and the Sino-Singapore eco-city project in Tianjin, approved in 2007. Although

Fig. 1 Timeline of China’s environmental initiatives accompanying industrial and urban development. Data in the graph indicate urbanisation rates, GDP growth, and industrialisation rates. (Sources Authors’ compilation based on data from the World Bank and National Bureau of Statistics of China.)

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the Shanghai Dongtan project was dubbed the first purposely-built eco-city, China was not alone in its efforts to build eco-cities at the time (Chen and Hu 2010). Other eco-cities were being constructed in different locations worldwide, including Masdar in Abu Dhabi (Cugurullo 2013) and the Songdo eco-city in South Korea (Kim 2010; Shwayri 2013). In the spring of 2009, French President Nicolas Sarkozy announced that Paris would become the first “post-Kyoto eco-city” as part of his ambitious plan to transform the French capital into an expanded, regenerated greater metropolis; the same year, the British government published its decision to build four new “eco-towns” throughout England (Joss 2010). Unlike the initiation of the eco-city projects, the establishment of the SDZs movement was China’s response to the United Nations’ (UN) issuance of the 2030 Agenda for Sustainable Development in 2015. To implement the agenda promoted by the UN, the State Council issued China’s Implementation of the 2030 Sustainable Development Agenda Innovation Demonstration Zone Construction Program at the end of 2016 (Li et al. 2021), proposing to build ten demonstrative SDZs nationwide. Among them, six cities were approved by the State Council, including Shenzhen, Taiyuan, and Guilin in 2018 and Chenzhou, Lincang, and Chengde in 2019.

1.2 Green Infrastructure Despite being launched a decade apart as policy initiatives, the eco-city and SDZs initiatives share commonalities, including the application of green infrastructure penetrating the process of design, planning, and operation for achieving environmental sustainability. Green infrastructure, a relatively new term that emerged at the intersection of the fields of planning, ecological engineering, and development policies, was coined in 1999 from the namesake of the “Green Infrastructure Working Group” organised by the U.S. Conservation Foundation and the Department of Agriculture Forest Service. Its initial concept concerned green networks formed by urban open spaces, forests, wildlife, parks, and other natural areas as the necessary infrastructure to support the development of cities and communities (Yang and Chai 2016). From the viewpoint of the ecological theory, green infrastructure as a concept was differentiated from grey infrastructure (such as roads, municipal sewage pipe networks, and other municipal support systems) and social infrastructure (hospitals, schools, etc.) of the environment. Over the years, as green infrastructure has been increasingly deployed as a focus of the sustainability policy concerned with rapid urbanisation, global warming, and climate change, its variations in concept and geography make it difficult to achieve global consensus as a concept and practice. Three different interpretations seem to have emerged regarding the practice and benefits of green infrastructure. If one closely follows its conceptual origin, green

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infrastructure is a system of interconnected public parks and all other types of green spaces that safeguard the diverse interests of people, providing a wide variety of ecosystem services1 to promote the formation of green networks that integrate planned and unplanned urban elements. These physical elements include street trees, private gardens, lawns and parks, golf courses, urban forests, cultivated land, wetlands, lakes/sea, and streams (Kambites and Owen 2006). This interpretation of green infrastructure is at its roots a landscape dimension. For its next expanded level, green infrastructure can be interpreted as a key component of complex urban systems, incorporating green standards and ecological processes in engineered structures and built forms (Benedict and McMahon 2006). Its principal application can be deployed into water treatment facilities, electrical transportation systems, energy-efficient building complexes, etc., all of which – through the greening process – can be transformed from being otherwise grey infrastructures to contributing to the improvement of environmental quality of urban life. Through their green transformation, these systems help address biodiversity conservation, climate change adaptation, and temperature regulation by employing environmentally conscious intervention. Green infrastructure in this context, interpreted as green transformation, helps maintain the ecological balance in an otherwise man-built system, achieving cleaner air and water to enhance the quality of the environment. This level of interpretation highlights the urban dimension of green infrastructure application. Lastly, green infrastructure can also provide benefits at the socio-economic dimension. The concept of green infrastructure can serve as a rationale and framework, guiding the transition of conventional economic composition towards a construct of green economy and the establishment of green governance within the social structure of the existing legal, policy, and financial instruments (Kambites and Owen 2006; Simpson and Zimmerman 2013). Although some scholars have challenged whether economic growth and environmental protection can be taken as parallel initiatives, to the Chinese government, the environment is “becoming a necessity rather than contingent condition” for the sustainability of economic success (While et al. 2004, p. 554). This has led to the implementation of green infrastructure and an emerging “green” thinking underlying the country’s policy in establishing economic and environmental initiatives not as separate domains in Chinese policies, but rather in relational terms (Zhang et al. 2020). Although consensus on the definition of green infrastructure is still lacking, its multifaceted interpretation and application have played a large role in the planning, design, and implementation process of the pilot projects in the Chinese eco-city and SDZs initiatives. This chapter explores how green infrastructure has been applied and embedded in the larger context of the two initiatives, thereby contributing to the construct of sustainable urban developments. As current studies examining China’s eco-cities and SDZs have been conducted independently from one another, this 1

Ecosystem services refers to the benefits human populations derive from ecosystems.

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chapter seeks to place them side by side with each other, using the lens of green infrastructure, to make a necessary comparison in order to understand the impact of green infrastructure during the significant episodes of China’s pursuits of sustainable development. We use comparative case studies, observations from site visits, and information obtained from the literature and social media to examine how green infrastructure simultaneously performs as a policy tool in constructing an ecologically conscious environment and as an urban intervention improving the economic and social vibrancy of society. The remainder of this chapter is organised as follows: Section 2 uses Shanghai Dongtan and Tianjin Binhai as two case studies to articulate the strategic innovations of the physical planning and design of green infrastructure in the process of eco-city building at the city and project levels. Section 3 focuses on SDZs initiatives, with analyses of the green infrastructure applications in Shenzhen and Guilin to indicate the varying operational strategies at the urban scale. Section 4, based on the four case studies, analyses the commonalities and differences embedded in the two designated campaigns of Chinese eco-cities and SDZs from the perspectives of planning and design approaches, environmental impacts, and economic and social performances of green infrastructure. Section 5 concludes the chapter.

2 Green Infrastructure in China’s Eco-City Projects: Shanghai Dongtan and Tianjin Binhai The concept of “eco-city”, traces back to a spatial planning and development practice under the leadership of Urban Ecology, a non-profit organisation founded by the environmental activist Richard Register and others in Berkeley, California, in the 1970s. The phrase “eco-city” was later popularised by Register’s influential writing Ecocity Berkeley: Building Cities for a Healthy Future in the 1980s. It was then introduced in three consecutive conferences organised by his group to convene likeminded people to discuss urban problems and submit proposals to build cities based on ecological principles (Roseland 1997). China was one of the first countries to embrace the eco-city model and apply its concept as guiding principles for building cities on a national scale. The central government emphasised its plan to adopt “eco-culture” in 2007, introducing laws and regulations to restrain environmental damage and providing policy incentives to local governments. According to statistics from the Chinese Society for Urban Studies (2011), by February 2011, China had 230 cities at the prefecture level or above that had proposed establishing themselves as eco-cities. Among those aspiring to build eco-cities, two high-profile pilot projects caught the attention of the international realm: Dongtan Eco-City in Shanghai and Sino-Singapore Eco-City in Tianjin. These two pilot projects, which sought to introduce the best practices of eco-cities in China, have a comparable scale and embodied the concepts and practices of green infrastructure in the planning, design, construction, and operation processes.

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2.1 Dongtan Eco-City in Shanghai Dongtan Eco-City was China’s first attempt to build an exemplar eco-city that addresses a city’s ecological, social needs, and economic self-sufficiency. Its first phase was a Sino-British joint project initiated in 2005. Located at the eastern tip of Chongming Island, an alluvial island in the mouth of the Yangtze River, the site is 24 kilometers north of downtown Shanghai. Largely undeveloped land, Dongtan was owned by the Shanghai Industrial Investment Corporation (SIIC), a holding company publicly listed on the Hong Kong stock exchange. SIIC contracted the British engineering firm Arup, a London-based engineering and design firm, to undertake the first phase of the master planning for the site. SIIC also involved many Chinese and British state agencies, universities, and planning institutions during the conception process of this project. By January 2007, the master plan for Dongtan and its accompanying document Supplement to the Controlled Detailed Planning of Dongtan Ecological Start Zone were formulated, and they defined an area of 12.5 square kilometers as the ecological new city. The master plan introduced the concept of “integrated urbanism” in three successive phases, with the planned community aiming to reach 80,000 residents by 2020 and up to 400,000 by 2050 (Castle 2008). Through the application of green infrastructure in three different dimensions—namely, landscape, urban, and economic—Dongtan Eco-City sought to achieve a “66% reduction in energy demand, 40% energy use from bioenergy, 100% renewable energy use for buildings, on-site transportation, 83% reduction of landfill waste, and almost no carbon emissions”. The vision of the master plan was to “convene the imagination of the public and launch future possibilities” of an ecological living (Wang 2017, p. 340). For the landscape dimension of its green infrastructure, Dongtan’s master plan retained the city’s existing river system, farmland landscape, and rich vegetation as key green elements on site, with Tuanwang River and the central lake located in the center, forming an ecological core. The master plan further suggested constructing ecological corridors in a north-south direction on both sides of the ecological core, each with an interval of approximately 500 meters. Twenty-four parks were planned within the city boundary, each bounded by field edges and connected to nearby irrigation channels. Surrounding agricultural land was converted to wetlands called “eco farms”, creating a linear buffer zone between the city and mudflats to protect the thousands of rare migratory birds that concentrated on the island each spring. Outside the buffering strip was continuous countryside green space that served as a natural habitat for wild animals. In addition, a stormwater cell was introduced to reinforce the localized absorption of rainwater, limiting large-scale stormwater gathering and reducing the flows of surface water. The city was planned to be compact, with low-rise energy-saving condominiums interspersed with green spaces. This clustered layout structure facilitated the idyllic urban form and closely followed the planning principles of green infrastructure in constructing an interrelationship between the ecological core and green corridors. All residents and visitors were to be in close contact with green spaces, lakes, and

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canals; visitors would arrive at the coast and leave their cars behind, traveling along the shore as pedestrians and cyclists, or via sustainable public transport vehicles, to a networked green space. For the urban dimension, Dongtan was divided into three separate villages that join to form the city center, following a compact land use pattern. The entire city was to be powered by renewable energy, such as solar and wind energy as well as biomass. The proposed buildings were to conform to the embedded development model, where the priority was to integrate the development with the natural environment. In addition, as the city was established with a fossil-fuel-free transportation system, all buildings were planned to be situated within a seven-minute walk of public transport to lower energy consumption and enable transportation to run on renewable energy. Given that the site is flat and windy, wind turbines were set up for energy generation with the orientations of plot sites and buildings to form a microclimate, thereby avoiding wind tunnels (Castle 2008). Waste output was recycled and composted before being returned to the local farmland to help ensure its long-term fertility and its capacity for food production. After some period of suspension in construction, the eco-city recently initiated its third phase of construction.2 With the completion of a newly constructed bridge tunnel linking downtown Shanghai to Chongming Island in 2010, Dongtan Eco-City is only a one-hour drive from Shanghai. To maintain Dongtan’s economic sustainability, the transformation of its conventional agricultural production into a modernized agricultural and farming lifestyle economy has become critical. Within this process, the economic benefits of green infrastructure were highlighted. The community groups’ farmlands were converted into spatial containers of a series of programs for agriculture-related commercial activities and a diversified farmland-related operation, including organic planting, farming classrooms, farmland lease, and even open platforms for agricultural product sales, design, and packaging. The government and local communities also provided citizens with an opportunity to participate in food processing and production and simultaneously offered an alternative farmland choice for metropolitan residents from Shanghai who seek agricultural experiences. This act of urban green spaces serving as infrastructure and medium for the green economy for Dongtan was not envisioned in its initial master plan; nevertheless, it reflected the economic benefits and dimensions of the green infrastructure, which have become increasingly imperative for sustainable development.

2 The first phase of Dongtan Eco-City development was initiated in 2005, with the master plan by Arup dominating the process. The second phase lasted from 2010 to 2014, when transportation systems on Chongming Island were largely built, including the ocean tunnel-bridge linking the island and Shanghai. Dongtan Eco-City entered its third phase of development in 2015, and mixed-use programming has become the core of planning and development.

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2.2 Sino-Singapore Tianjin Eco-City (SSTEC) Initiated in 2007, the Sino-Singapore Tianjin Eco-City (SSTEC) was intergovernment cooperation between China and Singapore, formalised by the Chinese Premier Wen Jiabao and Singaporean Prime Minister Lee Hsien-Loong. The SSTEC was envisioned as an “economically sustainable, socially harmonious, environmentally friendly and resource-conserving” city. Its site, occupying 30 square kilometers of land, is located within the Tianjin Binhai New Area, a new district 40 kilometers from Tianjin downtown and 150 kilometers from Beijing’s city center. The project was expected to be fully completed by 2020 to host 350,000 residents.3 Regarding its physical landscape dimension, the green infrastructure on the SSTEC site was planned with three interrelated spatial networks: a green system, formed with conserved ecological wetlands as a central core linked to its surrounding rehabilitated water bodies; two ecological corridors—one extensive green (vegetation) and the other blue (water)—interspersed with public green spaces continuously winding throughout the four districts of the eco-city; and the southern bank of a historic river meandering through the city center, which was planned to accommodate the mixed uses for commercial, cultural, and recreational activities. Three spatial units constituted the hierarchical urban organisation of the SSTEC: the eco-cell, the eco-community, and the eco-valley. As a basic unit of the ecocommunity, the eco-cell comprises four blocks, each ranging 400 meters by 400 meters, with 20- to 30-story residential towers surrounded by shared public infrastructure, schools, and businesses. Four eco-communities form an eco-district, which contains a central business area (Ong 2019). The eco-valley is essentially an expansive greenway, along which transportation and other infrastructure are aligned. The spine of the eco-valley acts as an axis that incorporates water-sensitive urban design elements, including eco-swales and dry streams that function as a green mobility network linking all districts and serving as one of the SSTEC’s major public spaces. The core of the SSTEC high-rise buildings contain vertically stacked programs interconnected with various sky-bridges at multiple levels to achieve efficient use of vertical spaces. The SSTEC was to provide, on average, twelve square meters of public green space per person, with at least 70% of the plant species being native to the region. Regarding the urban dimension, the first step in building Tianjin Eco-City was treating the overall site with land desalination. The desalination of seawater, together with wastewater treatment, rainwater recycling, and the construct of solar-scape, wind-scape, and solar and wind power constituted the fundamental step in the prevention of environmental degradation and served to achieve energy conservation. Desalinated water was then filtered to provide the water supply for the city. The wastewater pond was rehabilitated and transformed into the clean and beautiful Jing Lake, a component of the major scenic view of the city. In addition, a comprehensive green 3 Approved by the central government, the SSTEC’s master plan was jointly developed by the China Academy of Urban Planning and Design, the Tianjin Urban Planning and Design Institute, and the Singapore planning team led by the Urban Redevelopment Authority (URA).

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transportation system constituting a critical component of the overall green urban theme was to provide a light rail transit system serving as the main mode of transportation to reduce carbon emissions, supplemented by a secondary network of trams and buses running on clean eco-fuel. In comparison, the green infrastructure for the SSTEC was much more systematically organised than that of Dongtan Eco-City, at least from the physical planning and design perspective. Unlike Dongtan Eco-City (or other ambitious projects at the time, such as Masdar Eco-City), the SSTEC was not envisioned to reach zero carbon emissions and depend entirely on 100% renewable energy; instead, the focus of green infrastructure in the SSTEC’s urban system dimension was to implement green strategies and technologies that are practical, replicable, and affordable (Ong 2019).

3 Green Infrastructure and Sustainable Development Zones: Shenzhen and Guilin While China’s environmentally-centered agenda primarily focused on project-based new town developments in the late 1990s and early 2000s, including the aforementioned Shanghai Dongtan and Tianjin Binhai projects, the country’s recent agenda has shifted toward a holistic promotion of existing cities aimed at technological and innovation-driven sustainable developments. The designation of existing cities as SDZs was part of China’s response to the United Nation’s global plan Transforming Our World: The 2030 Agenda for Sustainable Development in 2015, which incorporated 17 Sustainable Development Goals and 169 related targets to address the global challenges of climate change, social inequality, and environmental degradation (Khaled et al. 2021). China’s State Council formulated the country’s implementation plan towards the UN’s 2030 agenda with ten existing cities selected as SDZs. This implementation plan was incorporated into China’s 13th Five-Year Plan in 2016, and Shenzhen and Guilin were designated as two pilot programs. Each SDZ was expected to deliver the Sustainable Development Goals by 2030 and develop a detailed threeyear action plan, including identifying green-related focuses, achieving a development balance between economic growth and sustainability, setting up targets and indicator measurements, finding solutions for funding, and establishing institutional support (Wang et al. 2020). The principles of green infrastructure were incorporated into Shenzhen’s and Guilin’s operational strategies at multi-scale dimensions. Whereas the primary mission for the Shenzhen government as an SDZ was to solve the conflicts between limited environmental resources and sustainable economic growth, Guilin as an SDZ aimed to address issues related to ecological development and lagging economic growth.

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3.1 Green Infrastructure Development in the Megacity of Shenzhen Shenzhen, established in 1979 as one of the special economic zones in China, has transformed itself from a fishing village to a hustling and bustling metropolis with a population of nearly 13 million in 2020. Its gross domestic product surged from less than 200 million RMB (28.5 million USD) in 1980 to 366 billion RMB (52.3 billion USD) in 2018 (To et al. 2021). Known for its innovation capabilities, Shenzhen has become a testament to China’s successful economic story over the past four decades and is home to more than 14,000 high-tech enterprises and technology giants, including Huawei, Tencent, and DJI. However, as successful as it has been in many aspects, Shenzhen has faced critical bottlenecks in its own development, including constraints to the carrying capacity of its natural environment, a shortage of land supply, rising costs of production, high and unaffordable housing prices, and a pressing need to upgrade its economic structure and boost innovation (Ng 2011). The central government’s announcement “Supporting Shenzhen to Build a Pilot Demonstration Zone of Socialism with Chinese Characteristics” (hereinafter referred to as the “Opinions”) identified five strategic positions as Shenzhen’s priorities as an SDZ: achieving innovation-driven high-quality development, becoming a city with effective urban management under the rule of law, becoming a model of urban civilization, serving as a benchmark for people’s livelihood and happiness, and being a pioneer in sustainable development. Specifically, to become a pioneer in sustainable development, “Opinions” identified the need for Shenzhen “to create safe and efficient production spaces, comfortable and livable livingspaces, and ecologicalspaces with clean waters and blue sky. [To] take the lead in development to provide China’s experience for the implementation of the UN’s 2030 Agenda ” (“Opinions” 2019). Far before its designation as an SDZ, in 1986, Shenzhen became one of the first Chinese cities to incorporate the protection of natural ecosystems into its master plan, laying the foundation for its cluster-oriented multi-center development pattern. In 2005, Shenzhen’s Basic Ecological Control Management Regulations specified the various land types under the government’s protection control that was prohibited from development encroachment, including basic farmland, nature reserves, firstlevel water source protection areas, major rivers, wetland reservoirs, mountains and woodlands with slopes greater than 25%, ecological corridors, and 978 kilometers of coastal land and islands. Shenzhen was also one of the first pilot cities to set up, among the general master plans, special plans for green space systems. Its 2004 version of the special plans for green space systems established a three-tiered park system: natural parks, urban parks, and community parks. Expanding from the green infrastructure’s landscape dimension to its ecological dimension, Shenzhen’s special plans for green space systems became the foundation for the “Shenzhen Green Infrastructure Planning Study and Pilot Planning Program.” The city conducted a thorough green infrastructure planning study that defined the required qualities of green space as well as the maintaining capacity of diverse species within these green spaces. The green infrastructure planning study enlisted

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the protection of connecting green corridors among habitats and clarified the need to improve the city’s natural environment, air and water quality, and public health. The Green Infrastructure Planning Study also proposed ecological assessment methods and advocated for the creation of an ecological security pattern for environments based on the construction of ecological green space. It carried out pilot plans in testing the various means for achieving ecological protection, environmental conservation and restoration, and green space improvement. In terms of the urban dimension, the Shenzhen municipal government promulgated “General Specifications for Ecological Community Evaluation” in 2021 to highlight green infrastructure as an important component for improvements of retrofits to old urban neighborhoods. This Ecological Community Evaluation established the first standardised evaluation system covering details for the design, construction, operation, and management of the defined ecological residential communities. Details include maintaining the quality of community “pocket” parks, increasing the proportion of green lighting to 95% of the pubic lighting, adopting energy-saving measures and centralised air-conditioning systems for vertical elevators, equipping residential buildings with room temperature-adjustment facilities and reaching a 100% utilisation rate of household water-saving appliances and equipment, among other goals (Zhang 2021). In addition to building green infrastructure at the community and urban levels, the construction of Shenzhen’s new subway line has also become a showcase of how green infrastructure has been adopted as an integral part of a public transportation system. Through the site-specific green rainwater infrastructure, including green roofs, recessed green spaces, infiltration paving, shallow vegetation trenches, and a rainwater collection and utilisation system, rainwater was turned into water resources during the construction phase. Solar energy, hot air technology, and wind-solar hybrid street lighting technology were implemented. The otherwise grey infrastructure of the city became the testing grounds for green infrastructure implementation (Yang and Chai 2016). Through the promulgation of land use regulation at the urban scale, Shenzhen allocated its green coverage rate to reach 45% of the built areas, with the public green area accounting for 16.04 square meters per capita. The municipal government also allocated 32 billion RMB (roughly five billion USD) to support the Shenzhen Air Quality Improvement Action Plan. Shenzhen has also focused its efforts on expanding the benefits of green infrastructure to construct a green economy. It upgraded and transformed power plants, eliminating yellow-label vehicles and VOC treatments to reduce air pollution. It often sacrificed the city’s short-term revenue for long-term environmental gains. For example, although Shenzhen is China’s largest furniture export base, it recently sacrificed the city’s gratifying tax base by closing many heavily polluted production lines of furniture makers that did not fit the environmental standard, in an effort to ensure the benefits of prioritizing environmental quality when constructing its economic structural composition.

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3.2 Green Infrastructure in the Scenic yet Less-Developed City of Guilin Located in the northeastern part of China’s Guangxi Zhuang Autonomous Region, Guilin is a city connecting South China and Central China. It covers approximately 5,306 square kilometers of mostly hilly and karst terrain4 and boasts a unique natural landscape that features the scenic beauty of karst terrestrial characteristics. However, in recent years, Guilin has increasingly faced development bottleneck issues, including water pollution and its insufficient resource conservation capacity, as the city was exposed to a high risk of soil erosion, stony desertification, and slow economic growth (Zhang et al. 2020). As an SDZ, Guilin aims to improve its ecological environment and promote the development of its green industry by following the development principle of constructing “inclusive, safe, disaster-resistant and sustainable cities and human settlements.” Regarding the landscape dimension of green infrastructure, since 1999, Guilin has been improving the quality of water and linking the four water bodies, including two major rivers—Li River and Taohua Riverand four lakes that constitute the scenic core of the old city, into an urban green corridor. Its comprehensive treatment of the waterbodies included freshwater diversion into the lakes, the dredging of silt from the lakes, the restoration of ancient waterways, and the installation of sewage interception systems. A series of water conservancy engineering measures were put into place to achieve the formation of a linear ecological zone dominated by rivers and lakes. Along with the linear water network, a variety of vegetation was planted and nurtured to help reduce the heat island effect of the central city as well as store rainwater and purify the air through a high-quality green layer. However, the efforts in systematically expanding the green infrastructure in the city started to slow in the mid-2010s and have not been achieving much progress lately. For the urban system dimension, from 2016 to 2020, the Guilin Transportation Bureau actively promoted the use of green transportation systems, putting efforts into reducing the number of diesel trucks that exceeded emission standards, taking the lead in the prevention and control of pollution at the ports, and reducing petrol-fueled boats in rivers. The city also helped to carry out trials of gradually replacing petrolfueled vehicles on the road with electrical automobiles for green public transportation and logistics transportation systems. By the end of 2020, Guilin had a total of 1968 new energy operating vehicles, including 1,631 new energy buses, accounting for 77.5% of all buses operating in the city (Liu and Jiang 2021). In terms of the economic dimension, Guilin seems to have more generalised plans than detailed implementation. It plans to focus on green and high-efficient agriculture production to conserve its natural landscape resources, making efforts to promote ecological tourism, ecological agriculture, and culture cultivation, with particular 4

The word karst is a Germanized form of the name of a carbonate plateau. It is defined as a group of karst features including macroscopic forms and microscopic forms, surface forms, and subsurface forms, as well as dissolutional forms and depositional forms that developed under a similar environmental background.

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attention to the restoration and environmental protection of the karst rocky desertification areas. It has also planned to accelerate the concept of green manufacturing based on the development of green industrial parks at the national and regional levels, focusing on the greening of the manufacturing production process through waste recycling with low-carbon emission and intensive and clustered land use. Although both Shenzhen and Guilin as SDZs seem to have established multidimensional strategies in terms of utilising green infrastructure and its wider interpretation of the concept to promote sustainable development, given the different stages of their modernisation and the various levels of economic resources, the scope and depth of their green infrastructure implementation vary. Shenzhen has systematically pursued the implementation of the multi-functionality of green infrastructure, aiming directly to improve its residents’ quality of life, with a detailed concentration on macro- and micro-green strategies facilitated by an established evaluation system. Meanwhile, as a less developed mid-sized city, Guilin does not seem to have made much progress since establishing its status as a national SDZ. Its concrete implementation in achieving the listed greening goals has been limited to the construction of its green network at the city center, which took place years ago, and the reduction of petrol-fueled vehicles in the city. Its promotion of eco-agriculture and eco-tourism as a means for propelling economic growth while protecting vulnerable ecosystems still seems to be more of a vision than a reality.

4 Green Infrastructure-Focused Agenda in China: Comparative Studies With inspiration for integrating economic and ecological development, amidst its policy shift from growth-driven to the environment-focused pursuit, China’s two major campaigns of sustainable development—eco-cities and SDZs—adopted different approaches to and applications of green infrastructure. Created almost a decade apart, the two campaigns were embedded into the continuity of China’s efforts in pursuing sustainable development, yet also reflected the specific socio-economic, political, and urban contexts of the different times. The eco-cities campaign was initiated from 2005 to 2008, when China’s gross domestic production (GDP) increased by double digits for several consecutive years and the growth rate of the country’s fixed assets investment surpassed 25% yearly on average. It was an era of undoubted optimism with the country’s confidence in the investmentled development model (Wang 2021). The eco-city in Dongtan Shanghai sought to become the first eco-city model ever built worldwide. Even its not-so-rosy temporary suspension did not deter China’s decision to pursue another eco-city demonstration project, the SSTEC Eco-City in Tianjin—this time with more concentrated investment, intensive centralised support, and a joint venture between the Chinese national government and Singapore’s national government. In comparison, the SDZs were initiated more than a decade later, in 2016, when China’s GDP had been in decline for

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six consecutive years, and the growth model based on fixed-asset investment, especially real estate investment, had lost its luster. For both the country and individual cities, searching for an alternative yet sustainable growth model at that time became imperative. The regional thinking and acceleration of new technology rendered a more systematic focus on green infrastructure as a critical force for growth. The different economic and political contexts of the two campaigns entail different planning and design approaches to green infrastructure and various dimensions of its application and impacts. As the understanding of sustainable development models has expanded, both theoretically and in practice worldwide, China has experienced its own learning curve on the environmental agenda, gaining experience and learning from both its successes and failures.

4.1 Planning Principles The difference in planning principles for eco-cities and SDZs is, first and foremost, reflected in site selection. Both eco-city pilot projects, Dongtan Eco-City, and SSTEC Eco-City, were built on largely vacant land and, in essence, were new town developments. Whereas Dongtan Eco-City was built on undervalued rural land near an ecological wetland, the SSTEC Eco-City in Tianjin chose a vacant brownfield site comprising mainly saltpans, barren land, and polluted water bodies from a wastewater pond of 2.6 square kilometers (Singapore Government Agencies, 2007). If the site choice for Dongtan seemed to be less sensitive to the environment as it placed a new town development near a wetland, the SSTEC project tied the idea of brownfield rehabilitation to the eco-city development, demonstrating a more progressive ecological rationale for site selection. That being said, the site choices of both eco-cities highlight a land-driven mentality and project-based approach. Meanwhile, for the SDZs sites, existing cities were selected, containing large and dense populations with high-density built environments. Without singling out the designated project sites by the national government, the SDZs were at the scale of metropolises. Shenzhen and Guilin were set as test grounds to address their unique bottleneck issues along the growth trajectories. Shenzhen was to address the conflicts between its limited resources and rapid growth, whereas Guilin needed to balance between ecological restoration and future development. As the two eco-cities were built on vacant land, large-scale master planning was done from scratch. For both Dongtan and SSTEC, the master planning envisioned a perfect city of the imagination. Advised by international experts, the plans depicted the future spatial structure of the city and functioned as guidelines for the establishment of the cities. The SDZs, in comparison, had no form-driven visual planning at the city scale. Rather than rely on a blueprint for new cities, the local municipal government was tasked with making long-term strategic plans, focusing more on urban policies as a catalyst than physical forms for urban regeneration, thereby reinforcing the green infrastructure layered on top of existing systems. The strategies

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for green infrastructure are required to be suitable for accommodating existent urban forms and dense populations. The planning processes and methods were also different for the eco-cities and SDZs. The former was based on collaborations with international domain experts to establish large-scale and visionary master plans; the latter relied heavily on local governments, using policy means to address local conditions and situations with acupuncture mentality and incremental planning methods. Eco-cities aimed to build a green network with a hierarchical structure from anew; SDZs (i.e., Shenzhen and Guilin) were to improve the existing urban fabric, reinforcing the interconnectivity of existing green resources to form a coherent network. Whereas the eco-cities pilot projects sought to demonstrate a scalable urban development model and master planning principles that could be replicated in other locations, the SDZs model explored a combination of urban policies and economic strategies that promoted sustainable development for unique localised conditions.

4.2 Design Approaches A common theme for both eco-cities and SDZs was to enhance livability for residents while nurturing the intrinsic values of the natural environment through green infrastructure. In eco-cities, the form and physical dimensions of green infrastructure were specific and given priority. In Dongtan Eco-City, the large-scale natural wetland was the focus of environmental protection. It became a focal point of the physical design of the form, guiding the programmatic organisation of the surrounding neighborhood. For the SSTEC Eco-City, a multiscale approach was applied to construct a hierarchical green network. Open spaces were linked by a meandering green belt, penetrating each district and linking various culturally themed public buildings. The green infrastructure became the most apparent visual design element and a spatial component of the city, integrating the “green valley”, “green corridor”, and “green cells” into one coherent urban design system. For SDZs, however, the green infrastructure focused on both the individualised forms of space and the construct of a multiscale network linked with green corridors, placing an emphasis on physical and functional connectivity. The potential of green infrastructure lay in its multi-functionality, reducing costs and tackling multiple urban problems. For example, during the renovation of a few residential communities in Shenzhen, adding a flood attenuation pond not only provided water management functions such as a storage area for floodwaters, filtration, and permeation but also created a locational identity as well as a landscape component for leisure and a habitat for flora and fauna. At the regional scale, Shenzhen reserves and locates large-scale parks in the inland and edge-conditioned wetlands along the coastal areas to form a continuous green belt throughout the city.

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4.3 Environmental Performance Indicators It is challenging to measure the environmental impacts of green infrastructure given that its implementation often extends along various time frames and involves multiple stakeholders whose focuses span physical, social, and institutional domains. For the Dongtan Eco-City project, environmental impacts tend to be quantitatively driven yet fragmented, focusing on individualised indicators, such as the specificities for the carbon footprint, energy reduction, and public green space per capita. However, the measurements of the environmental performance for the SSTEC project became increasingly systematic. A set of binding Key Performance Indicators (KPIs) was developed as benchmarks to measure the quality of development and implement a full life-cycle analysis of the project, including its green infrastructure. The KPIs were based on the national standards of China and Singapore as well as international best practices, compromising 22 quantitative and four qualitative indicators, which were categorised into three broad areas – ecological and healthy environment; social harmony and progress; and dynamic and efficient economy – each with specific measurements on green performance (Deng et al. 2020). The SSTEC was the first ecocity development to use the KPIs framework to guide its planning process and urban management system. The KPIs framework acted as a method of simplicity “derived from scientific evidence used to inform decision-makers on the key direction” (Deng and Cheshmehzangi 2018). Although China’s central government entities, such as the Ministry of Environmental Protection (MEP) and the Ministry of Housing and Urban-Rural Development (MoHURD), had already developed national standards for the environmental indexes of eco-cities (Zhou et al. 2012), the SSTEC KPIs were praised as “broader in scope, and, in part, more ambitious” than the eco-garden city standards regulated by the MoHURD and MEP, particularly on the specifications of greenhouse gas emissions, renewable energy, solid waste recycling, and water reclamation by the World Bank (The World Bank 2009, p. 4). While the green infrastructure played a significant role in propagating the idea of sustainable and ecological development in the eco-city model, its role was expanded in the SDZs to include multiple dimensions of sustainability that promote the construction of an “ecological civilization,” going beyond simply an “ecological environment.” The assessment of the green infrastructure for the SDZs shifted from the assessments based on the quality or quantity of built elements at the landscape dimension to the measurement of the quality of life at the urban level. For example, Shenzhen, as one of the SDZ pilot projects, concentrated its efforts on improving the city’s air and water quality. In the first half of 2020, Shenzhen ranked fourth among 168 major cities nationwide according to the Comprehensive Air Quality Index (CAQI),5 the highest ranking among the 20 metropolises boasting the highest GDPs in China. By the end of 2019, through the systematic use of sewage treatment,

5 The Comprehensive Air Quality or Common Air Quality Index (CAQI) was proposed to facilitate the comparison of air quality in Chinese cities in real-time. There are many air quality indices in use in the world.

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ecological restoration, river improvement, rain and sewage diversion, and other technologies, Shenzhen had successfully eliminated 159 large, polluted water bodies and 1,467 small polluted and odorous water bodies, improving the water quality of 310 rivers. All assessment sections for the five main streams in Shenzhen reached Class V and above standards for surface water (Bao 2021). Air and water quality at the urban level, a comprehensive indicator to which the green infrastructure effectively contributes, is tightly monitored in Shenzhen and has become a constant measurement of environmental quality. Both eco-cities set the goal at the building level to achieve a full 100% of green buildings. For the SSTEC, a set of green building evaluation standards (GBES), a hybrid between Singapore’s Green Mark system and China’s Three Star rating system, was established as a guideline for architects and developers to follow. The proposed GBES encourages passive design features to lower the cost of green buildings. In the SDZ of Shenzhen, sustainable thinking goes beyond green building specifications. It includes a comprehensive evaluation of many aspects of community living, both for the physical environment and the measurement of life quality based on ecological standards. The “General Specifications for Ecological Community Evaluation,” the first standardised evaluation system, addresses the core of ecosystem services that the green infrastructure is to serve. The approach reflects an expanding understanding of sustainable urban development. That being said, there is still a lack of in-depth research on the monitoring and evaluation of green infrastructure’s comprehensive effectiveness. China’s research and application of green infrastructure have mainly focused on the protection of natural systems, the integration with urban space planning, the construction of greenway systems, the usability of green infrastructure for recreational and cultural purposes, and the implementation of sponge cities. There has still been inadequate attention given to comprehensive ecosystem services that the green infrastructure offers.

4.4 Economic Consideration of Green Infrastructure From the project-based operation in the two eco-cities to using green infrastructure as a catalyst for establishing economic anchors for a green economy in Shenzhen, there has been a long journey in China’s pursuit of its environmental agenda. The lack of planning for the intangible aspects of new towns, such as job market creation and means for attracting migrants to newly built cities, led to unexpected economic losses. In the cases of Dongtan and the SSTEC Tianjin, both eco-cities aimed to absorb and reduce the burden of a burgeoning population in the nearby mega-cities of Shanghai and Tianjin. Shanghai Dongtan Eco-City was designed to reach an estimated population of 30,000 by 2010 and 500,000 people by 2040, and SSTEC Tianjin aimed to house 350,000 people by 2020 (The World Bank 2009). In SSTEC Eco-City, however, since the launch of phase one in late 2008, only 12,000 people and 1,000 enterprises by 2014 moved into the city (Wang and Mell 2019). The lack of population density hindered the development of urban amenities and led

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to insufficient attention being paid to cultural infrastructure investment . Likewise, Dongtan Eco-City also did not reach the estimated target population when the project was delayed due to financial constraints, a change in local government priorities, and environmental concerns. As a result, despite the extensive green infrastructure planned in both eco-cities, the lack of planning for the intangible elements of the city decreased the attractiveness of the projects. It led to negative economic impacts during the initial decade. The gap between the physical spatial planning and the intangible resource management of eco-cities revealed the inadequate economic planning and preparedness when confronting sustainable urban development in eco-cities. Thus, despite a clear vision and strong governmental support at various levels, eco-cities had to constantly negotiate with the tension between economic and environmental interests. Although green infrastructure played a promotional role in “branding” the eco-cities and elevating their green image, effective project delivery was not fully planned in the guidelines, leaving a high unexpected hidden cost that became a financial and economic burden. Consequently, the socio-economic development of the eco-cities was compromised by their environmental ambition despite the objectives. China has aimed to tie economic growth as a part of sustainable development, with the intention to build an ecological civilization. While the strategies of green infrastructure during the eco-city movement were aimed primarily at improving the physical quality of the environment and utilising associated ecological amenities to attract residents and business, for the SDZs, the concept of green infrastructure was broadened. The mission of the SDZs is, in essence, to search for a practice paradigm whereby green infrastructure can act as a medium and framework for delivering both sustainable economic growth and an ecological environment. Green infrastructure is thus interpreted as the infrastructure of a green economy. It has expanded to include a large array of technological and innovative measures that address sustainability issues beyond the physical network of the urban system. In the two SDZs of Shenzhen and Guilin, particularly in Shenzhen, the application and interpretation of green infrastructure have focused on optimising the industrial structure and transforming production channels to improve the quality of the environment for the long term. Shenzhen has pursued selective industry focus, with “light (industry), refined (production), high (value-adding process)” as priorities in the establishment of innovative production sectors. It identified seven strategic industry anchors, including energy, biology, internet, finance, logistics, culture, and hightech, with the last four as pillars of the local industry growth. Among them, energy is a new industry recently established, with high-quality clean energy as a focus. Innovation is regarded as the pathway to identify and locate the “secret ingredient” of establishing a green economy, that is, an environmentally oriented economy.

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4.5 Social Vitality of Green Infrastructure The social consideration of green infrastructure often highlights how green infrastructure’s design, planning, and implementation addresses users’ needs. Two social impacts are often discussed in the literature: social equity and the well-being of ordinary citizens. Regarding social equity, for the Eco-Cities, given its project-based approaches and real estate-led financing mechanisms, while there were master plans that reflected future visions, the social aspects were less developed. For Dongtan Eco-City, in the bidding process of locating developers for construction, “individual developers were not required to address these (sustainability or green elements) requirements in the tendering process in a systematic way.” Thus, there lacked a “clear linkage between the plot requirements and the city-wide requirements (stipulated at the master plan level)” (Deng et al. 2020). Consequently, implementation carried out by individual developers failed to address the sustainability objectives and social needs of residents at the parcel level. In addition, to fully achieve targeted green standards of building 100% green buildings, the construction cost was increased with a 30–40% premium above regular costs and rendered newly built houses unaffordable for many, and the cost of eco-friendly energy generation also increased for existing residents in the vicinity (Shang 2018). Another major social benefit of green infrastructure that has often been studied is how green infrastructure brings together cultural/human activities by creating better environmental quality and generating a greater sense of place. The measurement of the social outcomes of green infrastructure thus often concentrates on the dynamics established between people and the constructed green space and its network effects, including the popularity of green infrastructure as a site for social capacity building and as a medium for improving well-being of citizens. In this context, we collected the rating data from social media as a proxy to measure the usability and popularity of key green infrastructure components embedded in the Eco-Cities of Dongtan and the SSTEC Tianjin and in the SDZs of Shenzhen and Guilin. It is increasingly important in the domain of urban studies to use big data generated through social media (online social networks) and point-of-interest data to understand location-based human dynamic distribution, behavior, and highdensity urban environments (Chen et al. 2019; Huang et al. 2020). Our purpose is to understand the location-based social vibrancy of the key components of green infrastructure in the four locations to compare their perceived popularity. Fifty critical and different types of green infrastructure elements of the four pilot projects were identified, including public parks, natural and semi-natural urban green spaces, public civic places, water bodies, natural reserves serving as green corridors, regional and urban forests, and newly designated national parks. The list ranges from intensively cultivated controlled and managed public areas to areas where control appears minimal, and “natural” rather than “man-made” elements are dominant. The category of natural and semi-natural urban green spaces includes areas such as grasslands, woods, forests, water areas, cliffs, coastlines, and beaches. Some of these locations

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serve recreational, aesthetic purposes and may include cultural heritage sites, while others offer various combinations of different urban functions. We then downloaded the green space and boundary maps from Google Map, Gaode Map, and ArcGIS of these localities and used cartographical coordinates to map the identified green infrastructure locations. In total, 79,095 user online reviews and ratings regarding these critical green infrastructure elements were collected from a popular Chinese social media App, Dazhongdianpin. Better visualise locations in relation to its popularity and user frequencies as reflected through the number of online reviews collected, we used the size of the mapped dots to correlate with the numbers of reviews on social media and marked the rating scores from the social media next to the location dots on the maps (Figs. 2, 3, 4 and 5). Respectively, a dot of 6 × 6 pixels represents a location with comments fewer than 500 on the social media App; a dot of 12 × 12 pixels represents a location with comments between 500 and 1,000; a dot of 24 × 24 pixels represents comments between 1,000-3,000; a dot of 8 × 48 pixels represents reviews between 3,000 and 5,000, and a dot of 96 × 96 pixels represents a location with 5000–7000 reviews. The ratings listed are the average ratings in association with the green infrastructure element identified, with 5.0 being the most satisfying experience that users gained from this location and 1 as the least satisfying experience for users.Dongtan From the visualisation maps, a connection was established between the locations of critical green infrastructure elements in each city and the vibrancy and popularity of the places represented by online review volume and rating scores. It is evident that the two eco-cities of Dongtan Shanghai and SSTEC Tianjin have fewer networking effects from the green infrastructure than the SDZs of Shenzhen and Guilin. Dongtan and SSTEC each have one or two independent locations that draw more visitors/users than the remaining locations within the areas. While the number of people they attracted was impressive due to the proximity to Shanghai and Tianjin, two metropolises, there is a lack of interconnectedness among different elements of the green infrastructure. Meanwhile, the green infrastructure is well connected in the two SDZs locations of Shenzhen and Guilin, although key green infrastructure elements are more expansive and have wider coverage in the territory of Shenzhen than in Guilin. The network effect of the green infrastructure in Guilin concentrates only in the old city center of Guilin surrounded by the famous karst terrain and water scenes, beyond which there have been barely any newly developed or improved green infrastructure that is vibrant in attracting users. In Shenzhen, almost every district has locations with large-scale green infrastructure that boasts vibrancy. Shenzhen has a significantly lower variation (0.82 for comments and 0.012 for rating) compared to the other three cities. This demonstrates that Shenzhen’s critical locations of green infrastructure enjoy more visits and consistently boast higher evaluations. It has the highest average review volume for each location (2,173.7), with the highest average rating (4.91). Given the consistent efforts in Shenzhen to improve the urban physical environment over the years and active management and promotion of green infrastructure and green economy by the government, the popularity of Shenzhen’s key green infrastructure elements among

Fig. 2 Mapping of users’ comments and ratings on components of urban green infrastructure located in Dongtan (Chongming Island), Shanghai (Source compiled by Authors)

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Fig. 3 Mapping of users’ comments and ratings on components of urban green infrastructure located in the SSTEC, Tianjin (Source compiled by Authors)

users is not surprising. On the other hand, Guilin does not seem to have generated effective strategies in dealing with its increasing pressure to balance the protection of its environmental resources for sustainable development and as a revenue source.

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Fig. 4 Mapping of users’ comments and ratings on components of urban green infrastructure in Guilin (Source compiled by Authors)

5 Conclusions This chapter traced the evolving proposition of green infrastructure in two of China’s most significant sustainability campaignsthe Eco-Cities movement initiated in 2005 and the Sustainable Development Zones campaign in 2016. Through a comparative

Fig. 5 Mapping of users’ comments and ratings on components of urban green infrastructure in Shenzhen (Source compiled by Authors)

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lens, the chapter explored and presented how green infrastructure was utilised with a multi-scale approach to facilitate the country’s effort to pursue environmentally conscious development. From landscape and ecological dimensions to embedded benefits represented in constructing urban systems and economic production, green infrastructure’s multi-functionality and its broad range of applications were delineated and reflected in the context of China’s search for a sustainable development paradigm. The utilisation of green infrastructure and, to a large extent, sustainable development models in China has been adopted with an experimental, evidence-based approach. The four projects in the case studies are all pilot projects, with the intention and promise that their approaches, principles, and methodologies can be emulated and expanded in different locations throughout China. Initiated as joint ventures with international experts and as a borrowed concept, Eco-Cities utilised green infrastructure to protect biodiversity and facilitate environmentally conscious urbanism in both Shanghai Dongtan and SSTEC Tianjin. While the two projects are still to some extent ongoing, the many unexpected setbacks in the process attested to the complexity of implementing sustainability across its basic tripartite dimensions: economy, environment, and (social) equity—often known as the “three E’s” of sustainability (Wheeler and Beatley 2002). In the SDZs initiative implemented ten years later, China charted its own course for a sustainable urban model, with the hope of fitting into local conditions and context – a pathway not unfamiliar to many pursuits in the country’s modern history for better growth and development (Wang 2010, p. 112). Instead of using a natural wetland as a core to organise residential development patterns, such as in Dongtan, or constructing the layered organisation of green systems, such as in the SSTEC, the project-based and physical form-oriented design and planning approaches to green infrastructure of the Eco-Cities were altered in the SDZs campaign. This time, accompanied by a broader understanding of green infrastructure and lessons learned from different sustainable development models worldwide and within China, the application of green infrastructure in the designated SDZs, especially in Shenzhen, was extended to various scales, including community, district, and regional scales, and with multi-dimensions–namely, environmental, economic, and social. The network effects of green infrastructure were expanded and reinforced. An experiment with local governments took the lead in utilising urban policy and strategic institutional building as channels to build green infrastructure and expand to a green economy. This constant trial-and-error process embodied in the Eco-Cities and SDZs campaigns does not seem to have reduced China’s enthusiasm for searching for a model that integrates environmental protection with economic growth. After experiencing its learning curve and realising that there was no readily available international model to adopt, China’s recent confidence in leading the way towards an ecological civilization has grown increasingly firm. There is still a long way for China to find the most suitable model for sustainable urban development, not least of which is applying green infrastructure in many urban settings and scenarios. Yet, Shenzhen holds promise in practice as a city. With one of the fastest-growing economies, Shenzhen has been leading via an increasing presence of green sectors, simultaneously

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being a city with some of the best air and water quality and lowest carbon emissions among Chinese metropolises. The city’s green infrastructure continues to make gains in popularity and contributes to the social vibrancy of its urbanism. That being said, the challenge for Shenzhen and China overall is to deepen the understanding of multi-layered benefits of green infrastructure in providing comprehensive and diverse ecosystem services, thereby fostering an ecological integration of the planet, humans, and society.

References Bao R (2021) Shenzhen ecological civilization progress and future. Harbin Industrial College Publication 23(1) Benedict MA, McMahon ET (2006) Green infrastructure: linking landscapes and communities. Island Press, Washington, D.C. Castle H (2008) Dongtan, China’s flagship eco-city: an interview with Peter Head of Arup. Archit Des 78(5):64–69. https://doi.org/10.1002/ad.741 Central Government Document (2019) Opinions of the Central Committee of the Communist Party of China and the State Council on Supporting Shenzhen to Build a Pilot Demonstration Zone of Socialism with Chinese Characteristics. http://www.mofcom.gov.cn/article/b/g/201909/201909 02900710.shtml. Accessed 6 Jan 2021 Chang CC, Leitner H, Sheppard E (2016) A green leap forward? Eco-state restructuring and the Tianjin-Binhai eco-city model. Reg Stud 50(6):929–943. https://doi.org/10.1080/00343404.2015. 1108519 Chen T et al (2019) Identifying urban spatial structure and urban vibrancy in highly dense cities using georeferenced social media data. Habitat Int 89:102005. https://doi.org/10.1016/j.habita tint.2019.102005 Cheng H, Hu Y (2010) Planning for sustainability in China’s urban development: status and challenges for Dongtan eco-city project. J Environ Monit 12(1):119–126. https://doi.org/10.1039/ B911473D Chinese Society for Urban Studies (2011) China low-carbon eco-city development report 2011. China Building Industry Press, Beijing Cugurullo F (2013) How to build a sandcastle: an analysis of the genesis and development of Masdar city. J Urban Technol 20(1):23–37 Deng W, Cheshmehzangi A (2018) Eco-development in China: cities, communities and building projects. Palgrave Macmillan, Singapore. https://doi.org/10.1007/978-981-10-8345-7 Deng W, Cheshmehzangi A, Ma Y, Peng Z (2020) Promoting sustainability through governance of eco-city indicators: a multi-spatial perspective. Int J Low Carbon Technol 16(1):61–72. https:// doi.org/10.1093/ijlct/ctaa038 Huang B et al (2020) Evaluating and characterizing urban vibrancy using spatial big data: Shanghai as a case study. Environ Plan B Urban Anal City Sci 47(9):1543–1559. https://doi.org/10.1177/ 2399808319828730 Joss S (2010) Eco-cities: A Global Survey 2009. The Sustainable City 2010. WIT Trans Ecol Environ 129:239–250. https://doi.org/10.2495/SC100211 Joss S, Molella AP (2013) The eco-city as urban technology: perspectives on Caofeidian International Eco-City (China). J Urban Technol 20(1):115–137. https://doi.org/10.1080/10630732. 2012.735411 Kambites C, Owen S (2006) Renewed prospects for green infrastructure planning in the UK. Plan Pract Res 21(4):483–496. https://doi.org/10.1080/02697450601173413

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Khaled R, Ali H, Mohamed EKA (2021) The Sustainable Development Goals and Corporate Sustainability Performance: Mapping, Extent and Determinants. J Clean Prod 127599. https:// doi.org/10.1016/j.jclepro.2021.127599 Kim C (2010) Place promotion and symbolic characterization of New Songdo City, South Korea. Cities 27(1):13–19. https://doi.org/10.1016/j.cities.2009.11.013 Li J et al (2021) Measuring performance and its influence factors of national sustainable development pilot zones in Shandong, China. J Clean Prod 289:125620. https://doi.org/10.1016/j.jclepro.2020. 125620 Liu CB, Jiang RX (2021) Implementing the five development concepts and building people’s satisfactory transportation. In: Summary of Guilin Transportation Bureau’s “13th Five-Year” Work. Guangxi Zhuang Autonomous Region Department of Transportation Bureau, May 11, 2021. jtt.gxzf.gov.cn Ng MK (2011) Strategic planning of China’s first special economic zone: Shenzhen city master plan (2010–2020). Plan Theory Pract 12(4):638–642. https://doi.org/10.1080/14649357.2011.626316 Ong CXY (2019) The making of an eco-city: an examination of the Sino-Singapore Tianjin eco-city as a new model of transnational new town development. MIT thesis, 2019 Roseland M (1997) Dimensions of the eco-city. Cities 14(4):197–202. https://doi.org/10.1016/ S0264-2751(97)00003-6 Shang A (2018) Whatever happened to Dongtan? http://shanghaiist.com/2008/06/24/whatever_hap pened_to_dongtan/ Shwayri ST (2013) A model Korean ubiquitous eco-city? The politics of making Songdo. J Urban Technol 20(1):39–55 Simpson R, Zimmermann M (eds) (2013) The economy of green cities: a world compendium on the green urban economy. Springer Netherlands (Local Sustainability), Dordrecht. https://doi. org/10.1007/978-94-007-1969-9 Singapore Government Agencies (2007) Tianjin | Who we are. Sino-Singapore Tianjin eco-city: a model for sustainable development. https://www.mnd.gov.sg/tianjinecocity/who-we-are#vision Sze J (2015) Fantasy Islands: Chinese dreams and ecological fears in an age of climate crisis. University of California Press, Oakland, CA The World Bank (2009) Sino-Singapore Tianjin eco-city: a case study of an emerging eco-city in China. World Bank Technical Assistance Report No. 59012, November 2009 The World Bank (2020) The World Bank | Data. https://data.worldbank.org/country/CN. Accessed 1 Aug 2021 To W-M, Lee PKC, Lau AKW (2021) Economic and environmental changes in Shenzhen—a technology hub in Southern China. MDPI Sustain 13(10):7–8. https://doi.org/10.3390/su1310 5545 Wang B (2010) Cities in transition: episodes of spatial planning in modern China. In: Patsy H, Robert U (eds) Crossing borders: international exchange and planning practices, Ch 5. Routledge, London, New York, pp 95–115. https://www.taylorfrancis.com/chapters/edit/10.4324/978020385 7083-14/cities-transition-episodes-spatial-planning-modern-china-bing-wang Wang B (2017) The design of real estate: a framework for value creation. In: Graham S, Erwin H, Richard P (eds) Routledge companion to real estate development, Ch 25. Routledge, London, pp 338–352. https://www.routledgehandbooks.com/doi/10.4324/9781315690889.ch25 Wang B (2021) The evolving real estate market structure in China. In: Bing W, Tobias J (eds) Understanding China’s real estate markets: development, finance, and investment. Springer, Cham, Switzerland, pp 9–19. https://link.springer.com/chapter/10.1007/978-3-030-71748-3_2 Wang B, Just T (2021) Understanding China’s Real Estate Markets: development, finance, and investment. (eds). 2nd edn. Switzerland: Springer Nature. https://doi.org/10.1007/978-3-03071748-3 Wang XK, Mell I (2019) Evaluating the challenges of eco-city development in China: a comparison of Tianjin and Dongtan eco-cities. Int Dev Plan Rev 41(2):215–242

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Design Solutions

Green Exposure as a People-Centered Metric for Green Infrastructures: A Shanghai Case Study Fabien Pfaender, Francesca Valsecchi, Xiulin Sun, and Wei Chen

Abstract Green Infrastructures refers to components of the built environment, encompassing various shapes and functions from leisure to utilitarian through aesthetics, including elements entirely natural to entirely artificial. In this spectrum of intrinsic natures, purposes, and sizes, green infrastructures are mainly defined as static objects placed into an environment. As such, the definition fails to depict the influence such infrastructures exert on urban dwellers. In this chapter, we propose the concept of “exposure” as a metric that considers green infrastructures not as static outcomes of planning and design but rather as a component of a dynamic relationship involving the citizens. Exposure recognises how many and which kind of infrastructures exist, and, most importantly, how accessible they are and where they are placed in ordinary commuting and living patterns. To validate the concept of exposure, we use a twofold data-driven methodology that combines a Quantitative space analysis approach (from the domain and the tools of urban data science) and a Qualitative Space observation approach (from the field and tools of design and planning). The chapter details the methodology and the quantitative and qualitative data used for the analysis, considering Shanghai as a proof of concept: we provide exposure assessment of 5,000 communities in Shanghai, integrated with fieldwork to detail the nature of each infrastructure and their capacity for interaction. Through this twofold exposure concept and assessment method, we look at the green infrastructures, their presence, and meaning, and understand their role for the community to better inform planning and design solutions from a dynamic perspective. Keywords Green exposure · People-centric metric · Green infrastructure · Data-driven · Shanghai · Quantitative space · Qualitative space F. Pfaender (B) Shanghai University, Université de Technologie de Compiègne, UTSEUS, Costech, Compiègne, France e-mail: [email protected] F. Valsecchi College of Design and Innovation, Tongji University, Shanghai, China X. Sun · W. Chen Center for Data and Urban Sciences (CENDUS), Shanghai University, Shanghai, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_10

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1 Introduction Green Infrastructures most often refer to a wide variety of components and elements of the built environment. Directly or indirectly, they aim to improve an ecological footprint. Such an acceptance encompasses a large variety of shapes and functions from leisure to utilitarian through aesthetics. It does so by including elements with no size constraints along a scale from entirely natural elements to completely artificial ones. In fact, in literature, Green infrastructures appear as a broad term with different nuances. For example, it may include assessing the “urban green” and its functional and aesthetic instances. It may also describe systematically the network of natural and semi-natural features appearing within and in-between the built environment. Green Infrastructures is a term used within the cities at the buildings, streets, and neighbourhood scale, as well as across cities, encompassing districts, communities, and towns: it can therefore include street trees, private gardens, roofs, parks, woodlands, to the larger scale of wetland and agricultural lands. Different disciplinary scopes in urban sciences aim to classify GI, resulting in several alternative taxonomies (Bartesaghi-Koc 2020; Honeck 2020). Such taxonomies usually share the common goal to rank GI to define ecological footprints such as climate change adaptation, biodiversity, and human health and wellbeing. In climate studies, for instance, taxonomies are built to distinguish different vegetation layers or differentiate ground surfaces from building structures (Bartesaghi-Koc et al. 2016) to measure greenery’s efficacy in climate mitigation. Another example is to look at GI from the perspective of environmental agencies such as EPA, which categorises GI according to their capacity to provide a “cost-effective, resilient approach to managing wet weather impacts”. In this way, GI is incorporated within the scope of regulatory planning and public investments (EPA n.d.). With such aim, GIs acquire a multifunctional role, being “elements of green” and also complements for water management, landscaping, biodiversity enhancement, Urban Heat mitigation, etc. The European Union, through different agencies and DGs, also is looking at the “identification, promotion and uptake” of GI as a part of the larger framework of Ecosystem Service, mainly as an asset for habitat restoration and enhancement of urban biodiversity (European Union. Biodiversity, Information System for Europe; Naumann et al. 2011; European Commission 2013; EU Commission DG Environment 2012). Architects and planners are also looking at GI as assets of future-oriented city development, and in some cases, reconfiguration, which can sustain social, economic, and environmental benefits (ARUP, n.d.). Such variegated interest from researchers, administrations, different urban stakeholders and agencies demonstrates that an overarching goal of all these classification and taxonomies is the protection and enhancement of GI as a vital instrument of planning and landscaping (UK Green Building Council 2015). Regardless of the formats by which GI are classified, as Honeck (2020) point out, “GI describes an interconnected network of natural and semi-natural areas designed and managed to deliver a wide range of ecological, social and economic benefits”.

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Therefore, this paper contributes to such exploration of benefits, relying on previous taxonomies and yet offering a specific and complementary contribution in the way GI can be analysed and assessed throughout a data approach. By proposing a methodology of mixed methods (analytics-driven by data science and qualitative driven by ethnography), we consider GI from the abstraction offered by the “green shapes” on publicly released maps and then providing an analysis of spatial occupation not in relation with scale and quantity, but with the dynamic perspective of potential access and practical usage. In fact, in the vast spectrum of intrinsic natures, functions, and sizes that taxonomies underline, green infrastructures are defined as static objects placed into an environment. As such, the definition fails to depict the influence such infrastructures exert on urban dwellers.

2 The Rationale of the Concept of Exposure Concerning Green Infrastructures This chapter discusses “infrastructures” as a potentially dynamic element of citymaking: we want to analyse and define green infrastructures by looking at the relational possibilities they open up to citizens. In fact, despite recognising infrastructures as elements of planning of the city, we also acknowledge that they represent affordance for the city’s living. How they are built and placed constitutes a very fundamental condition for the citizens1 to be exposed to them and eventually to be able to interact. Such affordance is not limited to the quantity of GI available or their distributions, but it suggests further questions about their nature and actual usages. To address this issue, we propose to introduce the concept of “exposure” as a metric that considers green infrastructures not as static outcomes of planning and design (like the physical materialisation of a decision making or design work) but rather as a component of a dynamic relationship between these infrastructures and the citizens. Exposure is a measure of the possibility of feeling, accessing, and interacting with green infrastructures that have hitherto been considered a lesser feature. We speculate that measuring such opportunity may represent the first step to include into the planning and landscaping efforts not only the notion of where to locate the GI, adding instead the consideration of which ones and for which reason they can be provided and maintained. The notion of exposure may contrast with the common sense acceptance that sensation and perception are “received’ and thus passive. Instead, it recognises them as the output of an “enaction”. In the words of Varela et al. (1991), the user’s perception of space emerges from the feedback loop of the user’s action within a space and the sensations that result from such actions. The more diverse the action capacity 1

We do acknowledge that affordance is not limited to humans: whereas it could be extended to multispecies, yet in this specific chapter we only consider the influences on citizens. As we mentioned, in literature, whenever GI has been considered within the framework of ecological and biodiversity restoration, it takes more often the naming of Ecosystem Service.

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is, the richer and more complete the perception of the space will be; imagine a lush flower bed on your walkway, in the two situations where you could adjust your trajectory and get closer, or where you could not. Would this be influencing the “perception” of the green? According to the “enaction paradigm”, the perception would be richer in the first case, ultimately translating into a higher exposure measure. In functional terms, to name an example, a green bed may play the same role if placed at the size of an urban highway or as a division area on the street side. Yet, the impression and the potential influence and interaction that it drives with people are different. The affordance of GI, and therefore its importance, results from the co-existence in the same space of the users and the city elements: such coexistence is about the presence and even more about behaviours. This concept also refers to the notion of “distance decay” as Tobler elaborates it in its “first law of geography”: he declares that perceived distance is a fundamental component of spatial significance. Thus the exposure to the green infrastructure is strongly correlated to the capacity of the user to interact physically with it regardless of what sensory attribute is invoked. We must consider the existence of spatial barriers between the city users and their environment as a fundamental component of the exposure measure: a mixedmethods methodology—the analytical lens and the qualitative lens—support one another in understanding the current status of GI and assessing its relevance on the scale of exposure. Indeed, this definition of exposure implies that the green spaces are accessible: exposure considers how many and which kind of infrastructures exist and how accessible they are and where they are placed in relation to typical patterns of commuting and living. In this perspective, a higher exposure signifying more green is less desirable than a better exposure where the quality of the user/environment dynamic is improved. We can draw two photographs from the dataset of the fieldwork to make an example of such a difference between higher and better exposure (Fig. 1). In Figs. 2 and 3, we can observe two ordinary greenery spaces and the sitting equipment. The Fig. 1 On the left, ordinary greenery on the sidewalk, with a sitting area. The position of the seats is relatively immersive into the green, although the seats are facing the street

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Fig. 2 In the right image, a green space within a compound: a parked car impedes the access and use of the sitting area

first image is taken on a sidewalk, the second image is taken from inside a residential compound. The methodology discussed in the paper is helpful to look at these photographs throughout data about the GI. The rationale of exposure considers such dynamic properties of infrastructures, which do not depend on quantity but from the context of use. How can the affordance of GI be measured and assessed? Which kind of uses does GI suggest in their spatial presence? How much are they exposed to access and use by citizens and social groups? How much of such use is guaranteed? We acknowledge that these are important research questions that this work can only partially address. Yet, they possibly sow a plan for future urban transformation beyond the shapes and means of planning as we know it traditionally. We believe that a convergence between data analysis capabilities and the urgent demand for environmental awareness can inspire, if not help, the transition towards future urban planning models. With this chapter, we take the first step into this direction: starting from the data representation of the city, we describe the composition of the green infrastructures and their implication with urban life patterns, using a mixed-method approach that combines analytical assessment and qualitative evaluation.

3 Methodology of Analysis To explore the concept of exposure as the capacity of the user to experience green spaces, we propose to perform an exploratory analysis of urban green infrastructures with a strong emphasis on its accessibility as a potential for interactions.

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Fig. 3 Plot of urban green infrastructure within Shanghai administrative zone excluding Chongming district

3.1 Area of Interest Although urban greenspaces in China are vast and extraordinarily diverse, we chose to limit our study to the city-province of Shanghai. There are two main reasons for this. The first reason is that Shanghai municipality covers 6,341sq km and hosts a large variety of urban conditions: newly expanded urban space in suburban areas like Songjiang town in Yueyang sub-district, older westernised spaces in former international concessions, a variety of agricultural and sub-agricultural land. The fact that Shanghai offers such a variety provides us with an excellent testing ground for the concept of exposure. Furthermore, the area is restrained enough to allow a computationally reasonable data harvesting and exploratory data analysis. Additionally, in the “Shanghai 2035” master plan, the Shanghai municipality proposes “more emphasis on green development” as one of the five strategic directions for the next city development. It announces the intention to increase the green spaces to attain 60% of the total land area in the whole prefecture, including its most peripheral communities away from the CBDs, including 23% of forest coverage and 13 sqm pro capita (Shanghai Urban Planning and Land Resource Administration Bureau 2018, pp. 24–25). Shanghai consequently provides a well-suited testing ground for

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a green infrastructure exposure assessment at a reasonable scale with an underlying urban planning agenda increasing the stakes of our measures. The second reason is a scientific methodological advantage. Shanghai municipality proposes many urban open data through different beneficial initiatives when doing a large-scale, composite, greenspace assessment where other cities only offer a limited amount of data. This data accessibility and completeness at the municipal scale is vital to conduct a GI study encompassing all the possible urban and rural conditions.

3.2 Visualisation-Driven Quali-Quantitative Methodology In order to validate the concept of exposure, we use a twofold methodology that combines a Quantitative space analysis approach (from the domain and the tools of urban data science, including Geographic Information Systems) and a Qualitative Space observation approach (from the domain and tools of design and anthropology). Such a methodology closely follows the principles of Exploratory Data Analysis (Tukey 1977; Andrienko and Andrienko 2006), where data and relations are systematically analysed using visualisation to drive the study. Hence, the visualisations within this chapter are building blocks of the research process; they were not produced as outcomes of the analysis to communicate results. Instead, they are designed as systematic hypotheses exploration apparatus. Furthermore, it is essential to consider that such methodology is not performed in a linear timeline but in an integrated and mutually informed way: the quantitative analysis performed hereafter lacks in particularity and multiplicity what it gains in universality and transcendence (Latour 1999). Its accuracy depends on an extensive comprehension of the ground reality provided by the qualitative investigation. In turn, the latter acts both as an insights provider and a crucial, grounded, conceptual safeguard the quantitative analysis amplifies.

3.3 The Dataset The exposure concept takes its source for our team in a long-term, de facto limited, investigation of nature in cities. Available municipal natural data, including GI, are scarce and confined to particular scientific domains such as remote sensing, or urban planning,2 while business-related or civic data providing direct economic or political opportunities abound. Thus, a novel dataset published as a map API3 in one of the Shanghai Government open data initiatives offered a perfect opportunity to develop this concept. The map features all urban greenspaces, from trees to parks 2 3

None of which is the authors’ primary domain. The API is accessible at http://lbs.tianditu.gov.cn/staticapi/static.html, last access May 27th, 2021.

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and flowerbeds, from compound gardens to street furniture and impervious elements, roads with four levels of importance (highway, link, primary road, and other roads), buildings, and waterways. The dataset has been built harvesting on a series of such indicators, throughout the following steps: (1)

(2)

(3)

As with most online maps, this map is a tileset, i.e. precalculated small squared pictures that can be accessed individually with an URL. This access can be automated using a computer script. Map tiles details usually differ with the chosen map zoom level 1 for the entire world, up to 18 for a fraction of a building) to help users orient themselves. For example, the green areas were exhaustive in this open map when the zoom level was relatively high. Naturally, with a higher zoom level, it takes more tiles to cover an area. To gather the whole map for Shanghai Municipality, it was necessary to download 358,263 tiles in the PNG picture format. Each tile takes approximately one second to download at best, so the elapsed time in the best conditions is a little more than four days. Once downloaded, the tiles need to be reassembled to create a single large picture of the whole municipality.4 The final map is just a single picture with no geographic attributes. Hence, it must be geolocalised into a WGS84 Mercator projection using a series of anchor points of WGS84 known coordinates. We saved it as a GeoTIFF picture. This picture alone weighs almost 90 Gb which makes it very hard to manipulate properly on most personal computers. It also limits the scope of field researchers (i.e. not computer scientists) adequately capable of dealing with such a problem, subsequently limiting analysis capabilities. As such, the dataset was not directly suitable for further analysis. GeoTIFF is a transition format not meant for computations, so an additional step is necessary: transform the picture into a more manipulable geometric representation, namely polygons, to simplify all further analysis. As most software and tools are incapable of handling such a large dataset, either refusing to open it or being extremely slow, we opted for a custom python language computer script. The script extracts the three red, green and blue channels of colours of the GeoTIFF. Using manually determined colours, the script then detects the colours associated with green areas and other general urban space elements (water, buildings, and impervious elements). All areas of each urban space element are converted to geographic polygons and saved in a computer ready format called parquet. The parquet file for each space element weighs 2.5 Gb.

It is essential to notice that as a result of this process, the polygons contain no detail about the nature of the green infrastructure. They just represent a geographic shape. Only a cross-reference with other datasets containing Point of Interest (POI) information would allow for a complex annotation process, but this is beyond the scope of this chapter. Thus the exploratory analysis is based on an area surface, 4

The islands of Chongming, Changxing and Hengsha (Chongming district) are not part of the dataset as we found some inconsistencies in the tiles from the islands so we chose to exclude the whole islands from the present dataset.

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spatial proximity, shape, or relations with other categories of space elements such as buildings or roads but not on a greenspace taxonomy prior knowledge. In Fig. 3, we plot the layer of green infrastructures without any other element. At first glance, we can see the city’s geography, evident in its major geographical and architectural features, such as the rivers and some other water bodies, the airports, the road rings. Other elements that can be intuitively seen are significant urban spread crystallised in suburban districts like Songjiang, Jiading, and Qingpu. Such intuitive observation does not bring insights per-se. It merely confirms the validity of the dataset as it is evident that major residential districts have less green than peri-agricultural areas. However, this global map is not enough to demystify common theories about green, such as higher real estate prices in greener areas or the livability of such areas, etc. It confirms one crucial point: this spatial visualisation and the underlying dataset serve as a starting point for our inquiry: visualising the position of the GI does not say enough about their quality, their accessibility, and their use. Additionally, such reading is important to give a first overview of our experimental ground, valid for the experiments we present in the next section.

3.4 Description of the Analytical Zooming We conducted a series of general analyses using the whole green dataset (see Sect. 4.1), particularly assessing different surface elements and their ratio in the entire municipality of Shanghai minus Chongming District. We also created an exposure indicator using a buffer around roads (see Sect. 4.2) using the whole dataset. The next step is to investigate the green exposure and quit the polygons dataset continuum and aggregate key indicators. Several aggregations techniques are possible, from a grid of hexagons or squares to less uniform grids to administrative boundaries. We chose to work with the latter for Shanghai. Several levels of administrative boundaries exist for this province-city. We wanted to use an aggregation close to the block level to reflect the different strategies (economic, health, mobility, energy, etc.) each block can have in implementing urban green space to analyse exposure. At the same time, we had a dataset available with a large-scale census of the Shanghai neighbourhood conducted in Shanghai University School of Sociology. This census operates at the community level, also called the village level. It proposes several key statistics useful to evaluate the impact on people of green spaces around them. There are 5,264 communities at the community level within our experimental boundaries, each with a population of an average of 5000 inhabitants. A community encompasses one or two blocks with an average area of 1.1 km square (1 km x 1 km). It can be a compound or two in a dense urban area but spread to a much larger area in rural Shanghai. Contrary to neighbourhood level boundaries in China, the corresponding grid of communities covers the whole territory. Moreover, it is not uniform. It follows urban sprawl: the grid is denser, with smaller communities closer to CBDs or downtown (defined by highway rings contouring them). It becomes less

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dense with larger communities as the distance from downtown increases. The nonregular grid is also advantageous for aggregation as an adaptive non-uniform grid better matches urban dwellers’ real-life interactions and mobility capacity. We use this grid for medium-scale green exposure indicators analysis. Furthermore, most of the visualisations in this chapter use the choropleth map technique for advanced reading of maps. The choropleth grid is based on the community boundaries. To facilitate analysis and increase the reading abilities, we split the communities into four classes using the quantile (25%, 50%, 75%, and 100%) of the communities’ surface distribution in square meters. As visible in Table 1, the urban characteristics of each quantile is specific: the smaller ones, Quantile 25 to 50, correspond to high density, downtown or suburban new CBD areas with low green ratio and high building ratio, whereas the Quantile 75 and 100 correspond to rural and agricultural part in concentric circles around the CBDs with higher green ratio, higher waterway ratio, and lower building ratio. Given these characteristics, we used the quantile categorisation as a proxy of the urbanisation index. Additionally, each quantile has been associated with a specific colour using a perceptually uniform colour scale. The colours per quantile are consistent throughout the whole chapter to facilitate visualisation interpretation. Table 1 Global assessment of urban element layers in the Shanghai study area. It features the total area, community/area aggregation, and community/area quantile statistics with absolute surface and ratio Layers Overall Green Buildings Imprevious Water area (km2 )

5889

2375

537

217

805

area ratio (layer n/overall)

–

40%

9%

3%

13%

mean village area (km2 )

1.11

0.43

0.1

0.04

0.15

mean village area ratio (layer n/overall)

–

38%

9%

3%

13%

mean village area (std)

3.78

1.51

0.21

0.06

1.48

mean Quantile 25 area (km2 ) 0 < village area 0.066 ≤ 0.164 km2

0.011

0.018

0.025

0.001

mean Quantile 25 area ratio (layer n/overall) –

17%

28%

37%

1%

mean Quantile 50 area (km2 ) 0.164 < village 0.14 area ≤ 0.314 km2

0.031

0.031

0.034

0.004

mean Quantile 50 area ratio (layer n/overall) –

21%

21%

23%

3%

mean Quantile 75 area (km2 )0.314 < village area ≤ 44 km2

0.11

0.075

0.055

0.07

22%

15%

11%

14%

3.75

1.56

0.29

0.05

0.53

–

41%

7%

1%

14%

0.50

mean Quantile 75 area ratio (layer n/overall) – mean Quantile 100 area 44 km2

(km2 )village

mean Quantile 100 area ratio (layer n/overall)

area >

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After focusing on the communities as an aggregation grid for a grid-enabled analysis, we focused on 170 communities for which we have detailed information. This dataset is an unbiased sample accounting for 3% of the whole communities’ dataset. The dataset is the result of the “Shanghai Urban Neighborhood Survey” (SunS), a large-scale regional survey on urban community research conducted by the Center for Data and Urban Sciences (CEDUS) of Shanghai University (孙, 2018), and it consists of a sampling of Shanghai residential communities (170 in total). Through social surveys of urban and rural households in Shanghai, it collects research data about social change trends to provide data support for academic research and policy decision-making. The dataset offers a series of quantitative metrics to produce more inference about the exposure of such GI, and it seems appropriate to use such metrics concerning Green Exposure. Once such zooming is complete, the analysis moves to a fieldwork phase, going back to the communities at the street level for a 1:1 scale observation of the GI and assessing the findings.

3.5 Description of the Mixed Methods: The Qualitative Outlook While the analytical approach on the polygons dataset has generated insights about metrics and indicators of classifying GI in different city zoning, absent from this quantitative approach are the details and the nature of each infrastructure and their capacity for interaction. For this reason, qualitative approaches such as space observation and sampling fieldwork are performed to refine the data analysis, provide crucial context to a necessary incomplete data-driven analysis, and inform the design practice that may ensue from the analysis. Leveraging the dataset of the 170 communities we used for the zoning, a further reduction has been made to 7 communities we visited. An “exploration guide has supported such sampling fieldwork”: a booklet of maps generated as well from the main dataset, through a slicing script,5 which would show the main components of the green in each area, and would include the indicators used in the analysis. More details will be offered in the next section about the qualitative analysis, yet it is evident that due to the size of our datasets (both the green map and the communities zoning), the production of such a fieldwork guide would have taken enormous amounts of work if done manually. Exploration has been done by foot, regardless of the weather or the time of the day, and aiming to collect a series of photographs as standardised as possible: 1. 2. 5

A view from the centre of the streets in front of each residential unit entrance A view at 15mt within the entrance

https://github.com/fpfaende/green-exposure-book-chapter/blob/main/book-exploration-guide. ipynb.

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Details of major GI composition and forms When available, images of possible interaction by people When available, other interesting details about use, misuse and dysfunctions.

The collection of images is made publicly available,6 and it will be discussed in the next section.

4 Shanghai Green Infrastructure and Exposure Analysis This section uses the process of scaling/zooming introduced in the methodology to explore the green exposure concept. The content of this section not only sheds light on the exploratory data analysis approach, de facto data-driven, but also discusses its relevance while used in combination with the situated insight of the ethnographic outlook. Despite this chapter being dedicated to the concept of green exposure, not all analyses had it as a primary focus. In actual fact, green exposure is conditioned to the presence of green infrastructure, so both green infrastructure and green exposure received similar attention in the following analysis. We performed 6 analyses in total: (1) general overview of Shanghai green infrastructure and ratio of different urban elements; (2) first dedicated exposure indicator using road buffer; (3) per village green infrastructure distribution analysis with other urban elements; (4) second dedicated exposure indicator as the distance to green in Shanghai analysed per village and custom categories; (5) detailed analysis of the correlation of green infrastructure with six sociological census indicator to study exposure potential effects on citizens; (6) fieldwork of green infrastructure in context.

4.1 General Overview of Shanghai Green Infrastructure This overview aims to provide a global assessment of Shanghai green in itself and in relationship to the other urban elements. This assessment is on a par with international initiatives measuring or advocating for Green presence. For example, European Green Capital (European Commission 2021) uses various green ratios, building ratios, or impervious and water ratios to award greener cities. Shanghai area as studied in this chapter7 covers 5889 km2 . The green space itself covers 2375 km2 and represents 40% of the total surface. Green space distribution is not uniform, as it is visible in Fig. 3. Indeed, looking at green space in the categorised communities, green spaces go from 17% of the communities’ surface to more than 40%. It hints at a difference in green exposure for citizens that motivated the present study. 6 7

https://github.com/fpfaende/green-exposure-book-chapter/tree/main/figures/. That is without Chongming district.

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Green space area total is immediately followed in terms of size by water and waterways areas in conformity with the fact that Shanghai is both a coastal city and a city of canals. Part of the coastal communities include seawater within their surface. Still, communities bordering the river do as well, which become a significant percentage downtown where the Huangpu river is 400 m wide in communities of average size 66,000m2 (≈257 m x 257 m). For this reason, we created a total ground area without water and waterways elements when calculating the green ratio inside communities in Sects. 4.3 and 4.5. The building’s surface is also significant, especially in downtown areas. It is essential to notice the apparent negative correlation between green space and water increasing against buildings decreasing when leaving downtown to suburban and rural areas. Once again, this hints at a green exposure gradient increasing from downtown, suburban secondary CBDs and residential areas, and finally, rural areas. Impervious represents impervious land-use excluding highways and railways. The high ratio observed downtown could be partly due to parking and greenless mixed spaces built for a higher population density with higher standards sometimes owning a car they need to park. This is examined and partially confirmed in Sect. 4.6. The rest of the areas unaccounted for are most likely dedicated to highways and railways, but we did not include them in Table 1 as we do not have precise data in the same map dataset. This can be found in other datasets like openstreetmap.org under a different format but mixing datasets of different origins lower accuracy in this global assessment. Table 1 summarises the primary ratio for the total area, the area on a per village basis, and most notably, an aggregated mean and ratio for communities categorised by areas following the 0.25, 0.5, 0.75, and 1 quantiles described in the methodology (see Sect. 3.4). Although 40% in global green space appears to be considerable, considering the per capita Urban Green Space (UGS) is still a better measure for the Green Exposure concept compared to all international counterparts. Green exposure is a human interaction concept that incarnates partially into the amount of UGS available for each human. Shanghai Population in our area is around 23.7 million (Information Office of Shanghai Municipality & Shanghai Municipal Statistics Bureau 2019), so the per capita UGS equals 101 m2 /inh. This index is above the minimum recommendation issued by WHO of 9 m2 /inh., with an ideal of 50 m2 /inh. Of course, this necessitates additional detail as density in cities is rarely uniform, especially not in Shanghai, as Table 1 suggests. Moreover, this indicator is relatively common in the literature (Kabisch and Haase 2014; Rigolon et al. 2018; World Health Organization 2012) and allows for better comparison. Sadly, precise population density is not available in Shanghai. However, our communities census data contains the population estimate for 3% of the communities of this study, so we can calculate UGS per inhabitant on a selection of communities from smaller, highly urbanised areas to larger agricultural areas, as seen in Table 2. Table 2 shows a high disparity in the data (standard deviation is high) but shows a scale of per capita UGS going from 2 for the most urbanised parts to 400 and

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Table 2 Per capita UGS (m2 /inh.) in 170 communities categorised by total area. The total area is a proxy of an urbanisation level Community classification by quantile of total area

Standard count

mean

deviation

min

25%

50%

75%

max

Q25 smaller

51

2.9

2.2

0.1

1.3

2.5

4.1

11.4

Q50 small

39

5.7

3

0.3

3.4

4.9

7.2

11.7

Q75 large

32

16.4

12.7

3.8

8.5

12.1

19.6

53.6

Q100 larger

48

444.6

451.5

27.5

76.4

276.5

744.7

1696.3

more in less urbanised parts of Shanghai. It compares with Berlin where the target is 6 m2 /inh. or Leibzig where the target is 10 m2 /inh. It is also above the WHO recommendation for most of the population if we consider the most urbanised part. It suggests that Shanghai needs to intensify its effort to greenify better in the denser parts. Indeed, Shanghai’s target for its green park space is up to 13 square meters per capita but, more importantly, 4m2 per capita when it comes to community parks, small squares, and street-corner green areas (Shanghai Urban Planning and Land Resource Administration Bureau, 2018). Both these targets seem achievable and reasonable. The issue is to offer these possibilities to all citizens regardless of where they are. In addition, the disparity also suggests that most inhabitants are exposed to a smaller amount of UGS. To confirm this insight on green exposure, we also need to consider the interactions capabilities. For example, if all the green space is concentrated around the mobility paths, exposure can still be high even though the per capita UGS tends to demonstrate otherwise. We will investigate this hypothesis in Sects. 4.2 and 4.6. One last global analysis can be performed using the polygons in the dataset: shape analysis. Shape analysis is a typical analysis for geographic features, so it made sense to apply it here. Figure 4b shows a small extract of the global map in detail and reveals an extraordinary variety of shapes. The diversity and complexity of the shapes are such that only four classes of urban green spaces can be distinguished visually: Parks and gardens with smooth curves, clearly designed; sports fields with recognisable oval or square shape; very elaborated laced-like-shape of the compound or lilongs where green makes a deep etch the buildings; lastly, patches of very various shape and size filling many spaces in the city. We intended to qualify our UGS with this nomenclature, but with 1.5 million polygons, it was necessary to find a data analysis possibility of doing so. Unfortunately, all indicators of shapes (circular compactness, convexity, corners count, elongation, square compactness) (Basaraner and Cetinkaya 2017) we calculated could not distinguish these simple classes of shapes except for the sports fields. As it was imprecise, computationally intensive, and added minimal benefit to the green exposure concept, we chose not to incorporate a shape analysis in the present section. However, it might be helpful in the future if coupled with a complete POI dataset to get the UGS functions.

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The general analysis gave us an overview of the large dataset at hand and the global situation of green in Shanghai and compared it with other international cities. It suggests that exposure is not spatially uniform as access or interaction to UBS in Shanghai varies significantly. To better understand exposure, we chose to focus our attention on interaction, especially when the chances of interacting with UGS are high, that is when citizens are changing places.

4.2 Exposure Indicator Using 15 m Road Buffer This first exposure indicator aims to have an indicator of the quantity of UGS accessible to citizens to interact with when they move around the city. For example, users can encounter UGS as long as UGS is accessible or not blocked from view when using motorways or pathways in the cities. We chose to focus on a 15 m buffer around the ways that incorporate the pavements (4 to 5 m on average) and surrounding green space and possible chunks of parks or gardens. The 15 m buffer is chosen from ground observations to get all green spaces surrounding ways but stopping at buildings. To get the ways, we used another dataset collected from https://www.openstree tmap.org (OpenStreetmap 2021). We downloaded the whole Shanghai province map and used the python library policosm (Pfaender 2020) to extract all the ways with the highway tag. Thus, we obtain a dataset of all the ways accessible to pedestrians, bikes and mopeds, and motorcars in the city. Although motorcars are not our primary target as the level of interaction with UGS is very low, we kept their designated ways as urban planners and designers usually include many UGS around these ways. The highway tag that describes the type of way is aggregated into a level from 0 to 8.8 We do not need level 0 and 1 so they are excluded from the rest of the study. Level 2 is forbidden to motorcars and sometimes to bikes and mopeds. Level 7 and 8 are forbidden to pedestrians, bikes and mopeds. Using the geolocalised line of the way, we expand it to its boundary using the lane count and the lane width to obtain an elongated polygon resembling a 2D pipe. This polygon is then extended (bufferised) in all directions from 15 m. Inside this area, we intersect with the UGS from our original dataset, get the area of UGS for 8

Levels are aggregated into a ordered number using this dictionary of correspondence with tags: 0: construction, demolished, raceway, abandoned, disused, foo, no, projected, planned, proposed, razed, dismantled, historic. 1: stairway, stairs, elevator, corridor, hallway, slide. 2: services, bus, busway, bus_guideway, access, bus_stop, via_ferrata, access_ramp, emergency_access_point, emergency_bay,service, footway, traffic_island, virtual, cyleway, cycleway, byway, path, track, pedestrian, steps, platform, bridleway, rest_area, escape, footway, 3: residential, yes, unclassified, crossing, unknown,bridge, lane, ford, psv, living_street, alley. 4: tertiary, tertiary_link, turning_circle, road, roundabout, ice_road. 5: secondary, secondary_link, 6: primary, primary_link, 7: trunk, trunk_link, 8: motorway, motorway_link, ramp.

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Fig. 4 a Detail of Jing’an district area (left). b Detail of North ZhongShan Road area inside Jing’an district (right)

this way and normalise by dividing this area with the bufferised area minus the way area itself.9 We repeated this operation for all the 156,432 ways. We obtain a green space ratio inside the way buffer that is one green exposure indicator. It represents the potential of interaction with green space (see Fig. 5). This ratio is minimal as it contains part of the pavement, which is usually empty of green space. The hypothesis here is that green exposure measured as a green ratio of buffered ways should not be fundamentally different from the total green ratio and follow the same distribution with less deviation between the most urban ways and the more rural ones. From Fig. 4b, we also predicted that the smaller the level of the way, the more people would be exposed to green because the green in Shanghai is extremely composite and exploit many small areas to flourish. The higher the level, the less close to residential areas the less green we are supposed to find. We can observe this ratio in Fig. 6. It comes as a relative surprise that our first hypothesis is not confirmed. Rural communities do not have a better green ratio for buffered ways. In fact, it is the contrary that occurs where downtown or suburban areas get a higher ratio. This is visible on the map where the darker spots are in downtown or 9

The original way area contains no UGS so it can be removed.

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Fig. 5 Sketch of the settings to calculate the buffer indicator

Fig. 6 Per community Choropleth map of the mean ratio of green space against the ways 15 m buffered area

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newly developed areas. One explanation is that there is a greater concern downtown where space is scarce and green less present to expose people to it by putting green next to roads. Moreover, if this is true, our second hypothesis would also be confirmed because people live closer to low-level roads and only go to a higher level to move faster. So lower-level ways have more chance of being greenified to provide green to inhabitants, and higher-level ways have less green, so lower ratio. This is consistent with the map and the rural areas already filled with agriculture, so no particular effort is made to provide leisure or aesthetically pleasing greenery. We will also observe this phenomenon in Sect. 4.5. To verify the second hypothesis, we created the visualisations in Figs. 7 and 8. Figure 7 is a boxplot statistical visualisation of the green ratio for each level of ways. We can observe that the green ratio distribution goes lower when the level goes higher. It confirms the second hypothesis: effort in proposing urban green space is

Fig. 7 Green ratio in ways 15 m buffer per way level. The largest rectangle is the quantile 0.25 to 0.75 and contains the mean value. Other smaller rectangles represent the other quantile, enhanced for better visibility

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Fig. 8 Histogram distribution of the green ratio in ways 15 m buffer for level 8 motorway and motorway link with their kernel density estimation (KDE)

made close to low-level ways, closer to where inhabitants live. When they use the way to get faster, that is with higher levels, there is intentionally or not less green around. That is true with two exceptions. The first exception is level 2, where no motorcars are allowed. We might expect a higher level of green close to pedestrian ways, but we do not observe that. While exploring the distribution of level 2, we found that this level is misrepresented in Shanghai because it is found chiefly inside compounds or groups of buildings. However, our data source is not Chinese. It relies on public information available to all users globally, and this general public information primarily concerns roads in Shanghai, not pathways inside compounds. This is a known issue for Chinese users of OpenStreetMap and efforts continue to integrate more of this less critical level to OpenStreetMap. The second exception is level 8 and, to some extent, level 7. The green ratio in 15 m buffered ways of level 8 is very high, even though it is forbidden to all except

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motorcars which means less interaction and less exposure, as we suggested. Ground observation suggests that there is much land around the highways and that this land should not be used for buildings or for impervious elements as it shall not be permitted to park. The default is to put green around them. Moreover, when we look at the ratio for level 8 only in Fig. 8, we can observe a clear difference between the highways themselves, straight with no exits and motorway links that allow motorcars to get in and out. The motorway link buffers are much more green than the motorway itself. The motorway links of Shanghai can be seen in Fig. 9. So exposure as a green ratio of buffered roads is maximal when people are in their cars, focused on a driving change and therefore most likely oblivious to the additional green around them. This first exposure indicator proved helpful and yielded interesting results on the city designers’ and planners’ focus on UGS implementation. Greenifying the ways is a reality, and it is done to maximise inhabitants’ interactions in their short-distance local movements. Before we dive further into details with another exposure indicator derived from this one, we want to observe the per community Green Infrastructure Distribution and test some assumptions about the correlation between green space and other urban elements.

Fig. 9 Map of the level 8 motorway (greenish) and motorway link (purple) as extracted from Openstreetmap on the city of Shanghai. The motorway links with their higher green ratio have a distinctive curvy shape

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4.3 Per Community Green Infrastructure Distribution Analysis To better understand exposure to green, it is essential to understand its composition, especially at a decision-making level. The per community Green Infrastructure distribution goal is to confirm our assumptions, previously seen in Fig. 4 and Sect. 4.1 in an aggregated, non-uniform administrative boundary grid as explained in Sect. 3.4. These boundaries represent city planning and political decisions, so assessing UGS with this perspective makes sense as it drives the local implementations with policies and incentives. The community level is also in charge of part of the care of the green spaces. Figure 4 of the green continuum shows a gradually more significant predominance of green spaces when leaving downtown that is hard to qualify. The aggregated per community map yields a more accurate view of the green ratio. It also shows a significant disparity in size that illustrates the reason behind the categorisation in quantile seen in Sect. 4.1. The hypothesis we are pursuing here is that there is a high disparity in the green ratio with a circular gradient going from downtown to the outskirts. The green exposure capacity or potential follows the same circular gradient. Furthermore, the population density as approximated by the building ratio as its proxy also follows the same gradient but in reverse. So the greener the land gets following the gradient, the less the population is concerned. It bears consequences for the green exposure to influence planning and policymaking to reverse the exposure gradient. For these maps, we adapted the methodology as previously mentioned in Sect. 4.1 to remove the influence of water elements on the community’s total area. Thus, the green ratio and building ratio is calculated by dividing the green space in the community by the total ground area of the community without water or waterways. The main choropleth map of Fig. 10a shows the per community UGS versus total ground area ratio. It confirms a gradient of green ratio hinting at green not being uniformly developed but dependent on other factors. Moreover, even if the gradient of green ratio is still visible from downtown to outskirts, it is composite and non-uniform with pockets of low green ratio into otherwise high green ratio. Thus, there is little spatial continuity. Even downtown, where all the communities are supposed to have a high density of buildings with a low green ratio, there are pockets of flourishing green: parks. For example, Century Park in Pudong has a prominent influence to increase the ratio, but the newly built compounds include many UGS to raise real estate prices. Downtown Shanghai hosts a mix of these newly built compounds and traditional lower residential units, leading to a relative spatial discontinuity in green ratio. Then the gradient follows the suburban newly developed areas like Songjiang new town, where urbanisation has intensified, leading systematically to a lower green ratio. It is confirmed by Fig. 10b, showing the built ratio that follows a reverse gradient. Interestingly, the built diversity downtown is also very high, with even more contrast than the green ratio. It also hints at the alternation of residential building types inside the inner ring.

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An additional phenomenon is the existence of small seeds of urbanisation in small green spots in the rural parts where groups of buildings are built together to form highly urbanised communities with all their characteristics (small area, low green ratio, high built ratio). However, they remain isolated with a high contrast with neighbouring communities’ green and built ratio. All these phenomena, spatially diverse even locally, partial gradient from downtown to outskirts, pockets of urbanisations, and seeds of urbanisation advertise for careful construction of our green exposure concept. Consequently, Green exposure is not an effortlessly built indicator that can be computed the same everywhere. The urban situation of green spaces has many components and will affect the way citizens with different habitats, mobilities, and cultural habits will experience green. It

Fig. 10 a per community UGS versus total ground area ratio choropleth map of Shanghai experiment area (top). b per community built versus total ground area ratio choropleth map of Shanghai experiment area (bottom)

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Fig. 10 (continued)

is partly confirmed in Sect. 4.5 when we observe 170 communities to understand the possible way UGS affects inhabitants. This means that policies and planning aiming at smart greenifying cannot be simple global solutions but rather composite locally designed solutions that reflect the diversity of situations sustained by data and local anthropological understanding. When analysing exposure using this per community ratio, one last interrogation was the possible use of built ratio and green ratio as proxies of each other. Figure 11 hints at a correlation between the two, but the standard deviation is high, and there is high dispersion. Hence they follow patterns together, but one does not explain the other. We need to find other parameters to define the dispersion, such as those already described earlier in this section. Nonetheless, we can affirm that the more buildings there are, the less green is present, which is true when the communities become smaller. Therefore, it confirms

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Fig. 11 Scatterplot of buildings area ratio (y) and green area ratio (x) with their corresponding Kernel Density Estimation categorised by quantiles (hue)

that smaller communities are the more urbanised ones and that the 25% larger communities follow a specific pattern with communities having few buildings (left skewness a normal kurtosis of building ratio distribution of this quantile) but with many different green ratios (left skewness and negative kurtosis of green ratio distribution of this quantile). In conclusion of this relationship, we can say that green exposure for 75% of communities needs to consider the buildings as influential for the measure as there is an effect but not necessarily as a primary component. For the larger communities, green exposure itself will find various implementations that need to be explicitly considered. That will also receive partial confirmation in Sect. 4.5. Now that we have a better idea of the composition of the green ratio and its relation with the built ratio, we can try out another exposure index many cities advocate for, the distance to green space for every citizen.

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4.4 Distance to Green in Shanghai Even though each community gets a non-null green ratio, the green spaces inside the communities can be all in one corner, leaving inhabitants with a non-exposure to green even though the ratio says otherwise. This new indicator aims to inform this issue and measure the average distance to the next green space wherever the users are. Cities often advertise for access to green in 300 m (European Commission 2021; Kabisch and Haase 2014). The UK is more precise with the necessity of having a natural space of 2 ha 300 m from homes (Handley et al. 2003). Unfortunately, we do not have access to the details of the UGS, such as parks or natural spaces, to compare with these indexes. Nevertheless, we can get to a similar measure of the distance between every green space in Shanghai. The hypothesis here comes from qualitative observation where we encounter green spaces very often in downtown Shanghai. Therefore, we expect a gradient of distance to green relatively shorter when we leave downtown as more green spaces are in the outskirts. To calculate the distance between each polygon of green, we use a Voronoi tessellation (de Berg et al. 2000). It aims to partition space into regions where each region is closest to a set of points. We use the polygon centroids to partition space around them. As a result, we obtain region polygons around green polygons covering the whole space with no holes. To get the distance to UGS, we need to calculate the average distance one person needs to cover from the fringe of the region polygon to the fringe of the green polygon and repeat this operation 1.5 million times. We approximate this question by considering the region polygons and green polygons as circles to reduce computing time. It is computationally fast to get a polygon area, and knowing the area of its approximated circle, one can quickly get a radius. So we get the region’s radiuses and the corresponding green space radiuses. The distance the user has to cover anywhere in Shanghai to get to a green space is the region radius minus the green radius, like a buffer around green space. Having calculated this distance to the green approximated radius, we average it per community to obtain the familiar choropleth map one can observe in Fig. 12. The range of resulting radiuses is approximately 5 m to 50 m. Counterintuitively, downtown has a much shorter distance to green than suburban areas, including newly urbanised parts that do not share the same gradient like the green ratio. Downtown is also not wholly the shorter distance as if we look in detail, the fringes of downtown (corresponding to the inner ring) hold a better distance to green. Areas close to the sea or Huangpu river have a slightly longer distance to green as there is no green in the water. The mean distance to green on the whole map is 17 m, and 75% of communities have a distance to green less than 21 m which is a very short distance. For exposure, it means that most inhabitants can find a green space 21 m to wherever they are. Of course, the green space can be minimal as the dataset also contains flower beds, so ground observation is needed to verify this assumption yield by data. It is interesting to notice that neither green ratio nor distance to green nor exposure as a 15 m road buffer have similar patterns. They all point to different properties of green infrastructure, and it confirms that exposure to green is a complex

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Fig. 12 Per community distance to green space choropleth map with 5 classes of distance calculated with a Ficher Jenks Scheme

issue. We also verify this by using a boxen visualisation of the distance to green per quantile category. Figure 13 shows that the repartition of distance is not uniform in the more or less urbanised area. Figure 13 shows that the distance to green is minimal in more urbanised areas with a denser built environment and fewer green spaces. The reason is the systematic use of small areas like the street-corner green areas wished by the Shanghai Urban Planning and Land Use Administration Bureau (see Sect. 4.6). Again there is a shift between the 50% smallest community and 50% biggest where the exposure to green from road buffers indicator of Sect. 4.2 and from this distance to green radius is pretty low even though they account for the vast majority of green space. Such an effect is unexpected as rural life does not necessarily seem to equal higher access to nature or greenery, at least not directly close to home or during mobility. It results in our next question questioning the consequences of low green exposure on life satisfaction while we continue to zoom in on communities’ life with more precision.

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Fig. 13 Boxen visualisation of distance to green radius approximated per quantile category. The larger rectangle represents quantile 0.25 to 075 with the mean

4.5 UGS Correlation with Sociological Indicator in Communities’ Samples A common issue with large exhaustive datasets is that they adequately describe a single phenomenon but are hard to pair with equally complete additional datasets. It is particularly true in social sciences, where the study of human populations requires tedious work to get large-scale results and often ends up with an unbiased sample. Our urban element dataset pairing with communities boundaries makes no exception, and there is no available dataset of human communities census covering all communities. So instead, we turn to a sample of community census proposing a list of valuable indicators to pair with the same sample of our communities’ already calculated indicators. Details about the dataset are explained in Sect. 3.4.

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This pairing aims to examine various life satisfaction indicators and see if we can draw any relationship between green exposure and the more general green ratio. The hypothesis is that a high green exposure and green ratio can make life more satisfactory for inhabitants, emphasising the necessity to properly understand, plan, and design exposure to green spaces. To better grasp the location of the communities chosen in the sample, we first plot all the 170 communities on the map in Fig. 14a and b. In this figure, all the 170 communities are visualised. Communities entirely located in outskirt areas at the edge of a municipality have a larger size with a higher green ratio but a lower green exposure, whether the indicator is the 15 m road buffer or the distance to the green. In addition, the 170 communities sample contains an almost regular count of communities in the four quantiles selected in Sect. 3.4. The 170 communities dataset contains six social indicators we wanted to confront with green spaces. They are all graded from 1 to 5 to all inhabitants inside the community and averaged. Due to the nature of the question, some of these indicators have a narrow range of grades. We performed a standard scaler10 so scores appearing on the visualisations is not the original score but a standard scaled one. The indicators are: (1) the feeling of anxiety; (2) the feeling of depression11 ; (3) green satisfaction that is how satisfied are inhabitants of the UGS around them in the community; (4) how healthy people feel; (5) how satisfied are inhabitants of the community with their life; (6) how satisfied are inhabitants of the community with their neighbourhood. We made a systematic linear regression model between each indicator and the green area ratio (Sect. 4.3). As the urban situations are different, we also split the regression into our four quantile categories. The results are detailed in Fig. 15a-f. In addition, for clarity of reading, we highlighted in red when the regression failed, meaning no correlation(when the P-value was larger than 0.05 along with a low F-statistic) and in the black when it succeeded, meaning a correlation is established. The results of the indicators yield interesting trends to understand the influence of green on people’s lives and how green exposure influences inhabitant satisfaction and comfort. We can observe that there are two general trends: (a) for communities in quantile up to 75, there is a positive correlation between green area ratio and satisfaction; (b) for communities in quantile 100, there is a positive correlation between green area ratio and life unsatisfaction (anxiety, depression, and adverse health). (A)

10

is an encouraging result as greenifying is felt by inhabitants, especially when exposure is higher (quantile 25–50). Without explaining life satisfaction, neighborhood satisfaction and green satisfaction, it is certain that a higher green area ratio affects inhabitants positively. It calls for both more UGS but also a better exposure as preliminary results of this section suggests the importance of also exposing inhabitants better. The status of quantile 75 (suburban characteristics) is also interesting as it globally follows more urbanised communities trends in a less pronounced way.

Standard scaler is a preprocessing method removing the mean of the data and scaling to unit variance. The mean becomes the origin (0) and the unit variance the scale of variation. 11 Depression here is not a medically checked state but an overall feeling.

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Fig. 14 a The 170 communities of the Shanghai CENDUS datasets plotted on choropleth map; hue according to quantile categories of total surface similarly used in all experiments except for in Sect. 4.2. (top). b Map extract zoomed on downtown communities (bottom)

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Fig. 15 a Per quantile category scatterplot and regression model of Anxiety (y) and green area ratio (x) b. Per quantile category scatterplot and regression model of Depression (y) and green area ratio (x) c Per quantile category scatterplot and regression model of Green satisfaction (y) and green area ratio (x) d Per quantile category scatterplot and regression model of Health (y) and green area ratio (x) e Per quantile category scatterplot and regression model of Life satisfaction (y) and green area ratio (x) f Per quantile category scatterplot and regression model of Neighborhood satisfaction (y) and green area ratio (x)

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Fig. 15 (continued)

(B)

is slightly counter intuitive. The 25% larger communities, all located further from downtown in less urbanised more natural areas show a loss of quality of life when green area ratio gets higher. Anxiety and depression get higher while health goes lower in these communities in relation to green. There are for sure social reasons for this and green area ratio here might be a proxy for another phenomenon: more green area also means more agricultural area and intensity of rural life might be the reason why life is unsatisfactory when green area gets larger. Green exposure for both road buffers and distance to green is also decreased here but this needs to be investigated further. However, It should also be noted that green satisfaction and neighborhood satisfaction are weakly positively correlated with green area ratio so there is a composite phenomenon at play that also needs further investigation, especially to be fairer to inhabitants of these less favored communities of Shanghai.

4.6 Fieldwork: Direct Observation of the GI in Context As the final step of our analysis, we shortlisted communities to visit and explore. This phase, which is not by any means a complete form of ethnography, still leverages on tools and methods of fieldwork to collect and utilise data coming from the real environment; such data are very rich of details, granular and fragmented: granular because they arrive at the very source of the polygons represented in our first map, fragmented because they are not comprehensive. They offer only partial representation of GI in use. Such data have qualitative instead of statistical relevance. Fieldwork observation has different goals: (a) looking at information about the typology and variety of GI in place in Shanghai, information which is missing from the polygonal map; (b) extend our understanding of the interaction and use by being in the very location where the GI is placed and being able to capture traces, if not the real-time evidence, of uses; (c) possibly verify the relevance of our analytical findings and match the data with reality. Continuing to use the metaphor of zoning and zooming, which pertains to the domain of visualisation in general, we call this phase “the qualitative lens”. In this phase, we do not propose a systematic protocol for analysis, yet we tried to be as structured and accurate as possible in the way we collected our data. For each of the

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locations selected, several pictures and annotations have been taken, following this list: • Image of the side-walks or side road in references to experiment 2 • Sampling of different GI typology, with relevance to details, from aesthetic to functional • GI in liminal and boundary space • Photographs following the 15 m road buffer (See Sect. 4.2) • Images of use, presence of people, images of malfunctioning, images of creative tweaks of GI uses. Actual interaction and survey with people have been purposely excluded - the scope of the paper does not satisfy a social science approach, and it is really focusing on looking at GI from a specific data-driven methodological perspective. In the spirit of the data-driven methodology grounding the whole paper, images are, therefore, data points. The data approach is looking at ways in which an indicator of and for GI could be built, and in which way it may support the decision making, leveraging on the possibility of the data availability (which in the case of GI can come from open data portals, government initiatives, urban sampling, and a variety of other sources) and aiming to improve their quality, their presence and their impact on city liveability. We acknowledge that this is the first step of using data to build a meaningful understanding of the urban environment. Therefore, having a “qualitative lens” is important to keep a strong link with the real context and situate the data’s meaning. In fact, from the qualitative observation, many questions which will be discussed in the conclusions arise, both regarding how spaces and infrastructure are or might be utilised, and what is the overall “green feeling” within a community or throughout a neighbourhood, and which aspects it may come from. In the same way, within the limitation of the practice, we tried to explore the places as crude data points, meaning without pre-existing personal knowledge of where they are, which district they belong to, which may be a certain degree of familiarity with the areas, etc. For doing so, a quick “exploration guide” has been compiled, composed by a cropped image of each of the 170 neighborhoods plotted on a map and adding a “reference guide”. Such ID cards include these other data points for a quick outlook of the neighbourhood: population, the indicators coming from the “Shanghai Urban Neighborhood Survey” (SunS, Sect. 3.4), and the exposure index. Finally, in relation to the GI, each of the seven communities visited is described by three data points: image from the satellite (geolocalised, Fig. 16a), image from the plotted GI dataset (Fig. 16b), and fieldwork photographs (Fig. 16c). Many details have been observed and emerged during the fieldwork. First of all, the administrative organisation of the “neighbourhood” may include residential units or compounds with different or opposite characteristics, such as places with excellent green environments or severe lack. The Exposure index works on average values, which in the case of neighbourhood 48 helped to point out a “malfunctioning” of the public space: it has a low green ratio (third over four), it covers a pretty large area, it is very centrally located, and it is composed by extremely lush high-end buildings next to offices and commercial areas built around no green (Fig. 17a). The

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Fig. 16 a–c The three data-points collected for neighbourhood 67

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Fig. 16 (continued)

exploration guide suggested such unbalance (Fig. 17b). Yet, the fieldwork clarifies the striking contrast and let rise the question about which kind of planning would allow commercial areas to be built with such limited green exposure. Indeed the fieldwork is helpful to understand the variety and the complexity of GI, not only in their decorative functions of gardens but also in the possible role as Ecosystem Service and in the significant value of community/environment enhancement which has an impact on the quality of the “common space”. Despite the limited number of communities visited, we collected numerous GI images with functional uses, place-holder of space separator between compounds, units, behind parking lots, for drainage, embellishment, and street/interior divider, canopies (Fig. 18a). GI is abundant within the 15 m radius (Fig. 18b). There are images of people using benches and seats with or without rain, in the internal gardens or at the street sides (Fig. 18c). There are some remarkable images of GI which are further “greenified” by the intervention of individuals (Fig. 18d). Moreover, there are many cases where circumstances impede GI use, such as temporary uses (like construction sites), lifestyle habits (bicycle parking, clothes hanging, storage and deposit), etc. To what extent such a situation is configured as a misuse of the GI, and therefore impacting their value, is another valuable question that opens up. Which possibilities of intervention are there from a planning perspective to maximise the GI’s value and use? Such understanding may open opportunities for

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Fig. 17 Neighbourhood 48, with a contrast between green and not green areas in the fieldwork (A, top) and in the polygons dataset (B, bottom)

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Figs. 18 a–d More examples from the fieldwork (order is clockwise staring from top left)

the planning in terms of how such best practices can be supported and how negative practice may be inhibited. The objective of the fieldwork, looking at the variety of GI, understanding better its uses, and matching the validity of the Green Exposure with reality have been achieved. We are aware that more exploration would lead to more solid confirmation and make us able to ask more precise questions (or offer more clear suggestions) about how GI could and should be managed and maintained. Finally, we believe such observations are interesting for the methodology: they suggest that data may bring indicators useful to an assessment, but an exclusive data approach may fall short when considering the qualitative condition of social living and well-being.

5 Discussion and Conclusions 5.1 Social and Environmental Aspects of GI Summarizing, the paper details the twofold data-driven methodology applied to the analysis of Shanghai GI. Such methodology acts on three types of data: (a) the dataset of all the green areas extracted from maps, (b) the Shanghai CENDUS dataset about 170 communities within the cities, and (c) the fieldwork of 7 communities. The methodology describes and applies the concept of exposure and uses it as an assessment method for the presence and quality of GI in Shanghai. By the creation of the Green Exposure indicator, we offer a measure to validate whether people are exposed or not to green. This measure quantifies the green and attempts to measure the possibility of interaction given to citizens. Data visualisation has been used as a research method. The methodology described in detail in Sect. 4 demonstrates the role of visualisation in supporting research hypotheses throughout a

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progressive understanding, leading to various findings, some of which present points of interest about the built environment. It seems that most of the green is among buildings, their liminal space and transition zone, it resides inside of such areas, and it is not in the “public space” of the street; such green is also often a combination of GI placed by the administration and other layers of informal greenery which are placed and maintained directly by individuals and communities. This comes evident while exploring the neighborhoods, and it cannot be carefully mapped or seen just by the analysis of the dataset. Hence, by understanding the role that GI plays in the community, it is possible to better inform planning and design solutions. On another note, there is a general intuitive bias of thinking that peripheral areas are greener (because less built), but this is true only for bigger parks. While it is not verified within communities and compounds, it seems that Green Exposure is lower in places with more GI presence, for example, the rural and peri-rural Shanghai. In such areas, the census indicators receive relatively lower scores: it would be necessary to inquire deeper on the reasons and implications of such a situation. In an example like this, the findings coming from the visualisation have a strong perspective for further research, and they are critical: they introduce some anthropological observation in our perspective of data-driven green infrastructures. What are social and economic conditions that make green less accessible? What are the conditions which decouple the quantity of green from the green satisfaction index in some of the rural communities? Which are the policies that support the implementation of GI, and how much do they look at qualitative aspects of their intervention? How can such policies utilise green as a strategy to promote well-being in the long term? It is the combination of both quantitative and qualitative approaches which help us to look at green infrastructure as something that belongs to management instruments, but yet it has strong sustainability and social implications. Obviously, we acknowledge that the process of city-making and the development of infrastructure are long-term, but such findings may inspire the planning in taking more careful considerations of well-being policies in rural areas, reducing the fragmentation of different Shanghai areas. In comparing the index with international (mainly European, as we analysed) cities, Shanghai has relatively good positioning in terms of quantity of green. Yet, the city is not homogeneous, and some communities may still be considered underserved. In such a perspective, the fact that management of greenery could be utilised as a strategy of social inclusion for future development of the city is indeed a very valuable opportunity to explore.

5.2 Strengths and Limitations of the Methodology This section concludes some findings of using a hybrid methodology and a qualiquanti approach to data. As data professionals, we are convinced that the only automation of analytics cannot satisfy a complex and accurate understanding of reality, which richness and specificity elude the possibility of comprehensive measurements. Somehow we acknowledge that data, per se, may always be “incomplete”. In using

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such methodology, we were interested in making a point about urbanism and green by stating how important green would not be considered merely an element to be placed in contemporary urban planning. Indeed, it is an asset for better cities, and it needs to be considered for the affordance of interaction included in the infrastructures. We demonstrated that data could provide a wide range of hypotheses and understanding. Yet, data fall short on reporting actual behaviors. Therefore such research and methodology have a general value as a data-human approach, which we consider relevant to apply in an urban environment mostly to support definitions such as “sustainable urbanism”, and even a more general concept of “smart cities”. Furthermore, the data approach turns out to be very limited in specific situations, which yet are crucial for exposure and quality assessment: data, for instance, they do not count cars, and in the fieldwork, we regret to say that the presence of cars has been a significant factor to limit efficacy and impact of GI. This is important because it reveals that public infrastructure and space are often occupied by private assets, thus losing their public value and interest. How policy may address, this is also an important question to be addressed in terms of liveability, which should be fair and equal towards all citizens. Another situation that emerged only from the fieldwork is that GI use seems to be unregulated, and the infrastructures are often adapted to various uses. It looks like GI is considered “space that can be used in other ways”, again, against more private or subjective interests (i.e., parking, storage, trash deposit, etc.). We believe instead that the quality of GI should be protected, meaning that they should be maintained and accessible as solely green spaces. Of course, the data work we proposed also has limitations of time and resources. The fieldwork, for example, has not taken into account time fluctuation, changes between day and night, or weather conditions, all of which impact largely on how the infrastructures are utilised. Moreover, in the dataset as well, the calculation of GI is approximated: at the moment, we are only offering a static analysis of the dynamic process of GI implementation, maintenance, and update. To reflect such change, the Green Exposure would need to find a way to update as well, and therefore develop in the direction of a monitoring tool.

5.3 Conclusions and Future Works There is a final remark worth mentioning since this work is about measures and assessment of Green Exposure, and it is how “digital green infrastructures” may impact such indicators. We used the dataset of the green space as a research tool to reflect on exposure. Still, such a dataset could be exploited in various ways to become a visualisation tool given to the citizens. We think of UGI as physical constructions in the cities, but if we think of their digitalisation (as in the case of the maps that we used for this analysis), could they become digital infrastructures? Could they be designed as the touchpoints given to the citizens to re-route commuting and living towards more green? Could the data-driven approach take more into account green indicators (not only to inflate real-estate prices but to offer a better urban experience

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to people? On a larger scope, can digital infrastructures support the growing interest towards green presence in our built environment? We believe these are perspectives that should attract the interest of planners and stimulate more interdisciplinary work that can support city management and city-making. This section demonstrates that green is not an accessory of buildings, and that the green space cannot be studied only in relation to the built space. It has to be studied as its own. There are many opportunities to apply the Green exposure into practice and contribute to its improvement: • Deepen the understanding of the Green Exposure applying it to specific regeneration projects ongoing in the city, giving more space for in-depth fieldwork • Scaling out the methodology and adapting it to other Chinese cities (or to other cities abroad). A comparative perspective could offer more insights on how to build a significant Green Exposure indicator, and also suggest if such an indicator can be more or less universal, or how much it is composed of parameters which only have a local validity • The Green Exposure could become a tool to assess the improvement of GI over a time span (supporting for example the implementation of |5 years green plans”. The value of the indicator as an assessment tool would of course grow over time. In the same way, the notion of exposure could include “space and time” and be crossed with other urban data indicators, peak time, flows, spatial routing, etc. A variety of services and potential business opportunities could be opened once considering the GI as the asset of an active, accessible, sustainable urban experience. We suggest this as a direction that planning and development practice should take care of and proactively into account. Acknowledgements This research has been supported by the NSFC research grant 202062050410353. We are also thankful to the colleagues at CENDUS, Shanghai University, for the possibility to access the SunS dataset, and to UTSEUS, Shanghai University for the hardware utilised for the computational work necessary to the analytics and the visualisations included in this chapter. We declare that all the diagrams and the photographs have been originally produced by the authors for the specific purpose of editing this chapter.

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Comprehensive Evaluation of Green Infrastructure Restorative Practices for High-Quality Transitional “Sponge Node” Renewal Programs in China Jing Sun, Ali Cheshmehzangi, and Sisi Wang

Abstract In general, Green Infrastructure (GI) is described as part of nature-based solutions (NBS). It is not only recognised as a driver in sustainable water management and water resilient city construction, but also for promoting urban ecosystem restoration, climate change adaptation, and enhancing urban liveability and well-being. Due to their multi-objectives and multi-benefits, GI practices and GI-guided land use policies have gained attention in China’s Sponge City Program (SCP). Hence, the assessment of hydro-environmental performance is recognised as the foundation of SCP; however, there is a lack of a comprehensive quantitative evaluation system and a design and assessment process model including this evaluation system for high-quality SCP at neighborhood scale. Taking the GI planning of the Liangnong Town, Siming Lake sponge node restoration as an example, this chapter applies the Storm Water Management Model (SWMM) to examine key indicators of hydroenvironmental performance. The findings utilise ten design scenarios to compare the effectiveness of each facility and their combinations in practice. Furthermore, based on Analytic Hierarchy Process (AHP) system, other benefits are quantitatively evaluated through a comprehensive performance analysis of the ten GI scenarios. The final results suggest the most suitable GI general plan for the transitional regeneration of Liangnong Siming lakeside area. Finally, a comprehensive evaluation system is J. Sun School of Civil Engineering and Architecture, Zhejiang University Ningbo Institute, Ningbo, China J. Sun · A. Cheshmehzangi (B) Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, China e-mail: [email protected] A. Cheshmehzangi Network for Education and Research On Peace and Sustainability (NERPS), Hiroshima University, Hiroshima, Japan S. Wang Key Laboratory of Urban Stormwater System and Water Environment, Ministry of Education, Beijing, China Beijing University of Civil Engineering and Architecture, Beijing, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_11

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developed to highlight key sustainability indicators and design pathways for highquality GI design for the neighborhood scale SCP. The chapter’s findings provide a useful reference for similar program’s decision-making and GI design. Keyword Green infrastructure · Sponge city · Stormwater management · Comprehensive assessment · Key performative indicators framework · High-quality landscape transition

1 The Background of Sponge City Programme China’s rapid urbanisation has led to large-scale urban expansion and a series of ecological environment problems, especially water ecological crises. In recent years, many large and medium-sized cities in China have suffered from extreme stormwater runoff events and water-logging disasters. At the same time, water pollution and degradation of waterfront habitats are becoming increasingly prominent. Hence, there is an urgent need to cope with water-related challenges in urban areas by minimizing the adverse effects of land cover change and improving the built environment’s resilience (Chan et al. 2018). As a response, the Sponge City Program (SCP) was launched under such motivation. President Xi Jinping’s speech at the Central Urbanisation Working Conference held in December 2013 mentioned building a “sponge city” that rainwater can naturally accumulate, penetrate, and get purified (Xu 2015; Xie 2016), which can be regarded as an official announcement of the beginning of SCP. In October 2014, the Ministry of Housing and Urban–Rural Development, adherent to President Xi Jinping’s speech and the spirit of the Central Urbanisation Working Conference, issued the Sponge City Development Technical Guide (SCDTG). This SCDTG clearly defines the concept of sponge city: sponge city program (SCP) is a new strategy of sustainable urban stormwater management in China, which refers to the idea of a city that can absorb, store and purify rainwater as a sponge does, then naturally filter the rainwater through the nature-based solutions, allow it to reach urban aquifers, and release it for reuse when needed (Ministry of Housing and Urban–Rural Development 2014). During 2015 and 2016, 30 cities were selected as the sponge construction pilot cities. Additionally, each sponge pilot city receives 400–600 million RMB (1 RMB is approximately equal to 0.15 USD) annually from the central government for three years. The total investment is estimated to be about 42.3 billion RMB (Jiang et al. 2017). Currently, sponge city, as an effective way towards a resilient city for people and nature to coexist harmoniously (Jiang et al. 2018; Nguyen et al. 2019), has drawn great attention both nationally and internationally.

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1.1 Research Scope: GI for Sponge and Resilient City The twenty-first century is already known for unprecedented and fundamental changes and new trajectories, considering climate change, global economics, migration, and population growth (Cheshmehzangi and Dawodu 2019). And the world has entered a new geological era, which is described as the Anthropocene, as we discussed in the introduction section. In this new Anthropocene era, adaptation to challenges calls for resilient cities (Alberti et al. 2003; Chandra et al. 2010; World Health Organization 2011). Faced with numerous environmental, economic, and social challenges (Cheshmehzangi and Griffiths 2014; Cheshmehzangi and Butters 2016, 2017; Butters et al. 2020), modern cities have tried to re-direct themselves towards sustainability, resilience, as well as improved quality of life and human wellbeing (McDonnell and MacGregor-Fors 2016; Wigginton et al. 2016). In the past few decades, Green Infrastructure (GI) was often considered for both immediate (Elmqvist et al. 2003, Ni¸ta˘ et al. 2017) and long-term solutions to the challenges of urban environments globally (Gómez-Baggethun et al. 2013; Lafortezza et al. 2017; Badiu et al. 2019). The nexus between GI and urban sustainability is apparent in the literature (Cheshmehzangi et al. 2021a). GI has been adopted as an important measure in many popular strategies of stormwater management practices and employed as a comprehensive approach that provides a range of ecosystem services (Deng and Cheshmehzangi 2018; Xie et al. 2020; Cheshmehzangi et al. 2021b). Additionally, GI is regarded as a spatial connecting media for linking ecological infrastructure to social infrastructure in the city, with the potential to enhance both ecological resilience and social resilience and ultimately benefit both humans and ecosystems (McDonnell and MacGregor-Fors 2016; Chatzimentor et al. 2020). Additionally, Green Stormwater Infrastructure (GSI), which is part of broad meaning GI, such as Bio-Retention (BR), Rain Gardens (RG), Bioswales (BS), Permeable Pavements (PP), Rainwater Harvesting, Planter Boxes, Green Streets and Alleys, Green Parking, Green Roofs (GR), has been wildly used in the site scale SCP (Lucas and Sample 2015; Luan et al. 2017; Tao et al. 2017). Besides, the site land conservation and land-use transition design with the natural landscape restoration, as nature-based design pathways towards sustainability, have recently gained popularity. These neighbourhood scale multifunctional broad mean GI measures (including GSI) towards all-around sustainability and the corresponding planning and evaluation methods improvements for SCP are the scope in this research.

1.2 Sponge City Frontiers with GI Comprehensive Assessment Stress Needs In the construction of sponge cities, the quantitative assessment of hydrological benefits is an essential requirement for assessing pilot cities. The SCDTG, issued in 2014, has clearly put forward the proposed objectives of the annual total runoff control rate

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(ATRCR) for different regions of those pilot cities. Some stormwater management models such as SWMM, Mike-Urban, and InfoWorks are commonly used worldwide (Nguyen et al. 2020), supporting the quantitative assessment of hydrological benefits. These models have brought benefits for planners and policymakers by simulating the process of the urban stormwater runoff process and estimating water quantity and water quality (Jiang et al. 2018). Moreover, with the recent advances in software package capabilities and technologies, these models have performed better in recent years. Most of these kinds of models have the site scale GI evaluation module, capable of evaluating hydro-environmental performance evaluation of GI plans of neighbourhood scale projects. However, there is still a need to stress a comprehensive evaluation system. China faces a high-quality urbanisation transition, aiming to the comprehensive sustainable development of the economy, environment, and society (Jia 2018; Fang 2019). Therefore, towards better planning and implementing high-quality GI with multifunctionality, there is a need to stress a comprehensive and quantitative evaluation system with all-around sustainability and a design and assessment integrated process model (Cheshmehzangi et al. 2010, 2017). These will help optimise the GI design scheme with not only environmental health improvements but also human well-being improvements and trade-off the needs of different stakeholders at neighbourhood scale.

2 Research Objective, Key Points of Methods, and Overall Structure 2.1 Research Objective and Research Questions Taking the evaluation of SCP at Liangnong Siming Lake waterfront area of city Ningbo as an example, this research’s main objective is to develop an evaluation system. This includes a set of quantifiable KPIs for comprehensive and quantitative evaluation of different GI scenarios for the neighbourhood scale program. Therefore, the research questions are: (1)

(2)

How to further develop a KPIF combined with sustainability KPIs and a process model of high-quality GI design for SCP using this KPIF as a comprehensive and quantitative evaluation system?; and How to calculate each value of KPIs for the competition of different GI design scenarios?

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2.2 Overall Structure This chapter focuses on the Siming Lake waterfront area in Ningbo as the research area and is carried out through a five-stage design and assessment process model. These stages include (1) multi-solution GI scenarios design; (2) development of the evaluation KPIF by choosing a set of comprehensive evaluation KPIs, and calculating the weighting of all KPIs based on AHP; (3) hydro-environmental performance evaluation of the designed GI scenarios evaluation based on SWMM, and calculating the values of KPIs for hydro-environmental; (4) further evaluation of the GI scenarios based on experts’ grading, and calculating the value of other KPIs for sustainably criteria; and (5) final check of the comprehensive performance of the designed GI scenarios based on AHP, which concludes the best performance scenario for decision making. Hence, from multiple design to comprehensive evaluation, the whole improved design and assessment process model includes three self-evaluation stages: stage2, stage3, and stage4 (shown in Fig. 1). The involved detailed methods are illuminated in the fowling section.

3 Methods 3.1 Study Area The case study area is an ecological node of Siming Lake watershed (Fig. 2) in the City of Ningbo, China. Ningbo was selected as a national-level sponge pilot city with an average annual rainfall volume of 1517.1 mm. The City of Ningbo is surrounded by the Siming Mountains, while the central city is situated on the Sanjiang Plain. There are three rivers in the middle of the city, the Yao River, the Fenghua River, and the Yongjiang River. The Siming Lake watershed is located in upstream of the Yao River in northern Ningbo and is an important water source area for the city. Therefore, Liangnong Siming’s waterfront area, as an important ecological barrier of Siming Lake, plays an important role in the water ecology and water security for the City of Ningbo. During the past 30 years, with the process of rapid urbanisation and industrialisation, the Liangnong lakeside waterfront area has been seriously disturbed by new development and construction projects. In particular, the lakeside wetland area nearest to downtown Liangnong, where the research area is located, has been partially occupied by industrial buildings. This has resulted in serious environmental problems, including water quality deterioration and the ecological and environmental deterioration of the waterfront area. More recently, the site has been scheduled to be restored and transformed into a waterfront wetland park in multiple stages. Therefore, an appropriate GI scenario needs to be developed. The total area is 34.19 hectares, and the primary aim is to reduce 75% of the annual rainfall runoff from the reconstruction projects, as required by the government for a sponge pilot city.

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Fig. 1 Overall research framework of the study (Source The Authors)

3.2 Design of the GI Scenarios According to the design requirements for the Ningbo sponge pilot city construction, the annual total runoff control rate of the site should be at least 75%. Besides, due to the implementation requirements, the ecological restoration scheme of the Liangnong Wetland Park sponge project was divided into two phases: (1) short term

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Fig. 2 The location, topography and the focus case study area (Source The Authors)

(implemented in 3–5 years), and (2) long term (implemented in 5–10 years). This study primarily focuses on a comparative evaluation of the recent restoration general design. This GI general plan includes an overall site landscape restoration plan, including the demolition of approximately half of the buildings in the park building area. In addition, it includes functional transformations and upgrades of all the buildings within the site area, as well as combinations with specific GSI facilities, including bio-retention cells (BC), vegetative swales (VS), rain gardens (RG), and permeable pavement (PP). Among these, PP is the most suitable strategy for parking lots. Based on the various locations and sizes of the BC, VS, and RG facilities, the use of PP in combinations with these facilities was selected. Therefore, a total of ten scenarios with some areas of GSI facilities but different combinations were designed as alternatives (Figs. 3 and 4). These design alternatives are identified as Siming Lake design scenarios 1–10, numbered SS1-SS10 for simplicity. The allocated surface area of each LID facility in each scenario is shown in Table 1. In addition, to further study the role and effect of GSI measures for rainwater management for the environmental restoration of the entire site, the hydrological effects of the GI plan, which only conducted the demolition of some buildings and redesigned using just green space without specific GSI facilities were also simulated, and this was numbered SS11. The status quo, numbered SS12, was used as a benchmark for comparison. This chapter highlights the assessment of hydrological and comprehensive benefits of the different scenarios with GSI measures in a certain total facility area but

272

Fig. 3 The GIS design of cases from SS1 to SS5 (Source The Authors)

J. Sun et al.

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Fig. 4 The GIS design of cases from SS6 to SS10 (Source The Authors)

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Table 1 Allocated surface areas of each LID facility in each scenario Scenario

Bio-retention cell (m2 )

Rain garden (m2 )

Vegetative swale (m2 )

Permeable pavement (m2 )

Total area (m2 )

SS1

24,166

–

–

3615

27,781

SS2

–

24,166

–

3615

27,781

SS3

–

–

24,166

3615

27,781

SS4

22,665

1501

–

3615

27,781

SS5

7741

16,425

–

3615

27,781

SS6

9242

–

14,924

3615

27,781

SS7

7741

–

16,425

3615

27,781

SS8

–

9242

14,924

3615

27,781

SS9

–

1501

22,665

3615

27,781

SS10

7741

1501

14,924

3615

27,781

different combinations. Also, a comparison of those 10 scenarios with GSI to the SS11 without GSI measures, a scenario that only recovers green landscape design, is conducted.

3.3 AHP Method Overview with Selection of KPIs An Analytic hierarchy process (AHP) based preliminary research for the key performance indicators (KPIs) selection was carried out (Sun et al. 2020). The KPIs from many indicators were selected based on reviews and interviews. Additionally, 20 experts (15 local experts and 5 non-local) from four groups were interviewed in this preliminary research. Moreover, it is proposed that the AHP hierarchical model structure with the KPIs can be generally summarised, as shown in Figs. 5 and 6. The top goal layer is goal

Fig. 5 A general AHP hierarchical model structure with KPIs (Source The Authors)

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Fig. 6 The hierarchical model structure for the preliminary research (Source The Authors)

A. The middle-level criteria B; sub-criteria level C, as well KPIs level D; and the bottom alternative levels denoted as SS1, SS2, SS3, …, and SSX. The selection and ranking of the KPIs are based on the experts’ interviews. These results and the reference will be summarised in Sect. 3.1, and the calculation steps of the AHP method of this study will be further discussed in Sect. 11.5.

3.4 SWMM Modelling for Hydro-Environmental Performance Hydrological Model SWMM In this study, SWMM 5.1 was used to simulate the water quantity and water quality control performance of the scenarios mentioned above. SWMM was developed by the United States Environmental Protection Agency (USEPA) for the design and management of urban stormwater (Zhu et al. 2019). EPA-SWMM is a popular catchment model for simulating the process of the urban stormwater runoff process, as well as for use in estimating water quantity and water quality. It has been widely used in many countries, including China (Jang et al. 2007; Kong et al. 2017; Palla and Lanza Barbera 2008; Versini et al. 2015; Zhang et al. 2009; Jin et al. 2010; Xu and Guo 2017; Moscrip and Montgomery 1997; Cai et al. 2017; Zhou et al. 2017; Guan et al. 2015). SWMM 5.1 was extended to simulate the hydrologic effects of low impact development (LID) facilities, such as bio-retention areas and rain gardens (Rossman 2010).

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4 Data Collection The planning and meteorological data in this study were primarily provided by the Ningbo Bureau of Natural Resources and Planning Bureau, the Ningbo Meteorological Bureau, and the Ningbo Housing and Urban–Rural Development Bureau. Land-use data were collected from the Liangnong government of the city of Ningbo (Fig. 7). The spatial distributions of the land-use, terrain, and detailed built information were collected from a site survey conducted by our research team as permitted

Fig. 7 The spatial distribution of land-use in Liangnong (Source The Authors)

Comprehensive Evaluation of Green Infrastructure Restorative Practices … Table 2 Total and impervious areas of sub-catchments

Sub-catchments No Areas (m2 ) ZHS1

3.22 × 104

Proportion of impermeable area (%) 3.00

ZHS2

4.43 ×

104

1.30

ZHS3

4.30 × 104

78.00

ZHS4

2.13 × 104

80.00

ZHS5

5.59 ×

ZHS6

5.9 × 104

3.50

ZHS7

8.62 × 104

1.90

Total area

34.19 ×

104

104

277

0.00

16.33

by the Liangnong government, using an unmanned aerial vehicle (UAV) surveying and modelling.

4.1 Model Setup In this study, the Horton equation was used to estimate infiltration losses. The representation of the rainfall and runoff processes was based on the water balance approach and Manning’s equation (Luan et al. 2019; Horton 1933). This approach evaluates green stormwater infrastructure strategies efficiencies using the SWMM-based approach (Luan et al. 2019). The saturation function was chosen for simulating the pollutant build-up process for the model of pollutant wash-off. In contrast, the exponential function model was used to represent the wash-off process (Baek et al. 2015). According to “Ningbo urban planning and design guideline for Sponge City” (Ningbo Municipal Housing and Urban–Rural Development Bureau 2019), compared with the monitoring data, the EMC values used in this study were COD 40 mg/L, TSS 135 mg/L, TN 4.31 mg/L, and TP 0.34 mg/L. In addition, the LID model that contained the bio-retention cell, rain garden, vegetative swale, and permeable pavement was set up based on the “Technical Guidelines for Sponge City Design,” and the specific technical parameters are expressed in Tables 2 and 3.

4.2 Model Calibration As the scenarios used in this study are for future planning, relevant monitoring data could not be obtained. In addition, there was also a lack of relevant observational comparison data for the Ningbo local pilot project. Therefore, the parameters used in this study referred to the published articles that have previously examined the

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Table 3 Design parameters of LID for module GI practices in this study Layers

Parameters

Units

BC

RG

VS

PP

Surface

Berm Height

mm

150

100

80

5.0

Vegetation Volume fraction

Soil

0.8

0.8

0.8

0.0

Surface roughness

%

0.1

0.1

0.1

0.1

Surface slope

%

1.0

1.0

0.5

1.0

Thickness

mm

–

500

300

50

Porosity

0.35

0.35

–

–

Field capacity

0.12

0.12

–

–

Wilting point Conductivity

Mm/h

Conductivity slope Storage Underdrain

Pavement

0.1

0.1

–

–

3.0.0

3.0

3.0

–

10.0

10.0

–

–

Suction head

mm

87

80

–

–

Thickness

mm

650

250

50

200

Void ratio

0.75

0.75

0.75

0.75

Flow coefficient

0

–

–

0

Flow exponent

0.5

–

–

0.5

Offset height

mm

6

–

–

6

Thickness

mm

–

–

–

100

–

–

–

0.15

Void ratio Impervious Surface Fraction

%

–

–

–

0

Permeability

mm/h

–

–

–

100

–

–

–

0

Clogging factor

same region, Shanghai, and Nanjing (Yufei et al. 2019), as well as the SWMM user’s manual by the US EPA and the sponge city technical manual (Zhu et al. 2019; Duo 2019; Cai 2019).

4.3 Simulated rainfalls and Standards Settings In order to have a more accurate and comprehensive evaluation of the hydrological environmental effects of each scenario according to the requirements of the SCDTG, this study utilises the long-duration model simulation that was used 30 years of continuous daily rainfall data in the city Ningbo to calculate the annual total runoff control rate and related pollutant reduction. The long-duration rainfall events were from 1981 to 2010. The primary objective of sponge city construction is to control and store small- and medium-sized rainfall events. In addition, an annual total runoff control rate (ATRCR) of more than 75% is considered to meet the governmental standard for this project. Also, a simulation

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of two-hour rainfall events with a return period of 3 years for each scenario was conducted, and the peak flow reduction was compared based on experts’ suggestions. Ningbo Rainstorm Intensity Formula as shown in Eq. 1 (Ningbo Municipal Housing and Urban–Rural Development Bureau 2019) and Chicago Approach calculate the rainfall data with a return period of 3 years, which is commonly adopted in China (Xie et al. 2017). q=

2293.666 × (1 + 0.698lg P) (t + 9.77)0.723

(1)

where q is the rainfall intensity, P is the rainfall data with the designed return period, t is the duration of the rainfall.

5 Comprehensive Evaluation and Based on AHP 5.1 Weighting and Ranking of KPIs Selected KPIs were weighted based on the AHP method, and four detailed solution steps of the AHP method can be found in the literature review (Dos Santos et al. 2019, Sun et al. 2020), as shown in Fig. 1. In addition, a synthesis and consistency check is included, and a Consistency Index can be calculated by Eq. 2 (Dos Santos et al. 2019). CI =

λmax − n , n = 1, 2, . . . , 9 n−1

(2)

where CI is the Consistency Index, λmax is the maximum eigenvalue, n is the order of each comparison matrix. Then, CR is obtained by dividing the CI by the Random Consistency Index (RI) as shown in Table 4. CR =

CI RI

(3)

The final weighting priorities, denoted by W D1 , W D2 , …, W Di , of the alternatives in terms of all the criteria combined are determined according to Eq. 4. Table 4 The RI values Elements

1

2

3

4

5

6

7

8

9

RI

0

0

0.58

0.90

1.12

1.24

1.32

1.41

1.45

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J. Sun et al.

W Di =

n j=1

WCi j W j , i = 1, 2, . . . , m

(4)

where W j is the overall ranking weight of each element of the above layer c; Wcij is the ranking weight of the layer corresponding to cj , and m is the number of KPI.

5.2 Comprehensive Evaluation of Each Scenario In this study, after calculating the final weight of each KPI, it was also necessary to multiply the basic value of each KPI that was based on the SWMM assessment and the expert’s grading. This was done to score each scenario and obtain the final values for each KPI. The calculations are shown in Eq. 5. These final values were then added to calculate the final score of each scenario, as shown in Eq. 6. The higher the final score, the higher the ranking of each GI scenario: Si = Pi W Di , i = 1, 2, . . . , m SS k =

m 

Si , k = 1, 2, . . . , 10

(5)

(6)

i=1

where Si is the final value for each KPI, Pi is the basic value of each KPI, and SS k is the final score of each scenario.

6 Results and Discussions 6.1 Hierarchical Structure Module and the Selected KPIs A hierarchical structure of the evaluation system with the KPIF was developed, as shown in Table 5 and Fig. 8. There are 15 KPIs are selected in the KPIF (Sun et al. 2020), including seven KPIs for environmental performance criterion, four KPIs for the economic and adaptability performance, and four KPIs for social-cultural and wellbeing performance criterion.

6.2 Ranking and Weighting Results of the KPIs Based on the total ranking and weighting analysis process, the final weighting results of the KPIs are shown in Fig. 9. In addition, the following KPIs ranked the first four of

Criterion Hierarchy (B)

Environmental performance(B1)

Target Hierarchy (A)

Comprehensive Assessment

Water quality regulating services (C2)

Water quantity regulating services (C1)

Table 5 The AHP Structure with the KPIs in this study

D3

5: D3 > 45% 4: 44% < D3 ≤ 45% 3: 43% ≤ D3 ≤ 44% 2: D3 < 43%

5: D2 > 60% 4: 50% < D2 ≤ 60% 3: 40% ≤ D2 ≤ 50% 2: D2 < 40%

Peak reduction rate‘ D2

SS reduction rate

5: D1 > 77% 4: 76% < D1 ≤ 77% 3: 75% ≤ D1 ≤ 76% 2: D1 < 75%

Calculating and marking standards for the value of KPIs

D1

Annual total runoff control rate (ATRCR)

Indicator Hierarchy Symbol (C)

(continued)

MOHURD (2015, 2019)

MOHURD (2015, 2019); Ningbo Municipal Housing and Urban–Rural Development Bureau (2019)

MOHURD (2015, 2019); Ningbo Municipal Housing and Urban–Rural Development Bureau (2019)

References

Comprehensive Evaluation of Green Infrastructure Restorative Practices … 281

Target Hierarchy (A)

Criterion Hierarchy (B)

Table 5 (continued)

5: D4 > 47% 4: 46% < D4 ≤ 47% 3: 45% ≤ D4 ≤ 46% 2: D4 < 45% 5: D5 > 45% 4: 44% < D5 ≤ 45% 3: 43% ≤ D5 ≤ 44% 2: D5 < 43%

COD reduction rate D4

D5

D6

TN reduction rate

TP reduction rate

5: D6 > 45% 4: 44% < D6 ≤ 45% 3: 43% ≤ D6 ≤ 44% 2: D6 < 43%

Calculating and marking standards for the value of KPIs

Indicator Hierarchy Symbol (C)

(continued)

Ningbo Municipal Housing and Urban–Rural Development Bureau (2019)

Ningbo Municipal Housing and Urban–Rural Development Bureau (2019)

Ningbo Municipal Housing and Urban–Rural Development Bureau (2019)

References

282 J. Sun et al.

Target Hierarchy (A) Habitat supporting services (C3)

Economic and Cost saving (C4) adaptability performance (B2)

Criterion Hierarchy (B)

Table 5 (continued)

Construction cost saving

Promotion of Biodiversity

D8

D7

Indicator Hierarchy Symbol (C)

5: Highest level 4: Relatively higher level 3: Medium level 2: Lowest level

5: Highest level 4: Relatively higher level 3: Medium level 2: Lowest level

Calculating and marking standards for the value of KPIs

(continued)

Dhakal and Chevalier (2017); Mei et al. (2018); Luan et al. (2019); Kim and Song (2019); Liang (2018);

Sadler et al. (2010); Yu (2015b); Hunter et al. (2015); Payne and Barker (2015); European Commission (2016); Pakzad and Osmond (2016b); Jeanjean et al. (2016); Frumkin et al. (2017); Sinnett et al. (2018); Revised National Planning Policy Framework (2018); Jerome et al. (2019); Ministry of Housing Communities and Local Government (2019); Heymans et al. (2019); Charoenkit and Piyathamrongchai (2019); Pauleit et al. (2019)

References

Comprehensive Evaluation of Green Infrastructure Restorative Practices … 283

Target Hierarchy (A)

Social-cultural and wellbeing performance (B3)

Criterion Hierarchy (B)

Table 5 (continued)

landscape cultural services (C6)

D12

D13

Promotion of landscape aesthetics and identity Promotion of educational opportunities

5: Highest level 4: Relatively higher level 3: Medium level 2: Lowest level

5: Highest level 4: Relatively higher level 3: Medium level 2: Lowest level

5: Highest level 4: Relatively higher level 3: Medium level 2: Lowest level

5: Highest level 4: Relatively higher level 3: Medium level 2: Lowest level

Efficient adaptability Facility adaptability D10 (C5)

D11

5: Highest level 4: Relatively higher level 3: Medium level 2: Lowest level

D9

Maintenance cost saving

Efficient land –use

Calculating and marking standards for the value of KPIs

Indicator Hierarchy Symbol (C)

(continued)

Ministry of Housing Communities and Local Government (2019), Kim and Song (2019)

Yu (2015a); Wang and Banzhaf (2018); Kim and Song (2019); Zhang and Muñoz Ramírez (2019); Jerome et al. (2019)

Wu et al. (2017); Kim and Song (2019); Mulligan et al. (2019)

Wu et al. (2017); Gordon et al. (2018); Cao et al. (2018); Ye et al. (2018); Huang et al. (2018)

Mei et al. (2018); Luan et al. (2019); Pauleit et al. (2019); Bai et al. (2019)

References

284 J. Sun et al.

Target Hierarchy (A)

Criterion Hierarchy (B)

Table 5 (continued)

Health and wellbeing supporting Services (C7)

D14

D15

Recreational and wellbeing improvements for all times a year Recreational and wellbeing improvements for all people

Indicator Hierarchy Symbol (C)

5: Highest level 4: Relatively higher level 3: Medium level 2: Lowest level

5: Highest level 4: Relatively higher level 3: Medium level 2: Lowest level

Calculating and marking standards for the value of KPIs

Pakzad and Osmond (2016a); Ministry of Housing Communities and Local Government (2019); Ramyar et al. (2019); Garau et al. (2019); Jerome et al. (2019); Kim and Miller (2019); Mulligan et al. (2019)

Pakzad and Osmond (2016a); Ministry of Housing Communities and Local Government (2019)

References

Comprehensive Evaluation of Green Infrastructure Restorative Practices … 285

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J. Sun et al.

Fig. 8 Structure of the KPIF for the case study (Source The Authors)

Fig. 9 Weighting results and the comparison of the KPIs (Source The Authors)

the 15 indicators (Sun et al. 2020): D1 (the weight of the ATRCR), D7 (the promotion of biodiversity), D8 (the construction saving), and D15 (the level of recreational and wellbeing improvements for all people).

6.3 Hydro-Environmental Performance of Different Scenarios Based on SWMM (1)

Hydro-environmental performance results base on long-duration simulation

Long-term rainfall data of Ningbo City from 1981 to 2010 were used to simulate the ATRCR and pollutant reduction rate of the different scenarios. The results are

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287

Table 6 Results of the hydrological environment simulation based on the long-term rainfall data Scenario

ATRCR (%)

SS reduction (%)

COD reduction (%)

TN reduction (%)

TP reduction (%)

1

77.18

45.50

47.49

45.42

45.50

2

75.29

43.14

45.45

43.04

43.12

3

73.75

42.50

44.26

42.68

42.06

4

77.03

45.28

47.28

45.19

45.26

5

76.55

44.20

46.29

44.11

44.18

6

76.57

44.26

46.35

44.17

44.24

7

75.90

42.72

44.93

42.62

42.70

8

76.11

42.92

45.12

42.82

42.90

9

75.85

42.55

44.75

42.45

42.53

10

77.23

44.04

46.14

43.95

44.02

11

70.39

40.31

40.31

40.20

40.29

12

64.98

35.79

35.79

35.67

35.78

shown in Table 6 and Fig. 9. Among these, the ATRCR of SS1 (with a BC of 87.0% + PP 13.0%), SS4 (with a BC of 81.6% + RG 5.4% + PP 13.0%), and SS10 (with a BC of 27.9% + RG 5.4% + VS 53.7% + PP 13.0%) was 77.18%, 77.03%, and 77.23%, respectively, which were greater than that of other the facility combinations. It can be seen that the first three scenarios with GSI (SS1, SS4, and SS10) are all increased nearly 7 percentage points compared to SS11 (GI scenario without GSI, only restoring the green landscape) in terms of ATRCR, based on the Long-term rainfall data. Moreover, all the scenarios had an increased ATRCR of approximately more than ten percentage points in general compared with SS12, the current benchmark situation. In addition, the ten scenarios with the GSI facilities, except for SS3 (with an ATRCR of 73.75, slightly lower the project control standard), reached the ATRCR control standard of 75% for the project as a short-term plan implemented in 3–5 years. The results of pollutant reduction rates are shown in Table 6. It was found that SS1 (with a BC of 87.0% + PP 13.0%) and SS4 (with a BC of 81.6% + RG 5.4% + PP 13.0%) were consistently the best performers, ranking the first and second of the GI plans, respectively. While SS3 (with a VS of 87.0% + PP13.0%) had the worst performance based on its Long-term rainfall data, and the GI scenario consistently ranked last. (2)

Hydro-environmental performance results base on short-duration simulation

Hydrological performance simulations of different scenarios under a short-duration simulation were conducted using the two-hour rainfall data of 65.5 mm with a return period of 3 years. The simulation results (also in Table 7) show: SS11 has the lowest peak flow reduction rate, while SS4 has the highest peak flow reduction rate. In

Peak flow rate

(m3 /s)

56.44%

SS1

56.25%

SS2 41.60%

SS3 62.36%

SS4

Table 7 The runoff control data of different scenarios at P = 3 61.64%

SS5 61.64%

SS6 54.22%

SS7

60.98%

SS8

44.65%

SS9

56.62%

SS10

18.97%

SS11

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addition, scenarios SS1-SS10 with GSI facilities combination have a relatively strong effect on peak flow reduction, nearly 30% higher compared to SS11 (without GSI facilities). (3)

Summary for hydro-environmental performance simulation and further discussions

The ten combinations were not very different in terms of the overall hydroenvironmental performance because the scenarios selected in this study were mainly based on different green facility combinations, including BC, VS, RG, and PP. In addition, because the site’s location is a wetland park area and adjacent to a natural wetland, the selected GSI facilities are facilities with certain landscape effects. Hence, the water storage facilities, such as storage tanks, are not included. The primary reason for selecting these GI combinations was that the study area is a primary water source area. The Siming Lake Reservoir is a large natural storage tank, so there is no need for artificial storage facilities. Moreover, the facilities with high suitability and recommendation by the local sponge design guidance are selected in this study (Ningbo Municipal Housing and Urban–Rural Development Bureau 2019). They all have ground green vegetation, but the underground structure layers are different in complexity. Therefore, the storage capacity and pollutant removal capacity are different. Obviously, the underground structure of the VS facility is relatively simple, and it is primarily a water transport facility. Therefore, the pollutant removal ability of SS3, which is only VS and PP, is the weakest. In addition, its water storage capacity is also the weakest among the ten scenarios. While the underground structure of the BC is most complex, among the BC, RG, and VS. Furthermore, the GI combinations SS1 (with a BC of 87.0% + PP 13.0%) and SS4 (with a BC of 81.6% + RG 5.4% + PP 13.0%), which both had a higher percentage of a BC facility of the total surface area of the GSI facilities, were consistently the best performers for hydro-environmental benefits in terms of both water quantity and quality control. This result is in accordance with the literature that suggests that a BC coupled with a PP has a great effect in reducing the total runoff and reducing the total runoff and peak flow by 40% (Li 2017). Finally, even though uncertainties influence the accuracy of each GI scenario’s simulation result in both the SWMM model settings and the GI parameters, the primary trends and key insights derived from the comparison of relative results remained unaffected. This study primarily compared the relative differences in the environmental effects of several combinations. Hence, the comparisons’ results are reliable and can be used for further AHP assessments for assisting in the final decision-making analysis.

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7 Comprehensive Performance Evaluation Results and Further Discussions Before conducting a comprehensive evaluation, the scoring standard was first defined. Simultaneously, a specific performance score based on the SWMM and the expert interviews for each value of the KPI was further divided into four grades. The specific scoring standard of these four grades is shown in Table 5 (shown in Sect. 11.6). The ten combinations of SS1-SS10 were calculated and ranked based on the scores and weights of the KPIs. The calculation results are summarised in Tables 8 and 9. It can be seen that, among the ten scenarios, SS4 had the maximum comprehensive benefits. Although its performance on ATRCR is slightly lower than the combination SS1, its economic and adaptability performance exceeded those of SS1. Moreover, SS1 was the combination with a BC of 87.0% + PP 13.0%, while SS4 contained a BC of 81.6% + RG 5.4% + PP 13.0%. The evaluation result showed that the economic and adaptability of the combination was stronger after replacing the portion of the BC with the GR with the same total area of the GSI facility. This was because the GR’s construction and maintenance costs are relatively lower than BC, and the economic performance of the combination is increased. Scenario SS3 had the minimum comprehensive benefit, although its economy was the best. SS3 is the combination with a VS 87.0% + PP 13.0%, which had the largest percentage of VS, except for the same percentage of PP compared to the other scenarios. Besides, the VS facility’s underground structure is relatively simple; therefore, its construction and maintenance costs are lower than the BC and the RG. In addition, the environmental, social-cultural, and wellbeing benefits of SS3 were lower than other combinations. Combination SS9, ranking second to last, also contained a higher percentage of VS in the case of the same total area of the GSI facility. The other combinations (SS2, SS5, SS6, SS7, and SS8) ranked in the middle. Moreover, the KPIs system (KPIF) applies to the whole GI scheme design stage, including two stages of the initial design stage for the general plan and an in-depth detailed design stage for implementation. In addition, both stages can use this comprehensive evaluation KPIF to help the self-optimisation of GI design. At present, the score of social and wellbeing design is based on the degree of freedom of operation in the in-depth detailed design stage. In this initial design stage, the GSI facilities selected are all highly recommended facilities in the local guidance, as mentioned in Sect. 3.3.3. Due to the different complexity of underground structures, the corresponding degree of freedom of ground landscape design is slightly different. The corresponding design freedom to enhance the landscape aesthetics, identity, and human wellbeing of VS and the scenarios contains a large area of VS is lower. Hence, they (SS3 and SS9) received a lower score. Moreover, there is little difference between the RG and BC. The corresponding scenarios mainly contain BC and RG; sometimes, just the locations or the proportion are different, according to the interview and marking results from the experts. Finally, the developed KPI framework (namely KPIF) indicates the further design direction in the next stage. Hence, the detailed design can be further evaluated

0.9840

0.5904

0.3936

0.9840

0.7872

0.7872

0.5904

0.7872

0.5904

0.9840

SS1

SS2

SS3

SS4

SS5

SS6

SS7

SS8

SS9

SS10

D1

0.3344

0.2508

0.4180

0.3344

0.4180

0.4180

0.4180

0.2508

0.3344

0.3344

D2

0.1740

0.0870

0.0870

0.0870

0.1740

0.1740

0.2175

0.0870

0.1305

0.2175

D3

0.1792

0.0896

0.1344

0.0896

0.1792

0.1792

0.2240

0.0896

0.1344

0.2240

D4

0.1359

0.0906

0.0906

0.0906

0.1812

0.1812

0.2265

0.0906

0.1359

0.2265

D5

0.1824

0.0912

0.0912

0.0912

0.1824

0.1824

0.2280

0.0912

0.1368

0.2280

D6

Table 8 Basic score value of each KPI for the 10 scenarios

0.4905

0.3924

0.4905

0.4905

0.4905

0.4905

0.4905

0.2943

0.3924

0.4905

D7

0.4220

0.4220

0.4220

0.4220

0.4220

0.4220

0.4220

0.5275

0.4220

0.3165

D8

0.2408

0.2408

0.2408

0.2408

0.2408

0.2408

0.2408

0.3010

0.2408

0.1806

D9

0.1436

0.1077

0.1436

0.1077

0.1436

0.1436

0.1436

0.1077

0.1436

0.1795

D10

0.1416

0.1062

0.1416

0.1416

0.1416

0.1770

0.1770

0.0708

0.1416

0.1770

D11

0.1175

0.0705

0.1175

0.0940

0.1175

0.1175

0.1175

0.0705

0.0940

0.1175

D12

0.2280

0.1368

0.2280

0.1824

0.2280

0.2280

0.2280

0.1368

0.1824

0.2280

D13

0.2415

0.1449

0.2415

0.1932

0.2415

0.2415

0.2415

0.1449

0.1932

0.2415

D14

0.4395

0.2637

0.4395

0.3516

0.4395

0.4395

0.4395

0.2637

0.2637

0.4395

D15

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Table 9 Comprehensive evaluation calculation results of the 10 scenarios Environmental performance (B1)

Economic and adaptability performance (B2)

Social-cultural and wellbeing performance (B3)

Comprehensive performance

SS1

2.7049

0.8536

1.0265

4.5850

SS2

1.8548

0.9480

0.7333

3.5361

SS3

1.2971

1.0070

0.6159

2.9200

SS4

2.7885

0.9834

1.0265

4.7984

SS5

2.4125

0.9834

1.0265

4.4224

SS6

2.4125

0.9480

1.0265

4.3870

SS7

1.7737

0.9121

0.8212

3.5070

SS8

2.0989

0.9480

1.0265

4.0734

SS9

1.5920

0.8767

0.6159

3.0846

SS10

2.4804

0.9480

1.0265

4.4549

according to the KPIs requirements and the related delivery pathways. Also, a highquality GI with the distinction application effects will be presented in the detailed further design stage.

8 Conclusions Sponge Cities, as a sustainable water management concept, are currently in the experimentation stage in China. Due to its multi-functionality and multi-beneficial nature, GI has gained great attention in ongoing sponge-related comprehensive restoration programs. Thus, it is implemented at a national scale as the main tool, helping to build sponge cities while contributing to the overall comprehensive benefits in the process of all-around sustainability transition. To achieve the high-quality GI design for SCP during this transition period, the whole design and assessment process model with a KPIF, which links to all-around sustainability, is necessary and important for both designers and government administrators. By assessing the Siming Lake case study, this chapter discusses the hydrological and comprehensive benefits of the GI scenarios with high suitability GIS measures under the condition of a certain total facility area. Furthermore, the comparison is researched between those scenarios with the basic GI scenario, which only recovers green landscape design without GSI measures, and the comparison with the status quo benchmark. Based on the EPASWMM simulation, data were modelled for a set of hydrologic performance KPIs, the hydro-environmental benefits of ten GI scenarios with the same total area of green stormwater infrastructure (GSI) management, and one basic GI restoration scheme without the GSI and the status quo benchmark were quantitatively evaluated. The results indicated that: (1) the water quantity control effect of the ten scenarios with GSI combined facilities was significantly better than that in S11, without the

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GSI facilities. (2) The findings utilised ten scenarios of the GSI facilities, except for SS3 (with an ATRCR of 73.75, slightly lower the project control standard). With this exception, they all attained the ATRCR control standard of 75% and an increase of approximately more than 10% in general compared with SS12(status quo benchmark). Additionally, they displayed an increase of nearly 7% compared to SS11 (basic GI scenario without GSI). (3) SS4 (with a BC of 81.6% + RG 5.4% + PP 13.0%) and SS1 (with a BC of 87.0% + PP 13.0%) were consistently the best performers overall hydro-environmental benefits in terms of both water quantity and quality control based on long-term rainfall data. (4) Other benefits were quantitatively evaluated based on interviews and the comparison of comprehensive performances of the ten GI scenarios. It was found that the SS4 combination had the best comprehensive benefits in this case study. (5) This best performance scenario was selected for the short-term GI general plan for the Liangnong Siming wetland construction, scheduled to be implemented within 3–5 years after the further detailed design stage optimisation. In summary, the proposed KPIF and the improved design and assessment integrated process model can provide insights into ways for considering the multi-benefit of GI practices, especially for neighbourhood-scale projects. Also, the evaluation system applies not only to the initial design stage but also to the further design stage and the performance assessment management stage for the projects at the site level. It highlights the key sustainability indicators and the design pathways for high-quality GI design. Moreover, it can also help for comprehensive evaluations of similar or sponge-related renewal projects in other regions. While the ranking of KPIs and the related calculation ways can be further developed in future research for other regions. Acknowledgements We especially thank the National Natural Science Foundation of China (NSFC) for the provision of funding for two project numbers 31870704 (led by the third Author) and 71850410544 (led by the second author). This work is partially supported by Ningbo Science and Technology Bureau, project code 2017A10072. We also thank the experts who have been involved in this project completion.

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Countermeasures and Empirical Research on GI Network Construction of Coal Cities in the Eastern Plain Xiangxu Liu and Linlin Wei

Abstract The coal cities in the eastern plains have made a significant contribution to China’s economic development. However, the explosive economic growth has severely impacted the environment. The integrity of the green infrastructure has been terribly threatened by the mining activities with the damaged surface and unexpected urban spatial pattern. This paper analyses the existing problems of the green infrastructure in the coal cities in the eastern plain and proposes some countermeasures to build the green infrastructure network. At last, this paper takes Yongcheng as an example, building a GI network based on MSPA, landscape pattern index, and MCR model, aiming at providing a scientific guarantee for the sustainable development of coal cities. Keywords Coal city · Green infrastructure · Construction strategy · MSPA · MCR

1 Introduction The coal city is a typical resource city with the characters of the general and resourcebased cities. It appears due to coal resources and developed due to coal mining. The National Sustainable Development Plan for Resource-Based Cities (2013– 2020) in China pointed out that the sustainable development of resource-based cities plays an essential role in constructing the national economy, promoting regional coordinated development, and constructing ecological civilization. The coal-bearing areas in the Eastern Plain span across the four provinces, Jiangsu, Shandong, Anhui, and Henan, which are energy bases in eastern China (Feng 2016), while these cities have made an enormous contribution to the economic development of China. However, these cities developed with the model that pays more on the industry development and pay less on the environment with lacking supporting measures (e.g., ecological restoration), leading to some problems such as surface subsidence and water and soil pollution (Jiang and Wu 2003; Shen et al. 2006). At the same time, the rapid process X. Liu (B) · L. Wei School of Ecological and Environmental Sciences, East China Normal University, No. 500, Donchuan Road, Shanghai 200241, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_12

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of urbanisation also pulls much pressure on the environment during urban development (Qiu 2010; Wang et al. 2020a, b) and brings challenges to the healthy and sustainable development of the cities. Coal cities also face such problems. We can see that green infrastructure faces the dual oppression of coal mining and urbanisation in the coal city. Green infrastructure first appeared in the Greenway Movement in Maryland, the USA, in the 1990s. And the formal green infrastructure concept was first proposed by the Conservation Fund and the USDA Forest Service (Benedict and Macmahon 2002). And then, GI was widespread studied by scholars from different aspects (Andersson et al. 2014; Lovell and Taylor 2013; Meerow and Newell 2017; Mitsova et al. 2011; Shokry et al. 2020). To protect the key elements in natural ecosystems and landscapes, reduce disasters, and protect key agricultural areas and other productive lands, relevant stakeholders should work together to build urban green infrastructure (Hostetler et al. 2011; Lovell and Taylor 2013; Meerow and Newell 2017). In China, many researchers focus on the concept of green infrastructure, analysis of classic cases of foreign green infrastructure (Li and Qiu 2018; Li et al. 2020; Pei 2012; Shao et al. 2016; Zhou and Yin 2010). They also put the concept of green infrastructure into urban green space planning and landscape construction (Chen et al. 2019; Feng et al. 2019; Meng and Wang 2013; Mei et al. 2018; Su et al. 2011; Wang et al. 2020a, b; Zhang and Li 2013; Zhang et al. 2020), and ecological effect of green infrastructure on the environment (Li et al. 2021; Liao et al. 2020; Tang et al. 2021; Wang et al. 2019). Generally, all these papers research the city scale (Byrne et al. 2015; Chang et al. 2015; Guo and Bai 2019), seldom focus on the regional scale, and research papers of resource-based cities are rare (Feng et al. 2019; Hou et al. 2021; Hu et al. 2018; Wu et al. 2020). As the green infrastructure will play an important role in the coal city’s environment, this article takes the coal cities in the eastern plains as the study area. With the aim to construct the resilient ecological environment of the coal cities and “stitching” the urban green space, this paper analyses the current characteristics and spatial layout of the coal cities in the eastern plains and proposes the construction of green infrastructure. This paper takes Yongcheng, a resource growth coal city, as empirical analysis to provide constructive guidance for sustainable development planning. At present, the definition of Green Infrastructure (hereafter referred to as GI) has not yet reached a unified conclusion. Most scholars believe it is a green space network that can maintain biodiversity, with potential social, economic, and ecological benefits, and emphasise connectivity, network, integrity (Benedict and Macmahon 2002; Lovell and Taylor 2013; Tzoulas et al. 2007). GI includes core patches, corridors, and stepping stones (Fig. 1), which scholars well recognise. Coal mining activities make coal cities form unique topography. The abandoned land formed after mining provides habitats for many species, many of which are endangered and rare species, which constitute a unique ecosystem (Huttl and Weber 2001; Schulz and Wiegleb 2000). Therefore, abandoned land in coal cities can be a unique GI element different from the general city. The coal cities in the Eastern Plain include Zaozhuang (decline

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Fig. 1 Green infrastructure concept structure

type), Jining (mature type), Xuzhou (regeneration type), Yongcheng (growing type), Huainan (mature type), Huaibei (decline type), and Pingdingshan (mature type) (Fig. 2).

2 The GI Network Status of the Coal Cities in the Eastern Plain 2.1 Mining Abandoned Areas Threaten the Integrity of Green Infrastructure The coal cities expand rapidly during industrialisation and urbanisation, forming a mixture of construction land, non-construction land, residential land, and industrial land, which seriously impact the landscape. The brownfields in coal cities, industrial plazas, and other mining wastelands impact urban construction land expansion. Most brownfields exist in the fringe areas of urban. With the expansion of cities, brownfields are getting closer and closer to urban built-up areas. The contradiction between them has become more and more fierce (Fig. 3). Economic benefit-oriented development often lacks consideration of the ecological environment. This may degrade the ecosystem and even cause its functionality loss (Gao and Yang 2015), having a negative impact on the integrity of urban green infrastructure. The underground mining method is widely used in the eastern plains. Due to the high groundwater level in this area, large areas of coal mining subsidence formed after mining, which seriously restricts the city’s development. The appearance of dumping yards, tailings areas, potholes in the coal city creates unique landscape features of

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Fig. 2 Distribution of coal cities in eastern plain

the mining area, which will cause irreversible damage to the surrounding forests and slopes. Excavation of damaged land, subsided land, occupied land, industrial plazas (Feng 2016), and other mining wasteland fragmented the ecological network and hindered organisms’ migration. In addition, urban mining land eroded farmland and mountains destroyed biological habitats, reducing the area of the central control area of the GI network of coal cities during the development of coal urbanisation. These could weaken the connectivity of the network. The problems of urban development and ecological environment are prominent: For example, as of the end of 2009, the total area of coal mining subsidence in Jining City accounted for 2.09% of the city’s total area. It destroyed 16,443 hectares of agricultural land and seriously impacted farmers’ production and life (Liu 2015), which was a kind of "central control point" of green infrastructure. Therefore, we should not underestimate the degree of damage caused by coal mining subsidence.

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Fig. 3 Subsidence and in coal cities (Draw according to Feng 2016, a built-up area and mining subsidence in Huaibei, and b built-up area and mining subsidence in Zaozhuang)

2.2 The Whole Green Infrastructure Network is Weak and the Local Ecological Effects Are Better The development of coal cities is mostly driven by the industrial land, residential land, and commercial land. Finally, the urban green space is unevenly distributed, and the landscape pattern of road green space and residential green space is weakly connected. Uneven distribution of green space and serious artificialisation are common (Feng 2016). The fragmentation of urban green space is related to landscape design that does not consider site scale in urban construction. Urban construction divides the urban green space landscape and "seizes the green space" The situation is even more common (Yang and Xue 2006). In the early development, coal cities pay more attention to the development of the urban economy than the protection of the urban ecological environment. After being aware of environmental problems, many cities have issued relevant plans for urban green space construction (Table 1). However, there are still great challenges in the restoration of mining abandoned land. For example, the local restoration has been quite effective in several coal cities, such as Pan’an Lake Wetland Park in Xuzhou City, and Riyue Lake Scenic Resort in Yongcheng City, but the ecological effect is not ideal at the landscape scale. In addition, traditional planning pays more attention to the green space system of urban built-up areas and less attention to the periphery of the city and the urban–rural zone. To a certain extent, the overall GI network of the coal city is incomplete.

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Table 1 Green space planning of coal cities in the eastern plains Province

Provincial-level green space planning

City

Shangdong Shandong Province Urban Green Zaozhuang Space System Planning and Compilation Measures (2002) Jining

City-level green space planning Zaozhuang urban green space system planning (2017–2020) Jining urban green space system planning (2011–2030)

Henan

Forest Henan Ecological Construction Plan (2018–2027)

Pingdingshan Pingdingshan urban green space system planning (2011–2020)

Jiangsu

Compilation Outline of Urban Xuzhou Green Space System Planning in Jiangsu Province (2009)

Xuzhou urban green space system planning (2015–2020 年)

Anhui

–

Huaibei

urban green space system planning (2012–2020); Huaibei urban green Line planning (2014–2020)

Huainan

Huainan urban ecological network planning (2017–2035)

Yongcheng

–

3 Construction Strategies of the Green Infrastructure Network in Coal Cities 3.1 Restore the Abandoned Mine Lands and Enhance the Ecological Effect of GI Core Patches We know from the above that the mining wasteland is a unique special area with high ecological value. For example, open-pit mining or underground mining in areas with high phreatic levels forms a water body or wetland, providing a new living environment for fish. In addition, the large underground space also provides large living space for many terrestrial organisms (Feng and Chang 2017). Most of the coal cities in the Eastern Plain are mature and declining coal-city. There are many mining wastelands in the cities, and the coal mining subsidence area accounts for the most significant proportion. The coal mining subsidence area is regarded as the “scar” in the coal city, but it is also a potential ecological land (Liu et al. 2019). When constructing the GI of the coal city, priority should be given to restoring the ecological functions of the mining wasteland. Such priority includes comprehensive regulation of Pan’an coal mining subsidence area in Xuzhou, Jiangsu Province (2011), and comprehensive improvement project of coal mining subsidence area between east and west urban areas in Yongcheng, Henan Province (2009). Now, Xuzhou Pan’an Lake Wetland Park and Yongcheng Riyue Lake have already been the core of the urban green infrastructure, providing habitat support, regulation, and cultural services. We could

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do a SWOT analysis before restoring the mining wasteland. We could combine the restoration objective with its internal and external environment (Wang and Zhang 2015), making full use of the surrounding existing natural resources. We could integrate the ponds to form a large-scale lake surface or preserve and improve the existing woods and green spaces to create an excellent natural living environment to protect biological habitats. After studying the soil structure and soil physical and chemical properties, we use several methods, such as grass planting, organic fertilizer, and backfill of external/foreign soil, to solve the common soil pollution and destruction phenomena in mining wasteland (Alday et al. 2012; Li et al. 2007; Liu et al. 2014; Miao and Marrs 2000). In the process of ecological restoration, it is necessary to gather the government, private enterprises, and non-profit organisations together and clarify the responsibilities of different stakeholders to make ecological restoration more reasonable.

3.2 Optimizing the Green Infrastructure Network and Implementing Rigid Planning There is a flow of energy and information among the green infrastructure’s hubs, corridors, and stone steps, maintaining the overall diversity and functionality of the city ecosystem. We can construct the GI follow the following three steps. First, it is necessary to identify the different GI network elements, sort out and integrate them, and recognise the suitable GI elements, such as collapsed waters, pond water surfaces, polluted agricultural land. Secondly, integrate existing green spaces and focus on increasing the proportion of large and medium-sized green patches during construction. For example, we can create large green spaces in front of industrial buildings, improve the quality of life of surrounding residents, and green the cinder hills to make them truly accessible to residents (Kang and Zhao 2016). Finally, we should make full use of urban natural water bodies and roads to build green corridors and dredge the connections among nature reserves, urban water source protection areas, urban rivers, and lakes, large parks, urban farms, and woodlands (Zhou et al. 2014), to form a complete GI network structure compatible with the development of coal cities. After conducting a detailed survey of coal cities, knowing the development status and problems of different green spaces in coal cities, we established multi-level green spaces corresponding to the land and space planning under different levels and targets. In doing so, the aim is to increase the feasibility and rationality of green space and ultimately realise the green development of coal cities. When we construct the GI network, it is necessary to consider biodiversity and ecological restoration of species habitats and plan and design based on actual conditions rather than meet the index (e.g., green space ratio). The GI construction should be a guiding planning strategy system that gives local planning departments greater power for decision-making and development. We should conduct regular monitoring during the implementation of

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the GI construction and update the construction based on the monitoring results as soon as possible.

4 An Empirical Study on the Construction of the GI Network 4.1 Study Area Yongcheng is the easternmost city in Henan Province. It is located at the junction of Henan, Anhui, Jiangsu, and Shandong, Covering a built-up area of 35.94 km2 between 114°48 –116°39 E and 33°42 –34°18 N. The east–west width is 62.25 km, the north–south length is 72 km, and the total area is 2012 km2 (Fig. 4). The built-up area of its central city is 35.94 km2 . Yongcheng City is a regional sub-central city and a national garden city in Henan Province. Moreover, Yongcheng is one of the six large anthracite coal bases in China and the largest coal chemical industry base in Henan Province.

4.2 Current Status and Evaluation of the GI Network in Yongcheng Up to 2018, according to Yongcheng Urban and Rural Master Plan (2015–2035), the urban area is divided into Dongcheng District and Xicheng District. There are rigid control indexes for urban green space, but the GI network in the city’s periphery is unclear, and there is no constraint. The public green spaces in Xicheng District are

Fig. 4 Location of Yongcheng in Henan Province, China

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Fig. 5 Land use and land cover map of Yongcheng

mainly concentrated around Chongfa Temple, and there are no coastal green spaces and green spaces along the river. The public green spaces in Dongcheng District are mostly street green spaces and smaller parks, but large-scale comprehensive parks are still lacking. The main GI problems in Yongcheng are (1) the imbalance between green space construction and regional development, (2) insufficient green space planning strategies, and (3) the existence of untreated mining subsidence land. The land-use type data of this study comes from the interpretation of remote sensing image data. We use unsupervised classification combined with target interpretation and field investigation to get LULC information (Fig. 5), and we finally get five land classifications. The remote sensing data is obtained from the geospatial data cloud platform (see www.gscloud.cn). We divided land use and land cover into 5 types using landsat8 OLI images (spatial resolution is 30m) of Yongcheng on August 8th in 2018. The geospatial reference data is the vector file of the administrative division of Yongcheng City. We processed the analysis with the help of ENVI5.3 and ArcGIS 10.4.

4.3 Extraction of the GI Network Morphological Spatial Pattern Analysis (MSPA) is a tool used to describe and analyse geometric shapes. It is an image analysis derived from mathematical morphology

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and based on lattice theory and topology. Mathematical morphology is based on binary morphology, using morphological, structural elements to measure and extract corresponding shapes in images and classify them based on their shape characteristics and structural characteristics (Soille and Vogt 2009; Vogt et al. 2007). This paper’s extraction of GI core areas and corridors is based on the morphological spatial pattern analysis. The extraction of stepping stone is based on the accumulated cost distance surface. Based on the land cover map of the study area, the forest, grassland, rivers, and lakes extracted by remote sensing interpretation are used as the GI elements (foreground), and the rest of the land types are used as non-GI elements (background). GI hubs and corridors are recognised with the help of ArcGIS and GuidosToolbox based on MSPA. Use Neighborhood module, Flow Direction, Flow Accumulation in Hydrology module, and raster calculator to extract the maximum cumulative cost distance path and minimum cumulative cost between source patches, and we use the intersection of the two paths as the ecological stepping stone (Fig. 6).

Fig. 6 GI elements in Yongcheng. The a core areas, the b corridors, and the c stepping stone

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4.4 Evaluation of the GI Network In this part, we use the landscape pattern index method for the evaluation. We calculated the landscape pattern index from the patch level index, class level index, and landscape-level index. Combining related research results (Baldwin et al. 2004; Langford et al. 2006), we use GI patch composition, GI spatial characteristics, and GI landscape diversity to build a landscape pattern index evaluation system. All the indexes are completed on FRAGSTATS 4.2 (Table 2). We calculated the number of patches patches (NP), patch area ratio (PLAND), and area ratio (CA) for measuring the GI patch composition. And we calculated the patch density (PD) and maximum patch index (LPI), and patch index (LSI) for measuring the GI spatial characteristics. And GI landscape diversity is measured by Shannon Diversity Index (SHDI), landscape richness density (PRD), and evenness index (SHEI). From these indexes above, we know that the current GI network of Yongcheng City has a relatively high degree of fragmentation. There are obvious differences in the importance of various GI landscape elements. In addition, the GI network has a low degree of landscape diversity and low abundance.

5 The Optimisation of the GI Network of Yongcheng 5.1 The Optimisation Concept of the GI Network The optimisation of the GI construction should not only be based on nature as the main principle, nor should it be based solely on human needs. It should respect the laws of nature and maximise the satisfaction of residents’ demands to optimise the structure and function of the urban ecosystem. In order to dredge the coal city landscape pattern and integrate the mining wasteland (especially the collapsed water area) into the urban GI construction. At the same time, we should also pay attention to integrate farmland, rivers, lakes, urban green spaces, and wetlands into the urban GI optimisation construction to improve the heterogeneity of the coal city landscape and stabilise the city ecosystem.

6 The Optimisation Approach of the GI Network 6.1 GI Core Patches Optimisation The patch level is determined according to the patch’s importance and the patch’s size. This progress is based on the landscape index IIC and dA with the help of Conefor Sensinode2.6 software and ArcGIS 10.2. We select patches with an area greater than

NP

10,988

3926

2476

2007

204

19,601

Land use

Forest & grassland

Cropland

Rivers & lakes

Construction land

Transport

Total

17,076.33

22.23

227.07

3561.66

451.98

12,813.39

CA(hm2 )

Table 2 Landscape characteristics in Yongcheng City

100

0.13

1.33

20.86

2.65

75.04

PLAND(%)

–

1.1946

11.7531

14.4996

22.9909

64.3464

PD

–

0.0043

0.0042

1.0920

0.0063

1.2017

LPI

–

14.4688

45.9703

70.4322

64.6831

142.7629

LSI

0.0293

–

–

–

–

–

PRD

0.7047

–

–

–

–

–

SHDI

0.4378

–

–

–

–

–

SHEI

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Countermeasures and Empirical Research on GI Network Construction … Table 3 Ecological patch classification of optimised GI network in Yongcheng

311

Patch level Amount Location Level 1

2

Riyue lake scenic area Hui river- Wangji zone

Level 2

7

Mount Mangdang scenery Jangkou water conservation area Tuo river country park area Xuehu mining district Chensiloumining district Gucheng cultural protection area Riyue lake scenic north district

Level 3

5

Huanjin lake- Hui river zone Zanyang cultural protection zone Shunhe mining district Liuhe mining district Prehistoric cultural relics protection zone

10hm2 and an IIC greater than 1.5, combined with the natural breakpoint method. Finally, 14 important habitat patches are identified, including two patches at the first level, seven at the second level, and five at the third level (Table 3). The important habitat patches that are priority protection are mainly located in the Riyue Lake zone, Tuohe Scenic Belt, Hui river-Xinqiao-Mangdang zone, Xuehu coal mining subsidence district, and Chensilou mining subsidence district. All the patches are a nature reserve, water conservation area, and coal mining subsidence remediation area. The restoration target for the first-level protected patches is to protect biodiversity, and human activities are strictly controlled in the surrounding areas. The coal mining subsidence area is given priority to restoration. Human activities can be appropriately controlled for the second-level patches, and economical construction activities with less impact can be appropriately considered. For the third-level patches, the development of eco-tourism and other activities can be appropriately encouraged, and development can be carried out rationally (Fig. 7).

6.2 GI Corridor Optimisation Ecological corridors are an important part of GI network construction that connect different ecological patches together to maximise ecological effects (Mo et al. 2017; Wang et al. 2020a, b). We need to consider urban ecological construction, restoration of mining wasteland, and humanistic appeals when we optimise the GI corridors, aiming to build a multi-objective and comprehensive corridor. This paper uses the minimum cumulative resistance model (Eq. 1) to optimise the construction of the corridor (the least cost path is the least liquidity cost path, which does not mean that the target species will definitely choose the corridor to move during the actual migration process). The Minimum Cumulative Resistance Model (MCR) is an important method for studying landscape, ecology, which was first proposed to simulate pollen

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Fig. 7 Priority of GI core patch in Yongcheng

transmission (Knaapen et al. 1992). Essentially, the most petite cumulative resistance model is to realise the quantitative analysis by calculating the resistance values of different landscape units. The formula is as follows: MC R = f min

i=m  

Di j × Ri × ki



(1)

j=n

Where MCR represents the minimum resistance, Dij represents the distance from source j to resistance factor i, Ri represents the resistance factor, Ki represents the value of the resistance factor faced by source i. Its value is related to the expansion capacity of the source. The entire formula reflects the work done by the species to overcome resistance from source j to unit i. This paper uses ArcGIS to build a minimum cumulative resistance model, in which the "source" and the resistance factor are the keys to the realisation of the model. According to relevant research literature (Fu et al. 2012; Gao et al. 2020; Hu et al. 2011; Kong and Yin 2008; Wei et al. 2018), the cost surface in this study is a comprehensive weight value composed of multiple factors. The "source" in this paper is the central source of the core patches. The resistance factor refers to the research results of related researches (Liu et al. 2010; Li et al. 2016, 2018, 2019; Yao et al. 2021). Based on the type of land use, we select the resistance factor. The resistance value of the corridor, the potential ecological restoration corridor, and the

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Table 4 Landscape process resistance Landscape category

Subclass

Resistance value I: (Ecological and ecological restoration corridor)

Resistance value II: (Cultural corridor)

Ecological source

–

1

200

Core area

Level 1 Level 2 Level 3

5 10 15

100 20 10

Corridor

Level 1 Level 2 Level 3

20 25 30

100 20 10

Stepping stone

Level 1 Level 2

30 40

20 10

Forest and grassland

–

30

20

Cropland

–

50

40

Rivers and lakes

–

100

30

Construction land

–

1000

50

Transport

–

800

1

resistance value of the potential cultural recreation corridor are based on relevant data and expert consultation (Table 4). The resistance value reflects the relative ease of movement, and the evaluation system is dimensionless. This paper constructs the corridor to meet small mammals’ movement goals and particular bird habitats (e.g., Azure-winged magpie, and Mandarin duck). Finally, we get 105 potential ecological corridors, 14 ecological restoration corridors, and 26 humanistic corridors with the help of the ArcGIS 10.4 platform. Based on the location of the corridor and the level of the ecological patches connected by the corridor, we divide the corridors into two levels. “Level 1” connects the first-level ecological source patches and the second-level ones. And “Level 2” connects the second-level ecological patches and the third-level ecological patches. There are four “Level 1” corridors in Yongcheng, which are the city’s main ecological space. And the rest four “Level 2” corridors can strengthen the ecological network.

6.3 GI Stepping Stone Optimisation We use the optimisation method of elements in the ecological network to identify the GI stepping stone, which is based on the geospatial grid method and is implemented through the Create Fishnet command in the ArcGIS 10.2 software platform. We can get the distribution of stepping stones in the study area. It can be clear that the areas with fewer ecological stepping stones in the study area are ecological blind areas. After clarifying the blind areas of ecological stepping stone, integrating with the potential ecological corridors, we confirm the potential ecological stepping stone

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Fig. 8 Blind identification of ecology stepping stone in Yongcheng

positions and determine the key optimisation areas and non-key optimisation areas of the ecological stepping stone according to the distribution of connectivity (Fig. 8).

7 GI Network Optimisation Countermeasures? 7.1 Corridors and Stepping Stones Optimisation Countermeasures From the above analysis, we identified three different key types of ecological corridors and blind zone of ecological stepping stones: (1) we get Jiangkou-Shunhe-Xuehu ecological corridor, central urban area-Gaozhuang-Miaoqiao ecological corridor, and Wolong-Wangji-Xinqiao ecological corridor, in order to provide more routes for biological movement and to increase the city’s GI supply function; (2) there are four cultural and recreational corridors, the Wolong-Yucheng recreational corridor, Peiqiao-Xinqiao cultural corridor, Xinqiao-Taiqiu cultural corridor and MangxianChengguan cultural corridor, forming a linkage effect with the surroundings; (3) we select Gucheng-Shunhe-Riyue Lake- Xinqiao Water Conservation ecological restoration corridor is selected to enhance the ecological effect of the region; and (4)

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Fig. 9 GI optimised corridor in Yongcheng

we also add some ecological stepping stone to the blind zone to make the GI network more effective (Fig. 9).

7.2 Priority of the Restoration of the Mining Subsidence Areas Based on the above output, we make four priority restoration classes in mining subsidence areas: “Priority class 4” has the highest priority, mainly distributed in Chensilou and the Chengjiao districts. For this class, we should consider restoring the subsidence to the large-scale Conservational Restoration areas to maintain the ecosystem service function. ‘Priority class 3’ was mainly distributed in Xuehu district, Xinqiao district, and Cheji North district, which suggest to restore to large green open spaces that allow moderate human activities. ‘Priority class 2’ was mainly distributed in Cheji South district and Xinzhuang district, which we expect them to restore into the small green site. ‘Priority class 1’ has the lowest priority and is mainly distributed in Shunhe East district, Shunhe West district, Liuhe district, and Gedian district, that can be considered as a green open space in urban construction (Fig. 10).

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Fig. 10 Priority of ecological restoration in subsidence areas

7.3 Priority of the Restoration of the GI Network GI networks are divided into two classes based on the priority of the cores and corridors: Level 1 patch and corridor are selected as the “Priority Level 1” network; the level 2 and level 3 patches and level 2 corridor are selected as “Priority Level 2” network. And then, we get the final GI network for Yongcheng (Fig. 11). “Priority Level 1” network is based on four corridors: Mangdang-Chensilou- RiyueHuangkou corridor, Tuo- Riyue- Yucheng corridor, Gucheng- Chensilou- Shunhe corridor, and Wolong- Yucheng- Xinqiao corridor. We suggest that an ecological buffer zone should be set around these areas to prevent them from being disturbed by the urban economic construction. And for the “Priority Level 2” network, we suggest that these areas should be restored into the landscape, recreation, and urban ecological area based on respect for nature.

8 Discussion and Conclusions More precise models are needed to optimise the GI network in future research, such as the cellular automata model, system dynamics. In addition, our analysis has some limitations. The MCR model in our study is based on the existing related research and expert knowledge, which will have different results for different species. Thus,

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Fig. 11 Distribution of GI network in Yongcheng

a method that can validate the output to ensure its efficacy is needed. As a data limitation, we cannot do the research at the regional level. All analyses depend on the data availability of the study interest, and we hope that more landscape-level research studies could be seen in the future. Furthermore, in our study, cropland land is regarded as one type of important land use, which accounted for 67.89% of the total area. As for the cultivated land may bring threats such as the loss of habitat and pesticide pollution. Therefore, we do not consider it as an ecological area in the analysis. Moreover, the ecological restoration of mining subsidence areas is a longterm and dynamic, and our research does not consider the dynamic connotation. We will do the ecological restoration scenario simulation in the following research. However, large numbers of coal mining subsidence areas in China still have an unrestored status (Hu et al. 2018) due to the urban planning focus. And this status will change better after the implementation of territorial spatial planning. The coal cities in the Eastern Plain are typical resource-based cities, including different types of coal cities. The high groundwater level has made large areas of collapsed water in its mining abandoned areas to be the prominent feature of these coal cities. Ecological and environmental issues have attracted more and more attention developing resource-based cities. The conflicts between resources and environment, resources and development are unavoidable problems in its urban development, and the GI network is the key to ensuring the sustainable development of cities. However, the abandoned mining land in plain areas is generally restored to agriculture. Some

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Land use management departments choose some typical and easier cases for restoration in general, which result in the improvement of local ecological effect but not the overall ecological effect of the city. Therefore, it is necessary to use GIS and other analytical methods (e.g., InVEST) to create the integrity green space in the coal city, promote the restoration of landscape fragmentation, and restore ecological problems. At the same time, we could also improve residents’ quality of life and promote city transformation and sustainable development. Acknowledgements This work was supported by the National Natural Science Foundation of China (Grant No. 41671524). We would like to thank the coal mining subsidence data provided by Yongcheng Bureau of Geology and Mineral Resources. We would also like to thank the other members of the project team for the helpful discussion.

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Strategies and Tactics for the Design of Green Infrastructure in the Public Realm of Chinese Cities Fin Church, Siyan Zhang, and Yu Ye

Abstract Core to Green Infrastructure (GI) concept is multi-functionality serving manifold benefits across the environment and society. This chapter presents current design strategies and tactics, mainly spatial strategy, to establish multifunctional green infrastructure in the public space of Chinese cities. The spatial strategy will be used to determine the overall planning and spatial integration of the scheme. It will provide a framework throughout the planning and design process for the substrategies and tactics to be considered and executed in parallel with a cross-reference. It is noted that the associated spatial and material qualities of each service category are often interlinked and overlapping. The chapter examines the spatial strategy and takes a look at sub-strategies with selected case studies. The findings help develop strategies and tactics for the design of GI in the public realm of Chinese cities. The concluding remarks could be utilised as planning and design guidelines for future GI integration projects in public realms. Keywords Green infrastructure · Public realm · Chinese cities · Biodiversity · Multi-functionality · Morphological spatial pattern

1 Introduction Green Infrastructure can mitigate environmental degradation, increase biodiversity, increase resilience and maintain quality of life, bearing social-economic benefits (Wang and Banzhaf 2018; Tzoulas et al. 2007a, b; Hansen et al. 2019). GI’s broad and evolving definition encompasses a correspondingly broad and evolving set of F. Church (B) Planet Earth Ltd, Ningbo, China e-mail: [email protected] Planet Earth Ltd, Grantham, England, UK S. Zhang Ningbo University, Ningbo, China Y. Ye Beijing Forestry University, Beijing, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_13

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spatial typologies that range in the urban environment from forest and river to green roof and wall (Wise 2008; Cameron et al. 2012; Norton et al. 2015). As it is recorded in previous chapters, China has seen an unprecedented scale and pace of urbanisation, which is intrinsic to the national aspirations of its leaders (Taylor 2015), namely, modernisation (Xinhua News Agency 2014). This process has, however, had significant adverse effects on the environment (Lin and Zhu 2018; He et al.2017) and climate, and it has been suggested that the negative consequences of urbanisation on health outweigh the positives ones (Van de Poel et al. 2011). Thus the central government has since the 1990s applied environmental policies and regulations to cities (Zhang et al. 2019). More recently, the National New Urbanisation Plan (2014– 2020) proposed a set of guiding principles that included the ‘Ecological Civilization’ concept (Xinhua News Agency 2014). The continued emphasis on the deepening of the new urbanisation model, as stated in the 14th Five-Year Plan and Long-term Goals for 2035 (Xinhua News Agency 2020), promotes liveable, green, resilient cities where ecological restoration projects are, according to Wang Menghui, Minister of Housing and Urban–Rural Development, ‘implemented in a bid to improve the quality of the living environment’ (Xinhua 2020). The services provided by GI in cities can be mapped to Urban Ecosystem Services (UES), which are commonly divided into three or four categories. These categories include Habitat or Supporting services, Regulating services, Cultural services, and Provisioning services (MEA 2005; Haase et al. 2014), where Habitat or Supporting service and Regulating services are combined (Haines Young and Potschin 2018). These service categories and associated benefits define and drive the key substrategies of multi-functional green infrastructure design metastrategy, the spatial strategy. Regulating and Habitat or Supporting services include environmental purification such as bioremediation of polluted waters, management such as stormwater control and temperature regulation, and sustainable living spaces for organisms. Cultural services include enabling direct interaction with living landscapes, recreation, and spiritual fulfillment, contributing to health and well-being by delivering cognitive, psychological, and physiological benefits. Provisioning services include the output of consumable materials such as food, water, and timber (Haines-Young and Potschin 2018) (Keniger et al. 2013; Kaplan 1995; Rudolf de Groot et al. 2005). Correspondingly, the key sub-strategies are; (1) Increasing biodiversity, (2) Floodwater management-based design (sponge city), (3) Human scale leads space design, increasing urban public areas and amenity, (4) Urban food production. This chapter uses spatial strategy to determine the overall planning and spatial integration of the scheme. It then provides a framework throughout the planning and design process for the sub-strategies and tactics to be considered and executed in parallel with a cross-reference. It is noted that the associated spatial and material qualities of each service category are often interlinked and overlapping. The following section will examine spatial strategy and take a look at sub-strategies one and two with case studies.

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2 Spatial Strategy, Integrating Ecological and Social Logic into the System 2.1 Brief Introduction of the Chinese Planning System Throughout the ancient Chinese period, there have been two major schools of thought and complementary strategies for the planning system; (1) Power Structure-based strategy as evidenced in many great size historic cities built in China, such as Changan, Beijing, Luoyang, and Nanjing. The theory behind the design focuses on the spirit of God and an attempt to present the human and cosmic natures in harmony. For instance, the spatial structure of Beijing was that all the major temples had to be built along the center axis, and the center of the whole city is the palace, which also shows the power structure of the kingdom. (2) Daoist concept-based strategy; In the Daoist ideology, human beings are a part of nature, and everything is related to each other to form a strong force. This belief is named “TianReHiYi”, which means nature and human harmony and is reflected in the spatial design. Unlike the Power Structure planning system, the highest goal within the Daoist concept-based strategy is that any artificial work should look like nature created by itself; organic. Hence, there is an avoidance of Euclidian geometry and perfect symmetries. The famous examples found under the Daoism school are Hangzhou Westlake and Suzhou Gardens. The Modern Chinese Urban design theory originated in 1946. Liang Sicheng first mentioned in the article “Urban physical environment and his plan” in the People’s Daily; it proposed the city should meet four functions: Residence, work, recreation, and transportation. In the 1980s, after the reform and open policy of China, with rapid urbanisation, the urban design theory developed along with economic development. In 1990, Huang translated Edmund N. Bacons’ “Design of cities”, and in 1989 Wang, using comparison studies symmetrically researched into different urban design theories and practices in cities across the world. In 1991 Chinese City Planning Legislation was enforced. In line with the law, in the same year, the urban planning standard states every stage of any urban project has to go through the planning process. Since then, Chinese planning theories have developed rapidly. The fundamental characteristic of the Chinese planning system is the Planning Control System, which is the regulatory system; it is based on administrative law and a written constitution. Under the system, development control is based on a complete statement of what is permissibly made in advance. It is stated that the planning control system has two different types, (1) Legislation Control; the government agency such as the local planning department will set up the general regional-scale planning, and through the planning control system control the actual development. (2) Administrative Control, the control system based on the law or other development standards to control the specific development project; a planning department will undertake the control tasks through the administrative tool, design approval. The control index normally includes the environment standard, the project boundary,

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building height, volume, etc. Under the economic-driven market, many local governments will encourage the developer to invest in the public space in lieu of meeting specific planning requirements. There are many problems associated with recent planning and renewal planning methods, particularly the ecological and environmental issues. Neglecting the natural structure of the space and emphasizing the structure or function balance breaks the potential linkage between spaces by nature, weakens the natural bio function, ruins the existing biological chain, destroys the natural ecological process, and reduces the psychological restoration serviceability of public space. The conflict between urban development and ecological protection becomes more and more intense; the planning system struggles to properly deal with the problems for land usage while considering both ecological and sociological perspectives. Cheshmehzangi (2016) argues for China’s city planning, suggesting that the cities are planned at a large scale, often with high-density patterns. This trend continues to grow beyond their existing capacity; there are usually no clear green buffer zones around Chinese cities. Various approaches of leapfrog development and satellite cities are negatively contributing to this unmanageable pattern of expansion. The current planning system was based on the 1990 “China Urban Planning legislation” but did not specify the overall planning task. The later version of the legislation, Article no. 22, states that: “According to the outline of urban planning, the task of urban master planning is to comprehensively study and determine the nature, scale, capacity and development form of the city, make overall arrangements for the construction land in urban and rural areas, reasonably allocate the infrastructure of the city, and ensure the optimisation of the development goals, development approaches, development procedures and layout structure of the city at each stage, to guide the reasonable development of the city” (see Tables 1 and 2).

2.2 Theories Review Regarding the Urban Planning and Green Infrastructure Integrated Urban Planning In this part of the chapter, we will review the different theories in urban design to understand the rationale behind modern planning, examine why the Chinese urban spatial structure is how it is today, and how green infrastructure could integrate with the existing system from a theoretical perspective. Regarding Chinese cities, we could generally separate the influential urban planning theories into four main categories: spatial pattern, the morphology of urban space, place, and ecological based. The work of the following typifies these categories. In 1882, Soria Y Mata first proposed the concept of linear city (Mazzeo and Fistola, 2009). It presents the importance of the transport system toward the development of regional development. Howard (1989) puts forward the concept “Garden City”, it emphasis the planning design should be the focus on the people. He created concentric patterns with open spaces, and his concept combined the town and country in

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Table 1 Master planning stage urban control system content: (Based on Zhoujin planning control of The urban public space, 2005) Content and Details control system Overall consumption level of public urban space

Land consumption level PP Environmental quality (air, surface water, noise) Road and square index (road space PP, square space PP, road network density) Green index (green area rate, green coverage rate, public green space rate, public green area PP) Waterfront and mountain region public space Centre region index (air quality, land use level, greenspace, road and public space)

Overall layout Road layout: traffic roads, street, pedestrian traffic system, avenue of urban public Public square layout: different square layout, size, the green ration in the space square, surrounding protection zone area, and surrounding protecting requirement Public green space layout: layout of different scale public green space, surrounding protection zone area, and general requirement from surrounding protection zone Building height zoning: strengthen the city landmark, landmark building height proposal, landscape building intention, sight corridor and shoreline building contour Building volume control: control requirements of maximum face width, diagonal length and building height, etc Historical culture layout: spatial control for protection area Waterfront public area protection control Important landscape exhibit belt: optimisation contour, vision protection, interface building volume, façade, lighting design

order to provide the working class an alternative to working on farms or in crowded and unhealthy cities. The idea puts forward the “organic decentralisation” urban planning theoretical system, it was developed to deal with the various problems of over-expansion of the big cities. In the paper, he discusses that new towns do not suddenly separate from the central city but move away organically. His theory of living organisms describes a city made up of many cells with certain gaps in between. The aim was to control cells. In his vision of the future, Wright (see Pigliucci, 2008) imagines cities will be based on community, and the space will be able to provide freedom and beauty necessary for the growth of the individual; the urban spatial structure will be decentralized and coexist with a natural environment. In the Broadacres project, Wright proposed a grid of high-capacity roads extending over the regional landscape, with each family occupying one acre of land. Hence, the overall space will be very open. Le Corbusier introduced the concept of "The City of To-Morrow" in 2022 and then the Radiant City in 1933 (Le Corbusier, 1987). The layout of Corbusier’s ideal city was inspired by the arrangement and functions of the

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Table 2 Detail stage for Renewal planning control system; there are 6 major types of elements that will need to be considered for the public urban space (Based on Zhoujin Planning Control, The urban public space, 2005) Types

Details

Land usage

Function form: function arrangement, scale, size, topology condition Spatial form: visual center, visual corridors, heights

Transportation

Accessibility: public transport, vehicle, walkability, parking space Spatial cognition: spatial form, path, spatial sequence

Spatial interface

Building Interface: height, building boundary, form, colour, materials Other Interface: the walls on the side of the street, green, advertising boards: height, form, materials, colour

Service facilities

Seats, sanitation facilities, sign, culture, information, and communication facilities serving radius

Green space layout

Green layout, shade space, plant species and composition, green planting facilities, water scene, water facilities

Lightings

Function lighting, decor lighting, landscape lighting

human body. Like a living organism, it consisted of organized parts that would work together as a whole. The basic spatial strategy was to create vertical architecture and leave plenty of shared open space in between for people to use and enjoy. The resulting horizontal areas would serve as traffic corridors and ecological parks. Le Corbusier’s model was most heavily adopted in the modern Chinese Planning system today. Bacon (1976) demonstrates the movement systems, i.e., the paths of pedestrian and vehicular traffic; public and private transportation are the fundamental forces and considerations that determine the form of the city (see Fig. 1 for six selected examples). He emphasizes the importance of the open space, the impact of space, color, and perspective on the city-dweller. Opposite to Le Corbusier’s Machine Pattern, Alexander (1979) was more aligned to Frank Lloyd Wrights concept of the organic architecture. However, it promoted design due to bottom-up community involvement. In publishing the Oregon Experiment (Alexander 1975), he states, “natural or organic order emerges when there is perfect balance between the individual parts of the environment and the needs of the whole". In addition, Roger Trancik, in his book "Finding Lost Space” (Trancik 1986), has criticized the cause of the lost space in the last five decades due to the automobile-oriented planning system, the attitude of the modern movement towards the open space, zoning or other land-use policies with lack of responsibility towards the environment. He believes the functionalism obsession with efficiency laid the groundwork for the loss of the space, and the solution to finding the lost space is using urban landscape design to establish the spatial framework of public design rules for streets, squares and prioritizing open to the design of individual buildings.

JinNan

Lanzhou

Fig. 1 Spatial framework of green infrastructure in six selected Chinese cities

Nanjing

Chongqing

Beijing

Chengdu

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3 Theoretical Framework for Green Infrastructure Design Of the urban planning theories, the most relevant one to the green infrastructure concept is urban ecological planning. Frederick Law Olmsted did much propagate the ‘lungs of the city’ concept regarding large public parks in cities as promoted by politicians in 18th England, particularly with the design of the New York Central Park; by which means he sought both to counter physical ill health and disease and provide mental relief for the city dweller (Thompson 2011). Olmstead stated that what we (the people) want in the town or city is the park as a central, accessible feature that provides ample amenity space. Patrick Geddes was the first to present the idea that both city and environment should evolve closely together (Gaddes 2017). He states, “the city is not a closed and autonomous organism but is located inside an environment taking and dissipating energy”. He emphasizes the unity and interdependent relationship between culture and nature. Geddes believed the urban design should encompass bioregional, geological, and human activity integration. His approach, ‘diagnosis before treatment’, became the framework of planning analysis tools today. McHarg (1969), in the book ‘design with nature’, presents a strong philosophical belief regarding the value of ecological process in nature and demonstrates a ‘layer cake’ method associated with the more modern GIS; a suitability analysis that maps ecological land values determining design to nature’s morphologies. He emphasizes form must follow more than just function; it must respect the natural environment. For instance, McHarg used the ‘landscape method’, the metropolitan landscape ‘METLAND’ team lead by Zube and Fábos (2004) employed a ‘parametric approach’ based on the statistical data information to the analysis of the site. Their approach focuses on the factors which influence each other, and through comparison, they study to create an optimal model. Since the beginning of the modern environmental movement, there have been many ecological-related urban planning approaches found in ‘A Systems Approach’ (Mcloughlin, 1973), urban and regional planning, Chadwick’s (1971) ‘A Systems View of Planning’. These examples are grounded in the systems thinking of biological sciences and treat the city as a complex system with several interconnected parts. During the same period in China, Ecologist Ma pointed out that the urban ecological system is different from the natural ecological system, which involves the ecological, sociological, and economic environment; those three elements interfere with each other. Wang (2010), in the book Ecological Civilization City, published by CPC Central Committee Party School Press, states the public planning strategy should focus on achieving the goals of harmonious coexistence between humans and nature. Such an approach should help improve the living environment and integrate economic development and environmental protection, natural ecology, and human ecology. In the 17th CPC National Congress, the Ecological Civilization Concept was put forward and written into the party constitution. The important ecological planning concept of greenways was initiated by Frederick Law Olmsted in nineteenth century America. The concept was to utilize the

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original river or other ecological corridors to create green public space, as demonstrated by Olmsted’s earliest greenway, the Boston Park System also referred to as the Emerald Necklace Fábos (2004). In 1959, William. H. Whyte, in his famous book ‘Securing space for urban America’, first mentions the words greenbelt and parkway, later in the 1970s, the greenway has been widely adopted (Whyte 1959). Charles E. Little in Greenways for America (1990), describes numerous greenways as linear space that follows the natural ecological corridors that could act as part of the urban road system and carry out the leisure function for the public. Flink and Seams (1993) provide a holistic approach to using the green corridor as the basic urban frame to create the spatial planning system, the space connected by the different size and green function corridors. Huang (2013) firstly proposed creating the green network and then determining the city development strategy. This means the transport network system, land usage, open space; will ultimately generate the city structure that feeds the overall environmental and societal needs. Landscape-ecological planning discusses general planning through the overall landscape perspective. It focuses on improving the overall space, such as habitat, sustainability, and urban development. At the same time, the landscape ecological planning approach is featured by the focus on the linkage of ecological patterns and processes. It integrates the sociological and ecological as well as economic perspectives of the environment. The concept of landscape urbanism emerged more recently, coined by Waldheim (2022), and is more design-focused; the landscape is posited as the foundation for city design with natural or cultural processes being used to organize the urban form (Steiner 2011). Ecological Networks: the literature on ecological networks is extensive. Ideas sprang from the need to reduce the isolation of species in human-dominated landscapes and understand the importance of spatial scale and provide for the migration and dispersal of species and the protection of large core areas such as ancient woodlands.

4 Green Infrastructure Planning and GI Planning Strategy and Methods in Major Developed Countries Green infrastructure is an interconnected network of green space that conserves natural ecosystem values and functions and provides associated benefits to human populations. (Benedict and McMahon 2001) Similar to Benedict, Natural England’s (2009) definition of green infrastructure emphasizes that “GI is a strategically planned and delivered network comprising the broadest range of high-quality green spaces and other environmental features”. The North West Green of UK Infrastructure Think-Tank has suggested that the green infrastructure has five significant characteristics: Typology, multi-functionality, context, scale, and connectivity. The GI planning strategy and method have been adopted in many regions across the world. However, the fundamental approach was very similar; based on the GIS

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information, a base plan, and then according to the base plan to fill the other contents, such as settlements, related economic activities, circulation for the space, etc. Table 3 below shows methods and approaches related to such GI planning strategy.

4.1 Green Infrastructure Development in China As we have introduced earlier, China’s spatial planning system, which is highly function-based, has always emphasised economic development. The government at almost every level prioritises the Gross Domestic Product (GDP) growth rate. Consequently, China has had significant economic achievement over the last 30 years; on 25th Feb 2021, China claims all 98.99 million rural poor people have been lifted out of poverty. Without any doubt, the highest function-focused spatial planning system is effective in economic development. However, the same system, especially regarding insufficient consideration of the environmental or ecological aspects in the land policy, has caused severe problems, such as development disparities, uncontrollable urbanisation, water scarcity, biodiversity loss, and destruction of the ecological environment, pollution, and disease. All those problems will restrict sustainable development and may cause a great threat to social stability, especially passing carrying capacities, which can cause dramatic alterations in ecosystem functions, leading to social-ecological collapse (Cumming and Peterson 2017). In recent years, the top institution of China government has understood the importance of the ecological environment and that the old planning system might cause environmental issues. President Xi Jinping and the Central Committee of the Communist Party refer to the spatial planning system as the major function zone system or functional zoning strategy (China State Council PRC 2010). In 2010, the State Council published the National Plan on ’Major Function Zones ’, which was subsequently upgraded to the ’Major Function Zone Strategy’ published in the 12th FiveYear Plan (2011–2015). The planning strategy, according to the carrying capacity of resources and environmental potential of different regions, separates the land space into four categories: (1) optimal and (2) priority development zones for urban and industrial functions; (3) restricted development zones for agricultural and ecological functions; (4) prohibited development zones for ecological and cultural functions. Following the national level plan change, in March 2014, the National New-Type Urbanisation (NUP) Plan starts to pay attention to environmental and ecological issues. However, its emphasis is on urbanisation’s importance and focuses on the town level and small-scale development. Cheshmehzangi (2016) has argued that urban planning with the current pattern is both pro-developer and economic-oriented. The NUP will put further pressure on the environment since increasing urban areas and extensive urban development. In the same article (ibid), he pointed out that the rural to urban lifestyle change will lead to more dependency on private car use, operational energy, and resource consumption. Also, the policies have shifted from economic development to a more balanced ecological and development integrated system. The natural system has separated

Strategy and methods

EEA 2013 report Based on the 20 years across EU countries experience, conclude the EU strategy for GI

• Different Scale GI should be interconnected and interdependent. It imports to set up the policy at EU level to be able reach full potential to restore natural capital and cut the costs of heavy infrastructure • Integrating GI into the key policy areas. Set up policies to implement GI spatial planning and territorial development, which will also facilitate the projects funding mechanism • The need for consistent, reliable data. Within the context of the EU Biodiversity Strategy, together with the European Environment Agency, set up the clear data, will help for the consistency of implement the GI strategy as well strengthen the scientific community research purpose • Improving the knowledge base and encouraging innovation. More research is needed to under stand the links between biodiversity and the condition of the ecosystem, hence the capacity to delivery the ecosystem services, boost the Bio economy • Providing financial support for GI projects. EU commission to provide the fund and policy support for the GI projects at all levels • EU-Level GI projects. Many geographical features go beyond national boundaries. They require coordinated, joined-up actions and a pan-European vision (continued)

American GI case studies, • Goal Setting: According to the site background information, setting up the clear goals according to the different concluded the standard “Green stakeholder Interest Infrastructure Plan Evaluation • Analysis: Using the landscape ecological theory as basic tool set up network design criteria and hence through the network suitability analysis by using the data information Frameworks.” • Synthesis: Enhance the model, future considerations of the scale of the network system, such as the scale, opportunity for (McDonald, Allen, Benedict the local development, how the system integrates overall etc O’Conner 2005) • Implementation: Set up the Conservation Strategies and funds for the future protection projects, and implementation strategy at different government managerial levels

Country or region

Table 3 Demonstration of country/region-level strategy and methods for GI planning

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Strategy and methods

Stage 1. Local Development Scheme: Identify how GI will be addressed in the Local Development Framework Stage 2. Strategic vision development and evidence base: (a) Environmental characterisation of plan, with mapped data layers. (b) Establish local need for GI functions. (c) Identify deficiencies in existing GI (amount and type). (d) Initial assessment of broad opportunities and key delivery partners. (e) Document evidence base for future examination in public Stage 3. Spatial options and policy development: (a) using the evidence gathered in stage 2 to draw up an outline GI network, or alternative options. (b) Identify GI opportunities. (c) Develop spatial GI options. (d) Develop supporting policy options. (e) Consult GI stakeholders. (f) Refine Options. Other relevant strategies. (g) Initial scoping of delivery mechanisms Stage 4. Submission Plan (Develop spatial plan for GI network with: (a) Strategic GI on Key Diagram. (b) All GI in Site Allocations/DPD/Area Action Plan. (c) Core Strategy policy framework. Consult on and define delivery. (d) long term management mechanisms Stage 5. Examination in public (EIP): Refer to GI evidence base, if required Stage 6. Delivery: (a) Secure relevant Local Area Agreement targets. (b) Planning decisions Stage 6. Monitoring: Monitor performance of GI in relation to identified functions Note: in 2008 revision of the planning policy, no longer regulates the LPA have precise detailed development plan Local Planning Authority (LPA) Local Developers (LDS)

Country or region

UK Natural England development 7 stages integrating green infrastructure, green infrastructure strategies and the spatial planning process for the local development framework Green Infrastructure Guidance www.naturalengland.org.uk

Table 3 (continued)

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space, but it is very different from the Green Infrastructure Planning system. The GI planning emphasizes the importance of multifunction. The central government will not schedule any strategy in advance, as introduced in the UK system. It will be locally based, case by case, set up the development goal and spatial strategy. Since the 1990s, the ‘Green Infrastructure Concept’ introduced in China has gone through three research stages of development, according to Jia (2013). Stage one includes early understanding, which was first introduced by SWA boss Kalvin Platt in the “Asia pacific region international park and other leisure facilities conference”. He proposed that constructing a green infrastructure network will have a significant impact on our living conditions. Stage Two is about the slow development period (2004–2008). Most research studies were based on introducing the existing Western green infrastructure theories. Amongst the most influential papers was Shen (2005) “A guide to green infrastructure for Canadian municipalities” published in Urban Planning magazine. It systematically introduced the basic characteristics of the green infrastructure and the spatial strategy, interconnecting and integrating with other spaces and services. Also, it states that the green infrastructure targets connect between buildings and space and service provision. GI would be a nature-based or low-impact design solution, considering appropriate materials and local resources, multifunctionality, and adaptability. This paper became the fundamental theoretical framework for the GI in China. Stage Three is about rapid development (after 2009). In this stage, GI has been one of the most studied areas in planning and architecture and landscape architecture. However, most research is focused on the specific area of the green infrastructure, such as ecology, green space, greenway, and rainwater management. Since the land usage and existing planning system, it is challenging to establish the green infrastructure network system. Therefore, larger cities, such as Beijing and Shanghai, try to promote the green infrastructure idea. However, it is only part of the overall open green system planning (Jia 2013). Currently, there are four major methods (strategies) for GI planning: • • • •

Ian McHarg theory-based Layer Cake Method Forman Landscape-Ecological theory-based GI network Method Landscape Metrics and Network Analysis method (Graphic Theory-Based model) Morphological spatial pattern analysis-based GI planning. The following four sub-sections discusses these methods in detail.

4.2 Layer Cake Method Creating “Physio-Bio-Culture” System McHarg (1981) introduces the theory of human Ecology planning. As stated in McHarg’s paper, ecological planning “can be defined as the study of the interaction of organisms and the environment. It is an instrument for revealing regions as interacting

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and dynamic natural systems having intrinsic opportunities and constraints for all human uses.” McHarg believes good planning (system) should be syntropic-fitnesshealth. In other words, planning the system which fits the environment requires the minimum work of adaptation, both environmentally and culturally. The Layer Cake method maps information such as: bedrock geology, surficial geology, groundwater hydrology, physiography, surface-water hydrology, soils, vegetation, wildlife, inhabitants, micro, meso- and macro-climate, in layers for analysis. This can be achieved through a geographic information system (GIS). Hence using the GIS data mapping the site became the fundamental strategy of green infrastructure planning. However, most projects in China will only use single layout data to map information and work out a specific problem, such as defining the nature conservation zone or the potential environmental hazard location. This approach is quite different from the original McHarg wish, to overlap all the layouts and find the intersection space as the natural hub, center.

4.3 Landscape-Ecological Theory-Based GI Network Method or Construct the Security Patterns of the Space Through Finding the Minimum Cumulative Resistance (MCR Model) The spatial analysis method based on the landscape ecological theory focuses on the ecological process and the GIS information. The horizontal ecological process influences the spatial pattern such as species migration, natural habitat fragmentation. The most widely used is the ‘least cost’ modelling to calculate ‘effective distance’ that a measure for distance modified with the cost to move between habitat patches based on detailed geographical information on the landscape and behavioral aspects of the organisms studied (Adriaensen et al. 2003). The least-cost method has become one of the most important pieces of evidence for constructing the corridor (Adriaensen et al. 2003). The planning methodology is as follows; first to determine the center of the ecological hub, and then according to the factors, such as land cover, water system, waterfront width, habitats condition, road, slope, land management to find out the potential resistance for the animal, work out the minimum cumulative resistance path from the center to each hub, finally, according to the surrounding terrain and land cover to determine the width of the corridor. C = f min

i=m   j=n

Di j × Ri j



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where C is the minimum cumulative resistance move from landscape unit i to source unit j; Dij is the spatial distance between unit i to unit j, and Rij is the resistance coefficient that in transition from landscape unit i and to source unit j. Therefore the potential green infrastructure planning will be able to be constructed through simulating the ecological process to find the critical position, possible nature spatial pattern, or security pattern (SP) (Yu 1996) and the minimum cumulative resistance pattern. Ecological security pattern has become the fundamental national land strategy (GuangMing Newspaper 2020). Using the ecological security pattern methods has been a widely adopted approach, especially in regional planning, such as Guangxi Hechi Karst Mountainous areas planning (Gao et al. 2021), Layout optimisation of rural residential land in the yellow sea region through the MCR method. The ecological security pattern planning method is also used for wildlife protection, i.e., Biological conservation security patterns plan in Beijing based on the focal species approach (Hu and Wang 2010). In the paper, the author pointed out, Beijing urbanized land is around 84.9%, the wildlife in a critical living condition, and the green infrastructure planning for protecting the animal habitats has been done through vertical GIS spatial analysis, the vertical habitat suitability analysis in which the optimum areas for species were selected as the movement sources, and then work out the movement resistance surface through simulating the horizontal movement across the landscape by using the MCR model.

4.4 Landscape Metrics and Network Analysis Method, Graphic Theory-Based GI Planning The network analysis method was originated from the graphic theory, which concerns the network structure and network optimisation (Linehan et al. 1995). In green infrastructure planning, the graphic theory became a very effective tool to analyze the connectivity in landscape planning; the spatial pattern could be simplified as a sequence of nodes and connections between the nodes. Under the landscape ecological theory, the degree to which all nodes in a system are linked is known as network connectivity (Linehan et al. 1995). A node generally represents a habitat patch, while each link represents the spread of species. There are two different types of patterns, a branched network and circuit networks. The cost balancing, that is, “cost to the user”, “cost to builder,” i.e., branched network and circuit network, is a general framework to explain the spatial patterning of networks (Hellmund 1989) (see Fig. 2). Generally speaking, minimize the builder’s cost. The network will be a minimum spanning tree, as in the Paul Revere example, in which all nodes are visited only once, with no extraneous segments. Models with the least cost to the user minimize the travel cost between two points and represent an ideal situation where all points connect directly (Hellmund 1989). Accordingly, the number, length, and density of corridors were undertaken to describe their structural

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Fig. 2 Different patterns, including Paul Revere, with minimum cost to builder (left), hierarchical (middle), and least cost to user (right)

characteristics. Combining two or more networks could extend to a very complicated pattern and create the ecological network. It developed a sequence of indications to measure the model, such as: network circuitry α, Node/line ratio β (Haggett and Chorley 1972), network connectivity γ (Forman and Gordon 1986), and cost ratio, which is based on the landscape conditions and socio-economic realities (Dalton et al. 1973). Interactions between nodes are usually assessed using the gravity model (Forman and Godron 1986); the interaction between the nodes is determined by the efficiency of the corridor and the importance of the node. Where Gab is the interaction between nodes a and b, Na and Nb are the corresponding weights, and Dab is the normalized cumulative impedance of the corridor between these nodes. G ab =

Na Nb 2 Dab

The gravity model can help rank the importance of the corridor by ordering the interaction between the nodes (G value) and hence help create the GI spatial plan. The graphic theory is a quick tool to understand the landscape and create a basic data-based framework for the site. Unlike the ecological security pattern method, the graphic model to construct green infrastructure planning has been widely used; most work is focused on nature conservation. Kong et al. (2010), using the combination of the least-cost path method, gravity model, and graphic theory, developed an urban space network for biodiversity conservation for Jinan city. The result suggests that the graphic theory and the gravity model combination methods effectively select the corridor. Hence, while establishing connections between different patches, there might be several choices, thus identifying the potential greenspace and urban planning for biodiversity conservation. However, using the graphic method also reveals problems in the current planning system. Zhang et al. (2021) used the graphic theory to help create the habits land for the amphibian in the XiongAn region. The optimal locations suggested by the graphic theory have improved the overall landscape functional connectivity of the habitat network by 19%. Zhang and Wang (2006) use the graphic theory to construct the green infrastructure plan and compare the result with the greenway augment plan issued by the local

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authority, and the result shows that the augmented greenway plan only have marginal improvement for the overall ecological condition through serials of landscape metrics (McGarigal 2014) the greenway plan carried out by the graphic theory-based network analysis has significant improvement to the ecological condition.

4.5 Morphological Spatial Pattern Analysis-Based GI Planning Morphological Spatial Pattern Analysis (MSPA), which is based on concepts from mathematical morphology (Soille et al. 2003), uses a sequence of controlled morphological mathematical inputs targeted at an image to derive values. We can use the MSPA method to identify hubs and links from a single map rather than the GIS overlay of several maps. The land cover is the foundation of GI network mapping. To construct the GI plan by using the MSPA method, the main steps are as follows. Based on the remote sensing image or the land use map information to obtain the information of the urban spaces, divided into urban green space and non-green space and identify the urban green space as foreground in the binary map, and non-green space as the background in the binary map. Then, segment the urban green space into mutually exclusive seven landscape pattern categories: Cores, isles, loops, bridges, perforations, edges, and branches (Chang et al. 2012) (see Table 4). MSPA is a relatively new approach; however, it offers an efficient and robust method that is also scientifically based to identify the potential corridors (linkages) and patches (hubs) in the urban green space area. Morphological Spatial Pattern Analysis approaches are normally in combination with Least Cost Path Model, Minimum Cumulative Resistance model, or Gravity method after identifying the potential linkages and hubs to help improve the overall planning. Table 4 Definition of categories in morphological spatial pattern analysis Core

Equivalent to hub, Patches surrounded by the foreground (greenspace) pixels and the distance to the background pixels is greater than the distance to the specified edge of the foreground

Bridge

Connect two or more disjunctive cores

Edge

The pixels form the outer transition zone between foreground and background (i.e., urban green space vs non green space)

Perforations The pixels form the inner transition zone between foreground and background (i.e., urban green space vs non green space) Isle

The green space pixel does not contain core

Loop

Within the foreground area, a pixel group represents the foreground and background conversion area

Branches

The green space pixel extends from one core green space, but do not connect to another green space

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He et al. (2021) used MSPA and Least Cost Path combination method to construct the Fuzhou City green infrastructure planning by using the remote sensing image and the GIS data to create the initial mapping (Figs. 3, 4, 5, 6, 7, 8, 9 and 10). In order to improve the Green Infrastructure plan, then use the Minimum Cumulative Resistance and the least-cost path method and gravity model to construct the potential corridors at multiple levels. The resistance factors, including landuse type, MSPA landscape type, elevation, slope, relief degree of the land surface, distance from railway, distance from the motorway, and distance from road, are in eight different categories. And the resistance coefficient was determined through the experts’ opinions and other researchers. It uses the Graphab 2.4 and ArcGIS 10.6 to select the hubs and linkages, and then use the least cost path model to create the multicenter network system and connect the linkage between the cores. The optimal choice of the linkage between the different cores could use the gravity model to select. According the MSPA method, and based on the PC (Probability of connectivity) value create the various level. The bigger the core area importance is to the ecological system the more linkages will be required (Fig. 6). Based on the Least cost model, using the Graphab, it worked out 265 possible corridor choices, and using the gravity model: Gab < 10, third level connection, 10 ≤ Gab < 100, and, Gab ≥ 100, first level connect; 149 GI nodes, using the grad system, according to the density of the nodes, D < 0.5 third level network center, D > 0.5 but not in blind area defined as second level network center. D > 0.5 but in blind ar ea de f ined as f ir st level networ k center.

Fig. 3 GIS based spatial distribution of land use type

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Fig. 4 MSPA based landscape type

Finally, based on the construction priority, economic development strategy, finish the Green Infrastructure Plan for the Center Fuzhou Region. Morphological Spatial Pattern Analysis has been adopted in many big regional green space planning by officials. Xie et al. (2020) study took 13 major cities in Sichuan in the Chengdu-Chongqing city group, using the MSPA method to identify the spatial structure of green infrastructure networks in each city. The study is based on the landscape composition, landscape pattern, and urban development (i.e., as the three criteria). It uses the analytic hierarchy process-variation coefficient method to construct the improved GI regional planning system. The result suggests that it is important to understand the ecological pattern and functions in a larger regional context, and cross cities cooperation is essential towards the region’s environmental protection and economic development. The MSPA method suggests that there are large numbers of ecological corridors in the region. The continuity of forest and river corridors is a priority. A large portion of the green infrastructure could easily be disturbed by human activities. Ecological Performance of Space Utilisation based-GI planning: An and Shen (2013) put forward the concept to use the ecological performance such as ecological sensitivity, patch choice, corridor scale, minimum path simulation, and spatial distribution of human ecology as the assessment tool to evaluate the effectiveness of the spatial structure.

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Fig. 5 Single factor resistance surface and comprehensive resistance

Fig. 6 Minimum cumulative cost resistance

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Fig. 7 Spatial distribution of GI network center at various levels

Fig. 8 Spatial distribution of GI connecting corridor at various levels

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Fig. 9 Spatial distribution of GI node at various levels

Fig. 10 A combined spatial distribution of GI nodes and connecting corridors at various levels

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5 Macro-Meso-Micro-Integration The following table orders and categorizes urban green space according to scale and spatial structure. These elements will be utilized in unison to form the comprehensive GI system (Table 5).

6 Community Scale Green Infrastructure Planning Community public space is an important place for locals’ daily life and communication where the community culture is formed, creating the fundamental social structure of the society (Carr et al. 1992). The current planning system focuses on peoples’ usage. The community-scale public environment includes three major aspects; physical, spatial structure, and culture. The physical aspects include mountains, rivers, public green space, squares, the trees around the built environment, and decorations on the streets; the spatial aspects include corridors, boundaries, nodes, signs; cultural aspects are such as the community history and social activity. Those three aspects form the overall substantial community space and public space system. The traditional community planning and renewal methods for community-scale public space will focus on those three aspects. However, these planning methods just ignore the internal relationship between public space and natural green resources and all the ecological perspectives in the area. The current community-scale planning method of public space is based on the mesoscale control planning system. It normally emphasises the overall integrity, human-used experience, and the structure of the space that fits the function of the area. The latter can be classified into three different types; linear structure, node structure, and public space network system structure. 1. 2.

3.

The community space’s linear structure is normally determined by the road system, according to the vehicle usage. The community-level node-oriented structure, where space can be divided into city-scale nodes and community-scale nodes. It is based on the service scope and scale level. Usually, this is function-based, such as residential blocks, commercial areas, police stations, hospitals, parks, etc. Under the condition of meeting the spatial index, its emphasis is on overall space balance to create efficiency in the space. Network system structure in the community is normally created by the different nodes and the connections in between. It forms the spatial foundations for the Chinese community and social network.

Important ecosystem in large area

Urban Green space network

The formation of community open space

Region (Macro)

City (Macro)

Community (Meso)

Morphological character

Spatial structure

Part of the overall ecosystem, and integrating for the sociological and ecological, public space

Community greenways, natural drainage ditches, community bicycle lanes, community footpaths, community stream corridors, green streets, river corridors and landscape corridors Small scale ecological land with single connection to community GI network

Community corridor

Community patch

(continued)

Community Park, community cemetery, garden, large-scale lawn, small-scale woodland, undeveloped reserved land

Independent urban ecological land

Park, pond, wetland, woodland, and other medium-sized ecological land connected to urban GI network

Urban river corridor, stream corridor, shelter forest, ecological greenway, urban bicycle lane, urban footpath, etc

Urban natural scenic spots and reserves, urban parks, zoological and botanical gardens, urban lakes, farmland, important reservoirs, large wetlands, forests, mountains, etc

Agricultural fields, large suburban parks, suburban golf courses, suburban reservoirs and ponds

Linear riparian forest, ridge line of main river corridor, valley and hilly forest, etc

Ecological sensitive areas, large inland forest, nature reserves, wetlands, lakes, coastal ecosystems, natural scenic spots, national parks

Elements

Community network

As the core In city network component of urban GI system, it ensures urban ecological Urban corridor security and biodiversity, and City patch focuses on supporting GI system Urban ecological island

The core component In regional network of regional GI system to guarantee regional Regional corridor ecological security pattern, the most important part of the Regional patch ecosystem

Main roles

Table 5 Urban green space categorisation based on their scale and spatial structure and four levels of Region (Macro), City (Macro), Community (Meso), and Field (Micro)

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Field (Micro)

Scattered distribution, focusing on the enhancement of environmental quality

Morphological character

Table 5 (continued)

Green infrastructure Implementation methods and part of the overall GI system

Main roles

Rainwater garden, wetland, detention pool, ecological planting ditch, green roof and vertical greening, permeable pavement, rainwater filtration system, etc Community garden, community farm, community garden, theme square, urban waterfront, etc Footpath, bicycle lane, greenway, Riverside walkway Ecological restoration, wasteland and agricultural land, urban brown land and abandon agriculture land

Rainwater treatment system Social service space Green transportation system Others

Independent community level ecological land

Community Island

The site level ecological greening landscape includes street green space, residential green space, street corner Park, small forest, bush forest, etc

Roadside tree row, flower bed, Bush row, building attached green space, corner garden, roof greening, small pond, building attached green space

Community ecological jump Ecological greening landscape

Elements

Spatial structure

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6.1 Introduction of Green Infrastructure in the Community-Scale and Procedures of the Green Infrastructure Planning Community-scale green infrastructure is understood as a network of groups and projects which aim to deliver locally relevant functions and benefits to respond effectively to changing social and environmental needs (Jerome 2017). Similar to the “spatial structure” in community public space planning research, community-scale GI can also be described as the spatial structure; GI planning structure refers to the spatial pattern formed by the interconnection and connection of various spatial units. According to Forman and Godron’s (1986) Landscape Ecology theory, the elements in the natural system can be separated into three major categories, namely patch, corridor, and mosaic. It can be used as a basic structure in the Green Infrastructure planning system. Corridor: Road and the tree surrounded by the road, river edge, green walkways, bicycle lane, landscape corridor, and liner rain garden. Patch: General speaking, the patch was formed by the edge and content within. Typical patches in the community include a pocket park, pond, roof garden, trees, and flower parterre. Mosaic: Community Parks, squares, rain gardens, golf courts, anything at the community levels. The objective for the community green infrastructure is normally to improve the quality of the living environment. In terms of planning, it is the same as the traditional planning method. It will be required to pay attention to the spatial structure, such as the connection between different patches, the overall network system, the ecosystem, and the functional biodiversity of the space. The planning system will be based on the biodiversity, flood management, and function of the public space. And the procedure of the Green Infrastructure planning for the new development areas will be as follows. (1)

Set up clear targeting such as what ecological problem might arise in the community area. For instance, the risk mapping identifies the potential problems related to natural hazard, such as floodingc, fire, and ecologically sensitive areas.

Ecological priorities system Priority ecological area

Conservation areas, such as natural forests, mountains, wetlands, especially pay attention to the ecologically sensitive area with threatened species

Significant ecological area

Fresh open water area, such as rivers, lakes; woodland; Meadows, Agriculture lands

Other ecological area

All man-made area, such as parks, ponds, green corridors, other public open space with soft landscape

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Identify the ‘Corridor’, ‘Patch’, and ‘Mosaic’ as three aspects in the planning area and green nature green infrastructure layout plan. i.e., where the animal is likely to inhabit, a suitable location for the green mosaic; is there any specific requirement condition for the animal migration. Identify the function structure of the community area and other requirements for the urban public space, culture, history and economic viabilities of the area, and other elements of the public space. Potential incorporation with the public space and the green infrastructure area, such as increasing the number of pocket parks and green corridors.

The integrated planning system: The space structure under both GI design and functional public space structure design. The spatial patterns under the functionbased planning system, most common in China currently are; Rectangular pattern, Radical Pattern, Radical Ring Pattern, Linear Pattern, Contour Forming, and Combined patterns. The road and streets determined all those patterns. The green infrastructure planning system will put forward the importunateness of biodiversity and Nature-Based Solutions as essential. However, for the renewal planning system, which will be based on the existing conditions of the site, the green infrastructure planning will have to be incorporated (see Table 6).

6.2 Strategy Two: Increasing Bio-diversities The global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES 2019) concludes that ‘nature is declining globally at rates unprecedented in human history. It also states that the rate of species extinctions is accelerating, with grave impacts on people around the world now likely’. Then IPBES chairman, Sir Robert Watson, is quoted regarding the loss of biodiversity; “We are eroding the very foundations of our economies, livelihoods, food security, health and quality of life worldwide… it is not too late to make a difference, but only if we start now at every level from local to global”. The IPBES report promotes nature-based solutions within urban areas, improving access to green spaces and ecological connectivity within urban spaces, particularly with native species. Biodiversity includes the diversity within and between species and within and between ecosystems. Biodiversity enhances ecosystem resilience (Fischer et al. 2006). The basic strategy is to create sustainable habitat environments for, mainly native flora and fauna; this consists of creating patches for habitation, corridors for habitation, and movement between patches and possibly extra-urban green areas and buffers for sensitive habitats. The Green infrastructure design should focus on making the place attractive and connected to the fauna and consider the habitation behaviors such as migration, foraging, and breeding.

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Table 6 The strategies for urban renewal system under GI planning Current Features function-based structure

Linear pattern

A primary thoroughfare radiates down the center with buildings on either side

The road system cut off the eco system, there is not any intersection necessary for the structure either, hence the strategy will be creating green patch, pocket pack and any road cross position, add additional eco island

Streets are grid-like, with parallel streets intersected by perpendicular streets

There are many intersections in the grid system, we could add the green patch or green mosaic to create and green corridor along the road, to create an ecological web system

Terrain relief influences construction of road, which normally parallel to contour lines, with intersecting roads connecting them

The mountain area is the dominant nature ecological area, the GI planning could add some patch green space to accommodate the nature resources

It is generally centric design, all the rings are the road, which will intersect with both radial and ring

Based on the radical ring structure, to improve the overall ecological system, the design could include patch of green space, green corridors, or even mosaic, such as community parks, to create an ecological network system

Rectangular

Contour forming

Radial ring

Mixed

Potential Biodiversity based GI strategies

Based on the function of the space, Similar as the radical ring system, the the road connects different place, and mixed structure has many node space, without clear geometric patterns the GI strategies will be focus to create a comprehensive ecological network, by add green corridor, green patch or even green mosaics in the community

Hence, with the urban green infrastructure planning and design, a considerable challenge is to create the system that fits the social structure and provides an environment suitable for fauna habitat, encouraging connection between different species. There are seven basic spatial design categories of patch and corridor format with regards to green infrastructure implementation in public areas of cities; spaces from each type should be deployed in tandem to create and connect fauna habitat and help establish a better ecosystem.

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(1)

(2)

(3)

(4)

(5)

(6)

(7)

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The city park. Due to scale, this may be the most crucial eco-environment. For example, West Lake sits in the middle of Hangzhou city. It connects many different parts of the city and links residential, commercial, and some of the most important structures built around West Lake. If there is a large area of natural green resource, such as wetland, lakes, mountains, it will be the natural eco focus point for the overall area in green infrastructure planning. Other things should be able to connect to the area. Community or Pocket park. The small-sized park provides links for the green corridor and other major green areas. It will be vital for the migrant animal temporary settlement and provide the locals’ vital communal space. Eco-island. Suppose the area is far from the city or community park, such as in the industrial-based area. In that case, the green infrastructure planning will require adding a green island to facilitate the animal needs to achieve biodiversity even if there is no structure demand. Green corridor. The green corridors in the city include river edge green space, road edges, and green corridor. It is the linkage between different ecological environments, enabling bio-system energy dynamics and providing the space for everyday human activities such as walking. The green corridor is also an essential view corridor. The green corridor is generally over 10 m wide, providing security for birds and some amphibian settlement. Streets with vegetation. The green separation belt on the road or green corridor on the side of the road is typically 1 to 3 m. It is the essential linkage between different green areas. Small patch on the road. Add shrubs or trees on the Road, for example, around the traffic island, add bit green, it will be vital for birds, creating the ecological jumping points for the animals. Public square. The public square design should not only focus on social utility but also include vegetative elements and areas.

Increasing the connectivity between spaces: Both Function-Based planning systems and green infrastructure planning systems are essential for designing the urban services, e.g., water resource, water cycling, energy generation, food cultivation, mass mobility, and network communication as living landscapes. McHarg (1969), focusing on energy in nature, discusses the ecological circles, nature’s morphologies and has given the basic framework of how the landscape design should be incorporated with the natural resource available on site. Perrotti (2015) has put forward the concept’ urban metabolism’, emphasising the regional economic and ecological relationship between green, grey, and blue infrastructure in the urban area. Infrastructures are seen and designed as artificial ecologies and landscapes as social-ecological infrastructures providing the metabolic foundations for urban life. Williams et al. (2007) describes the landscape design as ‘facilitating a connection between the sustainable energies and the materials of the site and region to capture and store energies and materials. Namely ecological design of connections’. Thus, the spatial structure in ecological design is also enmeshed to the design and management of the energy flow. Under the green infrastructure network system, the

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network structure also presents the energy moving system through the ecological chain. Hence creating a place with biodiversity is essential for a stable system. The spatial patterns also present the connectivity for species, communities, and ecological processes. The design strategy for green infrastructure planning is to create a stable structure through designing a more comprehensive ecological network by increasing the connections between spaces. The connection places are the nodes, and the connections in between the nodes are the corridors. According to Forman and Godron’s (1986) ecology theory, the network system is the most important and common way to reflect the spatial relationship, manifested in the way of corridors and patches, with corridors connected; its distinctive feature is its edge effect. In the field of physical space planning, the network is the most concerning form, such as the common terms “ecological network”, “green network”, “green space system network,” and so on. Corridor: The concept of the corridor was first mentioned by William H. Whyte (1959) as ‘greenway’ in the book ‘Securing Open Space for Urban American’ (1959), later it has been a widely adopted ecological concept to describe the spatial structure. Later on, MacArthur and Wilson (1975), in the book “The Theory of Island Biogeography’ followed the concept of greenway, using the term ‘corridor’, and also described use the corridor to link different patches; helping to reduce the negative impact of habitat fragmentation on the survival of species. In 1997, the International Union for Conservation of Nature (IUCN) emphasises the importance of the corridor for ecological conservation and proposed the idea of using the eco-network model instead of the eco-island modelto protect biodiversity (Wood and Stahl 1997). Ecological corridors have many functions; Forman has concluded five major functions: habitat, conduit, filter, source, and sink. The corridor width is the most important factor to the organism’s movement, energy flow, and exchanges through the green corridors. The numbers, size, and shapes of the corridor create the ecological web in the system. Hence the GI planning is to create a network structure for both the ecological and sociological demand. For the GI planning, according to Zhu and Yu (2005), whose paper was based on the research over a series of existing corridor size studies concluded the appropriate values of width for biodiversity conservation: • 3 m is the minimum width for the ecological corridor, hence in the community level, and 3 m will be just enough to meet the requirement for invertebrate animals. If the width is less than 3 m, it is very difficult to reach the Biodiversity target. • Forman 1986, through the study of the different edge animals, find out 12 m is the minimum requirement for the biodiversity. The range is appropriate for protecting many edge species, but the diversity is still low, but it will provide the spaces for birds, invertebrate, fish, and small mammals. • Between 30 and 60 m, the overall biodiversity is still relatively low. Still, it nearly meets the need of protecting wildlife migration, over 30 m width, wetland living condition, will be able to meet the habits requirement for small wildlife, such as fish, birds, little mammals, and amphibians.

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• Between 60/80 and 100 m, it could satisfy the needs for the biodiversity for the animals and herbaceous plants, and they are able to protect wildlife migration and protect biodiversity. It is the minimum width for the arbour species. • Between 100 and 200 m. This is the level appropriate for biodiversity. • Greater than 600–1200 m. It creates nature landscape structures. High-level biodiversity. Since the large mammal’s migrant requires hundreds of meters or more, anything less than 600 m won’t have real interior mammals. The application of the Ecological Corridor; suggested values in different scales. Due to high networking and ecosystem functioning, rivers and floodplains in their natural state are among the most species-rich ecosystems. In recent years, sharply declining species types have a significant affect toward the water eco-system. Especially in the freshwater area, the species decreased rapidly in the last centuries caused by the land use; urbanization (Millennium Ecosystem Assessment 2005). Furthermore, the change in the river embankment structure, due to innovation of the convenient concrete, lead to the increasing in the water velocity and soil consolidation within river bodies, therefore, not only affecting the living conditions for the animals but also the high risk in flooding events. Forman suggests that the river corridor’s width should include the river embankment from an ecological perspective since it provides the space for animal habitats. The river riparian buffer zone has a significant impact on the ecological system. It can filter the water pollutants through the buffer zone structure, soil condition, topography, plants species. In the same study as mentioned, Zhu and Yu researched a series of existing papers for the river corridor width and concluded appreciate value of the width of riparian protecting river ecosystem: (1)

(2)

(3)

If the width of the riparian is 10 m, it will be able to reduce 95% of the phosphorus attached to the sediment. And the riverside plantation and wetlands can remove 100% nitrogen through soil microbial processes. If the width of riparian vegetation is greater than 30 m, it can effectively reduce the temperature, increase the supply of biological food and effectively filter pollutants. If the width of riparian vegetation is between 80 to 100 m, the element loss of sediment and soil can be well controlled.

They also suggest three key steps to find the suitable value for the riparian: (1) Understand the river corridor’s fundamental ecological processes and functions. (2) Understand the spatial structure for the river and understand the river source and outlet types. (3) Integrating the space structure of the river with the ecological process and determine the corridor width for the river. The key strategy for the green infrastructure design for the river corridor is to understand the ecological processes and using the bioengineer method to tackle animal habitat problems, water quality, and flood management problems.

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From the perspective of ecological engineering, the gravity retaining structure with voids is far better than the artificial bank structure, which is poured with reinforced concrete. In China, many governmental agencies favour the concrete structure because it has a high degree of certainty and will resolve the problem such as natural erosion process. It provides a quick remedy for the embankment problem. At the moment, the most common methods are mortar block stone embankment, concrete embankment, vertical masonry embankment with a steel pile system. However, over time, this artificial structure may cause many environmental problems. The existence of voids can make plants or plant branches grow in them. In the long run, the native biota will adapt to flood disturbances and even channel changes, increasing the probability that the embankment will have a more stable structure and provide the possibility of better animal habitats condition. The river embankment stabilisation by bioengineering could also serve as ecological steppingstones for riparian biodiversity. According to the existing research, Li and Eddleman (2002) have concluded 12 biotechnical embankment stabilisation methods through reviewing other embankment bioengineer papers. The 12 methods are live stakes; live fascines; brush layering, branch packing; vegetated geogrids; live crib wall; joint planting; brush matters; tree revetment; root wad; dormant post-plantings; coconut fiber rolls.

6.3 Strategy Three, Flood Water Management-Based Design: Sponge City Strategy Green infrastructure planning in China allows for the systematic design of comprehensive water runoff systems. In 2014, the central government put forward the Sponge City concept (issue 75); its target by 2030 is to have 80% of urban area rainwater absorbed and utilized locally. The construction methods to achieve the ‘sponge city’ will include six steps; water infiltration, stagnation, storage, purification, utilisation, and drainage. The sponge city water management strategy is essential to tackle floods and harvest rainwater and the most recognized and established strategy to construct an urban ecological area. On the community scale, green infrastructure for water management could also be separated into three categories: patches, mosaic, and linear structures. The ultimate goals are to create a web system to tackle water flooding and enhance the overall ecological system (see Table 7). Since rainstorms occur at different intensities and durations in other times and areas, sustainable planning and design should be carried out for public spaces in other areas according to other rainwater management objectives: • In areas with frequent rainstorms, the planning strategy should be to slow down rainwater accumulation and increase the water storage capacity; • In areas with occasional rainstorms, identify the lowlands and strengthen the major drainage pipelines within the lowland area. Also, improve the overall capacity for

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Table 7 Summary of structures and functions based on three types of patch, corridor, and mosaic Type

Structures

Functions

Patch

Bioretention basin, sedimentation basin, swale, small lawn, permeable pavement, roof garden, filter system (sand and gravel pavement)

It undertakes infiltration, removes contaminants, and recycles when rainfall is limited. The patch is normally attached to buildings and small-scale public spaces

Corridor Permeable pavement, Soft green corridor including shrubs, Bioretention zone (swale), retention belt, infiltration ditch, and other linear planting structures such as herbaceous plants and grasses

It undertakes infiltration, removes contaminants, utilisation, drainage for regional spaces. Corridors often appear in the community along footpaths, bike lanes or linear parks

Mosaic

Could be very large areas, which have great ability to treat rainwater, even polluted water, runoff water and provide clean water for the community

Lakes, wetlands, rain gardens, woods, forests

the rainwater storage such as increasing the number of swales, rain gardens, and change to the permeable pavement; • In an area of low rainwater, the strategy should focus on how to recycle the rainwater; hence, designing rainwater retention facilities is essential. Another problem associated with rainwater is the impact associated with the water quality; rainwater collects pollutants from land surfaces during runoff, and this polluted water eventually goes back to the aquatic system. Created by the activities and materials of various land uses in Chinese cities, waste such as rubbish in residential areas, toxic residue from factories and industry, particles emitted and shed by automobiles, etc. This results in the pollutants, such as heavy metals, petroleum hydrocarbons, excess nutrients, and pathogenic bacteria, that all contribute to the degradation of the aquatic system. Also, the inner pipes of traditional drainage systems accumulate many pollutants, washed out along with surface runoff, and discharged into urban rivers (Lou et al. 2009). Hence another important consideration for green infrastructure planning is to design facilities that remove contaminants and excess nutrients. Facilities Such as Bioretention Swale, plants, and different grades of sands will create a natural water filtration system. Constructing Bioretention bases, such as rain gardens, sunken gardens, and small linear swales, are some of the most effective ways to handle water pollution. The basic structure for the bioretention base involves water retention, plants, filtration, absorption, and isolation layouts. The plants are essential to the bioretention base since the roots of these plants remove nutrients, create suitable habitat conditions for some animals, and transpire water. In addition to the removal of nutrients, certain plants may be utilised for more comprehensive phytoremediation; an effective method of removing or degrading a broad range of pollutants across heavy metals and organic compounds typically associated with runoff pollution.

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Phytoremediation Bioremediation is the general term used for the broad use of living organisms, traditionally primarily micro-organisms, to degrade environmental contaminants (Vidali 2001). Phytoremediation uses plants to remove and/or degrade pollutants to render them harmless (Salt et al. 1998). The methods of remediation by the plants are stabilisation or degradation of pollutants in the rhizosphere (the microbial environment of the root system). It is referred to as phytostabilisation and phytostimulation, respectively. The extraction and accumulation of pollutants in the plant tissue, which may require harvesting, is called phytoextraction. The degradation of organic pollutants directly in the tissue, phytodegradation. And the process by which plants uptake certain pollutants into their tissue and then release them in a volatile state is called phytovolatilisation. These processes are not mutually exclusive and may occur simultaneously (Pilon-Smits 2005) (see Table 8). Hyperaccumulators are plants that are able to extract extraordinarily large quantities of heavy metals, in instances several orders of magnitude greater than normal plants, and survive (Salt et al. 1998). Examples of hyperaccumulators suitable for phytoremediation and in particular heavy metal extraction in Chinese sponge city schemes include Lythrum salicaria, Typha Orientalis, and Ophiopogen Japonicas (Ma et al. 2019). • The strategies implement flood management system into the community scale green infrastructure planning. • According to the function, public level open spaces could include squares, parks, streets, and the space around the building (including roof). Same as the biodiversity principle, the green infrastructure planning should try to create a comprehensive Table 8 Summary of pollution types and removal methods Pollution type

Removal method

Phosphorus

Sedimentation and adsorption, using media with high levels of calcium or magnesium. Artificial fertilizers with high phosphorous content is needed if the Phosphorus is high. Mulch and sand high in phosphorus in the filter media will cause a worse phosphorus problem

Contaminants, and other toxic organic compounds

Contaminants removing through Filtration, Chemical and Biological processes three stages Beneficial bacteria in the soil filter are responsible for the consumption of organic material and the conversion to ammonia, nitrite, and nitrate before removal as nitrogen gas

Pathogenic bacteria

Soil often dries between storms, reducing pathogenic bacteria. Since drainage through the soil media is rapid, high oxygen levels will return to the soil volume quickly. Drying is due to evaporation and transpiration

Nitrate

If the Nitrate is the main pollution source, it is needed to have additional 60 cm deep gravel layout. Since it will create an anaerobic zone, which encourages the growth of bacteria that use carbon instead of oxygen as an energy source. This process will make nitrate convert into nitrogen gas that escapes to the atmosphere

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network system to reach the goal of managing stormwater and dealing with the problem of water purification. The possible potential solutions could involve: Installation of permeable pavement system in squares, streets, parks, and other open space areas in the communities. Green roof system. Green roofs can slow down the runoff water, store rainwater, and recycle rainwater, and create habitats for wildlife such as birds, dragonflies, butterflies, bees. Integration of different formats and types of bioretention bases, such as linear swale, patch sunken park, rain garden, etc., within roads, to detain runoff, filter pollutants, and allow for groundwater infiltration. Eco-car park. The fundamental of the eco-car park is to use the permeable surface material, the structure level of the car park, such as different size stone, soil, gravel will act as filtration, absorption layout for the runoff water. Porous paving systems can accommodate average vehicular and pedestrian traffic while allowing water to percolate and recharge groundwater. Eco river embankment structure and Riparian buffer zone.

It is essential to have the water management facilities equally spread out in the space and create a comprehensive network system. Below are some of the planning strategy general considerations: • Provide capacity according to the amount of annual rainfall and 10-year, 25-year, and 50-year storm extreme flooding information and existing local underground pipe rainwater drainage facilities. • Connect to the metropolitan level wastewater or rainwater runoff system and consider the groundwater overflow scenario if there is an extreme flooding situation at the metropolitan level; make sure having channels connect to the city runoff water pipelines. • Fully understand the nature of the topology of the space and use the level difference to design the different facilities. For instance, in the lowland area, design sunken gardens with bioretention function, design green corridor with strongrooted plants in the big slope area, such as the bottom of the mountain; to help prevent erosion and contribute to the structural integrity of the land. • River edge design: Rainwater on the ground level will eventually go into the river. Hence it is important to have the water purified before. Therefore designing the river edge with a purification capacity or an additional bioretention facility in advance should be considered. • Guide the filtered runoff water into the agricultural land or other areas, potentially saving freshwater. • Try to avoid the hard surface area, if required by function, make sure there is a fair percentage of green space to catch the runoff water.

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7 Case Study: Xiangshan East Bay Industrial Zone C Planned in 2010–11 as an industrial zone with residential, commercial, and other supporting facilities, Xiangshan East Bay, Zhejiang, had previously been used primarily for salt production after reclamation from the sea by diking in the 1970s. Landscape Architects Planet Earth Ltd initiated the design work for the ‘landscape axis’ in 2012. The design strategy focused on forming ecological habitats and environmental purification systems and interweaving these with amenity and other utilitarian functions in a way that would integrate the immediate and wider landscape context (Figs. 11 and 12). By 2017 the construction of the green infrastructure landscape axis was generally complete.

7.1 Planning The planning of Xiangshan East bay as Xiangshan Industrial Zone C was prepared by the Building Planning and Design Institute of Zhejiang University of Technology and made in accordance with the People’s Republic of China Urban and Rural Planning Act of 2008.01, “Urban Residential Area Planning and Design” (2002) GB50180-93, Ningbo City Master Plan (2004–2020) and Xiangshan County Master Plan (2005– 2020). The Planning structure combined four spatial organizing concepts deployed on a grid structure that accommodated the existing major topographical features; the

Fig. 11 Xiangshan Industrial Zone C photographed 2012

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Fig. 12 Xiangshan Industrial Zone C landscape photographed 2020

surrounding mountains and water system. The four concepts were; ’core’, ’four’, ’ninth ward’ and ’biaxial’. ’Core’ referred to the service core and key waterfront. This area would be developed first, following the land infill and road construction. ’Four’ and ’nine’ referred to the division into four neighbourhood areas and nine districts. ’Biaxial’ referred to the commercial axis and the axis of the landscape. Along the landscape corridors connecting the seafront to the east and the central park and waterfront core areas to the west, commercial units are integrated (Fig. 13).

7.2 Design As previously mentioned, a defining design challenge of the multi-functional green infrastructure aiming to provide for high-intensity amenity usage and promote biodiversity; is to integrate or allow compatibility between the amenity space and ecological habitat. This was achieved in several ways. A buffer zone is created between the roads and the more open landscape on the waterside in the central landscape area. These mounded buffer zones consist of dense and diverse native woodland species matrices derived from the adjacent mountains, for the canopy layer with bark chip and planting drifts and patches beneath. Thus, the buffer areas provide resilient and biodiverse canopy layer patches that serve birds, link with the contextual landscape and the meadow layer of the landscape corridors. They provide a significant carbon sink while also serving as the people in mainly two ways. The first is to screen visually and sonically the urban development, creating a fully immersive natural environment as promoted by Olmstead and later by Kaplan and consequently many others for the psychologically restorative benefits provided. The second is to attract and encourage people to explore and utilise the space beneath

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Fig. 13 Xiangshan Industrial Zone C land usage planning

the canopy freely; free exploration of natural environments is restricted in China in particular (see Figs. 14, 15, and 16). The landscape corridors consist of six main elements: (1) River edge (2) Meadow (3) Platforms (4) Gardens (5) Buildings (6) Green margin swales and walkway. The composition literally integrates the non-accessible ecological areas, river edge, and meadow with the commercial and public spaces. The gardens shown in green are positioned between the meadow and buildings; the platforms intersect the roads,

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Fig. 14 Xiangshan Industrial Zone C landscape masterplan

green margin swales, and walkway for access to the buildings, the gardens, meadows, and in some instances, the river edge. The platforms are raised above the meadows and river edges to allow for free movement of flora and fauna, to discourage access to the ecological areas, and to provide views (see Figs. 17, 18, and 19).

7.3 River Embankment The main functions of the river bank are stabilisation, habitat creation, and water purification. Several embankment edge types are deployed to create various habitat types, purification capabilities, and water edge access. The embankments avoid hard edges allowing for more flexibility and thus resilience, throughflow of organic materials, organisms and water, and natural habitat formation. Plant regimes are

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Fig. 15 Plan for central landscape area

deployed to target the removal of specific pollutant types and support ecologies. Islands provide areas undisturbed by human activity for nesting etc. and increased areas for phytoremediation and marginal ecologies (Figs. 20 and 21).

8 Conclusions China has seen rapid development over the last 30 years; urbanisation has reached over 68% in 2021, with significant economic achievements and general social welfare

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Fig. 16 Metagraph showing planting scheme with matrix pattern and a potential circulation

improvement. This has come at a cost to the environment and city dwellers’ health. One contributing factor is the economic-oriented planning system. Having discussed different strategies for the design of GI in the public realm of Chinese cities, we find strategy starts from the identification of multiple factors through the diagnosis and treatment method. These factors include the existing problems associated with automobile-oriented city spatial planning, zoning or grid system, the control policy, which requires the development project to meet the specific criterion, a rigid system with not enough consideration of the natural form of the space. Strategies for implementing GI, defined as nature lead design solutions, are proposed to provide diversified and overlapping functional systems, including hydrology, environmental purification, ecology, amenity, transportation, and energy. They will typically consist of a leading meta-strategy, the spatial strategy, to integrate ecological and social logic into the system. Spatial strategies adopted by officials and professionals, especially in recent years, include the trending data-based strategies

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Fig. 17 Plan for landscape corridor, detailed design 1

Fig. 18 Plan for landscape corridor, detailed design 2

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Fig. 19 Cross section sketches for environmental services

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Fig. 20 The main shelf embankment type showing various planting schemes for phytoremediation

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Fig. 20 (continued)

such as GIS-based layer cake strategy, Network Analysis based strategy, Graphic theory-based strategy, morphological spatial pattern analysis-based strategy. These strategies are quite effective in regional planning, especially for the protection of the ecological security zone. However, there lacks consideration of many factors, especially human activities. It might be an excellent way to establish green infrastructure planning, but it requires a place where people meet to engage with society in general. Hence, the requirement for specific key sub-strategies is increasing biodiversity, flood water management-based design (sponge city), human-scale lead space design (i.e., increasing urban public areas and amenity), and urban food production. These strategies map to the ecosystem service categories; habitat or supporting services, regulating services, cultural services, and provisioning services. The importance of a robust and connected network of distributed green areas is repeatedly emphasised by the inclusion at the core of all of the spatial strategies. Generally, there is scope to deepen the integration of the key sub-strategies. Planting is a highly important design consideration, with multiple benefits served across the service categories.

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Fig. 21 Xiangshan Industrial Zone C landscape photographed 2020

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Fig. 21 (continued)

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Technical Integration

Smart Technologies for Urban Farming and Green Infrastructure Development: A Taxonomy Saeid Pourroostaei Ardakani, Hongcheng Xie, and Xinyang Liu

Abstract The need for urban farming and green infrastructure is quickly growing due to the increased population and rapid urbanisation during the past decades. They have the capacity to increase urban farm productivity, enhance fresh food quality, optimise farming resource conservation (i.e., soil and water) and boost the economy. Urban farming and green infrastructure applications can be enriched by advanced smart technologies such as Artificial Intelligence, Machine learning, Telecommunication, and Big data analysis. In China, cities have a great opportunity to benefit from smart technologies in farming to enhance urban sustainability, and life quality as this country rapidly moves on the edge of advanced technologies. This chapter surveys state-of-the-art smart technologies, particularly in the domain of farming and green infrastructure. It outlines the technologies’ advances, benefits, and superiorities and highlights their distinct features, potential trends, and challenges in agriculture applications. Keywords Smart techologies · Urban farming · Green infrastcurure · Technical · Productivity · Agriculture application

1 Introduction Green infrastructure (GI) is a broadly used term aiming to propose cost-effective strategic plans to interconnect natural and semi-natural areas (Zuniga-Teran et al. 2019), such as parks, gardens, woodlands, and rivers. The main aim is to deliver a wide range of ecosystem services -mainly air quality and climate mitigation. This has the capacity to propose a number of applications, including green roofs, rainwater harvesting, hedgerow, wildflower verge, and smart multifunctional farming in urban and/or rural areas (Commission 2021). GI has the potential to propose urban planning solutions and offer progressive cities benefits to manage urban resources, risks, and costs -mainly urban water cycle including storm/ground and wastewater. S. P. Ardakani (B) · H. Xie · X. Liu School of Computer Sciences, University of Nottingham Ningbo China, Ningbo 315100, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_14

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For example, this aims to design and propose promising solutions that locally collect, harvest, and store rainwater as water resources for urban gardens and parks (Denchak 2021). This results in reduced fresh-water resource consumption and the cost of urban agriculture. China has proposed a long-term plan to extend GI (Zhang et al. 2019). There is a national-level sponge city programme (SCP) in China to manage stormwater (Dai et al. 2017). This aims to address the following (Qi et al. 2020): (1) flood risk attributes; (2) site management; (3) green infrastructure; and (4) waterbased solutions. One example is the Yanweizhou Park in Jinhua City deployed to sequester stormwater during flooding periods (Kishnani 2019). By this, there is no need for building concrete floodwalls. Farming is one of the key applications of GI (Lin et al. 2017). It plays a vital role in providing fresh food sources in the world. Due to recent climate change, and increased population, farming has become an essential industry globally and took the attention of engineers, researchers, and scientists to enhance the quality of farming and improve agricultural products. According to (UN and Affairs 2021), the world population is expected to reach around ten billion people by 2050. By this, agriculture and farming need additional attention and investment to significantly enhance the food production capacity and quality with minimised (natural) resource consumption and pollution production. Smart farming takes the benefits of information and communication technologies (ICT) to manage farms, improve agricultural products and conserve the required resources -mainly human power and water. Indeed, agricultural applications utilise modern and smart techniques/technologies such as sensors, robotics, Artificial intelligence (AI), Big data, and Internet of Things (IoT) to offer benefits including (Bacco et al. 2019): (1) enhanced farming product quality, (2) reduced farming resource consumption, and (3) enhanced agriculture profitability. However, smart farming still suffers a lack of new/modern technology adaptability in traditional urban or rural agricultural fields. It needs additional cost to fit the technologies into smart farming applications. Smart technologies play a critical role in farming to develop smart and sustainable agricultural applications (Walter et al. 2017). As Fig. 1 shows, this has a great capacity to help farmers and agriculture stakeholders to manage farming resources such as land, weather, soil, and/or crops and optimise the farming jobs and productions with a minimised resource consumption—mainly time and human resources. For this, farming events are recorded via sensory devices and cameras and analysed using machine learning and artificial intelligence techniques to explore and model the current farm and predict the next conditions. For example, farming applications may take the benefits of AI-enabled drones to autonomously fly over farms (Tsouros et al. 2019), monitor the farming resources (Faryadi and Velni 2020) and/or track the objects such as farm animals (Li et al. 2020). Internet of Things (IoT) is another technology that offers farming many benefits (Navarro et al. 2020). This allows connected sensory devices that capture and report farming events for various applications such as irrigation, fertilisation, disease, and weed detection (Balasubramaniyan and Navaneethan 2021). Indeed, IoT technology has the capacity to provide an enhanced sensory data management for smart farming applications (Debauche et al. 2021)

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Fig. 1 Smart farm

and (Raja and Vyas 2019). Yet, IoT enabled smart farming can take the benefits of image processing techniques to recognise the crop/plant health/growth condition and predict the farm diseases/conditions using machine learning techniques (Bacco et al. 2018). This chapter focuses on farming applications that utilise smart technologies to enhance the intelligence and capacity of agriculture. It is organised as follows: Sect. 2 addresses Artificial Intelligence, whereas Sect. 3 and 4 discuss machine learning and mobile apps. Section 2 and 6, respectively, outline the benefits of drone and robotic applications in farming. Internet of Things (IoT), sensor, and big dataenabled farming applications are discussed in Sects. 7, 8, and 9. Section 10 describes the benefits of cloud-based and blockchain computing in agriculture. Section 11 summarises and concludes smart farming benefits, challenges, and trends.

2 Artificial Intelligence in Farming Artificial Intelligence (AI) can be utilised in a wide range of fields such as medicine, education, transamination, and agriculture. It aims to enhance the performance and capacity of applications. AI-enabled agricultural approaches can propose farmers’ best-fitted solutions to enhance the quality of farming products with minimised resource consumption (Talaviya et al. 2020). Indeed, AI aims to personalise farming jobs and agricultural algorithms to achieve optimal results and/or farming conditions. Moreover, AI-enabled techniques and tools provide intelligent solutions to manage farming resources such as soil, water, nutrition, and human resources with maximum

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accuracy and efficiency (Saiz-Rubio and Rovira-Más 2020). In addition, they result in increased quality of agriculture products with minimised cost and delay. By this, researchers, engineers, and scientists are highly interested in developing AI-based tools and techniques to offer farmers the benefits of fast, accurate, and cost-effective agricultural approaches to optimise the farming performance with minimum resource consumption -mainly water. Microsoft provides farm consulting services to farmers in India (Dharmaraj and Vijayanand 2018). This program uses Cortana Intelligence Suite to transform farming data analysis results into intelligent operations. An AI-based seeding application is designed and proposed to provide farmers with seeding dates, farming field preparation, fertilisation, and seed handling/selection. According to the results, a 30% increase is achieved for crop yields per hectare. Moreover, they designed and proposed a machine learning-enabled application programming interface (API) for pest risk prediction. Fernando et al. (2020) design and propose an intelligent robot that moves to capture and report environmental data such as temperature, humidity, and soil moisture via internet links to cloud-based servers in real-time. Moreover, it utilises image processing and machine learning techniques to monitor crop and plant growths. This results in humanpower resource conservation and enhanced farming production. Apart from AI benefits in farming applications, two key reasons describe why AI-enabled farming solutions still have difficulties to be increasingly used in farms (Eli-Chukwu 2019). The first is that farmers usually have minimum knowledge in machine AI and high-tech solutions and lack familiarity with AI products in farms. By this, they may face serious challenges setting up AI solutions for their own farming applications and taking the benefits of high-tech in farms. The second is there is a lack of AI-enabled agricultural equipment adaption in farms. AI farming products usually need training and personalisation to learn the farming application and optimise the farming results. This needs time, practice, and AI knowledge that are significantly increased in wide and dense farms.

3 Machine learning Machine learning (ML) is a branch of AI that aims to learn from data patterns to minimise human intervention in machine operation, pattern recognition, and decision making. This technique can offer farming several great benefits such as crop growth modelling, plant health motoring, and prediction (Liakos et al. 2018). Frequent and continuous data collection from large and dense farms to monitor the farm (health) condition is very difficult and needs plenty of resources and equipment. For this, machine learning techniques are used to collect partial datasets as samples and predict the farm’s health condition using ML models with no further data collection (Balducci et al. 2018). However, ML model training is still a problem in agriculture applications. Some crops/plants may be threatened by diseases once a year when they are growing or seeding. By this, building a robust and accurate ML model may need a significant

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amount of time to collect sufficient data samples (e.g., crop health conditions) and a mature training dataset. ML has the potential to offer farmers and/or agriculture stockholders financial and statistical analysis benefits -mainly price prediction and farm insurance (Yadav et al. 2020). It helps farmers collect statistical data, including price and market demand, from various online data sources during the farm lifecycle. This can be used to predict farming product prices and monitor the market. Hence, they will observe the farming products’ prices (or market demands) to minimise the price change/loss and enhance financial profits. Blue River Technology (Heraud and Redden 2021) proposes an AI-enabled agricultural machine that utilises machine learning to optimise farming production and resource consumption. By this, plants and crops are identified using computer vision techniques to receive particular treats and/or farming services. Sensors and cameras capture plants and weeds images and then analyse them to recognise their types and characteristics. They take the benefits of machine learning techniques to learn how to identify and categorise plants and crops. Yet, this agricultural machine is equipped with precision herbicide spraying to kill unwanted plants on the farms.

4 Mobile Apps Smart farming takes the benefits of AI-powered Mobile apps—mainly chatbots to monitor and optimise the farming products (Belakeri et al. 2017). Farmers and agriculture stockholders utilise communicative mobile apps to ask questions, share experiences and/or problems, and receive recommendations and solutions. For this, they communicate with AI-enabled mobile software via text and/or voice. The mobile apps may take the benefits of machine learning techniques such as Natural Language Processing (NLP) (Nadkarni et al. 2011), supervised and reinforcement learning (Zhang et al. 2020) to understand the farmers’ discussions and provide the best fitting answers. FarmBot (Plantix 2021) proposes a mobile app through which farmers could learn and understand more details in seed planting, weed recognition, plant disease detection, soil test, and watering farms. Plant diseases diagnosis (Plantix) (Farmbot 2021) proposes a mobile app to recognise plant diseases using image processing techniques. This utilises smart phone’s camera to capture pictures from crops and plants in farms and reports them to a cloud-based server for further image processing and disease recognition. The meaningful image features are extracted and utilised by machine learning models to report the best-fitted diseases and provide the farmers the most optimal treatments. The agri-e-calculator (AgiApp 2021) as a smart application helps the smart farmer to find suitable seeds and crops according to their requirements, demands, and concerns. Indeed, this mobile app provides farmers the best-fitted farming methods according to the farm condition and weather. This utilises machine learning techniques to collect data from farm stockholders and learn the farming features and

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modelling parameters. The collected farming data is processed to train a machine learning model through which the outputs of the next farming requests are predicted and optimised.

5 Unmanned Aerial Vehicle (UAV) Unmanned Aerial Vehicle (UAV) applications are rapidly growing as they are designed to be small, light, and intelligent to move throughout farms for data collection and environmental monitoring. This has been used in a wide range of applications such as agriculture monitoring, plant protection, farm surveying, and wildlife observation (Chen et al. 2016). The agricultural applications of UAVs are relatively new to utilise flying drones for the environment and green infrastructure monitoring and modelling (Lottes et al. 2017). They can be programmed to carry water and/or pesticide resources to spray while flying with minimised cost and risk (Joseph et al. 2020). UAVs have the potential to enhance farming sustainability (Tripicchio et al. 2015) and/or provide/increase communication capacities in wide farms (Nintanavongsa and Pitimon 2017). As Tronics (2021) reports, UAV spraying is five times faster than ground-moving machinery. UAV-enabled remote-sensing allows drones to take photos/videos for farm monitoring and analysis (Mukherjee et al. 2020). This technique utilises computer vision and image processing technologies to analyse taken photos for crop monitoring and/or farm surveying. As Fig. 2 depicts, UAVs record (and aggregate) the farming parameters and conditions and forward the results to the user access point for further analysis and/or decision making. For example, Aerial Tronics proposes an image processing API for UAVs to process real-time image data (Mazur 2021). This can be used in smart farms to detect mobile objects such as animals. The benefits of UAVs in farm applications are outlined below (Islam et al. 2021): (1)

(2)

(3)

(4)

Plant/crop disease detection and health monitoring: UAVs are able to scan farms, take photos and utilise image processing techniques to detect farm diseases. A zone is labelled as infected if UAVs find farm diseases. With minimised user intervention, the infected zones are allocated to drones for automatic treatment (e.g., pesticide). However, UAVs need to be allocated by high-quality sensors and cameras to detect farm diseases. Soil and field analysis and management: UAVs are useful for farm data collection (e.g., soil pH and moisture), seed planting, and harvesting. Moreover, they take high-quality images in real-time that are used for farm resource management, field surveying, and landslide modelling. Planting: UAVs are used to support seed planting as they shoot seeds into the field. They are also able to include nutrients in the shootings to provide required items for crop growing. Crop identification: UAVs are able to provide high-quality images to recognise and classify the growing crops on a farm.

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Fig. 2 UAV remote-sensing in farms

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UAV-enabled agriculture has increasingly become popular due to agricultural modernisation. This technique stems from the fact that AI is rapidly growing. This pushes the technology of agricultural UAVs to take the benefits of AI and move toward the direction of intelligence, systematisation, and precision (Theile et al. 2020. According to (Unal 2020), deep learning technique can be used in UAV-enabled farming to enhance farming automaticity and optimise the quality of agricultural activities such as resource management. However, farm UAVs still suffer obstacle collision and lack of communication capacity. To resolve this, UAV technology companies adopt ultrasonic and infrared sensors for obstacle perception (Maddikunta et al. 2021). For example, MG-1S Advanced, developed by DJI, is equipped with three directional radars and one OA (obstacle avoidance) radar for obstacle perception (Dji 2021). Yet, digital beamforming technology is used in communication to realise 3D point-cloud imaging, which further improves the recognition ability of complex agricultural terrain (Wang et al. 2019).

6 Robotics Agriculture takes the benefits of hardware solutions-mainly robots to manage farming resources and autonomously perform farm jobs. This would result in resource conservation -mainly labourers, money and energy, reduced production cost, and enhanced production quality. As Fig. 3 shows, robots take the benefits of ML techniques to monitor farm conditions and perform autonomous farming jobs.

Fig. 3 ML enabled robots (e.g., farming actors)

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An intelligent robot application is proposed to harvest strawberry farms in complex and unstructured environments (Xiong et al. 2020a). This robot moves throughout the farm to find and cut strawberry fruits. It utilises machine visionenabled deep learning techniques to recognise fruits on the farm. Yet, the robot utilises probabilistic location technology and topology to move across harsh lands, whereas 3D mobile visibility enabled search algorithm to find the best paths for picking the fruits throughout the farm. This addresses a more qualified strawberry picking at a certain time using the robots. Yet, Harvest CROO Robotics (Robotics 2021) is an industrial project to design robotic equipment for strawberry picking.

7 Internet of Things (IoT) in Farming The Internet of Things (IoT) is a new technology that connects digital devices through internet links to provide interpretability and communication. This technology has a high impact on agriculture and farming performance as it provides communication links for data sharing (Boursianis et al. 2020). Indeed, IoT technology forwards huge volumes of structured or unstructured data samples between data collector/logger devices (e.g., sensors) and users. By this, farming datasets such as water, power, soil, pest infestation, and rainfall are collected using static (e.g., proximity sensing such as ground soil pH sensor) and/or mobile sensors (e.g., remote sensing such as UAV cameras). They reported data processing units via internet ties for further data analysis and/or decision-making (Madushanki et al. 2019). Yet, the recordings are used to form a historical dataset for each farming factor which is used by machine learning algorithms to recognise agriculture production and/or resource consumption patterns. Cognitive IoT techniques provide a deeper insight into data analysis as they are able to forward data samples according to their characteristics (e.g., freshness), meaningfulness, and/or application/user requirements (Navarro et al. 2020). Tan et al. (2020) proposes an IoT platform that automates the urban farming process by embodiment IoT, big data, and cloud computing. The IoT platform is designed so that users, especially farmers, can monitor the growing environment, and the nutrient can be adjusted automatically without human intervention. The platform utilises pH, total dissolved solids (TDS), oxidation–reduction potential (ORP), and temperature data to regulate the optimum concentration of the nutrient solutions. The growth rate of the plant is continuously monitored using a camera. Commons is a hydroponic management and monitoring system for an IoT-based farm using web technology (Crisnapati et al. 2017). The significant decrease in agricultural land and the rapid development of hydroponic system technology such as the Nutrient Film Technique (NFT) address a serious farming challenge. To deal with this, a hydroponic farm management system should be designed that has the capacity to monitor water temperature, water level, densities of nutrient solution, and the acidity (pH) of a nutrient solution. It aims to collect data through several (internet) contented sensors and report the results online in real-time. It also allows farmers to monitor farm conditions remotely and perform farming jobs.

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In the study by Podder et al. (2021a), an IoT-based Smart AgroTech system is proposed in the context of urban farming that considers humidity, temperature, and soil moisture. The proposed system decides irrigation action should begin or stop depending on the farming land condition and provides the monitoring facility and remote control to the farm owner. In this context, farm management and appropriate monitoring of farm parameters are indispensable for productive farming in smart cities or rural areas. Zamora-Izquierdo et al. (2019) propose an IoT-enabled edge computing platform for smart farming. This mainly focuses on precision agriculture, covering precision agriculture management in semi-arid conditions by using IoT technologies. The SmartArgoTech system is an IoT-based urban agriculture management system that monitors essential agricultural parameters such as temperature and soil moisture (Podder et al. 2021b). This approach decides whether to start or stop irrigation based on the condition of the cultivated land. In addition, the system is equipped with monitoring facilities and remote control to provide farmers with a more efficient management method. It uses DHT11 temperature and humidity sensors and soil moisture sensors to collect relevant environmental data and processes the data through a microcontroller and network interface.

8 Sensors Sensory devices (and/or sensor networks) have the capacity to collect and report environmental data -mainly agricultural for further processing and decision making (Kadam et al. 2018). As Fig. 4 shows, they measure/capture the surrounding events and transmit the recordings via data transmission infrastructures (e.g., Bluetooth, Zigbee, and Internet) to the user’s access point. For example, an IoT-enabled sensor network is set up in a farm to capture ambient and/or farming data such as farming resource condition, soil moisture/PH, crop growth, and seed setting and report the results through internet links. In addition, remote sensing techniques can be used to collect farming data. They may utilise hyper-spectral imaging and/or 3D laser scanning to remotely capture farming data. This allows to monitor crop growth during a particular period such as a season and report the results in detail for further processing and decision making. Triantafyllou et al. (2019a) propose an agricultural monitoring system consisting of (1) a sensory system to capture and report farming data and (2) a data processing and analysis framework to analyse sensory recordings. The former allows ground and/or UAV sensory devices to collect the environmental events such as seed/crop conditions. Yet, this transmits sensory recordings from the sensory devices to the data analysis framework (e.g., Mahout Apache 2021) using wireless ties -mainly the Internet. Malthouse takes the benefits of sensory technology in farming (Dolci 2017). This technology aims to increase alcohol content during the brewing process by converting grains into protein. For this, a number of environmental variables have

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Fig. 4 Sensor technology for smart farms

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to be taken into account. For example, soil pH, carbon dioxide, temperature, and humidity are the keys to the indicators of metabolic reaction, germination progress, and environment, respectively. They are monitored by sensory devices installed in the factory to enhance converting starch and protein converted during the whole brewing process and achieve better results (alcohol content). Yet, this system utilises machine learning methods such as Bayesian network analysis and multivariate analysis to study the correlations between the input variables (sensory data such as soil pH) and the targets (e.g., starch and protein production). According to the results, this system could significantly increase the consequence for a 150-year-old malt company. Triantafyllou et al. (2019b) propose a sensory system architecture that collects and reports farming data to provide real-time crop monitoring and optimisation. However, there are still several challenging issues -mainly sensor network restrictions (e.g., power and communication) and sensory data accuracy and reliability that have to be taken into account (Kim et al. 2019).

9 Big Data Big data and data-intensive techniques have the capacity to offer smart farming and agriculture a number of benefits such as crop growth and lifecycle (Kamilaris et al. 2017). This technical approach gives farmers and agriculture stakeholders the ability of data pre-processing, analysis, and manipulation to explore data patterns and correlation among various farming datasets such as weather condition, soil quality/pH/moisture, seed/crop growth, plant diseases, and market trends. Hence, they will be able to make the best-fitted decisions in real-time during the whole farming procedure from seeding to the farm product market. However, due to the required information technology skills, big data applications are not widely used for farming and agricultural applications (Klauser 2018). Machine learning-enabled smart farming applications can take the benefits of big data techniques to train the machine learning model with increased accuracy and received optimised results (Wolfert et al. 2017). Machine learning models are trained by big datasets that increase their accuracy to enhance the farming operation results. They also predict the whole food supply chain, mainly farming jobs such as resource consumption (e.g., water and soil), crop growth, and market trends in the future (Islam Sarker et al. 2020) focuses on utilising big data technology in smart farms to analyse farm datasets and make optimal decisions to manage farming resources minimised delay. According to the results, the decision’s accuracy and quality highly depend on the data availability and amount of data samples. Bendre et al. (2015) utilise big data techniques to collect and analyse environmental data aiming to forecast weather to enhance the farming results. For this, a big data approach is designed and proposed according to distributed and parallel data processing models to collect and analyse data samples in wide and large farms. Big data applications benefit from remote-sensing techniques to collect high-resolution data samples (Huang et al. 2018). Remote-sensing enabled smart farming applications utilises satellites, drones

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and/or ground sensory devices to capture farming data samples. They usually aggregate real-time data samples and forwards the results through wireless internet links, e.g., 5G, to centralised data processing machines for fuhrer processing, e.g., feature extraction and machine learning model training.

10 Cloud Computing and BlockChain For example, Waqar Malik et al. (2020) focuse on cloud-based (fog) data computing that provides farmers a distributed farming simulation on the cloud. The Cloud computing paradigm provides smart farming applications data sharing and distributed/parallel data processing benefits. This technical approach aims to connect digital devices such as UAVs, sensors, and farming machines through internet ties (e.g., 5G) to enhance communication and computation capacities. This allows them to share their data and experiences via the cloud-based simulation beyond their physical locations. Prospera (2021) proposes a cloud-based data processing platform through which data samples such as soil/water recordings are pre-processed and aggregated. Indeed, Prospera interconnects many IoT-enabled sensory devices and equipment via internet links to receive, share, and analyse farming data. Yet, it takes the benefits of machine learning techniques for feature extraction, decision making, correlation modelling and/or farming job optimisation. Blockchain technology offers the agriculture industry many benefits, especially farming resource and/or food supply chain monitoring (Xiong et al. 2020b). This technology provides a secure and traceable data processing platform that allows connected devices such as sensors and data loggers to securely share/process farming/ambient data to monitor farming resources in wide and large farms (van Hilten et al. 2020). According to (Lin et al. 2018), blockchain technology has the capacity to trace and monitor the quality of agri-foods and enhance the consumers’ satisfaction. Indeed, Blockchain can collect and process the sensory recordings from cloud-based (or IoT) sensor networks to monitor agricultural products from farm to fork. However, Blockchain and cloud-based computing still suffer high development costs to set up the data processing platform on the cloud.

11 Conclusions Smart farming plays a vital role in GI development and urban planning. This can take the benefits of smart technologies such as IoT, ML, and Big data to propose several applications such as green roofs and farm parks in urban areas. It results in agriculture resource conservation (e.g., water and soil), reduced natural/environmental risks/disasters (e.g., storm-water), increased suitability, and enhanced quality of farming products. Indeed, smart farming has the potential to manage agricultural

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resources (e.g., land, weather, soil, and/or crops) and/or automate/optimise farming jobs with a reduced cost and delay. Technology-enabled agriculture is a key in urban modernisation. Thanks to the development of AI technology and hardware breakthroughs in developed countries— mainly China—this forwards smart farming toward sustainable and modernised urbanism. Indeed, this significant shift from traditional farming to smart, modern, and precise farming offers agriculture stakeholders and other citizens many benefits, including resource conservation, food quality, and healthcare. Smart technologies are the key to re-shaping the farming and agriculture industry by proposing a great number of new hardware and/or software equipment/techniques dedicated to farming purposes. They allow farmers and agriculture stakeholders to produce agri-foods with minimised risk, resource consumption, delay, and cost. However, smart farming still needs to deal with the difficulties of technology adaptability, especially in traditional farms. This needs to pay additional costs to adopt new technologies into old-fashioned and/or conventional farms with limited technology infrastructure such as internet coverage. Table 1 summarises the key techniques and technologies which are used in smart farming. This outlines their characteristics by highlighting their key benefits and challenges. As Table 1 summarises, smart technologies can offer farmers and agriculture stakeholders a number of benefits -mainly automated and optimised farming jobs, the Table 1 Smart farming technologies: summarisation Technology

Key benefits

Key challenges

AI

Automated/optimised farming jobs

- Development/utilisation cost - Needs user training

ML

Automated/optimised farming jobs

- Design/development cost - Needs user/developer training

Mobile app

Accessible and on-demand farming jobs

- Development cost - Usually low flexibility

UAV

Automated remote-sensing

- Data collection risk/cost - Cptimisation for limited resources

Robotics

Automated farming jobs

- Development/utilisation cost - Needs user/developer training

IoT

Connected farming devices

Infrastructure availability/accessibility

Sensors

Remote/connected data collection

Development/utilisation cost

Big data

Large-scale data processing/analysis

Needs user/developer training

Cloud and Blockchain

Accessible/traceable data processing/sharing

Development cost

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ability to manage large-scale/real-time and variant farming data, data and processing accessibility, and remote data collection. However, the most highlighted challenge for smart technology utilisation is the development and training cost. This means farmers and agriculture stockholders should pay additional costs to set up, utilise, and maintain technology-enabled applications. Yet, smart farming applications suffer a lack of flexibility as they are designed for particular farming jobs. Farmers and agriculture stockholders usually have difficulties working with technologies and/or develop them according to new requirements. For this, they may need short, medium and/or even long-term training to understand smart technology and learn how to develop new applications. This takes time and increases the cost of smart farming utilisation.

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Integrated Decision Support System for Sponge City Management: A Case Study of the National Demonstration Area of Guangming District, Shenzhen Yan Wei, Jiping Jiang, Jingxian Lai, and Yunlei Men

Abstract China is currently entering a post-sponge-city era. Determining how to effectively present and manage the construction and operation of green infrastructures is one of the critical issues arising. Decision support systems (DSSs), which combine advanced information technologies such as the Internet of Things (GIS) with environmental models, provide intelligent solutions for integrated management. This chapter presents a state-of-the-art DSS platform of Guangming District, Shenzhen, one of the best national sponge city demonstration regions. In this platform, seven subsystems are integrated according to the requirements of stakeholders, including the big data centre, data mining and comprehensive simulation systems, a 3D sponge city display system, a project lifecycle management system, a performance appraisal system, a monitoring system of black and odorous water, and a flood control and drainage management system. The focus of this chapter is the system architecture, monitoring campaign, data processing, model intergradation, and workflows of supervision. The system has been online for one year. The advantages and drawbacks of the DSS are also summarised herein, and the future trends of integrated management in the postsponge-city era are discussed. This chapter can provide a good engineering reference for smart sponge city management in other cities. Keywords Decision support system · Sponge city · LID modelling · Guangming district

Y. Wei · J. Lai Shenzhen Howay Technology Co., Ltd., Shenzhen 518000, China J. Jiang (B) Shenzhen Municipal Engineering Lab of Environmental IoT Technologies, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China e-mail: [email protected] Y. Men Shenzhen Zhishu Enviornmental Science and Technology Co., Ltd., Shenzhen 518000, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_15

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1 Introduction In recent years, to improve the quality of the urban ecological environment and improve the safety, sustainability, flood control, and drought resistance of urban water bodies, many rainwater management concepts have emerged, such as the best management practices (BMPs) proposed by the United States in 1972, low impact development (LID) proposed in 1990 (Ahiablame et al. 2012), blue-green infrastructure (BGI) proposed in 2017 (Liao et al. 2017), the Sustainable Urban Drainage System (SUDS) proposed in the United Kingdom (Joshi et al. 2021) and the active beautiful clean (ABC) water plan of Singapore (Liao 2019). China started to run its first batch of sponge city demonstration pilot projects in 2015, and these projects made great achievements in the effective management of drought and flood disasters, the mitigation of the urban heat island effect and the rain island effect, and restoration governance (Sapkota et al. 2018). Many stormwater management platforms have been developed around the world, such as MS4web (Chiang 2014), CULTEC (Nguyen et al. 2019), Mapistry (Mapistry 2021), and the STORMTANK System (Brentwood 2021) in America; the European SDS GEOlight and SW2; Asia’s “Haveli system” (Sahu et al. 2015), the ACO StormBrixx (Zhai et al. 2021), and GPDC (Shishegar et al. 2021). However, there are few reports on comprehensive management and control platforms of sponge cities that integrate data collection, model coupling, and management platforms. After the construction of sponge cities, determining how to carry out effective management is an urgent problem that must be solved. Although the first batch of sponge city construction pilot projects achieved good improvements, some problems still challenge their performance. First, there is a gap between the construction and management of sponge cities. Some pilot cities only focus on engineering construction but ignore operation and management after construction. Many sponge city demonstration areas, including those in China, lack comprehensive management platforms. Second, integrating data collection, model, and management services to serve the operation and maintenance of sponge cities is still exceptionally complex. Effective management and control mechanisms can ensure that sponge facilities give full play to their engineering benefits. Therefore, determining how to effectively ensure that a sponge city achieves its expected benefits is a problem faced by scientists globally. In this study, the Shenzhen sponge city demonstration area is taken as the study area. With the support of national sponge city construction funds and local government funds, management platform development and operation are carried out. Our team developed a sponge city intelligent management and control platform by combining advanced information technologies, such as the Internet of Things, geographic information systems, hydrological and hydrodynamic simulations, optimisation algorithms, and environmental models. In doing we, the work provides decision-making support for real-time rainwater management in Guangming District of Shenzhen city. The system has seven functions: black and odorous water monitoring, sponge city life cycle monitoring, performance evaluations, and so on. The

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construction scheme and technical system of the platform are introduced in the following section. This system provides a reference for the construction of related platforms. The system architecture, data collection, model intergradation, and workflows of supervision are the focus of this chapter. The advantages and drawbacks of the DSS are also summarised. The future trends of integrated management in the post-sponge-city era are discussed. This chapter can provide a good engineering reference for smart sponge city management in other cities.

2 Study Area and System Architecture 2.1 Fenghuangcheng Sponge City Demonstration Zone Shenzhen’s 2018 GDP ranked third in China (Wang et al. 2021), and Shenzhen is the core city of the Guangdong-Hong Kong-Macao Greater Bay Area in China. More than 20% of Shenzhen’s urban area met the requirements of sponge city construction in 2020. Shenzhen, taking Fenghuangcheng (meaning phoenix city in Chinese), Guangming District as the sponge city pilot area, was approved as the second batch of national sponge city construction pilots in April 2016. The project passed the acceptance of the Ministry of Housing and Urban–rural Development (MoHURD) of the People’s Republic of China (PRC) in August 2020 with excellent results, becoming an outstanding example of sponge construction and management in China. Guangming District, located in northern Shenzhen, Guangdong Province, has a subtropical climate with an average temperature of 23°C. The green coverage rate of the whole area is high, and 53.6% of the land is designed as ecological protection areas. Guangming District is a national low-impact development demonstration zone and a green building demonstration zone. As the core area for the future development of Guangming District, Fenghuangcheng city, where the administrative center, cultural center, and commercial center of the new district are located, has carried out green building and low-impact development practices and completed more than 100 construction projects. Regional construction projects covered urban water systems, water supply, and drainage systems, reclaimed water systems, drainage and waterlogging prevention systems, garden and green spaces, municipal roads, green building communities, and old city reconstructions to the requirements of sponge cities. The current land use of Fenghuangcheng city is mainly based on industrial function and will be transformed into a comprehensive functional area integrating industries, residences, commercial offices, and public services in the future. The southeast side of Fenghuangcheng city is surrounded by Liangming Forest Park and Guanlan Forest Park. The west side is the Maozhou River, its tributaries, the Dongkeng watercourse, and Ejingshui River, run through Fenghuangcheng city from west to east. The “Guidance Plan of Fenghuangcheng City Development” proposed the sponge city concept as the development framework, connecting mountains, water,

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Fig. 1 Map of monitoring stations

countrysides, and other natural-ecological elements, constructing the “Green Ring Park project” in Fenghuangcheng city and creating an important sponge city carrier. The development of the sponge city smart management system (SCSMDSS) of Guangming District is required by the national sponge city demonstration projection (Fig. 1).

2.2 System Architecture The structure of the SCSM-DSS of Guangming District is shown in Fig. 2. The Guangming District sponge city intelligent management and control platform is divided into five layers: the physical support layer, basic support layer, data support layer, application layer, and an interaction layer. At the same time, the security system and standard and regulation system run through all platform construction

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Sponge City Smart Management DSS (5-layer-2-wing) Interac on Layer

PC Terminal

Large Screen

Others

J2EE Environment + Middleware

Data Layer

Data Acquisi on Interface

Data Service Interface

Big Data Center

Intermediate Library

Fundament al Support Layer

Physical Environment

Host Storage

Network Communica ons

STANDARDS & REGULATORY SYSTEM

Data Cleaning

Mobile Applica ons

3D Display

Black & odorous Water Supervision

Applica on Support Layer

Geographic Informa on

Flood Control & Drainage

Assessment & Evalua on

Project Management

Data Mining

Data Center

Applica on Layer

SECURITY SYSTEM

Model Cloud

Mobile Terminal

Monitoring& Control

Fig. 2 Structure of the platform (SCSM-DSS)

levels to ensure the overall security, standardisation, and normalisation of the platform. Among them, the basic support layer provides a basic support environment for platform operation, including the physical environment, host and storage, monitoring, network communication, etc. The data layer, namely, the big data center (BDC), is used to collect and store various platform data and provide data services for the application systems of the platform. The BDC includes eight databases: the metadatabase, basic geospatial database, high-level model database, three-dimensional model database, infrastructure database, business database, monitoring database, and user permission database. The application support layer is the basic service and platform supporting application operations, such as the model cloud platform,

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geographic information platform, and data cleaning service. The application layer is the core and soul of the platform and provides comprehensive information and intelligent support for sponge city construction assessments, project management, 3D displays, daily operations, flood control and drainage systems, black and odorous water supervision, and other businesses. The interaction layer enables platform users to interact with the application system through terminal devices such as computers and mobile phones to obtain all kinds of desired information. The security system is based on the relevant requirements of the security domain division to provide security for platform communication, networks, and applications.

2.3 Functionality of the Decision Support System According to its functional organisation, the platform is divided into three supporting systems (the BDC, data mining and modelling system, and sponge city 3D display system) and four application system platforms: the project life cycle management system, assessment system, black and odorous water monitoring system, and flood control and drainage management system. The BDC is the core part of the system. It is used to maintain all kinds of online and manual monitoring data, monitoring equipment, business data, spatial data, etc., and provide a data service center for other applications. As the key technical support systems of the platform, data mining and model systems can provide various model operations for the platform and support intelligent business functions, such as platform simulations and predictions based on the monitoring data and other basic data obtained by the platform. The sponge city 3D display system uses 3D data of some regions of the sponge pilot area obtained by airplane for artificial modelling to show the public the operation of typical sponge city projects and the structure and working principle of sponge facilities. The life cycle management system of the sponge project manages the whole life cycle of the sponge city construction project, from the project approval and design to the construction, management acceptance, and maintenance of the project, to comprehensively supervise the construction progress, completion effect, and operation of each sponge project. The sponge city assessment system is based on the state and Shenzhen sponge city construction; this system decomposes the assessment indicators and evaluates the construction effect of sponge city pilots through data monitoring and model operation. The supervision of black and odorous water bodies is the specific application concern of sponge city construction. Through the real-time monitoring of river water quality in the pilot area, dynamic changes in water quality can be perceived in real-time. Through real-time monitoring of the construction of black and odorous water body treatment projects, the influence of these treatment projects on water quality and the effect of the treatment of black and odorous water can be understood, providing a reference for the adjustment and decision-making of treatment projects. The flood control and waterlogging management system can predict the safety of floods and waterlogging by analysing monitored river water level and waterlogging

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data with the help of an integrated flood and waterlogging model to provide an auxiliary basis for flood control and waterlogging decision-making. In other words, the project life cycle management system, sponge city 3D display system, assessment system, and BDC incorporate data management and data display as the main methods to realise the function of the project. The monitoring system of black and odorous water bodies and the management system of flood control and drainage are mainly realised by data analysis and decision support.

3 Monitoring and Data Processing Sponge city construction is a comprehensive and systematic engineering process involving municipalities, water conservancy, environmental protection, construction, land, and other industries. Therefore, sponge city construction covers a large amount of data, including (1) basic data such as vegetation, road, water system, and residential area data, (2) data on sponge facilities such as rainwater and sewage pipe networks and low-impact development facilities, (3) data on the spatial location and information of construction projects, and (4) dynamic monitoring data such as hydrological monitoring, meteorological monitoring, river water quality monitoring and video monitoring. These data are used to build a system with unified, standardised, spatially integrated, and business-integrated data service capabilities that the BDC manages (see Sect. 2.2) (Ju et al. 2018). First, when all kinds of data collected by the data acquisition layer (mainly including all kinds of sensor devices) are imported into the BDC, they are stored in the Hadoop Distributed File System to ensure the security and reliability of the data (Guan et al. 2019; Zhu et al. 2020). Then, the stream data processing engine focuses on the rapid processing of the stream data and feeds back the processed results to the relevant business platform for further processing. Finally, the real-time data, such as rainfall, water quality, and flow rate data, are processed by the real-time data processing engine, and the processed data are transmitted to the back-end data mining platform.

3.1 Monitoring Programmers By monitoring the whole natural background (Herms et al. 2021; Pitzschke 2021; Rahman et al. 2021), source emission reduction (Yang et al. 2020), process control (Bequette 2003), and systematic water pollution treatment (Keating et al. 2014) processes, Fenghuangcheng city can realise the full-coverage monitoring of typical facilities, typical plots, drainage areas and catchments in the region.

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Monitoring network layout of natural background

The natural background values include information on rainfall, the infiltration capacity of the soil, and underlying surfaces. Rainfall data are fundamental for regional net flow analyses in sponge city monitoring practices. Combined with the distribution of existing meteorological stations and installation conditions in the demonstration area, the layout of rainfall monitoring stations is designed according to the “local professional specification of precipitation observation”. The infiltration capacity of the soil in the demonstration area was detected, and the infiltration capacities of the sponge facilities were monitored. On the basis of understanding the natural infiltration capacity of the background soil in the region, the amount of rainwater infiltration into the underlying surface after the construction of the sponge city can be compared to judge the reduction in rainwater runoff in the region and achieve monitoring. The purpose of underlying surface monitoring is to evaluate the hydrological and water quality of the underlying surface during sponge construction and accumulate basic data for the construction, performance evaluation, and smart platform construction of sponge cities. The monitoring contents of the underlying surface include six categories and 11 monitoring objects in bare lands, grasslands, roads, pavement, squares, and flat roofs. The non-point source pollutant characteristics of roads and pavement are affected by the pollution emissions of the local area. Therefore, we selected monitoring objects to represent the major land-use types (residential, public and industrial areas) in the demonstration area. (2)

Monitoring network layout for source emission reduction

The monitoring of source emission reductions mainly includes the monitoring of typical facilities and typical plots. By analysing monitoring data, we can evaluate the water quantity, water quality process, and operation effect of runoff from typical sponge facilities and typical plots and determine the amount of rainwater runoff controlled, the reduction rates of ammonia nitrogen and other main pollutants, and the relationships among these processes. (3)

Monitoring network layout for process control

Process control monitoring includes the monitoring of the rain water pipe network in the drainage area, key nodes of the rain water pipe network, sewage main pipe, sewage interceptor, reclaimed water, waterlogging locations, and drainage outlets. First, by monitoring the variations in surface runoff under different rainfall conditions and analysing the variation law of the peak runoff, we can grasp the variation process of the water level and the flow of drainage pipelines corresponding to rainfall events of different frequencies. Second, by dynamically monitoring the drainage characteristics of each drainage pipe network in the demonstration area and analysing the contribution rate of runoff pollution to water environment pollution, we can determine the relationship between the controlled amount of rainwater runoff and the controlled amounts of ammonia nitrogen and other major pollutants, as well as the rainwater runoff process and sewage drainage characteristics. Finally, we

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can (1) provide services such as performance evaluations, daily operation risk identifications, and combined sewage overflow diagnoses for the operation of drainage systems, (2) provide basic data for model evaluations and parameter calibrations, and (3) provide monitoring evidence for separate rainwater and sewage reconstructions, runoff pollution control, and the effects of black and odorous water treatment. (4)

Monitoring network layout of systematic water pollution treatment and control

Herein, we mainly aimed to monitor the water quality, water quantities, and water levels of the Dongkengshui River and Ejingshui River. By monitoring these river water systems, we can (1) grasp the variabilities in the river water levels and flows corresponding to rainfall events with different frequencies, (2) understand the quantitative relationship between runoff pollution and river water quality, and (3) evaluate the improvement effect of water quality before and after river regulation. The treatment effect of black and odorous water can be evaluated by comparing the water quality changes of tributaries and main streams before and after black, and odorous water is treated (Figs. 3, 4, 5, 6, 7).

Fig. 3 Technique route of the monitoring campaign

External System Data

User Data

Flow Data

Internal Operation Data

Energy consumption Data

Engineering Data

Level Data

Water Quality Data

Data Type

Data Sources

Fig. 4 Data collection system

Monitoring Objects

Specific time combined with rainfall distribution

Monthly / Quarterly

Hourly

Minute level

Data Frequency

Patching Data

Original Record Data

Data Processing

Management Data, Facility Design Parameters)

Fill on the Data (Project

Manual Sampling Monitoring Data

Monitoring Data, Regularly Updated Data)

Real-Time Data (Online

Presentation Style

Environmental Warning

Equipment Warning

Data Early Warning

Data Application

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Fig. 5 Map of the monitoring sites

3.2 Data Pre-processing Sponge city monitoring data, which comprise diverse types, large volumes, and strong interference, require efficient and scientific-technical support for data pre-processing. Data pre-processing is an important tool used to obtain reliable monitoring data and ultimately serves simulation and evaluation decision-making purposes, including data exploration, data cleaning, data patching, and data screening. Data exploration represents preliminary exploration within a large amount of data. First, a histogram and scatter plot were used to obtain the outline of the data. Second, the distribution of the data magnitude, the extremum, and the range of data were obtained through observations of the histogram. The outliers were calibrated to begin the data cleaning process after the aggregation and dispersion of the data were obtained. Relevant data exploration rules, equipment technical parameters (measurement range), and site environment monitoring were used to set data-cleaning rules, including range cleaning, logical relationship cleaning, and statistical method cleaning (Calabrese 2019). The original data were saved in the original database, while the cleaned and repaired data were saved in the application database. As shown in Fig. 8, before cleaning (left), if a large number of outliers existed in the data and these outliers did not conform to the monitoring environment (in the red box), they were judged as abnormal; after cleaning (right), the data availability was greatly improved. Data patching repairs the missing individual values in continuously monitored online data that occur due to external interference. The patching method is selected from the interpolation method, fitting method, and hydraulic formula calculation

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Fig. 6 Photo of monitoring devices and sampling work

interpolation according to the data type, while data screening selects suitable monitored data for the model calibration and validation through a platform data screening function. Data screening was mainly conducted with the flow data, while the catchment area and rainfall were counted at each monitoring point, and the runoff coefficient was calculated. The data were selected according to the reasonable range of runoff coefficients. The reasonable range of runoff coefficients refers to the runoff coefficient table in the technical guide for sponge city construction. In practice, the catchment area corresponding to a monitoring point often covers a variety of underlying surfaces, so the reasonable range should be expanded to retain as much effective data as possible; this reasonable range of runoff coefficients should be set as 0.08– 0.95. Table 1 shows the rainfall data of outlet #3–1 on May 26, 2019. The rainfall is 22.8 mm, the total amount of monitored drainage is 2249.59 m3 , and the corresponding catchment area of outlet #3– 1 is 87260 m2 . After calculation, the rainfall runoff coefficient of this field is 1.13, which is beyond the range of reasonable values and is regarded as an invalid datapoint.

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Fig. 7 Web-based GUI for real-time data visualisation (the upper panel shows the locations of devices, and the lower panel shows the historical flows monitoring)

3.3 Details of Data Cleaning (1)

Range cleaning.

Rule 1: Clean the measuring range data of the instruments and equipment. Rule 2: Set the cleaning range for the environmental parameters measured on site. If the height of the weir is 0.5 m, the measured water level is less than 0.6 m (see Table 2).

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Fig. 8 Data before cleaning (top) and after cleaning (bottom)

Table 1 Data filter table Outlet ID

Date

Catchment area (m3 )

#2–2

2018.8.4

97,310

6.4

33

0.34

Effective

#3–1

2019.5.26

87,260

22.8

2250

1.13

Invalid

(2)

Rainfall (mm)

Discharge flow (m3 )

Runoff coefficient

Remarks

Cleaning based on logical relationship.

Logical data cleaning judges the rationality of data according to the logical relationship of monitoring parameters and then cleans data according to the judgement results (Prokoshyna et al. 2015). For example, on dry days, the water level and flow

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Table 2 Screening rules of monitoring equipment and parameter ranges ID

Measuring equipment

Measurement parameter

Range

Processing rules

1

Rain gauge

Rainfall per minute (r)

0–15mm

If r < 0 mm, adjust to 0 mm; identification; If r > 15 mm, the interpolation method is used to obtain and mark the number. If r > 15, a data anomaly warning is issued

2

Doppler flowmeter

Water level (h)

0–5m

If h < 0 m, adjusted to 0 M; identification; If h > 5 m, use the interpolation method and mark. If h > 5, send out an abnormal data warning

Instantaneous flow (f)

>0 m3 /h

If f < 0 m, set as 0 m and mark

Water level

0–0.5 m

If h < 0 m, adjust to 0 M; identification; If h > 0.5 m, it is identified by the interpolation method. If h > 0.5, send out a data anomaly warning

3 4

Open-channel Flowmeter

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Suspended solids (SS) SS online monitor

0–4000 mg/L

If SS < 0 m, it is adjusted to 0M; If SS > 4000, an abnormal data warning is issued

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Water quality online monitoring station

Each parameter < 0 is adjusted to 0M; identification; Each parameter > the limit value is identified by interpolation method. If it is still > the limit value, a data anomaly warning is issued

Temperature

0–50 °C

PH

1–12 pH

8

Dissolved oxygen

0–20mg/L

9

Conductivity

0–20,000 uS/cm

10

Turbidity

0–4000 NTU

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Ammonia nitrogen

0–100

12

COD

0–100mg/L

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Total phosphorus

0–10mg/L

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Total nitrogen

0–25mg/L

15

ORP

−2000–2000 mv

7

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data of the waterlogging location and facility location are 0; on dry days, the water level and discharge data of the overflow well are 0; corresponding to SS = 0 and ammonia nitrogen < total nitrogen, when the water level measured by the flowmeter is 0, the flow rate is 0. As shown in Fig. 9a, the runoff is inconsistent with the rainfall, the peak shifting time is more than 60min, and the data validity is low. In Fig. 9b, the peak shifting time is 3min, and the correlation coefficient between the runoff and precipitation is high; hence, the data validity is high. (3)

Cleaning based on statistics.

The statistical methods include the correlation coefficient method (J and S 2018) and Pauta criterion (Li et al. 2016). With the help of the linkage analysis of a large number of flow and rainfall data, it can be clearly found that the variation trends of instantaneous flow and rainfall data at each monitoring point have the same peak staggering law; this result is also in line with the actual process in which the timing

Fig. 9 Examples of data cleaning. Subplots (a) and (b) denote data cleaning by logical relationships; (d) shows the fixing process for missing data; (e) denotes data cleaning by statistics; and (f) denotes the rainfall and run-off of drainage #3–1 on 2019/05/26

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of the runoff confluence and outflow lag behind the timing of the rainfall peak. Therefore, the correlation coefficient can be used to determine the accuracy of the flow data after obtaining the correlation coefficient between instantaneous rainfall and instantaneous flow: if this correlation coefficient is low, the flow data are not accurate; thus, early warning and clean-up services can be provided. Outliers were analysed using the Pauta criterion and were then screened using a normal distribution. For example, 51,700 instantaneous flow values (excluding datapoints indicating zero flow) were monitored at monitoring station #7–2, and 252 outliers were screened by statistical methods. Figure 9e shows the outliers after the data was cleaned using statistics. (4)

Cleaning interruptions from hardware and the environment.

Some monitoring points will produce local interference values that are relatively small and stable in certain time periods due to the internal interference of the hardware and the interference of the surrounding environment on the monitoring equipment and transmission process. Therefore, it is necessary to separate and analyse highfrequency values to clean the hardware and environmental interferences. Figure 9c and d demonstrate the data interpolation from the interrupted data time series.

4 Model Integration 4.1 Set up of Model Group Based on the application requirements of the pilot city model issued by the Ministry of Housing and Urban–Rural Development (MoHURD) and the current construction practice of sponge cities in Guangming District, six types of models were built: a rainwater management facility model, non-point source pollution model, urban waterlogging model, urban flood model, river water quality model, and rainwater management optimisation model. The technical route showing the design of these models is shown in Fig. 10. A stormwater management model is a hydrological and water quality model applied for a single sponge facility or a combination of several sponge facilities, such as biological detention pools, infiltration channels, infiltration pavement, green roofs, rainwater buckets, and grass planting ditches. The runoff generation and sink model within a stormwater management model is integrated into the underlying surface runoff generation and sink models. The sponge city model of Guangming district is a 2D hydrodynamic integrated model that takes the controlled plot as the sub-catchment area to build the runoff, sewage, pipe network, river channel, and ground systems. The process-based source pollution model applies the underlying surface pollution generation and sink models, taking the plot as the smallest unit. The LID pollution generation and sink model is part of the underlying surface pollution generation

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Sponge city model system structure Generaliza on of minimum unit sponge facili es Non-point source pollu on process model

Coupling Runoff yield and concentra on model of underlying surface

Pipe network water quality model

Hydrodynamic model of pipe network

River water quality model

Hydrodynamic model of river

Dynamic model of surface overtopp ing flow

Flood rou ng and reservoir scheduling model

Parameter defini on

Parameter assignment method

Parameter es ma on and parameter value es ma on without observa on data Parameter calibra on with observa on data

Model application scenario development Effec veness evalua on of sponge city construc on at district scale

Sponge city design scheme evalua on at project scale Urban flood forecas ng and scheduling effect evalua on River water quality forecas ng

Fig. 10 Model application scenario and output diagram

and sink model and reflects the effects of sponge facilities. The urban waterlogging model reflects the coupled use of underlying surface runoff generation and confluence, pipe network hydrodynamics, and surface 2D hydrodynamics, corresponding to the surface overtopping hydrodynamic model in the system structure. The generation and confluence of the underlying surface use the lid generation and confluence as a link, reflecting the reduction effect of sponge facilities on water quantity. The hydrodynamic force of the pipe network is used to simulate the surface runoff dynamics after entering the drainage system. The two-dimensional hydrodynamic force of the surface interacts with the underground pipe network system in realtime, reflecting the evolution process of the surface water, which is used to simulate and analyse the risk of waterlogging. The urban flood model is based on the urban waterlogging model coupled with the hydrodynamic formation of river networks. This model corresponds to the river hydrodynamic model in the steel system structure. The contribution of the waterlogging model includes simulating the influence of surface water accumulation and the drainage of pipe network outlets on the river water quantity. The river water quality model was developed based on the urban flood model, non-point source pollution model, pipe network water quality model, and pollutant transfer model. The sources of river pollutants include upstream water, non-point source pollution, and node inflow. The non-point source pollution model takes the simulation results as the input conditions. The stormwater management optimisation model reflects the comprehensive use of the above models. Through the comprehensive simulation of several aspects of stormwater management optimisation, this

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chapter analyses the influence of different schemes on water and pollutant reductions and compares the economic benefits of these schemes to provide a basis for evaluating the stormwater management optimisation scheme. Various models couple different simulation modules, including runoff generation modules, slope confluence modules, one-dimensional and two-dimensional hydrodynamic modules, pipe network modules, water quality modules, and positive and lateral coupling modules. Some of the modules are secondary developments of the SWMM or other open-source sponge city models. In confluence modules, the nonlinear reservoir method in the SWMM is used as a reference, and a multi-node allocation mode is proposed based on inverse distance interpolation. For each minimum calculation unit of the model, the runoff can be allocated to multiple nodes, and other calculation units can receive incoming water according to the elevation relationship. This method improves the shortage of the traditional SWMM, which only allocates runoff to a unique node or parcel. In the hydrodynamic model, the 2D shallow water equation in the form of conservation is used to calculate the surface overtopping caused by overflow. The mass conservation and momentum conservation of surface water flow is considered accurate. The SWMM pipe model is used in the pipe network model, and the OpenMP acceleration technology module is improved. In the aspect of the water quality model, the “accumulation scouring model” based on runoff generation in the SWMM is used for the calculations. In terms of the sewage collection calculations, three types of water collection models are provided, including a complete hybrid model based on the pipe network confluence, a water quality model based on the 1D dynamic confluence of rivers, and the 1D dynamic confluence of convection–diffusion and first-order dynamic responses (1D water quality model) and a water quality model based on the 2D dynamic confluence of slope (2D water quality model). The coupling module was constructed from these three kinds of confluence models to simulate the actual process of rainfall. The principle of vertical coupling is as follows: first, water flows directly into the pipe network after rainfall runoff occurs. Then, the time series of overflow at the overflow hinge point is loaded into the surface 2D hydrodynamic model in the form of a point source to simulate surface overflow after the hydrodynamic simulation finishes in the pipe network. Four types of models are constructed, namely, a typical underlying surface, typical sponge facility, typical sponge project, and typical pilot area model, after coupling eight sub-modules. Finally, all these models were used to evaluate the performance of the sponge city development model in the pilot area, the management of urban flood control and drainage, and the supervision of black and odorous water bodies.

4.2 Model Management Figure 11 demonstrates the model pipe network and 3-D surface model of the studies area, as part of the overall model management.

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Fig. 11 Model pipe network (left) and 3-D surface model (right)

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Model calibration

The parameter calibration was divided into three levels: typical underlying surfaces and facilities, typical projects, and drainage divisions, for a total of 20 objects. Each object underwent two rainfall calibrations and two rainfall verifications. The efficiency coefficient was more than 0.5, ensuring the reliability of the model. The model included the output, query, and update of the data calibrated from the underlying surface, facilities, project, and area models and the calibrated parameters, NES coefficient, and calibrated calculation data. Additionally, the model calibration could be updated with the accumulated monitoring data, and the calibrated parameters could be stored, displayed, and analysed on the access platform. (2)

Model output

Six typical underlying models, bare land, green space, pavement, road, square, and roof models, were determined and verified by their runoff rates, and the parameter localisation model was obtained and output to the regional model. The localisation model parameters of sponge facilities should be output to the sponge project such that the area model can be obtained through the calibration and verification of the six typical sponge facility models in the area: grass planting ditches, rainwater gardens, ecological tree pools, sunken green spaces, permeable pavement, and green roofs. At the same time, the model was used to simulate and evaluate the runoff control and pollution reduction effects of different sponge facility types. Six typical project models of residences, public buildings, schools, and parks were built to simulate and evaluate the runoff control, pollution reduction effect, and contribution rate of different sponge projects. In the pilot area, models coupling runoff generation and drainage, sewage generation and drainage, pipe networks, and river hydrodynamic integration were constructed. These models include integrated flood and waterlogging simulations, combined non-point source pollution generation models, one-dimensional hydrodynamic river water quality models, and modelled simulations of rainwater management facilities (BMP/LID). This model was calibrated to obtain the following values: the annual total runoff control rate, pollutant reduction rate, waterlogging risk, drainage capacity of the pipe network, and other indicators of the built-up sponge area under various rainfall scenarios. This model can highly support the simulation analysis and platform application of the scheme formulation, sponge construction effect evaluation, waterlogging risk, flood safety, etc. (3)

Model maintenance update

The topological structure, catchment area parameters, pipe network confluence parameters, boundary conditions, and lid parameters of the sponge city construction model were determined after it was built. However, it is difficult to maintain accurate simulations of the model over long periods due to the spatiotemporal dynamic characteristics of the actual pipe network and lid facilities. The declining accuracy of the model greatly reduces the role of the hydraulic model in the operation and management of drainage networks, thus resulting in unreasonable decision-making

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or excessive simulation errors. The maintenance and updating of the model mainly include the updating of the pipe network topology, the updating of the basic data of the pipe network, the adjustment, and recalibration of the model parameters, etc.

4.3 Simulation Function (1)

Waterlogging simulation

According to the “Technical Specification for Urban Waterlogging Prevention and Control” (GB51222-2017) issued by the Ministry of Housing and Urban–Rural Development (MoHURD) of China, factors such as the uneven spatial and temporal distributions of regional and ground permeability and the confluence process of the pipe network should be considered when the catchment area is more than 2 km2 , while the rainwater design flow should be determined by the mathematical model method and the surface ponding depth under the recurrence period of waterlogging prevention and control should be checked. Therefore, the GRSWMM distributed hydrological model was used to couple the calculation of the one-dimensional pipe network model and the 2D surface model. In the design of urban waterlogging prevention and control facilities, the rainfall duration should be determined according to the service area of the facilities, using a duration range of 3 ~ 24 h. A 24-h design rainfall was used for the simulation evaluation. According to the "sponge city construction plan of Shenzhen national sponge city pilot area", the waterlogging standard shows that the duration of road waterlogging is more than 30 min and the depth is more than 15 cm. Three designed rainfall events were used as the input conditions for waterlogging risk assessments, with return periods of 30 years (370.66 mm), 50 years (411.32 mm), and 100 years (465.83 mm) and rainfall durations of 24 h. In the case of a 50-year return period rainfall, waterlogging occurs in the demonstration area, but it does not meet the waterlogging standard. The largest waterlogging depth in the whole area is located in zone 2, with a waterlogging depth of 29.2 mm and a duration of 12 min. In addition to risk assessments, the waterlogging simulation system can be used to link the rainfall forecasts of the Meteorological Bureau in real-time and select rainfall of the same grade through the platform to realise waterlogging simulations and forecasts. (2)

Flood simulation

There are two rivers in Guangming District: Dongkeng River and Ejingshui River. The designed flood standard was once in 50 years. Therefore, a 24-h design rainfall with one rainfall event in 50 years was used to simulate the river. The river water level and river fullness were observed to analyse the risk of river overflow. The simulation results are shown in Fig. 12. According to the results of the analysis and model simulations, under the condition of 24-h designed rainfall with a return period of 50 years, the fullness of most rivers was under 50%, and the water depths of the rivers did not exceed the designed warning water levels of the rivers. As a result,

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Fig. 12 Flood control and drainage management-related interfaces. Subplots (1) and (2) show waterlogging simulation interfaces; subplots (3) and (4) show diagrams of the deepest water level and the maximum fullness of the river course with a return period of 50 years and 24-h designed rainfall; subplot (5) shows the simulation results of 24-h rainfall with a 50-year return period

it can be considered that Dongkeng River and Ejingshui River do not exhibit flood risks under the flood control standard with a return period of 50 years. (3)

Water quality simulation

According to the rainfall situations when pollution occurs, water pollution incidents can be divided into 2 sudden pollution events: rainfall-based pollution events and leakage events. To address river pollution emergencies in these different situations, the smart sponge platform embeds the core of the water environment calculation model, and some simulation scenarios are used as references for the platform.

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5 Benefit Cases of SCSM-DSS For more than one year, since 2019, the system has been running steadily. Standardised monitoring operation and maintenance workflows have been established, such as monitoring data collections, analyses and discriminations, and platform warning notices. A long-term management and control business chain has formed combined with on-site verification, traceability of operation and maintenance personnel, relevant management, and the response of engineering personnel. Since the system started monitoring in August 2018, a total of 283 rainfall events and more than 20.8 million pieces of data have been obtained. Combined with visualisation, a datamining algorithm, and other big data analysis methods, in-depth clustering, slicing, outlier, and correlation analyses are carried out to mine contextual data from the massive data on the basis of conventional statistical analyses. Furthermore, the system makes full use of the actual correlations among the data, such as between rainfall and runoff and between the liquid level and runoff, conducts multi-dimensional and multi-level cross-comparisons, and realises the efficient cleaning of 45,000 new data points per day in 3–4 min. Combined with business needs and experience, platform functions are continuously updated and optimised automatically. Platform intelligence is improved to realise the whole process management ability of sponge city construction, from first planning to, finally, acceptance. The system has realised the automation of the management of monitoring equipment, the collection of monitoring data, business system classifications such as filtering, analysis, push, project management, and assessment, partition statistics, and iterations.

5.1 Typical Function 1—Flood Control and Drainage Management Flood control and drainage management systems are important typical applications in smart sponge city projects. These systems include river information, flood safety, and waterlogging safety. Flood safety, which is mainly used to monitor and simulate the safety situations of river channels during rainfall (once in 50 years or once in 100 years, with a 2-h temporal resolution), includes weather forecast viewing, simulation scenario selection, river safety simulation, water level maps, and other functions. To realise waterlogging prevention measures in advance, it is vital to simulate changes in waterlogging in the pilot area of the sponge city under various rainfall scenarios (different return periods, typically measured rainfall, etc.) according to the rainfall situation of the latest weather forecast. The main functions of these forecasts include weather forecast views, rainfall scenario list views, plot ponding change curves, ponding change simulations in the pilot area, and waterlogging scheduling. The platform records the relevant information of all the rivers in the pilot area and visually displays all the rivers in the pilot area in the form of a list on the left.

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5.2 Typical Function 2—Sponge City Performance Assessment System Sponge project construction is designed based on the “national sponge city construction pilot performance evaluation index”, “national sponge city construction pilot performance evaluation index scoring rules” (November 20, 2017), and “sponge city construction evaluation standard” (GBT51345-2018). The implementation effect of sponge city construction in Guangming District of Shenzhen was evaluated by measuring and simulating values such as the total annual runoff control rate of the project, the total annual runoff control rates of different districts, the effectiveness of the project implementation, the drainage capacity of the rainwater pipe network, the prevention, and control capacity of urban waterlogging, the treatment effect of black and odorous water bodies, and the proportion of the sponge city that is up to the standards in the demonstration area. From the results of the simulation analyses of the traditional development mode and sponge construction mode, the annual total runoff control rate of the sponge construction mode in each drainage area of the demonstration area is clearly and significantly higher than that of the traditional development mode. All indicators of sponge city construction fully meet the planning objectives, with an annual total runoff control rate of 72% and an SS reduction rate of 62% based on the monitoring and evaluation analyses conducted from 2019 to 2020. The peak runoff of typical rainfall with 3-year and 5-year return periods is delayed by 5–20 min, and the reduction rate of the peak runoff is approximately 35%. According to the analysis of the network and surface waterlogging, the networks of the Dongkengshui and Ejingshui watersheds are better than the other watersheds, and the length of these networks with 5-year return periods or greater than 5-year return periods reaches 89.4% of the total network length (see Table 3). In other words, the waterlogging risk has been significantly reduced in the study area. The demonstration area has achieved the goal of no waterlogging under 50year heavy rainfall and no waterlogging under light rainfall or heavy rainfall. The Dongkeng and Ejingshui Rivers have reached their flood control targets of once per 50 years.

5.3 Typical Function 3—Project Lifecycle Management (PLM) Managing the whole life cycle of sponge projects, from the project approval, design, construction, and acceptance to the management and maintenance of the project aftermath, is vital. The workflow of PLM includes collecting the regional planning scheme, design information, location information, facility construction information, operation management, and maintenance information of sponge city projects. To conclude, it is convenient for the construction management department to (1) track

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Table 3 Summary of evaluation results Evaluation content

Target threshold

Actual rate

Meet threshold

Key points

Annual runoff control 70% rate

72%

Yes

The DSS helped to complete the simulation Analysis of the total runoff control rate of the whole demonstration area and 19 drainage zones from 2008 to 2017 and the analysis of the measured total runoff control rate of 4 drainage zones in the rainy season from March to September 2019

Shoreline ecological restoration

100%

100%

Yes

Maintenance degree of natural water area

≥4.46%

5.4%

Yes

Rate of surface water quality meet national standards

100%

100%

Yes

Index of non-point source pollution control

Clear background data of stormwater pollutants Initial rain pollution control (calculated by SS) ≥ 60%

Runoff pollution investigation is completed; 62%

Yes

Utilisation rate of rainwater resources

≥3%

7.4%

Yes

The water area in the pilot area increased by 0.26 square kilometres (20.6%)

3976 runoff sampling and pollutant detection times were completed in the pilot area, data stored in the DSS, see Sect. 3 With the help of the DSS, the simulation results shown the SS reduction rate of each drainage area in the pilot area are between 40 and 72%, and the overall reduction rate of the pilot area is 62%

(continued)

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Table 3 (continued) Evaluation content

Target threshold

Actual rate

Meet threshold

Wastewater recycling rate

–

100%

Yes

Waterlogging control standard

Once in 50 years Once in 50 years

Yes

In the pilot area, 7 waterlogging spots were eliminated. Through the modelling analysis of the DSS, under the 24-h rainfall scenario with a return period of 50 years, the rainfall reached 411 mm, and there was no risk of waterlogging

Flood control standard

Once in 50 years Once in 50 years

Yes

According to the model analysis, under the condition of 2-h rainfall with a 50-year return period, the rainfall reached 138 mm, and there was no flood control risk

Compliance rate of flood bank construction

100%

Yes

The flood control standards of the Dongkeng watercourse and Ejingshui River in the pilot area reached 50-year return periods, and the compliance rate was 100%

DSS platform

It should be able Competed to support the pilot effect assessment, facility operation scheduling and auxiliary government approval

Yes

Introduced in this chapter

100%

Key points

(continued)

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Table 3 (continued) Evaluation content

Target threshold

Actual rate

Meet threshold

Key points

Model application

Model application should be scientific and reasonable

Completed

Yes

Introduced in this chapter, specifically in Sect. 4

the whole process of the project, (2) understand the progress of the project, (3) determine the problems existing in the concealed works through time, (4) realise the effective evaluation and monitoring of the construction of sponge cities, (5) improve the design and construction quality of sponge city projects and (6) ensure the overall effect. Combined with the whole process of sponge project construction management and control in the pilot area, the PLM system combines all levels of management and users participating in the construction. These include the workflow and management requirements of the construction units, the approval units at all levels, and the management and maintenance units). According to the actual business management processes of the project approval, design, construction, acceptance, management, and maintenance, two main business functions are realised. With the comprehensive promotion of sponge city construction in Guangming District, all new reconstruction and expansion projects should be implemented to meet the requirements of sponge city construction, and the platform described herein supports the global control of sponge projects in Guangming District (Fig. 13). The results show that the whole process management of the 121 sponge construction projects in Guangming District can be realised through this system by the end

Fig. 13 GUI of the project lifecycle management system

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of 2019. The project types include sponge parks and green spaces, buildings and communities, roads and squares, urban water affairs, pipe network engineering, clean-up, comprehensive environmental improvement, etc. By the end of 2019, the completed project covered an area larger than 10km2 , and the management process involved more than 20 government management units, such as construction and approval units. This project has become a powerful tool for users to grasp the construction status of sponge cities in real-time and provides great convenience for managing and controlling sponge construction and operation- and maintenancerelated work. At the same time, this project has also become an important starting point for Guangming District to guide the pilot area and even other key areas in Guangming District (Fig. 14).

5.4 Discussions The integrated decision support system SCSM-DSS coupled three support systems and four application platforms. Based on the “five layers and two wings” framework, SCSM-DSS covered the entire construction and management processes and all the performance evaluation factors. It also realised “360°” monitoring of flows, liquid levels, water quality, rainfall, soil permeability, and other key indicators. In addition, eight databases, including the sponge city construction project database and sponge city construction monitoring database, were set up to integrate and analyse the monitored data to realise digital, intelligent, and refined project management. Comprehensive system monitoring, intelligent analysis, and dynamic evaluation can provide scientific data support for the operation, maintenance, and management of facilities in sponge cities and aid in the construction of sponge cities. However, it is difficult to obtain comprehensive business data and spatial data for various reasons, which may lead to distorted decision-making. An optimised monitoring network based on a quantitative design method must be considered and applied in future projects. Almost 30% of the system development budget is used for monitoring campaigns. Driven by big data and artificial intelligence algorithms, the control areas of smart city management and control platforms will be transformed from “pilot areas” to “demonstration zones”, from areas under project management to areas under behavioural management, and from areas that reach individual catchment standards to areas that reach the standards of the whole construction area. This development will further control the large-scale sponge background of landscape forests, land, lakes, and grasslands, strengthen water infrastructure and space management, and improve medium-scale sponge types such as shallow drainage systems. Shenzhen is promoting the creation of fine micro-sponge types such as green roofs, concave green spaces, rain gardens, and permeable pavement and is building a modern water management system.

Fig. 14 Project lifecycle management flow chart

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6 Conclusions This case study chapter introduced the consolidation and integration of management technology into a decision support system named SCSM-DSS for a national sponge city demonstration area in Shenzhen, China. The results reveal the role of sponge cities’ smart management and control platform in the construction and operation of sponge cities. Hydrology and water quality monitoring indices and monitoring technology were integrated with the demonstration area well. Data pre-processing techniques were found to be necessary for such comprehensive data sources and types. The modelling and performance evaluation process benefitted well from data exploration, data cleaning, data pathing, and data screening. We also developed very strong data cleaning methods covering the range, logical relationships, statistics, and the data’s interruptions. Different models were successfully integrated into a group to meet management needs, which were highlighted as waterlogging simulations, flood simulations, and water quality simulations. Flood control and drainage management practices, sponge city performance assessments, and project lifecycle management may be the most beneficial features obtained from the SCSM-DSS. The SCSM-DSS provides scientific and reasonable results as well as convenient use. In the long run, determining how the system can improve or maintain its performance in analysing facilities, plots, and overall areas and determining how it can help facility operations is worthy of consideration. This case study has significance as a reference for other regions building informative and intelligent systems for sponge city construction and operation. Acknowledgements This work was supported by the National Natural Science Foundation of China (Grant No. 51979136) and the Science, Technology and Innovation Commission of Shenzhen Municipality (Grant No. JSGG20201103094600001).

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Applying Multiple Nature-Based Solutions (NBS) with Regional Flexibility in Bio Building Design in Southeast China Minjia Fan and Ali Cheshmehzangi

Abstract With the global population increase, satisfying the quality of living of urban citizens has become a major challenge in urban design and planning. In addition, the environmental damage intensifies rapidly, land sources have been limited, and species diversity is failing. On account of urbanisation expansion, construction is growing to higher levels and underground development, both intensifying density of the built environment. In both cases, we continuously face the reduction of space used for green and blue infrastructures. As a result of living stress, human beings’ physical and mental behaviour are increasingly affected by buildings. The idea of bio building combines ecology and architecture. Based on the local condition, architects/designers and planners can apply buildings with biological characteristics, such as living materials or vegetation and plants. This is one of the common ways close to nature-based solutions and can be utilised for various planning and design projects at multiple scales. China has been one of the fastest populations growing countries. Eco building design has been developed in China since the 1980s. As the increase of sustainable consciousness, experts have considered the relationship between architecture and ecology. Eco building design aims to connect nature with building design, reduce energy consumption and reuse the existing energy. This chapter will discuss the strategies of eco-building design and figure out a feasible ecological cycle in a rural area in China at the micro-level. The chapter focuses on applying multiple nature-based solutions (NBS) for bio building design in Southeast China. The feasibility study benefits from modelling and simulation, demonstrating the benefits of NBS integration at the micro-level, specifically for building energy performance, users’ satisfaction, and sustainable strategies for building refurbishment design. The findings will benefit future research that aims to include NBS as their strategies for refurbishment. M. Fan · A. Cheshmehzangi (B) Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, China e-mail: [email protected] A. Cheshmehzangi Network for Education and Research on Peace and Sustainability (NERPS), Hiroshima University, Hiroshima, Japan © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_16

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Keywords Nature-based solutions · NBS · Bio building · Design · Building performance · Refurbishment

Glossary of Symbols Sv SA d η1 DL η2 LAI GWR WWR k-value

storage volume (ft3 ). the area of green roof (ft3 ) depth of substrate (inch) maximum water retention of substate, taking 0.15 depth of drainage layer (inch) maximum water retention of drainage layer, taking 0.15 leaf area index greening to wall ratio window to wall ratio heat transfer coefficient

1 Aims and Objectives The primary aims of this chapter are to refurbish a small village in southeast China, which is located in Guangxi Province with hot and wet climate conditions. The poor economic condition means the refurbishment needs to consider the cost problem, utilising existing natural conditions for further improvement. The objectives of the study can be divided into two primary parts: • Applying Natural Based Strategies (NBS) to improve building performance and to promote local economic situation under specific local requirements; and • Establish a feasible agro-ecological cycle frame to further improve the energy efficiency of buildings, using an NBS-based approach in building refurbishment design.

2 Introduction: Nature Based Solutions (NBS) as Integrated Strategies Nature-based solutions (NBS) are strategies in bio buildings aiming to improve the environmental quality in inhabitant districts with economic and social benefits. This chapter seeks to design a refurbishment of a small village located in Southeast China with multiple natural-based solutions and assume a reasonable ecological cycle frame to improve the connection between nature and human beings. NBS was first defined in the late 2000s (Mittermeier et al. 2008; Li et al. 2020; Sun et al. 2020; Li et al. 2021),

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refer to resolve social challenges to urban buildings utilising sustainable management strategies, such as green roofs, green streets (Perini et al. 2018), and vertical greening systems (Pérez et al. 2018a; b). Applying NBS will help protect biodiversity and human living comfort, greening systems can provide habitat for species, Aesthetic sense to buildings will also improve residents living index. (1)

Green roofs consist of plants or seeds in growing medium above a waterproof membrane on the rooftop.

The benefits of green roofs are significant. The vegetation layer absorbs the solar radiation, leading to the lower thermal performance of roofing. The increase of heat mass in the roof leads to the reduction of building cooling demand. The decrease of heat flux causing by vegetation can efficiently emit the heat island effect. With 90% surface green roof, the urban heat island effect can be reduced by 3.8 ◦ C temperature drop. The improvement of thermal comfort for residents caused by urban heat island reducing 5.7 ◦ C for roof surface (Imran 2018). Compared to traditional concrete roofs, Green roofs can minimise the biodiversity influence to the least (Brachet et al. 2019). As a sustainable drainage system that can be helpful for rainwater management, the reduction of metals concentration is significant. In addition, the resilience function of a green roof refers to the feasibility under extreme weather. Pollution concentrations can be expanded rapidly due to the cool air produced by vegetation. Thus, the air quality of streets can be improved. Regarding residents’ living comfort, green roofs can reduce noise by weakening differing sound waves on roofs and sound transmission paths within the roof to prevent the reveal of internal privacy for residents (Van Renterghem 2018). Additionally, the aesthetic value of green systems is considerable. The improvement in the human sense is helpful for remit stress of residents (Cheshmehzangi and Griffiths 2014). For social perspective, green roofs provide spaces for human entertainment and working. (2)

Vertical greening systems (VGS) normally indicate the green façades and living walls.

The classification of VGS can be summarised as two types, extensive systems, and intensive systems. Green façades adapt to the extensive system, located outdoors and structural composition utilising lightweight stainless steel, selection of vegetation mostly climbing and hanging, cost of green façades are lower than the intensive green system. Intensive systems contain living walls, providing different types of VGS based on the residents’ goals, living walls including cloth systems, modular panel network, and active living wall systems. The first two types install at both outdoors and indoors, providing vegetation generation for habitants. According to the local climate condition and resident requirements, vegetation selection is multiple. The cost of cloth systems and panel systems are higher than green façades, lower than the last type, active living walls. The installation of functional/active living walls is primarily indoors. Unlike the other kinds of VGS that provide passive energy savings, they can generate active energy-saving solutions to occupants due to biofiltration causing by the forced airflow passing through living walls (Darlington et al. 2000). Similar to green roofs, vegetation can improve biodiversity for local species by

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providing habitat. The passive functions of VGS can reduce the heat island effect by providing solar shading to cool buildings. By selecting appropriate plants that have no influence on the local ecological system, vegetation on VGS can absorb huge pollution concentrate to improve residents’ air quality, such as the capacity of cooling in plants can indirectly decrease the gas emission of air conditioning system (Perini et al. 2018). Additionally, evapotranspiration from vegetation refers to cooling streets and surroundings. For rainwater management, the foliage can be able to control by managing the runoff and autologous absorption. Those benefits are significant in urban sustainability control. Although the primary design for VGS is not including acoustic insulation, the reduction of high and middle frequencies contributed by vegetation indicates the noise reduction by 20z–300 mm VGS can reach 2 or 3 dB. (3)

Green streets normally consist of integtating green sstems into the built environments, considered as outdoor urban environments and landscaping.

Green roofs and VGS have not been evaluated and applied widely in China. Green streets, on the contrary, can be seen everywhere. The green street has been a universal green system in urban design. Based on the different cultures and different climates, the plants applying on the streets are different. However, the limitation of plants diversity is significant. For instance, almost 50% of street trees in Taiwan are Cinnamomum camphora, Ficus microcarpa, and Koelreuteria elegans. Green streets have been ignored usually, the indifference of the government results in the high death of street trees. Like VGS and green roofs, green streets can improve outdoor thermal comfort for citizens by reducing radiant temperature. Pollutant reduction is also the benefit of green streets, such as reducing CO2 emission by photosynthesis. Although the exact effect of CO2 reduction by green streets cannot be determined based on existing technology, the positive influence of green streets is undoubted.

2.1 The Agri-ecological Cycle The next goal of refurbishment is to establish an ecological cycle frame of buildings and nature. The village is a traditional Chinese countryside. Cultivation and breeding industry are two basic modes for residents living. Combining agriculture and buildings and figure out the relationship can be positive for energy saving. Figure 1 shows the relative energy between building and agriculture. Wasted water from buildings that after treatment can be utilised in irrigation of agriculture and vegetation of NBS. Moreover, cultivation can also provide electricity and water for buildings correspondingly. As Fig. 2 demonstrates, agricultural water can be obtained from building through systematic water treatment and vice versa. Ecologically reclaimed water can also utilise in artificial water ecosystems, such as wetlands for landscape. Biomass generation is efficient for a rural region. Agricultural residues can be converted into biomass energy for power generation, increasing the efficiency of agricultural waste and

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Fig. 1 Relationship between buildings and agriculture

Fig. 2 Water treatment impact

improving air quality, providing environmental benefits (Wang et al. 2019). Figure 3 shows the utilisation of agriculture residues conversion, which is originally developed by Wang et al. (2019). As shown in Fig. 4, excrement from occupants and breeding animals produce marsh gas. Moreover, the crop residue ‘straw’ can also produce marsh gas for biomass power generation, and residue from biomass plants can be re-utilised for manure.

3 Methodology Package for Case Study Research The study is designed in four stages of (1) pre-design and case study evaluation, (2) fieldwork and data collection, (3) design and modelling, and (4) calculation and integration. In stage one, the intention is to define green NBS and to understand the building ecological cycle. In doing so, we determine the benefits of three types of NBS. We also learn about limitations, conditions of acceptability (i.e., for plants, climate, and building function for case study research). In stage two, the fieldwork would help to provide case study data collection. It is done in three steps of developing an estimated layout of the selected area as the case study, micro-climate analysis, and natural resources data collection. This is followed by questionnaire research from residents about the acceptability of NBS, which also includes questions about their living experiences. The materials are used as secondary materials. We then select one building as a case study building and collect building information (e.g., dimensions, spatial layout, materiality, structure). In the third stage, we model the selected case. This is done by making a decision on vegetation, structure, maintenance of NBS for

Fig. 3 Agricultural residues convert into renewable fuel. Adapted from Wang et al. (2019)

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Fig. 4 Biogas cycle

its integration in building renovation or design. The follow-up decision is on energy cycling elements. The model is developed using SketchUp software to establish 3D models to present NBS results in multiple scenarios. The fourth stage includes the manual calculation of energy savings caused by NBS. The findings are supported by software simulation but mainly focus on manual calculation and integration options. A feasibility assessment is done and discussed towards the end of the study. Figure 5 below summarises the methodological framework of the study. During the field visit in Stage two, energy resources of the case study area were investigated, such as water source and electric source. In the rural area of China, some regions apply natural resources for their routine use. For instance, fetching water from mountains is the most common way for a remote area to receive its water supply. Some villages have established a special path for fetching water. Water at the top of the mountain can be guided to passing through a particular path designed by the locals. Therefore, we can argue a closer link with nature in such environments compared to city areas. Except for the local energy sources, the vegetation environment in the surrounding is also investigated in this study. Due to poor economic conditions, the cost from the integration of NBS should be minimised as much as possible. This approach affects the selection of local plants for the purpose of refurbishment; hence, the link between nature and buildings can be more interrelated. After the investigation of energy resources, the ecological cycle frame is designed preliminarily. The elements of the establishment include crops in the local area. In such cases, the crop has special significance in the connection between nature and humans. The importance of establishing an ecological cycle at the building level is to figure out how to utilise crops to improve nature in return. In addition, we could apply renewable energy as a supporting method which can be another feasible strategy in ecological cycle establishment. Thus, we summarise that biomass energy of rejected material of crop can help generate power at such scale of the built environment.

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Literature review

Case study of multiple NBS buildings

Case study of typical building ecological cycle

Village information

Questionnaire

Case study building data collection

Design concept of NBS

Decision of energy cycling components

Taking case study building as an example to establish 3D model

Through literature review to calculate energy savings Proving final ecological cycle frame

Discussion of feasibility

Fig. 5 Methodological framework of the study in four stages

3.1 Other Case Study Examples Case study 1: Integrated NBS building: Khoo Teck Puat Hospital in Singapore Khoo Teck Puat Hospital (KTPH n.d.) is located in the north of Singapore. The total green area is approximately four times the area of KTPH occupied. The floor area of green space achieves 18%, and 40% among them is open to the public. The building is based on the ‘forest principle’, with water elements, vegetation in façade connects the ground garden with a green roof, attracting huge numbers of birds and aquatic organisms. Aesthetics from greenery significantly satisfy patients, creating a perfect healing environment. The green roof in KTPH is an intensive green garden, and vegetation selection is also cultured. For example, the green garden on the Specialist of Clinical Service utilises edible species, such as fruits and vegetables. It can not only service the kitchen; some of them can also be a part of herbs recycling by the hospital. Local climate belongs to a tropical climate. The species are all adaptable to a hot and humid climate, indigenous species reach 70%, low-maintenance demand. For operating these huge green systems, the hospital takes full advantage of peripheral nature resources, irrigation systems use the water from the Yishun pond

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nearby, largely plant edible vegetations, including 130 fruits and more than 50 edible vegetables. Case Study 2: Local Bio Building utilised NBS: Guangxi Province, Nanning Ecological Science Education Center Guangxi Province, Nanning Ecological Science Education Center is located in the countryside of Nanning (107° 45 E, 22° 13 N), which has a similar geographic location as the refurbished targeted village. The whole building is double layer construction with a green roof and vertical greening system as a micro integrated NBS building. With similar climate conditions and economic situations, this building is a successful case study of bio building design in southeast China. Design philosophy includes five critical points. Low construction cost, low maintenance cost, and low operating cost are the clear concepts by applying a high-efficiency ventilation design to cool the building without an air conditioning system. These could be achieved according to the circulation principle to achieve a sustainable green building. The building has no artificial cooling strategies. A green roof and vertical greening system will completely meet the cooling requirements. The roof greening utilises a drip irrigation system and dislocation arrangement. The vertical greening system is not directly working on the external building wall. The vertical greening design uses a thin wall with multiple holes in front of the building façade that directly receives sunlight. According to the architects’ team, this design is for considering solar radiation influenced this building. Only two façade can receive sunlight, and the other two sides can be shaded by a green roof. This building is isolated with vast fields, which means this building is suitable for natural ventilation. In order to improve natural ventilation to achieve a cooling purpose, the design uses courtyard ventilation, exhaust with no power located on the roof, and a buried duct ventilation system. The green roof and vertical greening can provide enough cooling for the whole building in summer. The temperature difference caused by green systems can reach to maximum 9 ◦ C, and the average of 6 ◦ C. Total power consumption reduces 108 kWh per one hour, and energy consumption has been significantly reduced.

3.2 Case Study Information: Location and Climatic Data This section is divided into three parts. At first, we introduce the basic background of the targeted village. The second part is the analysis of the local climate of the last five years. The third part investigates the vegetation of the surroundings in order to decide the choice of NBS application. And finally, the fourth part discusses the energy source of the selected area, which will be suitable for the agri-ecological frame cycle assumption. (1)

Location and Contextual Analysis

Targeted buildings in ‘Renhe Village’ are located in Guanyang Country, Guilin City, Guangxi Province, 111.14° E, 25.49° N. Figures 6, 7, and 8 show an estimated layout

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Fig. 6 Estimated layout of Renhe Village, showing rough land distribution in the area

Fig. 7 Renhe Village (Source The Authors)

of this village. The primary farmlands are located in the center of the village, and it is verified that utilisation of nature sources leads to a large terrace. The site includes many terraces and farmlands that are more visible in warmer seasons of spring and summer. Renhe Village is upstream of Xiangjiang river tributaries, water storage is abundant, with larger than 560 m altitude and luxuriant vegetation. During the recent years development, utilisation of natural resources is recognised to be prosperous. Renhe Village is located in a bowl surrounded by mountains. The only road to enter the village is a narrow winding path on the mountain. Along the road, there are four villages, and Renhe Village is the one located at the bottom of the bowl. The village’s natural resources represent a typical example of a nature-community relationship in rural and some peri-urban areas in China. Due to the winding and rugged roads, there are some platforms located at the corners of the path, mostly are also the corners of the buildings (Fig. 9). In Table 1, we summarise the basic information of the Renhe village, some that have been collected through a questionnaire survey of residents’ living experience.

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Fig. 8 Terrance of Renhe Village (Source The Authors)

Some information are extracted from local documents and official reports of the village community. (2)

Climatic Analysis

This sub-section investigates the 2015–2019 climatic data to ensure the accuracy of data. Local climate analysis is extremely important for designing nature-based strategies. Based on the analysis, filtrating vegetation cannot survive or need to exist under careful attention. Due to poor economic conditions, the selection of vegetation need to be easily transported, and their growing environment is adapted to the local climate. • Weather According to local weather station data, the primary weather condition of Renhe Village has mixed rainy, sunny, and cloudy weather conditions. Rainy days are amongst the highest every year, based on the extracted data from 2015 to 2019. The variation tendency of weather conditions is relatively obvious. For instance, sunny days were decimated in 2018 and 2019, and cloudy days occupy the most in the whole year. As per records, rainy days decreased slightly but remained as the uppermost weather conditions. The records show that extreme weather of this village is insignificant, such as snowy, foggy, and stormy weather conditions. Based on the above weather data, the local climate is appropriate for the healthy growth of

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Fig. 9 Narrow path of Renhe Village (Source The Authors)

Table 1 Basic Information of Renhe Village Population

450 (Maximum, including migrant workers) Residents: 200

Buildings

150 (including 112 three-layer constructions and 48 two-layer construction. Each building has a small and lower building utilising as breeding space)

Crop

Paddy, pear, and black plum

Breeding livestock

Fish, pig, and chicken

Seasonal living experience Winter: Cold and humid, poor ventilation condition, charcoal is the only strategy for keeping warm Summer: Extremely hot and humid, poor ventilation cannot satisfy cooling requirement

most vegetation in the area. Thus, the selection of NBS vegetation is relatively large, particularly if compared to other regions in China. • Temperature The variation tendency of temperature in 2015–2019 is indistinguishable (Fig. 10). In June, July, and August, the temperature is extremely high, with the highest temperature reaching 38 ◦ C in August. In winter, the average temperature shows that it

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Fig. 10 Average temperature of every month in last 5 years (Source extracted from historical weather data from local documents)

should be comfortable for residents. However, due to rain and high humidity levels, temperature varies widely from day to night, and sensible temperature can still reach subzero (based on historical weather, not dated). This region belongs to a subtropical monsoon climate that the agricultural products are particularly abundant. Generally, the refurbishment needs to achieve cooling in summer and thermal insulation in winter without a heating supply. However, thermal insulation in winter has a large requirement in ventilation, and locals prefer charcoal fire to keep the indoor spaces warm. • Precipitation Figure 11 illustrates the precipitation of annual rainfall and monthly rainfall in Renhe Village between 2015 and 2019. Average daily precipitation maintains approximately 15 mm, and annual precipitation remains greater than 5,500 mm. Those data show that Renhe Village has adequate rainfall. Therefore, the type of vegetation that can be used as part of the NBS strategy can have reduced irrigation. Lastly, the utilisation of natural irrigation contributes to cost-saving. • Humidity As per the local data of five years, it can be determined that this region has extremely high humidity. Thus, the type of vegetation for the NBS application requires to decrease humidity. In this regard, it is recommended that the refurbishment design should include dehumidification strategies as well.

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Fig. 11 Precipitation from 2015 to 2019 (Source extracted from historical weather data from local documents)

• Wind Orientation The wind orientation data is essential for the integration of greenery on vertical spaces and streets or outdoor environments (Fig. 12). Wind power has been a widely used electricity source in the Chinese countryside (see Fig. 13). According to Figure 12, the dominating wind of this region is northerly, northeasterly, and southerly. In April, May, June, and July, the dominating wind is southerly. Based on the wind orientation, the design of a vertical greening system requires considering the orientation of the window in order to achieve the best natural ventilation to reduce humidity in outdoor air environments. (3)

Vegetation Analysis

Vegetation investigation is mainly focused on crop and common vegetation in southeast China. Crop can be a part of the energy cycle to improve energy efficiency, and vegetation in subtropical monsoon climate could effectively contribute to the green system design. Due to the abundant rainy days in this region, the soil moisture content is mostly superabundant. Therefore, the locals usually select crops that can adapt the drippy climate. Staple crop is similar to other southeast regions. Also, paddy is cultivated twice annually, based on seasonal weather conditions. The vegetation information is summarised in Table 2. In order to achieve the maximum energy efficiency, the above information could be utilised in renewable energy design. For instance, based on different harvest time, the capacity factor for different crops in every season can be calculated. However,

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Fig. 12 Wind orientation from 2015 to 2019 (Source extracted from historical weather data from local documents)

Fig. 13 Wind power generation station on the top of mountain (Source The Authors) Table 2 Primary crops in Renhe Village (Source from on-site survey results)

Species

Sowing time

Harvest time

Yield (kg/year)

Paddy

April and August

July and November

375 and 500

Corn

April

August

500

Sweet potato

June

October

700

Pear, black plum

n/a

July

650

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the green systems will not select single vegetation, considering species diversity and aesthetics. Thus, selection could differ in each green system based on the utilisation and application process. (4)

Energy Utilisation

As the site is located in the mountains, natural resources storage is abundant. Residents have developed most of the natural resources to improve their domestic requirements. On account of high humidity and abundant precipitation, groundwater and spring water storage is extremely large in the nearby mountain. Copious water will drop through mountains and flow into farmland and terrace annually. In order to separate this water to prevent crops from being drowned, residents have applied two methods to get the utmost out of water utilisation. The first method is ‘Hydraulic Generation’, and the second one is ‘Domestic water use’. Both methods are deemed to improve the living experience as well. Figure 14 shows the hydraulic generation reservoir, which is also the forebay of this generation station. According to the report from the local Bureau of Water Conservancy and Power (2001), this forebay occupies 450 m3 area, with an annual Fig. 14 Forebay of hydraulic generation station (Source The Authors)

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generating capacity of 6,000 kilowatt-hours, which satisfies all residents’ requirements. The remaining power has been combined into the municipal grid, delivering to other regions based on their requirements. Except for hydraulic generation, spring water utilisation is also applied in domestic water. Groundwater is clean enough for domestic building use. The distinction between hydraulic generation and domestic water is that the water for generation is mostly from atmospheric precipitation (e.g., rain and snow) and river. Usually, the mixed water of the river and precipitation is muddy. Thus, if there is no water purification machine, this type of water cannot be utilised as domestic water. This is the reason that water for domestic use will be mainly from groundwater. Groundwater includes atmospheric precipitation; however, it is usually absorbed by vegetation on mountains, permeating into the ground. After filtrating by vegetation and inner mountain areas, it is sprayed out of the ground due to diastrophism, which forms a spring water effect.

4 Refurbishment Concept 4.1 Building Requirements According to a questionnaire survey of the locals about bio building refurbishment, we summarise their requirements in Table 3 and Fig. 15. Table 3 Questionnaire about green system refurbishment Refurbishment project

Residents’ opinion

Green roof

In paddy harvest time, their roofs need to be utilised as grain-sunning ground

Vertical greening system Concern about maintenance difficulty and cost Green street

Narrow road cannot accommodate more trees

If GS placed in front of/around their buildings

Fig. 15 Summary of the survey results, based on three types of green systems (Source The Authors)

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From the results, we verify that the NBS strategy of green streets is favoured the most. Although most locals have rejected the green roof strategy, it can be used to reduce the heat gain effect from the roof areas in summer. This could help to balance the situation and promote the potential bio building design. In this regard, there are abundant factors that can influence bio building design selection, including but not limited to: (1) Sustainability, (2) Cost, (3) Flexibility, (4) Safety, (5) Control and Adaptability, (6) Biodiversity, (7) Cooling, and (8) Economics benefits. However, in a real condition, the refurbishment design cannot satisfy all the decision factors. In order to evaluate a suitable design concept, the weight of each factor needs to be considered under local specific conditions. Therefore, a factor weighting approach is utilised to rank the above eight design considerations before reaching the design stage. The decision matrix analysis is applied based on this factor weighting to select appropriate devices or types for subsequent detailed design. Normally, for rural regions in China, the best performance is not the first selected criteria. The rural region of an underdeveloped countryside is more concerned about the basic cost and convenience, poor economic condition, and technology limitations. Thus, such factors lead to more attention on prime cost. Other factors become to add brilliance to the design’s present splendor. Tables 4 and 5 demonstrate the weighting Table 4 Criteria weighting for decision matrix

Table 5 Factor weighting in NBS design consideration

Criteria

Weighting

Not important

1

Less important

2

Moderately important

3

Important

4

Extremely important

5

Factors

Weighting

Sustainability

3

Cost

5

Flexibility

4

Safety

4

Control and adaptability

5

Biodiversity

1

Cooling

3

Economic benefits

2

Social and aesthetic

2

Water management

2

Comfort

4

Noise and insulation

2

System performance

3

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of NBS design factors. Based on the survey of locals, we note three factors of cost, control, and adaptability are given the highest priority in the refurbishment plan. Next are comfort, safety, and flexibility. Rural regions need concise control, which refers to daily maintenance and usage. Local residents have no requirements for complex and highperformance devices. But, they are more concerned about whether the systems can adapt to their daily routine and day-to-day requirements. Comfort is also important in building refurbishment. It is evidenced that traditional construction structure results in enormous cooling load. Thus, poor ventilation in hot-humid climates deteriorates original terrible indoor comfort, which is identified to be a major challenge for rural housing areas in China. The flexibility factor is based on residents’ requirements, such as balancing the usage of the roof. In particular, the main concern is about designing a green roof without influencing the initial utilisation of the roof. Based on the survey records, the weighting less than 3 indicates there are no requirements or demands by the locals. Certainly, those factors do not mean to be insignificant. But they will not be prioritised in system type or device selection.

4.2 Green Roof Design Concept According to the survey results, the green roof design needs to be (1) low cost, (2) seasonal, and (3) convenience for maintenance. Considering the fact that targeted buildings belong to residential buildings, an intensive green roof is inadaptable. Thus, the basic structure cannot bear intensive green roof weight load, even though intensive green roofs can provide better aesthetic and performance. Thus, the weighting load survey indicates safety as the first important determinant. In green system design, weighting load includes dead load, live load, and transient load. Permanent load refers to the systems’ initial structure load, building materials, vegetation, and water storage. The variable load includes residents and routine maintenance. And the transient load is the accidental loads, such as wind and tremor load (Growing Green Guide 2014). Buildings in Renhe village are primarily constructed in 2008, according to Load Code for the Design of Building Structure (GB50009-2001 2006). Thus, the maximum load of the floor for residential buildings is 2kN/m2 . It is argued that extensive green roof is more suitable for residential buildings. The weight loads of extensive green roofs are normally between 5.1 to 10.2, 5.1 kg/m2 for green turf roofs, and 10.2 kg/m2 for a low herbaceous green roof (FLL Guidelines 2018). These two vegetation are within the scope of the bearing load of the Renhe village building. Considering the cost factor, the refurbishment could be based on the initial building structure, strengthening the existing roof/façade systems. Figure 16 shows the common roof and façade of Renhe residential buildings. It can be seen that the roof was designed to be manned so that residents can walk on the roof for maintenance purposes. The roof was constructed with a basic roof surface

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Fig. 16 Typical roof and façade in the Renhe Village (Source The Authors)

and a round handrail. Considering the seasonal demand, the basic surface of the roof elect short and smooth vegetation. To improve the cooling demand in summer, the handrail can be utilised to support liana vegetation, with disassemble fixed ropes or trellis. Also, liana vegetation can be the first barrier to provide shading, helping for reducing heat absorption. The overhead vegetation species should be seasonal, harvested in July and November, then the ropes or trellis can be removed to empty for paddy depose. Moreover, the rejected material such as lamina can be used as food for breeding animals or biomass generation to achieve maximum energy efficiency. Vegetation Considering that individual residential buildings have no maintenance personnel, daily maintenance will fully rely on occupants/residents. The first selection of overhead vegetation should be edible to stimulate occupants to maintain green roofs voluntarily. In southeast China, liana vegetation such as Cucurbitaceae species is widely cultivated. This species of vegetation has large leaves that can provide excellent solar shading. In addition, the pumpkin belongs to the creeping perennial therophyte. The growing cycle is approximately 4–6 months. Therefore, it can be harvested twice a year. Its growth is slower in winter than in summer, so when residents reap paddy in November and start cultivating pumpkin, it can be harvested before July and during the second harvest of paddy. Considering the weight of the pumpkin at maturity, the basic surface of the green roof needs to select light vegetation. Turf is suitable for this type of green roof. Thus, the short and smooth characteristics allow residents to depose their harvest conveniently. It is widely known that a flat green roof can provide multiple utilisation. Although a smooth and orderly lawn requires more maintenance, the lawn can be a relatively perfect solution in this condition. Therefore, the vegetation types applied on green roof refurbishment are summarised in Table 6.

Applying Multiple Nature-Based Solutions (NBS) … Table 6 Proposed vegetation utilised on green roof design

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Position

Species

Upper plant

Therophyte, Cucurbitaceae Pumpkin/luffa

Surface plant Poaceae

Table 7 Initial building roof structure

Scientific name Cynodon dactylon

Layer

Material

Protection layer

Fine aggregate concrete

Waterproof layer

SBS waterproof roll

Insulating layer

Perlite

30

Screed-coat layer

Cement mortar

20

Structural layer

Reinforced concrete

Total

Thickness (mm) 40 3

180 273

Structure According to building information provided from the survey work and evaluating the local documents, the initial building roof construction is shown in Table 7. Considering the cost factor in the refurbishment plan, all structures cannot be redesigned again. Some required layers such as waterproof, structural, and screedcoat will have to be retained to avoid high cost and construction work. An extensive green roof typically requires eight layers, including, vegetation layer, filter layer, drainage layer, a protection layer, waterproof layer, insulation layer, moisture retention layer, and structural layer. The vegetation layer (substrate) provides living space for plants, and it should be able to retain water for plants growth and release redundant water to the drainage layer simultaneously. The filter layer is installed below the vegetation layer, while the function of this layer is to avoid substrate enter into the drainage layer with the water. Normally, the plastic film should be between 100 and 150 g/m2 to ensure proper drainage is provided for the green roof. Under the filter layer, the drainage layer is another important structure in a green roof. The drainage layer helps the redundant water transport into the drainage system. With adequate drainage design, this layer can promote airflow to reduce the possibility of detrimental anaerobic condition generation, meanwhile providing beneficial bacteria and worms (Weiler 2009). Common materials of the drainage layer include crushed stone aggregates, lightweight aggerates, synthetic and composite products. Due to the large load of stone aggregates and the expensive initial cost of lightweight aggregates, although these two types of drainage layers can provide water storage, they cannot be applied in the village community. Other factors such as moist and humid climatic conditions mean this region has no demand for excess water storage. The green roof protective layer is different from the traditional roof. The protective layer can protect plants’ roots, and it can also avoid damage to the roof due to routine maintenance and construction process. Plastic must be applied for a protective layer

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Table 8 Refurbished roof structure Layer

Material

Vegetation layer (substrate) Soil

Thickness 50.8 mm (2 inches)

Filter layer

Semi-permeable needled polypropylene filter / fabric

Drainage layer

High density polyethylene

50.8 mm (2 inches)

Root barrier

Plastic

/

Insulation layer

Perlite

30 mm

Waterproof layer

SBS waterproof roll

3 mm

Structural layer

Ranforced concrete

180 mm

to enhance protection. The waterproof layer (i.e., root barrier) protects the roots of plants, destroying the initial roof waterproof layer. As the initial roof is asphaltbased, it means the root barrier is extremely important. This is because the plants can rift and destroy the material and utilise asphalt as food (Weiler 2009). In the refurbishment design process for the green roof, root barrier material could also select plastic products. The refurbished structure is summarised in Table 8. Irrigation and Maintenance The extensive green roof has no requirements for irrigation. The selected grass requires extremely low daily maintenance, which can be done with upward vegetation by residents (i.e., by providing water for growth). Maintenance of grass includes inspection of dead and invasive vegetation, as well as regular trimming of plants. For green roof maintenance, the green roof requires a yearly professional inspection, which mainly focuses on leaks and drainage, ensuring the vegetation is not overgrown (ASTM 2006). Upward vegetation requires daily maintenance, which residents can do. Edible vegetation can not only promote the positivity of residents to maintain but also improve energy conservation. Moreover, in paddy harvest time, upward vegetation can be removed and fed to animals. Water Management As the community belongs to high rainfall and extremely humid climate, water management will mainly focus on stormwater management. The storage volume of the green roof can be manually calculated. Results are presented in Sect. 5.

4.3 Vertical Greening System Vertical greening systems contain living walls and green façades. Most living walls utilise potted plants, while the vegetation of the green façade is mostly climbing plants. For this village, potted plants on walls require changing or modifying the external wall structure completely. Thus the cost will be increased. Living walls

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require more maintenance than green façades, and hence, the initial cost is also greater. Accordingly, in the refurbishment design process, the vertical greening system design will select green façades. Vegetation Vegetation on a green façade can be specified into three types, including (1) selfclimbing plants, (2) climbing plants that need support, and (3) hanging plants. Selfclimbing plants use their tendrils to grow upward and can be cultivated on the external wall directly. Climbing plant with support refers to a support system, usually a trellis system. Such type can be installed in front of external walls. Hanging plants can usually be cultivated on top veranda or roof and growing from marginal pots downward. Considering the complexity of maintenance, climbing plants and hanging plants are suggested to be utilised in the refurbishment design. Most buildings in the village are surrounded by farmland, providing a suitable substrate for climbing plants growth. Combing previous green roof design, hanging plants can also grow on the lawn on roof. In order to achieve low maintenance, the species need to select that natural growing height equals the designed growing height. Climbing plants can be discerned into four types, including (1) bonders connection, (2) twiners connection, (3) shoots that grow from crevices, and (4) support climbers. Bonder connection refers to self-adhesive species, which has no requirement of support, growing away from sunlight, such as ivy. Twiner’s connection is the most common species in climbing plants. Their stems usually pursue sunlight through enwinding objects surrounding them, requiring a support system. Shoots that belong to the twiner connection use their specific tendrils to grow with support. Lastly, support climbers have thorns and hooks, which also have a demand for support systems. Following from studies of Hermy et al. (2005), Table 9 shows some suggested plants in different designed growing height. Furthermore, a green façade can exist multiple plants in the same wall. Based on the local climate, the plants need to be heatproof, with humidity resistance and low maintenance. For instance, ‘Clematis’, as a plant species, confirms these conditions. This type of plant is largely distributed in Guangxi Province, growing in rural mountains areas. It is also suitable for the façade, which has less direct sunlight. In addition, this plant species could attract some spiders and injurious insects that need to steer clear of windows. Another plant species to consider is ‘Morning Glory’, which is suitable for planting in façades that directly receive sunlight. This plant species can sustain in extremely hot and humid climatic conditions, largely planted in tropical and subtropical zones. Flowering climbing plants suitable for the hot-humid region are often abundant. For instance, ‘Bougainvillea’, ‘Chinese Wisteria’, etc. Residents can select their desired plants, cultivating two or more plants in green façades. Evergreen plant species, such as ‘Ivy’, could also be selected in green façade design. Unlike the above plants, ivy can grow upward to downward, which is appropriate for the roots in the top roof green façade. Ivy can be cultivated in multiple growth conditions and can grow with direct sunlight. It also can adapt to indoor conditions, with fewer requirements on the substrate. Therefore, it is suitable for extremely warm and humid

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Table 9 Suggested climbing plants in 5, 15 and 30 m Height

Species

Types

Up to 30 m

Common ivy (Hedera helix)

Self-bonders

8–25 m

American trumpet creeper

Three leaved creeper (Parthenocissus) Old man’s beard (Clematis vitalba) Staff vine (Celastrus orbiculatus) Russian vine (Fallopia baldschuanica) Chinese Wisteria (Wisteria sinensis) 5–15 m

Kiwi (Actinidia chinensis)

Self-bonders and with support

Birthworts (Aristolochia) Wild hop (Clematis virginiana) Honeysuckle (Lonicera) Five leaved creeper (Parthenocissus family) Japanese wisteria (Wisteria floribunda) Up to 5 m

Old man’s beard hybrides (Clematis vitalba)

Small climbers

Japanese spindle (Euonymus) Black Bryony (Dioscorea communis) Climbing rose

regions, like the case study research area. Ivy is also the most common plant species in vertical greening systems, benefitting from low-maintenance demand. Therefore, it can provide a significant impact on residential buildings, especially if to be considered for vertical greening. Support For the finalisation of the work, all selected plant species in green façade design require support. As mentioned previously, the selected support for the green façade will be selected in a way to have minimised structural support. Climbing plants can grow with trellis support, and hanging plants has no demand for support. An air gap between buildings and trellis system will be confirmed as 50 mm for each façade.

4.4 Green Street It is recorded that the selected case study community was refurbished in 2006. Based on the government regulations, the built environment of the community is not changed in recent years. Due to narrow roads in the area, and because of cropland’s existence, there is no possibility of extending roads. In other words, there will be no space for trees of green street solution application. Although trees can be planted between

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buildings or in front of buildings, it seems that the advantages of applying ‘Green Street only include biodiversity, water management, air quality improvement, and insulation. That leads to green street solutions in this community, which remains at micro-level advantages. Nonetheless, this can mostly be provided by a green façade solution, solar shading, and cooling from a vertical greening system. Such methods are expected to be sufficient to satisfy the residents’ requirements. In this regard, it seems that green street is not necessary for this refurbishment proposal plan. From the earlier analysis, we verified that the cost factor is the first consideration in refurbishment. Trees are different from plants in roof and façade, and the biodiversity improvement can be much greater than other solutions. Also, privacy (e.g., insulation) cannot be provided by the other two solutions. However, according to the survey results summarised earlier, these two factors are given less priority for the refurbishment design plan. The idea of green street integration could potentially increase the initial cost for the refurbishment plan, which also requires additional professional maintenance conditions. Therefore, it is not considered as part of the overall redevelopment proposal plan.

4.5 Energy Balance and Ideal Maximum Utilisation The selected case study is highly developed around heavy agricultural industries. Thus, we see an opportunity that the energy balance could mainly focus on the agroecological cycle. The agro-ecological cycle aims to improve the efficiency of agricultural resources to achieve energy conservation and emission reduction, promoting the sustainable development of modern agriculture. With nature-based strategies or solutions in the building design process, the plants can be combined with agricultural production. Thus, this approach could apply to multiple cycling structures, which can be attained as an ideal energy recycling process. Two examples of ‘water-cycling system’ and biological cycling’ are summarised here. Water-cycling system After applying the green roof strategy, rainwater can be reserved more sustainably. When simplified depose of water can occur, it can be used in some routine that does not demand high-quality water, such as cleaning, flushing, and washing toilets. Unlike rainwater, the local spring water is drinkable directly after boiling. According to the survey results from the local residents, the spring water that each building can receive is enough for washing, drinking, shower, and other domestic use. In addition, rainwater can provide moisture for green systems. Biological cycling Considering the selected community is located in the mountains, and wind power has already been utilised (i.e., wind generation station on the top of mountains—see Fig. 13), the most suitable clean energy that can be identified as secondary recycling is biomass energy. Using micro-organism treatment for domestic waste and agriculture

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waste, such as excrement from human beings and breeding animals, straw, could help to transfer the solid–liquid mixture into marsh gases and desilting. Marsh gases can be burned and used for power generation, providing electricity to nearby buildings. Desilting includes a solid substrate (i.e., grit, glass, and stone) and can be recycled as construction materials. In this regard, biogas slurry can be recycled as manure for agriculture.

5 Summary of Results: Nature-Based Solutions Integration at Micro-level As the community contains many buildings, we pick on one case study sample to present the specification of green systems. This is done at the micro-level using one building as a model. The results of the new model are shown in comparison to the original building example (Fig. 17), and as proposed (Fig. 18).

5.1 Green Roof Proposal Based on the original building model, we verify that the building has three verandas and balconies that are used differently. As mentioned before, the balcony on the building’s third floor is proposed to be used as a paddy disposal area. The balcony on the second floor cannot have a green roof solution. This is because, compared to

Fig. 17 The original building model from the community (Source The Authors)

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Fig. 18 The proposed refurbishment plan for the building model with the proposed green systems’ integration (Source The Authors)

other roofs, the area of this roof is minimal and insufficient for green roof design. Thus, this roof will be mainly used for daily routines, such as drying clothes. As seen in Fig. 17, the roof on the second floor includes a frame with vegetation on the other side. The roots of climbing plants will be cultivated in the topside roof (i.e., lawn), providing solar shading that could also increase aesthetics qualities. Considering the structural load, the veranda on the first floor will not be planted with more vegetation to ensure no impacts on the building’s structure. Details of the proposed green roof design of each level are shown in Figs. 19, 20, and 21.

5.2 Vertical Greening System Proposal Based on the orbit of sunlight, green façade solutions will be mainly applied in the north and south façades of the selected building model. As there is a small open space next to the west façade, it means there will be no substrate for vegetation growth in that location. Thus, the west façade will not include any vegetation plantation. Among other façades, the south façade will receive more direct sunlight. Therefore, in order to achieve the best solar shading and cooling, the south façade will have more plants than other façades (Fig. 22). Furthermore, there are two dominant types of plants in this façade. The plants will be cultivated for substrate in-ground based on panel trellis systems, which refers to dextral green façade and ground floor plants. In the above space, those hanging plants that substrate in the roof of the second and third floor can grow along with vertical façade and shelves. Figure 22 provides the details of this proposed design

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Fig. 19 Green roof on the first floor (Source The Authors)

Fig. 20 Green roof on the second floor (Source The Authors)

plan. Figures 23 and 24 show the vertical greening system applied to the north and east façades of the model building, respectively. They also indicate the differences in vertical greening strategies used to different façades of the building. In addition, Table 10 shows proposed plants of each façade of this case study building.

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Fig. 21 Green roof on the third floor (Source The Authors)

Fig. 22 Proposed Vertical Greening System applied to the south façade of the selected building model (Source The Authors)

5.3 Energy Cycling Frame As Fig. 25 shows, the water cycle starts from rainwater. As nature provides water for buildings and agriculture, vegetation in buildings (through a sort of NBS) and agriculture (for crops) will release moisture to the environment. The extra water from the building can provide a better service to agriculture for irrigation. As mentioned

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Fig. 23 Vertical Greening System applied to the north façade (Source The Authors)

Fig. 24 Vertical Greening System applied to the east façade (Source The Authors) Table 10 Plants in each façade of case study building Orientation

Species

GWR (%)

Notes

North

Morning glory

34

Less direct sunlight, with substrate

East

Chinese wisteria

11

Barely receive sunlight, with substrate

West

n/a

0

South

Ivy

77

Clematis

No substrate, less direct sunlight Receive maximum sunlight

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Fig. 25 Energy cycling frame. Note Blue text refer to water cycling, and red text refer to biological cycling

previously, in harvest time, the waste from green roof vegetation can be recycling. This could also be used for food for livestock breeding and manure. Domestic waste and agriculture waste can be collected into a biogas digester (separately), then the released biogas can provide power for buildings. Afterward, biogas slurry can be recycled for manure to service agriculture. Lastly, precipitation can extract solid substrate used as construction materials.

5.4 Energy Savings The initial parameters for the selected case study (at the micro-level) are summarised in Table 11, representing the energy-saving factors that should be considered in the refurbishment process. Table 11 Initial building parameters

Value Height

Total: 11 m, 3 m for each floor

Width

10 m

Length

10 m

Air change rate

1.5 per hour

k-value of external wall

2.85 W/m2 K, concrete hollow block, 190 mm

k-value of roof

1.8 W/ m2 K

WWR (window to wall ratio) 0.3 for east, 0 for south, 0.3 for west, 0.3 for north

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5.5 Water Storage by Green Roof According to the following equation (Washington DC Regulation 2020), we can verify that for the case study building, the storage volume of this green roof is 5 ft3 . Sv =

S A × [(d × η1 ) + (DL × η2 )] 12

This result is not precise due to the equation is used for the context of the United States. However, it still can be used as a reference to show the green roof can store rainwater that can be used for green systems growth and routine water for residents. In the followings, we summarise results for (1) thermal performance of green systems, (2) green roof improvement, (3) green façade improvement, and (4) biogas energy estimation. (1)

Thermal performance of green systems

The model’s findings cannot provide exact numerical results for the building’s energy performance, mainly because the green systems are dynamic systems. The exact Uvalue of green systems is variable every day, but some estimates could be conducted for detailed analysis. However, the thermal performance of green systems can be estimated. Using software or calculation model, the approximately annual consumption can be determined. This is not the scope of the study, but it could be considered for future research or studies that would like to look into other benefits of green system integrations at the micro level. (2)

Green roof improvement

In this design proposal, particularly for green roof consumption estimation, we use the green roof calculation model developed by David Sailor (2016). This calculation model is a part of the standards of the EnergyPlus model. The input data is summarised in Table 12. The results (see Figs. 26 and 27) show that the annual savings for electric and Table 12 Input data for calculating energy consumption by green roof

Value Leaf area index (LAI)

4.87

Total roof area

100 m2

Green roof area

90%

Rest roof

Dark (0.15albedo)

Growing media

300 mm

Building type

Old residence

Electricity price (kWh)

6 cents

Gas price (kWh)

43 cents

No irrigation

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Fig. 26 Annual energy saving for case study building

Fig. 27 Annual energy balance for case study building

gas of the case study building are 809.5 kWh and 670.5 kWh, respectively. Also, the total building electricity consumption is 45,328 kWh; and of that figure, the green roof occupies 18,467 kWh consumption. Thus, the estimated annual energy savings by green roof strategy is calculated at 1,480 kWh. (3)

Green façade improvement

Unlike green roofs, green façade has no model to estimate the thermal performance. Due to the fact that vegetation or plantation applied in green façades vary significantly, we can confirm that such green façade types are complicated for further evaluation. However, we can still use the results for K-value improvement with an improvement of 50 mm air interspace between external walls, which is verified by studies of Krusche et al. (1982) . In this regard, for the outer wall with vegetation, we can have a K-value improvement of up to 33% (e.g., the estimated range is from 10–33% based on studies of Krusche et al. 1982).

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Fig. 28 Exponentiation model used for estimating K-value improvement for the case study building model

The case study building’s K-value for the external wall is calculated at 2.85 W/m2 K. In order to obtain the improvement at 2.85 W/m2 K without vegetation, a mathematical model will be utilised based on the available data developed by Krusche et al. (1982). Among them, we have exponent, line, logarithm, polynomial, and exponentiation models. We can then verify that the exponentiation model has the most similar trend line with input data (Fig. 28). The equation of exponentiation line is: K −value impr ovement(%) = 24.386 × 2.850.7527 = 53.64% Thus, the K-value of the green façade should be 1.32 W/m2 K for fully vegetation cover walls. Based on the Green to Wall Ratio (GWR) from earlier analysis work, the initial fabric loss in summer (i.e., months of June, July, and August) is 3,783.1 kWh, and external wall with green façade is 1,811.12 kWh. Based on this calculation, we can estimate that applying a green façade can directly reduce 47.9% of fabric loss. Although we confirm the K-value improvement is just an estimate to demonstrate the model’s improvement, this result shows that the green façade can effectively improve cooling performance during the summer season. (4)

Biogas generation estimation

Finally, we focus on biogas generation estimation that could also utilise NBS integration at the micro- and even meso- levels. The raw material of biogas contains excrement from humans and breeding animals, straw, and residue from crops. Assuming that the annual excrement collection is 330 tones, the annual straw output is 3,600 kg, and residue from crops is 800 kg, we can then estimate how much biogas could be generated for the selected case study model. The results are summarised in Table 13.

Applying Multiple Nature-Based Solutions (NBS) … Table 13 Biogas generation estimation

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Raw material

Output per 1 kg

Total output (m3 )

Biogas generation (kWh)

Excrement

0.06 m3 /kg

19,800

37,026

Straw

0.35 m3 /kg

1260

2356.2

m3 /kg

280

523.6

Residue

0.35

Total Note reference from residents; 1m3

39,905.8 biogas can generate 1.87 kWh

electricity

6 Conclusions After refurbishment, we propose several improvement strategies for the Renhe village, using NBS integration at the micro- and meso- scales. These are summarised in the following five points: • Green roofs for each building, with edible liana vegetation and lawn surface, no irrigation; • Green façades for each building, climbing plants and hanging plants, clematis/morning glory and ivy, no irrigation; • No green street. If there is a possibility, trees can be planted in front of the façades that receive maximum direct sunlight; • Initial hydraulic generation station, and a biogas digester to provide electricity; and • Stormwater can be stored by a green roof system completely. Also, Table 14 summarises the main improvements from three key NBS-based strategies of green roof design, green façade design, and biogas generation. In conclusion, NBS design and integration at micro- and eventually at meso- scales in southeast China need to consider the actual requirements by residents. Such an approach has to be adaptable to such a specific context. This study evaluates this fact and suggests context-specific solutions, depending on climatic and geographical conditions, and what could happen through further design or refurbishment plans. This design proposal plan has three main difficulties, including lack of professional Table 14 Improvements Design strategies

Improvement

Green roof

Maximum utilisation of rain water, storage capacity 5ft3 per building, and estimated annual saving of 1,480 kWh

Green façade

Sharply reduces heat gain in summer. For a GWR 0.3 for the building façade, heat gain in summer can be reduced by 47.9%

Biogas generation

In an ideal condition, biogas annual generation is estimated at 39,905.8 kWh

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maintenance in such contexts, narrow roads, and unexploited roof areas. Without a possibility for extending narrow roads, the idea of a green street solution is not possible. But as a suggestion using NBS-based strategies at micro- and meso- scales, trees can be planted in front of building façades to reduce solar radiation loss. This can, however, be more effective if applied to buildings that receive significant direct sunlight. In order to alter the original roof design, the green roof design could select a short lawn as a surface. Also, seasonal liana vegetation could be used to ease the maintenance and removal of the lawn when and where needed. Considering there will be no professional maintenance, all the selected vegetation plantations must have less demand for maintenance. Thus, upward roof vegetation selected here is edible liana vegetation, which can help to enhance the positivity from residents to regular maintenance. We also verify the study is based on modelling and simulation. Therefore, the energy-saving calculation could not be precise enough. However, it still can prove that NBS has a positive impact on enhancing the buildings’ energy performance. As noted in the results, a new biogas digester can directly improve energy efficiency, which could be a significant NBS-based add-on to the community. In an ideal condition, Renhe village will not demand an extra water supply, and the existing spring water and rainwater would be enough for total water use in the community. Without biogas generation, the whole village is serviced by hydraulic generation, which is not enough. Thus, residents still need electricity from the national network system. Biogas generation can counteract this consumption, and other products from biogas digester can also be recycled. This also helps to consider NBS integration at a larger scale. Integrating clean energy and NBS in such contexts located in southeast China is feasible and adaptable. For NBS integration, the key point of the design is considering residents’ special requirements. In addition, the key point of energy cycling is secondary recycling, which requires multiple utilisation of energy resources to obtain maximum energy efficiency. The findings could help planners and designers to seek more ways of integrating NBS in refurbishment and new design proposals. Acknowledgements We would also like express our sincere thanks to all residents from Renhe village for questionnaires, Ms. Yamei Fan, Mr. Chuan Wei, and Mr. Zhuiyun Dai as providers to afford basic information of Renhe Village. Finally, we pass our special thanks to Arc. Bo Pang and Arc. Qiwen Zheng, from Hualan Design & Consulting Group, for providing information about case study building ‘Ecological Science Education Center’.

References ASTM 2400 (2006) Standard guide for selection, installation, and maintenance of plants for vegetative (Green) roof systems. https://www.astm.org/Standards/E2400.htm. Accessed 10 May 2020 Brachet A, Schiopu N, Clergeau P (2019) Biodiversity impact assessment of building’s roofs based on life cycle assessment methods. Build Environ 158(019):133–144

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Bureau of Water Conservancy and Power report of Guanyang (2001) Local government report, available in Chinese and from the original webpage of. http://enghunan.gov.cn/Government/ Who/ViceGovernor/201801/t20180104_4918922.Html Cheshmehzangi A, Griffiths CJ (2014) Development of green infrastructure for the city: a holistic vision towards sustainable urbanism. Architect Environ 2(2):13–20 Darlington A, Chan M, Malloch D, Pilger C, Dixon MA (2000) The biofiltration of indoor air: implications for air quality. Indoor Air 10:39–46. https://doi.org/10.1034/j.1600-0668.2000.010 001039.x FLL Green Roof Guidelines (2018) Guidelines for the planning, construction and maintenance of green roofs. https://commons.bcit.ca/greenroof/files/2019/01/FLL_greenroofguidelines_2018. pdf. Accessed 1 May 2020 Growing Green Guide (2014) A guide to green roofs, walls and facades in Melbourne and Victoria, Australia. ISBN 978-1-74326-715-8 Hermy M, Schauvliege M, Tijskens G, Groenbehndeer A (2005) een verhaal met toekomst; Velt i.s.m. afdeling Bos & Groen, Berchem Historical Weather Data (n.d.) https://tianqi.911cha.com/. Accessed 4 March 2020 Imran HM, Kala J, Ng AWM, Muthukumaran S (2018) Effectiveness of green and cool roofs in mitigating urban heat island effects during a heatwave event in the city of Melbourne in southeast Australia. J Clean Prod 197(1):393–405. ISSN 0959-6526. https://doi.org/10.1016/j.jclepro.2018. 06.179 Khoo Teck Puat Hospital in Singapore (n.d.) https://www.ktph.com.sg/main/home. Accessed 1 June 2020 Krusche P, Althaus MD, Gabriel I, Ökologisches B (1982) Herausgegeben vom Umweltbundesamt. Bauverlag GmbH, Wiesbaden & Berlin Li L, Collins AM, Cheshmehzangi A, Chan F (2020) Identifying enablers and barriers to the implementation of the Green Infrastructure for urban flood management: a comparative analysis of the UK and China. Urban Forest Urban Green 54:126770. https://doi.org/10.1016/j.ufug.2020. 126770 Li L, Cheshmehzangi A, Chan F, Ives CD (2021) Mapping the research landscape of nature-based solutions in urbanism. Sustainability 13(3876):1–41. https://doi.org/10.3390/su13073876 Load Code for the Design of Building Structure (2006) GB50009-2001, 2006. http://www.morgain. com/Help/GB50009-2001/LoadCodeForTheDesignOfBuildingStructures.htm Mittermeier CG, Mittermeier R, Totten M, Ledwith Pennypacker L et al (eds) (2008) A climate for life: meeting the global challenge. Arlington, VA: International League of Conservation Photographers, CEMEX Conservation Book Series, 359 pp Pérez G, Coma J, Cabeza LF (2018a) Chapter 3.1—vertical greening systems to enhance the thermal performance of buildings and outdoor comfort. In: Pérez G, Perini K (eds) Nature based strategies for urban and building sustainability. Butterworth-Heinemann, pp 99–108. ISBN 9780128121504. https://doi.org/10.1016/B978-0-12-812150-4.00009-4 Pérez G, Coma J, Cabeza LF (2018b) Chapter 3.7—vertical greening systems for acoustic insulation and noise reduction. In: Pérez G, Perini K (eds) Nature based strategies for uran and building sustainability. Butterworth-Heinemann, pp 157–165. ISBN 9780128121504. https://doi.org/10. 1016/B978-0-12-812150-4.00015-X Perini K, Chokhachian A, Auer T (2018) Chapter 3.3—green streets to enhance outdoor comfort. In: Pérez G, Perini K (eds) Nature based strategies for urban and building sustainability. ButterworthHeinemann, pp 119–129. ISBN 9780128121504. https://doi.org/10.1016/B978-0-12-812150-4. 00011-2 Sailor D (2016) Green roof energy savings calculation model. https://greenroofs.org/green-roofenergy-calculator. Accessed 29 May 2020 Sun J, Cheshmehzangi A, Wang S (2020) Green Infrastructure practice and a sustainability key performance indicators framework for neighbourhood-level construction of sponge city programme. J Environ Prot 11(2):82–109

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Van Renterghem T (2018) Chapter 3.8—green roofs for acoustic insulation and noise reduction. In: Pérez G, Perini K (eds) Nature based strategies for urban and building sustainability. ButterworthHeinemann, pp. 167–179 Wang Z, Lei T, Yan X, Chen G, Xin X, Yang M, Guan Q, He X, Gupta AK (2019) Common characteristics of feedstock stage in life cycle assessments of agricultural residue-based biofuels. Fuel 253:1256–1263. ISSN 0016-2361. https://doi.org/10.1016/j.fuel.2019.05.105 Washington DC Regulation (2020) Section 3.2 green roofs. https://doee.dc.gov/service/green-bui ldings. Accessed 24 May 2020 Weiler S, Scholz-Barth K (2009) Green roof systems: a guide to the planning, design, and construction of landscapes over structure. Wiley Press, New York, NY

Nature-Based Solutions for Transforming Sustainable Urban Development in China Linjun Xie

Abstract Urban sustainability transitions imply the co-evolution of the integrated social, ecological, and technical systems and can be driven by innovations initiated by different urban actors, both public and private. Drawing insights from sustainability transitions and urban governance literature, this chapter explores the potentials of nature-based solutions in transforming urban sustainable development in China, which has been characterized by a state-dominated top-down steering mechanism and a technocratic planning and development pattern. Currently, state-led and modernisation-guided urban sustainability programs and their pilot projects dominate both public and academic discourses on the efforts and promises for a sustainable urban future in China. This chapter argues that with few actual changes in the governance system that largely excludes the civil society and private sector organisations in decision-making and practices, these efforts often fail their promises in advancing transformational changes in urban China. The rush to build ‘eco’, ‘lowcarbon, ‘smart’, or ‘green’ cities even generated unintended and negative outcomes on local ecology and community. The rising concept of nature-based solutions encompasses multi-actor dynamics, various forms of interventions, and multiple benefits for people and nature. Its inclusiveness and multi-functionality could draw wider attention and support for non-state-led innovations across Chinese cities, and thus, open up a great opportunity for promoting urban sustainability transitions in China. Keywords Urban sustainability transitions · Nature-based solutions · Sustainable urban development · Nature · Urban governance · Top-down

1 Introduction China’s large-scale urbanisation started around the 1980s with a dramatic rise in the urban population from 17.92% in 1978 to 60.6% in 2020 (National Bureau of Statistics of China 2020). The swelling urban population and the continuous rapid L. Xie (B) Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_17

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urbanisation process stimulate swift economic growth while also bringing enormous challenges. Pollution, environmental degradation, and the shortage of water and other resources have drawn wider attention since the late 1990s. Along with the environmental problems is the widening gap between the urban and rural, the rich and the poor. Sustainable urban development has been promoted in China since the turn of the century, seeking to tackle these challenges. In the past two decades, there has been a proliferation of sustainability-oriented urban policies and programmes instigated at different levels of governments and implemented across the country, including but not limited to ‘eco-city, ‘low-carbon city’, ‘forest city’, ‘smart city’, and ‘sponge city’. As of 2020, there are 11 pilot ‘waste-free cities (MEE 2019), 19 national eco-garden cities, 30 pilot sponge cities, 58 pilot cities implementing the ecological restoration and city betterment (or ‘Urban Double Repairment’) programme, 81 pilot national low-carbon cities, and 441 cities that have conducted national forest city construction1 in China. The rolling out of these various initiatives (and many other local projects) demonstrates the country’s ambition to build ‘ecological civilization’ and to advance a transition toward sustainable urban development. There is a great deal of research exploring those sustainable urban programmes and their piloting projects in China. Some interpret the diverse concepts leading various programmes, such as ‘eco-city’, ‘smart city’, or ‘sponge city’ (e.g., Yu 2014; Liu et al. 2017a); some trace the design and implementation of a specific project such as the renown Sino-Singapore Tianjin Eco-City (SSTEC) and Chongming Eco-Island (e.g., Joss and Molella 2013; Caprotti et al. 2015; Flynn et al. 2016, 2020; Dai et al. 2018); some map the diverse actors involved (e.g., Cheshmehzangi et al. 2018); while some evaluate the performance and effects of these programmes/projects (e.g., Li et al. 2017; Xie et al. 2019a, b). However, despite a large body of research, few have systematically examined this plethora of initiatives in terms of their effects in transforming urban development and governance. Have these programmes and projects promoted sustainability transitions of Chinese cities? What are the main challenges and problems of current attempts and efforts? And what are the opportunities for overcoming existing barriers and advancing transformative actions? Addressing these questions is imperative as cities in China still confront with severe environmental and social problems, while global climate change and biodiversity loss show no signs of abating. In recent years, China increasingly plays a leading role in global environmental governance: it is the host the host country of the fifteenth meeting of the Conference of the Parties (COP 15) to the Convention on Biological Diversity (CBD); the green Belt and Road Initiative2 is deemed to be a catalyst for low-carbon development in the region; in 2020, China also pledges to hit CO2 emissions peak before 2030 and to achieve carbon neutrality by 2060. Considering the significant roles of cities in 1

Bulletin on China’s Land Greening in 2020. Available online: http://www.forestry.gov.cn/main/ 393/20210312/175043478886085.html (accessed on 12 June 2021). 2 State Council Information Office of the People’s Republic of China (23 June 2016) President Xi calls for building ‘green, healthy, intelligent and peaceful’ Silk Road [Online] http://www.scio.gov. cn/32618/Document/1481477/1481477.htm.

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global climate, biodiversity and sustainability governance (Bulkeley 2021), whether or not China can achieve sustainability transition in its urban development and governance matters not only to the successful fulfillment of its commitments in building ‘ecological civilization’ and ‘harmonious society’, but also to the achievement of the climate and biodiversity agenda and the overall global sustainable development goals (SDGs). This chapter aims to critically evaluate China’s sustainable urban development by examining the multiplicity of programmes initiated and implemented in the past two decades. Drawing on existing studies and the literature on sustainability transitions and urban governance, this chapter examines the key governance features and the main development patterns of China’s movement towards urban sustainability, as well as its current challenges and limitations. We argue that China’s contemporary exploration of sustainable urban development has largely followed modernisation thinking (Scott 2008) and adopted a state-led and planning-guided governance and development pattern with a near-absence of social mobilisation and public participation. The majority of existing academic research also tends to focus on large-scale projects developed by different levels of governments, with limited attention paid to the grassroots experimentations emerging across communities and cities. To promote urban sustainability transitions in China thus requires transforming the incumbent systems that shape the discourse and practices of urban developments. More recently, nature-based solutions are gaining traction in both political and public realms for their great potential in simultaneously addressing multiple sustainability challenges. This inclusive concept that encompasses multi-actor governance and social, ecological, and technical innovations, as we argue below, could provide significant opportunities for advancing sustainability transitions in China. The remainder of this chapter is structured as follows: Sect. 2 briefly reviews the literature of sustainability transitions and urban governance, which provides a theoretical basis for examining the past and ongoing urban sustainable development in China. Section 3 provides an overview of the urban sustainability movement in China by exploring the key policies and the main programmes implemented in the past two decades before critically examining their developments, practices, and effects. Section 4 then delineates the concept of nature-based solutions and discusses their potentials in transforming China’s urban sustainable development and governance. Section 5 explores how to unlock the potential of nature-based solutions in urban China, and Sect. 6 concludes the chapter by discussing the key areas for future research on promoting nature-based solutions and urban sustainability transitions in China.

2 Sustainability Transitions and the Governance of Urban Systems As main sources of both environmental problems and opportunities, cities and urban regions play a key role in the global sustainability transitions (Bulkeley et al. 2011;

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Frantzeskaki et al. 2017; Fuenfschilling et al. 2019). A sustainability transition is defined as a ‘radical transformation towards a sustainable society, as a response to a number of persistent problems confronting contemporary modern societies’ (Grin et al. 2010: 1). One typical example is the energy transition, through which societies are shifting from fossil fuels toward renewable energy systems. In particular, urban sustainability transitions refer to “fundamental and structural changes in urban systems through which persistent societal challenges are addressed”, such as shifts towards urban farming, renewable decentralized energy systems, and social economies (Frantzeskaki et al. 2017, p. 1). Understanding the dynamics of urban sustainability transitions needs to account for the urban systems as well as how systemic changes can occur. Cities and urbanized regions are typically complex systems (Batty 2008; Bettencourt 2013), consisting of dynamically interacting social, ecological, economic, and technological infrastructures, which feedback on one another, supporting the internal workings of a city and exhibit resiliency that is not necessarily sustainable (Pickett et al. 2013; McPhearson et al. 2015). These and other interconnected and often unpredictable dynamics make urban systems challenging to understand and to govern, especially when seeking to transform toward more sustainable and equitable development patterns (McPhearson et al. 2016). Given the complexity of cities, McPhearson et al. (2016) propose an approach to explore and advance urban sustainability transitions, arguing that cities are best understood as complex socialecological-technical systems (SETS) people, ecological processes, as well as built environments, are inextricably linked. The SETS approach bridges the historically divided social-technical and socio-ecological approaches in sustainability transitions studies and is well-positioned to cut across sectors and domains to study how social, biophysical, and technical patterns and dynamics affect urban sustainability and resilience (McPhearson and Wijsman 2017). The initial focus of sustainability transitions research was on analyzing transitions in socio-technical systems. Rooted in science and technology studies, the socio-technical approach emphasizes technology and society’s co-evolution (Geels 2005: 363). A socio-technical transition is a combination of processes leading to a fundamental shift of socio-technical systems (Geels and Schot 2007), which involves technological, organisational, institutional, political, and socio-cultural changes (Markard et al. 2015). A key analytical lens for socio-technical transitions is multilevel perspectives (MLP). In the MLP framework, shifts in technological regimes and related social practices are the result of the interplay between external landscape forces and emerging experimental ‘niches’ (Geels 2005, 2010; Caprotti, 2015). Here, regimes represent the current structure and practices featured by dominant rules, institutions, cultural/social norms, and technologies that are self-reinforcing and stable (Geels 2010), while niches are considered as protected spaces necessary for innovations to mature vis-à-vis incumbent socio-technical regimes (Schot and Geels 2008). The MLP model elaborates the interaction among the regime, niche, and landscape levels, and implies that sustainability transitions occur through the emergence, alignment, and scaling up of socio-technical innovations (Grin et al. 2010). Such innovations, in the urban context, include, for example, bike-sharing (van Waes et al.

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2018), low-carbon experiments (den Hartog et al. 2018), and smart city visions that are based on information and telecommunications technologies (Carvalho 2014). Comparing to the technology-focused socio-technical transitions studies, the socio-ecology system perspective of sustainability transitions focuses on complex and integrated systems that emerge through the continuous interactions of human societies with ecosystems (Redman et al. 2004; Haberl et al. 2006). Building on insights from ecology, biology, complex adaptive systems theory, ecosystem services, and adaptive governance (Loorbach et al. 2017), this approach regards socio-ecological interactions as a dynamic process in which self-organized subsystems interact (Ostrom 2009). Human societies evolve as distinct patterns of society-biosphere interactions are established (Krausmann et al. 2008; Schandl et al. 2009), which can be resulted from technological changes, economic and demographic developments, political revolutions, and resource scarcity, etc. (Haberl et al. 2006; Krausmann and Fischer-Kowalski 2013). Comparing to social-technical regimes, SES are place-bound, rooted in a particular spatial context such as a watershed, rangeland, a forest, or a region, although also comprising multiple interacting scales and levels (Smith and Stirling 2010). Cities represent typical integrated social-ecological systems, whose transition is associated with interactions between bio-geo-physical components and governance. The exploration of sustainability transitions, from an SES perspective, need to be based on the understanding of socio-ecological changes. The socio-technical regimes and the socio-ecological systems differ in a number of respects, while they are interacted on each other (see detailed discussion in Smith and Stirling 2010). They also share many common characteristics and elements, including the multi-actor dynamics, problem framing and visioning involved in driving transitions, as well as the importance of experimenting, evaluating and learning for achieving transitions (Loorbach et al. 2017). Among them, a key underlying conceptual foundation of both perspectives is that the reconfigurations of either sociotechnical systems or social-ecological systems do not happen autonomously and require the activities of human actors. Scholars have also emphasized that transitions involve multiple actors from diverse backgrounds (e.g., market, government, science, civil society) and that the shifting power relations and role constellations between various actors is inherent to any transition process (Avelino and Wittmayer 2016; Loorbach et al. 2017; Grin et al. 2010). Urban sustainability transitions are no exception. A key mode of governance for urban sustainability transitions is experimentation (Fuenfschilling et al. 2019), which can be undertaken by different actors for trialing new ways of organizing, doing, and relating, and further generate alternative forms of innovative solutions that can potentially address contemporary urban challenges (Bulkeley and Castán Broto 2013; Frantzeskaki et al. 2018). Arguably, the multiplicity of experimentations undertaken by various actors with different interests and diverse capacities and power can yield innovative ideas, practices, expectations, technologies, and new social relations, which can further be developed and aligned into a new, potentially more sustainable configuration (Pereira et al. 2018). These purposeful interventions, including people’s everyday actions to broad-sweeping government initiatives, are the catalysts and impetus for urban sustainability transitions.

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The more recent approach—SETS—is set to unite the socio-technical and socioecological approaches, providing a holistic framework to understand the dynamic interactions between social, ecological, and technical-infrastructural domains of the complex urban systems (McPhearson et al. 2016). As argued by Depietri and McPhearson (2017: 94), it can overcome ‘the limitation of a purely sociotechnological approach which tends to exclude ecological functions, or of a socialecological approach inclined to overlook critical roles of technology and infrastructure as fundamental constituents, and drivers of urban system dynamics’. The SETS approach is thus well positioned to explore the existing efforts of urban sustainability transitions in China and the current and potential roles of various urban actors in driving transitions. In recent years, the concept of nature-based solutions has drawn growing attention. Defined as “actions to protect, sustainably manage, and restore natural or modified ecosystems that address societal challenges effectively and adaptively, simultaneously providing human well-being and biodiversity benefits” (Cohen-Shacham et al. 2016, p. 4). Moreover, nature-based solutions are regarded as a cost-effective means through which multiple sustainability challenges in cities can be addressed simultaneously while bringing more comprehensive benefits to the urban communities and environment (Nesshöver et al. 2017; Xie and Bulkeley 2020). Nature-based solutions represent socio-ecological-technical innovations for urban sustainability transitions (van der Jagt et al. 2020a): they are either social, ecological, technological, or systemic (comprising social and ecological, social and technical, or social, ecological, and technical innovation) in nature. Social innovations include changes in social arrangements such as policies, governance, financing, or cultural framing (e.g., new modes of collaborations, innovative business models). Ecological innovations are the creation of new natural spaces or the restoration of existing ecosystems, which can be conducted in a novel way or used in known methods but can be innovative due to being applied in a new context. Technological innovations are new or significantly altered products, production processes, or technological infrastructures (e.g., a green bus stop that serves as an element of urban storm infrastructure or a low-maintenance green roof that requires minimum irrigation and care) (Dorst et al. 2018). Finally, systemic innovation can occur in interventions that create a systemic change and enable social, ecological, and technical innovations and interactions between them. Like other ‘green niche’ (Smith 2007) or urban sustainability experiments (Bai et al. 2010), the development of nature-based solutions can potentially break the path dependence and address lock-in, challenging the incumbent social-ecological-technical systems and driving transition processes, whether and how nature-based solutions can transform urban governance in China to facilitate and drive sustainability transitions is thus also worth pursuing. In summary, transitions occur when the dominant ways of thinking (cultures), doing (practices), and organizing (structures) are changed, and new configurations and dynamics of urban systems are developed (Augenstein et al. 2020). These processes are co-evolutionary, involving social, ecological, and technical changes, and can be driven by experimentation initiated and undertaken by a multiplicity of actors (Frantzeskaki et al. 2017). As China is known to practice an authoritarian

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governance system where the state actors play dominant (and sometimes exclusive) roles in urban and environmental governance, how sustainability transitions are pursued in urban China, what are the effects of existing attempts and efforts, and what are the challenges and opportunities for transforming urban governance towards sustainable development, are worth pursuing.

3 Sustainable Urban Development in China: Features and Dilemmas 3.1 An Overview of Sustainable Urban Development in China Urban planning and governance, as well as environmental regulation and management, have long been practicing a top-down mechanism in China. The state’s dominance is also prominent in exploring urban sustainable development (de Jong et al. 2016). Since the turn of the century, the Chinese government has been paying increasing attention to the quality of growth, stressing the construction of a “resourceconserving and environmentally friendly society”3 and “ecological civilization”4 as key building blocks of social and economic development. Accordingly, ambitious national targets on, for example, improving energy use efficiency, conserving arable land area, and reducing carbon emission, have been gradually set.5 Simultaneously, the country established an accountability system, assigning responsibilities for implementing and achieving these national targets to local governments by integrating environmental targets into local cadres’ performance appraisal system (World Bank 2009). The paradigm shift of China’s policy framework towards a more ecologically sensible development pattern has profound implications on urban planning and development. In 2014, the New-Type Urbanisation Plan (NUP) was launched to steer the country’s urbanisation onto a human-centered and environmentally friendly path (Xinhua News Agency 2014). Prior to that, the national government has already started exploring ecological urban development by setting up standards and promoting a wide variety of sustainability-themed programmes (see Table 1).

3

This concept was put forward by Hu Jintao, then General Secretary of the Central Committee of the Communist Party of China (CPC), during the fifth plenary session of 16th Central Committee of the Communist Party of China (CPC) in October 2005. 4 This concept was first put forward by Hu Jintao at the 17th National Congress of the CPC in 2007. 5 For example, the 11th Five-Year (2006–2010) Plan for National Economic and Social Development stipulates a 20% reduction in energy use per unit GDP between 2005 to 2010, and doubling per capita GDP between 2000 and 2010. In 2008, China’s State Council announced the National Land Use Master Plan (2006–2020), which sets stringent ‘red lines’ for protection of arable land: a minimum of 121.2 million and 120.3 million hectares by 2010 and 2020, respectively.

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Table 1 Timeline for China’s key policies and programmes for sustainable urban development Year Key policies (in bold type) and main programmes (with a bullet point) for China’s sustainable urban development, as well as some representative city projects (with a leading short dash) 2003 The Scientific Outlook on Development (kexue fazhan guan) was proposed by the 16th Central Committee of the Communist Party of China (CPC) • MEP initiated a program to establish eco-counties, eco-cities and eco-regions by issuing the ‘Indices for National Ecological County, Municipality and Province (trial)’6 2004 • MoHURD launched the Eco-Garden City Program • State Forestry Bureau (SFA) launched the National Forest City construction program 2005 The concept of building a ‘resource-conserving and environmentally friendly society’ was put forward during the fifth plenary session of 16th Central Committee of the CPC – Dongtan Eco-city was jointly launched by the Shanghai Industrial Investment Corporation (SIIC) and Arup—a British engineering consultancy firm 2007 “Ecological Civilization” was first introduced at the Chinese Communist Party’s 17th National Congress of the CPC • SFA formulated ‘National Forest City Evaluation Index’ 2008 China’s State Council announced the National Land Use Master Plan (2006–2020), which sets stringent ‘red lines’ for protection of arable land – The Sino-Singapore Tianjin Eco-city (SSTEC) was launched as a flagship government-to-government project between Singapore and China 2009 China’s State Council announced a target of reducing the carbon intensity of its GDP by 40–45% by 2020 compared to the 2005 level; the target was then incorporated into the national 12th Five Year Plan 2010 • NDRC issued the ‘Notice on Carrying Out Pilots of Low-Carbon Provinces and Cities’, calling for dozens of low-carbon city pilots to be launched across the country – Shanghai Municipal Government issued the ‘Chongming Eco-Island Construction Outline (2010–2020)’, announcing the plan to build Chongming into a world-class eco-island 2012 The CPC included the goal of achieving an Ecological Civilization in its constitution and it also featured in the Five-Year Plan 2014 The New-Type Urbanisation Plan was issued, emphasizing the social-environmental sustainability of urban development • The ‘Guideline on Promoting the Construction of Sponge City’ was jointly published by MoHURD, MoF, and MWR; the national government decided to start Sponge City pilot program 2015 • The MoHURD listed Sanya as the first national pilot city of “Double Urban Repairs” and put another 37 on the list in the following years • The first group of 16 cities were chosen as the pilot sponge cities 2016 • The second group of 14 cities were selected for piloting the sponge city program 2017 • MoHURD issued the guiding opinion on promoting Urban Betterment and Ecological Restoration7 2019 • Ministry of Ecology and Environment (MEE) published a list of 11 “Waste-Free Cities” pilot construction sites

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http://www.mee.gov.cn/gkml/zj/wj/200910/t20091022_172195.htm. http://www.scio.gov.cn/32344/32345/39620/40845/xgzc40851/Document/1658288/1658288. htm.

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In 2003, to promote Scientific Development, China’s Ministry of Environmental Protection (MEP) initiated a program to establish eco-counties, eco-cities and ecoregions (MEP 2003).8 This heralded a movement of constructing sustainabilitythemed urban projects across the country. For example, in 2004, the Ministry of Housing and Urban–Rural Development (MoHURD), responsible for urban physical development, proposed the ‘National Standards for Eco-Garden City’, promoting the development of eco-garden cities in China. In 2007, the State Forestry Administration (SFA) issued appraisal indicators of ‘National Forest City’, establishing a set of criteria and indicators for standardizing the certification and guiding local construction efforts. Then in 2010, following the announcement of the national carbon reduction 2020 target in 2009, the National Development Reform Commission (NDRC), which is responsible for formulating and implementing national economic and social development strategies, initiated a low carbon pilot province and city program; the first batch pilots include five provinces and eight cities (NDRC 2010). Furthermore, in responding to an increasing incidence of urban flooding or water-logging in Chinese cities, the Sponge City programme was launched at the end of 2014 under the direct guidance and support of three national ministries, including MoHURD, Ministry of Finance (MoF), and Ministry of Water Resources (MWR). In 2015, MoHURD further proposed the concept of “Urban Double Repairs (chengshi shuangxiu)”, which includes two programs of ‘Ecological Restoration (shengtai xiufu)’ and ‘City Betterment (chengshi xiubu)’. Through this plethora of national programs, the central government provides great incentives for local governments to embark on urban developments directed towards sustainability. Gradually, more and more urban ecological/sustainable projects have been initiated and implemented (as shown in the statistics listed at the opening of the chapter). Some have strong national government support, paired with structured foreign involvement (such as SSTEC); some are local initiatives, aiming to either achieve national standards so as to solicit political recognition, or to increase city competitiveness (through experimenting with innovative concepts or cutting-edge technologies, or by entrepreneurial maneuvers); and most of the projects fall somewhere in between—involving multi-level governments to a varying degree (de Jong et al. 2016; Xie et al. 2020a). Despite their different types and scales, these sustainability-themed projects received much critics. For example, Chien (2013) argued that most Chinese eco-cities are land-speculation-oriented new-town developments that were mainly implemented for land revenue and could generate social conflict instead of sustainable development. Green grabbing, displacement, and green gentrification are also reported in many studies on Chinese urban ecological developments (see Caprotti 2014; Caprotti et al. 2015; Xie et al. 2019a). Besides, existing studies also identified a wide range of challenges for implementing these initiatives, covering technical (e.g., lack of practitioner expertise, insufficient performance data), financial (e.g., lack of funding source, high development cost), and social (e.g., lack of public acceptance

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A revised Indices was introduced in 2007 with stricter standards. Available online: https://www. mee.gov.cn/gkml/zj/wj/200910/t20091022_172492.htm (accessed on 2 June 2021).

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and support) aspects (see Li et al. 2017; Yu 2014). To seek solutions for these problems and challenges and to advance urban sustainability transitions need to unearth the fundamental reason(s) behind the contemporary dilemmas.

3.2 Top-Down and Technocratic Governance and Exiting Challenges To evaluate the urban sustainability movement in China and identify the root causes of current dilemmas, we need to first understand how various programmes and associated projects are conducted and managed. A comprehensive review of relevant policies, plans, and strategies, as well as existing academic studies, allows the identification of several key characteristics of China’s sustainable urban development practices, while also reveals how these main features of governance and development result in a serious of problems that impede effective sustainability transitions. First, urban sustainable development in China is largely a state-led process, heavily relying on formal policymaking and planning mechanisms. National programmes (e.g., eco-city, low-carbon city, sponge city) initiated by different ministries in response to the guiding policies coming from the central leadership (e.g., ‘Scientific Outlook on Development’, ‘Ecological Civilization’) are substantiated by local governments (including provincial and municipal governments, as well as urban district governments) through various pilot projects. These pilot projects are designed/planned, and implemented mainly by state actors (e.g., planning bureaus, state-owned development corporations) under the national government’s generic and often abstract guidance. For example, along with the initiation of the Sponge City program, the MoHURD (2014) published the ‘Technical Guide for Sponge City Construction’ to support the implementation of pilot projects. The Technical Guide instructs the design, implementation, maintenance, and management of lowimpact development facilities by specifying the goals, targets, design route, and key standards and criteria for constructing, reconstructing, and expanding sponge city projects (MoHURD 2014). Besides, in 2016 the MoHURD published a catalogue of applicable technology and products for sponge city construction, including aquatic microbial bio-activation technology and stormwater collection and reuse systems and planting bags for green roofs permeable pavements (MoHURD 2016). The catalogue also lists a set of technical consulting companies, including private companies, state-owned companies, and universities, for sponge city project developers (i.e., the municipalities) to consult and collaborate with. Similarly, the implementation of municipal government-initiated ecological projects, such as the Chongming Eco-Island, is also often guided by the rigid plans and regulations promulgated by the municipal and urban district governments and carried out by local cadres and state-owned enterprises (Xie et al. 2019a). The top-down governance mechanisms through plans, guidelines and catalogues naturally from a formal and often standardized procedure and close network of actors for designing and implementing local sustainable and ecological projects. The level

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of civil society’s engagement is understandably low (Joss and Molella 2013; Li et al. 2017; Xie et al. 2019a; Yu 2014), and citizens’ behavior and lifestyle choices are often not considered (Flynn et al. 2016). In the case of SSTEC, research also found that most of the advanced green technologies (e.g., pneumatic waste collection system, household solar heating) implemented across the eco-city lay idle since residents are unwilling to pay for their extra costs (Flynn et al. 2020). Meanwhile, the policies, plans, and strategies made by bureaucrats and professional planners often take no account of the interests and needs of local people, which resulted in the lack of support from local communities and residents and even caused socio-spatial polarisation, social exclusion, and ‘environmental gentrification’ (Romano 2015; Lei et al. 2018; Xie et al. 2019a). Local people’s skills and traditional knowledge in managing the local environment are also undervalued and marginalized (Xie et al. 2019b). In addition, due to the variegated environment and cross-cutting nature of ecological management, policy-makers and urban planners that lack proper education and training (Li et al. 2017), and were heedless of the particularities of the locality, often resort to engineering and one-size-fits-all solutions, causing unintended and even disastrous ecological destructions (Xie et al. 2019b). The second feature, which is closely linked to the hierarchical top-down planning and governance mechanism, is the wide use of indicator systems. Both national and local programmes use indicators assessment criteria to guide local actions and to assess the progress and performance of the on-the-ground practices. For example, the Eco-Garden City Standard proposed by MoHURD consists of 19 quantitative indicators, including seven natural environment indicators, five living environment indicators, and seven infrastructure indicators. Cities must meet the targets represented by these indicators to qualify as eco-garden cities. Similarly, in SSTEC, a set of 26 key performance indicators (KPIs) is formulated, covering areas of environment, society, economy, and regional cooperation, to keep track of the development of the eco-city.9 These indicator systems provide quantitative measurement for the success or otherwise of the implementation of urban sustainable development project, and thus matter to both policy-makers and developers (Xie et al. 2019b; Flynn et al. 2020). For the former, the indicators serve as a key evaluation criterion for their performance and achievements, while for the latter, they point out the foci of development. For example, one key indicator set in the Chongming Eco-Island plan is the forest coverage rate, which is set to increase from 22.53% in 2015 to 30% in 2020 and 35% in 2035 (Shanghai Municipal Government 2016). Understandably, afforestation became a top priority for the Eco-Island construction and a number of strategies, which are not necessarily sustainable or ecological-friendly (such as converting farmlands into forest lands and monoculture afforestation), have been implemented swiftly to achieve the target (Xie et al. 2019b). These ambitious and often short-term goals and targets are found to be problematic and can lead sustainability-oriented urban development projects astray. Based on a survey of 30 pilot sponge cities, Li et al. (2017) pointed out that the standardized goals and targets of the sponge city programme (e.g., retaining 60–90% runoff on sites) 9

http://www.tianjineco-city.com/static/web/mobile/en/singapore2_2.html?lang=english.

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were set without a sound research foundation domestically and locally. Likewise, the Chongming Eco-Island’s target on increasing forest coverage rate was found to be set mainly for political reasons (to meet the target of Shanghai Municipality’s overall forest coverage rate) without much ecological considerations (Xie et al. 2020a). As warned by Mike Hulme (2019), while securing net-zero carbon emissions by a given date becomes the dominant indicator for fighting climate change, many other diverse policies and actions needed for addressing climate challenge would be sidelined. The same happens to many sustainability programmes implemented in Chinese cities, which often adopt a constricted and reductive set of indicators and thus have no holistic understanding of what sustainable urban development involves. Previous studies have shown that in order to achieve the ambitious targets set in the EcoIsland plan, developers and local cadres sprang into actions, employing measures that could produce quick results but nevertheless harm local ecosystems (e.g., using herbicides to clean weeds, canalizing rivers to maintain water flow and quality) (Xie et al. 2019b). The rush to obtain the numerical results lead to the paradox of ecological destruction through ecological construction in contemporary urban China. Third, besides stipulating the design and implementation of ecological development projects, Chinese governments (both national and local) also act as the main financier for the various pilot projects. For example, to support the construction of sponge cities, the national government allocated to each pilot city between 400 and 600 million Chinese Yuan (CNY) each year in the initial three years (MoF 2014). Generally, the national fund equals 15–20% of the total cost of sponge city construction (Peng and Reilly 2021). Although pilot projects are encouraged to raise matching funds through public–private-partnership and other financial ventures (MoF 2014), the remaining cost is largely paid by local governments (Li 2019). The overdependence on government subsidies for financing sponge city program and alike sustainability-oriented urban initiatives, on the one hand, renders these programmes and projects vulnerable to political and policy changes. For example, the change of Shanghai’s political leadership is deemed one of the main reasons that cause the miscarriage of the Dongtan Eco-city project, which was touted as the first purpose-built eco-city in China (Chang and Sheppard 2013). On the other hand, for projects that have particular political significance or have already received a large amount of subsidies from the governments, they become ‘too big to fail’ (Caprotti and Harmer 2017; Zhang and de Jong 2017) and thus require continuous inputs to make them a success, even though that could compromise the sustainability goals and targets (e.g., the development of real estate and car-dependent entertainment industries in SSTEC (Flynn et al. 2020)) or could add on the financial burden of local governments that were already heavily indebted. These pilot projects are also very unlikely to be replicated and upscaled (although they often promised to do so) since their development and success depend almost entirely on political will and governmental support (Zhang and de Jong 2017). Many other urban ecological projects that have less support from the national or local governments at the beginning or those who have lost such support during the development processes are struggling to maintain momentum. Some stall halfway through construction, and some become ‘ghost towns’ upon completion (Sabrie 2014).

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As can be seen, the development of various urban sustainability initiatives in Chinese cities conforms to a modernisation thinking and is largely based on administrative convenience, not ecological considerations. They represent a top-down and technocratic approach and calculative governmental logic to sustainable development and environmental management (Xie et al. 2019a). Actual changes in the governance and practices of urban planning and development appear to be scarce. Technology (e.g., multi-scale permeable pavement systems, pneumatic waste collection system, household solar heating, wind turbines) features centrally in these projects. Yet as Joss and Molella (2013, p. 117) argued in their examination of the Caofeidian Ecocity project, “little explicit attention has been paid… on the normative, conceptual, and practical role played by technology—as socio-technical visions, systems, artifacts—within these new urban innovations”. Whilst these projects were initiated with a common aim to experiment with a harmonious, people-oriented, and ecologically friendly urban place, ironically, their standardized and reductive plan and design language largely devoid of any culture-specific, local narratives (Joss and Molella 2013; Xie et al. 2019b). Furthermore, in the plans, designs, and indicator systems of these programmes, the roles of people—citizens, residents, commuters, visitors—as well as other non-state actors (e.g., ecologists, NGOs, private enterprises) are almost completely absent (Joss and Molella 2013; Yu 2014). Perhaps not surprisingly, existing academic research on China’s urban sustainable development and sustainability transitions have also been largely focused on governmental policies and state-led interventions. Very few studies have explored grassroots experiments in urban China, which are bottom-up and self-governed by the civil society comparing to guided experiments coordinated by governments or firms (Van den Heiligenberg et al. 2018). Meanwhile, many scholars argue that the current issues or the main challenges of China’s urban sustainable development stem from the weak scientific basis underpinned by the concepts and plans and the lack of specialized or detailed plan or guidance from higher-level governments (e.g., Li et al. 2017; Xia et al. 2017). Many suggestions have been proposed, including enhancing guidance and design standards, promoting government leadership and inter-agency cooperation, finding innovative ways to create more funding options, while also taking an integrated approach that is attentive to ecological scales and building knowledge through continuous research (Li et al. 2017; Liu et al. 2017b). These measures are indeed important and could improve the implementation and management of urban sustainability-oriented projects. However, drawing from sustainability transitions and governance by experiments literature, we argue that the issue is less on how clearer visions can be drawn, how more explicit and ambitious targets and indicators can be set, or how the existing governing systems can be better refined. But, much more whether and how the incumbent governance system can be transformed, enabling social-ecological-technical innovations initiated by all kinds of people to emerge and thrive. In the following sections, we explore the potentials of the rising concept of nature-based solutions in transforming sustainable urban development in China and how their potentials can be unleashed.

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4 Transforming Sustainable Urban Development in China: The Potential of Nature-Based Solutions Mitigating and adapting to climate change, protecting biodiversity, and ensuring human well-being are increasingly recognized as defining challenges of the twentyfirst century and require more coordinated and integrated actions (Seddon et al. 2020). Under such context, nature-based solutions are fast-rising, which are regarded as an umbrella term that covers a range of approaches to working with nature (e.g., ecosystem services, nature-based adaptation, green and/or blue infrastructure, natural climate solutions, etc.) to achieve innovative solutions to various sustainability challenges while delivering additional benefits to people and nature (CohenShacham et al. 2016; Nesshöver et al. 2017). Nature-based solutions can operate in diverse urban settings, including external building greens (e.g., green roofs, vertical greening), parks, community gardens, rivers or streams, green indoor areas, green infrastructure, and urban forests on derelict land (Bulkeley and Raven 2017). They are marked by multi-functionality and can effectively engage multiple actors (Kabisch et al. 2016; Raymond et al. 2017). For example, private sectors and local communities that are often either excluded or only taking a consultant role of urban policy-making and planning process can lead to nature-based solutions (e.g., green roofs in office buildings, community gardens) that provide co-benefits for bridging social, cultural, environmental, and economic interests (Xie et al. 2020c). The project-based, experimental form of nature-based solutions represents socio-ecological-technical innovations with significant promise to enable urban sustainability transitions (Raymond et al. 2017). Although being a relatively new concept, nature-based solutions have been advocated widely in policy and academic arenas worldwide, especially in climate change and biodiversity fields (IPCC 2019; IPBES 2019). As a key player in global environmental governance and actions, China has also called for incorporating naturebased solutions in climate policies and in the post-2020 global biodiversity framework. China is a co-lead, together with New Zealand, of the Climate Action Summit’s Nature-based Solutions action area. In 2020, the Institute of Climate change and Sustainable Development (ICCSD) of Tsinghua University set up the Nature-based Solutions Cooperation Platform to foster collective knowledge from multi-stakeholders in China and globally to explore and leverage nature-based solutions to improve environmental governance. The growing momentum for naturebased solutions in China, it seems, could supplement the state-led top-down urban eco-developments that prevailed in the past two decades. However, a review of the existing public and political initiatives and discourse of fighting climate and biodiversity challenges and promoting nature-based solutions in China reveals a narrow view and a worrying trend. Firstly, cities are not very present on China’s climate and biodiversity agendas, nor in the development of nature-based solutions. For example, in the Position Paper ‘Building a Shared Future for All Life on Earth: China on Action’ that jointly released by the Ministry of Foreign Affairs (MFA) and the MEE for the UN Summit on

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Biodiversity in September 2020, the only one mention of city/urban is that “China does not allow its ecological protection red lines to be trampled upon as it strives to protect biodiversity, adjust its economic structure, draw blueprints for industrial development and promote a new type of urbanisation” (MFA & MEE 2020: 9). The ecological protection redlines system sets up protective zones across China to constrain human activities in areas that are vital to national ecological security and provide essential ecosystem services (e.g., soil and water conservation, biodiversity protection, sand fixation, coastal stabilisation, desertification control, etc.), and is often promoted as a representative of China’s innovative nature-based solutions (Gao et al. 2020; Schmidt-Traub et al. 2021). Whilst protecting ecologically sensitive areas is critical, over-reliance on protected areas (or redline zones) as climate and biodiversity solutions or as a political fig-leaf risks distracting from the urgent need for systemic change of the overall socio-ecological-technical systems. Meanwhile, among the 26 nature-based solutions projects listed as good practices from Chinese government and documented by the UNEP,10 only four are associated to urban or cities, while the rest are regional or national projects such as the Three-North Shelterbelt program, the South-to-North Water Diversion, the Water Dispatching in the Pearl River during low water period, and the Saihanba Afforestation project. The four urban projects include the marine preservation project in Rizhao,11 the ecological restoration in Xuzhou,12 the construction of mangrove coastal wetland ecological park in Xiamen,13 and the comprehensive management project of Mulan River watershed in Putian,14 all of which are governmental projects. As can be seen, the role of cities is narrowly drawn, which, is nevertheless not unique in China as embedding urban perspectives in global climate and biodiversity governance is still a difficult challenge (Bulkeley et al. 2021). In addition, for those agendas that do consider nature-based solutions in cities, they tend to focus on state-led and largescale projects (such as the four projects listed above), and often under the banner of Sponge City and Eco-city (see, for example, He 2019). Comparing to the increasing political and public attention paid to the concept of nature-based solutions, academic research on their application in China is still in the initial stage (Li 2020; Liu et al. 2019). As of June 2021, there are less than fifty articles that specifically study nature-based solutions in the China Knowledge Resource Integrated Database (CNKI), the world’s largest Chinese database. This could partly because the concept of nature-based solutions is relatively new, stemming from European and North American contexts and still evolving. But among those studies that look at nature-based solutions specifically, only four are closely associated to cities in China, including topics on the application of nature-based solutions in Chinese cities in general (Li 2020), in urban heritage preservation (Wu et al. 2021), and in urban adaptation transformation (Lin and Sun 2020), while Wei 10

See https://wedocs.unep.org/handle/20.500.11822/21563/discover (accessed on 6 June 2021). See https://wedocs.unep.org/handle/20.500.11822/29507 (accessed on 6 June 2011). 12 See https://wedocs.unep.org/handle/20.500.11822/29441 (accessed on 6 June 2011). 13 See https://wedocs.unep.org/handle/20.500.11822/29510 (accessed on 6 June 2021). 14 See https://wedocs.unep.org/handle/20.500.11822/29513 (accessed on 6 June 2011). 11

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and Yan (2020) compare nature-based solutions with Park City Theory to explore implications for future urban development. Both these studies and many public discussions also tend to link nature-based solutions to exiting governmental initiatives in Chinese cities, such as the ‘eco-city’, ‘low-carbon city’, ‘sponge city’, and ‘urban double repairs’ programmes. Few mentioned grassroots experiments and their potentials, even though the constraints of incumbent institutional and administrative system have been recognized and discussed (Lin and Sun 2020). Same negligence has been found in most of the academic papers published in English that explore urban nature-based solutions in China (e.g., Huang et al. 2020; Wang et al. 2021), although some pointed out the significance of public engagement throughout the state-led development process of nature-based solutions (e.g., Qi et al. 2020; Xiang et al. 2017). While non-state-led nature-based solutions in Chinese cities are rarely reported or thought about in urban policies and existing academic studies, they are emerging across the country. For example, in 2017, The Nature Conservancy (TNC) launch ed an innovative pilot project named ‘Green Cloud’ in the Gangxia village of Shenzhen, a coastal city located in Southern China.15 The project was initiated to transform the rooftop of an old building into a green living space that can absorb and preserve rainwater, demonstrating a nature-based stormwater management system that can be adopted in other residential buildings. In the early inception of the construction, the project encountered resistance from both residents and local authorities. Neighbors filed complaints as many thought the rooftop renovation was illegal construction that sought to add additional floors to the existing building, and since the concept of a green roof was still so new that no associated regulations exist, local authorities put a halt to the construction. To solve the problem, TNC sought to build trust and earn local supports by actively communicating with local community centers, street government offices, and bureaus about the project and its objectives while also engaging many university students, residents, and youth volunteers. Through these efforts, the project eventually resumed and was later incorporated into Shenzhen’s Eco-Discovery Route by CityPlus, an official guidance platform of Shenzhen municipality. Moreover, the green roof also became a living space for communities (a live musical concert was held on its opening day), while also serving as an outdoor space for nature education, where children can learn about nature and environmental management during summer. An alternative example is the community gardens developed in Shanghai. In 2016, Shanghai’s first community garden in public space—the Knowledge and Innovation Community Garden (KICG)—was built on an abandoned lot in the Wujiaochang Business Area, Yangpu District. The leading developers of the area initiated the project—the Yangpu Science and Technology Innovation Group and the Shui On Group. They sought to transform the land and raise the market value of the whole area, which accommodates a large development project called the Knowledge and Innovation Community (KIC). The KICG project was designed and implemented by a team led by Yuelai Liu, who teaches at the College of Architecture and Urban Planning 15

See more details about the project in Qiang and Yu (2019).

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of Tongji University. In early 2014, Liu founded Clover Nature School, a non-profit NGO that organizes garden projects and workshops in schools, residential communities, and public spaces in the city. By 2019, Clover Nature School has fostered about 60 community gardens in Shanghai. KICG is a 2,000 m2 garden surrounded by residential communities. The garden includes different functional areas, such as a public social area, a one-meter vegetable garden area, a permaculture gardening area, etc. (Liu et al. 2017b). Edible vegetables were planted, and boardwalks and children’s playground were installed, attracting many residents and visitors. It was also designed to serve as an outdoor classroom for children to learn about nature and as a community center that can promote social interactions. Besides designing and implementing the KICG project, Clover Nature School also takes responsibility for its daily operation (e.g., plantings, educational activities) and maintenance, serving as the bridge between the government, business (developers), and residents. Today, more than 100 community gardens and 600 mini-gardens have been built across Shanghai. Many of which are initiated and funded by street offices and neighborhood committees while engaging local residents and communities. The development of community gardens was incorporated into Shanghai’s 2035 Urban Master Plan. Both projects showcase how grassroots, small-scale nature-based solutions emerge in cities and generate wider impacts by bringing changes to incumbent policies and regulations or catalysing many more similar interventions. They demonstrate the great potentials of urban sustainability experiments and innovations that are led and developed by non-state actors in cities (e.g., NGOs and private companies), while showing the importance of establishing cooperation mechanisms between government, enterprises, social organisations, and the public. There are many other similar initiatives carrying out in Chinese cities, and more research is needed to evaluate their innovations and potentials in driving urban sustainability transitions, and more importantly, to understand how to unlock their potentials in transforming China’s urban sustainable development.

5 Unlocking the Potentials of Nature-Based Solutions: The Need for a Paradigm Shift As Frantzeskaki et al. (2017, p. 2) write, “city governments are only one actor in the context of urban sustainability transitions”. The widely recognised constraints of government-led, modernisation-driven, and technology-centered governance and planning approaches in promoting sustainable urban development in China, as well as the existing successful cases of non-state-actors-led sustainability initiatives, show that there are enormous potentials resided in the civil society that have not yet been harnessed in Chinese efforts on transitioning towards urban sustainability. In the meantime, there are growing calls for a ‘whole of society’ approach to deal with the ongoing global pandemic (WHO 2020), exacerbating biodiversity loss (CBD 2020), and unpredictable climate change (UNEP 2019, 2021). Due to its multi-functional

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nature (that can enhance health and well-being, conserve and restore biodiversity, and address climate challenges and many other sustainability issues simultaneously) and its inclusiveness (that covers diverse urban interventions, large or small, and can be initiated and implemented by various actors in cities, public or private), nature-based solutions are advocated as a promising means for environmental governance and sustainable development across the globe. As demonstrated by the two cases above, nature-based solutions also present great opportunities in urban China. To unlock their potential in transforming China’s urban sustainable development, however, requires further exploration. Existing research on nature-based solutions in other regions in the world has amassed a large amount of knowledge of facilitating the wider uptake of naturebased solutions. Innovative governance approaches, business models, institutional settings, and collaboration models are argued to be critical to disrupting the obduracy of incumbent urban systems that tend to favor traditional grey infrastructure or pure technological and engineering solutions than nature-based solutions (Kabisch et al. 2016; Toxopeus and Polzin 2017; Zingraff-Hamed et al. 2020). However, scholars also warned that there is no ‘one-size-fits-all’ governance model or solution (Kabisch et al. 2016; Droste et al. 2017; Dorst et al. 2019; Zingraff-Hamed et al. 2020) since local contexts, both social and biophysical, condition not only the primary sustainability challenges in cities, but also the main institutional, financial, and cultural barriers and opportunities for undertaking effective nature-based solutions. Further empirical-based research is thus needed to explore the distinct structural conditions for applying and mainstreaming nature-based solutions in urban China. This, however, does not mean existing knowledge generated from other national or urban contexts is of no use. The key is that knowledge should be provincialized to offer different ideas for governing city and nature and to fit the needs and capacities of cities in China. Here, we argue to promote the uptake of nature-based solutions and transforming urban sustainable development in China, requires first and foremost, a paradigm shift. The traditional government-centric paradigms, as well as the top-down and technocratic urban planning and governance system, not only result in continued dependence on the machinery of existing approaches in managing urban nature and developing urban sustainability (e.g., the adoption of a set of reductive quantitative targets and ecological engineering approaches), but also masks the various existing and potential efforts made or can be made by non-governmental actors in initiating and practicing urban sustainability experiments. This, in turn, further limits the degree to which civil society and private sector organisations can be included as part of the transformative actions required to realize sustainability transitions. Social and political norms, values, rules, and relationships undergird and structure the myriad decisions made by both public and private actors (Eakin et al. 2017). Therefore, greater attention should be paid to the long-ignored social dimension of the socio-ecological-technical system that conditions urban governance in China. A new governance paradigm should be able to activate the innovation and creativity of the diverse actors in cities, creating an enabling environment, empowering different social groups, and allowing innovations at all levels to develop, grow, and thrive.

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Support from the authorities is undoubtedly the key, but mobilizing the whole society to take part is of primary importance. This relies on developing and disseminating knowledge on the multi-benefits of nature-based solutions, raising public awareness of the importance to act for sustainability as well as the responsibility of individuals in the fight against climate change, biodiversity loss, and many other environmental and social challenges.

6 Conclusions This chapter explores the potentials of nature-based solutions in transforming contemporary urban sustainable development in China, which is characterized by a state-dominated top-down steering mechanism and a technocratic planning and development pattern. Whilst currently, state-led and sustainability-themed urban programs and their pilot projects dominate both public and academic discourse on the efforts and promises for a sustainable urban future in China, this chapter argues that with few actual changes in the governance system that largely excludes the civil society and private sector organisations in policy- and plan-making and implementation processes, these programs and projects often fail their promises in advancing sustainable development in urban China. The rush to build ‘eco’, ‘lowcarbon, ‘smart’, or ‘green’ cities even generate unintended and pernicious effects on local ecology and community. The concept of nature-based solutions encompasses multi-actor dynamics, various scales and forms of interventions, and multiple benefits for people and nature. Its inclusiveness and multi-functionality could draw wider attention and support for non-state-led innovations across Chinese cities and thus open a great opportunity for transforming urban sustainable development in China. To unlock their potentials requires, first and foremost, a paradigm shift in urban and environmental governance, one that sees urban sustainable development and environmental governance not as government business but rather a systemic matter that requires whole-of-society efforts. Research on nature-based solutions in China is still in its infancy. Future studies could first explore and analyze existing nature-based solutions in Chinese cities, especially those non-state-led projects and those initiatives in lower-tier cities and smaller towns. By examining how these existing practices are organized, operated, functioned, and maintained, the potentials of nature-based solutions in addressing pressing urban sustainability challenges in China can be recognized, while the ways through which such potentials can be achieved and maximized can be explored and analyzed. An integral part of the research is the understanding of local historical, cultural, and socioeconomic contexts and the dynamic human-nature interactions that shape particular interventions. Moreover, the research could further investigate the structural conditions that shape the planning and governance in today’s China and examine the barriers and opportunities for applying and mainstreaming naturebased solutions to achieve urban sustainability transitions. Existing research in the European context can provide valuable insights (van der Jagt et al. 2020b; Xie et al.

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2020b, 2020c), but knowledge should be provincialized to be effective in specific contexts.

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Towards Sustainable Urban Green Infrastructures Ali Cheshmehzangi

Abstract This chapter serves as a summary of what we have covered in the last four parts of the book in 16 chapters. We could not have put together a more comprehensive volume, providing practitioners, policymakers, and researchers a set of guidelines, best practices, and innovative ideas for the future of green infrastructure practice (i.e., design and planning), implementation, and integration. The book has included many case study examples, policies, guidelines, and ideas for green infrastructures (GIs) in Chinese cities, some that could also be applied to other contexts. Moreover, this chapter summarises some key lessons and directions towards sustainable urban green infrastructures. It also highlights selected potential new directions in future research and practice of green infrastructure development in China and elsewhere. China’s progress (to date) is discussed as an emerging model, where we see a larger capacity for more investment, innovation, and opportunities that could lead to more sustainable planning and design solutions. Keywords Sustainable urban green infrastructure · Innovation · Urban sustainability · Environmental protection · Nature · China

1 A Summary This chapter serves as a summary of what we have covered in the last four parts of the book in 16 chapters. We could not have put together a more comprehensive volume, providing practitioners, policymakers, and researchers a set of guidelines, best practices, and innovative ideas for the future of green infrastructure practice (i.e., design and planning), implementation, and integration. The book has included many case study examples, policies, guidelines, and ideas for green infrastructures A. Cheshmehzangi (B) Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, China e-mail: [email protected] Network for Education and Research on Peace and Sustainability (NERPS), Hiroshima University, Hiroshima, Japan © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4_18

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(GIs) in Chinese cities, some that could also be applied to other contexts. We extract some lessons from each part in the next section. In this book, we have explored China’s case as a leading example in this area. We highlight China’s recent sustainability transitions, proving that green and blue infrastructures could be the backbone of contemporary and future urban development models. Integrated solutions are proposed to be sensible and holistic to address many urban pressures. By tackling some issues such as flooding, drought, food security, and urban resilience, cities and other similar (and not familiar) built environments could be better prepared and become smarter. We could think of various interdisciplinary and transdisciplinary approaches, such as integrating smart and green technologies in GI practices, nanotechnologies for GI design, AI-based optimised models for better performance and monitory of urban environments, hybrid models of urban development, etc. Some of these are summarised as potential directions in Sect. 3 of this chapter. As the world faces new (and perhaps more significant) challenges, we have to come up with more innovative solutions. The caveat here is the growing impacts of climate change on our natural and built habitats, which also put pressure on how we could allocate more room for an urbanising world. Despite only covering a very small proportion of land surfaces, cities are expanding uncontrollably, and rural-tourban migration seems inevitable than ever. These trends are becoming more popular elsewhere in other developing and emerging economies, such as Asia, Africa, and Latin America (Butters et al. 2021; Cheshmehzangi et al. 2021b). We are talking about at least half of the world’s population, where we may end up repeating the same mistakes of developed nations from several decades ago. Thus, this is our chance to think outside the box and move towards more interdisciplinary solutions, collaborative directions, and innovative pathways beyond just experimentation and pilot models. We must shift away from discarded urban development models and urbanisation processes and learn how genuine sustainability could be achieved. In doing so, we believe GIs could play a central role and help cities, urban regions, and urban–rural regions to have healthier environments for both humans and other species. We have to value our ecosystems within and outside of cities and ensure they are taken care of with a longer-term plan. We also have to recognise the negative impacts of insensible development on the environment and the planet and ensure health and sustainability come together through comprehensive thinking. Our earlier work highlighted four different elements of GIs (Cheshmehzangi and Butters 2015, 2017; Cheshmehzangi et al. 2021a), something that we would like to highlight again. We summarise four elements in four shades of GIs, namely ‘green’ resembling earth, ‘blue’ for water, ‘red’ for energy, and ‘white’ for air (see Fig. 1). This is because we believe GIs are more than what many planners and designers consider, and we should understand the climate benefits, co-benefits, and tradeoffs of GI (Alves et al. 2019; Choi et al. 2021; Li et al. 2021; Xu et al. 2021) for more sustainable solutions and directions. Some examples are urban flood mitigation (Alves et al. 2020), evaluating economic benefits of GIs (Jia and Zhang 2021), heat mitigation benefits of GIs (Liu et al. 2021), energy efficiency (Chen and Lin 2021), achieving environmental justice (Amaral et al. 2021), etc. We note that blue and green

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GREEN – Earth Such as: Vegetation, and soil. Providing: shade, oxygenation, biodiversity, noise abatement, and pollutant filtration.

BLUE – Water Such as: Pools, streams, and foundations. Providing: Infiltration, evaporation, purification, recycling, and cooling.

RED – Energy Such as: Bioclimatic urban design Providing: heat load reduction, and supplying renewable energy.

WHITE – Air Such as: Urban Ventilation Providing: cooling, fresh air, removing pollution, reducing heat island effect.

Fig. 1 The four proposed elements of green infrastructures (Source Adapted from Cheshmehzangi et al. 2021a, b)

infrastructures should be more than just a tool for sustainable urban development (Din Dar et al. 2021) and help us to strengthen the nexus between sustainability, health (Kumar et al. 2019), and development. Following such thinking, we also provide a set of guidelines for the utilisation of GI from four suggested elements (see Fig. 2). From vegetation and biodiversity enhancement, all the way to bioclimatic urbanism and urban microclimate design, we see greater opportunities for scientific-technical approaches in achieving urban sustainability and ultimately sustainable urbanism. We verify that GI is a small part of a much larger picture, but it can be more effective and impactful than it currently is in achieving urban sustainability. We are eager to see more co-benefits of GI integration in cities and similar built environments. These should allow us to have better approaches for environmental protection, ecological preservation, enhancement of ecosystem services, purification of our environments, and help us resolve some of the environmental pressures worldwide. We also hope to witness more progression in developing multi-spatial, multi-functional, and multi-objective GI best practices (Sun et al. 2020). Such practices would help break barriers between various stakeholders and shift towards comprehensive strategies that genuinely focus on achieving harmony between humans and nature.

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•Vegetation •Farming •Treatment •Biodiversity

•Bioclimatic urbanism •Renewable energy •Urban microclimate •Lessening heat load

•Purification •Cooling effect •Recycling •Leisure

EARTH

WATER

ENERGY

AIR •Cooling effect •Pollution reduction •Lessening heat island effect •Urban Ventilation

Fig. 2 The details of guidelines for utilisation of green infrastructure from four suggested elements (Source Adapted from Cheshmehzangi et al. 2021a, b)

As part of the ’Urban Sustainability’ book series, we trust this book sits well in considering nature-based solutions, promoting nature-centric development, and enhancing human-nature relations. For all these three factors, we trust in a better balance in our development. We hope we are just in time in developing and maintaining a good balance between the natural and built environments, or between nature and ourselves, or between everything else and our urbanisation processes. In the next section, we briefly highlight some of the lessons from four parts of the book. In doing so, we narrate these lessons for sustainable urban green infrastructures (SUGIs) and achieving urban sustainability in cities and communities in China and elsewhere. Afterward, the last section summarises potential new directions and future research in GI and urban sustainability. These are summarised in 12 potential areas, and we hope they conclude the book in a way that readers are left with ideas, innovative thoughts, questions, and answers for GI practices and their implementation and integration in cities and city environments.

2 Extracted Lessons for Sustainable Urban Green Infrastructures This section extracts some key points as potential lessons from all four parts of the book, mainly for SUGIs and achieving urban sustainability.

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We note from Part 1 that China’s GI theory is still relatively undeveloped and requires more attention on policy and guideline development and scaling up projects. Multi-stakeholder engagement is still lacking in GI policy-making, and the shift needs to be towards service efficiency and high-quality urbanisation strategies. Also, we note that the general public is still not fully aware of GI benefits and co-benefits. Hence, we would need to invest more in raising people’s awareness and engagement, something that could happen at smaller scales of micro and meso. In addition, we see China’s investment in urban forest planning could be replicated (i.e., with some contextalisation plans) by other countries. Although relatively new in China, we see tangible progress in this area, particularly in recent years. Yet, many urban transition factors need to be considered to achieve holistic urban forest planning. In line with in-fill development plans, urban forestation could lead to greening the cities against high-level densification and unrestrained urban development. Larger cities would struggle with such strategies as managing their migration influx/intake and considering the construction of healthy living environments for their residents. This could also be challenging in other rapidly-growing cities elsewhere, where renewal of urban areas, such as slums and informal settlements, could lead to slower greening and GI integration in urban environments. This leads to the role of regulations and implementation strategies, from large-scale GI development to smaller-scale green roofs. In all cases, a robust policy system is needed to ensure we could offer incentives, guidelines, and protocols, with smooth urban transitions that entail sustainability and sustainable development. We see the same development gradually for the national-level Sponge City Programme (SCP), which is yet to mitigate urban flooding issues across the country. The experimental and smaller pilot projects are expected to develop towards larger-scale projects of district-level, city-level, and regional-level. From Part 2, we summarise the nexus between national-level policies and municipal-level implementation plans. Hence, for planning to happen, we must assess and localise upper-level policies and strategies, same as the case of forest city policy and how it is then implemented at the city- and/or regional-levels. Correlated with China’s recent pledge towards carbon neutrality by 2060, we note that China’s investment in forest city projects and forestation of existing cities could lead to the reduction of air pollution and (towards) cleaner air in cities. However, the main challenge remains in existing cities on a larger scale, where there is little room for forestation. Nonetheless, we believe the role of regional planning could be enhanced to ensure urban–rural relations are enhanced and larger scale GI planning could be considered. In addition, we see a growing demand for urban greening, some that could help us promote urban farming and other GI integrations in cities. Once again, co-benefits of GI should be considered in such planning processes to enable involving multiple stakeholders and communities and their representatives. This approach helps to improve the harmonious development between humans and nature, allowing for the development of multi-objective and multi-functional green spaces and greenery in cities. Some of these approaches could support overarching movements, such as eco-development in China, where we still see minimal efforts on the enhancement of urban ecologies and ecological preservation in and around such new projects. Nonetheless, we note the importance of green-eco-development,

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more than just at one individual level, but more effective through synergies between different spatial levels and between multiple functionalities and objectives. Thus, we see a unique opportunity to enhance eco-policies and enable new opportunities for scaled-up projects and wider networks of ecological design and conservation in cities and between them. From Part 3, we extract key factors that lead to design solutions, enabling to achieve people-centric GI design, enhancing high-quality urbanisation strategies, developing GI networks, and GI integration for public realm design. Thus, we cover both larger-level master planning strategies and smaller-scale urban design solutions, including integrating GI as part of design and decision-making processes. First, on green exposure, we recognise the value of people engagement and/or participation in developing a platform where the capacity, quality, and type of GI could be generated. Thus, this allows the development of new indicators for urban greening and integrating GI in the urban environments. Second, we see a greater emphasis on sponge node renewal programmes and high-quality urbanisation strategies on GI restorative practices. Like the green exposure assessment approach, we note the importance of key performance indicators (KPIs), but with a shift towards developing comprehensive evaluation systems and scenario-based design and planning approaches. With the use of contemporary computational software, a performance analysis could help us evaluate design options before implementation and construction phases. We also see greater importance of high-quality urbanisation, which is also included in sponge node enhancement and restorative methods, such as ecological preservation, ecological restoration, etc. Third, we recognise the importance of GI network construction, particularly in brownfields and polluted environments. In doing so, we value the integrity of GI and how it should be restored in a healthy transition and through the use of spatial planning and design. This entails considering a larger scale GI network construction, allowing for scientific-technical design solutions and safeguarding sustainable development of cities. Environmental and ecological restorations are not easy tasks in places where land has become polluted for decades. Hence, we require introducing and undertaking integrated solutions where spatial planning and design could also guide transitions of land, environmental qualities, development modes, etc. And fourth, the design of GI in public realms has been discussed as a follow-up to spatial planning and design strategies. This approach complements what has been discussed earlier by considering spatial strategies and allowing for sub-strategies for pre-design, design, and construction phases. From Part 4, we note a variety of factors that suggest the growing importance of technical integration for GI design and development in cities. For instance, smart technologies are discussed as part of technological advancement in monitoring the GIs and their development and design. Such an approach could benefit the optimisation of GI performances and develop new trends of GI development down the line. From the development of floodwalls/floodgates to smart urban farming practices, we see that new technologies could help strengthen the resilience of our GI practices. From automated methods to optimised performances, such approaches could help us with big data collection, data assessment, and model development. However,

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we also note the importance of training and resource management that should be considered as part of using or utilising smart technologies for GI development in cities. In doing so, we could develop an integrated design support system, where urban environments are managed more smartly, and smart urban systems help to optimise the environmental qualities and integrated management processes. Examples of lifecycle management systems, flood control, stormwater management, and drainage management system are just a few for us to consider simulation systems, technical integration, and collaborative work. This leads us to the other two remaining points on nature-based solutions (NBS) and developing frameworks for utilising such strategies in the GI design and enhancement. The first point is related to the position of biophilic design, allowing NBS to take part in the development of bio buildings, eco-buildings, and potential renewal and refurbishment projects. The second point is about feasibility assessment and developing an ecological cycle for multiple uses/functions, often promoted in higher-level NBS projects and research. Lastly, we note the importance of urban sustainability transitions, which could be achieved by integrating NBS in eco-, green-, resilient-, low-carbon-, and smart-developments. The dynamic human-nature interactions are particularly highlighted as part of sociotechnical and socio-economic processes. We could then verify that NBS remains as a significant potential for China’s sustainable development agenda, which could be suggested as part of future research directions, too.

3 New Directions and Future Research In this last section, we summarise some potential new directions and future research in the field of GI and urban sustainability. We particularly look into these from the perspective of GI integration, implementation, design and planning, and development. Some could also crossover to restoration and conservation strategies, which are equally important to consider through sustainability transitions. The following list of 12 directions and future research summarise some of the viewpoints, discussions, ideas, and innovations covered in this volume. (1) Integrated design solutions for sustainable urban green infrastructure We expect to see more integrated approaches that could provide closer links between various sectors and stakeholders, such as ecologists, landscape architects, designers, and planners. We also urge that nexus between academia, practice, and governance should become closer and more robust, allowing for more interdisciplinary and transdisciplinary opportunities. (2) Scientific-technical emphasis on GI integration As noted throughout the book, we emphasise the position of scientific-technical methods or approaches related to GI development and integration in cities and urban environments. From heat mitigation to stormwater management, we see growing

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opportunities for technical methodological framework development, indicator-based scientific methods, and comprehensive models of GI development and integration. (3) Hybrid models of smart-resilient urban development The utilisation of smart technologies and strategies to enhance the resilience of cities could help us improve urban services and systems, such as those related to GIs, urban analytical studies, indicator-based frameworks, real-time studies, datadriven approaches, etc. Such procedures could help to promote recovery processes, restoration plans, conservation strategies, and design decision-making processes. (4) Multi-objective and multi-functional GI models The more we see the value of GI, the more we realise that they could be multiobjective and multi-functional. Set aside the social benefits of GIs (Cheshmehzangi and Griffiths 2014), we see growing numbers of projects and programmes that consider the nexus between NBS-GI, NBS-Eco development, health-GI, etc. In practice, such a shift has already taken place to integrate multiple facilities, services, and systems. In research, we are partly behind, but we are on the right track to develop comprehensive frameworks and multi-objective models of GIs. (5) GI co-benefits for both humans and the environment Research on GI co-benefits and trade-offs is expanding rapidly, focusing on coupling grey-green infrastructure systems, trade-offs between blue, green, and grey infrastructures for specific purposes, etc. Some of these studies suggest data-driven and big data analytical approaches, providing systematic solutions for GI and ecological infrastructure design. Some existing work include comprehensive assessments, but we hope to see a growing number of practicable studies for future GI design and planning. (6) Nature-based solutions for eco- and green-development NBS tends to integrate green, blue, and grey infrastructures mainly focused on environmental or ecological improvements and addressing other sustainability factors. As an integrated approach, NBS can produce multiple benefits, allowing to address trade-offs between urban services and enhance biodiversity and ecosystem services of the environments. NBS could be brought in to enhance eco- and green-development agendas, indicators, and targets for cities and urban environments. Such approaches could also advance further for flood risk alleviation strategies, wetland design, flood retention, and stormwater management plans, etc. (7) Forestation progress as part of long-term city-scale and regional-level plans As existing built environments struggle with their forestation plans, we see a greater opportunity to develop long-term plans and consider city-wide and regional-level strategies. In larger countries, regional planning is picking up fast, and we notice such an approach could also help smaller countries. Regional forestation programmes seem to be more effective than smaller-scale projects. Thus, we see a chance for rapid

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scaling-up experimental projects than just patches of greenery and urban greening projects. (8) Information and Communication Technologies (ICT) for smarter solutions The nexus between ICT infrastructure and green infrastructure will become even more attractive in the future. Currently, only a very few studies look into such nexus, but we expect the role of ICT to become more tangible in the coming years. Its application for smarter solutions in GI design and development is expected to open up novel opportunities for integrated design, data-driven methods, and enhancing environmental sustainability. (9) Urban health and societal wellbeing central to GI development As mentioned several times in the book, we expect to see a growing demand and research focus on urban health and social well-being issues. We expect they play a more central role in GI development, allowing researchers to study the health benefits of GI and consider the impacts of GI on human/societal health as well as the health and sustainability of our environments. (10) High-quality urbanisation with carbon neutrality goals With growing demand in the carbon neutrality market, we expect to see more opportunities for green innovation and environmental policies. GI fits well with carbon neutrality targets, as it could also be a platform to utilise green technology innovation, renewable energies, and other sustainability targets. We expect that more attention is given to high-quality urbanisation, which means more studies are needed on (urban) sustainability transitions, carbon reduction measures, and the ecological environmental performances of the built environments. (11) Interchangeability between multiple spatial levels of micro, meso, macro, and regional Apart from tangible interchangeability between different sectors, stakeholders, and contexts, we also see growing opportunities for interchangeability between multiple spatial levels of the built environments. We see scope for multi-spatial planning and design processes, particularly for the GI practices, which could ultimately suggest synergies between different spatial levels. This approach helps us to better understand and develop GI for multiple objectives and benefits. However, this approach requires long-term vision and planning. (12) Micro- and meso-level innovations for smart GI design An area of interest is the development of smart GI for cities and urban environments, particularly for compact urban areas where space is scarce and greening is challenging. With more attention on micro- and meso-level GI design, we could integrated new technologies and tools such as nanotechnology and AI and enable GIs to become more performative, intelligent, and resilient. In doing so, we could focus on enhancing water treatment processes, develop safe and sustainable urban services, and help to promote environmental sustainability of the built environments.

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To conclude briefly, we would like to reflect on this volume as an impressive collection of GI practices, guidelines, policies, and implementations. The case study examples provide us with a detailed knowledge of many recent and current GI practices, some that could be scaled-up and some that could be replicated, contextualised, and adopted in other contexts. We summarise these cases and examples as lessons learnt, some with a pinch of salt, allowing us to think about how GI could develop further and how it could help us achieve urban sustainability. Without a doubt, China’s development on GI has progressed rapidly in recent years, and we see more significant opportunities for collaboration, knowledge transfer, and technology transfer between multiple stakeholders. As our conclusion is on developing sustainable urban green infrastructures, we hope to see innovative ideas and numerous benefits of GI practices in cities and city environments. Thus, no single model could fulfil all these, but multiple models and opportunities could lead to smarter and more resilient urban environments. Our GI is partly part of the natural environment, but some are engineered as part of our living habitats. We have to distinguish between the two and learn more from our natural habitats to have better methods of nature-based solutions and strategies. The two, ‘nature’, and ‘natural’ differ quite a bit. We hope that by learning from the two, we can develop and design green infrastructures to achieve urban sustainability in China and around the world. Some measures and indicators suggest that sustainable urban green infrastructure could be developed and scaled up, and we hope not far from reaching that. This volume ends with some viewpoints on what has become the most comprehensive report on green infrastructure in Chinese cities. These examples must be studied further, and we have to become more critical and innovative for the development of GIs in China and elsewhere. Lessons learnt from this volume could simply become the guidelines for researchers, practitioners, and policy-makers. We hope the suggestions here could nurture their innovative research, help them develop best practices, and enlighten them with better decision-making processes. After all, our goal is to achieve urban sustainability, and with GI, this could be even better.

References Alves A, Gersonius B, Kapelan Z, Vojinovic Z, Sanchez A (2019) Assessing the co-benefits of green-blue-grey infrastructure for sustainable urban flood risk management. J Environ Manag 239:244–254. https://doi.org/10.1016/j.jenvman.2019.03.036 Alves A, Vojinovic Z, Kapelan Z, Sanchez A, Gersonius B (2020) Exploring trade-offs among the multiple benefits of green-blue-grey infrastructure for urban flood mitigation. Sci Total Environ 703:134980. https://doi.org/10.1016/j.scitotenv.2019.134980 Amaral MH, Benites-Lazaro LL, de Almeida Sinisgalli PA, da Fonesca Alves HP, Giatti LL (2021) Environmental injustices on green and blue infrastructure: urban nexus in a macrometropolitan territory. J Clean Prod 289:125829. https://doi.org/10.1016/j.jclepro.2021.125829 Butters C, Cheshmehzangi A, Sassi P (2021) Cities, energy and climate: seven reasons to question the dense high-rise city. J Green Build 15(3):197–214

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Chen Y, Lin B (2021) Understanding the green total factor energy efficiency gap between regional manufacturing—insight from infrastructure development. Energy 237:121553. https://doi.org/ 10.1016/j.energy.2021.121553 Cheshmehzangi A, Butters C (eds) (2017) Designing cooler cities: energy, cooling and urban form— the Asian perspective. Palgrave Macmillan, Singapore Cheshmehzangi A, Griffiths CJ (2014) Development of green infrastructure for the city: a holistic vision towards sustainable urbanism. Arch Environ 2(2):13–20 Cheshmehzangi A, Butters C, Dawodu A, Xie L (2021a) Green infrastructures for urban sustainability: issues, implications, and solutions for underdeveloped areas. Urban For Urban Green 59(127028):1–18 Cheshmehzangi A, Dawodu A, Sharifi A (2021b) Sustainable urbanism in China. Routledge, New York Cheshmehzangi A, Butters C (2015) Urban green infrastructure: for cities of developing countries. Technical report, Part of the ELITH project, pp 1–26 Choi C, Berry P, Smith A (2021) The climate benefits, co-benefits, and trade-offs of green infrastructure: a systematic literature review. J Environ Manag 291:112583. https://doi.org/10.1016/j. jenvman.2021.112583 Din Dar MU, Shah AI, Bhat SA, Kumar R, Huisingh D, Kaur R (2021) Blue green infrastructure as a tool for sustainable urban development. J Clean Prod 318:128474. https://doi.org/10.1016/j. jclepro.2021.128474 Jia J, Zhang X (2021) A human-scale investigation into economic benefits of urban green and blue infrastructure based on big data and machine learning: a case study of Wuhan. J Clean Prod 316:128321. https://doi.org/10.1016/j.jclepro.2021.128321 Kumar P, Druckman A, Gallagher J, Gatersleben B, Allison S, Eisenman TS, et al (2019) The nexus between air pollution, green infrastructure ad human health. Environ Int 133(Part A):105181. https://doi.org/10.1016/j.envint.2019.105181 Li L, Cheshmehzangi A, Chan F, Ives CD (2021) Mapping the research landscape of nature-based solutions in urbanism. Sustainability 13(7):3876. https://doi.org/10.3390/su13073876 Liu Z, Cheng W, Jim CY, Morakinyo TE, Shi Y, Ng E (2021) Heat mitigation benefits of urban green and blue infrastructures: a systematic review of modeling techniques, validation and scenario simulation in ENVI-met V4. Build Environ 200:107039. https://doi.org/10.1016/j.buildenv.2021. 107939 Sun J, Cheshmehzangi A, Wang S (2020) Green infrastructure practice and a sustainability key performance indicators framework for neighbourhood-level construction of sponge city programme. J Environ Prot 11(2):82–109. https://doi.org/10.4236/jep.2020.112007 Xu C, Liu Z, Zhu Y, Yin D, Leng L, Jia H, Zhang X, Xia J, Fu G (2021) Environmental and economic benefit comparison between coupled grey-green infrastructure system and traditional grey one through a life cycle perspective. Resour Conserv Recycl 174:105804. https://doi.org/10.1016/j. resconrec.2021.105804

Index

A Adoption, 70, 72–74, 76–80, 82–84, 86–90, 101, 114, 155, 484 Agglomeration, 33, 34, 127, 133, 134, 138 Agrarian, 146 Agriculture, 13, 22, 33, 74, 77, 145, 153, 155, 156, 158, 166–168, 170, 194, 203, 204, 240, 317, 347, 377–382, 384–386, 388–391, 432, 433, 453, 454, 457, 459 Agri-ecological, 432, 437 Anhui, 83, 84, 89, 105, 299, 304, 306 ArcGIS, 211, 307–309, 312, 313, 340 Artificial, 11, 13, 22, 33, 98, 101, 111, 113, 118, 165, 223, 224, 289, 325, 351, 354, 356, 377–379, 402, 425, 432, 437 Artificial Intelligence (AI), 378–380, 384, 390, 492, 499 Assessment system, 137, 402, 403, 421

B Beijing, 9, 35, 37, 40, 41, 58, 62, 63, 82–89, 93, 99, 107, 111, 115, 127, 143, 145, 146, 148–151, 153–155, 157–169, 178, 180, 183, 199, 325, 335, 337 Belt and Road Initiative (BRI), 37–39 Best Management Practices (BMP), 398, 417 Big data, 10, 13, 173, 175, 178, 186, 187, 377–379, 385, 388–390, 397, 401, 420, 425, 496, 498 Bio building, 14, 429, 430, 437, 445, 446, 497 Biodiversity protection, 25, 481

Biological corridors, 24 Biology, 28, 209, 471 Biomass, 198, 432, 433, 435, 448, 453 Bio-retention cells, 271, 274, 277 Bird habitat, 313 Blockage, 155 Blockchain, 379, 389, 390 Bottom-up, 8, 9, 70, 82, 83, 89, 93, 143–145, 148, 150, 157, 328, 479 Bourgeois lifestyle, 58 Buffer zone, 32, 60, 197, 316, 326, 353, 357, 359 Building performance, 430

C Campaign, 14, 56, 59, 62, 63, 191, 192, 196, 204, 205, 214, 397, 405, 425 Canada, 26, 56, 72 Carbon neutrality, 468, 495, 499 Carbon sequestration, 61 Central National Government (CNG), 8, 97, 99, 101–103, 112–114, 116, 118–120 Chengdu, 33, 45, 89, 147, 183, 341 Chongming, 197, 198, 212, 228, 230, 231, 234, 468, 474, 476–478 Chongqing, 31, 33, 45, 72, 82–86, 88, 94, 103, 104, 117, 341 Cinnamomum camphora, 432 CiteSpace, 23 City-scale, 7, 42, 69, 70, 73, 89, 91–93, 205, 300, 345, 498 Clematis, 451, 452, 458, 463 Climate change, 2, 4, 11, 26–28, 38, 40, 70, 99, 100, 119, 194, 200, 224, 265,

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 A. Cheshmehzangi (ed.), Green Infrastructure in Chinese Cities, Urban Sustainability, https://doi.org/10.1007/978-981-16-9174-4

507

508 267, 378, 468, 478, 480, 483, 485, 492 Climatic data, 437, 439 Cloud computing, 385, 389 CNKI database, 22, 23 Coastal stabilisation, 481 Communist Party of China (CPC), 33–35, 37, 40, 41, 48, 330, 473, 474 Comprehensive Air Quality Index, 207 Conference of the Parties (COP), 468 Cropland, 143, 146, 155, 165, 176, 180, 310, 313, 317, 452 Cultural, 25, 29, 33, 56, 58, 83, 139, 166, 199, 208–211, 244, 280, 284, 290, 292, 304, 311, 313, 314, 324, 331, 332, 345, 367, 399, 470, 472, 480, 484, 485 D Data-driven, 11, 223, 233, 234, 254, 258–260, 498, 499 Datapoints, 408, 413 Decision-making, 12, 15, 139, 225, 233, 243, 254, 266, 269, 289, 305, 380, 382, 385, 386, 389, 398, 402, 403, 407, 417, 425, 467, 496, 498, 500 Degradation, 266, 355, 356 Desertification, 25, 203, 204, 481 Dongtan, 196–198, 200, 204–211, 216, 474, 478 Drainage, 8, 14, 70, 75, 97–102, 109–111, 113–116, 119, 120, 152, 256, 346, 354–357, 397, 399, 402–405, 408, 412, 414, 415, 417, 419–422, 425, 427, 430, 431, 449, 450, 497 Drought, 25, 71, 98, 104, 106, 398, 492 Dynamic exposure, 178, 185 Dynamic human distribution, 177 Dynamic SAR model, 9, 125, 128, 132, 134, 138 E Eco building, 14, 429 Eco-cell, 199 Eco-garden city, 468, 474, 475, 477 Eco-island, 350–352, 468, 474, 476–478 Ecological city, 33, 192 Ecological civilization, 7, 27, 33–35, 37, 38, 45–48, 55, 57, 62–64, 78, 128, 132, 139, 192, 207, 209, 216, 299, 324, 330, 468, 469, 473, 474, 476 Ecological communities, 56, 202, 208

Index Ecological Corridor, 353 Ecological corridor, 197, 311, 313, 314, 331, 341, 352 Ecological destruction, 477, 478 Ecological environment, 6, 21–23, 31, 32, 34, 35, 37, 38, 41–44, 74, 77, 83, 84, 127, 163, 203, 207, 209, 266, 300–303, 332, 351, 398 Ecological Garden City, 192 Ecological infrastructure, 24, 26, 27, 267, 351, 498 Ecological performance, 26, 341 Ecological protection, 32, 36, 37, 44, 151, 155, 326, 399, 481 Ecological restoration, 29, 33, 43, 63, 205, 207, 270, 299, 305, 312–314, 316, 317, 324, 347, 422, 468, 474, 475, 481, 496 Ecological security, 25, 202, 337, 338, 346, 367, 481 Ecologist, 330, 479, 497 Eco-sensitive zone, 32 Ecosystem, 11, 22, 24–27, 29, 32, 33, 37, 40, 47, 56, 63, 64, 74, 98, 100, 101, 109, 118, 120, 126, 128, 191, 192, 195, 204, 208, 217, 224, 225, 256, 265, 267, 300, 301, 305, 309, 315, 324, 331–333, 346, 348–350, 353, 367, 377, 432, 471, 472, 478, 480, 481, 492, 493, 498 Embedded development, 198 England, 145, 174, 330, 331, 334 Environmental agenda, 191, 192, 205, 208 Environmental degradation, 60, 191, 192, 199, 200, 323, 468 Environmental gentrification, 477 Environmental justice, 4, 175, 186, 492 Environmental movement, 192, 330 Environmental protection, 7, 23, 36–39, 43, 59, 60, 69, 93, 126, 132, 140, 153, 159, 192, 195, 204, 206, 216, 275, 330, 341, 403, 493 Environmental regulation, 126, 192, 473 Evergreen, 186, 451 Experimentation, 3, 292, 469, 471, 472, 492 F Facility connectivity, 39 Farming, 8, 9, 13, 143–146, 148–152, 155–171, 198, 377–382, 384–386, 388–391, 470, 495, 496 Farmland, 43, 45, 110, 143–146, 152, 155, 156, 159, 165, 170, 171, 197, 198,

Index 201, 302, 309, 346, 438, 444, 451, 477 Fenghuangcheng, 399, 400, 403 Ficus microcarpa, 432 Fieldwork, 11, 223, 226, 233, 234, 253, 254, 256–258, 260, 261, 433 Financial support, 43, 77, 93, 151, 166, 333 Financing, 29, 30, 39, 43, 118, 119, 210, 472, 478 Fixation, 153, 481 Flood regulation, 25 Flood standard, 418 Flow Accumulation, 308 Flow Direction, 308 Food security, 9, 143, 144, 149, 349, 492 Forest coverage, 42, 127, 137, 153, 228, 477, 478 Formulation, 44, 417

G Gansu, 82, 108, 181, 184, 186 Geolocalised, 230, 237, 254 GeoTIFF, 230 Ghost town, 478 GI implementation, 260 GI integration, 2, 13, 323, 493, 495–497 GI measure, 8, 98, 113, 267 GIS, 272, 273, 292, 318, 330, 331, 336, 337, 339, 340, 367, 397 GI spatial plan, 338 Green building, 7, 33, 36, 37, 39, 40, 43, 47, 69, 72, 75, 77, 78, 87, 88, 93, 208, 210, 224, 399, 437 Green Building Evaluation Standards (GBES), 208 Green cell, 206 Green corridor, 160, 197, 203, 206, 210, 305, 331, 350–352, 355, 357 Green credit, 43 Green economy, 64, 100, 195, 198, 202, 208, 209, 211, 216 Green façade, 450–453, 455, 460–463 Green finance, 24, 27, 37, 39, 40, 43 Greenless, 235 Green Mark, 208 Green niche, 472 Green roof, 6–8, 69–94, 100, 202, 267, 324, 347, 357, 377, 389, 413, 417, 425, 430–432, 436, 437, 445–451, 453–457, 459–461, 463, 464, 472, 476, 480, 482, 495 Greenspace, 8

509 Green Stormwater Infrastructure (GSI), 267, 271, 274, 287, 289, 290, 292, 293 Green street, 267, 346, 431, 432, 445, 446, 452, 453, 463, 464 Green technology, 3, 25, 29, 43, 48, 477, 492, 499 Green urbanisation, 33, 35 Green valley, 206 Greenway, 22–24, 27, 32, 36, 45, 199, 208, 300, 330, 331, 335, 338, 339, 346, 347, 352 Gross Domestic Product (GDP), 40, 46, 131, 132, 191–193, 201, 204, 207, 332, 399, 473, 474 Groundwater, 98, 101, 109, 113, 119, 301, 317, 336, 357, 444, 445 Guangdong, 30–33, 45, 48, 82–86, 89, 108, 399 Guangming District, 13, 397–400, 413, 418, 421, 424, 425 Guangxi, 82–84, 86–88, 106, 203, 337, 430, 437, 451 Guanyang, 437 GuidosToolbox, 308 Guilin, 181, 194, 196, 200, 203–206, 209–211, 213, 214, 437 Guizhou, 82, 106 G value, 338

H Hangzhou, 89, 93, 183, 325, 351 Haze pollution, 9, 125–128, 130, 132, 138, 139 Healthy future, 196 Hebei, 41–44, 63, 82, 83, 86, 88, 89, 106, 127, 178, 180, 181 Heterogeneity, 10, 173, 175, 181, 182, 184, 186, 309 High-quality, 12, 35, 40, 42, 44, 63, 170, 177, 201, 203, 209, 265, 266, 268, 292, 293, 331, 382, 453, 495, 496, 499 Hong Kong, 31, 101, 103, 109, 180, 197, 399 Horton equation, 277 Hubei, 82, 84–86, 104 Human-nature, 485, 494, 497 Hydrological, 8, 97–99, 101, 103–109, 113, 119, 120, 267, 268, 271, 275, 278, 287, 292, 398, 403, 404, 413, 418

510 I Impervious, 60, 176, 177, 180, 230, 234, 235, 242, 277, 278 Index system, 46, 139 Industrialisation, 60, 62, 63, 140, 191–193, 269, 301 Industrial park, 39, 204 Infiltration, 35, 76, 99, 101, 113, 202, 277, 354, 355, 357, 404, 413 Information and Communication Technologies (ICT), 378, 499 Inner Mongolia, 31, 82, 181, 184, 186 Institutionalisation, 48, 64, 139, 140 Interactivity, 154 Interchangeability, 5, 499 Internet of Things (IoT), 378, 379, 385, 386, 389, 390 InVEST, 15, 151, 318, 326, 495 IoT-enabled, 379, 386, 389 Irrigation, 45, 113, 149, 152, 197, 378, 386, 432, 436, 437, 441, 450, 457, 460, 463, 472 Ivy, 451, 452, 458, 463

J Jiangsu, 83, 84, 86–88, 105, 299, 304, 306 Jilin, 31, 82, 104, 181

K Key Performance Indicator (KPI), 207, 268, 269, 274, 275, 279–286, 290–293, 477, 496 Koelreuteria elegans, 432 Kyoto, 194

L Laixi, 33 Landscape design, 118, 155, 159, 161, 166, 169, 175, 274, 290, 292, 303, 328, 351 Landscape fragmentation, 318 Legalisation, 47, 139 Liangnong, 12, 265, 268–270, 276, 277, 293 LID facility, 271, 274, 417 Lifecycle, 13, 381, 388, 397, 421, 424, 426, 427, 497 Life cycle management, 402, 403 Life support, 22, 25 Livable city, 33, 42, 139, 192 Living space, 304, 324, 449, 482

Index Low-carbon, 15, 35, 37, 39, 47, 204, 467, 468, 471, 474–476, 482, 485, 497 Low-Impact Development (LID), 8, 27, 35, 36, 76, 97, 100, 101, 111, 275, 277, 278, 398, 413, 417 M Machine learning, 13, 377–382, 385, 388, 389 Man-made, 210 Maritime, 37, 38 Maryland, 26, 300 Masdar, 200 Master plan, 32, 42, 61, 116, 120, 197–199, 201, 206, 210, 228, 306, 358, 473, 474, 483 Meadow, 359–361 Meta-database, 401 Micro-climate/Microclimate, 2–4, 140, 174, 198, 433, 493 Microgreen, 204 Ministry of Environmental Protection (MEP), 207, 474, 475 Ministry of Finance (MoF), 474, 475, 478 Ministry of Foreign Affairs (MFA), 480, 481 Mobile Apps, 177, 178, 379, 381, 390 Mobilisation, 469 Mobility, 175, 199, 231, 232, 236, 244, 248, 351 Model city, 129, 139, 192 Modernisation, 15, 204, 324, 384, 390, 467, 469, 479, 483 MoHURD, 36, 48, 75, 77, 78, 84, 102, 109, 114, 116, 207, 281, 399, 413, 418, 474–477 Monumental, 56 Morning glory, 451, 458, 463 Morphological Spatial Pattern Analysis (MSPA), 12, 299, 307, 308, 339–341 Mosaic, 348, 350, 354, 355 MS4web, 398 Multi-functionality, 12, 15, 204, 206, 216, 268, 292, 323, 331, 335, 467, 480, 485 Multi-objectivity, 3 Municipal government, 56, 59, 103, 112, 117, 119, 120, 202, 205, 474, 476, 477 N Nanning, 106, 437

Index National congress, 33, 34, 40, 41, 48, 58, 62, 63, 78, 330, 473, 474 National Development and Reform Commission (NDRC), 37, 77, 84, 474, 475 Natural purification, 35 Natural resource system, 22 Nature-based design, 267 Nature-Based Solutions (NBS), 3, 7, 11, 13–15, 56, 63, 69, 100, 101, 265, 266, 349, 429–433, 435–437, 440, 441, 446, 447, 454, 457, 462–464, 467, 469, 472, 479–485, 494, 497, 498, 500 New-Type Urbanisation (NUP), 35, 332, 473 New York, 29, 330 NGOs, 479, 483 Ningbo, 8, 98, 99, 107, 112–118, 120, 268–270, 276–279, 281, 282, 286, 289, 293, 358 Ningxia, 31, 79, 82, 108, 140, 184, 186 O OpenMP acceleration technology, 415 P Park, 22–24, 26, 29, 30, 33, 45, 56–63, 83, 102, 127, 130, 133, 135, 136, 147, 151, 153–159, 163, 166, 167, 174, 194, 195, 197, 201, 206, 210, 224, 229, 235–237, 242, 243, 247, 259, 269–271, 289, 303–305, 307, 311, 328, 330, 331, 335, 345–348, 350, 351, 355–357, 359, 377, 378, 389, 399, 400, 417, 425, 480–482 Patch, 60, 63, 154, 236, 300, 304, 305, 308, 309, 311–313, 316, 336–339, 341, 346, 348–352, 354, 355, 357, 359, 499 Path simulation, 341 Pearl River Delta, 32, 98, 127, 180, 182 People-centered, 11 Periphery, 145–148, 151, 160, 165, 168, 303, 306 Permeable pavement, 267, 271, 274, 277, 347, 355, 357, 417, 425, 476, 479 Photosynthesis, 432 Physical landscape, 199 Piecemeal, 6, 55, 57 Pilot, 8, 15, 34, 35, 37, 83, 98, 102–104, 107, 109, 117, 119, 195, 196, 201,

511 205–207, 210, 216, 266–270, 277, 398, 399, 402, 413, 415, 417, 418, 420–425, 467, 468, 474–478, 482, 485, 492, 495 Point-line-network, 32 Point of Interest (POI), 230, 236 Polarisation, 477 Policy-maker, 56, 477, 500 Political revolution, 471 Pond, 22, 43, 57, 99, 101, 102, 113, 118, 167, 199, 205, 206, 305, 346–348, 436 Project Lifecycle Management (PLM), 421, 424 Project management, 402, 420, 425 Protocol, 109, 114, 253, 495 Publicity, 45, 57, 129 Public open space, 24, 169 Public-private partnership, 118, 478 Public realm, 12, 13, 323, 363, 469, 496 Public square, 327, 351 Q Qingdao, 33, 107 Qinghai, 79, 82, 108 Quali-quanti, 229, 259 R Rainfall, 102, 109–111, 114, 116, 117, 120, 184, 269, 277–279, 286, 287, 293, 355, 357, 385, 403–405, 408, 410–413, 415, 417–421, 423, 425, 441, 450 Rain garden, 27, 267, 271, 274, 275, 277, 348, 355, 357, 425 Reform, 8, 37, 38, 40, 70, 73, 74, 94, 109, 153, 191, 192, 325 Refurbishment, 14, 429, 430, 432, 435, 441, 445–451, 453, 455, 459, 463, 464, 497 Regulatory, 7–9, 43, 69, 70, 72, 73, 92–94, 143, 145, 159, 224, 325 Renewable, 37, 197, 198, 200, 207, 434, 435, 442, 470, 499 Renewal, 11, 59, 102, 159, 265, 293, 326, 328, 345, 349, 350, 495–497 Renhe Village, 437–441, 443, 447, 448, 463, 464 Renovation, 33, 168, 206, 435, 482 Robotics, 378, 379, 384, 385, 390 Roof greening, 7, 69, 73–77, 82–89, 91–93, 157, 347, 437

512 Run-off , 412

S Sand storm, 60, 62 Sanitation, 2, 47, 70, 119, 328 Sanya, 108, 474 Scientific-technical, 407, 493, 496, 497 Seattle, 26 Self-reliance, 57 Sensor, 378, 379, 381, 382, 384–390, 403 Sensory device, 378, 386, 388, 389 Sensory technology, 386 Service function, 22, 140, 315 Sewage treatment, 39, 47, 207 Shandong, 30, 31, 33, 34, 48, 83–88, 93, 104, 107, 181, 299, 304, 306 Shanghai, 11, 61, 82–86, 88, 99, 107, 146, 160, 180, 183, 196–198, 204, 208, 211, 212, 223, 228–238, 241–244, 247, 248, 251, 253, 254, 258, 259, 261, 278, 335, 474, 477, 478, 482, 483 Shannon diversity index, 309 Shanshui, 139 Shanxi, 31, 84, 86, 88 Shenzhen, 13, 89, 93, 98, 99, 107, 117, 194, 196, 200–202, 204–211, 215–217, 397–399, 402, 418, 421, 425, 427, 482 Sichuan, 84, 106, 341 Silk road, 37, 38, 468 Siming, 12, 265, 268, 269, 271, 289, 292, 293 Simulation, 13, 14, 278, 286, 287, 289, 292, 317, 389, 397, 398, 402, 407, 414, 415, 417–422, 427, 429, 435, 464, 497 Singapore, 33, 100, 101, 109, 199, 204, 205, 207, 208, 398, 436, 474 Sino-Singapore, 196, 468, 474 Sino-Singapore Tianjin Eco-City (SSTEC), 199, 200, 204–208, 210, 211, 213, 216, 468, 474, 475, 477, 478 Smart farming, 378, 379, 381, 386, 388–391 Smart technologies, 13, 377–379, 389–391, 496–498 Smog, 9, 125–128, 130–134, 136–139 Social-Ecological-Technical Systems (SETS), 470, 472 Social exclusion, 477 Social participation, 29

Index Social vibrancy, 196, 210, 217 Societal wellbeing, 2, 499 Socio-ecological, 470–472, 480, 481, 484 Socio-spatial polarisation, 477 Socio-technical, 470–472, 479, 497 Songdo, 194 South Korea, 61 Spatial planning, 28, 196, 209, 317, 331–334, 363, 496, 499 Spatial routing, 261 Sponge city management, 13, 14, 397, 399 Sponge city programme, 6, 15, 266, 378, 475, 477, 495 Sponge node, 11, 12, 265, 496 State Council, 34–36, 42, 46, 60, 73, 74, 77, 83, 110, 128, 156, 194, 332, 468, 473, 474 State-owned, 476 STORMTANK, 398 Stormwater management, 24, 26, 27, 100–102, 114, 266–268, 398, 413–415, 450, 482, 497, 498 Storm Water Management Model (SWMM), 12, 265, 268, 269, 275, 277, 278, 280, 286, 289, 290, 292, 415 Structural, 75, 78, 308, 337, 357, 431, 449, 450, 452, 455, 470, 484, 485 Subsidies, 7, 70, 84, 86–89, 93, 478 Subtropical zone, 451 SunS, 3, 11, 174, 233, 254, 261, 265, 274, 279, 280, 286, 430, 481, 482, 493 Sustainability-oriented, 468, 477–479 Sustainability-themed, 473, 475, 485 Sustainable development agenda, 39, 194, 497 Sustainable Development Goals (SDGs), 70, 469 Sustainable Development Zone (SDZ), 191, 194–196, 200, 201, 203–209, 211, 216 Sustainable Urban Drainage Systems (SUDS), 8, 97, 398 Symbiotic system, 37 Systematic, 10, 22, 26, 36, 61, 64, 173, 205, 207, 210, 229, 248, 250, 253, 354, 403, 405, 432, 498

T Tai’an, 33 Taiwan, 31, 103, 432 Taohua River, 203

Index Taxonomy, 13, 224, 225, 231 Technical guide, 7, 35, 36, 69, 76–80, 82–85, 93, 266, 408, 476 Technical-infrastructural, 472 Technical specification, 76, 78, 82, 93, 418 Technologies, 13, 15, 26, 28, 29, 34, 36, 43, 64, 75, 76, 78, 98, 111, 118, 126, 131, 136, 166, 200–202, 205, 208, 268, 293, 358, 377, 378, 381, 382, 384–391, 397, 398, 427, 432, 446, 470–472, 475, 476, 479, 482, 483, 496, 499, 500 Temporal, 10, 165, 173, 175, 176, 178–180, 185–187, 418, 420 Tencent, 177, 178, 201 Terrace, 438, 444 Tianjin, 33, 40, 41, 43, 56, 60, 82, 84, 100, 107, 127, 140, 178, 180, 181, 183, 196, 199, 204, 205, 208, 210, 211, 213, 216, 468, 474 Tibet, 79, 82 Time fluctuation, 134, 260 Tokyo, 101, 109, 126 Transformation, 7, 8, 55, 64, 97, 98, 100, 114, 120, 139, 140, 166, 167, 195, 227, 271, 318, 470, 481 Trial, 35–37, 59, 61, 177, 203, 216, 474 Tuohe Scenic Belt, 311

U United Nations, 70, 92, 194, 200 Unmanned Aerial Vehicle (UAV), 277, 382–386, 389, 390 Urban double repairs, 475, 482 Urban ecologies, 127, 196, 495 Urban fabric, 192, 206 Urban forest, 6, 7, 43, 55–58, 60–65, 99, 126, 127, 137–139, 195, 210, 480, 495 Urban governance, 15, 467, 469, 472, 473, 484 Urban greening, 6–9, 45, 55–60, 62, 64, 65, 69, 70, 72, 73, 77, 81–84, 86–89, 93, 125, 137, 143, 145, 149, 151, 153–157, 159, 161, 168, 495, 496, 499 Urban green space, 6, 9, 25, 30, 36, 45–47, 55–61, 63, 74, 75, 77, 78, 138, 143, 145, 149, 153, 154, 156–159, 170, 198, 210, 231, 235, 236, 240, 300, 303, 304, 306, 309, 339, 345, 346 Urban green system plan, 56, 61, 159

513 Urban health, 2, 3, 499 Urban heat island, 4, 25, 60, 61, 70, 74, 75, 77–79, 92, 101, 109, 140, 398, 431 Urbanism, 15, 16, 100, 197, 216, 217, 260, 331, 390, 493 Urban landscape, 6, 55, 56, 58, 59, 63, 64, 78, 83, 84, 93, 127, 176, 328 Urban sustainability movement, 469, 476 Urban territory, 9, 143, 144, 146, 163 Urban transition, 4, 7, 55, 64, 495

V Variegated environment, 477 Vegetation, 8, 14, 56, 59, 61, 70, 71, 97–100, 113, 118, 155, 157, 160, 161, 163, 166, 168, 174, 176, 177, 180, 182, 184–186, 197, 199, 202, 203, 224, 278, 289, 351, 353, 403, 429, 431–433, 435–442, 444, 445, 447–451, 455, 457, 459, 461–464, 493 Vegetative swales, 271, 274, 277 Veranda, 451, 454, 455 Vertical greening, 73–75, 77, 83, 84, 89, 93, 347, 431, 437, 442, 445, 450–453, 455–458, 480 Vertical Greening Systems (VGS), 431, 432 Voluntary, 72, 78, 154, 165

W Wales, 145 Water conservation, 25, 110, 311, 314, 481 Waterlogging, 99, 104, 107–112, 120, 399, 402–404, 412–414, 417–421, 423, 427 Water pollution, 22, 25, 73, 79, 118, 203, 266, 355, 403, 405, 419 Water quality, 44, 109, 114, 119, 202, 207, 208, 217, 268, 269, 275, 281, 353, 355, 402–405, 411, 413–415, 417, 419, 422, 425, 427 Water treatment, 115, 195, 405, 432, 433, 499 Weed, 378, 381, 478 Weifang, 33 Wetland, 22, 26, 29, 32, 43, 99, 101, 102, 110, 113, 118, 153, 195, 197, 199, 201, 205, 206, 216, 224, 269, 270, 289, 293, 303, 304, 309, 346, 347, 351–353, 355, 432, 481, 498 Wireless, 386, 389

514

Index

Woodland, 56, 64, 110, 201, 224, 305, 331, 346, 359, 377

Y Yangtze River Delta, 22, 127, 180 Yongcheng, 12, 299–301, 303, 304, 306–318

X Xi Jinping, 6, 21, 34, 37, 42, 63, 266, 332 Xinjiang, 79, 82, 181, 186 Xiong’an, 6, 21, 24, 40–44, 48, 63

Z Zhejiang, 34, 82–89, 105, 107, 358 Zhengzhou, 89, 93, 147, 183 Zhou Dynasty, 22