Towards a Carbon Neutral Future: The Proceedings of The 3rd International Conference on Sustainable Buildings and Structures (Lecture Notes in Civil Engineering, 393) 9819979641, 9789819979646

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Lecture Notes in Civil Engineering

Konstantinos Papadikis · Cheng Zhang · Shu Tang · Engui Liu · Luigi Di Sarno   Editors

Towards a Carbon Neutral Future The Proceedings of The 3rd International Conference on Sustainable Buildings and Structures

Lecture Notes in Civil Engineering Volume 393

Series Editors Marco di Prisco, Politecnico di Milano, Milano, Italy Sheng-Hong Chen, School of Water Resources and Hydropower Engineering, Wuhan University, Wuhan, China Ioannis Vayas, Institute of Steel Structures, National Technical University of Athens, Athens, Greece Sanjay Kumar Shukla, School of Engineering, Edith Cowan University, Joondalup, WA, Australia Anuj Sharma, Iowa State University, Ames, IA, USA Nagesh Kumar, Department of Civil Engineering, Indian Institute of Science Bangalore, Bengaluru, Karnataka, India Chien Ming Wang, School of Civil Engineering, The University of Queensland, Brisbane, QLD, Australia Zhen-Dong Cui, China University of Mining and Technology, Xuzhou, China

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Konstantinos Papadikis · Cheng Zhang · Shu Tang · Engui Liu · Luigi Di Sarno Editors

Towards a Carbon Neutral Future The Proceedings of The 3rd International Conference on Sustainable Buildings and Structures

Editors Konstantinos Papadikis Xi’an Jiaotong-Liverpool University Suzhou, Jiangsu, China

Cheng Zhang Xi’an Jiaotong-Liverpool University Suzhou, Jiangsu, China

Shu Tang Xi’an Jiaotong-Liverpool University Suzhou, Jiangsu, China

Engui Liu Xi’an Jiaotong-Liverpool University Suzhou, Jiangsu, China

Luigi Di Sarno Department of Civil Engineering and Industrial Design University of Liverpool Liverpool, UK

ISSN 2366-2557 ISSN 2366-2565 (electronic) Lecture Notes in Civil Engineering ISBN 978-981-99-7964-6 ISBN 978-981-99-7965-3 (eBook) https://doi.org/10.1007/978-981-99-7965-3 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 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 Paper in this product is recyclable.

Contents

Green Building Design and Engineering A Comprehensive Review on Design Approaches of Adaptive Photovoltaic Façade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jiaxin Liang and Changying Xiang

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BIM, IoT, and Big Data Integration Framework in the Green Building Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Guofeng Qiang, Shu Tang, Jianli Hao, and Luigi Di Sarno

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Assessing the Energy Performance of Low-Rise Modularised Lightweight Steel-Framed Residential Buildings in China: Case Study of a Shanghai Suburb . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Y. Yang, M. Cimillo, J. Hao, D. Chow, P. S. Yap, and H. Zhang Energy Efficiency Optimization of Different Curved Building Integrated Photovoltaic (BIPV) Façades by a Parametric Shape Design Method: A Cross-Region Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shaohang Shi, Yehao Song, Weizhi Gao, and Yingnan Chu Embracing Local Biodiversity in Sustainable High-Rise Facades in Subtropical China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Herr, C. Li, M. Yan, and Y. Zhou AI-Based Models in Support of Human-Centric Indoor Environment Design: Towards Climate-Adaptive Façade Design Integrating Occupant Satisfaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Y. Zhou, C. M. Herr, and J. Y. Tsou Consideration on Carbon Emission of Existing Buildings in the Stage of Ultra-Low Energy Consumption Reconstruction . . . . . . . . Xiu Han and Jinghua Shen

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Analysis of Energy Saving of Building Envelope in Hot Summer and Cold Winter Region—Take an Office Building as Example . . . . . . . . Xiaoyi Zhang and Fuxia Zhang An Experimental Study on the Effects of Temperature and Humidity Levels on Human Thermal Comfort During Running . . . . Qinchen Yuan, Junjia Zou, Nuodi Fu, Luyao Guo, Jiabao An, Zhiyuan Chen, Fucheng Long, and Long Huang

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Study on the Design of Interior Lighting for the Environmental Satisfaction of Patients in Wards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Man Zhang, Shuya Zhang, and Qichao Ban Modular Façade Retrofit with Integrated Photovoltaics-Current Status and Future Development Demands . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Wanting Wang and Changying Xiang Study on the Synthetic Action of Environmental Factors on the Work Stress of Medical Staff . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Shuya Zhang, Man Zhang, and Qichao Ban Assessing Economic, Social and Environmental Implications of Implementing Sustainability in the Built Environment . . . . . . . . . . . . . . 141 C. S. Goh and Shamy Y. M. Chin The Impact of the University Built Environment on Students’ Mental Health and Well-Being: A Systematic Review . . . . . . . . . . . . . . . . . 153 Yuanyuan Wang, Yuyan Zhang, Xingyu Huang, Ziteng Zhou, and Marco Cimillo Integration of Unmanned Aerial Vehicles and Infrared Thermography in Building Energy Modelling: A Review . . . . . . . . . . . . . . 161 M. Jin, M. Cimillo, H. Chung, and D. Chow Fatigue Prediction of Attached Lifting Scaffolding Guide Rails Based on Midas Gen/Abaqus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Fan Fei Circular Economy and Sustainable Development Research on Energy-Saving Technology of High Efficient Recycling and Ladder-Form Utilization of Mid- and Low-Temperature Waste Heat in Large Hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Jun Luo, Quan Wang, and Dong Zhang Drivers of Circular Economy Adoption in the South African Construction Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 O. K. Otasowie, C. Aigbavboa, P. Adekunle, and A. Oke

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Challenges to Circular Economy Adoption: South African Built Environment Professionals’ Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 O. K. Otasowie, C. Aigbavboa, P. Adekunle, and A. Oke Designing Out Waste: A Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . 217 Mia Tedjosaputro Sustainability Assessment Practices in the Construction Industry: The Untold Story of South Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 M. Ikuabe, C. Aigbavboa, and E. Oke Research and Practice of Energy Saving Renovation Technology for Multi-zone Collaborative Network Operation of Central Air Conditioning Water System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 L. Z. Yang, Q. Wang, and J. Luo Application of Circular Economy in Facility Maintenance and Management: Moving Towards a Low Carbon Future . . . . . . . . . . . . 249 Qi Wu Sustainable Urbanism and Architecture Study on Sustainable Urban Block Form for Urban Ventilation—Nanjing as an Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261 L. Yao, X. X. Yan, Z. K. Wu, Y. Shi, and B. Wang Crack Detection of Masonry Structure Based on Infrared and Visible Image Fusion and Deep Learning . . . . . . . . . . . . . . . . . . . . . . . . 275 Y. M. Lu, H. Huang, and C. Zhang Generating Social Sustainability Through Placemaking: A Study of Everyday Lived Space in Basha Miao Settlement . . . . . . . . . . . . . . . . . . . 285 Yuan Xiong and Zhuozhang Li Study on the Design Method of Urban Renewal Based on Carbon Emissions and Carbon Sinks Calculation: A Case Study of Environmental Improvement Project of Suzhou Industrial Investment Science and Technology Innovation Park . . . . . . . . . . . . . . . . . . 297 L. Zhang, Y. Q. Cai, S. D. Song, and L. L. Sun Implementation-Oriented Renewal Planning of Suburb Townlet in South Jiangsu: A Case Study of Zhangpu Old Town in Kunshan . . . . . 311 H. T. Wang, S. Q. Gao, and W. Z. Lu Research on ‘5–10–15 Minutes Life Circle’ Planning in Urban Boundary Based on Landscape—Led Method—A Case Study in Beiqiao Town, Xiangcheng District, Suzhou . . . . . . . . . . . . . . . . . . . . . . . . 325 Lingyi Xiang, Shuyi Wang, and Liuxiulin Zou

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Retrofitting the Old Residential Communities to Save Energy, Reduce Carbon Emissions, and Improve the Microclimate: A Case Study of Panmen Residential Neighbourhood in Suzhou, China . . . . . . . . 345 X. Chen, S. Deng, B. Chen, and M. Cimillo Water Quality Inversion of UAV Multispectral Data Using Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357 L. Fu, Y. Lo, T. C. Lu, and C. Zhang Green Open Spaces as Catalysts of Culture-Led Urban Regeneration: Case Study of Yuyuan Cultural Heritage Neighborhood, Shanghai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 Jiemei Luo, Izzy Yi Jian, Edwin H. W. Chan, and Weizhen Chen Digital Oriented Museum Design Based on Collective Memory—Case Study of Bache Old Town . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 Y. T. Liu, Y. W. Q. Liu, G. S. Y. Liu, and J. Xia Heritage BIM for Sustainable Development Based on 3D Reconstruction and Semantic Enhancement . . . . . . . . . . . . . . . . . . . . . . . . . . 389 Y. Wang, H. Gao, Y. Dong, and C. Zhang Review on Ventilation Efficiency and Planning of Urban Blocks in the Context of Carbon Neutrality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 X. Y. Liu, B. Wang, Y. T. Qian, J. Z. Li, and Z. J. Xue How Sea Level Rise Impacts the Economy: A Study on Elevation’s Impact on Property Value Growth in Pinellas County, FL, USA . . . . . . . . 411 Wentao Shen Exploring the Role of NGOs in Rural Revitalization of Jiang Village . . . 425 Junyan Zhou and Ying Chang Greening the Public Realm: Incorporating Bio-Diversity into City Spaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 437 Y. Q. Xu, W. Dai, and T. Heath Indoor Thermal Comfort Prediction Model for Patients in Rehabilitation Wards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451 Puyue Gong, Yuanzhi Cai, Bing Chen, Cheng Zhang, Spyros Stravoravdis, and Yuehong Yu Deep Learning-Based Semantic Segmentation and 3D Reconstruction Techniques for Automatic Detection and Localization of Thermal Defects in Building Envelopes . . . . . . . . . . . . 467 X. Y. Yan, H. Huang, and C. Zhang

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Smart Construction Engineering and Management Methods of Managing Construction Information in the Fourth Industrial Revolution Era . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 Peter Adekunle, Clinton Aigbavboa, Opeoluwa Akinradewo, Kenneth Otasowie, and Samuel Adekunle Incorporating Cryptocurrency Platforms for Advancing Financial Transaction Within the Construction Industry . . . . . . . . . . . . . . . . . . . . . . . 491 Peter Adekunle, Clinton Aigbavboa, Opeoluwa Akinradewo, Kenneth Otasowie, and Samuel Adekunle Semantic Enhanced Segmentation Based on Thermal Images with Superpixel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499 Y. Xu, H. Huang, and C. Zhang Data Representation and Information Exchange of Large-Scale Solar PV Power Plant Harness Using Open BIM Standards . . . . . . . . . . . 511 J. Q. Liang and S. Tang Towards a Conceptual Framework of Construction Waste Management to Support Sustainable Development: The Case of Smart Integrated Construction System (SICS) . . . . . . . . . . . . . . . . . . . . . 523 Y. X. Wang, Y. T. Liang, H. Z. Li, and J. L. Hao Information Requirement Analysis for Establishing BIM-Oriented Natural Language Interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 531 Mengtian Yin, Haotian Li, Zhuoqian Wu, and Llewellyn Tang An Automatic Attribute Data Encoding Method for Prefabricated Structural Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541 Y. J. Zhang and S. Tang Holistic Review of Research on Off-Site Construction (OSC): A Three-Step Holistic Summary Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 551 Y. H. Han, X. Y. Zhao, X. Y. Zhang, and J. Liu PAR-Based Architectural Pedagogy: A Case Study of Gridshell Design and Built Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 567 Y. Chen, Z. Chen, D. Lin, L. Sun, and S. Wang Structural Assessment Methods for Architectural Façade Elements in Cross-Disciplinary Collaboration Between Architects and Structural Engineers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 581 D. Quan, Z. Gao, C. M. Herr, D. Lombardi, and J. Xia A Risk Evaluation Index System for Infrastructure PPP Model Based on FAHP Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591 Y. M. Ding, F. Y. Guo, and K. Y. Wang

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Smart Construction Engineering and Management . . . . . . . . . . . . . . . . . . . 603 B. Yang, J. Hao, and W. Ma A Digital Twin (DT) Framework at Design and Construction Phases . . . 615 E. X. Cao, F. Y. Guo, and K. Y. Wang Sustainable Materials and Infrastructure Post-fire Material Response of Structural Aluminum Alloys . . . . . . . . . . . 629 K. Zhang, G. Gong, E. Liu, J. Hu, and Y. Sun Design and Characterization of Architected Cellular Composite Material Embedded with Strain Rate Dependent Foam . . . . . . . . . . . . . . . 641 Xianhua Yao, Qing Dong, Xuanyou Li, and Nan Hu Influence of Manufacturing Factors on the Mechanical Properties of 3D-Printed Soft Architected Composite . . . . . . . . . . . . . . . . . . . . . . . . . . . 651 Zhixiong Li, Tongtong Ye, Xuanyou Li, Qing Dong, Qian Zha, and Nan Hu At-Rest Lateral Earth Pressure on Retaining Walls Under Narrow Backfill Widths . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 661 N. Weng, L. Fan, Y. Fei, C. Zhang, L. Tan, and X. Shen Exploring the Onset of Liquefaction of Saturated Loose Sand Under Monotonic and Cyclic Loading Using DEM . . . . . . . . . . . . . . . . . . . . 673 Minyi Zhu, Guobin Gong, Jun Xia, and Charles K. S. Moy Global Warming Potential Comparison of Lime and Cement-Based Masonry Repair Mortars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 683 L. A. Dickens and L. Di Sarno Properties of Self-compacting Concrete Incorporating Recycled Tyre Rubber Particles—A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 695 R. Zang, B. W. Xu, K. Y. Zhang, and L. Di Sarno Two-Scale Lightweight Optimization by Infilling Optimized Organic Truss-Based Lattice Material Based on the Principal Stress Trajectories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 705 Fuyuan Liu, Min Chen, Lizhe Wang, Zhouyi Xiang, and Songhua Huang A Brief Overview of the Applications and Potentials of Fractal Geometry in Sustainable Structures Design . . . . . . . . . . . . . . . . . . . . . . . . . . 717 Iasef Md Rian Exploring a High Strength Paste with Suitable Rheological Properties for Pervious Concrete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 731 J. Li, J. Xia, L. Di Sarno, and G. Gong

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Investigation of the Compressive Behaviours of Waste-Containing FRP-Confined Concrete Columns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 743 T. E. Dada, G. Guobin, J. Xia, and L. Di Sarno Low Carbon Self-healing Concrete—Mixture Analysis . . . . . . . . . . . . . . . . 759 João M. P. Medeiros and Luigi Di Sarno Architected Lattice-Reinforced Composites for Cementitious Material and Asphalt Concrete Toward Lightweight and Energy Absorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 769 Binglin Xie, Tongtong Ye, Ruitong Tian, Qian Zha, and Nan Hu Application Analysis of Environmental Protection Thermal Insulation Materials in Modern Buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . 779 Rui Zhou Study on Preparation and Polymerization Mechanism of CFB Fly Ash Geopolymer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 791 Z. B. Song, X. Y. Zhang, H. W. Qi, Z. B. Xu, J. W. Liu, J. Zhang, and X. Y. Wang Innovation in Education for Sustainable Development The Environmental Design for Eco Learning Camps for School Children: A Case Study of Changle, Fujian Province, China . . . . . . . . . . . 807 Chenghao Zhu, Qiqi Liu, and Xin Wu A Study of Early-Career Female Faculty’s Perceptions of Their Roles and Responsibilities in Computer Science and Engineering . . . . . . 819 Biying Wen, Qian Wang, Floriana Grasso, Qing Chen, and Juming Shen Pedagogic Strategies for Digitally Enhanced Sustainable Design . . . . . . . 827 G. Di Marco and D. Lombardi A Theoretical Framework of Systematic Pedagogical Design Based on the Principle of Outcomes-Based Education . . . . . . . . . . . . . . . . . . . . . . . 835 T. Jiang and B. Chen

Green Building Design and Engineering

A Comprehensive Review on Design Approaches of Adaptive Photovoltaic Façade Jiaxin Liang and Changying Xiang

Abstract The use of adaptive photovoltaic (PV) facades holds great promise in reducing energy consumption, harvesting clean solar energy on site, and optimizing indoor climate. To improve building facade performance, various design methods have been employed at both the city and building scale to optimize PV facade parameters and geometry. However, while prior studies have focused mainly on technical aspects such as PV energy performance and adaptive technologies, few have systematically investigated design methods of adaptive PV facades, particularly from an architectural or city design perspective. This literature review aims to address this gap by qualitatively analyzing applications of adaptive PV facades at both scales, discussing prevalent design methods and their effectiveness, and analyzing cuttingedge research in related fields. The review emphasizes three major aspects of adaptive PV facade design: energy efficiency, human comfort, and aesthetics. Additionally, the study evaluates the contributions and limitations of optimized design methods in selected papers, identifies research gaps in adaptive PV facades, and provides guidance for future research in this area. Keywords Adaptive photovoltaic (PV) facades · Energy efficiency · Design methods · Human comfort

1 Introduction The global building sector is a significant contributor to both final energy consumption and carbon emissions, accounting for 30–40% of the former and emitting 40% of total carbon dioxide through direct and indirect means. If current trends in energy usage and emission intensity persist, the building sector’s share of carbon emissions is predicted to surge to 50% by 2050 (Liu et al. 2019). Reducing greenhouse gas emissions while meeting the increasing demands for energy consumption in the building sector is a significant challenge. This is particularly true in super-dense metropolises, J. Liang · C. Xiang Division of Integrative Systems and Design, School of Engineering, The Hong Kong University of Science and Technology, Hong Kong, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_1

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where buildings are the primary energy consumers. To address these challenges, promoting energy-efficient solutions is crucial, and the urgent implementation of clean energy systems is also necessary (Zou et al. 2021). To enhance the energy efficiency of buildings, building envelopes are the essential study objects that should be addressed (Mohtashami et al. 2022; Monteleone et al. 2021). Meanwhile, building envelopes have a strong impact on the interior climate, such as indoor light comfort, visual comfort and thermal comfort. Due to the influence of the ever-changing outdoor climate, it is challenging for traditional static building envelopes to provide ideal indoor climates throughout the day and different seasons of the year. Therefore, there is a growing interest among architects—to use dynamic or climate adaptive façade, which can respond to the external environment while meeting the comfort needs of internal occupants (Loonen et al. 2013). As one of the most promising solutions to harvest clean solar energy onsite, building integrated photovoltaics (BIPV) has been applied in adaptive façade design recently (Pillai et al. 2022). The adaptive PV facade technologies present an idea that the building façade can adapt to real-time to the external climatic conditions; respond to dynamic needs of the interior occupants; meet the visual and aesthetic needs (Heidari Matin and Eydgahi 2019); reduce the buildings’ energy consumption (Aelenei et al. 2016) and generate clean electricity. Based on the author’s review of literature related to adaptive PV facades, it was discovered that the majority of studies focused on two fundamental scales, the building scale and the city scale. Research on advanced technological details predominantly centered on a minor scale, specifically single buildings or building facade details. In contrast, another segment of research focused on the application prospects of adaptive PV facades at the urban scale. In the context of this paper, the term “building scale” refers to research conducted on individual buildings or building facades detailing design, with the remaining studies examining the city scale. The adaptive PV facade is gaining attention in the academic field as a promising development for building envelopes. However, there is a gap in the literature regarding a comprehensive review of adaptive PV facade design methods from building and city design perspective. This study aims to fill this gap by collecting and evaluating academic papers on adaptive PV facades to identify promising future research areas and provide targeted recommendations for researchers and designers. This review aims to answer two main questions: (1) What are the promising methods supporting the design and applications of adaptive PV façades? (2) What are the differences and similarities between the design approaches for adaptive facade at city and building scales? The review is structured into five parts. Section 1 presents the introduction and objectives of this study. Section 2 presented the literature review methods and the specified study boundaries, then the study results of adaptive PV façade design methods are presented in the Sect. 3. The discussion with the study results is presented in the Sect. 4, and finally, Sect. 5 demonstrates a summary of the entire study.

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2 Methodology This study aims to investigate the design methods of adaptive PV façades at both the urban and building scales, exploring the similarities and differences in design approaches and evaluating existing methods. The study also identifies limitations in current design methods and discusses directions for future research from urban and architectural design perspectives. Four steps were taken to conduct the review, as shown in Fig. 1. In the first step, a large-scale literature search was conducted using keywords such as “PV facade” and “adaptive façade” to identify relevant scientific works published between 2014 and 2022. In the second step, the author established study boundaries to ensure a meaningful review of the two disciplinary domains, with the aim of ensuring that only those works that were relevant and germane to the research objectives were selected. This process resulted in the selection of 24 studies for in-depth analysis and further research. The third step involved analyzing the selected literature from both urban and building scales, categorizing the key focusing aspects of current adaptive PV façade studies. In the final step, the design methods of adaptive PV façades were compared based on the summarized focusing aspects to identify opportunities and constraints of existing design methods.

Fig. 1 Steps of the methodology for the literature review

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3 Design Methods Following the aforementioned methodology, the following section shown the included research was thoroughly analyzed based on 3 determined aspects, which were carefully examined and sorted into categories, according to the thematic focus, the findings and assertations presented in the studied articles. Three determined aspects of this study included energy performance, human comfort, and aesthetic, these were key elements as well as objectives of adaptive PV façade design which need to be considered at both city and building scales.

3.1 Design Methods at City Scale 3.1.1

Energy Performance

Even though this review cannot fully exhaustive, it can be concluded that most of literature of adaptive PV façade with city scale focus on the solar potential and solar energy generation. As shown in the Fig. 2, it describes a three-steps framework for estimating the energy performance of adaptive PV façade which was applicable to most studies. Main steps include (1) Input data; (2) Data processing; and (3) Solar potential simulation and recommendations. In many studies, both geographic and climatic data of the study subjects are used as necessary inputs to generate solar energy acquisition in the first step. The input data consists of urban contextual information, which is defined as the design elements that influence the building’s energy performance, such as the street network, vegetation, building footprint, and more. It is worth mentioning that architectural details, such as windows, balconies, cornices, and canopies, along with other buildinglevel data, significantly affect the overall solar potential results on a city-wide scale (Saretta et al. 2020). A study conducted in the Norwegian context by Lobaccaro et al. (2019) presented a solar planning approach for communities by optimizing

Fig. 2 General framework for estimating the energy potential of adaptive PV façade in city scale

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building layout and architectural form while considering overshadowing effects and solar-interbuilding reflections. Another research conducted in the Swedish context by Kanters and Wall (2014) showed that building density was the most influential parameter on solar energy harvest in typical building blocks in Sweden. A study by Machete et al. (2018) claimed that both building surroundings and topographic relief could significantly influence a building’s solar potential, and the absence of consideration of urban surroundings could lead to a 30% deviation in simulation results. The second step involve the use of different data processing tools and algorithms for different design purpose. (Machete et al. 2018) applied 2.5D and 3D GIS approaches as the assessment tool to estimate the incident solar radiation on buildings’ roof and façade of a downtown block located in the Lisbon. This study aims to compare the impact of levels of precision according to the two approaches and used three different tools. For the 2.5D approach, the study applied the Incident Solar Radiation (ISR) in ArcGIS software. For the 3D approach, the Incident Solar Radiation (ISR) and Solar Exposure Graph (SEG) were used and implemented in ECOTECT software. This study demonstrated how 3D tools can be used to study the solar potential of cities on a larger scale, and more effective and accurate than the 2.5D approaches. A TU Delft team (Zhou et al. 2022) used LiDAR (LightingDetection-And-Ranging) as a tool to collect detailed data to improve the accuracy of building and urban context geographical information during the reconstruction of 3D building models, to generate the annual solar irradiation map on building surfaces within the TU Delft campus. Vulkan et al. (2018) focused on residential block’s electricity generation in Rishon LeZion, Israel, to set up a series of algorithms for assessing the shadows cast on vertical building surfaces or rooftop, to compare the differences in solar energy production for different residential building typologies, therefore, to generate the design suggestions on the installations of PV facades in city scale. Duran et al (2022) investigated the effects of street network pattern on solar energy productions by Rhino and Grasshopper tool to model and compare different districts in the city, which with different morphological characteristics in terms of street network and building density, height, etc. The choice of data processing tools for this step is also determined by the need for different results, for instance, Shirazi et al. (2019) concentrated on the integrated techno-economic evaluation of BIPV system in the city scale based on Python tool which comprise three different algorithms, to create an analysis and design way to prioritize which part of building surfaces can install the PV material, based on the factors of energy production, economic benefits, and carbon footprint reduction. This study helps to give the suggestion to the urban designer, policy maker and investors to choose the most profitable plan of the BIVP installation in the urban areas. The final step of the framework generally leads to solar energy generation and different design recommendations, which including the urban planning guidelines and some photovoltaic technologies allocation recommendations on the building surface. As mentioned above, the detail degree of city contextual data and building information will tremendously influence the solar potential calculation results, and with more specifics are taken into account, the results can vary widely. In terms

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of the form of results presentation, different studies have also presented varied. Many studies resulted in the solar map (Lobaccaro et al. 2019; Zhou et al. 2022), a visualization that represents the amount of solar irradiation received by a building façade with different colors.

3.1.2

Human Comfort

Adaptive PV façades can improve human comfort in urban areas, with studies primarily focusing on their impact on the outdoor environment. In a large-scale simulation of adaptive PV façades in a dense area of Paris, Masson et al. (2014) found a 12% reduction in energy needs for air-conditioning and a decrease in the urban heat island effect by up to 0.3 K at night, and 0.2 K during the day. These findings indicate that deploying solar panels can effectively mitigate the warming of the city climate, particularly in the summer months. A case study by Boccalatte et al. (2020) investigated the impact of climatic and radiation conditions on both the energy demand and supply of a district comprising 11 residential blocks in Rome, Italy, when using PV façade technologies. The study used digital simulations with the EnergyPlus tool and the Sandia model, accounting for PV module temperature, irradiance intensity, and solar incident angles. The study found that (1) Urban Heat Island effects can increase building energy consumption for air conditioning by up to 30%, (2) the PV integrated façade’s energy efficiency is minimally affected by the Urban Heat Island effect with a decrease of only 0.33% in PV energy production, and (3) the darker material of the PV façade reduces the availability of reflected solar energy from the ground and surroundings, potentially reducing the PV façade’s power generation efficiency by up to 37% in the worst-case scenario.

3.1.3

Aesthetic

The integration of adaptive PV façades into urban contexts has presented challenges in maintaining visual harmony with the surrounding environment. The visibility of PV façades is a crucial factor in their acceptance, and Sun et al. (2021) conducted a visibility analysis of PV surfaces using a Grasshopper platform to simulate pedestrians’ visual angles from street-level viewpoints. The study also included a simulation of the solar harvesting potential of building façades, resulting in a visualized map of the most suitable surfaces for PV application. Another study by Lu et al. (2018) investigated the visual impact of PV installations on urban landscapes in different Chinese cities using a combination of quantitative and qualitative research methods, including the Q methodology. The study found that environmental harmony, power generation, innovative design, installation height, and social benefits are the most influential factors in the acceptance of photovoltaic applications in the landscape. Residential and industrial areas are more favorable for PV installation due to their lower visual impact.

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3.2 Building Scale 3.2.1

Energy Performance

Previous research on adaptive PV facades with building-scale energy improvement measures has primarily focused on enhancing specific technologies, such as doubleskin facades (Luo et al. 2017; Wang et al. 2021), dynamic solar shading systems (Jayathissa et al. 2017), and window-integrated ventilated blinds (Iommi 2018), among others. Meanwhile, there are some studies have investigated the impact of geometric design on building energy performance, providing direct design guidance and recommendations to architects, which will be discussed in the following sections. Moreover, the design indicators considered to assess building energy efficiency vary across studies. In order to achieve the zero-energy oriented residential building design goal meanwhile meet the lowest investment, Wu et al. (2022) used the parametric design tool of Grasshopper platform and the Non-Dominated Sorting Genetic Algorithm LL to explores the most efficient architectural design option by reaching the lowest total air-conditioning and heating load, as well as generating the highest solar power when considering the economic return benefits. The study initially to establish the functional relationship between the key design variables with the building’s airconditioning and heating energy load, based on the Grasshopper parametric platform and multiple regression method. After that the study constructed a mathematical model to calculate the photovoltaic power generation and the economics investment cost. Jayathissa et al. (2017) developed a design for adaptive photovoltaic shading facades that utilized a dynamic shading system with a novel hybrid actuator to actively modulate solar radiation, improving energy generation, passive heating, shading, and daylight penetration. The design process involved several simulations and experiments and consisted of five stages. First, radiation simulation was performed on Rhino/Grasshopper with the Ladybug plugin to determine incident insolation on the solar surface. Then, radiation data were coupled with circuit simulation to calculate the electrical losses of the self-shading module. The next step was to calculate building energy demand using a resistor–capacitor model. Lighting modeling was then performed to calculate the luminance of the room based on the total flux method. Lastly, an exhaustive search was conducted to eliminate individual objectives. The design framework was tested on a case study at ETH Zurich, using an adaptive facade composed of 400 mm CIGS square panels. The test results showed that the adaptive PV facade could save 20–80% net energy compared to an equivalent static shading system. A case study (Good et al. 2014) presented an accurate office building’s energy production simulation of PV system by multi-level simulation approaches which included the maximum solar potential calculation, the solar loss due to the shading effect by the surrounding environment, and the overall solar output due to the application of different PV technologies are evaluated in three steps; the first and second

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steps are performed using the DiVA for Rhino tool, and the last step was simulated by PVsyst software tool. A façade assessment and design tool for solar energy (FASSADES) was created in this study to provide the suggestion for stakeholders during the design process, which meanwhile can generate visual images to show the annual solar gain of the building façade, the cost-effectiveness of PV system extrapolate and the payback period.

3.2.2

Human Comfort

Many studies aimed to improve the occupant’s interior comfort by technological improvements or optimization of adaptive PV façade’s parametric design. Based on the analysis and summary of related studies, the enhancements of occupant comfort are mainly based on aspects of indoor thermal comfort, visual comfort, and daylighting performance. Sun et al. (2018) used the raytracing software RAIDANCE to evaluate the annual daylighting performance and optical comfort of a typical office facade design. The study aimed to balance daylight availability (represented by UDI) and comfort level (represented by GDP), and found that semi-transparent PV glazing provided a better indoor daylighting environment than traditional double skin glass while also significantly reducing indoor glare. Several studies have been concentrated on specific PV façade integrated dynamic techniques. The oriental sun responsive shading system has been created (Tabadkani et al. 2018), which can dynamically adjust the façade pattern by an oriental façade system to enhance the visual comfort and daylighting performance. The Grasshopper plug-in for Rhino and daylighting plug-in DIVA were used for simulating the indoor daylight quality under different geometrical configurations and physical properties during the design process. This study applied two geometrical components to simulate the geometrical and motional properties of the shading system, one was the Rosette modules, which has been widely used in Islamic regions known as a classic geometric pattern; and another one was the horizontal shade louvers. The Rosette module was set up as a smart module can rotate in response to the sun position. The study conducted design optimization stage lastly to converge the optimal solution based on the input variables, and 6480 runs were performed by means of Galapagos’ evolutionary algorithm which followed the genetic algorithm principles. Several papers have examined the impact of parametric design on indoor thermal and visual comfort. Rizi and Eltaweel (2021) proposed a user-driven adaptive façade design method that satisfies both optical and thermal comfort. In this study, the algorithm optimization method and the parametric simulation in Grasshopper tool were applied to generate a new design framework which constantly respond to the user’s movements. The study result claimed that the new PV shading system can cause 76% improvement of user’s optical comfort than the conventional shading system. According to the thermal comfort, there was an average 60% and 59% improvement of the renovative PV shading system correspond to the heat gain and cooling respectively. Tabadkani et al. (2019) explored the relationship between surface geometric

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form and visual comfort, generating 1800 design models to create a hexagonal adaptive PV façade system that maximizes visual comfort.

3.2.3

Aesthetic

Despite the growing interest in adaptive PV façade design, few studies have focused on the aesthetic-related effects, especially from an architectural perspective where aesthetics is an essential factor in the design process for architects and occupants alike. One important aspect of PV façade aesthetics is color design. Xiang and Matusiak (2022) conducted an online survey to test aesthetic designs and collect preferences from citizens of Trondheim city. The study proposed a set of evaluation criteria for PV façade designs based on color analysis to ensure harmonious integration of building façades with the urban context. Sánchez-Pantoja et al. (2018) conducted a survey using the Self-Assessment Manikin (SAM) to assess citizens’ perception and acceptance of new building-applied photovoltaic (BAPV) and building-integrated photovoltaic (BIPV) installations. The results indicated that all design prototypes received positive ratings, demonstrating that these new façade techniques can be visually appealing and well-accepted by observers.

4 Discussion This study conducts a comprehensive review of 24 academic research articles from 2014 to 2022 to investigate the design and optimization methods for adaptive PV façades. The study examines design methods at two spatial scales: city and building, and identifies three key elements: energy performance, human comfort, and aesthetics. At the city scale, solar energy potential and general electricity production are estimated through a three-step process involving data input, processing, and solar potential estimation. At the building scale, solar efficiency calculations for adaptive PV envelopes focus on the impact of architectural geometry and technical parameters on power generation efficiency (Mastoi et al. 2022). However, a paucity of practical experimental data in both scales is noteworthy, and few studies have investigated the application of adaptive PV façades in real-world conditions. Hence, future studies should aim to focus on the practical implementation of adaptive integrated PV technologies. Research on human comfort is more prevalent at the building scale than at the city scale, with studies focusing on occupants’ thermal and visual comfort and daylighting performance. Few studies have examined human comfort in urban environments due to the limited application of adaptive PV façades in real scenarios. Consequently, there is a need for comprehensive research on adaptive PV façades at the city scale. Despite the importance of aesthetic features in the design of adaptive photovoltaic (PV) façades, few studies have thoroughly explored this aspect. Current research has

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primarily utilized questionnaires or interviews to investigate the aesthetic preferences of observers. However, the positive findings of these studies suggest that there is potential for increased adoption and integration of adaptive PV façade systems into building design, as they are both functional and aesthetically pleasing. This may lead to more widespread use of sustainable energy solutions, contributing to a more sustainable built environment. Furthermore, the positive public perception of adaptive PV façade installations may encourage further research and development in this field, leading to even more innovative and visually appealing design options.

5 Conclusion In recent years, considerable research activities and dissemination have taken place in the field of adaptive façade and PV façade respectively. Due to the nascent stage of both research fields, there has been a dearth of studies investigating the intersection of the two areas, not to mention from the building or city design methods perspective. In order to address this research gap, this paper undertakes a thorough examination of 24 carefully selected articles from both fields and provides a comprehensive review of design methods in the domain of adaptive PV façades from two basic spatial dimensions, and identifies three key elements - energy efficiency, human comfort, and aesthetics. A summary and evaluation of these research methods can provide guiding support and reference for future researchers interested in studying adaptive PV façade, as well as for designers and occupants who aim to utilize adaptive PV façade technology in practical scenarios. For instance, this paper provides a comprehensive summary of design methods at the city scale and identifies that most studies on the solar potential of building facades can be achieved through three-steps framework, with different simulation software being used depending on the application objectives. In conclusion, this review establishes a theoretical foundation to facilitate the development of design methodologies aimed at promoting the widespread adoption of adaptive PV façades in large-scale energy retrofit projects. In particular, future research should focus on the practical implementation of adaptive integrated PV technologies, the comprehensive investigation of human comfort in urban public spaces, and the exploration of aesthetic features to facilitate the integration of these systems into building design and urban planning.

References Aelenei D, Aelenei L, Vieira CP (2016) Adaptive façade: concept, applications, research questions. Energy Procedia 91:269–275

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Boccalatte A, Fossa M, Ménézo C (2020) Best arrangement of BIPV surfaces for future NZEB districts while considering urban heat island effects and the reduction of reflected radiation from solar façades. Renewable Energy 160:686–697 Duran A, Akgul CM, Dino IG (2022) Impact of urban street network on BIPV generation capacity of buildings. IOP Conf Ser: Earth Environ Sci 1085(1):012009 Good CS, Lobaccaro G, Hårklau S (2014) Optimization of solar energy potential for buildings in urban areas—a Norwegian case study. Energy Procedia 58:166–171 Heidari Matin N, Eydgahi A (2019) Technologies used in responsive facade systems: a comparative study. Intell Build Int 14(1):54–73 Iommi M (2018) The Mediterranean smart adaptive wall. An experimental design of a smart and adaptive facade module for the Mediterranean climate. Energy Build 158:1450–1460 Jayathissa P, Luzzatto M, Schmidli J, Hofer J, Nagy Z, Schlueter A (2017) Optimising building net energy demand with dynamic BIPV shading. Appl Energy 202:726–735 Kanters J, Wall M (2014) The impact of urban design decisions on net zero energy solar buildings in Sweden. Urban Plan Transp Res 2(1):312–332 Liu Z, Zhou Q, Tian Z, He BJ, Jin G (2019) A comprehensive analysis on definitions, development, and policies of nearly zero energy buildings in China. Renew Sustain Energy Rev 114:109314 Lobaccaro G, Lisowska MM, Saretta E, Bonomo P, Frontini F (2019) A methodological analysis approach to assess solar energy potential at the neighborhood scale. Energies 12(18):3554 Loonen RCGM, Trˇcka M, Cóstola D, Hensen JLM (2013) Climate adaptive building shells: stateof-the-art and future challenges. Renew Sustain Energy Rev 25:483–493 Lu M, Lin A, Sun J (2018) The impact of photovoltaic applications on urban landscapes based on visual Q methodology. Sustainability (Switzerland) 10(4):1051 Luo Y, Zhang L, Wang X, Xie L, Liu Z, Wu J, Zhang Y, He X (2017) A comparative study on thermal performance evaluation of a new double skin façade system integrated with photovoltaic blinds. Appl Energy 199:281–293 Machete R, Falcão AP, Gomes MG, Moret Rodrigues A (2018) The use of 3D GIS to analyse the influence of urban context on buildings’ solar energy potential. Energy Build 177:290–302 Masson V, Bonhomme M, Salagnac JL, Briottet X, Lemonsu A (2014) Solar panels reduce both global warming and urban heat island. Front Environ Sci 2:00014 Mastoi MS, Munir HM, Zhuang S, Hassan M, Usman M, Alahmadi A, Alamri B (2022) A comprehensive analysis of the power demand-supply situation, electricity usage patterns, and the recent development of renewable energy in China. Sustainability 14(6):3391 Mohtashami N, Fuchs N, Fotopoulou M, Drosatos P, Streblow R, Osterhage T, Müller D (2022) State of the art of technologies in adaptive dynamic building envelopes (ADBEs). Energies 15(3):829 Monteleone A, Rodonò G, Gagliano A, Sapienza V (2021) SLICE: an innovative photovoltaic solution for adaptive envelope prototyping and testing in a relevant environment. Sustainability (Switzerland) 13(16):8701 Pillai DS, Shabunko V, Krishna A (2022) A comprehensive review on building integrated photovoltaic systems: emphasis to technological advancements, outdoor testing, and predictive maintenance. Renew Sustain Energy Rev 156:11946 Rizi RA, Eltaweel A (2021) A user detective adaptive facade towards improving visual and thermal comfort. J Build Eng 33:101554 Sánchez-Pantoja N, Vidal R, Pastor MC (2018) Aesthetic perception of photovoltaic integration within new proposals for ecological architecture. Sustain Cities Soc 39:203–214 Saretta E, Bonomo P, Frontini F (2020) A calculation method for the BIPV potential of Swiss façades at LOD2.5 in urban areas: a case from Ticino region. Solar Energy 195:150–165 Shirazi AM, Zomorodian ZS, Tahsildoost M (2019) Techno-economic BIPV evaluation method in urban areas. Renewable Energy 143:1235–1246 Sun Y, Shanks K, Baig H, Zhang W, Hao X, Li Y, He B, Wilson R, Liu H, Sundaram S, Zhang J, Xe L, Mallick T, Wu Y (2018) Integrated semi-transparent cadmium telluride photovoltaic glazing

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BIM, IoT, and Big Data Integration Framework in the Green Building Industry Guofeng Qiang, Shu Tang, Jianli Hao, and Luigi Di Sarno

Abstract Building Information Modeling (BIM), the Internet of Things (IoT), and Big Data are widely applied in the green building industry (GBI) due to the fast-paced digital revolution. BIM enables the creation of digital models of buildings, supporting design optimization, construction management, and sustainability assessment. IoT can automatically acquire real-time data on building operations, occupant behavior, and energy consumption through large amounts of intelligent sensors. However, the vast amount of data created and captured by BIM and IoT is only useful with advanced storage and analysis technologies such as Big Data. So far, BIM, IoT, and Big Data integration in the GBI is still in its infancy. Therefore, this research aims to develop a big data based-framework to store and address context-based data from BIM and time-series data from IoT. First, BIM, IoT, and Big Data application in the GBI is presented. Then, the data exchange model of BIM, IoT, and Big Data is demonstrated through the proposed framework. Finally, digital management strategies are provided for decision-makers to improve the energy efficiency of GBI. This framework underpins the knowledge of digital technologies application in the GBI and provides insights for future research domains such as data exchange, smart construction, and energy management. The practical application of the framework can also contribute to GBI’s digital transformation and sustainable development. Keywords Big data · BIM · IoT · Green building · Energy efficiency

G. Qiang · S. Tang · J. Hao Design School, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China e-mail: [email protected] L. Di Sarno School of Engineering, Liverpool University, Liverpool L693BX, UK © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_2

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1 Introduction Green building (GB) strategies have been widely adopted to reduce natural resource depletion and environmental impacts. Digitalization technologies such as Building Information Modeling (BIM), Internet of Things (IoT), and big data have been regarded as major solutions to reduce energy consumption by optimizing and integrating building management systems during the whole building lifecycle. BIM is defined as a digital representation of the physical and functional characteristics of a building. It aims to provide a shared centralized information platform to manage the building efficiently (Lu et al. 2017). IoT can support the construction of the platform by collecting real-time data from a large number of sensors and actuators. The three-level layers of IoT architecture are widely used: the perception layer, network layer, and application layer. The six-layer or seven-layer model architecture is developed based on it (Gubbi et al. 2013). Big data refers to data sets that are very high in velocity, volume, and variety that require advanced technologies to enable the capture, storage, distribution, management, and analysis of the information (Gandomi and Haider 2015). The vast green building data accumulated from BIM and IoT platforms has pushed the advancements of the big data analytics era. The green building industry (GBI) is currently inundated with data due to its digitalization transformation advocated by governments and entrepreneurs. The GBI data has three main attributes: large, heterogeneous, and dynamic (Bilal et al. 2016). These characteristics challenge scientists in dealing with data captured from diverse digital platforms e.g., BIM and IoT. Existing research has tried to develop hybrid storage and analytics architecture to fit different data formats such as the Industry Foundation Classes (IFC), RFID, gbXML, OGC CityGML, converted from BIM and IoT (Li et al. 2018; Malagnino et al. 2021; Quinn et al. 2020). In the GBI field, quite a few studies focus on big data applications for building energy efficiency, environmental monitoring, and sustainability (Wu et al. 2016). However, the research for developing BIM and IoT-specialized Big Data processing, storage, and analytics platforms is still lacking. It will hinder digital decision-making for achieving highperformance buildings. Therefore, this study will introduce an integration framework for addressing BIM Big data and IoT Big data during the whole lifecycle of GB.

2 States of the Art 2.1 BIM-IoT in GBI BIM can support the reduction of construction costs, operation efficiency, and sustainability performance in the GBI. It enables a high-fidelity operable dataset, including physics, geometry, and location information. The IFC file format is widely adopted to exchange data between different BIM software. There are some limits. Designers

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cannot apply the IFC format for real-time design, construction, and operation monitoring. IoT technology is introduced to address this limitation by providing enough real-time and actual status of the building operation. Thanks to the embedded devices and sensors, massive time series data is extracted by the IoT platform to enhance the energy efficiency of GB (Malagnino et al. 2021). The construction industry’s BIM and IoT integration research has received considerable attention from scholars. These research domains include construction operation and monitoring, facility management, construction logistics, and management, etc. (Tang et al. 2019). However, most papers focused on the BIM application in the GB for achieving sustainability goals and IoT technologies for smart building management. The comprehensive research on BIM and IoT in the GB domain is still in its infancy. In addition, BIM and IoT integration methods are widely developed by researchers. For instance, Tang et al. (2019) showed that semantic web technologies and hybrid approaches are idea integration methods. Malagnino et al. (2021) divide the integration solutions into five categories: BIM data input through IFC files, data collection from IoT software, data storage in the central database, application programming interface (API) information sharing and extracting through the central brain, and information visualization through central GUI (Graphical User Interface) systems. Quinn et al. (2020) developed a database architecture for time-series data integration between BIM and IoT. The methods have four main steps: (1) collect raw data from sensors, (2) batch analytics of 2D CSV files and store data in a linked cloud-based database, (3) import these CSV files from Dynamo and transfer them to a 3D list, (4) employ the Dynamo Element to map time-series data and realize the integration of BIM-IoT.

2.2 BIM-Big Data in GBI BIM application in the GBI has received a large amount of attention in the past decade. The nexus between BIM and GBI has three main layers. The first is BIM application during the whole GB lifecycles, including design, construction, operation, and retrofitting. Secondly, BIM function application for sustainability issues such as energy performance, thermal comfort, and carbon emissions. The last is to support the GB certification (Lu et al. 2017). Although BIM benefits GB a lot, there are also some challenges: (1) overburdened due to using a stand-alone system, (2) multiple project management, (3) difficulty in information-sharing, and (4) batch analytics (Chen et al. 2016). To solve these issues, a few studies employed cloud computing technology. This technology can store and process huge data from massive BIM models based on the data center. It can also conduct statistical analysis and add dynamic data for multiple users like clients, owners, and designers (Chen et al. 2016). Recently, the term ‘processability’ of BIM has been regarded as an important issue because the volume of BIM files will become extremely large for supporting ndimensional (nD) management with the project ongoing. Specifically, a huge amount of memory and time are required for converting 3D geometric data to triangle meshes.

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Zhou et al. (2019) developed an online ‘BIMTriSer’ service for BIM triangulation based on a parallel computing framework. They found that the computing method can substantially strengthen the processability of BIM Big Data. Similarly, Lv et al. (2020) introduced a WebVRGIS system that can store geospatial Big Data of BIM in the NoSQL database. Furthermore, the research of Ali and Bandi (2022) showed that most of the BIM data, like design, schedule, and material data, positively influence the creation of big data. Overall, integrating BIM and Big data will improve the efficiency of data storage and processing to reduce costs throughout the lifecycles, especially in the GB assessment domain (Ibrahim et al. 2022). However, to the best knowledge of the author, there are limited studies on BIM-Big data application in the GBI.

2.3 IoT-Big Data in GBI IoT provides an intelligent platform for information sharing and seamless communication among a large number of sensors and devices. However, it is challenging to address extracted unstructured data, e.g., text, audio, and video, which accounts for 95% of big data (Gandomi and Haider 2015). Thanks to big data technologies, which can effectively store, process, and analyze large amounts of structured and unstructured data generated by digital devices of IoT (Marjani et al. 2017). Thus, integrating IoT and Big data plays a major role in the smart building environment era. For instance, Moreno et al. (2016) applied soft computing (SC) techniques to anticipate and optimize daily energy consumption and validated the prediction model was validated through a smart industry building. Marjani et al. (2017) systematically analyzed the relationship between IoT and Big data and then proposed a meta-model-based approach to integrate them seamlessly. In their constructed architecture, network devices and IoT devices are responsible for raw data collection. Then these data are uploaded to a cloud service through an IoT gateway based on wireless communication technologies like Wi-Fi, ZigBee, and RFID. Finally, a large amount of data is stored and computed using Big data technologies such as WebGL, MapReduce, and Spark. IoT-Big data integration is also widely applied in the heating, ventilation, and air conditioning systems (HVAC) domain. There are three main control strategies for the HVAC system. They are model-driven, data-driven, and context-driven control approaches (Lachhab et al. 2019). The context-driven control approach can monitor and process real-time data collected from wearable devices in uncertain and dynamic environments with the help of Big data technologies. They also showed that the hybrid control method outperforms proportional–integral–derivative (PID) control method concerning indoor/outdoor CO2 concentration feedback. Similarly, Luo et al. (2019) developed an IoT-based big data platform to predict energy demands. IoT sensors are used extensively to accurately detect temperatures in different locations in buildings. Then k-means clustering and artificial neural network (ANN) are used to construct a predictive model with only an 8% error in energy demands in testing

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cases. Therefore, according to the reviewed papers, IoT-Big data integration will be a promising research domain in the GBI (Wu et al. 2016).

3 BIM, IoT, and Big Data Integration Framework in GBI This paper developed an integration framework to store and analyze BIM and IoT big data based on distributed system architecture Hadoop. These hybrid data are characteristic of highly dynamic, heterogeneity, and volume. The core design components of Hadoop include HDFS, Yarn, and MapReduce, which can efficiently access large datasets through the stream. The five-layered BIM-IoT-Big data integration framework is illustrated in Fig. 1.

3.1 BIM-IoT Big Data Input The purpose of the data input layer is to access, manipulate and share diverse GB information with a unified data access interface during the design, construction, operation, and maintenance phases. In this layer, massive of static data and dynamic data are produced from BIM and IoT with the schedule of GB projects. Specifically, there are four types of data from the nD BIM platform: building attribute data, document data, geospatial data, and vector data. They have various data formats, such as industry foundation classes (IFC), ifcXML, ifcOWL, and Green Building

Big Data Input layer

Cloud Storage layer

BIM

GB Contextual data

Static data Vector data

Attribute data Document data Geospatial data

Spatial Database

HDFS Hbase NoSQL

IoT

Time-series data

Dynamic data

MySQL

Resource management layer

Cloud BIM/IoT System

Fig. 1 Framework architecture

Application layer

Big Data Analytics

Mesos Master

MapReduce Apache Spark

Mesos Slave Storm

Data visualization

Data sharing

Yarn

Resource Manager

Devices or Sensors (Terminal) Networks (Communication infrastructure)

Analysis and Computing layer

Node Manager

Amazon EMR Google AI Platform Azure ML

Web UI Web GL

REST API Management

High Energy Efficiency

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XML (gbXML). In the IoT system, real-time data are collected from numerous devices and sensors installed in the buildings. These data can be shared with other software, hardware, and platforms through communication infrastructures such as Zigbee, Bluetooth, and Wi-Fi.

3.2 BIM-IoT Big Data Cloud Storage The cloud storage architecture consists of three modes: spatial database, NoSQL database, and MySQL database. The BIM contextual data is stored in the first two databases, and the IoT time-series data is stored in the last one. Hadoop Distributed File System (HDFS) and Hadoop Database (HBase) can also be alternatives to NoSQL. Because they are all distributed file systems and can store unstructured data efficiently. Last, semantic web technologies are applied to serialize the two types of datasets and integrate BIM and IoT data to avoid data silos. Then they have stored in the graph database in Resource Description Framework (RDF) serialization.

3.3 BIM-IoT Big Data Resource Management The resource management layer aims to improve the utilization rate of the data center, cluster, and cloud environments by abstracting compute resources away from machines (physical or virtual). Mesos and Yarn are two types of distributed system kernels widely used in the Big Data resource management era. Mesos includes four types of services. They are Zookeeper, Master, Slave, and Framework (distributed application). The Slave is responsible for running tasks and constantly sends information to the Master that the Zookeeper appoints. The Framework is responsible for external computing framework access, such as Hadoop, Spark, etc. However, in the Yarn kernel, Resource Manager and Node Manager constitute a data computing framework, which acts the same function as Master in the Mesos.

3.4 BIM-IoT Big-Data Analytics The data analytics layer can process BIM and IoT Big Data based on the resource management layer to uncover hidden information, knowledge, and complex correlations. It includes text analytics, audio analytics, video analytics, and predictive analytics. MapReduce, Spark, and Storm are three commonly used programming paradigms for computing and analyzing vast data sets. MapReduce is a Yarn-based system that can process multi-terabyte datasets in parallel by splitting them into “map” and “reduce” tasks. It is highly reliable when computing vast static data in cloud BIM systems. The Storm is a distributed real-time computation system

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with advantages in processing unbounded data streams. Spark can process batch/ streaming data. It enables SQL analytics and Exploratory Data Analysis (EDA). Therefore, Storm and Spark can analyze real-time data from cloud IoT systems. After processing vast amounts of data, Web UI/ Web GL is JavaScript API that can provide clients for users to conduct cloud BIM/IoT system analysis and display them in 3D.

3.5 BIM-IoT Big-Data Application The Big Data application layer can support the interaction with the BIM and IoT systems through API and dashboard. Big Data visualization is crucial after the analytics process. It can help format, standardize and interpret the vast data generated from massive BIM and IoT systems. In addition, this layer integrates API with BIM and IoT applications to assess the real-time GB energy consumption. Furthermore, Representational State Transfer (REST) API is applied to connect different devices, machines, and applications by HTTP protocols. For example, IoT devices can be linked to other cloud services or resources with a URI to read and record data. All developers can GET, PUT, POST, and DELETE data through the REST API. Finally, these APIs can be shared with stakeholders involved in the GBI, e.g., designers, contractors, and end users, to manage energy-efficient systems.

4 Conclusions This research develops a BIM, IoT, and Big Data integration framework for improving building energy efficiency in the GBI. In this framework, the vast BIM building contextual data and IoT time-series data are exchanged based on Big Data technology. The framework includes five layers: BIM/IoT Big Data input layer, cloud storage layer, resource management layer, analysis and computing layer, and application layer. It can store, exchange, and compute massive building energy use data by integrating modules of the Apache Hadoop framework, i.e., HDFS, Yarn, and MapReduce. WebGL, Web UI, and REST API are applied to visualize, share, and manage the GB energy efficiency. The proposed framework provides new insights for researchers and practitioners regarding BIM-IoT Big Data integration management. It can also be a guideline for corporate decision-makers to develop new digital transformation strategies in the GBI. There are also some limitations. To begin with, the integration architecture is promising but needs to be validated with a sufficient number of real-world cases. Future research should focus on acquiring and analyzing massive GB project operation data using Big Data technologies. Moreover, the integration framework does not incorporate GB rating systems. Therefore, the framework can be further improved by including GB energy performance assessment in the future.

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Acknowledgements This study is supported by the National Natural Science Foundation of China (NSFC) Young Scientist Fund (Grant No. 62102324) and the Glodon company research fund (Grant No. RDS10120220066). Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References Ali FH, Bandi S (2022) Correlation between BIM data creation and big data attributes in construction. Int J Constr Manag. https://doi.org/10.1080/15623599.2022.2119071 Bilal M et al (2016) Big data in the construction industry: a review of present status, opportunities, and future trends. Adv Eng Inform 30(3):500–521. https://doi.org/10.1016/j.aei.2016.07.001 Chen HM, Chang KC, Lin TH (2016) A cloud-based system framework for performing online viewing, storage, and analysis on big data of massive BIMs. Autom Constr 71:34–48. https:// doi.org/10.1016/j.autcon.2016.03.002 Gandomi A, Haider M (2015) Beyond the hype: big data concepts, methods, and analytics. Int J Inf Manage 35(2):137–144. https://doi.org/10.1016/j.ijinfomgt.2014.10.007 Gubbi J, Buyya R, Marusic S, Palaniswami M (2013) Internet of things (IoT): a vision, architectural elements, and future directions. Futur Gener Comput Syst 29(7):1645–1660. https://doi.org/10. 1016/j.future.2013.01.010 Ibrahim O, Imoudu W, Donn M, Chileshe N (2022) Building information modelling and green building certification systems: a systematic literature review and gap spotting. Sustain Cities Soc 81:103865. https://doi.org/10.1016/j.scs.2022.103865 Lachhab F, Bakhouya M, Ouladsine R, Essaaidi M (2019) Context-driven monitoring and control of buildings ventilation systems using big data and internet of things–based technologies. Proc Inst Mech Eng Part I: J Syst Control Eng 233(3):276–288 Li CZ et al (2018) An internet of things-enabled BIM platform for on-site assembly services in prefabricated construction. Autom Constr 89(1):146–161 Lu Y, Wu Z, Chang R, Li Y (2017) Building information modeling (BIM) for green buildings: a critical review and future directions. Autom Constr 83(11):134–148. https://doi.org/10.1016/j. autcon.2017.08.024 Luo XJ et al (2019) Development of an IoT-based big data platform for day-ahead prediction of building heating and cooling demands. Adv Eng Inform 41(8):100926. https://doi.org/10.1016/ j.aei.2019.100926 Lv Z, Li X, Lv H, Xiu W (2020) BIM big data storage in WebVRGIS. IEEE Trans Ind Inf 16(4):2566– 2573 Malagnino A et al (2021) Building information modeling and internet of things integration for smart and sustainable environments: a review. J Clean Prod 312:127716. https://doi.org/10.1016/j.jcl epro.2021.127716 Marjani M et al (2017) Big IoT data analytics: architecture, opportunities, and open research challenges. IEEE Access 5:5247–5261 Moreno MV et al (2016) Big data: the key to energy efficiency in smart buildings. Soft Comput 20(5):1749–1762. https://doi.org/10.1007/s00500-015-1679-4 Quinn C et al (2020) Building automation system—BIM integration using a linked data structure. Autom Constr 118(5):103257. https://doi.org/10.1016/j.autcon.2020.103257 Tang S et al (2019) A review of building information modeling (BIM) and the internet of things (IoT) devices integration: present status and future trends. Autom Constr 101(5):127–139. https://doi. org/10.1016/j.autcon.2019.01.020

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Wu J, Guo S, Li J, Zeng D (2016) Big data meet green challenges: green applications. IEEE Syst J 10(3):873–887 Zhou X et al (2019) Parallel computing-based online geometry triangulation for building information modeling utilizing big data. Autom Constr 107:102942. https://doi.org/10.1016/j.autcon.2019. 102942

Assessing the Energy Performance of Low-Rise Modularised Lightweight Steel-Framed Residential Buildings in China: Case Study of a Shanghai Suburb Y. Yang, M. Cimillo, J. Hao, D. Chow, P. S. Yap, and H. Zhang

Abstract The development of low-rise modularised lightweight steel-framed (MLSF) residential buildings in China has significant potential to contribute to the country’s effort to reduce energy consumption. However, to fully realise this potential, it is crucial to assess the energy performance of these buildings and identify opportunities for further optimisation. This paper elucidates the main factors in the energy performance of low-rise MLSF residential buildings and presents a case study in suburban Shanghai, in China’s hot-summer-cold-winter (HSCW) zone. The preliminary results indicated that optimised building envelope thermal performance could significantly improve the energy efficiency of MLSF buildings, leading to a reduction of up to 40% in total energy and up to 68% in heating energy compared to the latest baseline standard. This paper advances the understanding of the energy performance of low-rise MLSF residential buildings in China and provides valuable insights to promote energy-efficient building practices in the HSCW zone. Keywords Low-rise modularised lightweight steel-framed · Residential buildings · Energy performance · Thermal performance

1 Introduction According to the International Energy Agency (2022), energy use in buildings increased from 115EJ in 2010 to almost 135EJ in 2021, accounting for 30% of global final energy consumption. In this context, the reduction of the energy consumption Y. Yang · M. Cimillo Department of Architecture, Xi’an Jiaotong-Liverpool University, Suzhou, China J. Hao · P. S. Yap · H. Zhang Department of Civil Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China D. Chow School of Architecture, University of Liverpool, Liverpool, UK © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_3

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of buildings is crucial. Low-rise modularised lightweight steel framed (MLSF) is a promising sustainable building construction method that improves energy efficiency and reduces carbon emissions as Veljkovic and Johansson (2006) emphasised that lightweight steel framed (LSF) structures are used extensively in the USA, Australia, and Japan. China, as a developing country, is still in the process of developing lowrise MLSF buildings in suburban or rural areas and is underused compared with most developed countries. However, it is set to become one of the most prominent construction systems in China to support the country’s process of revitalisation plan, which includes raising building standards both in terms of environmental quality and energy efficiency. Jiangsu Province alone has planned the construction of half a million rural houses in the next five years (Xinhua News Agency 2022), and MLSF buildings, as one of the most widely used types of modular construction in developed countries, will likely play a vital role in this plan, due to its advantages like high quality, fewer carbon emissions, and less construction waste (Hao et al. 2020). In hot-summer-cold-winter (HSCW) areas, compared to brick structures, the energy-saving rate of the MLSF house is 50.8%, which is much higher than that of brick structures (35.1%) (Wu et al. 2018). The thermal performance of the building envelope is crucial to provide good thermal behaviour and energy efficiency, allowing a reduction of operational energy in MLSF buildings (Santos et al. 2014). One feasible strategy to enhance the energy efficiency of buildings is to reduce undesirable heat losses by optimising the windowwall ratio (WWR), window-floor ratio (WFR), G-value of windows, and thermal resistance (U-value) across the building envelope. For instance, when the windowwall ratio (WWR) of the MLSF building is about 0.2, the U-value of the exterior wall, exterior windows, and roof are respectively at 0.4, 3.0 and 0.5 W/ (m2 · K), the energy consumption would be 179.1 MJ/m2 for heating and 90.612 MJ/m2 for cooling, which is 56.93% lower than the baseline standard published in 2001 (CABR 2001) in the HSCW area (Li et al. 2021). However, in order to fully highlight the potential improvements in current practices, simulation data of MLSF buildings must be updated to reflect the latest and specific standards. Furthermore, the HSCW climate region of China is one of the most challenging climate zones, due to its high requirements for heating as well as cooling (Li et al. 2019). Thus, it is important to simulate the energy performance of the newly built low-rise MLSF residential buildings in the HSCW region of China and compare it with the latest standards. This paper aims to understand the current energy performance of low-rise MLSF residential buildings in China and potential opportunities for further optimisation with a case study in suburban Shanghai, which belongs to the HSCW area of China. The paper consists of a brief review of current researches and practices of MLSF buildings in China and the methodology of the research, which is presented along with the case study, followed by results and conclusions.

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2 Methodology 2.1 Case Study The research is conducted through a case study in Jiading District, Shanghai, located in China’s HSCW zone. The climate data is provided by the Chinese Standard Weather Database (CSWD) and retrieved from the EnergyPlus website (2023). The simulations are conducted using OpenStudio (2023) and EnergyPlus (2023). OpenStudio is an open-source software to support thermal and energy balance simulation on buildings. OpenStudio covers most key factors of building with the geographical interface. EnergyPlus, developed mainly by the US Department of Energy and the National Renewable Energy Laboratory, constitutes the simulation engine of OpenStudio and has been extensively validated against a number of international standards (EnergyPlus 2023). Detailed architectural and construction data of the buildings, as illustrated in Table 1, Figs. 1 and 2, are provided by the developer, Yangdigang (Shanghai) Prefabricated Construction Co., Ltd. Q550 c-shaped cold-formed steel studs structure housing system, one of the most used steel frame in a low-rise residential building in China, is applied in this case. Table 1 Building data Specifications

Value

Specifications

Value

Number of floors

3

Total window area (m2 )

52.94 14.71%

Number of occupants

5

Gross window-wall ratio

Total floor area (m2 )

249.32

S/V ratio

Fig. 1 Photo and plan drawing

0.55

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Fig. 2 Elevation and wall section

2.2 Benchmarks and Scenarios The actual building complies with the requirements for the Three Star-level of GB/T 50378–2019 Assessment standard for green buildings (CCSSI and SRIBS 2019). The paper refers to it as Scenario 2, Actual Building (2-AB). As a three-star building, this is also representative of the local best practice. A baseline scenario (1-BL) was defined according to DGJ 08–205-2015 (SRIBS 2015). The standard stipulates the baseline requirements for all new residential buildings in Shanghai. DGJ 08-205-2015 assesses energy performance against a reference model, of which Table 2 illustrates the main characteristics. A third, high-performance scenario was created to represent the best international practice (3-BI) and is based on BREEAM In-Use International Technical Manual: Residential SD243-V6.0.0. The Building Research Establishment’s Environmental Assessment Method, or BREEAM (BRE Global Limited 2020), is one of the most comprehensive and widely used environmental assessment tools worldwide. The main simulation parameters are summarised in Table 2 and 3. The windows distribution in 1-BL and 3-BI has been modified according to relevant standards, which are expressed as WWRs by DGJ 08–205-2015, and as WFRs by BREAAM. Table 2 General settings Heating set-point temperature from December 1st to February 28th (°C)

18

Cooling set-point temperature from June 15th to August 31st (°C)

26

Performance time (h)

8760

Outdoor air flow air changes per hour

1

Internal heating gain

(w/m2 )

4.3

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Table 3 Scenarios 1-BL (Baseline/ code-compliant)

2-AB (Actual building/Best local Practice)

3-BI BREEAM (Best International Practice)

0.35

0.27

0.47

Window-wall ratio: East 0.25 and West

0.07, 0.08

0.12, 0.14

Window-wall ratio: South

0.50

0.25

0.44

Window-floor ratio

0.44

0.185

0.321

Roof U-value [W/ (m2 ·K)]

0.5

0.274

0.200

Exterior Wall U-value [W/(m2 ·K)]

0.6

0.366

0.200

Window U-value [W/ (m2 ·K)]

2.2

1.772

0.700

G-value/SHGC

0.4

0.579

0.5

Window-wall ratio: North

The research focuses on envelope characteristics, and HVAC is modelled through the “Ideal Air Load” system in EnergyPlus. Therefore, the simulation results represent the thermal energy needs for heating and cooling.

3 Results and Conclusion In general, the simulation confirms that interventions on the building envelope can result in a substantial reduction of the energy needs for both heating and cooling, as detailed in Figs. 3 and 4. The main conclusions can be summarised by the following points. First, in comparison to 1-BL, both 2-AB and 3-BI demonstrate significant energy savings. Specifically, 2-AB achieves a total site energy reduction of 15%, while 3-BI achieves a reduction of 22%. Second, the heating energy need of 3-BI and 2-AB show more marked reductions when compared to 1-BL. Specifically, the heating energy need of 3-BI is reduced by 68%, while 2-AB experiences a reduction of 40%. The cooling energy need of both 3-BI and 2-AB is also reduced in comparison to 1-BL, with 3-BI achieving a 37% reduction and 2-AB achieving a 31% reduction. Third, further analysis comparing the heating and cooling energy needs of 3-BI and 2-AB reveals that the heating energy need of the former is reduced by 38% when compared to the latter. Conversely, the cooling energy need of 3-BI experiences a 9% increase relative to 2-AB, primarily due to the incorporation of increased WWR and possibly also due to excessive insulation. These particular data seem to indicate that

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Fig. 3 Monthly energy needs for heating and cooling with average outdoor air dry bulb

Fig. 4 Heating/cooling energy need for three scenarios

the best-practice framework provided by BREEAM is mostly effective in limiting winter energy use, but may need adaptation in the local climate to achieve similar results in the hot season. Fourth, given the scarcity of previous research on this particular type of building and climate zone and the different research frameworks, the results are not directly comparable with the ones produced by previous authors -e.g. (Li et al. 2021)-; nevertheless, the results seem to be in line with the expectations. In absolute terms, the energy needs are limited, but this can be explained by the assumptions being based on the current regulations, which restrict the heating period between December and February and stipulates a set-point temperature of 18 °C. However, such requirements do not reflect the users’ needs in terms of thermal comfort, and seem unlikely to be applied rigorously in the actual use of the building. Limitations must be acknowledged, including the fact that the study is based on a single case study and the impossibility of validating the results against the actual building performance at the current stage. The building was simulated as built, but modelling errors cannot be completely avoided, and occupants’ behaviour can have

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a major impact on the final energy use. However, the focus of the research is not on producing extremely accurate predictions for a specific building, but rather on comparing different design options. These would all be similarly impacted by occupants’ behaviour and all modelling errors and inaccuracies not specifically related to the options themselves, like climate data or control systems. Therefore, results would not be likely to change drastically in comparative terms. In spite of its limitations, the paper provides insights into the energy performance of low-rise MLSF residential buildings in the HSCW region of China, which is currently under researched. Based upon a comparison of actual building and benchmarks, the result suggests that optimising the thermal performance of the building envelope can significantly reduce energy consumption even in comparison to the current best international practice. This can be achieved through a careful balance of values of WWR, WFR, U-value, and G-value of the building envelope, as demonstrated in the different scenarios. Future research will be able to provide more specific directions and guidelines. Overall, the findings of this study may provide guidance for the design and construction of low-rise MLSF buildings in similar climate zones and contribute to the development of more sustainable and energy-efficient building practices.

References BRE Global Limited (2020) SD243_BREEAM-In-Use-International_Residential-TechnicalManual-V6.pdf CABR (2001) JGJ 134–2001. 夏热冬冷地区居住建筑节能设计标准, Design standard for energy efficiency of residential buildings in hot summer and cold winter zone JGJ 134-2001 CCSSI, SRIBS (2019) GB/T 50378-2019 绿色建筑评价标准, GB/T 50378-2019 assessment standard for green building EnergyPlus Weather Data [WWW Document] (2023). https://energyplus.net/weather. Accessed 21 Mar 2023 EnergyPlus [WWW Document] (2023) https://energyplus.net/testing. Accessed 15 Mar 2023 Hao, J.L., Cheng, B., Lu, W., Xu, J., Wang, J., Bu, W., Guo, Z.: Carbon emission reduction in prefabrication construction during materialization stage: a BIM-based life-cycle assessment approach. Sci. Total Environ. 723, 137870 (2020). https://doi.org/10.1016/j.scitotenv.2020.137870 IEA—International Energy Agency [WWW Document] (2022) https://www.iea.org/. Accessed 16 Feb 2023 Li F, Zhang W, Wang Y, Wu J (2021) 夏热冬冷地区农村装配式钢结构节能建筑研究 Study on rural prefabricated steel structure energy-saving buildings in hot summer and cold winter area. New Build Mater 150–156 Li, Z., Chow, D.H.C., Yao, J., Zheng, X., Zhao, W.: The effectiveness of adding horizontal greening and vertical greening to courtyard areas of existing buildings in the hot summer cold winter region of China: a case study for Ningbo. Energy Build 196, 227–239 (2019). https://doi.org/ 10.1016/j.enbuild.2019.05.025 OpenStudio [WWW Document] (2023) https://openstudio.net/. Accessed 14 Feb 2023 Santos, P., Martins, C., da Silva, L.S.: Thermal performance of lightweight steel-framed construction systems. Metall. Res. Technol. 111, 329–338 (2014). https://doi.org/10.1051/metal/2014035 SRIBS (2015) DGJ 08-205-2015 居住建筑节能设计标准, DGJ 08-205-2015 Design standard for energy efficiency of residential buildings.

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Veljkovic, M., Johansson, B.: Light steel framing for residential buildings. Thin-Walled Struct. Tribute Edition to Rolf Baehre 44, 1272–1279 (2006). https://doi.org/10.1016/j.tws.2007.01.006 Wu Y, Zhu Q, Li M (2018) 装配式轻钢复合保温外墙板的制备及其在村镇住宅中的节能效果 评价. Preparation of assembled light steel composite thermal insulation exterior wall panel and its energy saving influence evaluation in village construction. China Concrete and Cement Products 63–67 Xinhua News Agency (2022) 江苏提出5年改善农房超50万户. Jiangsu proposed to improve more than 500,000 houses in rural in five years [WWW Document]. http://www.gov.cn/xinwen/202204/18/content_5685767.htm. Accessed 3 Mar 2023

Energy Efficiency Optimization of Different Curved Building Integrated Photovoltaic (BIPV) Façades by a Parametric Shape Design Method: A Cross-Region Study Shaohang Shi, Yehao Song, Weizhi Gao, and Yingnan Chu

Abstract With the development of green building technologies and photovoltaic materials, the emergence of flexible BIPV products has enriched building aesthetics and can also optimize the energy performance of building envelopes. However, it has yet to be adequately addressed how to maximize the energy potential of curved BIPV façades. Therefore, this paper investigates the energy efficiency of curved BIPV façade by building envelope form optimization. There are 22 types of curved BIPV façade investigated with design parameters including 3 intervals, 5 curvature and 2 combination methods, which is conceived to explore their production capacity in two cities, Beijing, China and Kuala Lumpur, Malaysia. The results prove that (1) There are differences in the annual power generation per unit of PV area for different forms of curved BIPV façade: The annual energy production ranged from 79.13 kW·h/ m2 to 110.68 kW·h/m2 in Beijing, while the annual energy production ranged from 52.49 kW·h/m2 to 71.25 kW·h/m2 in Kuala Lumpur. (2) Due to latitude and longitude, the optimized curved BIPV façade in Kuala Lumpur can improve energy efficiency by 4.49% compared to flat BIPV façades, corresponding to a 3.06 kW·h/m2 increase in annual PV system production capacity per unit of PV area. However, in Beijing, the curved BIPV façade has no increased production capacity compared to flat BIPV façades. (3) Different design parameters optimize the energy performance of the curved BIPV facade to different degrees. Firstly, the increased interval of BIPV units can improve energy efficiency by up to 18.55% (Beijing) and 28.12% (Kuala Lumpur) for the convex curved BIPV façade annually, but not significantly for the concave. Secondly, the reduced angle can improve energy efficiency by up to 37.50% (Beijing) and 28.68% (Kuala Lumpur) for the concave BIPV façade, and 11.99% growth for the convex façade in Beijing annually but insignificant in Kuala Lumpur. Thirdly, with the combination of convex and concave BIPV units, it is possible to improve energy efficiency by up to 10.21% (Beijing) and 14.56% (Kuala Lumpur) S. Shi · Y. Song · W. Gao · Y. Chu School of Architecture, Tsinghua University, Beijing, China Key Laboratory of Eco Planning and Green Building, Ministry of Education, Tsinghua University), Beijing, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_4

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annually. Thus, it is a feasible method to optimize curved BIPV façade’s energy performance by parametric form design in early stage. In addition, it is proof that the spatial and temporal distribution characteristics of solar energy in different regions cannot be ignored, which determines whether curved BIPV technology can optimize the production capacity efficiency of building façade systems. The methodology and data presented in this paper can provide guidance in both energy performance optimization and equipment selection by assessing benefits of curved BIPV façade application in different regions. Keywords Building Integrated Photovoltaic (BIPV) Façades · Energy production · Energy performance optimization · Parametric shape design

1 Introduction With the global promotion of carbon reduction efforts, the integrated use of solar energy in buildings is becoming increasingly challenging (Shen et al. 2023, Kou et al. 2022). Building integrated photovoltaics (BIPV) enables the possibility of buildings as energy producers (Maghrabie et al. 2021). With the increasing development of BIPV technology, emerging BIPV products can also meet the needs of various architecture aesthetics, such as color (Vossen et al. 2016), transparency (Wang et al. 2022) and form—which can be used for photovoltaic shading devices (Taveres-Cachat et al. 2019), BIPV double-skin facades (Yang et al. 2020) and BIPV window systems (Liao and Xu 2015). In recent years, flexible thin-film photovoltaic modules have received attention from architects (Fig. 1), engineers and real estate managers: Compared with conventional rigid PV, they have the advantages of flexibility, light weight, ease of transportation, and low consumption of raw materials for production (Li and Zanelli 2021), making it possible to produce electricity from curved shaped building skins.

Fig. 1 a The flexibility of a CIGS solar device, picture source: reference (Ramanujam et al. 2020), b building facades with flexible solar devices, picture source: https://www.continuousresources. com/products/global-solar-100w-powerflex-cigs-flexible-solar-panel

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Previous studies have been accumulated on the shape design parameters of building envelopes and energy efficiency, while the complexity of building performance studies and evaluation of curved building envelopes is significant due to their non-linear morphological parameters (Lu et al. 2020). Especially for curved BIPV façade, the design of its morphological parameters directly affects its production efficiency due to its self-shading effect, however, there are few related studies. It is worth exploring how to maximize the energy potential of curved BIPV facade. Relevant design parameters include angle, single PV product area, etc., which directly affects the trade-off between economic investment and PV system production. Al-Janahi et al. (2020) explored a method to optimize the production potential of a BIPV roof (3862 m2 area, 45 zones) of a building case with power generation loss caused by partial shading through building performance simulation. The results show that based on the optimized 9 × 5 BIPV array layout, the power generation can be effectively increased by 169.6 × 103 W. Walker et al. (2019) proposed a BIPV system modeling and performance optimization method based on parametric modeling tools, which was applied to the performance study of a hyperbolic roof. It was found that the layout of different PV unit orientations has an impact on the performance, and the optimal design of system parameters in the design phase can improve the power generation. Tian et al. (2022) compared the energy production performance of curved and flat PV panels under different tilt angles through an experimental study of CIGS modules in Hefei, Anhui, China. The results show that under the condition of smaller inclination angle, the energy production of flat PV is higher than that of curved PV; under the condition of larger inclination angle, curved PV has the advantage of energy production in summer. In another study by Tian et al. (2023) in Hefei, the effect of connection mode and building façade orientation on the production performance of curved BIPV façade was discussed. The results show that the CIGS cells connected in series generate 12.56% less energy than the parallel mode; the CIGS in west facade generates 21.49% more energy than the east facade. However, existing studies do not compare the production potential of curved BIPVs with different design parameters, and there is a lack of cross-region studies. The façade receives less solar radiation than the roof. Therefore, how to optimize the productivity of curved BIPV façade needs to be evaluated. Therefore, this study investigates 22 curved BIPV facades through building performance simulation with design parameters including 3 intervals, 5 curvatures and 2 combination methods. Furthermore, a cross-region study was conducted to explore the production potential of different curved BIPV façades in two cities, Beijing, China and Kuala Lumpur, Malaysia. This study also investigated the effect of different morphological parameter optimization strategies on the energy production improvement. The parametric models and data presented in the study can guide the performance optimization design of curved BIPV facades.

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Table 1 Different BIPV curved facades and case studies for simulations Façade type

Typical case images

Case studies

Flat facades

–

Base case

Concave facades, picture source: https://www. designboom.com/architecture/blackhome-bre wery-facade-yue-art-gallery-shenzhen-02-212020/

B1, B2, B3, D1, D2, D3, G2, H2, H4

Convex facades, picture source: https://div isare.com/projects/338162-alison-brooks-archit ects-dennis-gilbert-quarterhouse?utm_content= buffer7b1bf&utm_medium=social&utm_sou rce=facebook.com&utm_campaign=buffer

A1, A2, A3, C1, C2, C3, G1, H1, H3

S-shaped façades, picture source: https://www. gooood.cn/bristol-life-sciences-building.htm? lang=en

E1, E2, F1, F2

2 Methods 2.1 Case Study Compared with conventional rigid PV, flexible PV modules have more application scenarios and can realize performance improvement of curved-shape buildings. Therefore, it is needed to study and summarize the curved façade shapes of typical building cases. Table 1 shows photographs of different curved façade views from different completed projects, and the corresponding case numbers in this study are included. Figure 2 gives the definitions of the parameters selected for this study of curved BIPV facades. Table 2 shows the indexes of different curved BIPV façade cases, including single module curvature, single module area, individual spacing within groups, group spacing and total area. In order to compare the production performance of curved BIPV facades with different morphological parameters, the total area of PV panels used in all cases is 126.72 m2 .

2.2 Building Simulation The building performance simulation software used in this study is the Honeybee plug-in integrated with Rhino software, with EnergyPlus as the core for calculations;

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Fig. 2 Different design parameters of curved BIPV facades

Table 2 Design parameters of different curved BIPV facades Case number

Single module curvature (rad)

Module amount

Individual module spacing within groups (m)

Group spacing (m)

Base case

-

1

-

-

A1

π

9

0

9

A2

π

9

2

5

A3

π

9

3

3

B1

π

9

0

9

B2

π

9

2

5

B3

π

9

3

3

C1

π/2

9

0

6.5

C2

π/2

9

1

4.5

C3

π/2

9

2

2.5

D1

π/2

9

0

6.5

D2

π/2

9

1

4.5

D3

π/2

9

2

2.5

E1

π/2

9

0

6.5

E2

π/2

9

0

6.5

F1

π

9

0

9

F2

π

9

0

9

G1

π/2

3

–

6.5

G2

π/2

3

–

6.5

H1

π/2

1

–

–

H2

π/2

1

–

–

H3

π/3

1

–

–

H4

π/3

1

–

–

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Table 3 Meteorological parameters comparison of two typical cities Meteorological parameters

Beijing

Kuala Lumpur

39.80

3.12

Longitude (°)

116.47

101.55

Altitude (m)

31.30

22.00

Annual average solar radiation (W/m2 )

159.91

178.30

Average solar radiation in July (W/m2 )

198.47

176.31

Latitude (°)

Average solar radiation in January (W/m2 )

94.934

177.07

the applicability of EnergyPlus has been evaluated in numerous previous studies. The research model is set up as a standard-story south elevation with opaque walls. For the PV system, the solar energy conversion rate is set as 13% (Mendis et al. 2020).

3 Results and Discussion 3.1 Meteorological Parameters Comparison in Typical Cities Table 3 shows the geographical and meteorological data of two typical cities. In terms of available solar energy, the annual average solar radiation in Kuala Lumpur is higher than that in Beijing. However, there are differences in the average solar radiation of the two cities in different seasons. The average solar radiation in July is higher in Beijing, but the average solar radiation in January is about twice as high in Kuala Lumpur as in Beijing.

3.2 PV Generation of Different Curved BIPV Facades Figure 3 shows the annual production capacity of applied flat BIPV façade and 22 cases of curved BIPV façade in Beijing and Kuala Lumpur. It can be seen that the production capacity of all cases where BIPV technology is applied in Beijing is better than that in Kuala Lumpur. The annual energy production ranged from 79.13 to 110.68 kW·h/m2 in Beijing, while the annual energy production ranged from 52.49 to 71.25 kW·h/m2 in Kuala Lumpur. Due to latitude and longitude, the optimized curved BIPV façade in Kuala Lumpur can improve energy efficiency by 4.49% compared to flat BIPV façades, corresponding to a 3.06 kW·h/m2 increase in annual PV system production capacity per unit of PV area. However, in Beijing, the curved BIPV façade has no increased production capacity compared to flat BIPV façades. This shows that although the average annual available solar energy in Kuala Lumpur is superior to that in Beijing, the influence of the altitude and azimuth of the sun makes the total

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Fig. 3 PV generation of different curved BIPV facades in two typical cities

energy production in Beijing preferable; increasing the power generation of BIPV façade by adopting curved shape is feasible only in Kuala Lumpur.

3.3 Comparison of Production Optimization Strategies for Different Curved Façade Types The case comparison study table for various optimization strategies is shown in Table 4. Different design parameters optimize the energy performance of the curved BIPV facade to different degrees. Firstly, the increased interval of BIPV units can improve energy efficiency by up to 18.55% (Beijing) and 28.12% (Kuala Lumpur) for the convex curved BIPV façade annually, but not significantly for the concave. Secondly, the decreased angle can improve energy efficiency by up to 37.50% (Beijing) and 28.68% (Kuala Lumpur) for the concave BIPV façade, and 11.99% growth for the convex façade in Beijing annually but insignificant in Kuala Lumpur. Thirdly, with the combination of convex and concave BIPV units, it is possible to improve energy efficiency by up to 10.21% (Beijing) and 14.56% (Kuala Lumpur) annually. Table 4 Case comparison of PV production optimization strategies for different curved facade types Generation optimization strategies

Case numbers

Increased interval

A1, A2, A3; B1, B2, B3; C1, C2, C3; D1, D2, D3

Decreased curvature

A3, C3, G1, H1, H3; B3, D3, G2, H2, H4

Combination of convex and concave units

A1, B1, F1, F2; C1, D1, E1, E2

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4 Conclusions In this study, an energy production model for curved BIPV facades was developed based on different design parameters, and typical climate zones were selected to investigate the optimization design strategy of energy performance. Findings of the study are as follows. There is a difference in the energy efficiency of different curved BIPV façade in the same climate zone. Due to the solar altitude angle, the curved BIPV façade production potential of climate zones with lower annual average solar radiation may be better than that of climate zones with more solar resources. In addition, the curved BIPV façade technology can be used to increase the power generation in the Kuala Lumpur, but not in the Beijing. For the three typical curved BIPV facades—convex, concave and “S”—there are differences in the degree of energy improvement for different parameter optimization design strategies. For convex curved BIPV facades, increasing the interval of individual BIPV modules is the most effective strategy. For the concave curved BIPV façade, reducing the angle of individual BIPV components is the most effective. The “S” curved BIPV façade is optimized for energy efficiency for two typical cities. In the future, there is still a need to evaluate the self-shading effect (Shi et al. 2022) of the building between the lower and upper floors of the curved BIPV façade. At the same time, in order to increase the production capability of curved BIPV façade, adaptive facades (Zhang et al. 2022) based on solar chasing system will be a trend. Acknowledgements The project is supported by National Key R&D Program of China (2022YFC3803805) and National Natural Science Foundation of China (52078264).

References Aljanahi SA, Ellabban O, Alghamdi SG, Sciubba E (2020) A novel BIPV reconfiguration algorithm for maximum power generation under partial shading. Energies 13 Kou F, Shi S, Zhu N, Song Y, Zou Y, Mo J, Wang X (2022) Improving the indoor thermal environment in lightweight buildings in winter by passive solar heating: an experimental study. Indoor Built Environ 31:2257–2273 Li Q, Zanelli A (2021) A review on fabrication and applications of textile envelope integrated flexible photovoltaic systems. Renew Sustain Energy Rev 139:110678 Liao W, Xu S (2015) Energy performance comparison among see-through amorphous-silicon PV (photovoltaic) glazings and traditional glazings under different architectural conditions in China. Energy 83:267–275 Lu S, Lin B, Wang C (2020) Investigation on the potential of improving daylight efficiency of office buildings by curved facade optimization. Build Simul 13:287–303 Maghrabie HM, Elsaid K, Sayed ET, Abdelkareem MA, Wilberforce T, Olabi AG (2021) Buildingintegrated photovoltaic/thermal (BIPVT) systems: applications and challenges. Sustainable Energy Technol Assess 45:101151

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Mendis T, Huang Z, Xu S, Zhang W (2020) Economic potential analysis of photovoltaic integrated shading strategies on commercial building facades in urban blocks: a case study of Colombo, Sri Lanka. Energy 194:116908 Ramanujam J, Bishop DM, Todorov TK, Gunawan O, Rath J, Nekovei R, Artegiani E, Romeo A (2020) Flexible CIGS, CdTe and a-Si: H based thin film solar cells: a review. Prog Mater Sci 110:100619 Shen C, Peng J, Wang D, Pei G (2023) Recent advances in multispectral solar energy technologies for the building sector. Renewable Energy 202:1146–1147 Shi S, Sun J, Liu M, Chen X, Gao W, Song Y (2022) Energy-saving potential comparison of different photovoltaic integrated shading devices (PVSDs) for single-story and multi-story buildings. Energies 15:9196 Taveres-Cachat E, Lobaccaro G, Goia F, Chaudhary G (2019) A methodology to improve the performance of PV integrated shading devices using multi-objective optimization. Appl Energy 247:731–744 Tian X, Wang J, Ji J, Xia T (2022) Comparative performance analysis of the flexible flat/curved PV modules with changing inclination angles. Energy Convers Manage 274:116472 Tian X, Wang J, Yuan S, Ji J, Ke W, Wang C (2023) Investigation on the electrical performance of a curved PV roof integrated with CIGS cells for traditional Chinese houses. Energy 263:125911 Vossen FM, Aarts MP, Debije MG (2016) Visual performance of red luminescent solar concentrating windows in an office environment. Energy Build 113:123–132 Walker L, Hofer J, Schlueter A (2019) High-resolution, parametric BIPV and electrical systems modeling and design. Appl Energy Barking Then Oxford 238:164–179 Wang C, Ji J, Yu B, Zhang C, Ke W, Wang J (2022) Comprehensive investigation on the luminous and energy-saving performance of the double-skin ventilated window integrated with CdTe cells. Energy 238 Yang SL, Cannavale A, Di Carlo A, Prasad D, Sproul A, Fiorito F (2020) Performance assessment of BIPV/T double-skin facade for various climate zones in Australia: effects on energy consumption. Sol Energy 199:377–399 Zhang X, Zhang H, Wang Y, Shi X (2022) Adaptive façades: review of designs, performance evaluation, and control systems. Buildings 12:2112

Embracing Local Biodiversity in Sustainable High-Rise Facades in Subtropical China C. Herr, C. Li, M. Yan, and Y. Zhou

Abstract This paper extends the current focus in sustainable building design on aspects of building technology such as assessment of carbon emissions, embodied carbon or energy expenditure by including concerns of human inhabitants as well as ecological aspects. Sustainable design schemes increasingly feature green elements on and around buildings, including green roofs and green facades. While their benefits are recognized from a technical perspective, such as the regulation of air quality and reduction of noise as well as the reduction of building energy expenditure, the ecological aspects of such facades have not received much attention yet beyond a few case study buildings. In contrast, the potential contributions green building features can make to local biodiversity, urban ecological contexts and human well-being are not yet widely embraced. This paper discusses façade systems integrating green features for ecological as well as energy and carbon emission benefits alongside other sustainable design technologies, with a focus on the subtropical climate regions of china. We argue that successful façade design needs to address three aspects that remain understudied in recent literature: the capability of architectural facades to adapt to the human need to connect to exterior environments, to perform a host role for locally specific ecology and biodiversity and the role of local climate and urban context in comprehensive future façade design. To this end, the paper presents a crossdisciplinary, eco-systemic analysis of a building case study located in Shenzhen, china which was completed in early 2022. A discussion of design principles employed in the case study is complemented with a biodiversity analysis and proposals for alternative design approaches for ecological façade features. Keywords Sustainable design · Façade systems · Energy · Carbon emission

C. Herr · C. Li · M. Yan Southern University of Science and Technology, Shenzhen, China Y. Zhou City University of Hong Kong, Hong Kong, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_5

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1 Introduction While sustainable building design comprises a broad and evolving canon of design strategies, it typically focuses on aspects of building technology such as the assessment of carbon emissions, embodied carbon or energy expenditure. Accordingly, building facades designed within this framework tend to focus on quantifiable aspects of energy use or emissions. More recently, sustainable design is broadening its scope to include concerns for human well-being as well as ecological aspects. Previous studies have shown that integrating plants into the building envelope offers numerous benefits, such as increasing biodiversity, providing habitats and extending local ecology, mitigating urban heat islands, improving indoor and outdoor air quality, reducing building energy expenditure and reducing noise (Getter and Rowe 2006; Diamond et al. 2013; Manso and Castro-Gomes 2015; Aithal 2017; Besir and Cuce 2018; Addo-Bankas et al. 2021). Accordingly, comprehensive sustainable design schemes increasingly include green elements such as planted areas around the building, green roofs and green facades. Despite their benefits from a technical perspective, the ecological potentials of such facades have found limited application on high-rise buildings beyond a few well-known examples such as the Bosco Verticale residential building in Milan or the One Central Park mixed-use residential and commercial building in Sydney, respectively. This paper proposes an integrated perspective on façade systems, discussing green features on building facades in terms of their ecological as well as energy and carbon emission benefits. Addressing the integration of technological and ecological perspectives within an architectural design framework, we argue that successful façade design should address three aspects that remain understudied in recent literature: the capability of architectural facades to respond to the human need to connect to exterior environments, the high-rise building façade as a host for locally specific ecology and biodiversity and the role of local climate and urban context in comprehensive future façade design. To this end, the paper argues for a cross-disciplinary, eco-systemic approach to design and exemplifies this approach with an applied building case study located in Shenzhen, China, that was designed and certified as a net-zero carbon building and completed in early 2022. An analysis of the design principles employed in the case study is complemented with the discussion of potential alternative design strategies demonstrating the opportunities and challenges of designing specific ecological facade features.

2 A Brief Literature Review Sustainable or green buildings are high-performance buildings that consider and reduce their impact on the environment and human health (Yudelson 2010), while aiming to create a sustainable, resilient, and livable city (Weisser et al. 2023). Accordingly, sustainable architecture design aims to reduce the impact of construction on

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the environment by implementing green technologies for aspects such as energy, water systems, natural lighting, and natural ventilation (Neyestani 2017). Based mostly on quantitative considerations, existing sustainable design frameworks are human-centric and performance-focused (Sassi 2006; Iyengar 2015; Aithal 2017). More recently, sustainable design has broadened its research scope to include ecological aspects. A variety of conceptions of ecology have been adopted as part of design approaches in the past, as early as Ian McHarg’s landscape planning focused design with nature (McHarg 1969) and Paolo Soleri’s urban planning focused arcology (Soleri 1974). In 2008, Ken Yeang formulated a comprehensive set of sustainable architectural design strategies he called EcoDesign (Yeang 2008) which featured green elements of buildings and called for the integration of different perspectives in design, including ecology, architecture, urban design and landscape design. Despite the increasing importance attributed to green elements, interactions between humans, plants and animals have not received much attention until recently. In the past five years, an increasing number of studies has focused on ecology as part of architectural design. Responding to the biodiversity loss caused mainly by urbanization, Catalano et al. (2021) argued that unintentional habitats across urban spaces could be shared between humans and natural ecosystems. This Reconciliation Ecology involves a multidisciplinary design framework including architecture, cities, and landscape. Focusing on the building envelope, Weisser et al. (2023) proposed a multi-species design system, Ecolope, to transcend conventional anthropocentric design strategies and to establish improved human-nature relationships in cities. An applied example of nature-inclusive design was offered by Wildenberg (2022), who investigated specific local biodiversity as part of an architectural design project that provides a broad variety of habitats for local species. Ecological design initiatives respond to the severe biodiversity loss that rapid urbanization has caused, especially in high-density cities and their central areas (McKinney 2002; Rockström et al. 2009; Kowarik et al. 2020). Biodiversity can positively affect both ecosystems and the lives of its human inhabitants (Hooper et al. 2012). As viable low-impact methods to reintroduce green elements into urban spaces, establishing plant materials on walls and roofs, such as green walls and roofs, shows great promise (Getter and Rowe 2006, Orbendorfer et al. 2007; Colla et al. 2009; Elgizawy 2016). Many studies have indicated that green elements can potentially provide not only human-centered benefits, such as heat insulation, dustproofing, cooling, air purification and micro-climate improvement, but can also increase biodiversity by growing more plants providing habitats for urban wildlife, including birds, spiders, and beetles (Getter and Rowe 2006; Köhler 2008; Hop and Hiemstra 2012; Manso and Castro-Gomes 2015; Elgizawy 2016; Long 2018). In the context of increasingly densely populated urban areas, ecological design approaches cannot remain limited to roofs and balconies of low-rise buildings but must also address the large façade areas of high-rise buildings. High-rise buildings consume high amounts of energy and require more complex façade technologies along with special fire protection and maintenance approaches (Moghadam and Feizabadi 2018). For this reason, green elements are not common on high-rise building facades with only few built exceptions, such as the Oasia Hotel Downtown building

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in Singapore or the Eden Tower in Frankfurt. With ecological awareness still relatively low among architectural designers, however, these buildings tend to be known for their aesthetics instead of their actual performance, including their ecological benefits. In China, green facades were introduced around 1980, with interest peaking during 2010–2020 after government policies encouraged three-dimensional architectural greenery, especially in the big cities and subtropical China (Opinions of the Beijing Municipal People’s Government on Promoting the Construction of Threedimensional Greening in Urban Space 2011; Measures for the implementation of three-dimensional greening in Shenzhen 2019). A significant proportion of existing high-rise projects in China are located in large cities in the subtropical climate zone, such as Shenzhen and Guangzhou. In response to immediate challenges for high-rise buildings in subtropical China, design efforts so far focused primarily on high-tech responses to the year-long intense sunshine hours and complex wind environment (Huang et al. 2009). Deng (2017) was one of the first researchers examining ecological high-rise buildings in subtropical China by integrating Niche analysis based on Niche Theory (Whittaker et al. 1975) into preliminary design and assessing ecoefficiency. While Deng’s proposal integrates ecological solution aspects it remains focused on quantification of architectural energy exchange. Yet another rare case of high-rise green building facades in China is the Qiyi Forest Garden residential estate in Chengdu, completed in 2019, which features similar green design strategies as the well-known Bosco Verticale building in Milan, Italy. In contrast to the Bosco Verticale however, the Qiyi Forest Garden greenery seems to be installed primarily based on aesthetic considerations, and public reception has been mixed after the plants on unoccupied flats grew in an uncontrolled manner (Ikiz 2023). In summary, ecological considerations still rarely factor into the design of architectural green features, and biodiversity concerns are only beginning to be implemented into comprehensive sustainable design strategies. In part, this is due to insufficient available studies and guidelines on how green architectural facade features can be designed to support biodiversity. Our study, presented in the following sections, is a first step in responding to this gap in current research. It offers a biodiversity survey and related discussion of the ecological aspects of a completed zero carbon building in subtropical China in the following sections.

3 Case Study: The Future Complex in Longgang, Shenzhen The building we examine is located in Shenzhen, a city in the subtropical climate zone of China. The Future Complex Building (FCB), shown in Fig. 1, is an office building for research and development purposes that was designed and built by the Shenzhen Institute of Building Research Co., Ltd. (IBR) (Shenzhen Institute of Building Research Co., Ltd. internet source with no date). The building has a builtup area of 62,894 m2 and was completed in early 2022 as part of the Shenzhen International Low Carbon City in Longgang District, Shenzhen.

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Fig. 1 Overview of FCB: a Bird-view rendering of the entire project site, with building A located at the southeastern corner; b Study focus areas for the biodiversity survey shown in the general plan; c View of FCB from the east to the west side; d study focus areas for the biodiversity survey shown in the building elevations

3.1 The Green Building Design Approach of IBR IBR is a high-tech enterprise based in Shenzhen, China since 1992, and mainly focuses on the creation of local, low-cost, high-tech yet feasible types of green buildings. IBR employs their green building design approach in the design and construction of their own office buildings, with the first one, the IBR Headquarters Building (IBR building), completed in 2009 and awarded the Chinese three-star green building rating. As a technical demonstration building, it features more than 40 sustainable technologies, including a comprehensive water saving and recycling system, energyefficient technologies as well as on-site alternative energy sources like PV, solar and wind, and extensive landscaping on the roof, central atrium, and facades (Diamond et al. 2014). With even higher ambitions, the FCB, IBR’s new mixed-use office building, is one of the Shenzhen Demonstration Buildings included in the Phase-II Cooperation Projects of the Building Energy Saving Alliance by the U.S.-China Clean Energy Research Center. The site of the building is surrounded by a large road in the South, park areas on the East and older low-rise buildings with mature greenery on the North and West sides (Fig. 1). As a scientific research building, the FCB aims at a net zero energy consumption performance goal to address climate change. To this end, the building uses extensive energy management technologies, focusing on energy use and storage as well as water management. The FCB continues IBR’s practice of creating demonstration buildings that was started with the IBR Headquarters Building (IBR Future Complex—Active House, internet source with no date). While FCB is currently not fully occupied, several floors are operated as research office spaces, and some are used for intermittent public exhibitions. In Building A, only the 4th floor is currently occupied. The following sections of this paper focus on the ecological aspects of the building and an initial biodiversity survey.

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Fig. 2 The deep façade with planting and maintenance corridor on the East façade (left), and a section detail of the 4th floor of building A (right)

3.2 The Future Complex Building’s Green Façade System Based on overviews collating typological considerations in green façade design by Manso and Castro-Gomes (2015) and Besir and Cuce (2018) respectively, the green facade system employed on the FCB can be described as an indirect green façade using modular soil containers. Building A of the FCB features double-layered deep facades with narrow maintenance corridors between the façade layers. The primary function of the greenery on the eastern façade is to enhance occupant comfort and reduce operational energy by providing shading and cooling. The design team also recognized the negative impact of façade greening on views and opted to restrict green elements to the East and North facades. While green elements were a core part of the building design concept, many decisions were made in an experimental way only late in the building design process and differ from more formal planning that was obtained from an external landscape planning consultant. As shown in Fig. 2, modular planters are placed in intermittent floors on outer side of the maintenance corridor directly attached to the secondary façade structure that is cantilevered from the main building structure. The secondary façade structure further supports continuous thin vertical cables acting as guides for vine growth. The pre-vegetated elements are only placed on the east and north façades of Building-A.

3.3 Biodiversity Survey Results The biodiversity survey was conducted by walking through the FCB exterior and interior areas to survey the green areas located on the ground floor and the East and North elevations on October 24, 2022, and February 9, 2023. Species were identified and recorded as plants or animals (including birds, insects, and spiders). Figure 3 shows the overall results of the survey.

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Fig. 3 a Biodiversity identification of plants; b biodiversity identification of animals; c distribution of animal and plant species schematically mapped in relation to the building elevation of Building-A

Birds were observed through binoculars, with the classification based on A field guide to the birds of China (MacKinnon et al. 2000). Insects and spiders were recorded with a camera and high-resolution photos were uploaded onto the website iNaturalist 1 for further identification. We used the same recording method for the plants, but the identification was based on Plant Science Data Center 2 . All 48 observed species are listed in Fig. 3, most of which were found on the first floor. Some species which could not be identified precisely have been recorded as their likely higher classes. The seventeen kinds of animals observed in the survey consist of four birds, two spiders and eleven insect species. Among the insects, only two undesired species were observed: the Aleyrodidae, which is a pest, and Solenopsis invicta, which is a widespread invasive insect originally from South America. Among the 31 plants, both wild and cultivated plants were found. Most are cultivated as the pre-vegetated green planters located on the 1st to 8th floor (Fig. 2). The three wild plants are common viable weeds in Shenzhen: Symphyotrichum subulatum, Stellaria aquatica and Youngia japonica, which were all found on the first floor. 1 2

iNaturalist (no date). Available at: https://www.inaturalist.org/. Plant Science Data Center (no date). Available at: https://www.plantplus.cn/en.

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4 Discussion and Findings The quantitative visualization shown in Fig. 3c illustrates the biodiversity distribution in FCB, characterized by a marked difference in observed diversity between the ground floor and the higher floors of the building. The diagrammatic representation in Fig. 3c shows how biodiversity distributed on and around the examined building differs from biodiversity distribution in natural environments, where biodiversity is more likely to gradually change with increasing elevation. Only one Hasarius adansoni spider was found on the third floor, while all others were observed on the first floor (Fig. 4a). No other animals were found on higher floors. The distribution of plants follows a similar pattern. Apart from the few cultivated and evenly distributed plants, only three wild species were found on the first floor. Based on these observations, reasons for a lack of observed diversity relate to the limited diversity of cultivated plant species, limited diversity in the distribution of cultivated plants, and deficient connections between green areas. In the design of the current FCB green building façade features, species selection and distribution mainly followed criteria for sun shading as well as ornamental design intentions, resulting in a green and technically functional but at the same time ecologically deficient environment. Initial design concepts for the green façade features (not shown in this paper) were focused on creating vertical green features offering primarily visual patterns for the façade surface. These included vertical strips as well as large hexagonal green frames to represent cells or organisms, adopting plants of different colors to enrich the visual effects. In such schemes, many less competitive plants are likely to be replaced by freshly added ones as part of periodic maintenance, and adjustments of the overall artificial greenery system in order to respond to potential deficiencies of green feature design in the long term. To be able

Fig. 4 Strategies for supporting increased biodiversity in ecological building façades. a The schematic diagram of the current FCB east elevation with approximate locations of different species; b proposed façade features for enhanced biodiversity support; c matured integrated multispecies façade system

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to place and maintain plants in viable configurations supporting biodiversity in the case of the FCB and similar buildings, a more comprehensive long-term investigation of local ecological conditions and contexts is needed. Currently, the distribution of animals in the survey shows a strong relationship with plant diversity and spatial configuration. Selecting suitable plant species and distributions can create a broader variety and density of potential hiding spaces to reintroduce more animals to green features. Although we also found one spider on the third floor, the limited plant diversity of only four species and sparse shading seems not attractive enough for migration. To create supportive conditions for animals, especially insects and spiders, human intervention needs to be minimized. While plants are stationary, animals need increased movement ranges. On the ground floor of the FCB, this is made possible by spatial proximity and physical connections between a variety of plants. The current green façade of the FCB offers less plant diversity as well as less connectivity and thus restricts movement ranges of animals. We propose that biodiversity-aware design can provide more physical connections to shorten distances between green patches to support and enhance the mutual interactions between plants and animals. Figure 4b and c illustrate schematic facade design strategies to embrace biodiversity on architectural building facades in response to the biodiversity survey presented above. The proposal features more connective elements of different scales and forms such as linear as well as area-based elements (lattices). We anticipate that in combination with increased diversity of plants and selection of plants offering food and shelter to animals, such features will create a more coherent biodiversity strategy by enabling animals to move across green façade systems.

5 Summary Sustainable design has recently broadened its scope to integrate ecological perspectives. Architectural green elements can be an extension of natural features of urban ecological systems by offering habitats and food sources to a broad variety of species. Many recent sustainable building projects contain green features but lack ecological considerations in the design of green elements. In this paper, we examine the biodiversity aspects of an integrated sustainable façade on a high-rise building located in Shenzhen, China. While the project is a successful energy-efficient zero carbon building design integrating green features in its overall design strategy, we also find that its biodiversity profile could be further improved. As potential hosts for animal and plant life, sustainable high-rise buildings could do more to support larger urban ecosystems. The biodiversity survey results and discussion we present in this paper illustrates how successful sustainable façade design can potentially integrate high-tech methods with high quality ecological features to strategically blend interior and exterior environments. To this end, we offer several strategic approaches that result from our empirical findings. We argue that further work needs to be conducted to better

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understand and respond to local biodiversity through sustainable high-rise building design. We also argue that biodiversity should be considered a future integrated sustainable façade performance criterion.

References Aithal S (2017) A review on sustainable building (green building). Social Science Research Network [Preprint]. Available at: https://doi.org/10.2139/ssrn.2968885 Besir A, Cuce E (2018) Green roofs and facades: a comprehensive review. Renew Sustain Energy Rev 82:915–939 Catalano CE et al (2021) Smart sustainable cities of the new millennium: towards design for nature. Circular Econ Sustain 1(3):1053–1086 Colla SR et al (2009) Can green roofs provide habitat for urban bees (Hymenoptera: Apidae)? Cities Environ (CATE) 2(1) Deng M (2017) Research on the ecological design strategy for super high-rise buildings in Lingnan (岭南超高层建筑生态设计策略研究). PhD thesis. South China University of Technology Diamond R et al (2014) Model for China’s future. Shenzhen Institute of Building Research Headquarters Building, Shenzhen, China, pp 18–28 Diamond RC et al (2013) Sustainable building in China-a green leap forward? Buildings 3(3):639– 658 Elgizawy EI (2016) The effect of green facades in landscape ecology. Procedia Environ Sci 34:119– 130 Getter KL, Rowe DE (2006) The role of extensive green roofs in sustainable development. Hortscience [Preprint] Hooper DC et al (2012) A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature 486(7401):105–108 Hop MECM, Hiemstra JA (2012) Contribution of green roofs and green walls to ecosystem services of urban green. In: II International symposium on woody ornamentals of the temperate zone, vol. 990. Ghent, Belgium, July 1–4, 2012, pp 475–480 Huang H et al (2009) Application of green and energy-saving building technology in super high-rise buildings in subtropical regions (in Chinese). Archit J 9:99–101 Ikiz SU (2023) Vertical gardens are cool but what about mosquitoes? Parametric Architecture, April 03 2023 [Online] Available at: https://parametric-architecture.com/vertical-gardens-arecool-but-what-about-mosquitoes/ Iyengar K (2015) Sustainable architectural design: an overview. Routledge Köhler M (2008) Green facades—a view back and some visions. Urban Ecosyst. 11(4):423–436 Kowarik I et al (2020) Biodiversity conservation and sustainable urban development. Sustainability 12(12):4964 Long H (2018) The use of green roofs and living walls to regenerate the urban eco-system and revitalize the public realm. (Unpublished document submitted in partial fulfilment of the requirements for the degree of Master of Landscape Architecture). Unitec Institute of Technology, Auckland, New Zealand. Available at: https://www.researchbank.ac.nz/handle/10652/4562 MacKinnon JR et al (2000) A field guide to the birds of China. Oxford University Press Manso M, Castro-Gomes J (2015) Green wall systems: a review of their characteristics. Renew Sustain Energy Rev 41:863–871 McHarg IL (1969) Design with nature. American Museum of Natural History McKinney ML (2002) Urbanization, biodiversity, and conservation. Bioscience 52(10):883 Moghadam TT, Feizabadi M (2018) Increasing ecological capacity by designing ecological high-rise buildings. Open House Int 43:94–104

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Measures for the implementation of three-dimensional greening in Shenzhen (深圳市立体绿化实 施办法) 2019. Available at: http://www.sz.gov.cn. Accessed 30 Mar 2023 Neyestani B (2017) A review on sustainable building (green building). SSRN Electron J 6(1):451– 459 Oberndorfer E et al (2007) Green roofs as urban ecosystems: ecological structures, functions, and services. Bioscience 57(10):823–833 Opinions of the Beijing Municipal People’s Government on Promoting the Construction of Threedimensional Greening in Urban Space (in Chinese) 2011. Available at: http://www.beijing. gov.cn. Accessed 30 Mar 2023 Rockström J et al (2009) Planetary boundaries: exploring the safe operating space for humanity. Ecol Soc 14(2):32 Sassi P (2006) Strategies for sustainable architecture. Taylor & Francis Shenzhen Institute of Building Research Co., Ltd. (no date). Available at: https://szibr.com. Accessed 30 Mar 2023 Soleri P (1974) Arcology: the city in the image of man. J Aesthet Art Critic 33(1):115 Weisser WW et al (2023) Creating ecologically sound buildings by integrating ecology, architecture and computational design. People Nat 5(1):4–20 Whittaker RH et al (1975) On the reasons for distinguishing ‘Niche, Habitat, and Ecotope.’ Am Nat 109(968):479–482 Wildenberg E (2022) Nature inclusive design in high-density urban development to support urban biodiversity [Online]. Living with nature in Sloterdijk, Humboldt. Available at: http://resolver. tudelft.nl/uuid:a9e231dd-d9fa-4cb4-b135-226dba146ce6. Accessed 09 Mar 2023 Yeang K (2008) Ecodesign: a manual for ecological design. Wiley, Hoboken Yudelson J (2010) The green building revolution. Island Press, Washington DC

AI-Based Models in Support of Human-Centric Indoor Environment Design: Towards Climate-Adaptive Façade Design Integrating Occupant Satisfaction Y. Zhou, C. M. Herr, and J. Y. Tsou

Abstract With the emergence of Sick Building Syndrome (SBS) symptoms, the impact of the indoor environment on occupant health, productivity, and satisfaction has received much attention over the last few decades. The control of the indoor environment through building systems is equally important in the context of human health and energy efficiency but challenging to achieve in a comprehensive manner in practice. Due to the variability of indoor and outdoor contexts over time, as well as the subjective nature of building occupants’ perception of indoor environments, it is however difficult to recommend and design building systems that meet both occupants’ preferences and general indoor health criteria. More recently, advanced data acquisition technologies such as IOT and distributed cameras have created new opportunities to capture and quantify occupant satisfaction. In combination with recent advances in Artificial Intelligence, new opportunities arise to use historical data to analyze and predict the relationship between physical environments and their occupants’ satisfaction. The application of these advanced technologies offers new approaches to control building systems with a focus on more human-centric and intelligent approaches. To this end, this paper reviews new AI technologies and approaches that can be used in building systems control to enhance occupants’ satisfaction, health and wellbeing affected by indoor environment. The paper focuses on previous studies using physical environment data and occupants’ feedback in combination with AI models. Concluding the review, the paper identifies the most promising applications of AI models for intelligent building system control and discusses their potential impact on the design and operation of future building environments. Keywords Indoor environment design · Artificial intelligence · Occupants’ satisfaction · Building system control Y. Zhou · J. Y. Tsou Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China Y. Zhou · C. M. Herr School of Design, Southern University of Science and Technology, Shenzhen, Guangdong 518055, PR China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_6

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1 Introduction Sick Building Syndrome (SBS) has brought attention to the importance of green building certification schemes that prioritize occupant health. SBS symptoms, such as headache, tiredness, respiratory and ocular irritation (Hodgson 2000), have led to increased study on indoor environment quality and occupant satisfaction. This is crucial because we spend over 90% of our time in buildings (Ponce et al. 2016), and indoor environmental quality affects our health and productivity. Including actual occupant behavior in building energy simulations can greatly affect energy consumption (Fisk and Rosenfeld 1997; MacNaughton et al. 2015). Therefore, actual occupancy and interactions with buildings are key determinants of building energy consumption (Akadiri et al. 2012; Belussi et al. 2019). The energy-related behavior of occupants in buildings can be defined as their responses to comfort or discomfort: Occupants’ presence, movement, and interactions with building systems affect the performance of buildings in terms of energy, thermal comfort, visual comfort, acoustics, and indoor air quality (Bélafi and Reith 2018). However, due to differences in physical, physiological, and psychological factors among occupants, as well as external factors such as economics and culture, users do not all respond to their environments in the same way (Bluyssen 2020). They may adapt buildings to their own thermal comfort and improve indoor air quality by bringing in fresh air to eliminate pollutants and odors, as well as by controlling acoustical conditions to avoid unwanted noise and vibrations, visual conditions by adapting lighting, reflections, and glare, and thermal conditions by controlling indoor air temperature. Overall, IEQ has a significant impact on occupant health and productivity. Correspondingly, occupant discomfort caused by poor quality indoor environments is likely to increase corresponding system operation levels of HVAC, lighting, and window openings, leading to higher operational energy consumption as well as carbon emissions. Behavior patterns of occupants vary not only between individuals but also tend to change over time (Zhao et al. 2016). The stochastic and complex nature of occupant behavior and preferences in buildings makes it challenging to model and predict (Yan et al. 2015). However, integrating AI to create dynamic models to regulate building systems and predict occupant behavior is emerging as a potential approach to building system control to enhance human comfort and productivity while mitigating energy and carbon emissions (Alanne and Sierla 2022). This approach supports human-centric and data-driven design for the sustainable development of the building industry. Despite extensive research on how energy related building systems are controlled to enhance the indoor environment quality and energy efficiency, there is still a lack of comprehensive and in-depth understanding regarding the impact of occupant behavior on operational energy. As Yan et al. (2017) explained, occupant behavior includes presence, movement, and interaction with building energy devices and systems.

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Most of the control algorithms studied for investigating occupant-building system interaction so far are dedicated to making HVAC systems more automated or intelligent to alleviate energy demand and enhance occupants’ indoor comfort. However, facade systems, as the systems that serve as the interface between indoor and outdoor environments and most directly affecting occupants’ indoor comfort, have rarely been developed to the functionality advocated by related research. Aelenei et al. (2016) demonstrated that adaptive facades are most commonly influenced by solar radiation and outdoor temperature. Generally, external factors have a direct impact on thermal and visual comfort of occupants as well as on the energy performance of buildings. The primary goal of current adaptive facades thus emerges as the goal of enhancing human comfort, with other factors resulting from this primary performance criterion. However, constructing adaptive façade designs remains difficult and costly due to geometrical complexity and mechanical actuation. Completed cases of adaptive facades are limited to small-scale experimental or high-budget projects, highlighting barriers to industrialization and commercialization. Proposed kinetic design elements have so far remained confined to digital modeling and simulation. In the following, this paper addresses the central question of how to respond to occupant comfort in a comprehensive and intelligent way by summarizing and critically reflecting on the existing literature in machine and deep learning methods for learning and predicting occupant satisfaction. The review addresses a current research gap in modeling the relationship between occupant behavior, physical indoor environment, and operational energy by integrating HVAC, lighting, and adaptive façades into one comprehensive control algorithm. Our approach differs from previous research by focusing on the potential of adaptive facade design to improve indoor environment quality and energy efficiency, and focuses on the comfort level in the totality of indoor environments instead of one particular domain. Research results aim to support the design of intelligent facades to enhance human health and productivity in office high-rise buildings in the hot and humid climate of Subtropical China.

2 Method An extensive literature search was performed to identify publications on existing studies on the application of machine and deep learning methods for indoor environment and occupant behavior. Peer-reviewed journals and conference papers from the last decade (2013–2023) were searched using the Scopus search engines. The search was carried out using keywords occurring in the title, abstract and keywords of papers, including “machine learning” OR “deep learning” OR “reinforcement learning”) AND (“human” OR “occupant” OR “user”) AND (“comfort” OR “satisfaction” OR “sensation” OR “perception” OR “occupant-centric”) AND “indoor environment”. We initially selected and reviewed 93 articles. A further selection process considered the relevance of the papers to our research scope through a manual review of the publication title as well as the abstract and method sections. Following a process

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of identification, screening, eligibility analysis we included papers depending on their ability to address the topic of comfort level in relation to occupant feedback, and excluded papers defining comfort levels by PMV indications. Finally, 14 recent papers are selected as highly relevant to our research scope.

3 AI-Based Model Application in the Built Environment AI-based approaches adopted in occupant behavior prediction and modeling are mainly focused on three aspects of the built environment. The first is the application of AI to forecast a building’s energy demand over time. By employing AI in combination with large data sets, the accuracy and speed of energy demand forecasting can be increased compared to traditional predictive models (Mo and Zhao 2021). This facilitates building energy simulations without the requirement of detailed information about the building (Zhang and Jia 2016). The second aspect identified for AI implementation is to predict building occupancy. In this area, several studies have used conventional sensors such as RFID and environmental sensors to estimate the number of occupants in a room (Pan et al. 2010). Some studies have applied AI models based on input data derived from cameras for dynamically sensing occupancy. The utilization of camera-based techniques for occupancy and activity detection (Virote and Neves-Silva 2012) has been increasing recently due to the advancement of deep learning-based techniques such as Convolutional Neural Networks (CNN) (Ijjina and Chalavadi 2017). These techniques allow for enhanced distinguishing among human occupants’ actions and provide greater flexibility, performance, and accuracy. The third aspect for AI-based modeling is the prediction and enhancement of thermal comfort in buildings (Azuatalam et al. 2020). These control systems can use ML methods to adjust indoor thermal conditions in accordance with occupant preferences, while enhancing energy efficiency.

3.1 AI-Based Model Application for Occupant Behavior, Health, and Satisfaction Few previous studies have used AI to predict users’ behaviors. Ijjina and Chalavadi (2017) proposed a framework for human action recognition that uses motion in RGB and depth video streams to extract features and to train a classifier in a convolutional neural network model to predict activity. Castro et al. (2015) presented a method for analyzing images taken from a wearable camera to predict daily activities of an individual. Within the investigation, a dataset of 40,103 egocentric images over six months with 19 activity classes was taken, and the author used a Convolutional Neural Network (CNN) with a classification method to achieve an overall accuracy of 83.07% in predicting a person’s activity.

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Recent studies examine occupant satisfaction within different domains of indoor environments. Rodrigues et al. (2022) investigated the effects of short-term exposure of different air temperature and humidity conditions on human thermal comfort, based on the analysis of the autonomic nervous system (ANS) response. The authors propose an unobtrusive method for cardio-respiratory assessment that uses a combination of sensors and machine learning algorithms. The method uses a smart humidifier in combination with temperature and relative humidity sensors to monitor indoor environmental conditions. The output parameters of the AI model are heart rate variability (HRV), respiratory rate (RR), and oxygen saturation (SpO2 )2 (Rodrigues et al. 2022). Komuro et al. (2021) used three machine learning models including SVM, KNearest Neighbor (KNN), and random forest to predict emotions. This is based on the input features of heart rate and skin temperature collected by wearable devices, and environmental parameters collected by sensors. The output is the predicted emotion category of the individual, including: “happy”, “stressed”, “sad”, or “relaxed”. Assaf and Srour (2021) used machine learning to predict thermal discomfort using the complaints history data obtained from the facility management unit to develop time series of heating and cooling-related complaints. These time series, along with exogenous weather-related features, are used as input parameters for the MLP model to forecast the number of thermal complaints, similar study aims can also be found in a study conducted by Kim and Kang. The authors developed an AI-based model called Temperature Reduction Effect AI Model (TREAM) to determine the temperature reduction effect of fog cooling that varies with weather conditions. The model was developed to address the negative consequences of the Urban Heat Island (UHI) effect and summer-time heat waves on human mortality and thermal comfort.

3.2 Occupant Satisfaction as Parameter in AI-Based Models, and Applications to Building Systems Occupants’ thermal comfort votes (TCV) and thermal sensation votes (TSV) are two commonly used subjective measurement techniques in field studies and surveys to assess people’s thermal perception and preferences. Chai et al. (2020) used machine learning (ML) to predict thermal comfort and sensation in a naturally ventilated building. The authors used indoor and outdoor conditions and personal factors as input. Based on 5512 sets of thermal comfort data gathered in naturally ventilated residential structures in fourteen Chinese cities, the ML model outputs consist of occupants’ thermal comfort votes (TCV) and thermal sensation votes (TSV). The key findings include the quick ability of ML to analyze the relation between input and output parameters. Besides, compared with conventional models like PMV, ML was outperformed (Chai et al. 2020). Wu et al. (2018) used an ensemble decision trees method called Bagging to predict occupants’ thermal comfort in buildings. The inputs are various indoor environmental parameters and occupants’ thermal sensation votes. The ensemble model combines

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multiple decision trees to predict the thermal sensation. Each decision tree is trained on a random subset of the training data. The predictions from all the individual trees are then combined by averaging to give the final prediction. The output of their model is predicted subjective thermal sensation votes on a 7-point scale from −3 (cold) to +3 (hot) from occupants. Deng and Chen (2018) developed artificial neural network models to predict the thermal sensation and comfort of building occupants based on environmental parameters as well as occupants’ thermal sensations and thermoregulatory behaviors (Deng and Chen 2018). Occupants’ votes on their own thermal sensations and their actions to improve comfort like adjusting thermostats or opening windows were collected. Deng and Chen (2018) used ANN model to predict thermal sensation of occupants on a 7-point scale from −3 (cold) to +3 (hot). Ali et al. (2022) used machine learning models along with demographic, indoor environmental and survey data to automatically determine how demographics affect indoor environmental perception. The inputs are demographic, indoor environment and occupants’ satisfaction survey data. The outputs are the predicted impacts and influence of demographics on perception. Lee et al. (2022) propose an occupant-centered real-time control of indoor temperature using deep learning algorithms to make real-time predictions and generate optimal control strategies for the HVAC system in an office building (Lee et al. 2022). Specifically, they use a long short-term memory (LSTM) neural network to predict personalized thermal preferences and a model predictive control (MPC) algorithm to determine the optimal control inputs for the HVAC system. Input parameters in their AI-based model includes occupant thermal feedback (too warm/too cold votes), indoor environmental data (air temperature, relative humidity, CO2 level, etc.), and occupant attributes (age, gender, clothing insulation, activity level, etc.).The output parameters consist of predicted thermal preference (target temperature) for each occupant, and optimal control inputs (supply air temperature set points) for the HVAC system to satisfy the predicted thermal preferences of all occupants (Lee et al. 2022). Liu et al. (2021) used a long short-term memory (LSTM) based recurrent neural network model to predict occupants’ thermal preference. LSTM is a type of recurrent neural network that can learn long-term dependencies. One of the input features for the LSTM model are indoor environmental parameters (such as air temperature, relative humidity, air velocity, metabolic rate, and clothing insulation, which are measured by sensors in the office. Another set of input parameters are occupants’ adaptive behaviors: opening/closing of windows and doors as well as turning on/off fans and heaters. These behaviors are logged manually by the researchers. Besides, time information (hour of day, day of week, month) are also included in input parameters in the LSTM model to capture potential patterns related to time. The output is the occupants’ thermal preference on an 11-point scale from −5 (cold) to 5 (hot). The occupants’ thermal preferences are collected using questionnaires where the occupants rate their thermal sensation (Liu et al. 2021). Based on collected data on the satisfaction level of the single domain of indoor environment and occupants’ demographic information, Lin et al. use several AI-based model to predict overall comfort, perceived productivity, and perceived happiness (Liu et al. 2021).

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Huang et al. (2023) proposes a Space Match framework that leverages personal comfort models developed for each occupant using machine learning and natural spatial- temporal temperature variations in buildings to make space recommendations. The framework reimagines occupants as mobile agents who are willing to move to spaces where the conditions best match their personal preferences and needs. The input parameters for the Al model are personal comfort models developed for each occupant using machine learning and natural spatial–temporal temperature variations in buildings. The output parameter is space recommendations that match occupants’ personal preferences and needs.

4 AI-Based Model Application on Façade Design The challenge of developing intelligent facades capable of enhancing indoor environments at the same time as energy efficiency has very few precedent studies currently available. Fattahi et al. (2022) for example discussed the challenge of designing and implementing adaptive façade designs with a view to constructability. To this end, at least the three aspects of energy, structure and mechanical performance have to be considered. While some proposed intelligent facades are in principle constructible, their construction would be difficult and costly, with construction difficulties and cost deriving from geometrical complexity and mechanical actuation (ibid.). Overall, the practical application of adaptive facades to buildings has remained limited, with completed cases primarily relegated to either small-scale experimental projects or high-visibility, high-budget projects. One of the earlier examples of adaptive facades application is the Institut du Monde Arabe in Paris. Its south-facing facade features a series of light-sensitive, mechanical apertures inspired by traditional Islamic patterns. These apertures open and close in response to sunlight, providing optimal shading and natural light control. For energy conservasion design purpose, the façade system applied on Al Bahr Towers, Abu Dhabi, featuring a dynamic facade consisting of a series of folding umbrella-like shading devices. The façade system is designed to respond to the sun’s position and provide optimal shading throughout the day, reducing solar heat gain and energy consumption. Another example of the implement of adaptive façade system is the façade system applied on Media-TIC Building in Barcelona. It features an inflatable ETFE facade that can adapt to changing weather conditions. The facade is divided into several air chambers, which can be inflated or deflated to provide optimal insulation and shading. This further illustrates existing barriers of industrialization and commercialization of adaptive façades. In addition, some proposed kinetic design elements have so far remained confined to digital odelling and simulation. Given these limitations, the emergence of AI-based approaches and their implementation in the context of adaptive façade design offers new opportunities to empower the geometrical complexity and mechanical actuation design with higher capacities to enhance IEQ for occupants’ satisfaction and preference and energy efficiency. Only few studies to date have implemented AI techniques to predict features and further improve the capacity of façade component design for

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better building performance. Wang et al. (2022) proposed a workflow for designing an adaptive facade that takes into account the glare and thermal discomfort of the occupants. To identify user activities, a Convolutional Neural Network (CNN)-based model was utilized. Luo et al. (2021) used a radial basis function neural networkbased MBC method to regulate several blinds in an open office simultaneously. Using surrogate odelling approaches are used to forecast particular performance measures improves operational efficiency.

5 Conclusion and Future Work The brief review of recent literature presented in this paper points towards a gap in previous studies in that the entirety of occupant experience of indoor environments is often not fully understood or considered with a view to building systems controls. The majority of recent research focuses on evaluating and controlling only single aspects of the indoor environment, such as thermal comfort which is the most frequently studied domain. However, the indoor environment encompasses many factors beyond temperature that also determine occupant satisfaction and preference, including air quality, lighting, acoustics, and layout. Without a more comprehensive understanding of how all these different environmental domains interact to impact occupants, building systems cannot be designed and operated to provide the most habitable and responsive indoor environment. Further research needs to address occupant evaluations and feedback that cut across these different domains to gain a holistic view of what influences occupants’ comfort, satisfaction and productivity within a space. Only by evaluating the indoor environment in a multi-domain, integrated manner can be building controls start to facilitate a more comprehensive responsiveness to respond to occupant comfort and productivity. Occupant inputs on the indoor environmental experience as a whole are critical for achieving this integrated approach to intelligent building systems. Overall, current research and building controls do not yet provide a complete picture of how the totality of the indoor environment affects occupants and their behaviors. To improve indoor environments and enable intelligent building controls, a multi-domain and occupant-centered understanding of what constitutes a high quality indoor experience is needed. Once such models are available, designers will be able to address current challenges encountered in kinetic adaptive façades within design frameworks extending a current focus on geometric complexity and aesthetics. A combination of generative geometrical design implementing constructability considerations and based on the integration of dynamic AI based prediction and control models for building control systems are suggested as a future research direction to lead to more efficient and comfortable buildings that prioritize the needs of occupants.

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Consideration on Carbon Emission of Existing Buildings in the Stage of Ultra-Low Energy Consumption Reconstruction Xiu Han and Jinghua Shen

Abstract In China’s construction market, most existing buildings have high energy consumption and significant carbon emissions. This paper selects an office building in hot summer and cold winter areas for energy-saving transformation from high energy consumption to an ultra-low energy consumption building. By calculating carbon emissions in the transformation process stage by Yike Efootprint software, the building life cycle model is divided into an envelope Air tightness system, fresh air system, energy system, and door and window system. The five primary methods are described, energy input, energy consumption, pollutant output, process boundary, quantity used, upstream process traceability, sensitivity analysis. The materials and data are collected, analyzed, and calculated. The CLCD database is mainly used as the database, and some data are obtained from Ecoinvent. The CUT-OFF principle shall be used to reserve the materials with a significant weight proportion and high importance, and the materials with a weight less than 1% or with low significance and low material consumption shall be ignored. So we can get the critical influencing factors of carbon emissions in the transformation stage. By analyzing the influencing factors, we can provide some perfect suggestions for the energysaving reconstruction of buildings. This paper uses LCA for modeling, calculation and analysis, data quality evaluation, and result output. So as to calculate the carbon emissions and effective recovery period of energy consumption from an ultra-low energy consumption building to a zero energy consumption building, it is proved that the carbon emissions in the transformation process can be recovered quickly through the energy-saving transformation of ultra-low energy consumption buildings. Ultralow energy consumption buildings and zero energy consumption buildings will play a significant role in the development of China’s construction industry. It also provides more theoretical, and data support for developing zero-energy consumption buildings in China. Keywords Carbon emission · Energy consumption · Office building · Life cycle assessment X. Han · J. Shen Soochow University, Suzhou, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_7

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1 Introduction According to statistics, in 2020, the total CO2 emissions of the global construction sector will be about 11.7 billion tons (UN Environment Program 2021). accounting for 36% of the global final energy consumption and 37% of energy-related CO2 emissions. Therefore, reducing CO2 emissions from the construction sector is crucial to controlling global warming and atmospheric particulate pollution. As calculated by relevant institutions, our country is about 75 billion square meters, of which 90% is high energy consumption buildings (Tsinghua University 2020). Therefore, the carbon emission control of existing buildings will be the top priority of the two-carbon target of the construction industry. There are many methods for calculating carbon dioxide emissions. For example, there are actual measurement methods, quality balance methods, carbon emission factor methods, and Life Cycle Assessment (LCA), which are commonly used in the construction industry in our country (Cen and Zhang 2022). Bekker (1982) was the first to apply the LCA method to the construction industry to track the distribution of energy consumption and carbon emissions at various stages in construction. Explore the energy transition between the environment and the building throughout its life cycle. Peng (2012) statistically analyzed the energy consumption distribution and carbon dioxide emissions of more than 100 green building cases in the whole life cycle in China and used 304 material lists as a database to provide a theoretical basis for energy consumption and environmental impact assessment of building materials. Swedish scholar Nassen et al. (2012) used the LCA method to compare and analyze the carbon emission of 18 types of buildings and calculated the carbon emission value of the structure in the operation stage through the input and output methods. Filippin (2000) compared and calculated the carbon footprint of 15 schools and estimated the emission value and contribution value of influencing factors at each stage through the LCA method. Based on 19 countries, Schwartz et al. (2018) explored the carbon emission index of buildings between existing buildings and new buildings with 251 cases, and investigated the emission factors at each stage, to determine whether the renovation or replacement of design alternatives can achieve better performance and analyze its impact on the environment. In this paper, the existing public buildings of a university in Suzhou will be evaluated by the life cycle assessment method to calculate the carbon emission during the renovation process. The building was built in 2009 with a 300 cm thick frame structure. The existing building is located on the first floor of the whole building with an area of 300 m2 . The interior is in good condition, but due to the large glass curtain wall, the space energy consumption is huge. When transforming the building into a zero-energy building in the later stage, calculate the amount of carbon emission of the building materials and save the carbon emission recovery period. Life Cycle Assessment (LCA) is the usual method of the international standard (ISO 140000 series) and the regular practice of the GB/T24040 standard of China’s synchronous transformation. In 1990, the International Association of Environmental Toxicology and Chemistry proposed the concept of “whole life cycle assessment”

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for the first time. It established a particular advisory group for the whole life cycle in the international seminar. Since then, the theory has been formally generated and gradually developed (Zou 2020). It is to analyze the potential resource and environmental impacts of various products and technologies in the life cycle process. It is widely used in many products and technologies involving human production and consumption activities. The six steps of the LCA system are mainly divided into target and scope definition, data collection, modeling, calculation, evaluation and improvement, result report, review, and release. Currently, many LCA software can be used to calculate the impact of resources and the environment. This calculation is based on the reconstruction stage of the building. The carbon emission factor adopted is the same as that in the case of Lonan Town, Baoshan, Shanghai (Tang and Li 2022). Due to different individual conditions and configurations, the carbon emission factor is further adjusted. Adjust the part using Efootprint-CLCD, which is shown in Table 1. An example of this ultra-low-energy building model is in the Golden Mantis School of Architecture of Soochow University in Suzhou, Jiangsu Province. This building transforms the partial space on the first floor into an office space. The construction area is 300 m2 , with the main facade facing west. The model selected “transform 1 m2 office building” as the functional unit, and the system boundary was chosen from “cradle to gate”, that is, from the mining of various building material resources to the transformation of office buildings, including the conversion of enclosure system, air tightness system, energy system, fresh air system, door and window system. This transformation is to change the high-energy building into an ultra-low-energy building, so the carbon emission stage can be divided into the demolition and recycling stage of the original building and the materialization stage of the Table 1 Consumption list of main building materials and carbon emission factors Building materials

Consumption

Unit

Carbon emission factor

Data source

Passive window glass

104.6

m2

1071

www.efootprint.net

Vacuum Insulation board

794.8

m2

8.06

www.efootprint.net

Power

336

kWh

0.78

CLCD-China-ECER 0.8

Mesh cloth

0.11

t

3.28

www.efootprint.net

Bonding mortar

3.32

t

190

www.efootprint.net

Plastering mortar

3.12

t

190

Ecoinvent 3.1

Vapor barrier film

4.21E + 04

kg

1.973

Live process data

Fresh air pipe

1907

kg

3.254

www.efootprint.net

Louver shade

104.6

m2

2.869

www.efootprint.net

Fabric Shade

300.4

m2

2.671

www.efootprint.net

300.4

m2

253.7

Ecoinvent 3.1

Passive Window Profile

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new building. The materialization stage of a new facility includes the production, transportation, and construction stages of building materials. Therefore, this carbon emission calculation will use two LCA models as data sources. Since tracing the production process of bulk raw materials will constantly form new upstream forks, materials that comply with the CUT-OFF rule will be adopted to ignore the tracing of raw materials when tracing the upstream process. That includes when the weight of standard materials is less than 1%, and the importance of materials containing rare or high-purity components is less than 0.1%, the upstream production data of the modified materials can be ignored, and the total weight of the neglected materials is less than 5%. In most cases, the carbon emissions of production equipment, workshop, and production facilities can also be ignored.

2 Data Collection When building the quantitative model of LCA, the process structure and process data need to be structured hierarchically. Through data collection, the resource consumption and environmental emissions in each stage of the building life cycle can be described quantitatively, the data survey can be carried out as far as possible, and the product information can be filled in through the “input data” and “output data” of the survey data. For each unit process data set, process products, by-products, natural resource consumption, energy consumption, raw materials, energy consumption, environmental emissions, and waste to be disposed of should be mastered. The summary and summation of each unit process can obtain the life cycle inventory results of each resource consumption and environmental emissions, also known as LCI inventory results. Types of inputs to the model include energy, packaging, natural resources, transportation, infrastructure, recycled materials, materials, and component content. There are more than 400 natural resources to choose from. Types of output include environmental discharge waste to be disposed of, hazardous waste, and renewable waste. There are more than 7000 output types to choose from. In evaluating the LCA of building materials in different regions, local data should be given priority for analysis and calculation. When using various data sources, attention should be paid to data localization differences and reasonable transformation to ensure the rationality of results (Peng 2012)—appropriate input and output data indicators suitable for domestic materials. The data and frame structure of the demolition and recycling model (Model 1) and the physical and chemical stage model (Model 2) differ. Therefore, the carbon emissions generated by the two models are also quite different. The demolition and recycling model uses quantities based on material consumption. Because the process of building reconstruction does not involve demolishing a large area of perimeter structure, it only consists in destroying a small part of the wall (about 5%) and the removal of glass in the corresponding position. Once the glass is removed from the original building, the recycled material is recycled at a 90% rate.

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The remaining 10% will be disposed of in the landfill. The input and output data can be obtained according to the material calculation in the drawing, as shown in Table 2. The model of the transformation stage adopts the product delivery list and bill of quantities provided by the enterprise. In addition to accurate data, some data related to the production of energy consumption, mining, pollutant emission, and other processes can be traced through other databases. The Beijing data on electric energy production comes from the CLCD database of Sichuan University. The raw material production database of waste glass, concrete, and wood waste material comes from Ecoinvent3.1 and Ecoinvent3.8 databases of Switzerland. The database sources of other materials are shown in Table 1. The integrity of transportation information and material balance check in the data information provides an essential guarantee for the integrity of the data. To increase the adaptability and accuracy of the data model, it is imperative to improve the data set of ultra-low energy building materials. Therefore, 8 data sets, including passive glass, passive window profile, passive vacuum insulation board, and passive louver, were newly established in this model. The data of each data set is derived from environmental assessment reports issued by five similar manufacturers, feasibility study reports, national emission accounting methods, coefficient manuals for various industries, and field data from actual surveys. To provide accurate evaluation and calculation of carbon dioxide emissions of this model. Table 2 Inventory data of demolition and reuse process of existing buildings Type

List name

Quantity

Unit

Upstream data source Cause of discharge

Consumption

Existing building reconstruction office space

1

a

—

Consumption

Power

336

kWh

CLCD-China-ECER 0.8

Transformation process

Discharge

Waste glass

1569

kg

Ecoinvent 3.1

Recycling

Discharge

Waste wood

1125

kg

Ecoinvent 3.1

Recycling

Discharge

Waste concrete

1.67E + 05

kg

Ecoinvent 3.8

Recycling

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3 Model Calculation and Result Analysis 3.1 Impact Classification Based on list analysis, the next step is to sort out and analyze the list results. The composition results of energy consumption and carbon emissions as well as the contribution rate and sensitivity of each stage to environmental impact were analyzed (Zheng and Xu 2019). Combine resource consumption and environmental emissions, and convert them into common indicators of resource and environmental impact. Impact assessment can further clarify the effect of energy consumption and carbon emission on the environment. Figure 1 shows the overall framework of the model evaluation process. Through the summary of various indicators, it can increase the ways of technology and management improvement, adjust the direction of measures, identify critical steps, find essential methods, and solve fundamental problems, to reduce the impact of building renovation on the environment in essential links (Zheng and Xu 2019).

Fig. 1 The overall framework of the model evaluation process

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3.2 Index Analysis The input–output method is used to assess the life cycle environmental impact for the reconstructed buildings. Table 3 shows the LCA results of the existing building reconstruction, which show the percentage of greenhouse effect contribution of the list data and the average sensitivity of each factor. This paper analyzed the contribution potential of environmental impact indicators before and during the transformation. The contribution value of each material before the transformation is shown in Figure d in Fig. 3. It can be seen that the total carbon dioxide emission of the building before the renovation was 457,000 kg. In Fig. 3, picture e is the contribution value of each material to acidification before the renovation, and f is the contribution value to eutrophication. It can be seen that concrete is the most significant contributor to the greenhouse effect, acidification, and eutrophication, followed by steel, cement, and water. In Fig. 2, picture c is the carbon emission percentage of each material, and picture D is the normalized result of the impact on the environment. The result shows that the contribution rate of buildings before renovation to the greenhouse effect of environmental resources is Table 3 LCA results of existing building reconstruction Procedure name

List name

Office renovation

Upstream data type

Average sensitivity (%)

GWP (kg CO2 eq) (%)

Remarks

Windows and Real data doors system

87.67

87.77

Windows and doors system

Fabric shading

Background data

49.89

50.60

AP

Windows and doors system

Louver shading

Background data

36.35

35.74

AP

Office renovation

Fresh air system

Real data

9.71

9.58

Fresh air system

Fresh air pipeline

Background data

9.71

9.58

Office renovation

Enclosure system

Background data

2.24

2.28

Enclosure system

STP vacuum insulation board

Real data

2.05

2.08

AP

Windows and doors system

Passive window profile

Background data

1.37

2.37

AP

Office renovation

Air tightness system

Real data

0.38

0.38

Air tightness system

Air tightness film

Real data

0.2

0.21

AP

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the highest at 44.81%, followed by the PED index at 29.31%, and sulfur dioxide accounts for 11%. Similarly, Figure a in Fig. 3 shows the contribution value of each system to carbon emission. It can be seen that the total carbon dioxide emission in the transformation process is 356,000 kg, among which the carbon emission of the door and window system is 3,120,00 kg, accounting for 87.75% of the carbon emission in the transformation stage. In Fig. 3, picture b is the contribution value of each material to acidification before transformation, and c is the contribution value to eutrophication. It can be concluded that the door and window system is the most influential factor in the greenhouse effect and acidification, and the air tightness system is the most significant factor in environmental eutrophication. Figure a in Fig. 2 shows the contribution degree of carbon emission of each system in the transformation, and the contribution degree of the door and window system is the largest, 87.75%, which is shown in the red position of the internal pie chart. The external pie chart shows that the contribution rate of fabric shading to carbon emissions is the highest, reaching 50.61%, followed by the contribution rate of louver shading to 35.71%. Figure b is the normalized index chart, that is, from the contribution value of a single index to the comprehensive index, among the factors affecting the environment in the renovation process, the influence of COD is the largest, accounting for 43.86%, followed by PED17.02%, and carbon dioxide accounts for 13.82%. Therefore, this passive ultra-low energy consumption building has completed the transformation from a high energy consumption building through the process of construction, demolition, recycling, and new construction. The total carbon dioxide emissions generated by this passive ultra-low energy consumption building total 40,17,000 kg.

3.3 Development Potential To further explore the influence of ultra-low energy consumption on the carbon emission of the building, the monthly electricity consumption of the building is statistically analyzed by reading electricity meters. It can be seen that the electricity consumption index of the building after reconstruction is significantly lower than before reconstruction. It can be calculated that the total electricity saved by this building is 6120 kwh and about 4804.2 kg carbon dioxide emissions. As a result, the ultra-low-energy building will reduce carbon dioxide emissions by 4804 kg per year. It contributes to the energy saving and emission reduction of buildings. In terms of further development potential, this ultra-low energy consumption building can further reduce its carbon emissions through renewable energy, making it become a zero energy consumption house or production capacity house, which will be the development trend of the double carbon target of Chinese buildings. Therefore, the minimum area of renewable energy photovoltaic panels can be obtained according to the average monthly power consumption. The newly added building materials are

Fig. 2 Carbon footprint contribution percentage and normalized index before and after transformation

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Fig. 3 Contribution values of carbon emissions, acidification, and eutrophication

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bound to increase carbon dioxide emissions. According to the simple mathematical relationship, it can be obtained that the photovoltaic panels required by the existing building are 40 m2 , which can save the carbon emissions of the materials in 1.12 years. It is consistent with the research results of Peng (2012) of Tsinghua University.

4 Conclusion This paper calculates the carbon emissions of buildings through the life cycle assessment. A public university installation in Suzhou is selected to conduct modeling of carbon emissions through the stages of demolition, recycling, and transformation before building renovation. Statistical analysis is made on global warming indicators, terrestrial ecosystems acidification, and eutrophication in environmental impact assessment and the corresponding energy consumption combined before and after renovation. The main findings are as follows: 1. The carbon emission in the demolition and recycling stage is 457,000 kg, among which the environmental impact contribution of concrete is the largest. The concrete use process is the primary source of particulate matter formation and global warming ecological impact indicators of terrestrial ecosystems, accounting for 59.68% of the product life cycle. 2. The carbon emission in the transformation stage is 356,000 kg, and the change of COD in the transformation stage is the most significant impact on the environment. Among all the systems, the contribution value of the door and window system to the carbon emission of the building is the largest, about 87.75%, and the louver shading and fabric shading have the most considerable contribution to the global change environmental impact index, 50.61%, and 35.71% respectively. Therefore, improving shading materials and technology in the door and window system will provide a more effective way to build energy conservation and emission reduction. 3. Existing buildings’ ultra-low energy consumption transformation can significantly reduce carbon dioxide emissions. We can provide some perfect suggestions by exploring energy transformation and optimizing energy consumption inside buildings, carbon dioxide emissions will be significantly controlled by 2030. Acknowledgements This article is financially supported by the National Key R&D Program of China (2021YFE0200100).

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References Bekker PCF (1982) A life cycle approach in the building. Build Environ 55–61 Cen X, Zhang Y (2022) Research progress on calculation and evaluation of CO2 emission from concrete. Green Sci Technol 24(20):136–141 Filippin C (2000) Benchmarking the energy efficiency and greenhouse gas emissions of school buildings in central Argentina. Build Environ 35(5):407–414 Nassen J, Hedenus F, Karlsson S et al (2012) Concrete vs. wood in buildings: an energy system approach. Build Environ 51:361–369 Peng B (2012) Life cycle energy consumption and carbon dioxide emission of green buildings: a case study. Tsinghua University Research Center of Building Energy Efficiency, Tsinghua University. Annual Development Research Report of Building Energy Efficiency in China (2020) M. China Architecture and Building Press, Beijing, p 2020 Schwartz Y, Raslan R, Mumovic D (2018) The life cycle carbon footprint of refurbished and new buildings: a systematic review of case studies. Renew Sustain Energy Rev 81:231–241 Tang M, Li Z (2022) Technology practice and carbon emission analysis of ultra-low energy consumption building in Shanghai. Constr Sci Technol 15:66–70 UN Environment Program (2021) 2021 global status report for buildings and construction: towards a zero-emission, efficient and resilient buildings and construction sector Zheng X, Xu J (2019) Full life cycle carbon emission of prefabricated buildings based on LCA: a case study of a light steel prefabricated integrated villa in Chongqing. Build Econ 40(01):107–111 Zou YN (2020) Full life cycle carbon emission calculation and carbon reduction strategy of Chaoyang Wanda Plaza. Shenyang Jianzhu University

Analysis of Energy Saving of Building Envelope in Hot Summer and Cold Winter Region—Take an Office Building as Example Xiaoyi Zhang and Fuxia Zhang

Abstract The climatic conditions in hot summer and cold winter region are special, which is the hottest region at the same latitude except for desert areas in summer, and the coldest region at the same latitude in winter. The building envelope in this region is therefore a more complex option than in other regions to achieve the Doublecarbon target. This paper simulates and derives the single best retrofit scheme for different envelope structures via a basic model of CAD and Tianzheng energy-saving software, as an example of an office building in Zigong City. The study showed that the energy-saving rate of external walls in the region was 5.74–7.86%, roofs were 5.11–7.39%, external windows were 9.11–11.88% and shading was 3.09–10.95% respectively. Some recommendations are provided for the energy-saving design and retrofit of building envelope structures after comparing the energy-saving rate of different parts of the envelope in hot summer and cold winter regions. Keywords Building envelope · Hot summer and cold winter regions · Energy efficiency retrofit · Energy consumption simulation

1 Introduction With the continuous development of society, energy, which affects the survival of mankind, has become a primary issue of close attention in all countries, and in China the energy problem is particularly prominent. In China, the share of energy consumption in buildings was increasing, from 20% in 2000 to 23% in 2011, and if this trend continues, the share of energy consumption in buildings will exceed 35% by 2023 (National Bureau of Statistics of China 2018). There is a large population in hot-summer and cold-winter regions, and the region is growing rapidly economically. Due to the severe effects of hot and humid summers,

X. Zhang · F. Zhang International College, Yunnan Agricultural University, Kunming, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_8

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cold and wet winters, the building envelope needs to consider cold and thermal insulation in winter, heat insulation in summer, and moisture and water resistance, so the choice of envelope insulation and thermal insulation technologies and external shading technologies in this region are more complex than in other regions (Ruan 2017; He 2019; Chen and He 2009). However, the actual energy efficiency of most buildings in this region was not high (Ruan 2017; Du 2019). In addition, the energy use patterns of buildings in the region are characterized by intermittent and compartmentalized, which is quite different from the energy use patterns of district heating in the north. Therefore, it is very urgent and important to implement building energysaving designs in hot summer and cold winter areas, which is an important means to meet the growing energy demand, and also an important way to solve the energy gap in China. This study aims to develop an energy-saving model by considering building envelope energy-saving optimisation measures which will be suitable for hot summer and cold winter region, after comparing the energy-saving efficiency of each part of the envelope after renovation, looking forward to the most suitable high-efficient renovation plan.

2 Literature Review 2.1 Definition of the Envelope Although envelope is one of the most fundamental terms in the field of architecture, the definition of the envelope had been defined differently and with different emphasis by different institutions and academic groups. In the Code of Practice for Calculation of Floor Area of Building Works (2019), the envelope was defined as the structure that encloses the perimeter of the building space, which was broad and not classified in detail to avoid omissions when performing area calculations. Enveloping curtain walls are listed separately in the code. Gao and Zhang (2022) stated in their paper that the envelope of a building was generally divided into three areas, windows and doors, external walls and roofs, according to the location of the elements. In contrast, Han (2018) said that “building envelope refers to the walls surrounding the building space” was somewhat one-sided. However, none of the above definitions mentioned the element of ‘floor’, but the floor also provided some insulation and was part of the envelope of a space, so it should also be part of the envelope (Mi 2022; Yi 2022). Enclosures are also defined in different ways according to different classifications. Liao et al. (2022) stated that envelopes could be classified as internal or external according to whether they are in contact with the outside air. But many ignored this classification and defined envelopes directly as ‘external envelopes’ (Mi 2022; Yi 2022; Li 2022). The second classification was whether the envelope was transparent or not (Li 2018; Kumar et al. 2022). In addition to these two common classifications,

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Kumar et al. (2022), to discuss the energy efficiency and economics of different envelopes in their paper, categorised them into single-layer envelope, multi-layer envelope and sandwich wall, depending on the construction. These different classifications were not superior or inferior but were focused on different perspectives by different authors. The summary was shown in Table 1. In addition, because “envelope” and “maintenance structure” had the same pronunciation in Chinese, some authors confused the two concepts in their articles, which was a very uncritical behaviour. In summary, an appropriate definition of the building envelope is the enclosure of a building and all sides of a room. There are two types: transparent and opaque. Opaque envelopes include walls, roofs, floors, roofs, etc. Transparent envelopes include windows, skylights, balcony doors, glass partitions, etc. They can be divided into external and internal envelopes according to whether they are in direct contact with the outside air. Where not specifically indicated, the envelope is usually the external envelope, including external walls, roofs, windows, balcony doors, external doors, and partition walls and doors of unheated stairwells. Table 1 Classifications and definitions of the envelope Classification

Definition

Remarks

Classification by build location

The envelope is divided into windows and doors, walls, roofs and floors

The “ground” can generally be ignored. So “windows and doors”, “external walls” and “roofs” are the main three parts of envelope

Classification according to contact with outdoor air or not

The envelope can be divided into inner envelopes and outer envelopes

Some scholars ignored the “inner envelope”

Classification according to whether the material is transparent or not

The envelope can be divided into transparent and opaque enclosures

Windows can also be opaque enclosures (e.g. low permeability windows) and sometimes facades can be transparent enclosures (e.g. glass curtain walls)

Classification according to construction

The envelope can be divided into single-layer envelopes, multi-layer envelopes and sandwich walls

—

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2.2 Main Problems of Building Envelope Energy Efficiency 2.2.1

Unregulated Energy Efficient Building Design

Firstly, the principles and methods of envelope design are contrary to the principles of regional climate adaptability. It is difficult to arrive at the most suitable building energy-efficient design solution for the region when the building energy-efficient design is limited to passing the most basic national code requirement targets (Liu and Xie 2022; He 2019). There were even design units that repeatedly compromise on energy-saving conditions that do not meet code requirements in order to meet the economic requirements put forward by Party A. When carrying out energy-saving designs, they modify models privately, arbitrarily modify data, and even directly tamper with the energy-saving calculation reports. Liu et al. (2019) pointed out that the problem of self-built houses in rural areas was equally urgent. Many self-built houses in rural areas have not been designed by professional designers, and blind demolition and construction of houses have occurred in some rural areas. Most of the newly built houses are low-level repetitive buildings with high energy consumption, resulting in a serious waste of resources and energy.

2.2.2

Low Consumer Awareness of Energy Efficiency

The studies found that when purchasing a home, home buyers are most concerned with price, type, location, floor and orientation, with little attention paid to building energy efficiency. many people do not realise that good building energy efficiency design could also save money in their daily lives (He 2019; Khan et al. 2015). There are also some households who had modified their rooms by altering the roof, sealing balconies and terraces, causing the original closed insulation system to be destroyed, thus affecting the overall thermal insulation. Although these phenomena have improved in new buildings, they are still very common in older neighbourhoods.

2.2.3

Inadequate Technical Level of Workers

Some construction workers do not have sufficient knowledge of energy-saving technologies and techniques, and there are certain problems with their technical level. In the construction process, there are irregularities in management, not strictly following the construction steps, and even cutting corners. In the traditional form of the construction process, the application of green energy-saving technology was far from adequate (Feng 2017; Al-Tamimi 2022).

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Inadequate Regulation

In buildings with external wall insulation, it is often seen that the external wall finished layer or even the insulation layer is falling off in a large area, which not only affected the aesthetics but also posed a huge safety hazard. In view of the safety hazards of the external envelope of existing buildings, Wang (2022) said that the safety supervision of the external envelope of existing buildings should be strengthened, and the responsible body should be clarified. Government authorities should clarify the responsibility for the safety supervision of the external envelope of existing buildings, formulate the requirements for the supervision of the safety of the envelope during the use of the building, identify the person responsible for the safety management of the external envelope of the building, and formulate implementation rules for the safe maintenance management of the building facade in densely populated areas.

2.3 Importance to Retrofit Different Parts of the Building Envelope Scholars had put forward different views on the need to implement energy-efficient retrofitting of various parts of the envelope in hot-summer and cold-winter regions. In the energy-efficient design of the building envelope, the external wall was often the largest component in terms of area and plays an important role in thermal insulation and energy saving, the heat loss from external walls was the most important part of the building envelope (Xie 2022; Gao and Zhang 2022). However, some scholars believe that external windows and doors are often the weakest link in the building envelope, so the focus should be on these parts when carrying out energy-saving renovations in this area (Yi 2022; Xie 2022; Li and Liu 2018). The importance of the roof was also not negligible, and Li and Liu (2018) argued that the summer sun was very strong in the southern part of China and the roof was the highest temperature of the building envelope. So, it was important to take thermal insulation measures for the roof to improve the indoor temperature.

3 Research Methodology 3.1 Literature Research Method To collect information and read literature on measures to optimise the energy efficiency of envelopes in hot summer and cold winter regions. Explore the experiences and shortcomings of previous research. Study the latest domestic and international energy-saving renovation technologies and learn the relevant theoretical knowledge to provide theoretical support for the research.

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3.2 Software Simulation Method Field mapping was first carried out and the floor plans and elevations of the selected cases were drawn using Auto CAD. Currently, there are many building energy simulation software programs available worldwide, many scholars choose to use Energy Plus, Design Builder, and Ecotect. But these programs do not cover all regions of China, and the climate parameters may not be set accurately. In this paper, the Chinese Tianzheng energy efficiency simulation software was chosen, which can automatically set the relevant climatic conditions such as temperature and humidity after selecting the region and can set the corresponding codes according to the different climatic regional divisions.

3.3 Controlled Variable Method The control variables method was used in this paper to find the energy savings that can be obtained from the design solution compared to the baseline solution. In this way, the energy consumption of each individual retrofit solution was derived, and then the energy saving rate was derived. Finally, the energy-saving rate of each part of the retrofit was compared, and the one with the greatest energy-saving rate should be focused on the retrofit, resulting in a ranking of the importance of the retrofit of each part of the envelope in this area.

4 Data Analysis 4.1 Selection of Architectural Models An office building in Zigong city, Sichuan province, was selected as a typical building model and used as the base model for simulation analysis. The base model had 4 storeys, the structure was a frame structure, the long side of the building was about 36 m, the width was about 18 m, the height of each storey was about 3.9 m, the height of the building was about 16 m, and the construction area was about 2800m2 .

4.2 Set Up with Reference to the Building Envelope This section began with the establishment of a reference building, called the ‘benchmark building’. The reference building’s individual envelope construction practiced, and thermal coefficient indicators were shown in Table 2.

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Table 2 Reference to the thermal performance of the building envelope Envelope

Constructional practices (from top to bottom)

External wall

10 mm external decorative brick + 5 mm 0.72 alkali resistant glass fibre mesh + 30 mm rock wool board + 20 mm cement mortar + 240 mm brick wall + 20 mm cement mortar

–

Roof

5 mm waterproofing membrane + 20 mm cement mortar + 30 mm cement expanded perlite + 120 mm reinforced concrete + 20 mm mixed mortar

0.54

–

External Windows

6 mm aluminium double glazed plain window

3

0.72

Sunshade

None

–

–

Heat transfer coefficient W/ (m2 ·K)

Solar heat gain coefficient (SHGC)

4.3 Energy Saving Analysis of Individual Energy Saving Retrofit Technologies 4.3.1

Facade Renovation

The simulation used EPS board thin plaster external insulation systems to carry out energy efficiency analysis of a single facade retrofit. By varying the thickness of the EPS panels from 30–100 mm in 10 mm steps, a total of 8 retrofit solutions were used, with the solutions numbered W1–W8 respectively. The rest of the envelope structure remained unchanged without any retrofitting, in line with the reference building, and the specific external wall retrofitting technology solutions were shown in Table 3. Through the Tianzheng energy-saving simulation software, the exterior wall renovation solutions in Table 2 were simulated separately to derive the monthly heat and cold consumption of the building after the renovation of the exterior walls using Table 3 Technical options and specifications for facade renovation Facade renovation (Programme No.) Facade construction Combined heat transfer coefficient of external walls W/(m2 ·k) W1

30 mm EPS board

0.630

W2

40 mm EPS board

0.542

W3

50 mm EPS board

0.476

W4

60 mm EPS board

0.424

W5

70 mm EPS board

0.383

W6

80 mm EPS board

0.348

W7

90 mm EPS board

0.320

W8

100 mm EPS board

0.296

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Fig. 1 Heating and air conditioning energy consumption for facade renovation

different thicknesses of insulation, as well as the monthly power consumption, and the power consumption of heating and air conditioning were calculated separately, from which the annual heating, air conditioning and total energy consumption indicators were obtained, as shown in Fig. 1.

4.3.2

Roof Renovation

The insulation material chosen was XPS insulation board, the rest of the envelope structure remains unchanged, in line with the reference building, a total of 8 programmes numbered R1-R8, corresponding to XPS board thickness of 40-100 mm, the specific roof renovation technology programme was shown in Table 4. Through the Tianzheng energy-saving simulation software, the roof renovation schemes in Table 3 were simulated separately to derive the monthly heat and cold consumption of the building after the renovation of the external walls using different Table 4 Technical options and specifications for roof renovation Roof renovation (Programme No.)

Roof construction

Combined heat transfer coefficient of roofs W/(m2 ·k)

R1

30 mm XPS board

0.693

R2

40 mm XPS board

0.529

R3

50 mm XPS board

0.486

R4

60 mm XPS board

0.450

R5

70 mm XPS board

0.391

R6

80 mm XPS board

0.375

R7

90 mm XPS board

0.322

R8

100 mm XPS board

0.294

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Fig. 2 Heating and air conditioning energy consumption for roof renovation

insulation thicknesses, as well as the monthly electricity consumption, and the electricity consumption of heating and air conditioning were calculated separately, from which the annual heating, air conditioning and total energy consumption indicators were obtained, as shown in Fig. 2.

4.3.3

External Window Renovation

The technique of replacing the whole window was chosen to carry out the energysaving analysis for a single external window retrofit, like the external wall retrofit, where the rest of the envelope remains unchanged without any retrofit, in line with the reference building. The four options chosen are shown in Table 5. Through the Tianzheng energy-saving simulation software, the roof renovation solutions in Table 4 were simulated separately to derive the monthly heat and cold Table 5 Technical options and specifications for window renovation Programme No.

Window construction

Heat transfer coefficient

Solar heat gain coefficient

C1

Ordinary Low-E insulating glass (air 6 mm)

2.7

0.44

C2

High-transmission Low-E 2.6 insulating glass (air 9 mm)

0.40

C3

Medium-transmission Low-E insulating glass (air 12 mm)

2.5

0.32

C4

Low-transmission Low-E insulating glass (air 12 mm)

2.5

0.25

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Fig. 3 Energy saving rate for window renovation

consumption of the building after the renovation of the external walls using different insulation thicknesses, as well as the monthly electricity consumption, and the electricity consumption of heating and air conditioning were calculated separately, from which the annual heating, air conditioning and total energy consumption indicators were obtained, as shown in Fig. 3.

4.3.4

Sunshade Conversion

Fixed shading and movable shading were selected for the study. The rest of the envelope structure remained unchanged, and no renovation was carried out, in line with the reference building, except for the shading measures. The options are shown in Table 6. The monthly heat and cooling consumption of the building after the retrofitting of the four options and the monthly electricity consumption were obtained by simulating each of the shading retrofitting options in Tables 4, 5, and 6 through the Tianzheng Energy Saving Energy Simulation Software, and the electricity consumption of heating and air conditioning were calculated separately, thus obtaining the annual heating, air conditioning and total energy consumption indicators as shown in Fig. 4. Table 6 Methods of shading renovation

methods

Benchmark Building

Z1

Z2

Z3

No shading

Horizontal shading

Fixed horizontal Movable louvre shading horizontal louvre shading

Z4 Movable vertical louvre shading

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Fig. 4 Energy saving rate for shading renovation

4.4 Ranking of the Importance of the Various Components of the Envelope The energy saving rate of each renovation option was analysed according to the annual energy consumption value of the building before and after the renovation, which was defined as the difference between the total annual energy consumption value of the building before the renovation and the total annual energy consumption value of the building after the renovation, divided by the total energy consumption value of the building before the renovation: E = (E 1 − E 2 )/E 1

(1)

In this formula: E—Energy saving rate after retrofitting, %. E 1 —Total building energy consumption before renovation, kWh/m2 . E 2 —Total building energy consumption after renovation, kWh/m2 . Using the total annual energy consumption values of the building before and after the retrofit, the energy saving rates for each retrofit option were calculated according to Formula 1, as shown in Fig. 5.

5 Conclusions and Recommendations After simulation for this office building, when retrofitting external walls, it is recommended that EPS insulation is incorporated and that the thickness of the insulation is controlled to be between 30 and 70 mm. When retrofitting roofs, it is recommended that XPS insulation is added, and the thickness of the insulation is controlled

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Fig. 5 Comparison of energy-saving rates

to be between 30 and 70 mm. When retrofitting external windows, it is recommended that the whole window be replaced with a low-permeability Low-E insulating glass window. When carrying out energy-saving optimisation of shading, the use of movable shading is recommended. Among the various influencing factors of the envelope, the energy saving rate for external walls is 5.74–7.86%, for roofs 5.11–7.39%, for windows 9.11–11.88% and for shading 3.09–10.95%. Based on the magnitude of the respective energy saving rates, it is concluded that the importance of the envelope on the energy consumption of office buildings is ranked as follows: external windows > sun shading > external walls > roofs. The results of the software simulations in this paper can go some way to reminding building designers that facades and roofs are not the only things to consider when designing for energy efficiency, but that windows, doors and shading can also play a significant role and, in some cases, can be even more efficient. The software simulation approach in this paper has some reference value for other building types, for example, when studying the energy efficient design or retrofit of residential or public buildings, the same research ideas can be used to find the most effective way to do so. In the meanwhile, apart from technical improvements to buildings, it is not neglect to strengthen public awareness of energy efficiency. As mentioned in Chap. 2 of this paper, many of the problems with energy efficiency in buildings in this region are really ‘people’ problems rather than ‘building’ problems. Only by improving the efficiency of energy-efficient design and raising people’s awareness of energy efficiency at the same time, can we truly achieve our double-carbon goal.

6 Limitations In this paper, no economic analysis has been carried out when analysing the simulation results, which lacks practicality. In actual operation, a strictly economic analysis is needed to select a renovation plan with better energy saving and economic results.

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Acknowledgements This paper is an output from the author’s undergraduate dissertation and the Project of Yunnan International Joint R&D Centre of Smart Environment. We acknowledge with lots of thanks the involvement of the participants in the study.

References Al-Tamimi N (2022) Building envelope retrofitting strategies for energy-efficient office buildings in Saudi Arabia. Buildings 12:1900. https://doi.org/10.3390/buildings12111900 Chen G, He T (2009) Building energy efficiency in hot summer and cold winter regions from plot planning. Sichuan Construction 29(4):14–15 Du X (2019) Study on the optimization of energy-saving system of green building envelope in hot summer and cold winter areas. Xi’an University of Architecture and Technology, Shanxi, pp 58–93 Feng Y, Nan Y, Zhong H (2017) Thermal and energy efficient design of non-transparent envelopes for southern buildings. Civ Archit Environ Eng 39(4):33–39 Gao Y, Zhang C (2022) Research on energy saving reconstruction technology of envelope structure of the existing office buildings in cold area. City Build 19(03):1–4 Han J (2018) Experimental study of green roofs on building envelope energy efficiency. Energy Conserv Environ Protect 12:25–38 He X (2019) Research on energy conservation of residential building envelope in hot summer and cold winter area—take Chengdu as an example. Southwest Jiaotong University, Chengdu, pp 36–50 Kumar DA, Memon M, Bhayo AR (2022) A critical review for formulation and conceptualization of an ideal building envelope and novel sustainability framework for building applications. In: Cleaner engineering and technology, pp 4–16 Khan S, Abdo H, Al-Ghabban A (2015) Investigating consumer awareness of energy efficiency in Saudi Arabia. Energy Res J 6(1):1–6 Li B, Xu X, Li X (2022) Energy-saving transformation technology and energy consumption of building envelope. In: Energy and energy conservation, pp 2–8 Li H, Liu X (2018) Research on energy-saving construction techniques for the external envelope of civil buildings. Corporate Technol Dev 5:139–141 Li M (2018) Study on energy-saving renovation of the envelope of existing office buildings. The Residence 18:197 Liao W, Luo Y, Peng J, Wang D, Yuan C, Yin R, Li N (2022) Experimental study on energy consumption and thermal environment of radiant ceiling heating system for different types of rooms. Energy 244: 122555 Liu L, Han R, Zhao X (2019) Study on energy-saving renovation of rural residential envelope structure in Jizhong region. Energy Saving 47(08):140–214 Liu J, Xie J (2022) Principles and methods of thermal design of building envelopes in the broad sense. Build Sci 38(08):1–8 Mi S (2022) Introduction to the green technology series for archive buildings (II)—common envelope energy-saving technologies. China Archives 09:47 National Bureau of Statistics of China (2018) China National Bureau of Statistics database [DB/ OL]. Available at http://data.stats.gov.cn/easyquery.htm?cn=C01 Ruan F (2017) Theoretical study on energy conservation of residential building envelopes under intermittent energy use in separate rooms. Zhejiang University, Hangzhou, pp 34–38 Wang C (2022) Strengthening safety risk prevention, control and management of building envelope structures. Stand Eng Constr 3:32–33

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An Experimental Study on the Effects of Temperature and Humidity Levels on Human Thermal Comfort During Running Qinchen Yuan, Junjia Zou, Nuodi Fu, Luyao Guo, Jiabao An, Zhiyuan Chen, Fucheng Long, and Long Huang

Abstract This article explores the influence of temperature and humidity on human thermal comfort and exercise performance during dynamic exercise. While previous studies have investigated the relationship between exercise state and thermal comfort, few have focused on transient changes during exercise. To examine these relationships, a series of experiments were conducted in an environmental chamber with precise control over temperature and humidity conditions. Participants were selected and tested under nine different scenarios at the same running speed. Questionnaires were filled out at six different time slots, from pre-exercise till 5 min after the exercise. The predicted mean vote (PMV) model was used to estimate the average thermal comfort. The results showed that, despite a relatively constant environment, participants’ feeling of thermal comfort changed as the exercise progressed and after sweating during the post-exercise course. The sensitivity and feeling of thermal comfort varied during the whole process under different scenarios. This study provides innovative survey methods for questionnaires and objective environmental data that can be analyzed to enhance understanding of changes in thermal comfort during exercise under different environmental variables. The findings also offer suggestions for the regulation of temperature and humidity in indoor gyms, and the accuracy of the PMV model in dynamic applications is verified. Keywords Temperature and humidity · Thermal comfort · Predicted mean vote · Running scenario

Q. Yuan · J. Zou · N. Fu · L. Guo · J. An · Z. Chen · F. Long · L. Huang Xi’an Jiaotong-Liverpool University, Suzhou, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_9

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1 Introduction 1.1 Research Background In contemporary society, a sedentary lifestyle is prevalent among many individuals. It is estimated that one in three adults cannot attain the minimum weekly exercise level recommended by the World Health Organization (WHO) (World Health Organization 2010), WHO suggests 150 min of moderate-intensity aerobic physical activity per week for individuals aged 18–64(World Health Organization 2010). Furthermore, lack of exercise hides many risks for human health (Hills 2018), for example, chronic cardiovascular disease and long-term inactivity related (Prasad and Das 2009). In contrast, exercise regularly benefits developing a healthy lifestyle (Morris et al. 1953), reduces the adverse effects of aging on the body and mind, prevents age-related cognitive decline (Bherer et al. 2013), and decreases the risk of premature death and over 25 chronic diseases by at least 20–30% (Warburton and Bredin 2016). Thus, promoting increased exercise time and providing a comfortable exercise environment can positively impact individuals’ physical health. A pleasant indoor gym environment, characterized by optimal thermal comfort, can significantly influence people’s subjective willingness to exercise. An Indoor gym is an important place for physical exercise. Temperature, and humidity are the main factors that make up the indoor environment for exercise. At the same time, temperature, humidity are two main parameters in calculating predicted mean vote (PMV) (Olesen and Brager 2004), which is used to estimate the thermal comfort in the stationary state.

1.2 Related Studies on the Thermal Comfort Research on thermal comfort can be categorized into three main domains: static, dynamic, and experimental. Static Domain: Studies in this domain focus on thermal comfort in enclosed spaces with low heart rates, such as metro cabins (Wang et al. 2023), car carriage (He et al. 2022), and architectural interiors (Wang et al. 2022a, b). These studies aim to evaluate thermal comfort in static conditions, with objectives such as controlling indoor temperature systems (Wang et al. 2023), assessing construction materials (Wang et al. 2022a, b), and predicting thermal comfort models (He et al. 2022). Dynamic Domain: Research in this domain concentrates on thermal comfort during exercise periods, examining factors such as temperature and humidity on anaerobic exercise performance (Huang et al. 2021; Shi et al. 2022), the impact of different metabolic rates (Zhang et al. 2020, Wang et al. 2022a, b), and the influence of space types on exercisers’ thermal responses (Wang et al. 2022a, b), These studies also investigate sweat production during moderate exercise (Wang and Hu 2016).

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Experimental Domain: In previous experiment-based research, large sample sizes were typically used, with individual samples participating in single experiments (Huang et al. 2021; Shi et al. 2022; Taib et al. 2022; Wang and Hu 2016; Wang et al. 2022a, b; Zhang et al. 2020). In the questionnaire section, most of the studies reference the classical PMV questionnaire system, 7-point scale table (Huang et al. 2021; Shi et al. 2022; Wang and Hu 2016; Wang et al. 2022a, b; Zhang et al. 2020). The fourth aspect is the understanding and quantification of the issue of heat sensation and how this question can be set up so that participants can better understand it and the questionnaire questions can more accurately reflect the real situation. Different people have different understandings about how participants subjectively determine their thermal comfort level for their exercise state. Even though ASHRAE 7-point of cold, cool, slightly cool, neutral, slightly warm, warm and hot are widely used and interpreted, there are still errors in subjective understanding due to different circumstances (Al-Khatri and Gadi 2019; Buratti et al. 2016; Fabbri 2013; Li et al. 2020; Schweiker et al. 2020, 2017; Thapa 2021; Wang et al. 2018). In fact, the use of ASHRAE 7-point is based on the following assumption: (i) The distance between any two verbal anchors is equal. For example, the distance between ‘warm’ and ‘hot’ is equivalent to the distance between ‘cool’ and ‘cold’. (ii) The natural condition should highly coincide with the midpoint of the scale. That is says, the scale should be symmetry. However, there are some study shows that there exists some inaccuracy for the traditional 7-point scale. According to the first assumption, some studies have shown that the distance is not equal, and the rigor of the second hypothesis is also worth discussing (Schweiker et al. 2020, 2017; Thapa 2021). Moreover, previous studies have explored alternative scales to assess thermal comfort, such as the 7-point categorical scale (7pts CS), visual analog scale (VAS), and categorical scale combined with VAS (graphic CS) using questionnaire surveys (Lee et al. 2010). Categorical scales require participants to mark different boxes, similar to multiple-choice questions. In contrast, VAS is defined as a straight line with endpoints representing the extreme limits of a sensation, predominantly utilized in psychology (Collins et al. 1997). Participants are free to mark the line according to their interpretation of the extremes. For graphic CS, a typical example is the ASHRAE 7-point scale, which calibrates points on a straight line with specific interpretations, allowing participants to choose points based on their perceptions. Regarding the point-setting in graphic CS, it has been observed that traditional scales (7-value scales) may overestimate the proportion of individuals who report a heat sensation of 0 (Buratti et al. 2016). Moreover, the human body is more sensitive to heat sensations during exercise (Perception of effort during exercise is independent of afferent feedback from skeletal muscles, heart, and lungs 2009). Therefore, one study introduced 13 points (Hot, between hot and warm, Warm, between warm and slightly warm, Slightly Warm, between slightly warm and natural, Natural, between natural and slightly cool, slightly cool, between slightly cool and cool, Cool, between cool and cold, Cold) and achieved better accuracy (Buratti et al. 2016).

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To evaluate the performance of subjective measurement instruments, three criteria are considered: validity, reliability, and responsiveness. Validity pertains to the authenticity of the research results and assesses whether the instrument accurately measures the intended variable (Golafshani 2003). Reliability refers to the consistency of results over time and the instrument’s ability to be replicated under similar methodologies and conditions (Golafshani 2003). Responsiveness denotes the instrument’s ability and sensitivity to detect significant changes, even if these alterations are minor (Deyo and Centor 1986). In summary, understanding and quantifying thermal comfort during exercise is essential for creating optimal indoor environments that encourage physical activity. An appropriate scale application can more accurately reflect the participants’ heat perception and improve the authenticity of the data.

1.3 Study Objective In modern society, many individuals opt for indoor running in gyms, where temperature and humidity are regulated. While numerous studies have offered general suggestions for overall indoor environment control, there is a lack of data regarding specific sensations experienced by exercisers at different stages of a run under varying temperature and humidity conditions. This study focuses on a particular running process, examining individual feelings at distinct stages of an exercise session while altering temperature and humidity within climate chambers. The findings can inform indoor environment design and provide recommendations for optimizing personal running performance. The main objectives of this study are as follows: (1) To compare the differences in thermal sensation at various running stages under different temperature and humidity conditions. (2) To develop and apply a questionnaire system for use in the experimental trials. (3) Provide data points for indoor sports space temperature and humidity control, to help build a carbon neutral framework for the future.

2 Method 2.1 Participants and Experimental Condition According to Wang et al. (2018) study, when the number of experiments exceeded 40, the Standard Uncertainty of subjective measurements fell within 3% of the total scale length, confirming the reliability and accuracy of subjective thermal comfort measurements. Consequently, we selected five participants to engage in nine trials each, totaling 45 trials. During the experiment, participants were required to wear

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summer clothing (clo = 0.4). After each trial, participants were given adequate time to rest until their physical condition returned to normal before starting the next trial. Five participants (5 males, height 175.5 ± 10.5 cm, weight 78.5 ± 12.5 kg, age 21 ± 2 years) were recruited from the university community. All participants were healthy with basic running experience and volunteered for the study. In the presniffing we found that a 30-min run at 6 km/h was affordable for all participants. However, for the running speed of 8 km/h or more, some participants said it was difficult to accept. The experimental protocol was approved by the University Ethics Committee. Prior to the experiment, participants were instructed to abstain from alcohol and smoking and maintain a regular schedule for three days. Before each run, participants confirmed they were in good physical condition to proceed with the experiment. The experiment was conducted in a climate chamber in March 2023, with controlled temperature and relative humidity as the primary environmental parameters. Shi et al.’s study analyzed nearly 1500 data points from the ASHRAE Global Thermal Comfort Database and found that when human metabolic rate exceeded 1.5 during exercise, over 80% of the data points fell within the temperature range of 22 °C to 28 °C, and more than 90% of the data points were within the relative humidity range of 30–70% (Shi et al. 2022).

2.2 Measurement 2.2.1

Environmental Parameter

Regarding factors that affect human thermal comfort during exercise, temperature is a crucial element; inappropriate indoor temperatures can impact a runner’s comfort. The human body becomes more sensitive to temperature changes during running, as exercise generates more heat, necessitating greater heat dissipation and consequently increasing sensitivity to heat sensation(Perception of effort during exercise is independent of afferent feedback from skeletal muscles, heart, and lungs 2009). Additionally, a significant gap between indoor and outdoor temperatures can increase the uncertainty of subjective measurements (Wang et al. 2018). Based on these considerations, and Shi’s study (Shi et al. 2022), we set three levels of temperature factors at 22.0 °C, 25.0 °C, and 28.0 °C, which are not significantly different from outdoor temperatures and have suitable gaps between the levels. Humidity is another factor we focus on. High humidity can hinder sweat evaporation, making it difficult for the body to dissipate heat and increasing the risk of heatstroke. Low humidity can lead to dehydration. Referring to Shi’s article (Shi et al. 2022), we set humidity levels at 40, 55 and 70%. By combining these temperature and humidity levels, we obtain nine experimental environmental conditions as shown in Table 1.

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Table 1 Nine practical cases

Case number

Temperature (°C)

RH (%)

A

22

40

B

25

55

C

28

70

D

22

40

E

25

55

F

28

70

G

22

40

H

25

55

I

28

70

The nine environmental combinations of Table 1 were traversed by one runner participating. Differences in training levels between participants were avoided by analyzing the results of nine experiments with one participant. For other environmental parameters, such as wind speed, higher wind speeds facilitate sweat evaporation, thus increasing the body’s heat dissipation efficiency. However, strong winds may also cause individuals to feel cold, especially if they are sweating during exercise. Our research focuses on two environmental factors: temperature and humidity. Therefore, we controlled the ambient environment for the absence of wind to eliminate the effect of wind speed.

2.2.2

Physiological Parameters

The exercise state can be reflected by heart rate, and thermal comfort is closely related to the body’s skin temperature. Therefore, we continuously monitored participants’ heart rate and skin temperature during the running process. For heart rate monitoring, participants wore Polar OH1 devices (Range: 30–240 bpm, Interval: 1 s). These devices have been shown to exhibit high agreement with standard ECG heart rate measurements and can be used as valid measurements of heart rate in laboratory and field settings during moderate and high-intensity physical activities (Hettiarachchi et al. 2019). For skin temperature monitoring, subject’s skin temperature is obtained by measuring four points, i.e., arm, chest, thigh, and calf (Ramanathan 1964).

2.2.3

Subjective Questionnaire

Regarding the questionnaire design, many of the previous studies used ASHRAE 7-point indicators (Handbook 2006) to evaluate the thermal and humidity sensation of the participants. However, some articles have pointed out the limitations of the ASHRAE 7-point indicators for use in exercise (Lee et al. 2010; Schweiker et al. 2020). Therefore, our study focusses on the detail of questionnaire design. The following content explain the reasons about our questionnaire (Fig. 1).

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Fig. 1 The questionnaire system

Questionnaire Topic The questionnaire was designed to obtain subjective data aligned with the research objectives of this study. The questions covered three aspects: temperature, humidity, and movement status. To accurately assess thermal comfort, ISO 10551 (Fransson et al. 2007) suggest use different dimensions to evaluate the thermal comfort. The dimension including thermal sensation, Subjective temp ID for individuals. Thermal preference checks if adjustment needed. Thermal acceptance uses binary relation for current state. Affective aspects evaluate discomfort but may be affected by motion. We focus on three dimensions for the questionnaire. Humidity section uses dry–wet terms. Exercise status measured by MET. Pre-experiment showed sweating during running impacts thermal comfort. Sweat evaporation and heat absorption considered; added sweat start time to questionnaire.

The Analysis of Different Scales of Thermal Sensation When evaluating different scales for thermal sensation under exercise-specific conditions, it is essential to consider validity, reliability, and responsiveness. The VAS allows participants to mark their responses automatically, providing better responsiveness but potentially magnifying individual differences (Wang et al. 2018). Furthermore, free labeling can introduce uncertainty in subsequent data analysis.

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Fig. 2 Procedure and experimental demonstration

However, during exercise, the human body’s heat perception becomes more sensitive, and using a Categorical Scale or Graphic CS with a limited number of discrete points may result in errors and inaccuracies. To address these issues, our study introduces a creative modification to accommodate exercise conditions. We designed a combined VAS and Graphic CS, marking 7 points (cold, cool, slightly cool, neutral, slightly warm, warm, and hot) on a straight line and dividing them into segments. Each segment corresponds to a range of the PMV index, ensuring the VAS scale remains consistent with the PMV index and facilitating comparison and analysis of thermal comfort. For example, the VAS table is divided into 7 segments, each representing a PMV index range, such as −3 to − 2, −2 to −1, −1 to 0, 0 to 1, 1 to 2, and 2 to 3. This approach allows for a more precise and adaptable evaluation of participants’ thermal sensations during exercise while maintaining a structured and quantifiable scale for analysis.

2.3 Testing and Survey Procedure Each experimental procedure took approximately 30 min as illustrated in Fig. 2. The experimental demonstration shows a realistic scenario of participants engaging in the experiment. Following acclimatization, participants were asked to fill in relevant physiological parameters and questionnaires before starting the experiment. During the experiment, participants were prompted with a questionnaire every 5 min, with the tester posing the questions and the participant responding. The questions on sweating in the questionnaire were self-reported by the participants after they experienced sweating.

2.4 Statistical Analysis To study environmental factors’ impact on anaerobic exercise, we used variance analysis. Factor significance determined by F statistic size. If significant, level variation was examined. We explored changes in heat and wet sensation during different exercise times under consistent temperature and humidity.

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Fig. 3 Subjective environmental perception and comfort voting in different environments for each exercise time

3 Result 3.1 Questionnaire Result By analyzing the questionnaire (Fig. 3), we can get Table 2. For each dimension, we observed changes in movement periods and temperature conditions using avg values. Thermal sensation: -3 (cold) to 3 (hot); thermal preference: −2 (much cooler) to 2 (much warmer); thermal acceptance: binary (1 = accept, 2 = non-accept); humidity: −3 (very wet) to 3 (very dry); sweating: 0 (none) to 3 (heavy); exercise feeling: 0 (rest) to 10 (maximum).

3.2 Comparison with the Predicted Mean Vote (PMV) Model To investigate the relationship between PMV and experimental data during 6 km/ h running exercise. We calculated the relevant data by CBE Thermal Comfort Tool (Tartarini et al. 2020).

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Table 2 The result of questionnaire Temperature Time Thermal Thermal Thermal Humidity Sweating Heart sensation preference acceptance sensation (mean) rate (mean) (mean) (mean) (mean) (mean) 22

25

28

Exercise feeling (mean)

5

0.50

−0.08

1

0.25

0.33

130 3.85

10

1.36

−0.25

1

0.79

1.16

128

15

1.83

−0.21

1

1.29

1.91

134

20

1.85

−0.36

1

1.95

2.54

142

25

1.71

−0.54

1

2.22

2.90

150

30

1.71

−0.63

1

2.31

2.90

141

5

0.22

0

1

0.57

0.42

133 4.14

10

1.41

−0.85

1

1.35

1.42

152

15

2.14

−0.85

1

2.00

2.14

155

20

2.64

−1.28

1.14

2.42

2.71

157

25

2.85

−1.42

1.14

2.64

3.00

158

30

3.00

−1.28

1.14

2.50

3.00

150

5

0.50

−0.75

1.25

-0.25

0.75

153 ara> 5.25

10

1.50

−1.00

1.25

1.25

2.00

158

15

2.75

−1.25

1.50

2.50

2.75

154

20

3.00

−1.50

1.75

2.75

3.00

160

25

3.00

−1.50

2.00

3.00

3.00

161

30

3.00

−1.50

2.00

3.00

3.00

159

We calculated the collected data and obtained Fig. 3: PMV index under the proposed conditions, where the shaded range represents a neutral thermal sensation value (−0.5 to 0.5). Predicted Mean Vote (PMV), Predicted Percentage Dissatisfied (PPD), Sensation, Standard Effective Temperature (SET) are displayed above. Among them, the nine red circles from left to right in Fig. 4 correspond to the values of PPV, PPD, sensation, and SET for different temperature and humidity environments, respectively. The value of PMV is calculated based on different groups of temperature and humidity conditions, clothing resistance(0.54clo), Metabolic rate after entering the running state(3.8met), and wind speed(0 m/s). For example, at a temperature of 22 °C and 40% humidity, the questionnaire data showed that the average heat sensation of the participants after entering the exercise state was 1.8, but the PMV was calculated to be 0.25. At a temperature of 28 °C and 40% humidity, the questionnaire data showed an average heat sensation of 2.7 after entering the exercise state, but the PMV was calculated to be 1.44. By comparing the whole data, we confirmed the inapplicability of the PMV model at moderate exercise intensities. The PMV values were notably smaller than the

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Fig. 4 Calculation results on PMV and other data

questionnaire data, indicating the limitations of the model in predicting thermal comfort during exercise.

4 Discussion (1) It is widely believed that as exercise progresses, human heart rate increases, and the body feels hotter. However, in 25% of the tests conducted at 22 °C, the opposite conclusion was observed, contrary to the hypothesis. After 15 min of running, the heat sensation values of a subset of the population decreased compared to the results obtained during the last 5 min of the questionnaire. This anomaly was not observed at 25 °C and 28 °C. Our analysis of the questionnaire data revealed that sweating occurred after 10 min of exercise, irrespective of temperature and humidity conditions. Due to the relative speed generated while running, participants felt the wind blowing. Once sweating had commenced, the evaporation of sweat and heat absorption led to a decrease in thermal sensation values. In contrast, at 25 °C and 28 °C, we hypothesize that heat sensation values remained constant due to the persistence of high temperatures and continuous movement. The aforementioned conditions did not affect all participants, which could be attributed to individual differences in cold sensitivity (Gavhed 2003). (2) At a temperature of 28 °C with 70% humidity, some participants felt slightly dry during the acclimatization phase before exercising. However, at 25 °C with 70% humidity, no one reported feeling dry. Thus, increased temperature also impacts wet sensation. We speculate that high temperature and high humidity conditions may exacerbate participants’ perception of humidity. (3) Our findings indicate a correlation between sweating conditions and wet sensation. When exercise reaches the onset of sweating, a substantial increase in wet sensation is also observed.

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(4) We analyzed relevant data points during exercise to calculate the PMV (Predicted Mean Vote) index, demonstrating the limitations of PMV assessment in evaluating thermal comfort during physical activity. (5) Regarding skin temperature, the cooling effect of sweating during exercise resulted in lower skin temperature measurements. This observation should be considered in future experimental designs.

5 Conclusion To investigate thermal comfort during running, we asked five subjects to run at a speed of 6 km/h for 30 min in climate chambers. Throughout the experiment, we recorded thermal parameters and subjects’ thermal perception. The main findings of this study are as follows: (1) Running at a speed of 6 km/h at a temperature of 22 °C, sweating reduces heat sensation. However, no such effect of sweating on heat perception was observed at 25 °C and 28 °C conditions. (2) Running at 6 km/h at 28 °C is thermally uncomfortable. After more than 5 min of running, participants began to experience unacceptable thermal discomfort, and after 20 min, all participants reported feeling uncomfortable. (3) In this experiment, temperature changes had a more pronounced impact on thermal comfort-related indices than humidity changes. (4) Sweating during exercise influences both thermal and wet sensations. These findings contribute to our understanding of thermal comfort during physical activity and can inform the design of future studies and the development of guidelines for maintaining comfort in various temperature and humidity conditions. Further research should explore the impact of different exercise intensities, durations, and types, as well as additional environmental factors, to provide a more comprehensive understanding of thermal comfort during exercise. At the same time, personalize indoor temperature and humidity comfort control would provide solutions opportunity to move on from energy-consuming central airconditioning and heat pumps. Personal cooling and heating devices can be in-place to provide cooling or heating where necessary, therefore reducing total building energy emissions. In compliance with the carbon neutral future is framing this theme. Acknowledgements This work was supported by the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province, China (Grant No. 21KJB470011), State Key Laboratory of Air-conditioning Equipment and System Energy Conservation Open Project (Project No. ACSKL2021KT01) and the Research Development Fund (RDF 20-01-16) of Xi’an JiaotongLiverpool University.

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Study on the Design of Interior Lighting for the Environmental Satisfaction of Patients in Wards Man Zhang, Shuya Zhang, and Qichao Ban

Abstract Background: At present, the quality of the indoor environment in hospitals is attracting a lot of attention from society in order to improve the recovery and well-being of patients due to the requirements of health outcomes. Lighting plays a significant role in healthcare environments, directly affecting the physical and mental health of patients. However, most artificial lighting designs have not carefully considered the user experience, which means that some results or conclusions may not reflect reality. Users spend most of their time in hospital wards and their opinions are an invaluable guide for hospital architects. Objective: This study aims to investigate patients’ environmental satisfaction in wards with different interior lighting conditions, in order to provide useful advice for good designs of healthcare environments. Methods: Field investigations and a randomized controlled trial (RCT), which lasted four months (from 1st March 2022 to 30th June 2022), were conducted at the intensive care liver unit of a Class A hospital in Jiujiang, Jiangxi Province, China. Parameter values of nighttime lighting for these experiments were designed based on academic literature and the Standard for Lighting Design of Buildings (GB500342013). A questionnaire survey was conducted to investigate the problems faced by the artificial lighting environment in the wards. Data on patients’ satisfaction were collected by individual interviews under different parameters (i.e., illumination levels of 100 lx and 200 lx, light positions at head of the bed, opposite the bed and on the ceiling), and linear regression analysis was used for statistical analysis. Conclusions: This study showed that patients prefer bedhead lights with an illumination level of 200 lx and a color temperature of 3000 K. In addition, adjustable lighting in wards will improve the environmental satisfaction of patients, which will be verified in further studies. All findings can be used as evidence to inform the design of interior lighting in wards toward a better healthcare environment for health outcomes.

M. Zhang · S. Zhang · Q. Ban Innovation Institute for Sustainable Maritime Architecture Research and Technology (iSMART), Qingdao University of Technology, Qingdao, China College of Architecture and Urban Planning, Qingdao University of Technology, Qingdao, China M. Zhang College of Architecture, Qingdao City University, Qingdao, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_10

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Keywords Evidence-based design · Interior lighting · Environmental satisfaction

1 Introduction Studies on a number of hospital physical environments have confirmed that there is a clear association between healthcare environments and patient health outcomes (Mourshed and Zhao 2012). The upgradation of health environments can not only promote patients’ recovery and overall satisfaction, but also increase the work efficiency and nursing quality of medical staff (Ulrich 1984; Buchanan et al. 1991; Trochelman et al. 2012; Buchanan 2012). In 2014, Phiri and Bing had already incorporated considerations for improving patient well-being into the design of healthcare environments, including increasing patient safety and outcomes, improving staff efficiency and effectiveness, and enhancing user satisfaction (Phiri and Chen 2014). Research showed that light is a promising non-pharmacological intervention, which can improve the sleep quality of patients and reduce the degree of patients’ depression (Joseph, 2006; Lieshout-van Dal et al. 2019). Relevant Studies have also shown that artificial light, as a decorative environmental feature, has a positive distracting effect (Jamshidi et al. 2020). Robinson and Green (2015) compared the lighting environment of a new pediatric emergency department with a traditional one and discussed the effects of exposure to ambient lighting on patients. They found that, compared to the traditional emergency department, pediatric patients experienced less pain, nursing staff experienced less stress, and the anxiety levels of patient’s parents were also reduced. Research showed that the 24-h dynamic lighting design can reduce the symptoms of circadian disruption disorder by summarizing the effect of light based on the randomized controlled trials (RCTs) on patients’ circadian disruption (White et al., 2013). Light is a necessary condition for the operation of the visual system. A large number of epidemiologic studies show that the influence of light on patients’ circadian rhythm depends on several factors, including light intensity, color temperature, color rendering index, and the absorption spectrum of the lighting sources (Lieshoutvan Dal et al. 2019). Too little or too much light intensity can cause visual discomfort, resulting in eyestrain (Boyce, 2010). The color temperature of light also affected the secretion of melatonin. Warm color temperatures stimulate the secretion of melatonin, while cool color temperatures have the opposite function (Lieshout-van Dal et al. 2019). In addition, this study found great differences in wards’ artificial lighting among 13 hospitals in China. The most notable differences were observed in the aspects of the number of lights, light intensity, color temperature, and positioning of lights within the wards. Therefore, based on the above issues, this study aims to explore the patients’ preference for the combination of multiple groups of lighting parameters in the ward and to provide a reference for the design of interior lighting in the ward.

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Fig. 1 Scheme of the study design

2 Method 2.1 Study Design The object of this study was patients in the intensive care liver unit of a Class A hospital in Jiujiang, Jiangxi Province, China. This study consists of two stages: a survey of the current situation and a randomized controlled trial (RCT). The survey of the current situation aimed to collect basic environmental information about the wards and investigate patients’ attitudes towards the current lighting environment through a questionnaire (Qichao et al. 2016). The RCT is designed to further explore patients’ perceptions of comfortable lighting environments through individual interviews (Fig. 1).

2.2 Situation Investigation The process is divided into two parts: collecting current environment information and evaluating patients’ attitudes about the lighting in their wards by a questionnaire. The basic information collected includes some important aspects of the wards, for example, temperature and humidity, lighting situation, lighting equipment locations, ward layout, room size, and door and window positions (Fig. 2). In addition, the behaviors of medical staff and patients were observed for a week (1st March 2022 to 7th March 2022) to understand their habits about the use of lights. The second step involves questionnaire surveys, which were divided into three parts: subjective evaluation, demand evaluation, and open-ended questions. The subjective evaluation (Tables 1 and 2) used a Likert-type 5-point scale for descriptive statistics. The demand evaluation part uses a Likert-type 3-point scale, mainly for the demand for additional lighting and the demand for lighting adjustability. The survey is voluntary, and all patient information is kept confidential.

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Fig. 2 The situation of a ward

Table 1 Evaluation of lighting environment comfort Least Uncomfortable Commonly Comfortable Very comfortable comfortable ◻

◻

◻

◻

◻

Light brightness ◻

◻

◻

◻

◻

◻

◻

◻

◻

◻

Ward lighting Light position

1: Least comfortable, 2: Uncomfortable, 3: Commonly, 4: Comfortable, 5: Very comfortable

2.3 A Randomized Controlled Trial Before the experiment, meters for illuminance, temperature and humidity were installed in an unobstructed location next to each sickbed. The temperature and humidity meters were used to measure the temperature and humidity of the wards. The illuminance meters were used to collect real-time data about the illumination intensity in the ward. To investigate the lighting environment that suits patients’ comfort needs, the lighting color temperature was set to 3000 K based on previous research – “From the perspective of overall satisfaction, patients prefer 3000 K” (Xu, 2019). Based on the Building Lighting Design Standard (GB50034-2013) and the status of 13 hospital wards, the lighting intensity and the lighting positions were set as the independent variables, and patient comfort was set as the dependent variable (Table 3). Each experiment lasted for 14 days, and on the last day of each experiment, individual interviews were conducted with patients regarding their comfort with the lighting (Xu and Hao 2019). Patients were asked to describe their feelings regarding the brightness or position of the current lighting and provide improvement suggestions based on their experiences with different activities. The average number of participants in each experiment was 23 (±2), and all participants were recruited randomly.

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Table 2 Evaluation of the influence of lighting environment on sleep quality Least important

Unimportant

Neither important nor unimportant

Important

Very important

The impact of lighting brightness on patients’ sleep quality

◻

◻

◻

◻

◻

The impact of lighting brightness on patients’ recovery

◻

◻

◻

◻

◻

The impact of lighting position on patient’s sleep quality

◻

◻

◻

◻

◻

The impact of lighting position on patient’s recovery

◻

◻

◻

◻

◻

1: Least important, 2: Unimportant, 3: Neither important nor unimportant, 4: Important, 5: Very important

Table 3 Experiment groups Serial number

Independent variables Illuminance(lx)

Light position

1

100

Opposite the bed

2

200

3

100

4

200

5

100

6

200

Test time 1st April to 14th April 16th April to 29th April

On the ceiling

1st May to 14th May 16th May to 29th May

The head of the bed

31st May to 13th June 15th June to 28th June

2.4 Data Collection and Analysis The data collection of this study was from 1st March 2022 to 30th June 2022. The questionnaires and interviews were conducted from 7:30 pm to 9:00 pm. Based on relevant standards and literature review of previous relevant studies, the Benetech GM1361 thermometer, Benetech GM1030 illuminance meter, and TES-1330A color temperature meter were used for data collection and the data was regularly exported

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and collated (Zaitsev 2020; Korcz 2021; Chen 2014). The lighting equipment was managed by the researchers using Philips adjustable lighting. IBM SPSS Statistics 26 was used for data analysis.

3 Results 3.1 Participants’ Characteristics These 197 patients participated in this study, including 54 in questionnaires and 143 in individual interviews. Patients participated in an informed and voluntary manner. A total of 58 questionnaires were collected in this survey, of which 54 were usable questionnaires (93.1%). The demographic characteristics of the questionnaire respondents and their hospitalization days are shown in Table 4. Among the 54 respondents, 42 of them (77.8%) were male, and 12 (22.2%) were female. More than half of the participants (62.9%) were over 50 years old, while 24.1% and 13.0% of the participants were between 36–50 years old and 26–35 years old, respectively. According to statistics, more patients (79.6%) stayed in the hospital for more than 14 days (35.2%) and between 8 and 14 days (44.4%), and only 20.4% of patients stayed in the hospital for less than 7 days. Patients were encouraged to experience both types of lighting to fully experience the lighting environment while ensuring their comfort. A total of 143 patients participated in individual interviews, with an average of 23 participants in each interview. All respondents were conscious and non-critical patients. Table 4 Background information of the participants of the questionnaire

Variable

Scale/Category

Quantity

Rate (%)

Gender

Male

42

77.8

Female

12

22.2

26–35

7

13.0

36–50

13

24.1

>50

34

62.9

≤7

11

20.4

8–14

24

44.4

>14

19

35.2

Age(year)

Length of stay(day)

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Table 5 Descriptive analysis of patients on the comfort level Item

Comfort a (%) 1

2

3

Ward lighting

18.5

55.6

20.4

5.6

Lighting brightness

13.0

61.1

16.7

7.4

3.7

46.3

38.9

11.1

Lighting position a

4

Mean

SD

0

2.130

0.778

1.8

2.241

0.845

0

2.574

0.742

5

1: Least comfortable, 2: Uncomfortable, 3: Commonly, 4: Comfortable 5: Very comfortable

3.2 Subjective Assessment of the Situation of the Lighting Environment in Wards This study conducted a subjective questionnaire reliability analysis on the collected questionnaires. Cronbach’s alpha coefficient of the scale was 0.784, which indicated a high level of reliability. Table 5 shows the subjective evaluations of patients on the comfort level of the current ward lighting and the impact of lighting on their sleep quality and recovery. Overall, the patients in this department have an overall negative evaluation of ward lighting, with an average score of 2.130. Among them, the impact of lighting brightness on patient comfort level (2.241) is better than the impact of lighting position (2.574). Secondly, it can be seen from the scores that patients believe that both lighting brightness and lighting position have an impact on sleep quality and recovery (Table 6). The impact of lighting brightness is more significant than that of lighting position. Lighting brightness, compared to lighting position, has greater impacts on sleep quality (4.037 vs. 3.907) and patient recovery (3.963 vs. 3.519), respectively. At the same time, through the proportion of importance, it can be found that participants believe that the impact of lighting brightness and position on sleep quality (85.2% and 77.8%) is more important than their impact on recovery (59.3% and 51.9%).

3.3 Patient Comfort Ratings for Different Lighting Combinations Individual interviews were used to understand patients’ feelings toward different experimental lighting conditions and the reasons for their preferences. Figure 3 summarizes the results of patient comfort evaluation for different lighting positions and illuminance levels using grounded theory. According to Fig. 3, patients felt more comfortable when the lighting was positioned at the head of beds, instead of opposite the bed (100 lx: 4.20 compared with 1.92; 200 lx: 4.40 compared with 1.76). In the interviews, patients mentioned some reasons, for example, “the bedside light is not glaring”, “ the switch is near the bed, making it convenient to turn off the light before sleeping”, “ the lighting has a relatively small impact on other patients in the

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Table 6 Descriptive analysis of lighting on sleeping quality and recovery Item

Influence b (%) 1

2

The impact of lighting brightness on patients’ sleep quality

0

5.6

The impact of lighting brightness on patients’ recovery

0

Mean

SD

24.1

4.037

0.751

46.3

13.0

3.667

0.777

18.5

61.1

16.7

3.907

0.708

38.9

42.6

9.3

3.519

0.795

3

4

5

9.3

61.1

5.6

35.2

The impact of lighting position 0 on patient’s sleep quality

3.7

The impact of lighting position 0 on patient’s recovery

9.3

b

1: Least important, 2: Unimportant, 3: Neither important nor unimportant, 4: Important 5: Very important

same room”, and “ the light opposite the bed makes people more restless when there is obvious physical pain.” When the lighting was at the head of the bed, patients tended to prefer an illuminance level of 200 lx (4.40) so that they could engage in communication, read, or use their phones. Some interviewees mentioned that higher illuminance levels (200 lx) were more efficient than lighting level of 100 lx when treated at night. However, when patients were getting ready to sleep, they preferred a comfortable lighting level of 100 lx (4.20) that helped them fall asleep fast. When the light is positioned on the ceiling, 100 lx lighting is more suitable (3.80), compared with 200 lx. Patients believed that the 100 lx light at night is “relatively soft, and the light is not glaring when lying down”. However, during the day, patients prefer 200 lx illumination (3.60)—”this type of light is convenient for doctors to do rounds and can supplement the lack of sunlight, but it feels a bit too bright at night, and uncomfortable for the eyes”. When the light is positioned opposite the bed, both lighting level (i.e., 100 lx and 200 lx) are uncomfortable, mainly because “the light shines directly into the eyes”. Patients who had long-time stayed in these wards mentioned that “the facilities of the hospital are obsolete, and the design of the lighting environment should be renovated. After analyzing the interview records, it is found that the subjective differences were mainly that some patients believed that ceiling lights are more useful for even illumination than bedside lamps, and the most commonly used type of lighting in daily life.

4 Discussion Based on the results of this study, the environment of the wards had not reached a high level. According to Devlin and Arneill (2003), healthcare quality assessment, including the physical environment, is part of professional practice standards, and

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Fig. 3 Comfort evaluation of different positions corresponding to different illumination levels

this study confirms this conclusion. The natural lighting in the wards cannot meet the patients’ normal natural light needs. In this situation, the obsolete lighting equipment in the ward, as well as previous design of the wards, seriously affect rest and sleep quality of the patients. Furthermore, patients in this department already suffer from symptoms of pain and bad sleep quality, making it even more important to upgrade issues that may cause discomfort in the ward environment. During the experiment, there were cases that patients in the same ward had different preferences for the location of lights. However, the beds in the ward lack curtains, which cannot protect patients’ privacy or meet individualized lighting needs. Improving the functionality and medical process of healthcare buildings (by promoting patient recovery and healthcare staff work efficiency) can promote the comprehensive enhancement of green healthcare buildings and environmentally sustainable practices. In response to these issues, it is necessary to develop a renovation plan for the ward environment from the decision-making level and update the infrastructure equipment of the wards design promptly to provide a comfortable recuperation environment for patients. Finally, increasing the number of lights in different positions in the room and increasing the adjustability of light brightness may also serve as evidence to improve patient satisfaction. In addition, it is also important to consider individual patient preferences and needs when designing lighting environments in healthcare settings. Similar lighting may elicit different responses from different patients, so implementing the same lighting scheme in a new hospital may not necessarily result in the same level of satisfaction for all patients. Individual differences can exist between different ages, genders, health statuses, and cultural backgrounds, all of which may influence patients’ perceptions and preferences regarding lighting. For example, warmer lighting may be more comfortable for some older or unwell patients, while cooler lighting may be more attractive to other patients. Additionally, cultural backgrounds and social

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customs may also impact patients’ perceptions and preferences for lighting, with some cultures preferring softer lighting. Therefore, when implementing a lighting scheme in a new hospital, patient individual differences should be taken into consideration and efforts should be made to meet their needs and preferences as much as possible. This can be achieved through communication with patients, providing adjustable lighting equipment, and other strategies. During the experiment, this study only considered the effects of lighting intensity and position on patient comfort, but factors including color temperature, lighting uniformity, and glare. These factors may also impact patients’ healthcare outcomes and their perception of the lighting environment, which require further experimentation and discussion.

5 Conclusion The study focused on comparing the combined effects of lighting position and intensity on patient comfort. Through comparison, it was found that the overall comfort rating was highest for the 200 lx bedside lamp and lowest for the 200 lx lamp on the opposite side. In summary, through the randomized controlled trial, the degree of influence of different combinations of lighting brightness and positioning on patients’ comfort was evaluated, thereby determining the optimal lighting design scheme. It can improve patients’ hospitalization experience, improve their comfort, and accelerate their recovery, thereby improving medical quality and effectiveness. And this study further illustrates the necessity of including the physical environment in professional practice standards. In addition, the data and conclusions of randomized controlled trials can be used to update relevant standards and guidance principles in hospital design guidelines to better adapt to constantly changing clinical practices and technological advances. This helps guide future hospital renovations and new construction designs, improve the quality and efficiency of medical facilities, accelerate patients’ comfort during their recovery, and promote the continuous development and improvement of medical services. Acknowledgements Thank you for the financial support provided by the National Natural Science Foundation (NSFC) (no. 51908300) for this study. The authors would like to express our gratitude to all participants, including four researchers, the patients, doctors, nurses, and administrators who supported data collection. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patients to publish this paper. Conflicts of Interest The authors declare no conflict of interest.

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References Boyce PR (2010) The impact of light in buildings on human health. Indoor Built Environ 19(1):8–20 Buchanan TL, Barker KN, Gibson JT, Jiang BC, Pearson RE (1991) Illumination and errors in dispensing. Am J Hosp Pharm 48(10):2137–2145 Chen Y, Liu J, Pei J et al (2014) Experimental and simulation study on the performance of daylighting in an industrial building and its energy saving potential. Energy Build 73:184–191 Devlin AS, Arneill AB (2003) Health care environments and patient outcomes: a review of the literature. Environ Behav 35(5):665–694 Jamshidi S, Parker JS, Hashemi S (2020) The effects of environmental factors on the patient outcomes in hospital environments: a review of literature. Front Archit Res 9(2):249–263 Joseph A (2006) The impact of light on outcomes in healthcare settings. Center for Health Design Korcz N, Janeczko E, Bielinis E et al (2021) Influence of informal education in the forest stand redevelopment area on the psychological restoration of working adults. Forests 12(8):993 Mourshed M, Zhao Y (2012) Healthcare providers’ perception of design factors related to physical environments in hospitals. J Environ Psychol 32(4):362–370 Phiri M, Chen B (2014) Sustainability and evidence-based design in the healthcare estate. Springer, Berlin Heidelberg Qichao B, Chen B, Sharples S, Phiri M (2016) A study on architectural design tools and sustainability assessment standards of the healthcare environment. Archit J Robinson PS, Green J (2015) Ambient versus traditional environment in pediatric emergency department. Health Environ Res Des J 8(2):71–80 Trochelman K, Albert N, Spence J, Murray T, Slifcak E (2012) Patients and their families weigh in on evidence-based hospital design. Crit Care Nurse 32(1):e1–e10 Ulrich RS (1984) View through a window may influence recovery from surgery. Science 224(4647):420–421 van Lieshout-van Dal E, Snaphaan L, Bongers I (2019) Biodynamic lighting effects on the sleep pattern of people with dementia. Build Environ 150:245–253 White MD, Ancoli-Israel S, Wilson RR (2013) Senior living environments: evidence-based lighting design strategies. Health Environ Res Des J 7(1):60–78 Xu JL, Hao LX (2019) Evidence-based research and practice of healthy luminous environment in wards. New Archit 6:111–115 Zaitsev DV, Batishcheva KA, Kuznetsov GV et al (2020) Prediction of water droplet behavior on aluminum alloy surfaces modified by nanosecond laser pulses. Surf Coat Technol 399:126206

Modular Façade Retrofit with Integrated Photovoltaics-Current Status and Future Development Demands Wanting Wang and Changying Xiang

Abstract With the aim to promote carbon–neutral urban development, a number of recent pilot studies and building projects have investigated an innovative building retrofit solution: modular façade retrofit systems that combine photovoltaics products. Due to the novelty of this field, there is a limited systematic investigation of this promising solution. To present the state-of-the-art of this solution and to investigate future promotion needs, this study conducted a systematic literature study. Out of more than 200 relevant articles, 16 closely related papers were selected for in-depth review. Based on the review, the author proposed a definition of modular façade retrofit with integrated photovoltaics (MFRIPV) and summarized the current key focuses of MFRIPV, including energy performance and economic feasibility, system composition, and design process. The PV technologies and modular structural types of representative MFRIPV cases were also categorized. The findings showed that MFRIPV has satisfactory payback time and can be adopted in both residential and office buildings, providing multifunctional improvements such as better energy efficiency, interior daylight quality, solar energy harvesting and even vertical food production. To further promote MFRIPV application, the author suggested that aesthetic guidelines, integrated energy storage system, and design and management from a life-cycle perspective could be the next investigation priorities. The ultimate goal of MFRIPV should be “energy efficient, energy productive, aesthetically pleasing, user-centered design, easy for massive modular manufacture and assembling, easy for maintenance and upgrade, cost-effective”. This study provided a foundation for advanced MFRIPV study and could serve as a reference for architects, building engineers, researchers, and policy-makers working in the field of sustainable urban renewal. Keywords Modular façade retrofit · Review · Integrated photovoltaics · Sustainable urban renewal

W. Wang · C. Xiang Hong Kong University of Science and Technology, Kowloon, Clear Water Bay, Hong Kong, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_11

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1 Introduction Low-energy or even carbon–neutral urban renewal is an important ongoing trend in many cities. Most of the buildings constructed decades ago cannot meet current energy standards and have defects in thermal insulation and other aspects. In China, as stated in the 14th five-year plan, retrofitting existing buildings with sustainable solutions is the current emphasis instead of the previous large-scale demolishing and new construction (Ministry of Housing and Urban–Rural Development 2021). Similarly, the European Commission also proposed the European Green Agreement recently, which addressed “Energy-and resource-efficient ways to build and renovate” (European Commission 2019). Driven by market demands and supported by policies, various energy-efficient and smart solutions have been developed and tested in real projects. In terms of manufacturing and construction aspects, modular construction is one of the most effective and popular approaches that can significantly reduce waste generation (Loizou et al. 2021). Compared with traditional renovation activities, modular façades retrofits can reduce enormous construction waste, saving time and labour, while providing chances to implement state-of-the-art renewable energy technologies in supporting the carbon–neutral urban transition. In the aspect of utilizing renewable energy in urban contexts, building integrated photovoltaics (BIPV) is one of the most promising sustainable technologies to harvest solar energy onsite and thus can reduce carbon emissions of building operations by providing clean electricity. For façade retrofit, an emerging new solution combining the strengths of modular construction and BIPV is attracting growing interest in the research frontiers (Martín-Chivelet et al. 2018; Wilkinson et al. 2022). To help architects, urban designers, and urban policy-makers have a better understanding of the current development status of related technologies and methods, a systematic literature study is conducted by the authors. The research findings will support the advanced modular façade integrated BIPV design and construction in urban renewal applications.

2 Research Method A comprehensive literature study was conducted to serve as a review foundation. Firstly, a general search was conducted to collect relevant academic publications written in English from databases Science Direct from 2013 to 2023 in Science Direct. The keywords used in this step for identification were ‘PV façade AND modular retrofit’, ‘PV façade AND prefabrication retrofit, ‘and ‘BIPV AND modular renovation’. More than 200 related publications were found. Then the abstracts of the collected papers were investigated, and 67 publications were selected for full-text reading. Thirdly, through full-text investigation and the ‘snowball’ method to add literature, 16 closely relevant papers were chosen for in-depth review. Representative cases were analysed and summarized.

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3 Findings 3.1 General Trend of Research Interests The authors firstly investigated the trend of research interests of the modular methods for façade retrofit. Figure 1 shows the number of published journal papers related to façade retrofit with modular method, in recent 10 years (2013–2023). This indicated an apparent growing interest in academic for modular technologies. Modular façade refers to a system that consists of various units, each of which has a separate function and application within the building’s exterior layer. The separated units (called modules) can be manufactured off-site in factories and then transported and assembled on-site to form an integrated system (Ferdous et al. 2019; Lacey et al. 2018). The literature shows that the modular facades were often designed as multifunctional, besides the typical functions such as energy efficiency improvement (Favoino et al. 2016; Lacey et al. 2018; Lai et al. 2021; Lešnik et al. 2020; Menéndez et al. 2018), integrated ventilation module (Shahrzad and Umberto 2022), enhancement of interior daylight performance (Hosseini and Heidari 2022), there is a growing trend of utilizing integrated photovoltaic (PV) materials in façade retrofits (Fig. 2). According to the structural characteristics, modular facades can be categorized into two types: lightweight and heavyweight modular facades. Lightweight modular façades are represented by using wooden materials and lightweight metal frames (Chen et al. 2023). Benefiting from its minimal carbon footprint and thus little impact on the environment, timber structures has become increasingly popular in modular façade design in recent years (Arkar et al. 2020; Callegari et al. 2015; Hua et al. 2022). While heavyweight modular façades are typically using precast concrete materials as supporting components (Li et al. 2019; Pittau et al. 2017). According to the transparency of photovoltaic materials, they are classified into opaque photovoltaics and semi-transparent photovoltaics. Opaque PV materials are represented by crystalline silicon solar cells, which are now the most developed and widely used technologies. Fig. 1 Numbers of articles related to modular façade retrofit from 2013 to 2022. Source Science Direct

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Fig. 2 Numbers of articles related to BIPV façade retrofit from 2013 to 2022. Source Science Direct

Current commercial mono-crystalline silicon PV panels can achieve an efficiency of around 23%, whereas the efficiency of perovskite-silicon tandem solar cells can reach 30% efficiency (Pandey et al. 2023). Various technologies have been developed for producing semi-transparent PV materials, such as cadmium telluride (CdTe) PV, amorphous silicon semi-transparent PV, perovskite-based solar cells, etc.

3.2 Definition of Modular Façade Retrofit with Integrated Photovoltaics MFRIPV Although several studies related to modular façade retrofit have employed PV materials, there is still a lack of a common definition for this approach. Du et al. proposed a definition of modular façade retrofit with renewable energy technologies MFRRn as a renovation process meeting the following aspects: work for existing buildings, works for the facades, utilizing modular methods and integrating renewable energy systems during the building updates (Du et al. 2019). With reference to MFRRn, the authors proposed a definition for modular façade retrofit with integrated photovoltaics MFRIPV as a sustainable façade update process to implement BIPV technologies, while the main systems are manufactured and constructed via modular approaches. The ultimate goal of MFRIPV should be “energy efficient, energy productive, aesthetically pleasing, user-centered designed, easy for massive modular manufacture and assembling, easy for maintenance and upgrade, cost-effective”.

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3.3 Representative Modular Façade Retrofit Studies with BIPV Technologies Although many studies mentioned both modular approaches and usages of renewable energy systems, only a few studies were closely related to the concept of MFRIPV. The selected representative studies were presented below. Table 1 showed a summary of the representative works in the field of MFRIPV. Energy and economy were the most investigated aspects, as one of the key common purposes of modular façade retrofits was to improve the building energy performance and the economic feasibility was critical. The literature findings showed that modular façade retrofits with certain BIPV technologies can not only produce clean energy but also have considerable capacity to reduce energy consumption, such as saving interior cooling loads, while the payback time of the investment was also acceptable in local scenarios. Through a novel 3D GIS-based method (Saretta et al. 2020), Saretta et al. investigated the potential of BIPV façade retrofit of a Swiss residential area with multi-story houses. With accurate consideration of the impact of architectural and constructive characteristics of façades, the simulation showed that around 62% Table 1 Summary of the representative works in the field of MFRIPV Authors and years

Key functions

Nagy et al. (2016)

System name

Building typology

BIPV technology

Modular type

Harvest solar ASF energy, active shading, improve interior daylight

Office building

Thin-film CIGS modules (opaque)

Lightweight (aluminium)

Paiho et al. (2015)

Improve energy efficiency, harvest solar energy

Meefs

Residential building

CIS (copper–indium–selenium) technology or other types (opaque)

Lightweight (Fiber reinforced polymer)

Favoino et al. (2016)

Improve energy efficiency, harvest solar energy, improve indoor air quality

ATCRESS

Office building

Amorphous silicon panels (opaque)

Lightweight

Tablada et al. (2018)

Shading, harvest solar energy, food production

None

Residential building

Could be various type (opaque or semi-transparent)

Lightweight

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of the annual energy demands could be covered by the facade BIPV retrofit, while the payback time of investment was 18, 21, and 23 years for southern, eastern, and western facades respectively with the support of local subsidies. An adaptive solar façade (ASF) prototype was introduced by scholars from ETHz (Nagy et al. 2016). This type of modular dynamic system can be used for both new construction and building retrofit, to provide dynamic shading, harvest solar energy and also distribute daylight via a group of adaptive BIPV modules. The simulation results showed that this novel ASF can save 25% energy consumption compared to traditional fixed louvers shading systems. For high-density urban contexts, Sun et al. explored the feasibility of BIPV application with a case study of a main commercial and tourist street in Singapore (Sun et al. 2021) with the consideration of both solar irradiance and visual impact. Around 41% of vertical facade areas were considered as qualified for BIPV implementation. System composition was another crucial aspect for the MFRIPV systems. The typical profile of the multifunctional system included a supporting structure/frame plus insulation layers and BIPV modules. To update residential buildings in cold climate, Paiho et al. developed a multifunctional retrofit façade system named Meefs (Fig. 3) (Paiho et al. 2015; Rozanska 2016). The Meefs system consists of a several sub-systems: (1) Cost-effective structural framework made of lightweight fiber reinforced polymer, the structural framework will be anchored to the existing façade. (2) An intelligent operation control system that manages all mobile elements, the operation control system is installed on the structural framework and connected to the building energy systems. (3) Technical modules that include advanced technologies to reduce energy consumption and utilize renewable energy. (4) Back layer insulation that fixed mechanically to the back of structural framework to restrict thermal bridge effects. ACTRESS (active, responsive, and solar) was another façade retrofit system was presented and tested by Favoino et al. (2016). Half of the prototype was designed as an opaque part and the other half was designed as a transparent façade module. Three glass stacked laminated amorphous silicon a-Si panels were integrated in the Opaque part to harvest solar energy, a ventilation cavity was designed behind the a-Si panels to support both natural and mechanical ventilation. With focus on the energy performance evaluation, this prototype was installed on an outdoor test cell and tested through a series of experimental measurements over two years. The thermal characteristics of this prototype was approved to be satisfactory under various seasons, while the generated electricity could also power the system itself. The before mentioned ASF prototype (Nagy et al. 2016). The system consisted of a supporting lightweight aluminum frame, steel cable net connected to the aluminum frame, adaptive BIPV shading modules that mounted on the steel cable net (Figs. 4 and 5). The system design process of MFRIPV has been introduced in a few studies. A modular productive façade (PF) system with BIPV shadings and building integrated agriculture (BIA) was developed and tested in Tropical Technologies Laboratory in Singapore (Tablada et al. 2018). The aim of this innovative system was to analyze the possibility of harvesting solar energy and producing food simultaneously on the façades of residential buildings. Firstly, the design concept and main strategies were defined based on a literature study and communication with local experts. Then,

Modular Façade Retrofit with Integrated Photovoltaics-Current Status …

Fig. 3 Concept of Meefs system. Source Paiho et al. (2015) and Rozanska (2016) Fig. 4 Frame and cable-net of ASF system. Source Nagy et al. (2016)

Fig. 5 Building scale ASF prototype. Source Nagy et al. (2016)

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two types of preliminary productive façade prototypes were generated based on the consideration of local residential building profiles. The tilting angles of BIPV shadings and the locations of BIA planters were also defined in step 3. To assist the design decision making, five evaluation criteria were introduced in step 4: food productivity, electricity productivity, interior daylight quality (daylight autonomy DA), façade energy flow (heat gain minus heat loss), and view quality (view angle). Parametric design tools of Grasshopper plugins were employed to simulate the performance of different design variants. The final design was decided by analyzing the obtained simulation data via the VIKOR method (a multiple criteria decision-making method). The best-rated design variants were constructed and installed in an outdoor test lab at the National University of Singapore. The design process of the ASF system (Nagy et al. 2016) included several steps: firstly the system installation facades and positions were selected, then the types of supporting structure were defined, followed by the selection of the shape, size, and pattern of BIPV modules. Based on the shading/ self-shading analysis, the BIPVmodule grid spacing could be decided, and the final steps were the choice of module colors, transparency, and the operation mode. The systems’ energy productivity and its impact on the interior energy consumption were simulated via Rhino and Grasshopper plugins. An ASF prototype was built using 50 lightweight thin-film GIGS PV modules that were mounted via soft pneumatic actuators and small cantilevers on a cable net, which was spun on the aluminum frame. The physical prototype was installed on the ETHz campus to validate the simulation study and gather further user feedback.

4 Future Exploration for Promoting the Application of MFRIPV The review shows that MFRIPV is a promising trend in the AEC industry, supported by modular methods, multifunctional retrofit including solar energy harvest, energy efficiency improvement, interior daylight enhancement, and even food production could be achieved. Theoretically, MFRIPV is also economically feasible with reasonable payback time. Most of the developed MFRIPV systems were supported with lightweight modular structures, while various PV technologies especially opaque BIPV products were tested. It could be interesting to investigate the semi-transparent PV integration for MFRIPV systems, for instance, retrofitting the glazing on facades. However, MFRIPV is still in the early stages of development, not only in academic research but also in real practice. According to Du et al. only 14 projects out of recent 173 building energy efficiency research projects supported by the European Commission’s seventh framework and the Horizon 2020 program, were directly related to the concept of modular façade retrofit with renewable energy systems (Du et al. 2019). Many important aspects of MFRIPV are still rarely explored. The authors thus proposed several key aspects that could be further investigated in future research and real projects.

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First is the aesthetic aspect, only the productive façade (PF) system developed by Tablada et al. (2020) has been investigated via an online evaluation test among local architects, professionals in vertical farming, and experts of PV in Singapore (Tablada et al. 2020). The evaluation results showed an overall acceptance of the PF concept among the experts, the vertical farming designs were highly preferred while the PV systems (in dark color) were considered to need further aesthetic investigation. The overall aesthetic gestalt of PV systems such as shape, geometry, color, and texture play a crucial role in the architectural quality and urban images of a retrofit project, there is a need to systematically investigate aesthetic design guidelines of MFRIPV in various urban contexts (Xiang et al. 2021a, b). For instance, according to Lucchi, when implementing PV applications in architectural heritage sites, aesthetic integration (focusing on spatial, material, and visual compatibility) is the most concerned aspect, followed by technical integration (addressing on hygrothermal, structural, electrical compatibility, etc.) and the energy integration (energy performance and energy usage in life cycle perspective) (Lucchi 2022). In most of the current studies, the energy, economic, and technical aspects were often the focus, advanced aesthetic design is missing, and MFRIPV systems with tailored aesthetic design should be tested. Secondly, there is limited research on integrated energy storage systems for façade integrated renewable energy systems (van Roosmalen et al. 2021). This aspect should be further considered in the earlier design stages. For large-scale implementation of MFRIPV, the integration design of energy storage system is necessary. In addition, the design and management of MFRIPV from a life-cycle perspective is recommended. Since BIPV and other façade systems are evolving rapidly, there is a need to consider the upgrade of the MFRIPV system in certain years after retrofit. Current studies were mainly focusing on the initial design and construction phases. The authors suggest that BIM-based digital twin platforms could be an ideal tool to support the design, operation, maintenance, and upgrade of MFRIPV. The carbon reduction of MFRIPV can be more specifically calculated/measured with the digital twin platform during the dynamic operation periods. In terms of promoting the penetration ratio in the market, advanced technologies such as blockchain could be used to support complex supply chain cooperation (Dounas et al. 2021).

5 Conclusion The unclear differences among various photovoltaic systems together with their ambiguous definitions make it challenging for policymakers, the public, and researchers to acquire a holistic understanding of the evolution of modular facade retrofitting with integrated photovoltaics. Therefore, the authors aimed to provide a comprehensive assessment of MFRIPV through a comprehensive literature review. This study highlights the potentiality, the development opportunities, and related technical issues connected with the application of MFRIPV in modular façade retrofit of buildings. MFRIPV refers to the façade renovation technology that combines

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the advantages of building integrated photovoltaic (PV) and high-quality modular production. In addition to the capability to harvest solar energy through integrated PV materials, novel products need to fulfill the functional requirements of façade envelopes. MFRIPV has the advantages of a better return on investment (ROI), easy assembly, reduced energy consumption and improved renewable energy efficiency. The adoption of MFRIPV contributes to the sustainable transition of the AEC industry. A potential future study of MFRIPV could focus on three technical aspects: aesthetic aspect, integrated energy storage systems, design and management of MFRIPV from life-cycle perspective.

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Li M, Ma T, Liu J, Li H, Xu Y, Gu W, Shen L (2019) Numerical and experimental investigation of precast concrete facade integrated with solar photovoltaic panels. Appl Energy 253:113509. https://doi.org/10.1016/j.apenergy.2019.113509 Loizou L, Barati K, Shen X, Li B (2021) Quantifying advantages of modular construction: waste generation. Buildings 11:622. https://doi.org/10.3390/BUILDINGS11120622 Lucchi E (2022) Integration between photovoltaic systems and cultural heritage: a socio-technical comparison of international policies, design criteria, applications, and innovation developments. Energy Policy 171. https://doi.org/10.1016/j.enpol.2022.113303 Martín-Chivelet N, Gutiérrez JC, Alonso-Abella M, Chenlo F, Cuenca J (2018) Building retrofit with photovoltaics: construction and performance of a BIPV ventilated façade. Energies 11:1719. https://doi.org/10.3390/EN11071719 Menéndez A, Martínez A, Santos A, Ruiz B, Moritz K, Klein I, Díaz J, Lagunas AR, Sauermann T, Gómez D (2018) A multifunctional ETFE module for sustainable façade lighting: design, manufacturing and monitoring. Energy Build 161:10–21. https://doi.org/10.1016/J.ENBUILD. 2017.12.023 Ministry of Housing and Urban-Rural Development (2021) Prevention of large-scale demolition and construction in the implementation of urban renewal initiatives [WWW Document]. http:// www.gov.cn/zhengce/zhengceku/2021-08/31/content_5634560.htm. Accessed 30 Jan 2023 Nagy Z, Svetozarevic B, Jayathissa P, Begle M, Hofer J, Lydon G, Willmann A, Schlueter A (2016) The adaptive solar facade: from concept to prototypes. Front Archit Res 5:143–156. https://doi. org/10.1016/J.FOAR.2016.03.002 Paiho S, Seppä IP, Jimenez C (2015) An energetic analysis of a multifunctional façade system for energy efficient retrofitting of residential buildings in cold climates of Finland and Russia. Sustain Cities Soc 15:75–85. https://doi.org/10.1016/j.scs.2014.12.005 Pandey R, Bhattarai S, Sharma K, Madan J, Al-Mousoi AK, Mohammed MKA, Hossain MK (2023) Halide composition engineered a non-toxic perovskite–silicon tandem solar cell with 30.7% conversion efficiency. ACS Appl Electron Mater. https://doi.org/10.1021/ACSAELM. 2C01574 Pittau F, Malighetti LE, Iannaccone G, Masera G (2017) Prefabrication as large-scale efficient strategy for the energy retrofit of the housing stock: an Italian case study. Procedia Eng 180:1160– 1169. https://doi.org/10.1016/J.PROENG.2017.04.276 Rozanska M (2016) Multifunctional energy efficient façade system for building retrofitting Saretta E, Caputo P, Frontini F (2020) An integrated 3D GIS-based method for estimating the urban potential of BIPV retrofit of façades. Sustain Cities Soc 62:102410. https://doi.org/10.1016/J. SCS.2020.102410 Shahrzad S, Umberto B (2022) Parametric optimization of multifunctional integrated climateresponsive opaque and ventilated façades using CFD simulations. Appl Therm Eng 204:117923. https://doi.org/10.1016/J.APPLTHERMALENG.2021.117923 Sun H, Heng CK, Tay SER, Chen T, Reindl T (2021) Comprehensive feasibility assessment of building integrated photovoltaics (BIPV) on building surfaces in high-density urban environments. Sol Energy 225:734–746. https://doi.org/10.1016/J.SOLENER.2021.07.060 Tablada A, Kosori´c V, Huang H, Chaplin IK, Lau SK, Yuan C, Lau SSY (2018) Design optimization of productive façades: integrating photovoltaic and farming systems at the tropical technologies laboratory. Sustainability 10:3762. https://doi.org/10.3390/SU10103762 Tablada A, Kosori´c V, Huang H, Lau SSY, Shabunko V (2020) Architectural quality of the productive façades integrating photovoltaic and vertical farming systems: survey among experts in Singapore. Front Archit Res 9:301–318. https://doi.org/10.1016/J.FOAR.2019.12.005 van Roosmalen M, Herrmann A, Kumar A (2021) A review of prefabricated self-sufficient facades with integrated decentralised HVAC and renewable energy generation and storage. Energy Build 248. https://doi.org/10.1016/j.enbuild.2021.111107 Wilkinson SJ, Noguchi M, Kim J-T, Altan H, Bantanur S, Formoso CT, Frattari A, Hashemi A, Onyango JO, Anissa K, Aoul T (2022) A simplified method for BIPV retrofitting of emirati public

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Study on the Synthetic Action of Environmental Factors on the Work Stress of Medical Staff Shuya Zhang, Man Zhang, and Qichao Ban

Abstract Background: Much literature has indicated that the physical environmental conditions affect medical staff’s job performance—for example, satisfaction, behavior, error rates, and psychological stress, which further impacts the recovery and well-being of patients. Aims: This study investigates the environmental conditions of medical staff and explores the role of a combination of environmental factors that can reduce their work stress. Methods: From April 17 to June 2, a field investigation was conducted at a hospital in Jiujiang, Jiangxi Province. In terms of environmental factors, light intensity, decorative pictures, and vegetation were chosen as independent variables based on literature review, which were combined into six experimental groups. Twelve medical staff members, including doctors and nurses, were recruited from inpatient departments. They were asked to complete actigraphy recordings and self-reported satisfaction assessments (e.g., job satisfaction and environmental satisfaction) to evaluate their emotion during working shifts in different environmental settings. Several scales and questionnaires (e.g., Eye Fatigue Scale, Generalized Anxiety Disorder-7 items (GAD-7), Patient Health Questionnaire-9 items (PHQ-9), and Perceived Stress Scales (PSS)) were used in in-depth interviews to assess participants’ medical symptoms and mental health status. The between-subjects experimental design was adopted for descriptive statistics and multiple linear stepwise regression analysis. Results: Experimental results demonstrated that participants preferred the illumination level of 300 lx than 400 lx for night shifts. In regard to decorative pictures and vegetation, participants expressed that vegetation, instead of pictures, would create a comfortable atmosphere. Conclusions: The findings suggested that the combination of 300 lx illumination and vegetation could play an important role on the reduction of medical staff’s work stress, and decorative pictures had minimal effects. A better understanding can be achieved about the combined action of environmental factors on the working conditions of medical S. Zhang · M. Zhang · Q. Ban Innovation Institute for Sustainable Maritime Architecture Research and Technology (iSMART), Qingdao University of Technology, Qingdao, China College of Architecture and Urban Planning, Qingdao University of Technology, Qingdao, China M. Zhang College of Architecture, Qingdao City University, Qingdao, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_12

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staff, which can be used as evidence to inform the design of healthcare environments and optimize health outcomes. Keywords Healthcare environment · Environmental factor · Work stress · Evidence-based design

1 Introduction Many studies have shown that the physical environment of a building has a direct and indirect impact on the mental health of its occupants. The interaction between people and their surroundings in a work environment can cause physical and psychological stress, which can affect their comfort, performance, productivity, safety and health in the work environment (Parsons 2000). The physical environment of a hospital may affect the performance of staff. Studies have indicated that medical staff are experiencing increasing stress and decreasing job satisfaction, leading to a number of job-related health problems and inappropriate care (Hayes et al. 2012). The status of nurses is influenced by individual and organizational factors such as workload, stress, workplace conditions and the environment in which they work in practice (Chao et al. 2015). Hobfoll & Shirom et al. represented that when nurses feel stressed at work, receiving more support from their work environment helps them to cope more positively with difficulties (Hobfoll n.d. 2001). The demand for healthcare has been increasing in recent years. With an ageing population and a rising proportion of patients with chronic diseases, there is a need for a better understanding of the comfort and wellbeing associated with the physical environment of hospitals. Shift work has resulted in healthcare workers staying indoors for longer periods of time. While electric lights are the main source of lighting indoors, this single light pattern (and the associated circadian rhythm/sleep disruption) can negatively affect their health, sleep and productivity, thus compromising their physical health (Wang et al. 2018). Medical staff have minimal access to daylight during night shifts or when working mainly indoors. Excessive exposure to indoor lights at night or insufficient sunlight during the day can lead to disturbances in circadian rhythms (Kang et al. 2020). Constant exposure to artificial light, especially fluorescent light, is often considered by nurses to be one of the most debilitating aspects of work in a nursing unit (Bloor et al. 2006). An increasing number of research in recent years has demonstrated the calming, restoring, and mood-improving effects of indoor plant exposure (Deng and Deng 2018; Han and Ruan 2020). In addition to the effects of plants, greenery is vital as an effective natural element. Particularly, in experiments with pictures of indoor university premises, students preferred places with green elements, whether these were real plants or posters (Bogerd et al. 2018). In experimental plant-free studies green have been found to be calming and increase feelings of well-being (Huang and Lu 2015; Jalil et al. 2012). And green plants were more strongly correlated with improved comfort and relaxation than red plants.

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Hospital buildings are intricate structures, and the interactions between various departments and the staff’s health might be diverse. Understanding the relationship among the physical environment and the psychological condition of staff, while considering their particular preferences and needs, may help to develop appropriate hospital design guidelines.

2 Method 2.1 Study Design This research was conducted based on a series of field investigations, including measurements, observations, questionnaire surveys, controlled experiments and interviews, in a typical general hospital, located in Jiujiang, Jiangxi Province, China. The medical staff surveyed met the following requirements: (a) had a relevant license; (b) had worked in the inpatient unit for more than 1 year; and (c) volunteered to participate in the following study. The medical staff works in two shifts, with the morning shift beginning at 07:30 and the evening shift beginning at 17:30, with the morning shift lasting approximately 9.5 h whereas the evening shift lasts approximately for 15.5 h, including a 30-min handover and rest period. The trial and data collection takes place between March 2022 and June 2022. A total of five steps are involved. Both measurement (Step 1) and observation (Step 2) are intended to evaluate the condition of the interior physical environment and to pinpoint the key elements affecting the comfort of healthcare professionals. A control experiment (Step 3) was conducted to understand the impact of different physical environmental factors on the stress levels of medical staff at the workplace. During this period, questionnaires were developed to quantify the level of comfort and stress of them at each stage. In-depth interviews were conducted (Step 4) to further understand the link between more relevant environmental factors and the comfort and stress levels of healthcare workers.

2.2 Measurement Measured the illuminance of the lamps received at standard heights in various parts of the workstation, measured by four instruments installed in location A, B, C and D (Fig. 1). The three rooms of nurses’ station all face north and receive minimal natural light, with lights on round-the-clock. The measurements lasted three days (15th March 2022 to 17th March 2022). After the measurements were taken, all results were compared to the guideline values from the Standard for Lighting Design

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Fig. 1 Layout of the work station and measuring device locations

of Building GB/50034-2013. The Benetech GM1030 illuminance meter and TES1330A color temperature meter were chosen for the analysis in order to collect environmental data 24/7 in accordance with relevant government standards as well as recommendations from related studies.

2.3 Observation The observation lasted for one week (18th March 2022 to 24th March 2022). Different work habits of healthcare professionals were noted, and these differences may have influenced the health care workers’ evaluation of the work environment.

2.4 Questionnaire Surveys The questionnaire can be divided into two phases. The first phase of a questionnaire (25th March 2022) survey was conducted to understand the comfort and stress levels of medical staff in the pre-existing physical environment of the nurses’ station. The second stage is to quantify the extent to which environmental factors (lamp illumination, plants, green paintings) affect the comfort and stress of healthcare workers during the field trial.

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Table 1 Experimental Schedule Serial number

Illuminance

Section-1

300

Vegetation √ √

Pictures

Test time

×

1 April to 14 April

Section-2

400

×

16 April to 29 April

Section-3

300

×

×

1 May to 14 May

Section-4

400

×

× √

16 May to 29 May

Section-5

300

×

Section-6

400

×

√

31 May to 13 Jun 15 Jun to 28 Jun

The survey instruments that was used including the Perceived Stress Scales10 items (PSS-10) (Berlinberg et al. 2019), Generalized Anxiety Disorder-7 items (GAD-7) (Toussaint et al. 2020), Patient Health Questionnaire-9 items (PHD-9) (Levis et al. 2019), Eye Strain Scale (The occurrence of common eye strain symptoms is assessed using a score ranging from 1 to 9, with higher values being more severe.) and Lighting Satisfaction (assessed using a 7-point Likert scale ranging from “very satisfied” to “very dissatisfied”.) The questionnaire was distributed online to minimise direct contact.

2.5 Control Experiment A control experiment (Table 1) was set up with lamp illumination, plants and green pictures selected as variables according to the Standard for Lighting Design of Building GB/50034-2013, related studies and the current situation of nurses’ stations in inpatient units. The studies were conducted with Philips dimmable LED bulbs, and the researcher was in charge of the dimming apparatus. The relevant parameters were measured by a Benetech GM1030 illuminance meter and a TES-1330A colour temperature meter.

2.6 Interview In-depth interviews were conducted to find out what the medical staff wanted from the inpatient nurses’ station environment (29 June 2022 to 30 June 2022). Based on a convenience sampling technique, two doctors and four nurses were included to share their understanding of nurses’ station environment. Every interviewee was chosen at random. They answered three separate questions and each interview lasted for 15 min. • Question 1: What are your requirements for indoor lamps? • Question 2: Do you prefer vegetation or green pictures?

136 Table 2 Values of illumination and colour temperature

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Location

Illuminance (lx)

Colour temperature (k)

(24 h mean) A

148

5370

B

202

5322

C

193

5283

D

135

5315

• Question 3: What do you need from the physical environment of a nurses’ station? The grounded theory was applied to summarize the key words from the records of interviewees. The results were compared to the requirements in relevant design regulations about healthcare environments in China to offer a guiding solution for the design of nurses’ stations in hospitals.

3 Result 3.1 Illumination and Colour Temperature of the Light According to the measurements (Table 2), the original lamp illuminance and colour temperature of the nurses’ station could not meet the requirements of the Standard for Lighting Design of Building GB/50034-2013. The relevant standard stipulates that the standard value of illuminance for the 0.75 m horizontal surface height of the nurses’ station is 300 lx and the colour temperature range is between 3300 and 5300 k.

3.2 Consultations of Surveys and Interviews A total of 84 questionnaires were distributed in the survey and 64 were received, giving a response rate of 76.20%. The statistical results show that the medical staff were not satisfied with the original physical environment of the nurses’ station. They were most comfortable with the placement of plants and a lamp illumination level of 300 lx (Fig. 2). The interviews were designed to further explore some design guidance options based on participants’ attitudes towards the physical environment inside the nurses’ station. For question 1, respondents indicated that they would selectively turn off some lights during the night shift because the illumination level of 300 lx or 400 lx lights is too bright at night. They would like to increase the number of lamps with indirect lighting methods. They do not like warm interior lighting. For question 2, most people

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35

33.5 30

25

25.1 21.9

20

18

16.8 16.1

14.7

15.4 14.2

11.8

12.2 11.2

11.5

11.9

8.5

8.3

8.5

9

10.9 9

4.5

4.5

4.9

4.55

section-1

section-2

section-3

15

10

5

3.3

16.3 15.4 13.7 12.6 12.1

15.9 11.5 9

4.67

3.64

0 section-0

Lighting Satisfaction

Eye Strain Scale

section-4 PHD-9

section-5 GAD-7

section-6 PSS-10

Fig. 2 Results of questionnaire surveys. (The “section-0” is the raw data from the nurses’ station.) All data in the graph are average values per person. The data shows that the psychological condition of the health care workers in the original condition was significantly worse. Health care workers were more satisfied and comfortable with their environment at a lamp illumination level of 300 lx than at an illumination level of 400 lx, by comparing the data from section-1 and section-2, and section-3 and section-4. However, a clear difference was found, with healthcare workers preferring spaces with plants, when comparing section-1, section-3 and section-5, section-2, section-2 and section-6

prefer plants and would like to see more large plants in the hospital. For question 3, some people think that the colour of the walls affects their comfort.

4 Discussion The measurements showed that the illuminance of the lights at the nurses’ station in the selected nurses’ station inpatient unit was substandard. During the measurements, the illuminance and colour temperature received at 0.75 m horizontal height did not meet the requirements of the Chinese standard. This means that health care workers working in a substandard environment increases their stress and reduces their comfort level. Many issues can affect the emotional and physical health of health care workers, with the physical environment being one of the easier factors to deal with. In the hospital chosen, the nurses’ station faces north and has poor ventilation and light

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conditions. The lack of natural light and the dim interior lighting all affected the comfort and health of the medical staff.

5 Conclusions Based on a series of investigations and trials, this study found that a combination of factors in the physical environment of inpatient nurses’ stations affects the health and comfort of health care staff as well as their psychological well-being. The study assessed the combined effects of light levels and plants or photographs, all of which showed that placing plants at 300 lx light levels contributed to staff comfort, while inappropriate light levels had a negative impact on staff. The solution is to install lamps with illumination values of 300 lx and to place small plants in the room. Numerous relevant studies have shown that the satisfaction and well-being of medical staff can easily be overlooked in the design process. Therefore the needs of medical staff should be taken into consideration as information in the design of medical environments. In future work, more field measurements and interviews will be conducted in different hospitals to provide test–retest studies to ensure the reliability of relevant findings that can be used as evidence to inform the design of healthcare environments for public health protection in hospitals.

6 Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the medical staff to publish this paper. Acknowledgements The authors would like to thank all participants, including the patients, doctors, nurses, and administrators who supported data collection. Funding This research was funded by the National Natural Science Foundation of China (NSFC) (grant number 51908300).

References Bloor RN, FRCPsych Mp, Meeson L, Crome IB (2006) The effects of a non-smoking policy on nursing staff smoking behaviour and attitudes in a psychiatric hospital. J Psychiatr Mental Health Nurs Berlinberg EJ, Gonzales JA, Doan T, Acharya NR (2019) Association between noninfectious uveitis and psychological stress. JAMA Ophthalmol 137(2):199–205

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Chao M-C, Jou R-C, Liao C-C, Kuo C-W (2015) Workplace stress, job satisfaction, job performance, and turnover intention of health care workers in rural Taiwan. Asia-Pacific J Public Health 27(2):NP1827–NP1836 Deng L, Deng Q (2018) The basic roles of indoor plants in human health and comfort. Environ Sci Pollut Res 25(36):36087–36101 Han K-T, Ruan L-W (2020) Effects of indoor plants on air quality: a systematic review. Environ Sci Pollut Res 27(14):16019–16051 Hayes LJ, O’Brien-Pallas L, Duffield C, Shamian J, Buchan J, Hughes F, Laschinger HKS, North N (2012) Nurse turnover: a literature review—an update. Int J Nurs Stud 49(7):887–905 Hobfoll SE (n.d.) The influence of culture, community, and the nested-self in the stress process: advancing conservation of resources theory Huang L, Lu J (2015) Eat with your eyes: package color influences the perceptions of food taste and healthiness moderated by external eating. Market Manag 25:71–87 Jalil NA, Yunus RM, Said NS (2012) Environmental colour impact upon human behaviour: a review. Procedia Soc Behav Sci 35:54–62 Kang J, Noh W, Lee Y (2020) Sleep quality among shift-work nurses: a systematic review and meta-analysis. Appl Nurs Res 52:151227 Levis B, Benedetti A, Thombs BD (2019) Accuracy of patient health questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis. BMJ 365:l1476 Parsons KC (2000) Environmental ergonomics: a review of principles, methods and models. Appl Ergon 31(6):581–594 Toussaint A, Hüsing P, Gumz A, Wingenfeld K, Härter M, Schramm E, Löwe B (2020) Sensitivity to change and minimal clinically important difference of the 7-item generalized anxiety disorder questionnaire (GAD-7). J Affect Disord 265:395–401 van den Bogerd N, Dijkstra SC, Seidell JC, Maas J (2018) Greenery in the university environment: students’ preferences and perceived restoration likelihood. PLoS ONE 13(2):e0192429 Wang D, Ruan W, Chen Z, Peng Y, Li W (2018) Shift work and risk of cardiovascular disease morbidity and mortality: a dose–response meta-analysis of cohort studies. Eur J Prev Cardiol 25(12):1293–1302

Assessing Economic, Social and Environmental Implications of Implementing Sustainability in the Built Environment C. S. Goh and Shamy Y. M. Chin

Abstract The building and construction sector has been acknowledged as a main contributor to the global carbon emission. In addition to environmental implications, the built environment also has implications in the social and economic development. However, the social and economic implications are often sidelined in the past studies. It therefore calls for a need to investigate the implications of sustainability within the context of built environments. The objective of the paper is to determine the extent to which the three pillars of sustainability are adopted in the built environment and explore their environmental, social and economic implications in a holistic manner. A questionnaire was used to solicit information from a range of construction stakeholders to capture different stakeholder viewpoints on the implications of sustainability. The results showed that more than 80% of respondents considered they have implemented the three pillars of sustainability in their practice. The environmental pillar has the highest level of implementation followed by the social and economic pillars. This result reinforced literature by showing that the environmental sustainability is still predominant in sustainability practice, with an emphasis on energy efficiency and renewable or recyclable resources. Surprisingly, the social implications are greatly acknowledged where a sustainable built environment is perceived to creating a healthier environment and increasing user comfort and satisfactions. Construction stakeholders are however less convinced by the positive economic implications due to an absence of strong evidence of reduced life cycle cost associated with sustainable built environments. This paper provides an empirical insight into the implications of implementing sustainability in the built environment and offers an indication of a transition from the existing environmentaloriented system to a more socio-environmental context in the pursuit of sustainability. Future studies shall integrate more socio-environmental aspects in assessing sustainable built environments to reveal the complex relationships of the three pillars in the pursuit of sustainability. Keywords Economic implications · Sustainable built environment · Environmental sustainability · Social implications C. S. Goh · S. Y. M. Chin Heriot-Watt University Malaysia, Putrajaya, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_13

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1 Introduction The built environment is a spatial element that offers spaces and places for human activities to support their living, working and playing. It includes all kinds of human made spaces such as buildings, landscapes and infrastructure and it is always created for socioeconomic development of people. Because the built environment could affect and be affected, directly and indirectly, by the natural world, the built environment could therefore be a central to attaining sustainable development goals to ensure that future generations can continually live in a healthy environment and enjoy good quality of life. In this Anthropocene era, environmental and social degradation have become global concern. According to GABC (2016), the building and construction sector is responsible for 40% of worldwide energy use, 30% of energy-related greenhouse gas emission, nearly 12% of water use, and almost 40% of waste. It is also one of the main sectors generating approximately 3–15% Gross Domestic Products (GDP) of a country, regardless of developed or developing countries. On the other hand, Mistry (2007) also revealed that the building and construction sector consumes approximately 3 billion tons of natural materials across the globe each year and produces around 30% of the solid waste stream in most of the developing countries. Considering these substantial impacts, positively and negatively, the built environment could play a significant role to in restoring the biodiversity loss and reducing the negative impacts brought by climate change. Sustainability emphasizes the principles of resources efficiency and balanced development between the dimensions of environment, society and economy. By implementing appropriate sustainability measures, the built environment would offer a great potential in attaining the sustainable development goals. According to United States Green Building Council (2017), buildings in the United States surpass both the industrial and transportation sectors and generate almost 40% of national carbon dioxide emissions, but LEED-certified buildings are found to have lower carbon dioxide emissions, consume lesser energy and water, and have diverted more than 80 million tons of waste from landfills. To ensure sustainability is placed in the agenda of the building and construction industry, it is necessary to review and identity the environmental, social and economic implications in a holistic manner. Environment, society and economy are acknowledged as the three pillars (also triple bottom line) of sustainability. The interactions, integrations and interrelationships between environment, society and economy need to be embraced appropriately to ensure a balance between them can often be struck. Environmental sustainability concerns about the restoration of biodiversity, depletion of natural resources, climate change, carbon emissions, waste management, and pollution (Goh 2017). Social sustainability is concerned with social development, satisfaction, comfort, health and safety, accessibility, equality. Meanwhile, economic sustainability considers financial gain, productivity, consumption and competition, and the whole life cost (Goh 2017).

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While numerous literature studies the impacts of sustainable construction projects, few of them examine the impacts on environment, society and economy in a collective manner. Existing research are found to predominantly focus on environmental impacts of sustainable built environment, particularly in the areas of energy efficiency, carbon emissions and renewable energy (Chwieduk 2003; Fowler et al. 2010; Newsham Mancini and Birt 2009). The triple bottom line is the key principle in developing sustainable construction but intensive research focuses mainly on environmental sustainability performance (Goh 2017; Goh and Rowlinson 2015; Zainul Abidin 2010). Although some studies attempt to examine the environmental, social and economic impacts of sustainable construction practice (Beheiry et al. 2006), their analyses were often conducted individually. For instances, investigations on indoor environmental quality have also been carried out (Lee and Guerin 2010; Liu et al. 2018; Ries et al. 2006; Thatcher and Milner 2016) but most of the studies examine the impacts of sustainability on either economy, environment or society. There is a gap in addressing the totality of assessing the implications of sustainable built environment. Notwithstanding the academic research, there is also a significant skew towards environmental sustainability in the prevailing sustainable building assessment systems such as Leadership in Energy and Environmental Design (LEED), Building Research Establishment Environment Assessment Method (BREEAM), Green Mark, Green Building Initiatives, and etc. (Goh 2017). It necessitates more research to take into account a balanced development of the three pillars of sustainability. This research therefore fills the gap by investigating the environmental, social and economic implications of applying the three pillars of sustainability in the built environment in an integrated approach.

2 Implications of Implementating Sustainability 2.1 Environmental Implications Most research found that sustainable buildings and infrastructure could offer numerous environmental benefits in the aspects of carbon emission, pollution, resource consumption, waste generation, biodiversity restoration. Encompassing sustainability in buildings would reduce the depleting rate of natural resources and fossil fuels by replacing them with renewable and sustainable sources. Meanwhile, various energy efficient and water efficient products have also been developed to reduce the environmental impacts. In Scofield (2009)’s study, smaller LEED buildings use comparatively lower energy and majority LEED certified offices use less energy than their counterparts. In 2010, the US General Services Administration research team also assessed the green building performance and observed the whole building performance as follows: (a) aggregate operating costs are 19% lower than the baseline; (b) carbon dioxide equivalent emissions are 34% lower than conventional buildings; (c) energy use intensity are 10–25% better than multiple referenced

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baseline (Fowler et al. 2010). Newsham et al. (2009) also found that LEED buildings on average used about 18–39% less energy per floor area than their conventional counterparts. The past research indicates that sustainable built environment can definitely provide positive impacts in achieving the environmental goals, by preserving resources and restoring biodiversity.

2.2 Social Implications The social dimension is often overlooked in sustainability implementation but it is one of the key pillars for in delivering the sustainability goals. Sustainable practice in buildings could help organisations gaining positive reputations and thereby improving their community relations. As described by Tan et al. (2011), social equity and cultural concerns have been raised in construction related business and corporate social responsibility is being employed by leading construction companies in addressing their environmental, social and economic commitment. Social implications of sustainable construction practice can be examined at different levels—at the building, community and the general society level (US EEEE n.d.). The quality of built environment could bring varying degrees of impacts to occupants in terms of health, comfort and satisfaction. Poor design, improper lighting layout, inappropriate thermal condition, and poor ventilation and indoor air quality could result in illness, absenteeism, stress, fatigue, discomfort, and distractions (US EEEE n.d.). Other similar studies also revealed that introducing proper sustainable features into buildings has an ability to change the people interaction and thereby increasing security concern within the areas. Ries et al. (2006) conducted a case study of a green facility to investigate the benefits of green building construction and identified the social benefits such as daylight, air quality and thermal comfort in the studied project. In 2008, the US General Services Administration (GSA) also commissioned a post-occupancy evaluation to 12 green buildings to examine environmental performance, financial metrics and occupant satisfaction and found that the studied buildings on average perform better in occupant satisfaction than the national average for US commercial buildings (GSA Public Building Service 2008). Similarly, Thatcher and Milner (2016)’s study also shows significant improvements in air quality elements in green buildings. In a more recent study, Liu et al. (2018) also revealed green buildings generally have higher user satisfaction in terms of cleanliness, lighting, air freshness, visual privacy, acoustic, temperature and the overall satisfaction, regardless of cold zone, hot summer-cold winter zone and hot summer-warm winter zone. It can therefore be deduced that sustainable practice in the built environment has brought significant social impacts to users and communities by improving the user comfort level and increasing user satisfactions.

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2.3 Economic Implications Economic factor is often the main consideration of construction stakeholders since it represents cost and benefit of sustainable construction projects. There are two sides of views on economic implications of sustainable buildings. On one side, sustainable buildings are expected to incur higher initial cost compared to non-sustainable buildings due to the incorporation of green technology, integrated design, sustainable building certifications, and special arrangement for administering and operating sustainable buildings (Gan et al. 2015; Goh and Rowlinson 2015). The economic benefits of sustainable construction are often long-term, coupled with high investment and long payback period (Gan et al. 2015). As held by Tan et al. (2011), contractors believed that implementing environmental sustainability practices erode their competitiveness due to the loss of immediate economic benefits resulted from the presence of additional cost, time and resource consumptions. This predominant short-term view on economic implications has discouraged contractors and owners from active engagement in improving their sustainability performance (Gan et al. 2015; Tan et al. 2010). On the other side, sustainable buildings are also expected to achieve energy saving from 25 to 30% considering the increasing utilities cost worldwide. The empirical results of Dwaikat and Ali (2018) show that green buildings can save about 5756 kWh /m2 of energy as compared to the industry baseline and estimated to save $2796,451 at 1% average annual increase of energy price. Because of rising concerns on sustainable development, sustainable buildings are also believed to give higher rental premiums and property values as compared to non-sustainable buildings. At a macro scale, sustainable buildings could also boost up the economic development for communities in the surrounding areas by creating new jobs. A move towards sustainability would also bring impacts on cost and revenue of construction corporates in which financial values can be created via sustainability (Epstein 2014). For instance, green supply-chain management integrates environmental thinking into the project supply chain starting from the design to procurement, manufacture and project delivery phases. It gives concern on the end-of-life management as well as the profits gained in the business (Dadhich et al. 2015). Green supply chain management would improve the efficiency of a company in managing discrete activities, thereby reducing the operational costs, increasing the company’s economy scale, enhancing risk management strategies and increasing the operational effectiveness (Dadhich et al. 2015). In addition, embedding the whole life cycle costing can also reveal the true cost and benefits of sustainable construction projects, commencing from the supply, taking-off and bringing in to the site, until the disposal of built assets (Goh and Rowlinson 2015).

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3 Research Method The paper used a questionnaire approach to collect data. The questionnaire solicited views and information of implementing the three pillars and their associated impacts. The questions were designed with the variables identified through literature review. Closed-ended questions were used in the survey. A 5-point Likert scale from 1 to 5 was used to evaluate the relative context of sustainability implementation in the aspects of environment, society and economy. Stratified sampling was adopted in the study to recruit the target respondents. Stratified sampling allows an efficient supervision manner by forming state in a way that sample allocation to different strata can represent the population with respect to the characteristics under study. Representatives from various stakeholder groups in the built environment can therefore be included in the study. A total of 129 questionnaires were dispatched using either electronic or printed survey form. The research received 42 valid responses which accounts for a response rate of 32.56%. The response rate was deemed reasonable where it is found that a typical survey in the construction sector normally has a respond rate in the range of 20–30% (Takim et al. 2004).

4 Results and Analysis Descriptive statistics were used in the study to reduce the data in a simpler summary. Descriptive statistics give indicators of commonalities in the responses on the respondent background as well as the three pillars implementation in sustainable practice. Mean score was calculated to compare the relative significance of responses in each question while frequency distribution was used to determine how the tested variables disburse and distribute in the responses. The result is presented in two parts. The first part shows the background information of the respondents and the second part discusses the extent to which the three pillars are implemented and also the impacts of sustainable built environment on the triple bottom line, i.e. environment, society and economy.

4.1 Respondents Profile The questionnaire surveys were delivered to various groups of stakeholders in the built environment to determine the extent of the three pillars being implemented in the built environment from different stakeholder perspectives. Table 1 presents the respondent profile in the study. The distribution of survey collected is comprised of

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Table 1 The profile of respondents Stakeholder groups

Developers

Sustainability consultant

Architect

Engineers

Total

Questionnaire sent

34

45

18

32

129

Responses received

9

11

7

15

42

Fig. 1 The implementation of three pillars in sustainable built environment

Implementation of Three Pillars 19%

81%

Yes

No

about 36% engineers, 26% sustainability consultants, 21% clients, and 17% architects. About 86% of respondents hold an executive position and 14% hold a managerial post in their organisations. Majority of the respondents, i.e. 83% have worked in the construction industry for more than 5 years, and more than 65% have actively involved in sustainable built environment in a period of more than 5 years. This is indicative of the involvement of respondents in developing sustainability in the construction industry. As presented in Fig. 1, more than 80% of respondents have considered themselves implementing the three pillars of sustainability in their practice. This could improve the data reliability since the respondents have good exposure to sustainable construction practice and possess relevant experience in applying three pillars in their projects. The respondents were also asked about the understanding of the three pillars and their definitions. The result showed that 97% of respondents perceived themselves to have good understanding of three pillars, i.e. environmental economic and social sustainability, although their definitions towards each pillar could be vary from one another, subject to their interest and exposure in sustainable construction projects.

4.2 Extent of the Implementation of Three Pillars As indicated in Table 2, the environmental pillar has the highest level of implementation (mean score of 3.333), followed by the social pillar (mean score of 2.905) and

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Table 2 The extent to which the three pillars are implemented in the sustainable built environment Environment

Never

Rarely

0

0

Sometime 6

Often

Very often

Mean score

18

10

3.333

Economy

0

2

15

15

2

2.833

Society

0

4

8

20

2

2.905

economic pillar (mean score of 2.833). A wider implementation of environmental sustainability could be due to the vigorous development of legislation and regulation in the governmental policies. According to Gan et al. (2015), environmental protection has been regarded as the fundamental principle in the national policies and legal systems in Mainland China, such as Law on Environmental Protection (1989), Law on Environmental Impact Assessment (2003), Law on energy saving (2008). In Malaysia, various environmental related policies, acts, regulations have also been fully developed such as National Policy on the Environment (DASN), Environmental Quality Act 1974, National Energy Efficiency Action Plan 2016–2025. Considering the extensive governmental effort on legislation, it is no surprising that the environmental pillar has been implemented in a more extensive manner, as compared to the other two pillars. It appears that the social pillar, which is often overlooked in sustainable construction practice starts gaining attention and it is ranked higher than the economic pillar. The economic pillar remains to be less prioritized in the pursuit of sustainable development in the built environment nowadays, despite cost is always a priority of construction stakeholders especially clients.

4.3 Implications of Implementing Three Pillars Figure 2 presents the impacts of implementing three pillars of sustainability in the built environment. Approximate 81% of respondents agreed that applying three pillars in sustainable construction can lead to healthier built environment. User comfort and user satisfaction have been widely recognized as the main benefits of sustainable built environment and this finding concurs the results of Lee and Guerin (2010), Liu et al. (2018), and Ries et al. (2006). Apart from enhancing biodiversity (69%), the three pillars application is also perceived to improve efficiency of discrete activities (74%), offer better project planning and control (62%) and improve supply chain relationship (57%). Sustainability embraces a multiplicity of interfaces and support from various project team members, and hence sustainability promotes coordination and collaboration between project parties. As a result, efforts geared towards the three pillars can yield better results in project planning and management strategies at both organisational and project levels. Meanwhile, social and economic welfare is also acknowledged as a benefit of committing to the three pillars of sustainability (50%).

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Agreements on Impacts of Implementing Three Pillars Change property market to healthy property Better return on investment

20

Types of Impact

18

Improve supply chain relationship

24

16

Offer better project planning/ control

26

13

Enhance biodiversity

29

11

Improve efficiency of discrete activities

31

8

Produce healthier built enviroment 0 Yes

22

21 21

Provide social and economic welfare

No

24

18

5

10

34 15

20

25

30

35

40

Frequency

Fig. 2 Impacts of implementing three pillars of sustainability in the built environment

It appears that respondents have some doubts on the benefits of return on investment (48%) and a healthier and more efficient property market (43%). Literature considers return on investment and an efficient property market as economic gains of sustainability. However, respondents do not agree that implementing three pillars of sustainability would help organisations to gain better return although economic sustainability emphasises sustainable income and the whole life cost. The respondents revealed that profit or monetary gains is not their priority since improving environment benefits and social welfare are their main concerns in sustainable practice. This result is in line with the findings of Zainul Abidin (2010), Goh and Rowlinson (2015) and Hansmann et al.’s (2012), where people are not concerned about the economic impacts in sustainable practice. Instead of offering economic benefits, practitioners believed that sustainable construction practice involves high amount of capital upfront cost and it is not economically viable (Zainul Abidin, 2010). The local stakeholders are less convinced by the lower life cycle cost of sustainable buildings, especially there is no strong evidence demonstrating the tangible economic benefits of sustainable buildings due to the early stage of implementing sustainability in the industry. According to Zainul Abidin (2010), developers in Malaysia tried to balance the three pillars within their means but still found it challenging. In her study, sustainable construction is often viewed as an alternative form of environmental protection and few of them relate it to the social pillar and even the economic pillar. Examining the implications on triple bottom line could help to identify the flaws associated with current implementation sustainability in the built environment. Examining the implications of implementing the three pillars would also lead to better understanding to determine whether proper and sufficient measures have been taken in pursuing sustainability. Attention could be given on weaker areas or pillars for improvement.

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5 Limitations Sustainability is considered at its early implementation stage in Malaysia and some implications may not be fully captured due to the time limit of this study. Implications of sustainable features might take some time for materialisation, especially sustainability aims to attain long term development. Although the paper can still provide indicative results of applying the three pillars, more in-depth empirical studies should be carried out to observe and determine the ultimate implications of the three pillars in sustainable built environment.

6 Conclusion The research suggests some significant implications of applying sustainability in the built environment in terms of environment, society and economy. The results reinforce and give nuances to literature by showing that environmental sustainability is still predominant in sustainable practice, with an emphasis on energy efficiency and renewable or recyclable resources. The dominance of the environmental pillar in sustainability practice in the built environment could arise from overly emphasis on environmental impact in the prevalent governmental policies and legislations. In absence of a harmonized approach of sustainability, giving too much attention on subject areas of climate change, carbon emissions and energy could trigger more greenwashing behaviours amongst construction organisations. However, the paper suggests there is a shift in the current sustainability practice towards a more integrated approach, by taking the social and economic pillars in consideration. A healthier environment (social impact) is found to be the major implication of committing the three pillars in sustainable built environment, followed by improving project efficiency and enhancing biodiversity. The result implies that a traditional view of sustainable practice could have been changed whereby people tend to giving more recognition to social impacts in their implementation of sustainability in the built environment. The findings give an indication of a transition from the existing environmental-oriented system to socio-environmental context in the pursuit of sustainability. The transition could prompt more provisions and research to take social sustainability into account and move the practice towards a more balanced application of sustainable development. Acknowledgements The paper is supported by Fundamental Research Grant Scheme (project no. FRGS/1/2016/SSI11/ HWUM/02/1), provided by the Ministry of Education Malaysia.

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References Beheiry SM, Chong WK, Haas CT (2006) Examining the business impact of owner commitment to sustainability. J Constr Eng Manag 132(4):384–392 Chwieduk D (2003) Towards sustainable-energy buildings. Appl Energy 76(1–3):211–217 Dadhich P, Genovese A, Kumar N, Acquaye A (2015) Developing sustainable supply chains in the UK construction industry: a case study. Int J Prod Econ 164:271–284 Dwaikat LN, Ali KN (2018) The economic benefits of a green building–evidence from Malaysia. J Build Eng 18:448–453 Epstein MJ (2018) Making sustainability work: best practices in managing and measuring corporate social, environmental and economic impacts. Routledge Fowler KM, Rauch EM, Henderson JW, Kora AR (2010) Re-assessing green building performance: a post occupancy evaluation of 22 GSA buildings (No. PNNL-19369). Pacific Northwest National Lab: Richland, WA (United States) GABC (2016) Global status report 2016: towards zero-emission efficient and resilient buildings Gan X, Zuo J, Ye K, Skitmore M, Xiong B (2015) Why sustainable construction? Why not? An owner’s perspective. Habitat Int 47:61–68 Goh CS (2017) Towards an integrated approach for assessing triple bottom line in the built environment. Paper presented at SB-LAB 2017—International conference on advances on sustainable cities and buildings development, Portugal Goh CS, Rowlinson S (2015) Dimensions of sustainable construction: the perspectives of construction stakeholders. In: Proceedings of the 4th world construction symposium, Colombo, Sri Lanka, 12–14 June 2015, pp 224–230 GSA Public Building Service (2008) Assessing green building performance: a post occupancy evaluation of 12 GSA buildings. Retrieved 22 April 2018, from https://www.usgbc.org/Docs/ Archive/General/Docs4308.pdf Hansmann R, Mieg HA, Frischknecht P (2012) Principal sustainability components: empirical analysis of synergies between the three pillars of sustainability. Int J Sust Dev World 19(5):451– 459 Lee YS, Guerin DA (2010) Indoor environmental quality differences between office types in LEEDcertified buildings in the US. Build Environ 45(5):1104–1112 Liu Y, Wang Z, Lin B, Hong J, Zhu Y (2018) Occupant satisfaction in Three-Star-certified office buildings based on comparative study using LEED and BREEAM. Build Environ 132:1–10 Mistry V (2007) Briefing: BREEAM—making what is important measurable. Proc Inst Civ Eng— Eng Sustain 160(1):11–14 Newsham GR, Mancini S, Birt BJ (2009) Do LEED-certified buildings save energy? Yes, but…. Energy Build 41(8):897–905 Ries R, Bilec MM, Gokhan NM, Needy KL (2006) The economic benefits of green buildings: a comprehensive case study. Eng Econ 51(3):259–295 Scofield JH (2009) Do LEED-certified buildings save energy? Not really…. Energy Build 41(12):1386–1390 Takim R, Akintoye A, Kelly J (2004) Analysis of measures of construction project success in Malaysia. In: Khosrowshahi F (ed) 20th Annual ARCOM conference, 1–3 Sept 2004, Heriot Watt University. Association of Researchers in Construction Management, vol 2, pp 1123–1133 Tan Y, Shen L, Yao H (2011) Sustainable construction practice and contractors’ competitiveness: a preliminary study. Habitat Int 35(2):225–230 Thatcher A, Milner K (2016) Is a green building really better for building occupants? A longitudinal evaluation. Build Environ 108:194–206 US EEEE (n.d.) The social benefits of sustainable design. Retrieved 9 Nov 2018, from https:// www1.eere.energy.gov/femp/pdfs/buscase_section3.pdf Zainul Abidin N (2010) Investigating the awareness and application of sustainable construction concept by Malaysian developers. Habitat Int 34(4):421–426

The Impact of the University Built Environment on Students’ Mental Health and Well-Being: A Systematic Review Yuanyuan Wang, Yuyan Zhang, Xingyu Huang, Ziteng Zhou, and Marco Cimillo

Abstract Mental health and well-being of university student is critical in their academic performance, quality of life and personal growth at an important stage of their development. Among other factors, the built environment has a substantial impact, and students spend a significant part of their time in their university campus. This study reviews the relevant literature in order to synthesise the current body of knowledge and its gaps and limitations. Previous research from different fields of enquiry has demonstrated a range of effects on mental health for all the main aspects of the built environment, including its constitutive components (e.g. buildings, outdoor spaces), its spatial configuration (e.g. geometry, architecture), and its environmental characteristics (e.g. thermal, visual and acoustic factors). Furthermore, the current body of knowledge is still fragmented, lacking methodological consistency, systematisation and a specific framework for the educational spaces that can be translated in structured design guidelines. Keywords Mental health · Mental well-being · Built environment · College students · Systematic review

1 Introduction Mental health refers to a person’s overall state of emotional, psychological, and social well-being. It encompasses a wide range of factors, including one’s ability to cope with stress, maintain healthy relationships, and adapt to changes and challenges in Y. Wang Department of Public Health and Preventive Medicine, FMNHS, Monash University, Melbourne, Australia Suzhou Industrial Park Monash Research Institute of Science and Technology, Suzhou, China Y. Zhang · X. Huang · Z. Zhou Southeast-Monash Joint Graduate School, Suzhou, China M. Cimillo Design School, Xi’an Jiaotong-Liverpool University, Suzhou, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_14

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life. Good mental health is characterised by a positive outlook, a sense of purpose, and the ability to function effectively in daily life. Mental well-being, on the other hand, is a subjective experience of feeling good and functioning well in one’s life. It is a state of mind in which a person feels happy, satisfied, and fulfilled. Mental well-being can be influenced by a variety of factors, in-cluding relationships, work, and physical health. The main difference between mental health and mental wellbeing is that mental health is a broader concept that encompasses both positive and negative aspects of mental well-being. Mental well-being is a component of mental health and refers specifically to the positive aspects of mental health, such as feeling happy and fulfilled. We use the term “mental health and well-being” to examine mental health disorders and psychological distress rather than mental illness. The mental health of college students is regarded as an important public health issue (Barnett et al. 2021; Ohadomere and Ogamba 2021). When students enter university, they are at an important stage of development (Bantjes et al. 2022). During this stage, they are particularly vulnerable to increased psychological distress and mental health problems as they gradually become independent, shape values, engage in emotional regulation, develop new social connections, establish intimate relationships, and engage in career planning (Bantjes et al. 2022). Students report high level of psychological distress because of a variety of stressors such as academic pressure, personal problems, career issues, and financial problems (American College Health Association 2009). The World Health Organization’s World Mental Health Survey on mental disorders among college students revealed that 20.3% of college students experienced at least one mental health disorder in a given year (Auerbach et al. 2016). A systematic evaluation reported prevalence estimates of 6.73–0.24% for student anxiety disorders (Mortier et al. 2018). The psychological distress associated with these stressors increases as the semester progresses (Bewick et al. 2010). Recently, COVID-19 has had a profound impact on the mental health of college students. Since 2020, most schools were forced to temporaily close their campuses and implemented distance learning. Not only did the anxiety and depression symptoms of college students increase significantly, but many people also reported physical reactions such as sleep disorders, appetite problems and physical fatigue (Son et al. 2020). The research results of the American College Health Association also showed that the rapid spread of the pandemic hindered face-to-face psychological intervention, making it more difficult for students to obtain mental health care (Martinez and Nguyen 2020). When college students are on campus, space and environment concur to determine their mental state. Objective factors affecting their mental health (Wang et al. 2020), include the natural environment, the architectural design of the campus, and the design of the classrooms and dormitories. More in general, there is evidence of links between juvenile mental health and the urban environment dating back to the 1970s, as well as a substantial evidence base about the effect of the built environment on adults (Rautio et al. 2018) and childrens’ (Alderton et al. 2019) mental health and wellness. Du et al. (2022) delved deeper into a wider range of places on campus other than green and blue spaces. Asim et al. (2021) established the

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role of containment zone of built environments in the prevalence of anxiety and depression. Buttazzoni et al. (2022) examined how the built environment impacts the mental health of residents during COVID-19 lockdowns in the UK and identified design approaches that may have been previously overlooked. The systematic reviews in this field have encompassed green- space too. Song et al. (2020) validated the psychological advantages of viewing forest landscapes. Windhorst and Williams (2015) shed light on the types of natural environments that different individuals and groups find mental-health promoting. The aims of this review are to (1) assess the current state of evidence on how the spatial and environmental characteristics of campus are associated with college students’ mental health and well-being; (2) assess the quality of this evidence; and (3) identify gaps and limitations and provide suggestions for future study.

2 Methodology The research is conducted through a literature review. The first set of articles was selected among those listed in Google Scholar and Arxiv, and containing at least one keyword in each of the following sub-sets, identified after a scoping study: 1: Anxiety, Covid-19, Depression, Mental health, Mental well-being, Psychiatry, Stress; 2: Architecture, Campus, Campus outdoor, College students, Built Environment, Environment, University. The selection included studies that (a) are written in English; (b) are published in peer-reviewed journals or books from January 2012 to December 2022; (c) conduct original and empirical research relating to intervention to mental health/well-being; (d) measure built environment characteristics of the campus; e) measure outcomes relating to one or more of the following: depression, anxiety, stress, mental health or mental well-being; (e) focus on college students 18 years old and above; (f) do not exclusively focus on narrowly-defined subgroups (e.g. refugees, youth with autism disorder). Instead, The review excludes research focused on structural factors (e.g. neighbourhood socioeconomic status), life-course exposures (e.g. violence, crime and peer victimisation), and broader social processes (e.g. social capital and social cohesion). It also excludes studies addressing environmental contaminants’ role (e.g. air pollution, hazards and noise) on health. A second set of publications were selected by snowballing to extend the range of studies focused on indoor environmental quality and architectural features that were not captured by the first search. As detailed in Sect. 3, the breadth of the review scope and the range of involved disciplines and methodologies rule out a strictly quantitative and comparative analysis of the research findings. Therefore, these are illustrated with a narrative approach highlighting the main trends, commonalities and limitations in the current literature.

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3 Review and Analysis Out of the 20 studies examined, five focused on mental health outcomes such as depression, anxiety, and stress, while eight measured mental, emotional, or psychological well-being. These studies employed a variety of methods, with 20 different tools used to record and measure mental health and well-being. However, the CESD (Center for Epidemiological Studies-Depression Scale), PHQ-6 (Patient Health Questionnaire-2), and GAD-7 (Generalized Anxiety Disorder Scale) were the most commonly used tools, being employed in more than one study. Interestingly, seven studies used self-made questionnaires to collect data, which covered a range of topics such as satisfaction with the environment (Windhorst and Williams 2015), changes in daily activities due to the epidemic, spatial design preferences, and overall quality of life in relation to residential spaces and activities (Valizadeh and Iranmanesh 2022). Another study focused on feelings of isolation. Only three studies collected data on feelings and health complaints at specific times and places. It’s important to note that all of the studies relied on self-reported outcome data. The reviewed literature documented multiple findings using different research models, definitions, and key research questions. This results in significant variation between each report, and direct comparisons of the findings of these studies were not possible (Fig. 1). In these studies, it was found that 4/20 studies concluded that the natural environment on college campuses, including some green spaces and forests on campus, as well as rivers and streams, can provide a subtle influence on college students’ ability to reduce anxiety and lower their risk of depression. Lyu et al (2019). found that students rated the bamboo forest on campus highly. The freshness and tranquillity of the bamboo forest allowed college students to stroll through it during their leisure time to breathe in the fresh air and relieve their inner stress, which was instrumental in generating a positive psychology. What is more, the stress-relieving places on campus could be divided into five sections, in which both the green and blue spaces represented the natural scenery on campus, all of which played a crucial role in the development of college students’ mental health (Du et al. 2022). The cross-sectional

261 of records identified through data base searching 293 of records after screening

and duplicates removal 99 of full-text articles assessed for eligibility

Fig. 1 Study selection flowchart

8 additional records identified through other sources 194 records

20 studies included in

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study found that the difference in the degree of psychological stress relief among these five different spaces was not significant, and all of them showed positive effects. Our review concluded that the natural environment on campus plays a very important role in relieving students’ stress. Additionally, there are several implications for the design of campus building interiors on student mental health. Some studies have shown that the level of lighting in classrooms also affects students’ mental health. When students are in areas with high levels of light, they tend to be in a positive mood (Alah Ahadi et al. 2015). Therefore, the design of a classroom or dormitory balcony should ensure that it is well lit. Likewise, there are specific conditions that require different interior design. During the Covid-19 epidemic, when most schools were closed, a cross-sectional study found that a closed, isolated environment required more greenery or a place with good lighting and overlooking greenery to ease the students’ mood (Amerio et al. 2020). The review found that there was little consistency in the measurement of results evaluation, and different evaluation scales, and customised questionnaires made cross-study comparison difficult. Therefore, it would be important to standardise the measurement of the results of such research. Most studies have emphasised the importance of green space for college students’ mental health, but there is little evidence to directly study the causal relationship between green space and mental health. Moreover, confounding factors cannot be excluded. For example, when exploring the natural environment conducive to mental health, Windhorst and Williams (2015) found that symbolic factors would affect participants’ choice of natural environment; that is, all participants chose the natural place they were familiar with, linked the natural place they chose with positive childhood memory, and formed an attachment (Altman and Low 1992; Giuliani 2003). Research conducted in the architectural and engineering fields tends to focus on the impact of indoor environmental quality (IEQ) on well-being, comfort and productivity. IEQ refers to air quality, thermal, acoustic and visual comfort, including external views. Liu et al. (2023) found a strong correlation between these factors and the well-being and productivity of postgraduate students, while academic staff seem more affected by spatial factors and cleanliness. The differences between the two main groups of users highlight the importance of student consultation in campus design decisions. Granito and Santana (2016) also found that teachers underestimate the impact of the learning space compared to students. In their research, “space” is more comprehensive than just environmental comfort, and aspects like layout, furniture, technology and clutter were also found to affect psychological outcomes like concentration and engagement. A more general critical review on the impact of IEQ on comfort and well-being by Ganesh et al. (2021) confirms a strong link between thermal comfort and productivity and well-being. The study also highlights how environmental comfort, which is normally considered from a physical and physiological perspective, is significantly influenced by psychological factors, and how such nexus is under-researched. Even physical health conditions like the Building Sick Syndrome correlate to the psychological state of the occupants other than to the physical conditions of the environment. Shan et al. (2018) investigated student

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well-being and performance in university tutorial rooms, and demonstrated how accounting for these aspects (other than the classic operational costs, like energy) could produce quantifiable gains from a life-cycle costing perspective. For decades, there has been an interest also in evaluating the effects of purely architectural features. For example, Evans and McCoy (1998) identified through the “heuristic of psychological stress”, five main aspects of design (stimulation, coherence, affordances, control and restoration), although without conclusive empirical evidence of their impact. As of today, a conspicuous body of research has been produced in that direction. Numerous studies have also been investigating the psychological and neurological response to architecture measuring brain activity and other biometrics, like heart rate (Azzazy et al. 2020; Kim and Kim 2022). Such studies cast light on the mental reaction to architectural features more difficult to capture with the toolkit of the environmental comfort analysis, including aesthetic aspects such as the use of curvilinear or rectilinear geometries. More in general, the formal characteristics of the space were demonstrated to impact measurably states of mind like focus, engagement and excitement, or conditions like stress, that are directly related to well-being, mental health and productivity. Research conducted in this field, as well as the study concerned with environmental comfort and quality, suffer from the same limitations described above, i.e. the difficulty in establishing clear causality between external stimuli that are difficult to isolate, their effect on physical comfort or biometrics and the influence on mental health and well-being.

4 Conclusions This study reviewed the available literature to identify the current understanding of how space affects the mental health and well-being of university students. Limitations must be acknowledged, particularly in the limited number of publications reviewed in detail. Nonetheless, it is possible to draw the conclusions summarised below. Firstly, there is a strong consensus that a significant relationship exists and has been demonstrated from different angles. The relationship involves all aspects of the built environment, including its constitutive element (such as buildings and green spaces), its spatial configuration and functionality (e.g. geometry, architecture, activities), and its environmental characteristics (e.g. thermal, visual and acoustic factors). The effects of the composition and balance of the constitutive elements, in particular, are analysed by studies conducted from a mental health perspective (which are not limited to these aspects). They highlight, for example, the importance of the presence of green and blue spaces to mitigate stress and anxiety. Studies conducted with an engineering approach emphasise more quantitative aspects related to environmental quality and comfort and their impacts on mental well-being and performance. Studies concerned with the neurological and emotional response to spatial stimuli extend the analysis to geometric and aesthetic features, including form, colours and even architectural styles (but are not limited to these only).

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Other than synthesising the current state of the art, the analysis of the selected studies illustrates the complexity of the theme, involving several areas of research, from health science and psychology to engineering and neurosciences. Linked to this aspect, the main common limitations and gaps lie in the lack of a shared methodological framework and in the difficulties in establishing direct causality between the different characteristics of the built environment and mental health and well-being. Such shortcomings, together with the lack of a specific framework for the educational spaces, make it also challenging to translate the current knowledge into structured design guidelines. Future research in this direction would be necessary to produce a more direct impact on the spaces of higher education.

References Alah Ahadi A, KHanmohammadi M, Masoudinejad M, Alirezaie B (2015) Improving student performance by proper utilisation of daylight in educational environments (Case study: IUST1 School of Architecture). Acta Tech Napocensis: Civ Eng Archit 59(1) Altman I, Low SM (1992) Place attachment: a conceptual inquiry. Springer, US, pp 1–12 Alderton A, Villanueva K, Higgs C, Badland H, Goldfeld S (2019). The importance of the neighbourhood built environment for Australian children’s development. A report on a data linkage pilot project. Murdoch Children’s Research Institute and RMIT University American College Health Association (2009). American college health association-national college health assessment spring 2008 reference group data report (abridged). J Am Coll Health, 57(5) Amerio A, Brambilla A, Morganti A, Aguglia A, Bianchi D, Santi F, Capolongo S (2020) COVID19 lockdown: housing built environment’s effects on mental health. Int J Environ Res Public Health 17(16):5973 Asim F, Chani PS, Shree V (2021) Impact of COVID-19 containment zone built-environments on students’ mental health and their coping mechanisms. Build Environ 203:108107 Auerbach RP, Alonso J, Axinn WG, Cuijpers P, Ebert DD, Green JG, Bruffaerts R (2016) Mental disorders among college students in the World Health Organization world mental health surveys. Psychol Med 46(14):2955–2970 Azzazy S, Ghaffarianhoseini A, GhaffarianHoseini A, Naismith N, Doborjeh Z et al (2020) A critical review on the impact of built environment on users’ measured brain activity. Archit Sci Rev 64(4):319–335 Bantjes, J., Hunt, X., & Stein, D. J. (2022). Public Health Approaches to Promoting University Students’ Mental Health: A Global Perspective. Curr Psychiatry Rep 1–10 Barnett P, Arundell LL, Saunders R, Matthews H, Pilling S (2021) The efficacy of psychological interventions for the prevention and treatment of mental health disorders in university students: a systematic review and meta-analysis. J Affect Disord 280:381–406 Bewick B, Koutsopoulou G, Miles J, Slaa E, Barkham M (2010) Changes in undergraduate students’ psychological well-being as they progress through university. Stud High Educ 35(6):633–645 Buttazzoni A, Dean J, Minaker L (2022) Urban design and adolescent mental health: a qualitative examination of adolescent emotional responses to pedestrian-and transit-oriented design and cognitive architecture concepts. Health Place 76:102825 Du Y, Zou Z, He Y, Zhou Y, Luo S (2022) Beyond blue and green spaces: identifying and characterising restorative environments on Sichuan Technology and Business University Campus. Int J Environ Res Public Health 19(20):13500 Evans GW, McCoy JM (1998) When buildings don’t work: the role of architecture in human health. J Environ Psychol 18:85–94

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Ganesh GA et al (2021) Investigation of indoor environment quality and factors affecting human comfort: a critical review. Build Environ 204 Granito VJ, Santana ME (2016). 6.Granito-PsychologyOfLearningSpaces.pdf. J Learn Spaces 5(1) Giuliani MV (2003) Theory of attachment and place attachment. Na, p 137 Kim J, Kim N (2022) Quantifying emotions in architectural environments using biometrics. Appl Sci 12(19) Liu F, Alice Chang-Richards A, Wang IK, Dirks KN (2023) Effects of indoor environment factors on productivity of university workplaces: a structural equation model. Build Environ 233 Lyu B, Zeng C, Xie S, Li D, Lin W, Li N, Chen Q (2019) Benefits of a three-day bamboo forest therapy session on the psychophysiology and immune system responses of male college students. Int J Environ Res Public Health 16(24):4991 Martinez A, Nguyen S (2020) The impact of COVID-19 on college student well-being Mortier P, Auerbach RP, Alonso J, Bantjes J, Benjet C, Cuijpers P, Vives M (2018) Suicidal thoughts and behaviors among first-year college students: results from the WMH-ICS project. J Am Acad Child Adolesc Psychiatry 57(4):263–273 Ohadomere O, Ogamba IK (2021) Management-led interventions for workplace stress and mental health of academic staff in higher education: a systematic review. J Ment Health Train Educ Pract 16(1):67–82 Rautio N, Filatova S, Lehtiniemi H, Miettunen J (2018) Living environment and its relationship to depressive mood: a systematic review. Int J Soc Psychiatry 64(1):92–103 Shan X, Melina AN, Yang E (2018) Impact of indoor environmental quality on students’ well-being and performance in educational building through life cycle costing perspective. J Clean Prod 204:298–309 Son C, Hegde S, Smith A, Wang X, Sasangohar F (2020) Effects of COVID-19 on college students’ mental health in the United States: interview survey study. J Med Internet Res 22(9):e21279 Song C, Ikei H, Park BJ, Lee J, Kagawa T, Miyazaki Y (2020) Association between the psychological effects of viewing forest landscapes and trait anxiety level. Int J Environ Res Public Health 17(15):5479 Valizadeh P, Iranmanesh A (2022) Inside out, exploring residential spaces during COVID-19 lockdown from the perspective of architecture students. Eur Plan Stud 30(2):211–226 Wang M, Liu J, Wu X, Li L, Hao XD, Shen Q, Sun RH (2020) The prevalence of depression among students in Chinese universities over the past decade: a meta-analysis. J Hainan Med Univ 26:44–50 Windhorst E, Williams A (2015) It’s like a different world”: natural places, post-secondary students, and mental health. Health Place 34:241–250

Integration of Unmanned Aerial Vehicles and Infrared Thermography in Building Energy Modelling: A Review M. Jin, M. Cimillo, H. Chung, and D. Chow

Abstract The building sector is responsible for a significant portion of global energy consumption and Building Energy Modelling (BEM) is a vital tool for assessing and improving building energy performance. However, large-scale BEM is hindered by inefficiencies in modelling geometry and thermal characteristics, while Unmanned Aerial Vehicles (UAVs) and Infrared Thermography (IRT) might introduce innovative solutions. This paper aims to review these two emerging technologies from their historical origins to current applications. It summarises previous studies and current and future applications of integrated UAV and IRT in building inspection, diagnosis, and modelling. The main focus is on technologies, protocols and workflows for the generation of the building geometry and the assignment of thermal properties based on automated processes. Keywords Unmanned aerial vehicles · Infrared thermography · Building energy modeling · Integration

1 Introduction and Methodology In 2021 the operations of buildings accounted for 30% of global final energy consumption (IEA 2022), and 25% of the heating/cooling-related energy losses happen through the building envelope by transmission and air leakages (Energy and Baldwin 2015). By ratifying the Paris Agreement—COP21, most countries have committed to improving building energy efficiency and extending the lifespans of buildings. As the foundation step of renovation measures, designers and policymakers usually demand an analysis of the building’s current state. Building Energy Modelling (BEM) is an essential tool to provide insights into performance in the current situation M. Jin · M. Cimillo · H. Chung Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu, China D. Chow University of Liverpool, Liverpool, UK © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_15

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and potential future scenarios and recommend suitable retrofit measures. Considering that the EU alone plans to achieve “deep renovation of at least 35 million building units by 2030” (Cuffe 2023), the scale of the challenges ahead calls for more efficient processes and workflows. The modelling process can consume up to 40% of the total time and is typically labour and cost-intensive. Additionally, conducting onsite surveys of building roofs can be dangerous. Emerging technologies, including Unmanned Aerial Systems/Vehicles (UAS/UAV), often known as drones, and infrared (IR) cameras, might offer essential support to address these issues. UAVs provide an inexpensive and unique aerial perspective to access building roofs and avoid working at height, and they can contribute to various building surveys. Thermography has also proved helpful in detecting cracks and leakage in the building façade (Ocaña et al. 2004) and has been integrated into building energy audits. Existing studies have synthesised the applicability and utilisation of UAVs. For instance, a study reviewed various applications of UAVs in architecture and urbanism, including the combined use of photogrammetry, laser scanning, and infrared technology in the design and construction process, specifically for 3D modelling, construction site monitoring, building energy performance and damage assessments (Videras Rodríguez et al. 2021). Another research conducted a comprehensive review of the advancements made in the utilisation of UAVs and IRT in building inspection, spanning from historical developments to contemporary commercial applications (Rakha and Gorodetsky 2018). The review included an examination of onsite investigations, flight planning, and thermography model generation. Additionally, the authors presented a novel proof-of-concept study on building auditing that employed IRT and UAV. However, much of the research to date has been descriptive in terms of applicability and utilisation of UAV and failed to explicitly explore a systematic approach to integrate UAV and IRT to assist quantitative building energy modelling process at different scales. Therefore, the manuscript addresses this aim through the following objectives: (1) reviewing building energy prediction approaches from different application scales; (2) reviewing the development of UAV and IRT applications on building geometry model generation and thermal parameter collection; (3) investigating the integration of these two technologies, and identifying best practices, shortcomings, and possible future developments in the collection of input data for rapid and accurate BEM. The Web of Science was screened for relevant papers using the keyword search terms in March 2023 and resulted in 46 results, including academic journals and conference papers. The keywords are the following: (building energy modelling OR building energy simulation OR building energy consumption) AND (UAV OR UAS OR Drone) AND (thermography OR thermal imaging OR Infrared OR IRT). Additional papers were retrieved by snowballing, with relevant papers beings screened for additional relevant references.

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2 Building Energy Modelling (BEM) and Urban Building Energy Modelling (UBEM) 2.1 Scope Research (Chalal et al. 2016) classified the building energy prediction approaches based on their application scale into the building and urban ones. The engineering BEM and UBEM approach applies physical models of heat and mass flows in and around buildings to predict operational energy use. The typical workflow consists of 5 steps: (1) Input data acquisition; (2) Geometry model generation; (3) Energy model generation; (4) Simulation (5) Validation. While single buildings are modelled in detail in BEM, the modelling step is usually simplified with the help of archetypes in UBEM. Archetypes are fully characterised prototype buildings, which are selected to represent a group of buildings (Ferrando et al. 2020). Geometrical information from the 3D city model, non-geometrical information defined by building archetypes, and weather data, will be entered into a UBEM simulation engine (Johari et al. 2020).

2.2 Input Data At the BEM level, these data are needed for energy modelling: building geometry; location and weather data; occupancy schedule; energy systems, including HVAC, lighting, internal loads, and service hot water; building envelope information and actual energy consumption data, if available, for calibration and validation purposes (Hong et al. 2020). Reasonable assumptions are also acceptable. For example, envelope characteristics can be derived from the construction year and retrofit records. Referring to the purpose of retrofit measures analysis, building geometry and envelope thermal properties could also be the most essential variables.

2.2.1

Traditional Geometry Model Generation Method

When collecting input data for building energy modelling, the most direct approach involves generating a geometric model from construction drawings. However, creating a model from scratch can be time-consuming and increase costs. Furthermore, the resulting model can be inaccurate if the building plans are incomplete due to retrofits (Garwood et al. 2018). Some open-source databases are also available to provide geometry information on existing buildings. Building footprint, height, number of stories, construction year, and building type are available in the GIS database to construct 3D models in some regions. Some cities, like Berlin, Rotterdam, and New York, have 3D city models in the CitygGML format open to the public. However, especially in China,

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GIS databases and 3D City data are mainly owned by the local government, and it is complex to get the data due to privacy restrictions. Onsite surveying and mapping is another possible method to collect building geometry data. However, measuring tape and hand-held laser range finders are prone to measurement and recording errors during field surveys. Using a total station, a three-dimensional laser scanner, and close-range photogrammetry can result in higher mapping accuracy, with less measurement error due to human factors. However, the efficiency of field implementation and data processing is relatively low. Therefore, better accuracy and efficiency would produce substantial benefits.

2.2.2

Traditional Thermal Parameter Information Collection Method

Among all thermal parameters, U-value (W/m2 K) is considered critical for building energy use, as it influences the amount of heat loss or gains through the building envelope (O’Grady et al. 2017). There are four traditional methods to estimate the U-value of existing buildings (Ficco et al. 2015): (1) Estimation based on historical analysis of the building (Ballarini et al. 2014) or based on the expert’s experience; (2) Estimation based on the design data; (3) Estimation based on sampling or endoscope method; (4) In situ measurements using heat flow meters (HFMs). In summary, the current BEM and UBEM models’ main limitations are the lack of geometry and thermal information on existing buildings and the low efficiency of onsite surveying and post-processing methods to collect input data. Using UAVs and IRT can contribute to the solution of some of these issues.

3 Development and Application of UAV and IRT 3.1 UAV and IRT Development and Applications UAVs, also known as drones, are remote-controlled vehicles equipped with onboard sensors. They were developed for military use, and in the past decades, there has been a gradual shift to commercial use (Rakha and Gorodetsky 2018). UAVs are widely used now in various industries. Compared to traditional surveying and mapping methods, the UAV approach is faster, more efficient, and more cost-effective. To create a 3D model using a set of images, the Structure-from-Motion (SfM) algorithm is commonly used (Schönberger and Frahm 2016). Several commercially available software programs (e.g. Pix4D, DroneDeploy, and Agisoft Photoscan) could also be utilised for 3D reconstruction. A study that compared these programs revealed variations in the processing workflow, model production time, and output quality (Rakha and Gorodetsky 2018). The generated mesh model can be processed in other 3D modelling software, such as Rhino,

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and can be used in rendering and 3D printing. However, the mesh model could not be utilised directly as geometric input for BEM but need further processing. Similar to the UAV, thermography was initially for military purposes. IRT technology can detect and convert thermal radiation from objects’ surfaces into thermographic images. Different IRT techniques can be used to assess the thermal performance of building components. Qualitative IRT is performed by capturing thermal images of buildings using Infrared (IR) cameras, which have successfully identified material degradation, thermal bridges, and air leakages (Avdelidis and Moropoulou 2004). Quantitative IRT is applied to quantify thermal anomalies. It involves estimating heat loss indices such as the heat transmittance coefficient (U-value) using surface and indoor and outdoor air temperatures according to regulations. When IR cameras are mounted on UAVs, they have the potential to revolutionise the process of thermal assessment for buildings due to their efficiency and convenience. UAVs help streamline and partially automate building survey and provide a safe outlook into inaccessible building components compared to traditional hand-held thermal cameras. Despite the advantage of integrating IR into UAV, there are several limitations. Firstly, the limited battery life of most commercial drones, which typically last no more than 30 min, restricts their usage in large-scale surveys. Secondly, UAV operators must possess a valid license and undergo professional training, which may increase the overall costs of the assessment. Thirdly, privacy concerns may arise during residential building surveys. Concerning IRT, data obtained from the outdoor inspection is helpful for the qualitative energy audit. However, it faces limitations such as the inability to obtain indoor temperature data during urban-scale building surveys and the lack of accuracy in quantitative studies (Patel et al. 2018).

3.2 Integration in BEM The workflow integrating UAV and IRT to assist BEM and UBEM involves three main steps: pre-flight preparation, in-flight data collection, and post-flight processing. The post-flight processing is the most critical part. It can be divided into geometry model generation, thermal parameter data collection, energy model generation, energy simulation, and validation. Table 1 summarises the research incorporating technologies to assist with BEM and UBEM. This review evaluated the degree of automation and integration of the different techniques in the modelling workflow. There are several methods for generating a geometric model from the mesh representations of building envelopes. The first approach is manually tracing the building edge, extracting surfaces, and creating geometric models applicable to BEM, while the efficiency will be low if larger scale application is needed. The second method (Rakha et al. 2022) involves creating the geometric model using a custom Python module in the Rhino/Grasshopper environment. This approach takes a JSON file of the photogrammetry point cloud and outputs the necessary geometry for energy simulation in an appropriate layer structure that contains building mass geometry.

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Table 1 Summary of existing research integrating UAV and IRT. Automated steps are in Bold Scale and 3D massing photogrammetry model

Window Geometry U-Value extraction generation estimation

Energy modelling

BEM APS

Automated: Bitmap From Quantitative Energy ADE F into HSV UAV: IRT CityGML

BEM APS

Manual

Manual

Manual: Revit IFC

Heat flow meter and Qualitative IRT

BEM n/a

Existing model

Existing model

n/a

Quantitative EP IRT

BEM n/a

Existing model

Existing model

From IFC Quantitative TRNSYS to IDF IRT

BEM APS

Automated: Bitmap From TABULA F into HSV UAV: database CityGML

BEM APS

Custom ghPython

UBEM n/a

Automated: Bitmap From F into UAV: Textured CityGML wall polygons

Groesdonk et al. (2019)

DesignBuilder Etxepare (EP) et al. (2020)

TEASER

Manually Semi-auto: Quantitative Ladybug for Rhino/GH IRT Rhino (EP) ‘Random Forest’ algorithm and TABULA database

References

TEASER

Bayomi et al. (2021) Benz et al. (2021) (Groesdonk et al. 2021a) Rakha et al. (2022) Groesdonk et al. (2021b)

*

HSV—Hue-saturation-value; APS—Agisoft PhotoScan; EP—EnergyPlus; F—Frommholz et al. (2017)

Another study utilises a spatial ETL solution to reconstruct a 3D building model from a dense image-matching point cloud (Drešˇcek et al. 2020). The results are community-scale 3D building models in a semantic vector format consistent with the OGC CityGML standard, Level of Detail 2 (LOD2). Another method proposed by Frommholz et al. (2017) could be applied to both single building and urban scale and the outcome is the CityGML model in LOD3, see Fig. 1. It includes six steps: generating a 3D point cloud, digital surface model (DSM), and digital terrain model (DTM); projecting the point cloud to the ground plane to extract walls; reconstructing the roof through plane local linear regression; intersecting the DTM, walls, and roof plane patches to create 3D polygons; texturing wall and roof polygons with original RGB imagery; and recognising windows to separate walls and windows. In assessing the thermal performance of building envelopes with IRT, the calculation of U-Values by averaging radiation over the entire wall has been criticised due to the heterogeneity of surface materials. To address this issue, (Groesdonk et al. 2019) proposed two alternative methods: using the U-Value from a representative image region of the wall or taking the weighted means of the calculated U-Value for selected areas of the façade (Bayomi et al. 2021) and (Benz et al. 2021) also adopted this approach (Etxepare et al. 2020). Employed the traditional HFM method and applied

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Fig. 1 Potential workflow integrating UAV and IRT in BEM and UBEM. a Bayomi et al. (2021); b Dochev et al. (2020); Groesdonk et al. (2021b)

IRT for qualitative assessment (Rakha et al. 2022). Investigated thermal anomalies that indicate envelope defects under varying environmental conditions throughout the day and seasons of the year, and the authors translated these defects into modified envelope components resistivity. All the methods mentioned earlier conduct the IRT-based U-Value calculation manually, while (Groesdonk et al. 2021a, b) used the default value sourced from the TABULA database and automated the process. Figure 1 shows a potential workflow which integrates UAV and IRT in BEM and UBEM.

3.3 Limitation and Problems The modelling process is not yet standardised, and even the most advanced solutions still require manual intervention, particularly for data transfer across modelling steps. Additionally, the indoor temperature is necessary for quantitative IRT to estimate the facade U-Value and requires manual measurement. Most existing research focused on BEM rather than large-scale applications when IRT technology is applied, which might be due to the unavailability of indoor temperature in large-scale surveys. The most promising workflows to realise automatic modelling sourced the thermal parameters from TABULA instead of quantitative IRT (Groesdonk et al. 2021a, b). As a result, these are not applicable for regions outside of Europe, and the thermal parameters of the archetype buildings are also prone to cause a performance gap because of retrofit or material degradation. Aside from the limitation of UAV and IRT technologies mentioned before, several obstacles to the existing workflows must be considered. Firstly, generating a geometry model requires a computer with solid computing power and operators with the knowledge of algorithms and programming languages, which increases the labour cost. Additionally, no standardised workflow currently integrates these technologies to conduct building energy modelling seamlessly from preparation to onsite data collection to post-processing and simulating energy consumption. Finally, post-processing requires different software. Although some work can be automated with commercial software and algorithms, some part of the work, especially transferring data among other platforms,

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still requires manual intervention. Therefore, streamlining a standardised and automatic workflow is crucial to reducing labour costs and improving the efficiency of building energy modelling.

4 Conclusion and Future Work In the context of climate change, retrofitting existing building stocks to reduce energy consumption has become an urgent matter. To achieve this goal, it is necessary to adopt an efficient, safe, and low-cost approach to assess the energy situation of existing buildings. This research reviews various building energy prediction approaches based on the application scale, methods for collecting input data, and workflow. Specifically, the study focuses on the application of UAVs and IRT technologies, as they offer a non-destructive and efficient way to conduct onsite surveys despite some shortcomings, such as concerns about battery endurance, privacy, and the accuracy of outdoor quantitative IRT. The frameworks integrating these two technologies to conduct building energy modelling are examined. Although existing commercial software can automatically generate a 3D mesh model from photos, algorithms or customised coding could only realise the automatic massing model and geometry model generation. The entire building energy modelling process cannot yet be fully automated without manual intervention. Due to space constraints, this article does not describe collecting other input data for building energy modelling beyond generating geometry models and collecting thermal parameters. Additionally, the pre-flight preparation, flight path planning, and onsite survey processes are not thoroughly summarised. However, it is essential to note that these processes are critical components of the overall workflow for building energy modelling using UAV and IRT technologies. Researchers and practitioners should carefully plan and execute each step of the process to ensure the accuracy and reliability of the resulting energy model. Future research should build upon existing studies and investigate the potential of machine learning and computer vision to automate the post-flight processing stage of the entire workflow. It is also crucial to create detailed databases similar to TABULA for case areas, which include information about occupancy behaviour and construction materials to support the automatic process for large-scale applications. Automated methods of calculating U-Values based on IRT should also be investigated. By addressing these challenges, researchers can facilitate the adoption of efficient and cost-effective approaches to assess the energy consumption of existing buildings, contributing to efforts to combat climate change.

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Fatigue Prediction of Attached Lifting Scaffolding Guide Rails Based on Midas Gen/Abaqus Fan Fei

Abstract Attached lifting scaffolding is common equipment in the construction of high-rise buildings. The construction difficulty and construction risk of high-rise buildings are high. The strength of the guide rails of the attached lifting scaffolding determines the ability of the frame to withstand external loads and provides antioverturning function. In order to improve safety in the construction process and prevent the fatigue failure of guide rails, this paper uses the finite element software Midas Gen and Abaqus combined with the fatigue life analysis software Fe-Safe to calculate the fatigue life of the guide rail based on the Goodman fatigue damage theory. The results show that fatigue occurs when the load of each layer of the scaffolding exceeds 4.7 kN/m2 rail under the construction state, considering the wind load, and the number of fatigue is 9,581,413 times. Considering the lifting state of wind load, fatigue will occur when the load of each layer of scaffolding exceeds 3.8 kN/m2 , and the number of fatigues is 9,581,413 times, which can provide a reference for practical engineering. Keywords Scaffolding · Fatigue analysis · Finite element simulation

1 Introduction The attached lifting scaffolding is a new type of scaffolding that is installed in a highrise building, attached to the engineering structure, relies on lifting equipment and devices in the frame, moves with the engineering structure construction according to the needs, and has an anti-overturning and anti-falling device. Compared to ordinary scaffolding, linked lifting scaffolding minimizes danger, enhances mobility, and is more cost-effective in the construction of high-rise structures. However, as this new form of scaffolding has gained popularity, numerous safety accidents have occurred. The major cause of these accidents is a lack of awareness of the latest innovations and attention to safe construction. F. Fei (B) North China University of Water Resources and Electric Power, Zhengzhou, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_16

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2 Overview A large number of scholars have studied the structure and mechanical properties of the attached lifting scaffolding. Liu Guangming used ANSYS finite element software to analyze the mechanical properties of the attached lifting scaffolding under operating conditions and lifting conditions [1]. Wei Dong established a model for the study of the anti-overturning performance of the frame and carried out a mechanical analysis of the attached wall support under actual conditions [2]. Zhang Liankui carried out the actual anti-overturning load test and measured the horizontal and vertical load design values of the bearing [3]. Wang Xiuli measured the stress value of the support when the LZC10-attached lifting scaffolding rises, falls, works, and falls with a stress sensor [4]. In order to avoid the overload in the construction and cause safety accidents, this paper uses the finite element analysis software Midas Gen and Abaqus to simulate the attached lifting scaffolding, analyze its mechanical properties, analyze the most dangerous parts of the frame, and use the fatigue analysis software Fe-safe. The most dangerous parts are modeled, and the fatigue load and fatigue times of the frame are obtained by adjusting the load multiple, which provides references for practical engineering applications.

3 Finite Element Simulation of the Attached Lifiting Scaffolding Midas Gen software was used to construct the model of the attached lifting scaffolding for finite element analysis. The outer row height of the attached lifting scaffolding frame is 14.2 m, the inner row height is 13.4 m, the width is 0.6 m, the horizontal span is 10 m, the vertical rod spacing is 2 m, and the height step distance is 1.9 m. The finite element software Midas Gen is used to model, and the rigid connection is used to simulate the bolt connection. The attached lifting scaffolding frame uses Q235 steel. The material parameters are shown in Table 1, the section size of the frame is shown in Table 2, and the finite element model is shown in Fig. 1. Table 1 Model material parameters Material

E/GPa

μ

ρ/kg·m−3

[σ]/MPa

Yield strength/MPa

Q235

201

0.3

7800

205

235

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Table 2 Frame section size Categories

Section types

Sectional sizes/mm

External vertical poles

Rectangular steel tubes

40 × 80 × 3

Cross bars

Rectangular steel tubes

60 × 30 × 3

Horizontal support truss cross bars

Rectangular steel tubes

63 × 40 × 4

Horizontal support truss web members

Rectangular steel tubes

50 × 50 × 3

Sway struts

Rectangular steel tubes

38 × 25 × 3

Guide rails vertical poles

Circular steel tubes

ϕ52 × 3

Guild rails cross bars

Circular steel tubes

ϕ32 × 3

Z-type supports

Circular steel tubes

ϕ25 × 3

Fig. 1 Frame finite element model

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4 Load Application and Load Combination The load of the attached lifting scaffolding is mainly divided into constant load, live load, and wind load. The constant load is the weight of the whole frame structure, and the live load includes the weight of construction personnel, equipment, and material.

4.1 Constant Load The weight of the frame can be automatically calculated according to the structural material in Midas Gen, and the weight of the electric hoist is applied to each 1000 N, and the node force is applied to the frame [5].

4.2 Live Load According to the Safety Technical Specification for Construction Tool scaffolding, different live loads are applied to the frame according to different working conditions, as detailed in Table 3. Table 3 Construction load Working-state classes

Number of working layers

Live Remarks load value of each layer

Operating conditions

Structural construction

2

3.0

Decoration construction

3

2.0

Structural construction

2

0.5

All construction personnel, materials and machinery were evacuated

Decoration construction

3

Structural construction

2

0.5; 3.0

When falling under working conditions, the instantaneous standard load is 3.0 kN/ m2 ; the falling standard value under lifting condition is 0.5 kN/m2

Decoration construction

3

0.5; 2.0

When falling under working conditions, the instantaneous standard load is 2.0 kN/ m2 ; the falling standard value under lifting condition is 0.5 kN/m2

Lifting conditions

Falling conditions

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4.3 Wind Load The wind load is calculated according to Formula (1) [6]: Wk = βz μs μz W0

(1)

In the Formula, wind vibration coefficient βz is 1.0; the body shape coefficient μs = 1.3ϕ (ϕ is 0.985), and the height change coefficient μz is 1.5 (take the C area, high-rise buildings with the height of 100 m). Operating conditions: Wk = 1.0 × 1.3 × 0.985 × 1.5 × 0.45 = 0.864 KN/m2 . Lifting and falling conditions: Wk = 1.0 × 1.3 × 0.985 × 1.5 × 0.30 = 0.576 KN/m2 . Because this model only considers the stress of important components, it does not model and analyze the protective net. For the convenience of calculation, it is simplified to the line load applied to the outer pole, which is 0.144 and 0.096 N/mm by equivalent calculation.

4.4 Load Combination According to the provisions of JGJ202 Article 4.1.7, the design load value of the power equipment, spreader, sling and main frame on the attached lifting scaffolding should be multiplied by the additional load non-uniformity coefficient γ2 = 1.3 under the working conditions of the use. In the lifting and falling conditions, the design load should be multiplied by the additional load non-uniformity coefficient γ2 = 2.0, the constant load partial coefficient γG is 1.2, and the live load partial coefficient γQ is 1.4. The combined load is divided into two cases: (1) frame constant load + frame live load (2) frame constant load + 0.9(frame live load + wind load). Under operating conditions, combination 1: ( ) ( ) S = γ2 γG SGK + γQ SQK = 1.3 1.2SGK + 1.4SQK Under operating conditions, combination 2: ( ( )) ( )) ( S = γ2 γG SGK + 0.9γQ SQK + SWK = 1.3 1.2SGK + 0.9 × 1.4 SQK + SWK Under lifting and falling conditions, combination 3: ( ) ( ) S = γ2 γG SGK + γQ SQK = 2.0 1.2SGK + 1.4SQK

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Under lifting and falling conditions, combination 4: ( ( )) ( )) ( S = γ2 γG SGK + 0.9γQ SQK + SWK = 2.0 1.2SGK + 0.9 × 1.4 SQK + SWK

4.5 Constraint Application Under the operating conditions, according to the actual construction situation, six bearings are set at the corresponding position of the attached lifting scaffolding guide rails, and the degree of freedom is all constrained; under the lifting condition, the temporary removal of the attached wall bearings is simulated, and the two bearings at the lowest level are removed. Only four bearings are set at the corresponding position of the guide rails to constrain the corresponding degree of freedom, and the degree of freedom in the Z direction is constrained at the lower lifting point [7].

5 The Finite Element Model Calculation Results and Analysis 5.1 Operating Conditions 5.1.1

Combination 1

From Figs. 2 and 3, it can be seen that the deformation of the frame is S-shaped, the maximum combined displacement occurs at the top of the frame, and the displacement is 7.95 mm; the maximum stress of the climbing frame is 104.68 MPa, which is located at the lower guide rails, and the maximum stress of the footplate is 5.74 MPa, which meets the requirements.

5.1.2

Combination 2

From Figs. 4 and 5, it can be seen that the whole frame body deforms to the inside, and the maximum combined displacement occurs at the top of the frame body, with the displacement of 8.06 mm; the maximum stress of the climbing frame is 112.51 MPa, which is located at the upper guide rails, and the maximum stress of the footplate is 4.7 MPa, which meets the requirements.

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Fig. 3 Combination 1 scaffolding combination stress

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178 Fig. 4 Combined 2 scaffolding deformation

Fig. 5 Combination 2 scaffolding combination stress

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Fig. 6 Combined 3 scaffolding deformation

5.2 Lifting Conditions 5.2.1

Combination 3

From Figs. 6 and 7, it can be seen that the frame body deforms outward as a whole, and the maximum combined displacement occurs at the bottom of the footplate, with a displacement of 9.51 mm; the maximum stress of the climbing frame is 108.82 MPa, which is located at the upper guide rails, and the maximum stress of the footplate is 5.35 MPa, which meets the requirements.

5.2.2

Combination 4

From Figs. 8 and 9, it can be seen that the overall deformation of the frame body is S-shaped inward, and the maximum combined displacement occurs in the lowermost footboard, with the displacement of 16.29 mm; the maximum stress of the climbing frame is 159.18 MPa, which is located at the upper guide rails, and the maximum stress of the footplate is 7.73 MPa, which meets the requirements.

180 Fig. 7 Combination 3 scaffolding combination stress

Fig. 8 Combined 4 scaffolding deformation

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Fig. 9 Combination 4 scaffolding combination stress

6 Summary of the Finite Element Model According to the above model, it can be found that the scaffolding guide rails is the main bearing component; in the case of considering the wind load, the maximum combined stress under the operating conditions is basically the same as that without considering the wind load, and the maximum combined stress under the lifting conditions is 31.64% higher than that without considering the wind load. Under working conditions, it is necessary to take into account the dangerous state of overturning that may be brought about by wind load. Therefore, only combination 2 and combination 4 under wind load are considered, and the model of the guide rails is established by Abaqus finite element software for fatigue life analysis.

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Fig. 10 Finite element model of the guide rail

7 Fatigue Life Analysis of Guide Rails 7.1 Establish the Finite Element Model of Guide Rails Based on Abaqus 7.1.1

Modeling

The model of the guide rails is constructed by Abaqus finite element software. The mesh is defined as 10 mm by Mesh. The quad shape and medial axis algorithms are selected to select the overall model, and the software is used for automatic meshing. The overall model is selected, and the material properties of the unit Q235 steel are given, as shown in Figs. 10 and 11.

7.1.2

Constraints Imposed

This paper mainly analyzes the fatigue life of the guide rails in the construction state and the lifting state under the conditions of wind load. Therefore, the position and degree of freedom are applied according to the constraints on the model established by Midas Gen, and the same constraints are applied to the guide rails model. For the construction state, the constraints of the three attached supports are applied and all the degrees of freedom are constrained; for the lifting state, the constraints of two attached supports are applied and the corresponding degrees of freedom are constrained.

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Fig. 11 Rail mesh division

7.1.3

Loading

Because the live load is the decisive factor for the fatigue life of the guide rails, the influence of the weight on the guide rails is not considered, and only the live load is applied to the guide rails. The construction load is applied where the frame is in contact with the guide rails, and the horizontal wind load is applied.

7.1.4

Rails Stress Analysis

From Figs. 12 and 13, it can be seen that the maximum stress of the guide rails is 47.82 MPa under the lifting condition, and the maximum stress of the guide rails is 71.85 MPa under the operating conditions. The maximum stress does not exceed the allowable value of the material, so the model of the guide rails is reasonable.

7.2 Fatigue Life Curve of Guide Rails Based on Fe-Safe The Abaqus finite element model is imported into the fatigue analysis life software Fe-Safe, and the fatigue damage theory is the theoretical basis for calculating the fatigue life of the guide rails. When the guide rails is subjected to a load higher than its fatigue limit, it will be damaged with every load cycle. When this damage accumulates to a critical value with the increase in load cycles, fatigue failure will occur [8]. In this paper, the Goodman formula is used to modify the results, and only the live load is considered. The fatigue number-stress curve is shown in Figs. 14 and 15.

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Fig. 12 Rail stress under lifting and falling condition

Fig. 13 Rail stress under operating condition Fig. 14 Combination 2 fatigue times-stress curve

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Fig. 15 Combination 4 fatigue times-stress curve

After the construction load exceeds the limit value, the fatigue life of the guide rails decrease sharply. In order to avoid fatigue damage to the guide rails, the stress should not exceed 3.8 kN/m2 under lifting conditions with two layers of scaffolding as the bearing layer, and the number of fatigue is 9,581,413. Under the operating conditions, the stress should not exceed 4.7 kN/m2 when the two-layer scaffolding is used as the bearing layer, and the number of fatigue is 9,645,937.

7.3 Strength Calculation of Attached Support According to the anti-tilting, anti-falling, and jacking tests of the attached bearing measured by Zhang Liankui, considering the impact coefficient of 2 times the load, the horizontal design load of a single bearing should be controlled below 24 kN, and the vertical design load of a single bearing should be controlled below 50 kN [3]. Through the model built by Midas Gen, the construction load multiple is expanded. The construction load is set to 4.7 kN/m2 in combination 2, and the construction load is set to 3.8 kN/m2 in combination 4. The vertical load of each bearing is observed to be less than 6.2558 kN and 10.6839 kN from Figs. 16 and 17. The maximum design load is not exceeded, and the analysis is reasonable. The Horizontal load of each bearing is observed to be less than 7.3969 kN and 9.0883 kN from Figs. 18 and 19. The maximum design load is not exceeded, and the analysis is reasonable.

186 Fig. 16 Vertical load of combination 2 support

Fig. 17 Vertical load of combination 4 support

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Fig. 19 Horizontal load of combination 4 support

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8 Conclusion In summary, the finite element software Midas Gen and Abaqus are used to analyze the attached lifting scaffolding and guide rails. The force of the frame lifting and construction under the conditions of wind load and the maximum load of the guide rails are studied. The main conclusions are as follows: (1) The most unfavorable position of the frame is located on the small crossbar of the guide rails, which can optimize the material or structure of the guide rails and increase the reliability of the frame. (2) In the process of climbing frame lifting, due to the effect of the lower lifting point, the displacement of the lower scaffolding is large, and the area should be reinforced. (3) Compared with applying load during the construction process, the number of fatigue times decreases more during the lifting process of the frame. It should be avoided that materials and personnel stay in the frame during the lifting process.

References 1. Liu G et al (2021) Static finite element analysis of the attached lifting scaffolding. Shanxi Build 47(16):7–10 2. Mechanical analysis and experimental comparison of the attached lifting scaffold structure between Wei Dong and He Lile (2021). Build Mech 42(12):22–25 3. Zhang L (2021) Bearing capacity test and numerical analysis of attached lifting scaffold. Xi’an University of Architecture and Technology 4. Xiuli W, Jian C, Tao Z (2020) Applied research on new steel structure attachment joints of the attached lifting scaffolding. J Shenyang Jianzhu Univ (Nat Sci Ed) 36(02):273–281 5. Hu D (2021) Finite element analysis and test comparison of horizontal support trusses of the attached lifting scaffolding. Constr Mach Technol Manag 34(04):93–95 6. GB50009-2012, Load code for building structures 7. Xin W (2022) Simulation analysis of the aluminum alloy attached to lifting scaffolding in engineering. Sci Technol Innov Appl 12(16):32–36 8. Li H (2010) Strength and fatigue life analysis of cylindrical helical springs based on ANSYS. Mech Des Manuf 10:92–93

Circular Economy and Sustainable Development

Research on Energy-Saving Technology of High Efficient Recycling and Ladder-Form Utilization of Midand Low-Temperature Waste Heat in Large Hospital Jun Luo, Quan Wang, and Dong Zhang

Abstract Large hospitals need a large amount of steam every day as a heat source for high-temperature disinfection or heat exchange with domestic water. However, after steam is used once, it is rarely reused. Although there are some open or semi-open condensate water recovery systems, system defects lead to a large amount of steam condensate contaminated and disposed of as waste water, which eventually results in enormous waste of water resources and the heat in steam and condensate water. Therefore, there is great potential for cost savings and technological renovation in this area. In order to improve energy efficiency, recycle wasted heat and high-quality softened water resources, and achieve the re-utilization of condensate water in the system, the project designed an efficient steam cascade utilization system, which allows for the multi-stage utilization of medium and low temperature steam under different heat loads, achieving a seamless all-weather connection between the heating system and the heat utilization system in terms of supply and demand, start and stop, so that high quality softened water resources can be reused and heat can be recovered. All of these efforts are essential for energy conservation, environmental protection, and the implementation of circular economy and sustainable development. Keywords Energy-saving technology · High efficient recycling · Waste heat

1 Introduction Hospitals, as specialized institutions and service places to provide medical services, need to accommodate as well as treat a large number of patients, providing them with comfortable and clean resting places and therefore, there is a strong demand for hot J. Luo · Q. Wang NO.7 Construction Group Corporation of Gansu Province, Lanzhou, Gansu, China D. Zhang Lanzhou University of Technology, Lanzhou, Gansu, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_17

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water. At the same time, in order to meet the needs of high-temperature disinfection, hospitals generally use high-temperature steam generated by steam boilers as a heat source for high-temperature disinfection or for heat exchange with domestic water, providing hot water for patients and medical staff. However, after the steam is used once, it is rarely recycled. Although there are some open or semi-open condensate recovery systems, due to system defects, a large amount of steam condensate is contaminated and can only be discharged as waste water, which causes great waste of both water resources and the thermal energy contained in steam and condensate. Therefore, there is great potential for both cost savings and technological improvements.

2 Survey and Problem of Steam Heating and Disinfection System in a Large Hospital The disinfection and heating system used by a large hospital is mainly composed of steam boilers, steam disinfection equipment, heat exchange systems, condensate collection tanks and other systems. Steam is mainly supplied to the disinfection room of Building 1 and the water pump room of Building 2 as a medium for domestic hot water system. The condensate of the loop is collected in the condensate collection tank and can be used for boiler make-up water. After the system was put into operation, it has not been working properly since the condensate cannot be discharged automatically. The discharge valve of the drain valve must be opened manually to make the hot water system operate properly. After the steam condensate system operates normally, the condensate collected in the underground condensate collection tank is red and has a rusty smell, causing the boiler room to refuse to receive it and can only discharge it as waste water. Through a comprehensive investigation of the system and its operation status, it was found that the system is an open layout with a simple and clear structure, low technical content, and low energy utilization. The main cause of the problem is the defects within the system itself and the non-standard operation by humans, manifested in the following three problems: (1) In general, steam system of hospitals continuously operates for 24 h, while the steam disinfection equipment in hospitals does not. Large hospitals have morning and evening shifts, and medium-sized hospitals have 2–3 times a week. The other steam is mainly responsible for heating in the ward and living area, but due to the unstable usage, although a large amount of steam and condensed water are recycled into the condensate recovery tank for boiler make-up water, there is still a large amount of heat loss. (2) The hot water in the hospital is used at night. In order to ensure safety, the hot water in the ward area is turned off. In addition, the hot water in the other parts of the building is turned off after work in the afternoon. The actual use of hot water per day is much lower than the design value, and there is a considerable

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difference between the use and design conditions. Therefore, nine electric regulating valves installed in the steam inlet of the nine volume exchange heaters were closed because the steam condensed in the pipeline due to low circulation. (3) The pipe system of the open condensate water recovery system is connected to the air. After entering the air, it is prone to pipe rust, so the condensed water is contaminated and turns red, causing the boiler room to refuse to recycle, and causing a large loss of condensed water. This is very high-quality soft water, and the cost of softening water is also relatively high in the northwest region, which will cause serious waste of water resources and heat [1].

3 System Repair After preliminary research and demonstration, our company has carried out effective technical transformation on the central air-conditioning system of Gansu Telecom Second Hub Project, The First Hospital of Lanzhou University and Longneng Hotel. The recovery of condensate, as the final part of the system, should be approached in two ways in order to achieve proper operation: (1) Replace the steam trap and condensate automatic recovery device with low leakage and long service life, such as Armstrong’s steam trap (leakage rate is only 3‰) and condensate automatic recovery device [2]. (2) Filter out rust from condensate. The iron content and turbidity of the condensed water exceed the standard and contain impurities during operation. If it is directly returned to the boiler system without treatment, it will easily cause scaling, corrosion, and other problems of thermal equipment, which is the main cause of boiler accidents and economic losses. Therefore, strict control of the iron ion content in the water is necessary to prevent boiler corrosion. In order to remove iron from the condensed water, a fully automatic manganese sand filter was installed. The filter material is divided into three layers from top to bottom: (a) Quartz sand filter layer with a thickness of 300 mm, mainly filtering large particles impurities in the water; (b) Manganese sand filter layer with a thickness of 300 mm, mainly filtering iron ions and iron salts in the water; (c) Activated carbon filter layer with a thickness of 400 mm, mainly filtering some organic matter and salts in the water with the function of decolorization and deodorization. This filter system, easy to operate, is a pure physical process, which does not consume acid and alkali with no waste acid and alkali discharge. With these measures, the system has basically restored normal operation.

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4 Improve the Thermal Efficiency of the System After studying the principle and operation status of the existing system, the cause of the problem was identified, and effective measures were taken to restore the normal operation of the system. However, faced with a large amount of waste heat and high-quality soft water being discharged, it is hoped to further improve the thermal efficiency of the system. Therefore, a solution for high-efficiency recovery and stepwise utilization of medium and low temperature waste heat is proposed, and an efficient steam cascade utilization system is designed to achieve multi-stage utilization of medium and low temperature steam under different thermal load conditions. The system also recycles and reuses condensed water, reducing the energy consumption of hospital heating systems and enabling both the reuse of high-quality softened water resources and the recovery of heat. The specific plan of the system is as follows: The steam condensate water cascade utilization system includes a boiler system, disinfection equipment, the inlet for living areas, condensate recovery tank, water pump room, manganese sand filter, and cascade heat transfer system. The boiler system supplies heat to the disinfection equipment and the inlet for living areas through pipelines. The cascade heat transfer system includes a volumetric heat exchanger and steam-water plate heat exchanger, in which the thermal inlet of the volumetric heat exchanger is connected to the boiler system, the thermal outlet is connected to the thermal inlet of the steam-water plate heat exchanger, the thermal outlet of the steam-water plate heat exchanger is connected to the condensate recovery tank, and a manganese sand filter is set between the condensate recovery tank and the boiler system. The cold inlet of the steam-water plate heat exchanger is connected to the water pump room, the cold outlet of the steam-water plate heat exchanger is connected to the cold inlet of the volume heat exchanger, and the cold outlet of the volume heat exchanger is connected to the living end. The first two stages of heat utilization are realized. The cascade heat transfer system also includes a water-water plate heat exchanger. The thermal inlet of the water-water plate heat exchanger is linked to the condensate recovery tank, and the thermal outlet is connected to the manganese sand filter. The cold inlet of the water-water plate heat exchanger is connected to the water pump room, and the cold outlet is connected to a heat storage water tank. The third stage of heat utilization is realized. To further improve the efficiency of heat utilization, a water-source heat pump can be installed in parallel in the cascade heat transfer system. The thermal inlet of the water-source heat pump is connected to the thermal outlet of the water-water plate heat exchanger; the thermal outlet of the water-source heat pump is connected to the manganese sand filter; the cold inlet of the water-source heat pump is linked to the water pump room; the cold outlet of the water-source heat pump is connected to the heat storage water tank. The fourth stage of heat utilization is achieved. The system for high-efficiency recovery and stepwise utilization of medium and low-temperature waste heat is shown in Fig. 1:

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Fig. 1 The system diagram for high-efficiency recovery and stepwise utilization of medium and low-temperature waste heat

5 The Beneficial Effects of the System This system mainly targets the situation where the steam used in the hospital’s disinfection and sterilization steam system is unstable but the gas supply is constant, especially in the case where the supply of steam to the living end and disinfection equipment is not separated and the cost of separation and transformation is extremely high with insufficient budget. Under these special limitations, the closed condensate recovery system is used to replace the open system. On the one hand, the steam (soft water) is in a closed loop, air is not easily entered, rust is reduced, and the overall recycled water cleanliness is improved. The use of a manganese sand processor for purification ensures the recovery and utilization of soft water, and also reduces the purification load of manganese sand processors. On the other hand, all steam is recycled into soft water, thereby completely solving the problem of wasting water resources. Without wasting water resources, the problem of hot water discharge can be dealt with fundamentally. The recovery and utilization of heat are carried out in stages. The direct cooling water in the water supply pump room is preheated first, while the cooled steam is cooled. During the secondary heat exchange, the excess disinfection steam is cooled while the preheated water in the water supply pump room is reheated and supplied to the living end.

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The structure of this system is relatively simple. Compared to the independent steam supply systems for the inlet for living areas and disinfection equipment, its cost is extremely low. It has practical significance for the renovation of similar steam systems in medium-sized hospitals in Gansu province and even across the country. Even in other industries, the use of similar situations is unobstructed, and the system has strong practicality and applicability.

6 Conclusion The recycling of steam condensate effectively saves water resources, improves the quality of the water supplied by the water softening equipment, greatly alleviates the corrosion of heating equipment and pipe networks, and extends the service life of them. Effective recovery of the excess heat of medium and low-temperature steam and condensate utilization improves the reuse rate of energy. Energy-Saving technology for efficient stepwise utilization of Medium and lowtemperature waste heat actively promotes green manufacturing, energy conservation and emission reduction, completes two goals set for technology development, and strives to build a resource-saving and environmental-friendly society, thus reducing the pollution and destruction caused to the environment and establishing a good social image.

References 1. Yang J, Yang Y, Wang MT, Wang L (2004) Recycling and utilization of steam condensate. Energy Conserv Technol 22(1):33–84 2. Liu JM, Zhao Y, Ye JD (2010) Recovery and utilization of steam boiler condensate. China Water Wastewater 26(2):80–82

Drivers of Circular Economy Adoption in the South African Construction Industry O. K. Otasowie, C. Aigbavboa, P. Adekunle, and A. Oke

Abstract The take-make-dispose approach, which is linear in nature, still drives the building sector. A change in thinking is necessary because of the relatively considerable negative environmental effects of this approach. If the principles are followed in the sector, circular economy (CE) has been viewed as a strategy that might result in ecologically sustainable development. However, as a significant approach in emerging economies development, it is expedient the driving forces of the CE approach are recognized and comprehended. Hence, this study examines the drivers of circular economy adoption in the South African (SA) construction industry. A survey method was selected. Ninety (90) of the one hundred and thirtyfive (135) questionnaires that were sent to construction industry professionals in Guateng Province, South Africa, were returned and deemed appropriate for study. One-sample t-tests, Kruskal–Wallis, standard deviation, percentage, and mean item scores were used to analyze the collected data. The findings reveal the significant drivers of CE in SA construction industry which are regulations and policies on CE, incentives to customers, Stakeholders’ pressure and enabling infrastructure. This finding could inform construction stakeholders in the country on the drivers of CE and these highlighted drivers must motivate relevant parties to take considerable action on them in order for the SA construction sector to profit from this crucial strategy. Keywords Drivers · Circular economy · South African · Construction industry

1 Introduction The building sector is regarded as a major contributor to a country’s economic and social growth (Baloi 2003). However, construction activities are neither natural nor environmentally beneficial, and they contribute significantly to environmental issues O. K. Otasowie · C. Aigbavboa · P. Adekunle · A. Oke Faculty of Engineering and the Built Environment, Cidb Centre of Excellent and Sustainable Human Settlement and Construction Research Centre, University of Johannesburg, Johannesburg, South Africa © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_18

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such as air pollution, noise pollution, and water pollution (Shen et al. 2017). Ellen MacArthur Foundation (EMF) (2015) opined that the linear economic paradigm being adopted in the building industry has caused severe environmental issues. These environmental issues arise from the “take-make-use-dispose” concept which underpins the linear economic paradigm. The implication of this concept is that raw materials are extracted from the environment, processed into construction goods, and employed in ways that preclude deconstruction, finally become waste after the endof-life phase of the building. As a result of the above, the circular economy is gaining a lot of traction in the construction sector globally, intending to move from the linear economic paradigm of “take-makes-use-dispose” to the circular economic paradigm of “make-use-return”. The circular economy emphasizes the preservation of natural resources for future use, the reduction of energy consumption in industries, and the reduction of demolition waste. Velenturf and Purnell (2017) opined that employing the circular economy practices has the potential to reduce carbon emissions while improving resources and energy efficiency. This stand was further corroborated by Bherwani et al. (2022). Circular economy is promoted as a low-cost practice of converting resources into materials that may be utilized in other products and processes (Preston 2012). Likewise, EMF (2013) defined circular economy as a way for maximizing the value of time performance and usefulness of things, materials, and components. This viewpoint agrees with the claim of Mitchell and James’ (2015) that circular economy increases resource efficiency by increasing the value of materials and products after their average useful lifespan. The notions of the circular economy span a broad variety of topics, including but not limited to; the use of materials, improving planning and design processes, and implementing new environmentally friendly technology (EMF 2015). Kirchherr et al. (2017) described circular economy as a method for rejecting the total end-of-life in favor of a system that encourages reuse by lowering, recycling, and recovering resources throughout the distribution, manufacturing, and consuming processes. According to Geissdoerfer et al. (2017), circular economy is a process that maximizes raw material consumption while minimizing emissions and waste production via remanufacture, repair, reuse, refurbishing, and recycling. Given that the building industry consumes the most natural resources and generates the most waste, adopting circular economy principles is critical (Norouzi et al. 2021). The construction sector attracts a lot of attention since it uses a lot of resources and energy and has a significant environmental impact (Ge and Gao 2008). Du Plessis (2002) opined that the construction industry has a particularly harmful environmental impact in developing nations such as South Africa. This is owing to emerging economies’ continuous construction activities. Yeheyis et al. (2013) posited that the construction industry creates a quarter of the world’s solid waste particularly at buildings end-of–life phase, with South Africa creating more due to the linear economic model’s adoption. As a result, the circular economy paradigm has gained significant popularity (Pomponi and Moncaster 2017) in recent years. Through a variety of studies, the EMF (2015) has promoted the principles and possibilities of the circular economy, which it defines as a cycle of continuous improvement aimed at keeping resources in a circular path at their value. However, as a significant approach in

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emerging economies development, it is expedient the driving forces of the circular economy approach are recognized and comprehended. Hence, this study examines the drivers of circular economy adoption in the South African (SA) construction industry.

2 Methodology The study took a post-positivist approach in terms of philosophy, employing quantitative research that was carried out using a questionnaire survey. The questionnaire was divided into two segments, with the first segment intended to elicit background data from the respondents. The second segment tried to address the drivers of circular economy. The respondents, who are construction professionals were requested to rate the significance of the drivers of circular economy in South African construction industry using a 5-point Likert scale, with 5 being Strongly significant, 4 being significant, 3 being moderately significant, 2 being slightly significant, and 1 being not significant. The study population were made of qualified construction professionals (engineers, architects, quantity surveyors and construction managers) who are working in Guateng Province, South Africa and had at least five years of work experience. Due to time and financial restrictions, convenience sampling was used for the study. One hundred and thirty-five (135) questionnaires were sent out to the construction professionals and ninety (90) were received and considered appropriate for investigation. One-sample t-tests, standard deviation, percentages, mean item scores, and Kruskal–Wallis tests as adopted by Otasowie and Oke (2022) were used to analyze the collected data. Using the Cronbach’s alpha test, which yielded an alpha value of 0.840, the study validated the questionnaire’s validity and reliability. Given that the alpha score is over the cutoff point of 0.6, confirms the questionnaire’s high degree of reliability (Tavakol and Dennick 2011).

3 Result and Discussion Professionals from South Africa’s Gauteng Province participated in the survey. The profession with the most involvement (28%) is quantity surveyors. Following are engineers (22%), architects (20%), construction managers (18%), and project managers for construction (12%). The majority of these respondents (65.2%) hold bachelor’s degrees, while the next highest levels of education are masters, doctoral, and certificate degrees, respectively, with 14.5%, 13.4%, and 6.9%. The total number of respondents had an average working history of 8.4 years, which is a remarkably long period of time in the field. These findings suggest that the study’s target respondents, who were construction professionals, were fairly represented and that they had a sufficient degree of education to comprehend the study’s questions (Otasowie

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and Oke 2022). Also, the answers to these queries were based on a large amount of professional expertise. A one sample t-test was employed to evaluate whether the respondents viewed a certain driver to be important or not. The mean rank for every driver was tabulated to give a thorough assessment of the respondents’ views. The significance level was established at 95% in accordance with the customary threshold (Otasowie and Oke 2020), and a driver was deemed significant if it had a mean of 3.5 or above on the five-point Likert scale for rating. When two or more drivers had the same mean, the driver with the lowest standard deviation received the highest priority ranking (Field 2005). The drivers of circular economy adoption are shown in Table 1. According to the p-value of each driver, the respondents agreed that the listed drivers of circular economy adoption are significant in the building sector in South Africa. For each driver, there was a null hypothesis stating that the outcome was not significant (H0: U = U0) and an alternative hypothesis stating the outcome was significant (Ha: U > U0), wherein U0 is the population mean (3.5). Hence, the null hypothesis was rebutted. In Table 2, the observed data mean is shown by the standard deviation. While a large standard deviation shows that the data point is considerably distant from the mean, a low standard deviation suggests that most data are close to the mean (Field 2005). The standard deviations are smaller than 1.0, demonstrating the consistency of the data and respondents’ perceptions of the drivers of circular economy adoption (Field 2005). The study reveals the respondents’ rankings of drivers to adopting circular economy in South Africa. Based on Table 2, regulations and policies on circular economy ranked first with a mean score of 4.59 and (SD) = 0.458. This finding concurs with Khan et al. (2021) about the significance of the role played by the government through regulation policies in ensuring that manufacturing companies’ production processes are clean and do not harm the environment. Financial incentives to use of secondary materials ranked second with a mean score of 4.49 and (SD) = 0.469. According to Chen et al. (2022), financial incentives are a significant driver for industry partners to engage in circular building, especially among small to medium-sized businesses (SMEs), because replacing technical infrastructure and services requires capital. Kanters (2020) posited that just a small number of banks are prepared to offer a small loan to assist creative circular economy projects that take use of the residual value of construction materials at the end-of-life. Stakeholders’ pressure ranked third with mean score of 4.47 and (SD) = 0.471. Liu et al. (2018) defined stakeholder as “any group or individual who can affect or is affected by the achievement of the organization’s objectives”. From a management perspective, stakeholders’ involvement and engagement are important channels that are viewed as a transactional process to meet the demands of diverse stakeholder groups. Both internal and external stakeholders can play important roles in the adoption of a circular economy approach in the construction industry. Pressure from stakeholders in the construction industry will drive the circular economy concept. Other drivers identified from literature and considered significant drivers include construction of a reverse

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Table 1 One-sample test for drivers of circular economy adoption 95% confidence interval of the diff Drivers

T

Df

Sig. (2-tailed)

Mean Diff

Lower

Upper

Whole Life Costing (WLC)

4.914

89

0.001

0.661

0.814

0.978

Value of the raw materials or finished goods

4.378

89

0.000

0.635

0.732

0.921

Value chain management

4.078

89

0.000

0.624

0.713

0.881

Tools and tactics for collaboration and design

4.210

89

0.000

0.631

0.728

0.896

Stakeholders’ pressure

8.986

89

0.000

0.755

1.002

1.109

Regulations and policies on CE

14.643

89

0.000

1.016

1.089

1.204

Knowledge sharing 4.966

89

0.000

0.682

0.856

0.988

Improved understanding of CE in the built environment

4.447

89

0.000

0.647

0.742

0.937

Financial incentives to use secondary materials

12.018

89

0.000

0.796

1.013

1.118

Development of secondary marketplaces with higher value

4.678

89

0.000

0.651

0.753

0.961

Development of material recovery-enabling technologies

4.807

89

0.000

0.655

0.774

0.964

Design tools and guidance

4.012

89

0.000

0.601

0.705

0.875

Creation of standards and assurance programs

5.943

89

0.000

0.715

0.912

1.101

Construction of a reverse logistics infrastructure

6.163

89

0.002

0.716

0.942

1.104

Campaign to raise awareness

5.015

89

0.000

0.692

0.877

0.995

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Table 2 Summary of t-test for drivers of circular economy adoption Drivers

Rank

MEAN

SD

Regulations and policies on CE

1

4.59

0.458

Financial incentives to use secondary materials

2

4.49

0.469

Stakeholders’ pressure

3

4.47

0.471

Construction of a reverse logistics infrastructure

4

4.37

0.494

Creation of standards and assurance programs

5

4.21

0.513

Campaign to raise awareness

6

4.18

0.520

Knowledge sharing

7

4.10

0.565

Whole Life Costing (WLC)

8

4.05

0.568

Development of material recovery-enabling technologies

9

4.05

0.572

Development of secondary marketplaces with higher value

10

4.03

0.585

Improved understanding of CE in the built environment

11

4.02

0.590

Value of the raw materials or finished goods

12

4.00

0.608

Tools and tactics for collaboration and design

13

3.89

0.623

Value chain management

14

3.80

0.625

Design tools and guidance

15

3.75

0.627

Note SD—standard deviation

logistics infrastructure; creation of standards and assurance programs; campaign to raise awareness’ was Knowledge sharing; whole life costing; development of material recovery-enabling technologies; development of secondary marketplaces with higher value; improved understanding of circular economy in the built environment; value of the raw materials or finished goods; tools and tactics for collaboration and design; value chain management; and design tools and guidance. Furthermore, the opinions of the respondents were compared using a Kruskal– Wallis test based on the respondents’ various industry-related professions. Based on Table 3, no significant difference was found in drivers such as regulations and policies on circular economy, financial incentives to use secondary materials, stakeholders’ pressure, and construction of a reverse logistics infrastructure. However, for the other drivers of circular economy adoption, there is a significant difference in how the different category of construction professionals responded.

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Table 3 Kruskal–Wallis test for drivers of circular economy adoption Drivers

P-value

Regulations and policies on CE

0.062

Financial incentives to use secondary materials

0.068

Stakeholders’ pressure

0.081

Construction of a reverse logistics infrastructure

0.053

Creation of standards and assurance programs

0.011

Campaign to raise awareness

0.004

Knowledge sharing

0.000

Whole Life Costing (WLC)

0.001

Development of material recovery-enabling technologies

0.000

Development of secondary marketplaces with higher value

0.000

Improved understanding of CE in the built environment

0.001

Value of the raw materials or finished goods

0.000

Tools and tactics for collaboration and design

0.000

Value chain management

0.000

Design tools and guidance

0.000

4 Conclusion This study evaluates the drivers of circular economy in South African construction industry for the purpose of changing the take-make-dispose approach which is linear in nature that still drives the building sector in the country. A change in thinking has become necessary because of the relatively considerable negative environmental effects of the linear approach. If the principles are followed in the sector, circular economy has been viewed as a strategy that might result in ecologically sustainable development. Hence, the need to appraise the drivers. Based on the study’s findings, it can be concluded that to drive circular economy in the South African construction sector, government regulations and policies have to be enacted. This will ensure that construction related organizations’ production processes are clean and do not harm the environment. Furthermore, financial incentives are very important for industry partners to engage in circular building, especially among small to medium-sized organizations. This is because replacing infrastructure and services needed for circular economy processes requires capital. Other significant drivers include stakeholders’ pressure, construction of a reverse logistics infrastructure, and so on. It is necessary to be aware of what the South African construction industry and the country at large stand to gain if the circular economy approach is adopted. Apart from the fact that it will lead to a reduction in waste generated, it will lower the greenhouse gas emission and energy utilization of construction related activities, which the South African construction industry has received so much criticisms on. Therefore, all construction stakeholders in the country must motivate relevant parties to take considerable action

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as has been highlighted in this study in order for the SA construction sector to profit from this crucial strategy.

References Baloi D (2003) Sustainable construction: challenges and opportunities. In: 19th Annual ARCOM conference. University of Brighton, Association of Researchers in Construction Management, vol 1, pp 289–297 Bherwani H, Nair M, Niwalkar A, Balachandran D, Kumar R (2022) Application of circular economy framework for reducing the impacts of climate change: a case study from India on the evaluation of carbon and materials footprint nexus. Energy Nexus 5:100047. Chen Q, Feng H, de Soto BG (2022) Revamping construction supply chain processes with circular economy strategies: a systematic literature review. J Clean Prod 335:130240 Du Plessis C (2002) Agenda 21 for sustainable construction in developing countries. CSIR Rep BOU E 204:2–5 Ellen MacArthur Foundation [EMF] (2013) Towards the circular economy—opportunities for the consumer goods sector, vol 2 Ellen MacArthur Foundation (2015) Delivering the circular economy—a toolkit for policymakers. https://ellenmacarthurfoundation.org/a-toolkit-for-policymakers Field A (2005) Discovering statistics, using SPSS for windows. Sage Publications, London Geissdoerfer M, Savaget P, Bocken NM, Hultink EJ (2017) The circular economy–a new sustainability paradigm? J Clean Prod 143:757–768 Ge Z, Gao Z (2008) Applications of nanotechnology and nanomaterials in construction. In: First international conference construct development countries, pp 235–240 Kanters J (2020) Circular building design: an analysis of barriers and drivers for a circular building sector. Buildings 10(4):77. https://doi.org/10.3390/buildings10040077 Khan SAR, Ponce P, Thomas G, Yu Z, Al-Ahmadi MS, Tanveer M (2021) Digital technologies, circular economy practices and environmental policies in the era of COVID-19. Sustainability 13(22):12790 Kirchherr J, Reike D, Hekkert M (2017) Conceptualizing the circular economy: an analysis of 114 definitions. Resour Conserv Recycl 127:221–232. https://doi.org/10.1016/j.resconrec.2017. 09.005 Liu J, Feng Y, Zhu Q, Sarkis J (2018) Green supply chain management and the circular economy: reviewing theory for advancement of both fields. Int J Phys Distrib Logist Manag 48(8):794–817 Mitchell P, James K (2015) Economic growth potential of more circular economies, working paper. Waste and Resources Action Programme, Banbury, UK. Available at: https://www.researchg ate.net/profile/Peter_Mitchell21/publication/284187253_ECONOMIC_GROWTH_POTENT IAL_OF_MORE_CIRCULAR_ECONOMIES/links/564f4 0fb08ae1ef9296e83f3.pdf Norouzi M, Chàfer M, Cabeza LF, Jiménez L, Boer D (2021) Circular economy in the building and construction sector: a scientific evolution analysis. J Build Eng 44:102704 Pomponi F, Moncaster A (2017) Circular economy for the built environment: a research framework. J Clean Prod 143:710–718. https://doi.org/10.1016/J.JCLEPRO.2016.12.055 Otasowie OK, Oke AE (2022)“Drivers of mentoring practices in construction related firms: Nigerian quantity surveying firms’ perspective. Eng, Constr Archit Manag ahead-of-print(ahead-of-print) https://doi.org/10.1108/ECAM-09-2020-0679 Otasowie K, Oke A (2022) An assessment of exhibited drivers of mentoring in construction professional firms: a case of Nigerian quantity surveying firms. J Constr Dev Countries 27(2):63–86. https://doi.org/10.21315/jcdc-10-20-0225

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Otasowie OK, Oke AE (2020) Mentoring practices in construction professional firms in Nigeria. In: Aigbavboa C, Thwala W (eds) The construction industry in the fourth industrial revolution. CIDB 2019. Springer, Cham. https://doi.org/10.1007/978-3-030-26528-113 Preston F (2012) A global redesign? Shaping the circular economy Shen L, Zhang Z, Long Z (2017) Significant barriers to green procurement in real estate development. Resour Conserv Recycl 116:160–168 Tavakol M, Dennick R (2011) Making sense of Cronbach’s Alpha. Int J Med Educ 2:53–55 Velenturf AP, Purnell P (2021) Principles for a sustainable circular economy. Sustain Prod Consumption 27:1437–1457 Yeheyis M, Hewage K, Alam MS, Eskicioglu C, Sadiq R (2013) An overview of construction and demolition waste management in Canada: a lifecycle analysis approach to sustainability. Clean Technol Environ Policy 15:81–91

Challenges to Circular Economy Adoption: South African Built Environment Professionals’ Perspective O. K. Otasowie, C. Aigbavboa, P. Adekunle, and A. Oke

Abstract The linear approach which follows the principles of take-make-dispose’ still dominates the construction sector. The relative significant negative implications of this approach on the environment requires a paradigm shift. Circular economy (CE) has been regarded as an approach that could lead to environmentally sustainable development if adopted in the industry. However, there have been concerns in some quarters as regards the challenges to the adoption of CE approach. Hence, this study evaluates the challenges to circular economy adoption in the South African (SA) construction industry. A survey method was selected. Ninety (90) of the one hundred and thirty-five (135) questionnaires that were sent to construction industry professionals in Guateng Province, South Africa, were returned and deemed appropriate for study. One-sample t-tests, Kruskal–Wallis, standard deviation, percentage, and mean item scores were used to analyze the collected data. The findings reveal the significant challenges to the adoption of CE in SA construction industry which are lack of financial incentives, lack of knowledge, low virgin material costs, and lack of design expertise amongst others. This finding could inform construction stakeholders in the country on the present challenges to the adoption of CE and these challenges identified must encourage stakeholders to take significant steps towards addressing the them such that the SA construction industry benefit from this all-important approach. Keywords Circular economy adoption · South African · Construction industry

1 Introduction Construction demolition waste has emerged as a serious environmental concern in many nations throughout the world, and solid waste management is a big issue in the majority of developing countries. According to Menegaki and Damigos (2018), large amounts of waste are produced during demolition of construction projects. O. K. Otasowie · C. Aigbavboa · P. Adekunle · A. Oke Faculty of Engineering and the Built Environment, Cidb Centre of Excellent and Sustainable Human Settlement and Construction Research Centre, University of Johannesburg, Johannesburg, South Africa © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_19

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Although attempt to reuse and recycle construction and demolition waste (CDW) is growing, it is on record that approximately 35% of the amounts produced worldwide are sent to dumpsites with no further processing (Hossain et al. 2017). Over the years, the construction industry has continued to witness this trend due to the fact that urbanization has grown at an astonishing rate globally. Roser (2019) opined that urbanization increased globally overall by 54.3% in 2016, 55% at 2018, and by the year 2050, it is anticipated this number will increase to 68% (UN 2018). This pace is causing an excessive amount of CDW to be produced. Wu et al. (2017) posited that construction, demolition, renovation, extension, roadwork, maintenance, and other urbanization-related activities generate waste that must be handled. However, to handle the waste generated from these processes requires a paradigm shift. A shift from the hitherto linear economic approach of “take-makes-use-dispose” to the circular economic approach of “make-use-return”. The circular economy approach is a process that maximizes raw material consumption while minimizing emissions and waste production via remanufacture, repair, reuse, refurbishing, and recycling (Geissdoerfer et al. 2017). According to the Ellen MacArthur Foundation (EMF) (2015), circular economy systems use end-oflife design and construction, and their parts and pieces should be disassembled to serve as material banks for upcoming projects. Hopkinson et al. (2018) claimed that this helps keep materials moving in a circular pattern. In an attempt to holistically provide a summary of circular economy definition, Prieto-Sandoval et al. (2018) stated that “The circular economy is an economic system that represents a change of paradigm in the way that human society is interrelated with nature and aims to prevent the depletion of resources, close energy and materials loops, and facilitate sustainable development through its implementation at the micro (enterprises and consumers), meso (economic agents integrated in symbiosis) and macro (city, regions and governments) levels. Attaining this circular model requires cyclical and regenerative environmental innovations in the way society legislates, produces and consumes.” (p. 610). The essential feature of the circular economy is a comprehensive approach with the construction of circular loops of energy, material, and waste flows that incorporate all society activities. This separates the circular economy approach from previous initiatives to minimize energy and material use (Masi et al. 2018). Given that the building industry consumes the most natural resources and generates the most waste particularly at buildings’ end of life, adopting circular economy principles is critical (Norouzi et al. 2021). According to Aboginije et al. (2020), South Africa produced 108 million tons of solid waste in 2020 which includes waste from construction demolition, with 98 million tons of that waste ending up in landfills. As dumping sites become scarcer, finding new ways to manage these wastes, particularly those that may be transformed into resources, is becoming more important (Aigbavboa et al. 2017). Lowering CDW can lead to more sustainable growth and better green building projects (Aboginije et al. 2020). This can be achieved through maintaining, reusing, refurbishing, and/or recycling resources and materials utilized in every step of the construction value chain, which is the goal of circular economy (Høibye and Sand 2018). For this reason, the EMF (2015) has promoted the principles and possibilities of the circular economy, which it defines as a cycle of

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continuous improvement aimed at keeping resources in a circular path at their value. However, as a significant approach in emerging economies development, there have been concerns in some quarters as regards the challenges to the adoption of circular economy approach. Hence, this study evaluates the challenges to circular economy adoption in the South African (SA) construction industry.

2 Methodology The study took a post-positivist approach in terms of philosophy, employing quantitative research that was carried out using a questionnaire survey. The questionnaire was divided into two segments, with the first segment intended to elicit background data from the respondents. The second segment tried to address the challenges to circular economy adoption. The respondents, who are construction professionals were requested to rate the significance of the challenges to circular economy adoption in South African construction industry using a 5-point Likert scale, with 5 being Strongly significant, 4 being significant, 3 being moderately significant, 2 being slightly significant, and 1 being not significant. The study population were made of qualified construction professionals (engineers, architects, quantity surveyors and construction managers) who are working in Guateng Province, South Africa and had at least five years of work experience. Due to time and financial restrictions, convenience sampling was used for the study. One hundred and thirty-five (135) questionnaires were sent out to the construction professionals and ninety (90) were received and considered appropriate for investigation. One-sample t-tests, standard deviation, percentages, mean item scores, and Kruskal–Wallis tests as adopted by Otasowie and Oke (2022) were used to analyze the collected data. Using the Cronbach’s alpha test, which yielded an alpha value of 0.891, the study validated the questionnaire’s validity and reliability. Given that the alpha score is over the cutoff point of 0.6, confirms the questionnaire’s high degree of reliability (Tavakol and Dennick 2011).

3 Result and Discussion Professionals from South Africa’s Gauteng Province participated in the survey. The profession with the most involvement (28%) is quantity surveyors. Following are engineers (22%), architects (20%), construction managers (18%), and project managers for construction (12%). The majority of these respondents (65.2%) hold bachelor’s degrees, while the next highest levels of education are masters, doctoral, and certificate degrees, respectively, with 14.5%, 13.4%, and 6.9%. The total number of respondents had an average working history of 8.4 years, which is a remarkably long period of time in the field. These findings suggest that the study’s target respondents, who were construction professionals, were fairly represented and that they

210

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had a sufficient degree of education to comprehend the study’s questions (Otasowie and Oke 2022). Also, the answers to these queries were based on a large amount of professional expertise. A one sample t-test was employed to evaluate whether the respondents viewed a certain challenge to be significant or not. The mean rank for every challenge was tabulated to give a thorough assessment of the respondents’ views. The significance level was established at 95% in accordance with the customary threshold (Otasowie and Oke 2020), and a challenge was deemed significant if it had a mean of 3.5 or above on the five-point Likert scale for rating. When two or more challenges had the same mean, the challenge with the lowest standard deviation received the highest priority ranking (Field 2005). The challenges to circular economy adoption are shown in Table 1. Based on the p-value of each challenge, there is an agreement between the respondents that the listed challenges to circular economy adoption are significant in the building sector in South Africa. For each challenge, there was a null hypothesis stating that the outcome was not significant (H0: U = U0) and an alternative hypothesis stating the outcome was significant (Ha: U > U0), wherein U0 is the population mean (3.5). Hence, the null hypothesis was rebutted. In Table 2, the observed data mean is shown by the standard deviation. While a large standard deviation shows that the data point is considerably distant from the mean, a low standard deviation suggests that most data are close to the mean (Field 2005). The standard deviations are smaller than 1.0, demonstrating the consistency of the data and respondents’ perceptions of the challenges to circular economy adoption (Field 2005). The study reveals the respondents’ rankings of challenges to adopting circular economy in South Africa. Based on Table 2, lack of incentives ranked first with a mean score of 4.70 and (SD) = 0.348. This finding concurs with Masi et al. (2018) about the significance of financial incentives in the adoption of circular economy approach. High initial investment cost have been frequently cited as a significant challenge. Each significant social change has switching costs, which might vary. The supply chain being transformed, contracts being renegotiated, technology being modified to accommodate new inputs, or high technological costs for new product designs are just a few examples. According to Rizos et al. (2015), Small and Medium Enterprises (SMEs) have a particularly tough time getting finance to switch to circular economy approach without financial assistance. Lack of knowledge of the materials and structures already in place ranked second with a mean score of 4.59 and (SD) = 0.420. According to Guerra and Leite (2021), lack of awareness and knowledge of building circularity are a significant challenge for industry partners to engage in circular building. This is because, in the context of South African construction, several of the circular techniques are novel. Low virgin material costs ranked third with mean score of 4.58 and (SD) = 0.428. Grafström and Aasma (2021) opined that as new mines can open when material prices rise, the availability of virgin resources can adjust to price fluctuations more readily than the supply of recycled resources. Recycled materials have an inelastic supply since they are reliant on historical consumption trends.

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Table 1 One-sample test for challenges to circular economy adoption Challenges

T

Df

Sig. (2-tailed)

Mean diff.

95% Confidence interval of the diff. Lower

Upper

Low virgin material costs

12.019

89

0.000

0.978

1.012

1.131

Performance guarantees for recycled materials are absent

4.338

89

0.000

0.611

0.701

0.872

Perception of used materials

4.759

89

0.000

0.772

0.865

0.992

Material salvage cost

4.403

89

0.000

0.630

0.716

0.925

Limitations on deconstruction time

4.437

89

0.001

0.641

0.736

0.952

Lack of knowledge of used 4.512 materials

89

0.001

0.698

0.808

0.982

Lack of knowledge of the materials and structures already in place

15.182

89

0.000

1.016

1.034

1.157

Lack of financial incentives 17.264

89

0.001

1.075

1.071

1.192

Lack of design expertise

7.568

89

0.002

0.916

0.983

1.114

Inertia in the construction industry

5.342

89

0.000

0.855

0.934

1.105

Design regulations prioritize using new materials

4.364

89

0.002

0.618

0.708

0.884

Design cost

4.397

89

0.000

0.624

0.712

0.899

Deficiencies in the supply chain’s integration

4.745

89

0.000

0.745

0.842

0.987

Deconstruction labour costs

4.412

89

0.000

0.632

0.722

0.933

Cost of deconstruction and 4.458 potential effects on programs

89

0.000

0.648

0.786

0.976

Because of this, recycled materials have more price fluctuation, which breeds uncertainty. Because markets for recycled materials are uncertain, investors are less eager to invest in them, as long as there is a lesser substitute. Other challenges identified from literature and considered significant include lack of design expertise; inertia in the construction industry; perception of used materials; deficiencies in the supply chain’s integration; lack of knowledge of used materials; cost of deconstruction and potential effects on programs; limitations on deconstruction time; deconstruction labour costs; material salvage cost; design cost; design regulations prioritize using new materials; and performance guarantees for recycled materials are absent.

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Table 2 Summary of t-test for challenges to circular economy adoption MEAN

SD

Lack of financial incentives

1

4.70

0.342

Lack of knowledge of the materials and structures already in place

2

4.59

0.420

Low virgin material costs

3

4.58

0.428

Lack of design expertise

4

4.55

0.500

Inertia in the construction industry

5

4.51

0.400

Perception of used materials

6

4.47

0.422

Deficiencies in the supply chain’s integration

7

4.44

0.414

Lack of knowledge of used materials

8

4.43

0.330

Cost of deconstruction and potential effects on programs

9

4.42

0.337

Limitations on deconstruction time

10

4.40

0.296

Deconstruction labour costs

11

4.38

0.475

Material salvage cost

12

4.37

0.453

Design cost

13

4.36

0.348

Design regulations prioritize using new materials

14

3.82

0.433

Performance guarantees for recycled materials are absent

15

3.52

0.416

Challenges

Rank

Note SD = Standard Deviation

Furthermore, the opinions of the respondents were compared using a Kruskal– Wallis test based on the respondents’ various industry-related professions. Based on Table 3, no significant difference was found in challenges such as lack of financial incentives, low virgin material costs, lack of design expertise and perception of used materials. However, for the other challenges to circular economy adoption, there is a significant difference in how the different category of construction professionals responded.

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Table 3 Kruskal–Wallis test for challenges to circular economy adoption Challenges

P-value

Lack of financial incentives

0.078

Lack of knowledge of the materials and structures already in place

0.003

Low virgin material costs

0.075

Lack of design expertise

0.084

Inertia in the construction industry

0.011

Perception of used materials

0.064

Deficiencies in the supply chain’s integration

0.000

Lack of knowledge of used materials

0.001

Cost of deconstruction and potential effects on programs

0.000

Limitations on deconstruction time

0.000

Deconstruction labour costs

0.001

Material salvage cost

0.000

Design cost

0.000

Design regulations prioritize using new materials

0.000

Performance guarantees for recycled materials are absent

0.000

4 Conclusion This study evaluates the challenges to circular economy adoption in the South African construction industry for the purpose of changing the take-make-dispose approach which is linear in nature that still drives the building sector in the country. Given that the building industry consumes the most natural resources and generates the most waste particularly at buildings’ end of life, adopting circular economy principles is critical. Particularly, as dumping sites have become scarcer, it is important to find new ways to manage these wastes. However, there have been concerns in some quarters as regards the challenges to the adoption of CE approach. Hence, the need to appraise the challenges. Based on the study’s findings, it can be concluded that the challenges to circular economy adoption in the South African construction sector include lack of financial incentives, lack of knowledge, low virgin material costs, and lack of design expertise among others. Financial incentives are very important for industry partners to engage in circular building, especially among small to mediumsized organizations. This is because replacing infrastructure and services needed for circular economy processes requires capital. Furthermore, stakeholders in the South African construction industry must make necessary effort to educate industry partners on circular economy principles and benefits as several of the circular economy techniques are novel. In addition, designing for deconstruction is a new concept rapidly gaining attention. Hence, it is important for the designers in the South African construction sector to be retrained in this new concept, as it will aid rapid adoption of the circular economy approach in the industry. It is necessary to be aware of

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what the South African construction industry and the country at large can benefit if the circular economy approach is adopted. Apart from the fact that it will lead to a reduction in waste generated, it will lower the greenhouse gas emission and energy utilization of construction related activities, which the South African construction industry has received so much criticisms on. Therefore, all construction stakeholders in the country must motivate relevant parties to take considerable action as has been highlighted in this study in order for the SA construction sector to profit from this crucial strategy.

References Aboginije A, Aigbavboa C, Thwala W, Samuel S (2020) Determining the impact of construction and demolition waste reduction practices on green building projects in Gauteng province, South Africa. In: Proceedings of international engineering & operations management, Dubai, UAE, 10–12 Aigbavboa C, Ohiomah I, Zwane T (2017) Sustainable construction practises: ‘a Lazy View’ of construction professionals in the South Africa Construction Industry. In: Energy Procedia. Elsevier Ltd., pp 3003–3010. https://doi.org/10.1016/j.egypro.2017.03.743 Ellen MacArthur Foundation (2015) Delivering the circular economy—a toolkit for policymakers. https://ellenmacarthurfoundation.org/a-toolkit-for-policymakers Field A (2005) Discovering statistics, using SPSS for windows. Sage Publications, London Geissdoerfer M, Savaget P, Bocken NM, Hultink EJ (2017) The circular economy–a new sustainability paradigm? J Clean Prod 143:757–768 Guerra BC, Leite F (2021) Circular economy in the construction industry: an overview of United States stakeholders’ awareness, major challenges, and enablers. Resour Conserv Recycl 170:105617 Grafström J, Aasma S (2021) Breaking circular economy barriers. J Clean Prod 292:126002 Høibye L, Sand H (2018) Circular economy in the Nordic construction sector: identification and assessment of potential policy instruments that can accelerate a transition toward a circular economy. Nordisk Ministerråd Hopkinson P, Zils M, Hawkins P, Roper S (2018) Managing a complex global circular economy business model: Opportunities and challenges. Calif Manag Rev 60(3):71–94 Hossain MU, Wu Z, Poon CS (2017) Comparative environmental evaluation of construction waste management through different waste sorting systems in Hong Kong. Waste Manag 69:325–335 Masi D, Kumar V, Garza-Reyes JA, Godsell J (2018) Towards a more circular economy: exploring the awareness, practices, and barriers from a focal firm perspective Prod. Plann Contr 29(6):539– 550 Menegaki M, Damigos D (2018) A review on current situation and challenges of construction and demolition waste management. Curr Opin Green Sustain Chem 13:8–15 Norouzi M, Chàfer M, Cabeza LF, Jiménez L, Boer D (2021) Circular economy in the building and construction sector: a scientific evolution analysis. J Build Eng 44:102704 Otasowie OK, Oke AE (2022) Drivers of mentoring practices in construction related firms: Nigerian quantity surveying firms’ perspective. Eng, Constr Archit Manag ahead-of-print(ahead-of-print). https://doi.org/10.1108/ECAM-09-2020-0679 Otasowie K, Oke A (2022) An assessment of exhibited drivers of mentoring in construction professional firms: a case of Nigerian quantity surveying firms. J Constr Developing Countries 27(2): 63–86. https://doi.org/10.21315/jcdc-10-20-0225

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Otasowie OK, Oke AE (2020) Mentoring practices in construction professional firms in Nigeria. In: Aigbavboa C, Thwala W (eds) The construction industry in the fourth industrial revolution. CIDB 2019. Springer, Cham. https://doi.org/10.1007/978-3-030-26528-1_13 Prieto-Sandoval V, Jaca C, Ormazabal M (2018) Towards a consensus on the circular economy. J Clean Prod 179:605–615 Rizos V, Behrens A, Kafyeke T, Hirschnitz-Garbers M, Ioannou A (2015) The circular economy: barriers and opportunities for SMEs CEPS working documents, p 412 Roser HRM (2019) Urbanization. Published online at OurWorldInData.org. Retrieved from: https:// OurWorldInData.org/urbanization ([Online Resource]) Tavakol M, Dennick R (2011) Making sense of Cronbach’s Alpha. Int J Med Educ 2:53–55 UN World Urbanization Prospects United Nations Department of Public Information 2018, pp 1– 3 https://www.un.org/development/desa/en/news/population/2018-revision-of-world-urbanizat ion-prospects.html. Accessed 16 March 2023 Wu Z, Ann T, Shen L (2017) Investigating the determinants of contractor’s construction and demolition waste management behavior in Mainland China. Waste Manag 60:290–300

Designing Out Waste: A Literature Review Mia Tedjosaputro

Abstract This literature review paper studies the extent to which one of four central tenets of circular design, ‘designing out waste’ has been implemented. This study looks at the review of the literature within the period of 2014–2023 in Science Direct database. A thematic analysis of two main themes was conducted: (1) material reuse and recovery and (2) construction waste management. It is observed that substitutions of natural aggregates in concrete have been widely researched, and it is suggested that future research may include the feasibility of using other kinds of waste including from industries outside of the construction sector. In this regard, “designing out waste” has a more global meaning than the closed loop of the construction industry. Keywords Review · Circular economy · Material reuse · Construction waste management

1 Introduction In comparison with other sectors, the building and construction sector is the highest contributor to carbon emissions, according to the 2022 Global Status Report for Buildings and Construction. In addition, we are not on track for decarbonisation by 2050 with the gap between climate performance and the decarbonisation path is widening compare to pre-Covid 19 pandemic gap (UNEP 2022). The report also points out that after the decline of construction activities in 2020 due to the pandemic, the CO2 emissions rebound suggests that more significant effort needs to be in place. Moreover, Construction and Demolition Waste (CDW) accounts for half of the total solid waste generated yearly worldwide (Redling 2018). A more appropriate approach would be for waste reduction to be planned from the early design stage of a new design rather than relying on managing waste after waste is generated. As seen in Sect. 4 however, this philosophy also extends to the use of waste from

M. Tedjosaputro Xi’an Jiaotong – Liverpool University, Suzhou, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_20

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other industries as aggregate, so this is more of a holistic approach than a closed loop. This literature review paper aims to provide a snapshot of recent research conducted within one particular tenet of circular economy, ‘designing out waste’. The research question the author tries to investigate is “To what extent waste can be minimised and managed in regards to ‘designing out waste’?” This review is hoped to start a conversation for architects and designers to start a design with material circularity in mind, addressing one of the current challenges to transition to a circular design, which is the lack of standard methods and tools for architects and designers.

1.1 Circular Economy As opposed to the linear economy, with its ‘take-make-dispose’ sequence, the circular economy includes the restorative use of resources. In other words, it uses optimal sources of raw materials and resources. Kirchherr et al. (2017) analysed 114 definitions of circular economy, and the authors ultimately defined it as “an economic system that replaces the ‘end-of-life’ concept with reducing, alternatively reusing, recycling and recovering materials in production/ distribution…”.

1.2 Circular Design One of the critical ideas of the circular economy, which is transferable to built environment, is to keep the circularity of waste at its highest value. For instance, the reuse practice of waste glass. Instead of reusing them as glass which requires sorting, cleaning and melting, which are labour-intensive, crushing waste glass into aggregates allows for much lower water and energy use. In addition, it also removes toxic chemicals by being fixed in concrete. Circular design re-thinks the end of life of a building to avoid CDW being sent to landfill after demolition, providing a closedloop framework of material flows. While transitioning to circular design requires the building and construction industry to change their economy, other barriers observed by Kanters (2020) include a lack of flexibility in building codes and regulations, its transformation requires simultaneous changes in other sectors to keep up with the demand, and there is lack of standard methods and tools to help architects and designers to take the right decision.

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1.3 Four Key Tenets of Circular Design This paper addresses one of the four main ideas for Circular Building design, adapted from Rahla et al. (2021). The four interrelated fundamental tenets are: (1) Designing out waste (2) Design for adaptability 3) Selecting materials, and (4) Design for Disassembly. The first tenet will be expanded in Sect. 4. The second tenet, ‘design for adaptability,’ looks at increasing the independency of components and modularity of building elements and is also concerned with standardisation, computability, modularity and upgradability. The third tenet, ‘selecting materials’, entails choosing materials with low embodied energy and carbon, materials which embrace disassembly and adaptability, and technical or biological materials that can support circularity. The fourth tenet, ‘design for disassembly,’ considers deconstruction and disassembly processes, with design considerations which allow multiple uses and ease of maintaining building components.

2 Methodology 2.1 Search Strategy The search is conducted through Science Direct database. The keyword ‘designing out waste and building’ was used, and a search was conducted in available journal databases related to the built environment; they are: Construction and Building Materials, Energy and Buildings, Journal of Building Engineering, Building and Environment, Procedia Engineering and Automation in Construction. Subsequently, the search filters publications within 2014–2023 to provide a ten-year snapshot. In the initial phase, 1583 publications were identified and processed, which were then screened by title, abstract and keywords based on relevance. In the last stage, a total of fifty-nine full papers were identified, extracted and coded using qualitative data analysis software.

2.2 Analysis Strategy Qualitative analysis was performed after in vivo coding was completed. In vivo coding allows codes to be generated from the data (the full papers), manually done by the author and aided by the software. Coding full papers includes reading and classifying texts into two themes used for thematic analysis. The coded text was then visualised based on the themes listed in Sect. 4.

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Fig. 1 Cluster analysis diagram of coded full papers

3 Results Clusters were identified using Pearson correlation coefficient and is illustrated in Fig. 1 (in previous page), which provides an overview of the coded full papers. The cluster analysis diagram suggests that concrete is widely researched with proximity to other words such as cement, strength and compression. From this excerpt, it is also indicated that from the observed studies, parts of concrete were replaced by a variety of materials, which were then tested in terms of strength and compression. The subsequent section provides the discussion based on the thematic analysis. Due to the limited number of pages, only selected publications to exemplify this literature review is included in the bibliography.

4 Designing Out Waste ‘Designing out waste’ is one of four tenets of adaptation of circular economy for the built environment. Planning how waste will be generated, processed, optimised and potentially repurposed requires each stakeholder’s involvement from the early design stage. As opposed to processing construction and demolition waste (CDW), anticipating waste can potentially reduce high waste disposal annual costs. From the observed literature, two main themes arise, and the remainder of this paper focuses on the discussion around these themes.

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4.1 Material Reuse and Recovery 4.1.1

Granularity of Repurposed Elements

Li et al. (2022) examined the viability of using various types of waste, including waste concrete, as a replacement for natural aggregate in construction. They report for example that the United States buries tens of millions of tons of waste glass in landfill, which is a substantial figure that could be used as aggregate in construction. They note moreover that landfill space is becoming increasingly scarce in the US, especially in urban areas, and it is reasonable to extrapolate this finding to other countries, so there are additional benefits to repurposing waste suitable for aggregate in cementitious materials. Suitable materials would be chemically stable and they examine the feasibility of using other types of waste such as natural fibres, plastics, wood et cetera and conclude that glass is a particularly suitable candidate due to its chemical stability and the fact that it does not biodegrade. Recycled aggregates from construction waste include concrete, tiles, marble, asphalt, bitumen, and brick, and these are similarly chemically stable and suitable for use as aggregate. The processing of the aggregate is crucial to the success of its use as recycled aggregate and efficient crushing is particularly important, as is the water to cement ratio of the parent concrete (the recycled concrete). Concerning waste glass, it is preferable to use this as aggregate compared to other recycling methods because in order to be recycled as new glass products, the waste glass must be sorted, cleaned, and melted which is an energy and water-use intensive process, and these stages are not necessary when using glass as aggregate- only crushing is required. Moreover, there are toxic substances in glass which are fixed in a safe manner when it used in concrete. The same is true of natural fibres and woodalthough their toxicity is low, their used as aggregate is a form of carbon fixing and capture. The mechanical properties of wood and natural fibres make them attractive for use as additives in construction materials, as does their low density, but although early research into their use is promising, more research is still required in this area. While Li et al. (2022) examined the possibility of using recycled waste from the construction industry and domestic waste, Miraldo et al. (2021) further explored the use of aggregates generated as a by product of the mining industry. Similarly to Li et al. (2022), they identified the issues of depletion of natural aggregates as a major environmental consideration facing the industry today. They note that the mining and quarrying industries generate a substantial amount of mineral waste, but that this waste being rich in sulphides results in the need for special care when handling due to the possibility of the generation of toxic compounds when exposed to air or water. Gold mining waste rock is cited as an example of an aggregate with substantial annual volume, and in South Africa in 2001, this amounted to 47% of the country’s total waste rock production, at 221 million tons. Moreover, Kaolin tailing sand- used in the exploration of clay- is regarded as being similar in properties to gold mining waste rock.

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Other rock waste is produced from the need to cut various materials, such as granite and marble, into blocks, and this waste is also suitable for use as aggregate. Miraldo et al. (2021) also explore the use of fly ash from coal-fired boilers and note that this is suitable as an admixture in ordinary Portland cement concretes. Moreover, they report similar findings to Li et al. (2022) regarding the use of glass and other domestic waste. They report that thermoplastic waste is suitable for use as aggregate in structural applications, and that rubber wastes tend to produce lower densities and higher water absorption than natural aggregates- this lower density is a desirable characteristic of structural concrete, as noted above. Finally, they report that crushed mollusc shells can be used as aggregate in concrete, but not for structural applications. This is expanded upon by Martínez-García et al. (2019) who note that millions of tons of shells are sourced annually by the mussel farming industries of 40 countries, and Galicia alone produces 25,000 tons annually, most of which is disposed of in landfill. They state that after heat treatment, a mix consisting of 25% seashell can be used for accurate surface and base layer cement coatings. Mohseni pour Mohseni Pour Asl et al. (2022) examined the mechanical and structural properties of various recycled aggregates in acidic and alkaline environments, including glass, eggshell, iron and rubber powder as a replacement for ordinary Portland cement. They concluded that under acidic curing conditions, the substitution of glass, eggshell and rubber improved the strength of the resulting concrete significantly. The eggshells were sourced from industrial channels and the rubber was gathered from old tyres, themselves a significant contributor to landfill waste. Malabi Eberhardt et al. (2021) diverged from other research in this review in that they focused on reuse of existing building materials, rather than on aggregates. They noted that most of a building’s embodied greenhouse gas emissions arise from the production stage, so prolonging a building’s life can improve resource efficiency. They state that in Canada, reuse of the structure of a high-rise building can result in a saving of 33% of embodied greenhouse gas compared to demolition and new construction, and that retrofitting a hospital could save 31% over demolition and new build. As a result of their research, they make recommendations about the fixtures and fittings of new builds, incorporating the philosophy of Design for Disassembly (fourth key tenet of circular design as posited in Sect. 1.3) to maximise the efficiency of the refit process. This aspect of Design for Disassembly is further explored by Brütting et al. (2021) who posited that a modular kit could be developed for the purpose of building retrofit. They suggest that such a kit could reduce greenhouse gas emissions by reducing resource use, energy consumption and waste. The basis of their suggested kit is a system of spherical joints and linear bars which are configurable to different topologies. There are three areas of research incorporated in their study: reversible and modular construction systems (the reversibility is a key aspect of designfor-disassembly), architectural geometry rationalisation (essential for widespread compatibility of the system), and structural optimisation for reuse. Thus, it is apparent that the repurposing of materials extends beyond the use of waste/ by-products in building materials construction to the consideration of the manufactured structures used in both new builds and retrofits.

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Finally, Hossain et al. (2021) investigated the possibility of using waste materials to create blocks for partition walls. Their rationale was the production of ordinary Portland cement is highly energy intensive. They found that blocks produced with fly ash, concrete slurry waste and fine recycled aggregates can reduce emissions by up to 82% compared with using Portland cement. However, to make this feasible, the infrastructure needs development, particularly with regard to supply chains. Overall, when considering granularity of repurposed elements, it is evident that the main benefits include reduced emissions, reduced landfill waste, and reduced resource consumption. There are also less major, but still significant, advantages such as fixing carbon in the case of wood and natural fibres and isolating harmful chemical compounds as in the case of glass and mining waste. However, there are obstacles to be overcome, such as logistics and supply chain management.

4.1.2

Types of Waste to Be Repurposed

Li et al. (2022) has, as described above, listed several sources of suitable waste materials. These include construction and demolition waste and the authors posit that two problems are solved at once by using this material- namely, the reduced burden on landfill, and the conservation of natural resources. They also state that waste glass is a significant resource for creating aggregates. Miraldo et al. (2021) moreover recommend that mining waste and tailing sand are plentiful supplies of natural aggregate substitution, as are waste from quarrying such as marble and granite. The other viable but less plentiful materials they suggest are coal fly ash, thermoplastic waste, glass waste (as above), rubber waste (e.g. from used tyres) and mollusc shells, depending on the application. Mohseni pour Mohseni Pour Asl et al. (2022) adds iron and eggshell to these lists and suggests that glass, eggshell, and rubber provide excellent resistance to acid conditions. Martínez-García et al. (2019) further focuses on mussel shells and finds that millions of tonnes of shells annually are produced by 40 countries, and that it is suitable for non-structural applications such as mortar. Hossain et al. (2021) suggested the use of coal fly ash, concrete slurry and other recycled aggregates could be used in the creation of building blocks for non-structural purposes. B et al. (2023) suggested the use of agricultural waste, including paddy husk, sugarcane and red gram crops as a cementitious, pozzolana or binder material, or as fibre reinforcement. Waste glass was suggested by D˛ebska et al. (2020) as a substitute for sand in epoxy mortars. Waste glass was also tested by Lawanwadeekul et al. (2023) along with corn cob and found to improve the strength of clay bricks. Behera et al. (2019) suggested the use of recycled fine aggregate from construction waste for self-compacting concrete. Gharibi et al. (2022) found that compressive strength of concrete could be improved by approximately 10% by substituting natural aggregates with ceramic waste from scrap electrical insulator material. Dias et al. (2022) found that wood particles from treated end-of-life wood could be used as an aggregate in lightweight concrete that was not used for structural purposes. Other smaller scale aggregates suggested include areca nut husk fibres Miah et al. (2023), glass powder (Hendi et al., 2019), cathode ray tube glass and fly ash (Gao

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et al., 2022), and lime mud (Dong et al., 2022). Alhawat et al. (2022) suggested the use of geopolymers sourced from construction waste as a binder in place of ordinary Portland cement due to its lower carbon footprint, and plastic waste as filler was suggested by Mohan et al. (2021). Thermal insulation can be sourced from recycled duvets (Bourguiba et al., 2020). Coletti et al. (2018) suggested using quarry waste not as concrete aggregate but in brick production, and they also investigated the use of organic compounds, sewerage sludge, ceramic sludge and leach residues for the same purpose. Waste tyres are examined by Lamour and Cecchin (2021) for use whole and unprocessed, in applications such as earth retention, artificial reefs, and insulation which obviates the requirement for mechanical or chemical processing. Barrios et al. (2021) examined the use of three types of fibres, namely glass, basalt and carbon in lime and cement mortars made with recycled aggregate, and found that carbon fibres can reinforce these mortars to an extent that largely offsets the reduction in bending strength, compressive strength and adhesion resulting from the substitution of recycled aggregate for natural aggregate. It can be seen from the above summary that there is a wide variety of waste material which is suitable for replacing natural aggregate in both concrete and brick/block production, along with other more niche applications such as insulation. There has been substantial research on the more plentiful of these materials such as recycled construction and demolition waste, quarry and mining waste, and glass. In terms of their mechanical properties, these are all suitable materials, and they offer substantial benefits in terms of both economic and environmental aspects. The challenges are in terms of supply chain and supporting infrastructure for these materials.

4.2 Construction Waste Management In addition to the use waste from other industries outlined above, the construction industry itself is also a potentially rich source of recycled or repurposed aggregate. In the EU, recovery rates for construction and demolition rates are relatively high, at around 89% (Sobotka and Sagan, 2021) but in other parts of the world such as the US, Canada, Brazil and China, the figure is much less. In Brazil for example the recovery rate is less than 20% of the 70 million tonnes annually of generated construction and demolition waste (Puente de Andrade et al., 2020). China produces over 1.5 billion tonnes (of construction and demolition waste), the US over 500 million tonnes (of which approximately 2/3 comes from Portland Cement), and Canada over 9 million tonnes (of which only around 7% is recovered). Given the environmental concerns outlined in previous sections, it is therefore imperative that the rate of reuse is increased. These concerns include, but are not limited to, scarcity of natural resources, scarcity of landfill, and toxic substances threatening both human health and that of flora and fauna due to water leaching and other methods. A related mitigating concept is designing out waste at the construction stage, but this is not the focus of this paper. Several solutions have been proposed, including one by Davis et al. (2021) which proposes a deep convolutional neural network to

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assist with on-site sorting and classification of construction waste. The system in tests was found to be 94% accurate in its assessment, which can reduce project costs and potentially assist with another solution proposed by Kalinowska-Wichrowska et al. (2020) in which concrete rubble is subject to thermal and mechanical treatment onsite, and directly reused as aggregate in new concrete. Beyond this, the challenge is to create an infrastructure allowing for treatment sites of construction and demolition waste, as per Sobotka and Sagan (2021) who posit a system of mobile treatment centres. A stable supply chain is essential for widespread adoption.

5 Future Research Directions The posited research question; “To what extent waste can be minimised and managed in regards to ‘designing out waste’?” While in Europe, approximately 89% of construction waste is recycled, this figure is much lower in the rest of the world. Based on the above analysis and the success of Europe, it is likely that this substitution (such as in aggregates) can achieve significant success. Most of the above literature addresses the issue of reusing construction and demolition waste (CDW), though as can be seen from the above review, other industries are also rich sources of potential aggregate. While it is a significant size of landfill usage; this literature review suggests that domestic waste and agricultural waste could potentially be used as aggregates or fillers to replace natural aggregates in construction industry. It is suggested that future research may focus on the feasibility of using other kinds of waste beyond what has been reviewed above, since research into non-naturally occurring aggregates such as polymers is a relatively recent field of research.

References Alhawat M, Ashour A, Yildirim G, Aldemir A, Sahmaran M (2022) Properties of geopolymers sourced from construction and demolition waste: A review. Journal of Building Engineering 50:104104 B, S., Patil, N., Jaiswal, K. K., Gowrishankar, T. P., Selvakumar, K. K., Jyothi, M. S., Jyothilakshmi, R. & Kumar, S. 2023. Development of sustainable alternative materials for the construction of green buildings using agricultural residues: a review. Construction and Building Materials 368:130457 Barrios AM, Vega DF, Martínez PS, Atanes-Sánchez E, Fernández CM (2021) Study of the properties of lime and cement mortars made from recycled ceramic aggregate and reinforced with fibers. Journal of Building Engineering 35:102097 Behera M, Minocha AK, Bhattacharyya SK (2019) Flow behavior, microstructure, strength and shrinkage properties of self-compacting concrete incorporating recycled fine aggregate. Constr Build Mater 228:116819 Bourguiba A, Touati K, Sebaibi N, Boutouil M, Khadraoui F (2020) Recycled duvets for building thermal insulation. Journal of Building Engineering 31:101378

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Brütting J, Senatore G, Fivet C (2021) Design and fabrication of a reusable kit of parts for diverse structures. Autom Constr 125:103614 Coletti C, Maritan L, Cultrone G, Dalconi MC, Hein A, Molina E, Mazzoli C (2018) Recycling trachyte waste from the quarry to the brick industry: Effects on physical and mechanical properties, and durability of new bricks. Constr Build Mater 166:792–807 Davis P, Aziz F, Newaz MT, Sher W, Simon L (2021) The classification of construction waste material using a deep convolutional neural network. Autom Constr 122:103481 D˛ebska B, Lichołai L, Silva GJB (2020) Effects of waste glass as aggregate on the properties of resin composites. Constr Build Mater 258:119632 Dias S, Almeida J, Santos B, Humbert P, Tadeu A, António J, De Brito J, Pinhão P (2022) Lightweight cement composites containing end-of-life treated wood – leaching, hydration and mechanical tests. Constr Build Mater 317:125931 Dong B, Chen C, Fang G, Wu K, Wang Y (2022) Positive roles of lime mud in blended portland cement. Constr Build Mater 328:127067 Gao X, Yao X, Xie R, Li X, Cheng J, Yang T (2022) Performance of fly ash-based geopolymer mortars with waste cathode ray tubes glass fine aggregate: A comparative study with cement mortars. Constr Build Mater 344:128243 Gharibi H, Mostofinejad D, Bahmani H, Hadadzadeh H (2022) Improving thermal and mechanical properties of concrete by using ceramic electrical insulator waste as aggregates. Constr Build Mater 338:127647 Hendi A, Mostofinejad D, Sedaghatdoost A, Zohrabi M, Naeimi N, Tavakolinia A (2019) Mix design of the green self-consolidating concrete: Incorporating the waste glass powder. Constr Build Mater 199:369–384 Hossain MU, Xuan D, Ng ST, Amor B (2021) Designing sustainable partition wall blocks using secondary materials: A life cycle assessment approach. Journal of Building Engineering 43:103035 Kalinowska-Wichrowska K, Pawluczuk E, Bołtryk M (2020) Waste-free technology for recycling concrete rubble. Constr Build Mater 234:117407 Kanters J (2020) Circular building design: An analysis of barriers and drivers for a circular building sector. Buildings 10:77 Kirchherr J, Reike D, Hekkert M (2017) Conceptualizing the circular economy: An analysis of 114 definitions. Resour Conserv Recycl 127:221–232 Lamour M, Cecchin A (2021) Repurposed materials in construction: A review of low-processed scrap tires in civil engineering applications for disaster risk reduction. Constr Build Mater 293:123368 Lawanwadeekul S, Srisuwan A, Phonphuak N, Chindaprasirt P (2023) Enhancement of porosity and strength of clay brick fired at reduced temperature with the aid of corn cob and waste glass. Constr Build Mater 369:130547 Li X, Qin D, Hu Y, Ahmad W, Ahmad A, Aslam F, Joyklad P (2022) A systematic review of waste materials in cement-based composites for construction applications. Journal of Building Engineering 45:103447 Malabi Eberhardt LC, Rønholt J, Birkved M, Birgisdottir H (2021) Circular economy potential within the building stock - mapping the embodied greenhouse gas emissions of four danish examples. Journal of Building Engineering 33:101845 Martínez-García C, González-Fonteboa B, Carro-López D, Martínez-Abella F (2019) Design and properties of cement coating with mussel shell fine aggregate. Constr Build Mater 215:494–507 Miah MJ, Li Y, Paul SC, Babafemi AJ, Jang JG (2023) Mechanical strength, shrinkage, and porosity of mortar reinforced with areca nut husk fibers. Constr Build Mater 363:129688 Miraldo S, Lopes S, Pacheco-Torgal F, Lopes A (2021) Advantages and shortcomings of the utilization of recycled wastes as aggregates in structural concretes. Constr Build Mater 298:123729 Mohan HT, Jayanarayanan K, Mini KM (2021) Recent trends in utilization of plastics waste composites as construction materials. Constr Build Mater 271:121520

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Sustainability Assessment Practices in the Construction Industry: The Untold Story of South Africa M. Ikuabe, C. Aigbavboa, and E. Oke

Abstract Sustainability assessment is a formidable template for evaluating plans, policies, and activities toward the drive and actualisation of sustainable development. It helps appraise the steps taken and projected actions to align policies within the tenets of sustainability. However, the construction industry in South Africa appears to be on the back foot in fully harnessing the dividends of sustainable assessment. Based on the preceding, this study examined the critical hurdles to implementing sustainability assessment in the South African construction industry. A quantitative approach was employed with relevant professionals as the target population, while the data retrieved was subjected to appropriate empirical analysis. Findings showed that lack of requisite knowledge and cultural barriers were the most significant challenges in deploying sustainability assessment in the South African construction industry. The outcome of this study would serve as a good reference for policymakers, government officials, and relevant stakeholders in making informed policies and plans that aligns with the creeds of sustainable development. Furthermore, it serves as a solid theoretical base for future studies to propagate sustainability assessment for the South African construction industry. Keywords Sustainability assessment · Construction industry · South Africa

1 Introduction The construction sector contributes substantially to the country’s economy making it one of the most significant contributors. In addition, it has enhanced people’s lives and met their societal needs through its activities in the industry, such as providing homes and employment (Aghimien et al. 2021; Ikuabe et al. 2020). Although the industry is essential to people and society, it influences the environment negatively. The industry generates over half of the waste globally, contaminating water and causing global M. Ikuabe · C. Aigbavboa · E. Oke Faculty of Engineering and the Built Environment, SARChI in Sustainable Construction Management and Leadership in the Built Environment, University of Johannesburg, Johannesburg, South Africa © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_21

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air pollution (Ikuabe et al. 2023). However, the industry, being one of the significant sectors in urban growth, has the potential to play an important role in sustainability (Wang 2014). Hoffman et al. (2020) add that because of the detrimental impact of construction on the environment, there has to be a chance to incorporate sustainability practices. Sustainable and green practices are concepts that have already been established and implemented in most countries and have been seen to curb the harmful effects of unsustainable building design practices. Many built environment professionals seek better and more creative means to adopt sustainability in their new designs as they become more conscious of the need to maintain sustainable developments (Nilashi et al. 2015). Some countries have devised and adopted sustainability assessment systems to reduce environmental impact and promote green building due to the rising demand for construction activities (Liu et al. 2019). Various sustainability assessment systems have been implemented to control, analyze, and certify practices, methods, and techniques that meet environmental and climatic standards (Hoffman et al. 2020). The realization that the world has a finite amount of time to adapt to the rising concerns about climate change, particularly global warming, and those construction activities that contribute to the general conversation of environmental deterioration served as a driver (Yudelson 2007). For example, green rating systems are used to assess the success of a structure’s long-term in relation to its economic, social, and environmental surroundings. As a result, the green rating systems are used as a range of sustainable interpretations and assign different weight factors or scores to each category (United Nations Environment Programme 2020). Some of these sustainability assessment tools are leadership in energy and environment design (LEED), building research establishment and environmental assessment method (BREEAM), green star, evaluation standard for green building (ESGB), and comprehensive assessment system for built environment efficiency (CASBEE). For example, green architecture is an approach that advocates for the conservation of energy, the use of recyclable and safe building materials, the use of sustainable energy resources, and the construction of a building in consideration of its effects on the environment (Singh 2018). In conformance to this, several green initiatives have been explored in South Africa to help preserve the environment. For instance, the South African tourism industry has made efforts to place the city of Cape Town as a leading destination for the propagation of a sustainable built environment (MartinGonzalez et al. 2021). Also, South African urban centers have increasingly become a focus for addressing climate change, primarily through establishing sustainable practices that ensure sustainable urban practices (Gibberd 2021). However, these initiatives face many encumbrances, and one notable feature is the implementation of sustainability assessment systems or practices. The lack of sustainability assessment policies and regulations serves as a major hurdle to stakeholders in the drive to implement sustainability assessment (Zenios and Allen 2016). Also, Ebekozien et al. (2021) noted that the initial cost and lack of institutional framework for engagement in green rating deter stakeholders from indulging in the practice of sustainability assessment. Moreover, the lack of awareness and lack of support from the government serves as a major stumbling block (Addy et al. 2020). In light of the foregoing, this study intends to evaluate the challenges to sustainable assessment practices in South

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Africa. This is done with a view to proffering formidable recommendations that would aid in propelling the uptake of sustainability assessment systems to encourage sustainable development in the country. The outcome of this study would serve as a good reference for policymakers, government officials, and relevant stakeholders in making informed policies and plans that aligns with the creeds of sustainable development. Furthermore, it serves as a solid theoretical base for future studies to propagate sustainability assessment for the South African construction industry.

2 Research Methodology The study aims to investigate sustainability assessment practices in the South African construction industry. The study employed a quantitative approach using a questionnaire to collect data from the target respondents. Data was collected from built environment professionals in the Gauteng province of South Africa. The choice of the study area results from the characterization of the province with a vast number of built environment professionals. A total of seventy-five respondents partook in the study, aided by using purposive and snowball sampling techniques. Purposive sampling was employed to identify built environment professionals knowledgeable about sustainability assessment, while with the use of snowball sampling, the identified professionals helped in locating other professionals knowledgeable about sustainability assessment. The methods of data analysis deployed for the study were mean item score, standard deviation, and one-sample t-test. Cronbach’s alpha was used to evaluate the research instrument’s reliability and validity. The result of the test gave an alpha value of 0.836. This affirmed the reliability and validity of the questionnaire used for the study since the alpha value exceeds the threshold of 0.7 and gravitates towards 1.00 (Tavakol and Dennick 2011).

3 Results The study identified eleven challenges to implementing sustainability assessment in the South African construction industry. With a questionnaire, these challenges were presented to the target respondents for rating based on their significance. One-sample t-test was employed for the analysis of the retrieved data. Based on this, a hypothesis for framed for the study. The null hypothesis stated that a challenge is insignificant when the given mean score is less than or equal to the population mean (H0 : U ≤ U0 ), whereas for the alternate hypothesis, a challenge is significant when the given mean score is greater than the population mean (Ha : U > U0 ). The population mean (U0 ) fixed for the study is 3.50, while the challenges’ significance level was 95%; Pallant and Bailey (2005) affirmed that this is the conventional confidence level. The postulated hypothesis implies that when a challenge has a mean score above 3.50 is deemed significant, while a challenge having a mean score equal to or less than 3.50

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is deemed insignificant. The findings of the identified challenges, accompanied by their two-tailed p-values are presented in Table 1. Table 2 outlines the ranking of the identified challenges of implementing sustainability assessment in the South African construction industry. From the findings, it is revealed that all the challenges have a mean score above 3.50, the set threshold for the study. Hence, confirming the postulation of the study’s alternate hypothesis states that a challenge is significant when the given mean score is greater than the population mean (Ha : U > U0 ). Also, it is revealed that the p-values of the challenges are less than 0.05, thereby indicating that at a 95% confidence level, they are significant. Furthermore, the most significant challenges to the implementation of sustainability assessment in the South African construction industry are Low level of awareness (MIS = 4.68, sig. = 0.00); Lack of government support (MIS = 4.62, sig. = 0.00); Cultural barriers (MIS = 4.57, sig. = 0.00); Insufficient demand (MIS = 4.55, sig. = 0.00); High cost (MIS = 4.31, sig. = 0.00). Table 1 One-sample test Test value = 3.50 Leadership skills

T

df

Sig. (2-tailed)

MD

95% Confidence interval of the difference L

U

Lack of government support

2.362

74

0.000

0.528

0.5238

1.258

Cultural barriers

1.734

74

0.000

1.107

0.2291

1.139

Low level of awareness

5.551

74

0.000

0.771

0.3747

1.163

High cost

3.904

74

0.000

0.364

0.5374

1.207

Lack of building codes and 3.005 regulations

74

0.000

0.229

0.7725

1.158

Failure to commit to environmental protection

1.782

74

0.000

1.002

0.6281

1.264

Insufficient demand

2.735

74

0.000

0.984

0.5002

1.406

Lack of implementation capacity

5.218

74

0.000

0.735

0.4174

1.327

Inadequate manufacturer support

3.735

74

0.000

0.528

0.8203

1.184

Unfamiliar assessment techniques

2.996

74

0.000

0.365

0.3846

0.974

Lack of regulatory framework

3.626

74

0.000

0.659

0.6637

1.265

MD: mean difference; L: lower boundary; U: upper boundary

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Table 2 Summary of t-test showing ranking of the challenges to the implementation of sustainability assessment Challenges

Mean

Std. deviation

Sig. (2-tailed)

Rank

Low level of awareness

4.69

0.467

0.000

1

Lack of government support

4.62

0.311

0.000

2

Cultural barriers

4.57

0.926

0.000

3

Insufficient demand

4.55

1.322

0.000

4

High cost

4.31

1.005

0.000

5

Lack of building codes and regulations

4.28

1.291

0.000

6

0.000

Lack of regulatory framework

4.06

0.458

Insufficient demand

3.98

0.537

Lack of implementation capacity

3.84

0.802

7 8

0.000

9

Unfamiliar assessment techniques

3.71

0.617

0.000

10

Failure to commit to environmental protection

3.63

0.885

0.000

11

4 Discussion of Findings The data received from the study respondents were analysed and the findings showed that the most significant challenge confronting the implementation of sustainability assessment in the South African construction industry is the low level of awareness. This is affirmed by Atanda (2019) noted that the level of knowledge and awareness of sustainability assessment plays a pivotal role in the drive of implementation. Also, the unavailability of information on products and tools serves as a hindrance resulting from a deficiency in knowledge for most stakeholder groups. Moreover, the lack of government support is shown to be one of the most significant hindrances to sustainability assessment for the built environment in South Africa. Hwang (2012) noted that the government’s provision of tax breaks and subsidies would serve as an incentive for the embracement and utilisation of the tools and practices of sustainability assessment. Also, the associated cost involved in implementing sustainability assessment is given to be significant from the study’s findings. Ebekozien et al. (2022) stated that the high initial cost associated with sustainability assessment tools deters stakeholders from pursuing its implementation, consequently serving as a hurdle for the propagation of sustainable construction.

5 Conclusion and Recommendations The implementation of sustainability assessment practices encourages the pursuit of a sustainable built environment. The study outlined the findings from the assessment of the challenges plaguing the uptake of sustainability assessment practices in the

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South African built environment. With aid of a questionnaire, the identified challenges were presented to the target respondents of the study for rating based on their significance. The study’s findings indicate that the most significant challenges to the uptake of sustainability assessment practices in the South African built environment are a low level of awareness, lack of government support, cultural barriers, insufficient demand, and high cost. Based on the findings, the study recommends that the government play an active role in propagating the acceptance of sustainability assessment practices by relevant stakeholders in the built environment. Tax cuts and subsidies should be put in place by the government to aid boost the implementation by stakeholders. Also, policies and laws that can aid in boosting the embracement of the practices of sustainability assessment should be enacted by relevant arms of government. Furthermore, regular sensitization by relevant bodies should be conducted as a medium for knowledge acquisition by stakeholders saddled with the responsibility of engaging in the use of sustainability assessment practices. This would help fill the current knowledge gap and low awareness of sustainability assessment with respect to built environment professionals.

References Addy M, Adinyira E, Danku JC, Dadzoe F (2020) Impediments to the development of the green building market in sub-Saharan Africa: the case of Ghana. Smart Sustain Built Environ 10(2):193–207. https://doi.org/10.1108/SASBE-12-2019-0170 Aghimien DO, Ikuabe MO, Aigbavboa CO, Shirinda W (2021) Unravelling the factors influencing construction organisations’ intention to adopt Big Data analytics in South Africa. Constr Econ Build 21(3):262–281. https://doi.org/10.5130/AJCEB.v21i3.7634 Atanda J (2019) Developing a social sustainability assessment framework. Sustain Cities Soc 44:237–252. https://doi.org/10.1016/j.scs.2018.09.023 Ebekozien A, Ikuabe MO, Awo-Osagie A, Aigbavboa C, Ayo-Odifiri S (2021) Model for promoting green building certification of buildings in developing nations: a case study of Nigeria. Prop Manag 40(1):118–136. https://doi.org/10.1108/PM-05-2021-0033 Ebekozien A, Aigbavboa C, Thwala WD, Amadi GC, Aigbedion M, Ogbaini IF (2022) A systematic review of green building practices implementation in Africa. J Facil Manag 22(1):91–107 Gibberd JT (2021) Transforming urban residential sites for improved sustainability, developing and accessing alternative configurations. Alive2Green Hoffman D, Huang L, Rensburg J, Yorke-Hart A (2020) Trends in application of Green Star SA credits in South African green building. Acta Structilia 27(2):1–29 Hwang BG, Tan JS (2012) Green building project management: obstacles and solutions for sustainable development. Sustain Dev 20(5):335–349 Ikuabe MO, Aghimien D, Aigbavboa C, Oke A (2023) Drivers of the adoption of zero carbon emission in buildings in South Africa. In: Duffy VG, Ziefle M, Rau P, Tseng MM (eds) Humanautomation interaction. Automation, collaboration, & E-services, 12, Springer, Cham, pp 565– 573 https://doi.org/10.1007/978-3-031-10788-7_31 Ikuabe MO, Oke AE, Aigbavboa CO (2020) Impact of contractors’ opportunism on construction project transaction costs: construction professionals’ perception. J Financ Manag Prop Constr 25(1):125–141. https://doi.org/10.1108/JFMPC-04-2019-0040 Liu TY, Chen PH, Chou NN (2019) Comparison of assessment systems for green building and green civil infrastructure. Sustainability 11(7):2117. https://doi.org/10.3390/su11072117

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Martin-Gonzalez R, Swart K, Luque-Gil A (2021) Tourism competitiveness and sustainability indicators in the context of surf tourism: the case of Cape Town. Sustainability 13(13):7238. https://doi.org/10.3390/su13137238 Nilashi M, Zakaria R, Ibrahim O, Majid M, Mohamad Zin R, Chugtai M, Zainal Abidin N, Sahamir S, Aminu Yakubu D (2015) A knowledge-based expert system for assessing the performance level of green buildings. Knowl-Based Syst 86:194–209 Pallant JF, Bailey CM (2005) Assessment of the structure of the hospital anxiety and depression scale in musculoskeletal patients. Health Qual Life Outcomes 3:1–9 Singh C (2018) Green construction: analysis on green and sustainable building techniques. Civ Eng Res J 4(3):107–112 https://doi.org/10.19080/CERJ.2018.04.555638 Tavakol M, Dennick R (2011) Making sense of Cronbach’s Alpha. Int J Med Educ 2:53–55 United Nations Environment Programme (2020) Global status report for buildings and construction. Towards a zero-emissions, efficient and resilient buildings and construction sector. London, 2–3 Wang N (2014) The role of the construction industry in China’s sustainable urban development. Habitat Int 44:442–450 Yudelson J (2007) The green building revolution. Island Press, Washington, DC Zenios M, Allen CJ (2016) The perceived barriers to the construction of green buildings in Nelson Mandela Bay, South Africa. In: 9th CIDB Postgraduate conference, 2–4 Feb, Cape Town, South Africa, pp 191–201

Research and Practice of Energy Saving Renovation Technology for Multi-zone Collaborative Network Operation of Central Air Conditioning Water System L. Z. Yang, Q. Wang, and J. Luo

Abstract In a modern public building, the energy consumption of central air conditioning has reached 40% to 60% of the total energy consumption of the building. In the central air conditioning system composed of multi-zone, due to the seasonal changes, temperature difference between day and night, and differences in the use environment of each zone, the operating load of equipment cannot reach the design load, forming a situation of “big horse pull a small carriage” with high energy consumption and low utilization rate. In order to reduce the energy consumption of central air conditioning, reduce carbon emissions and achieve carbon neutralization as soon as possible, the energy consumption mode of the central air conditioning water system with insufficient zone load and independent operation of each zone at the same time has been transformed into a multi-zone collaborative network operation mode. On the basis of not changing the original zone operation, the collaborative network operation function of high, medium and low zones has been increased by the opening of valves which connected the zone pipe networks. Under the condition of full load operation of each zone, it operates in different zones. When the operation is not saturated, it will be converted to the collaborative network operation mode of high zone with middle zone and low zone, or the middle zone with low zone. It realizes the fast conversion between zone operation and multi-zone network operation, so as to achieve the purpose of energy saving and consumption reduction. This article verifies the feasibility of the energy-saving renovation technology for the multi zone collaborative network operation of the central air conditioning water system through the practice of three projects, including the Gansu Telecom Second Hub Project. Keywords Energy saving · Renovation technology · Collaborative network operation · Central air conditioning · Water system

L. Z. Yang · Q. Wang · J. Luo NO. 7 Construction Group Corporation of Gansu Province, Gansu, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_22

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1 Introduction Air conditioning refers to the equipment that adjusts and controls the humidity, temperature and other parameters of the ambient air in the building by artificial means to meet the comfort of human body. Central air conditioning is a system form that centrally handles the air conditioning load. The cold (heat) generated by the air conditioning unit is trans-ported to each room through a certain medium to meet the air conditioning needs of large public buildings [1]. Central air conditioning is widely used in residence, hotel, office building, shopping mall and other places to improve the comfort of people’s living and working environment [2–4]. In order to meet the air conditioning requirements of different zones in the building, the air conditioning design of the building generally adopts the multizone scheme, that is, ac-cording to the high, medium and low zones of the building respectively set up air conditioning systems. In the central air conditioning water system composed of multi-zone, especially in the northwest of China, due to the seasonal changes, temperature difference between day and night, and differences in the use environment of each zone, the operating load of equipment cannot reach the design load, forming a situation of “big horse pull a small carriage” with high energy consumption and low utilization rate. In order to reduce the energy consumption of central air conditioning, reduce carbon emissions, and achieve carbon neutralization as soon as possible, we have carried out re-search on the situation that the load of each zone of central air conditioning is insufficient, resulting in high energy consumption of equipment. We hope to achieve network operation between zones through technical means, give full play to the working efficiency of single equipment, so as to reduce the overall energy consumption index of unit building.

2 Feasibility Study 2.1 Preliminary Study According to the types of media used by the central air conditioning to carry indoor load, the central air conditioning can be divided into four categories: all-air system, all-water system, air–water system and refrigerant system. All-air system means that the indoor cooling (heating) load is fully borne by the treated air. More air is needed to achieve the effect, so a large cross-section air duct or high wind speed is required. The system is expensive and noisy. All-water system means that the heat and humidity load in the room is completely borne by water as the cold (hot) medium. However, the water can only solve the problem of residual heat and residual humidity, cannot solve the problem of ventilation, so it cannot be used alone.

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Air–water system means that the indoor cooling (heating) load is borne by new fan and water. This system is economical, practical and widely used in the market. Refrigerant system means that the evaporator of the refrigerant system is placed indoors directly to absorb residual humidity and heat. It is usually used in local air conditioning units with dispersed installation. However, because the refrigerant pipeline is not convenient for long-distance, it is not suitable to be used as a central air conditioning system. To sum up, the all-air system, all-water system and refrigeration system are not widely used in the market due to their own conditions. At present, the central air conditioning with the air–water system as the medium to bear the indoor load is widely used in the market. The system is mainly composed of refrigeration compressor system, refrigerant (freezing and hot) circulating water system, cooling circulating water system, coil fan system, cooling tower fan system and so on. The refrigeration compressor unit compresses the air conditioning refrigerant (refrigerant medium such as R134a, R22, etc.) into liquid through the compressor and then sends it to the evaporator. The freezing circulating water system pumps the normal temperature water into the evaporator coil through the freezing water pump for indirect heat exchange with the refrigerant, so that the original normal temperature water becomes low temperature frozen water. The frozen water is sent to the cooling coil at the air inlet of each fan to absorb the air heat around the coil. The generated low temperature air is blown to each room by coil fan to achieve the purpose of cooling. After the refrigerant is fully compressed in the evaporator and the heat absorption process is completed, it is sent to the condenser to restore the atmospheric pressure state, so that the refrigerant releases heat in the condenser, and the heat released is taken away by the cooling water of the circulating cooling water system. The cooling circulating water system pumps the normal temperature water into the heat exchange coil of the condenser through the cooling water pump, and then sends the heated cooling water to the cooling tower. The cooling tower naturally cools it or spray-type forced air cooling it through the cooling tow-er fan, and carries out sufficient heat exchange with the atmosphere to make the cooling water return to the normal temperature for recycling. When heating is needed in winter, the central air conditioning system only needs to pump the normal temperature water into the coil of the steam heat exchanger through the cold and hot water pump (called the frozen water pump in summer). After the full heat exchange with the steam, the hot water is sent to the fan coil of each floor to provide the warm hot air to the user [1, 5, 6]. In this system, the cooling (heating) load is exchanged by water as the medium. At the same time, the circulating water system also needs to consume higher energy when working. When the cooling (heating) load is insufficient, the energy consumption of the circulating water system does not decrease. In a building with multi-zone central air conditioning, each zone operates independently, and the energy consumed cannot be ignored. According to incomplete statistics, in a modern public building, the energy consumption of central air conditioning has reached 40–60% of the total energy consumption of the building. The system diagram before trans-formation of each zone is shown in Figs. 1, 2 and 3.

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Fig. 1 Air conditioning system diagram of low zone before transformation

Fig. 2 Air conditioning system diagram of medium zone before transformation

Through the study of the multi-zone central air conditioning system, it is shown that the original system is transformed into the multi-zone collaborative networking mode by connecting the zone pipe network and controlling the opening of the control valves between the pipe networks without changing the original independent operation mode of each zone, so as to increase the collaborative networking operation function of high, medium and low zones. When each zone is running at full load, it works in the mode of independent operation of each zone. When the operation of a certain zone is not saturated, it is a feasible scheme to convert to cooperative

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Fig. 3 Air conditioning system diagram of high zone before transformation

network operation, to realize the mutual conversion between the independent operation of the zone and the operation of the network system by taking the high zone with the medium zone, the low zone, or the medium zone with the low zone, and to stop the work of circulating pump, condenser and evaporator in the lower zone, so as to realize the purpose of energy saving and consumption reduction.

2.2 Theory of Technical Transformation According to the uneven operating load and insufficient operating load in the operation process of the central air conditioning system in the high, medium and low zones, the water system of the central air conditioning is taken as the main technical means to transform the water system of the central air conditioning. By setting the connecting pipe and control valve between the water systems in each zone, the water system with low working pres-sure is connected to the water system with high working pressure through the opening and closing of the control valve. The zone with high working pressure drives the zone with low working pressure to network operation, forming a variety of networking modes of high zone with medium zone, high zone with low zone or medium zone with low zone. At the same time, stop the work of the central air conditioning host in the lower zone, so as to achieve the purpose of energy saving and consumption reduction.

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2.3 Principle of Technical Transformation The structural form of the original water system in each zone will not be changed, and only the connecting pipe and control valve will be reasonably set at the appropriate position. By controlling the opening and closing of the valve, the connection between the zones can be closed when the zones are running at full load. Each zone operates independently ac-cording to the original mode of independent operation of each zone. Also, when the operating load of each zone is insufficient, the connection between the zones can be opened. According to the original mode of cooperative operation of each zone, each zone can operate in network to meet the demand of each zone for environmental comfort.

2.4 Applicable Scope of Technical Transformation This technology is only applicable to the central air conditioning system with multizone and air–water as the indoor load medium.

3 Engineering Application After preliminary research and demonstration, our company has carried out effective technical transformation on the central air-conditioning system of Gansu Telecom Second Hub Project, The First Hospital of Lanzhou University and Longneng Hotel.

3.1 Process Schematic Diagram The network operation system diagrams of high and medium zones, high and low zones and medium and low zones are shown in Figs. 4, 5 and 6.

3.2 Key to Technical Transformation 3.2.1

Reasonable Connection and Setting of Control Valves

Select the appropriate pipeline location and reasonably connect the circulating water sys-tem in high, medium and low zones, and set control valves. Generally, the expansion pipe above the water collector in the high working pressure zone is set with a tee to connect to the front of the pressure relief valve installed in the main return connection pipe, and in-stall control valves. Control valves are also installed on the

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Fig. 4 Network operation system diagram of high and medium zones

expansion pipe of the water collector in each networking zone. By controlling the opening and closing of the valve to realized the state transformation between network operation and zone operation. When each zone is networked, the valve above the water collector is closed, and the valve in-stalled after the tee is opened, so that the water of the circulating water system in the lower zone enters the return water system in the higher zone through the expansion tube and pressure reducing valve, so as to realize the network operation between the lower zone and the higher zone. When the original zones need to operate independently, close the valve installed after the tee, open the valve above the water collector, and each zone will resume independent operation.

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Fig. 5 Network operation system diagram of high and low zones

3.2.2

Reasonable Adjustment and Control of Working Pressure

During network operation, the working pressure is adjusted and controlled to maintain the original working pressure of the water supply pressure in the higher zone, and the pressure sent to the main water supply pipe in the lower zone is reduced to the original water supply pressure. The return water pressure in the higher zone will be adjusted to the same pressure as the main return water pipe in the lower zone before entering the water collector, and the return water working pressure in the original lower zone will remain unchanged.

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Fig. 6 Network operation system diagram of medium and low zones

3.2.3

Using Rubber Damping Throats to Avoid Damage to the Pipe Network

The rubber expansion joint is used to eliminate the internal stress caused by the pressure difference during the networking of zones and avoid the damage to the pipe network. At the same time, the adjustable pressure reducing valve is used to depressurize the water supply from the outlet of the circulating pump in the higher zone and then enter the water supply system in the lower zone, and then the adjustable pressure reducing valve is in-stalled on the return pipe in the higher zone to depressurize the return water and then enter the water collector or the suction port of the circulating pump.

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3.3 Specific Operational Key Points for Renovation Construction 3.3.1

Determination of Connection Position and Opening of Water Supply and Return Pipe Network

The opening position of the water supply pipe in the network zone is 0.5–1.0 m above the main outlet pipe of the water distributor in the high (medium) zone, and then 0.5–1.0 m above the main outlet pipe of the water distributor in the medium (low) zone. The opening height should be easy to operate and does not hinder the maintenance personnel of the equipment room. The opening position of the water return pipe in the network zone is 0.5–1.0 m above the water return main pipe of the water collector entering in the high zone (medium zone), and then open at 0.5–1.0 m above the water return main pipe before the water collector entering in the medium zone (low zone). It can also be connected in the horizontal pipe of the suction inlet of the zone pump at 0.5 m away from the valve. The size of the pipe opening is based on the network pipe diameter required by the drawing design or construction scheme. First, make the template according to the pipe diameter, then mark and draw the line at the opening according to the template, and then use the gas cutting tool to open.

3.3.2

The Transformation of Expansion Pipe System After Networking

After the high (medium) and low zones are networked, the expansion water is completed by the high (medium) zone expansion water pipe. The original low zone expansion water pipe is installed with a stop valve with the same diameter as the water make-up pipe in front of the low zone water collector. It is closed when the network is running, and the water make-up can be opened when the original zone system function is restored. At the same time, open a connection point on the expansion pipe in the high (medium) zone, and lead the expansion pipe to the front of the adjustable pressure reducing valve installed on the air conditioning return pipe in the high (medium) zone, so as to ensure that the expansion pipe in the high (medium) zone also enters the network system after pressure reduction, and install a valve with the same pipe diameter, which will be opened during network operation and closed during zone operation.

3.3.3

Water Pressure Test and Flushing of the System After Networking

After the completion of networking construction, the valve of the connecting pipe section is closed during the water pressure test, and the zonal pressure is carried

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out first. The regulating knob of the reducing valve should be relaxed in the high or medium zone to prevent the excessive pressure from damaging the reducing valve, and then the networking pressure is carried out. The strength and tightness test should be carried out in accordance with the specifications. The system should be flushed repeatedly until the water quality is the same before and after flushing. The circulating pump can be started after filling with water, and the water can be circulated, drained and replenished at the same time, and the drain valves of the water collector are all open [7, 8].

3.4 Debugging of System Network Operation Before debugging and operation of the system, it is necessary to check in detail whether the connecting valves are closed and opened as required [7, 8]. When filling water into the system, loosen the adjusting nut on the top of the pressure reducing valve to ensure that the water in the high (medium) zone can enter the low zone smoothly. After confirming that the high (medium) and low zone systems have been filled with water and the air at the highest point has been exhausted, tighten the nuts for commissioning [7, 8]. After the system is running, the water supply pressure reducing valve should be debugs first. The regulating nut of the pressure reducing valve should be relaxed slowly. Pay attention to the pressure gauge before and after the valve, and pay attention to the pressure gauge after the valve display data to reach the low working pressure zone immediately stop adjusting. Then use the same method to adjust the adjustable pressure reducing valve for the return water in the high (medium) zone, and adjust the pressure behind the valve to the working pressure of the return water in the same medium (low) zone [7, 8]. After debugging and operation of the system, observe the control panel of the refrigeration After debugging and operation of the system, observe the control panel of the refrigeration compressor after the water separation and collection pressures of high (medium) zone and medium (low) zone up to the design pressure. Then observe the outlet temperature and re-turn water temperature of the refrigerator, and set the refrigeration temperature at the de-sign temperature or the required temperature. After 24 h operation reaches the design tem-perature, it can be put into normal operation [7, 8].

4 Effect After Transformation After the statistical analysis of the electricity consumption of the three projects before and after the transformation, it is found that the daily electricity cost of the second hub project of Gansu Telecom is about 13,072 yuan before the transformation, and about 7224 yuan after the transformation. Before the transformation, the daily electricity

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cost of the first hospital of Lanzhou University is about 10,230 yuan, and after the transformation, it is about 6372 yuan. The daily electricity cost of Longneng Hotel before the transformation is about 15,466 yuan, after the transformation, it is about 12,355 yuan. Compared with the original multi-zone independent operation, the network operation can reduce the electricity cost by 20–45%, and the economic benefits are very obvious.

5 Conclusion The energy-saving transformation technology of the central air conditioning water system with multi-zone network operation can better save energy consumption, especially for the public buildings with unbalanced air conditioning demand and low load in each zone, its economic benefits are more obvious. The construction of the energy-saving transformation technology of the multizone net-work operation of the central air conditioning water system is not only short in construc-tion period and low in cost, but also can reduce the operation of a set of main equipment after the multi-zone network operation. At the same time, due to the short operation time of the equipment, it can further reduce the maintenance cost and the labor intensity of the maintenance personnel. The energy-saving transformation technology of the central air conditioning water system with multi-zone network operation is helpful to protect the ecological environment, reduce carbon emissions and realize carbon neutrality as soon as possible.

References 1. Wang SG (2006) Technical manual of air conditioning and refrigeration. China Machine Press, Beijing 2. LI JW (2016) Research on optimization technology for energy saving operation of air conditioning water System. Xi’an: Xi’an University of Architecture and Technology 3. Zhang L (2013) Research on the energy-saving improvement of a certain central air-conditioning system. Harbin Institute of Technology, Harbin 4. Peng XL (2012) Optimization for central air conditioning system and research on energy saving of the water system. Hebei University of Science and Technology, Hebei 5. He YD, He Q (2006) Appropriate technology of central air conditioning. Metallurgical industry press, Beijing 6. Wu JH, Li ZZ (2006) Design and construction of central air conditioning engineering. Higher Education Press, Beijing 7. (2002) Code of acceptance for construction quality of ventilation and air conditioning works (GB52243-2002). China Planning Press, Beijing 8. (2011) Code for construction of ventilation and air conditioning(GB50738-2011). China Architecture & Building Press, Beijing

Application of Circular Economy in Facility Maintenance and Management: Moving Towards a Low Carbon Future Qi Wu

Abstract The study explores the potential of integrating principles of the circular economy into facility maintenance and management towards sustainable development. With the environmental pressures associated with industrialization and the over-reliance on non-renewable energy sources, there is an urgent need for strategic changes in facility management. This paper details the principles of the circular economy—closed-loop design, efficient resource utilization, and viewing waste as a resource, and their application in the context of facility maintenance and management. Using a combination of theoretical analyses, case studies, and quantitative methods, the study provides a comprehensive exploration of the benefits and practical implications of adopting circular economy principles in facility maintenance and management. This includes improved resource efficiency, reduced carbon emissions, and waste minimization. The paper also includes an illustrative case study of Hong Kong’s Circular Modular Building Project and quantitative methods for measuring the effectiveness of facility maintenance and management. The findings suggest that the circular economy offers a valuable framework for creating a sustainable, low-carbon future in facility management. Keywords Circular economy · Facility maintenance and management · Sustainable development · Closed-loop design · Resource utilization · Waste management · Quantitative methods · Carbon emissions · Energy efficiency

1 Introduction In the global environment of the twenty-first century, the concept of circular economy is becoming an important consideration. The circular economy is an economic system whose goal is to achieve long-term sustainable development of the economy, society and environment by designing products and business processes to maximize resource Q. Wu (B) Faculty of Built Environment, University of Malaya, 5060 Kuala Lumpur, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_23

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utilization, reduce waste, optimize energy utilization, and promote effective recovery and reuse of resources [1, 2]. At the heart of the system is the concept of “closing the loop”—reducing, reusing, recycling and recycling materials to close the loop in the production and consumption process, thereby reducing environmental stress and improving the efficiency of resource use. The application potential of the circular economy principle in facility maintenance and management is huge. In facility management, we can adopt the concept of circular economy, design and implement a set of sustainable maintenance strategies to maximize the use of resources, reduce waste and reduce energy consumption while ensuring the long-term operation and maintenance of facilities [3]. For example, facilities can achieve circular economy principles through improved design, the use of recycled materials, the implementation of energy-efficient operational strategies, and the optimization of waste management processes [4]. Therefore, the application of circular economy in facility maintenance and management can not only help us achieve higher resource efficiency and lower carbon emissions but also provide us with a sustainable way of building and facility management to help us achieve sustainable social and economic development while protecting the environment. Global industrialization and over-reliance on non-renewable energy sources have led to an increase in solid waste and climate change, calling for a strategy of circular economy in all sectors to reduce carbon emissions by 45% by 2030 and become carbon neutral by 2050.

2 The Concept of Circular Economy Principles 2.1 The Importance of Closed-Loop Design Closed-loop design is a core element of the circular economy principle. This design philosophy emphasizes the consideration of environmental impacts at every stage of the product life cycle, including design, production, use and final treatment [5]. This way of thinking encourages us to take a thorough look at products and systems to identify potential efficiencies and waste reduction opportunities. In facility maintenance and management, closed-loop design practices can include the use of renewable and recyclable materials, the design of energy-efficient facilities, and the implementation of effective waste management strategies. This design strategy helps to reduce the facility’s environmental footprint and improve resource efficiency while reducing operating and maintenance costs.

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2.2 Means of Efficient Use of Resources Efficient use of resources is another key strategy to realize a circular economy. This involves reducing the consumption of resources as much as possible in the design, construction and operation of facilities while maximizing the efficiency of resource use [6]. Some specific practices include: using efficient energy systems to reduce energy consumption, choosing renewable and recyclable materials to reduce resource consumption, and implementing effective waste management strategies to reduce waste generation. Through these methods, facilities can maintain efficient operations while minimizing their impact on the environment.

2.3 Waste as a Resource Perspective In the idea of a circular economy, waste is seen as an underused resource rather than just a problem to be treated and disposed of. In facility maintenance and management, this means that we need to change the traditional view of waste as a valuable resource that can be recovered and reused [7]. For example, construction waste can be converted into new building materials through regeneration and recycling processes, while wastewater and waste gas can also be converted into valuable resources through specific treatment processes [8]. Through this shift in perspective, we can develop new solutions to manage and use waste in a more sustainable and efficient way. By understanding and applying the principles of the circular economy, we can achieve greater resource efficiency in facility maintenance and management, reduce carbon emissions, and at the same time, move the building industry towards a more sustainable and low-carbon future.

3 Application of Circular Economy in Facility Maintenance and Management 3.1 Manage Policy and Process Improvement In facility maintenance and management, the implementation of the principle of the circular economy needs to make corresponding improvements in the strategy and process. For example, maintenance strategies can emphasize the use of durable and repairable materials to extend the life of the facility and reduce the frequency of replacement required. In addition, management processes can be optimized for more efficient use of resources and waste reduction, such as optimizing energy use at facilities or improving waste management processes and waste reduction through recycling and reuse [9].

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3.2 Sustainability Improvements in Facility Design At the facility design stage, the principles of circular economy can be used to guide the sustainable improvement of the facility. This includes choosing renewable and recyclable building materials, designing efficient energy systems, or considering the environmental impact of a facility over its life cycle. For example, green building design may include the use of solar or wind energy systems, the installation of energy-saving equipment, or the use of water-saving technologies [10]. Through these design improvements, the facility can use resources more efficiently, reduce waste, and lower carbon emissions, while improving the economics of the facility.

3.3 Waste Management and Efficient Use of Renewable Resources In facility maintenance and management, waste management and efficient use of renewable resources are key aspects of realizing the principle of the circular economy. This includes implementing effective waste separation and recovery procedures to ensure that waste can be properly sorted, recycled, reused or recycled. In addition, facilities can also use renewable and sustainable resources, such as using renewable materials for facility maintenance or using renewable energy for power supply [11]. These strategies can not only help facilities reduce waste and carbon emissions but also improve the efficiency of resource use, thus reducing operating costs.

4 Quantitative Application of Circular Economy in Facility Maintenance and Management 4.1 Algorithms to Optimize Energy Use Efficiency of Data Centre Cooling Facilities In this part, we offer a comprehensive building evaluation method that uses a hybrid model created from the gathered data to apply a single-agent deep reinforcement learning technique to existing data centres in order to increase their energy efficiency [12]. The goal is to assess if a deep reinforcement learning agent can help a data centre use less energy. PUE (Eq. 1) is frequently used as a benchmark indicator to compare data centre performance. The measure used to assess data centre performance is chosen in accordance with the research topic. Power usage efficiency (PUE) and HVAC efficiency indicators were employed in this study because energy efficiency was the focus. As a result, (Eq. 2)’s HVAC efficiency index is also utilized to assess the efficacy of the air

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conditioning system. A lower figure implies greater room for improvement in energy efficiency, whereas a higher value denotes superior performance. A baseline value of 1.4 denotes acceptable performance, whereas 2.5 denotes greater performance. This is the value recommended by the National Renewable Energy Laboratory in the Best Time to Design for Energy Efficiency guide [13]. Additionally, huge data centres that employ chilled water systems typically function better. In a similar vein, we create the Power Efficiency Index (EEI), an indication comparable to HVAC, as given in (Eq. 3). IT equipment’s utilization of the entire power provided to it is evaluated by EEI. A value of 1 indicates perfect power transmission with no loss recorded. Finally, (Eq. 4) defines the server equivalent junction temperature, TS Ns represents the number of available servers, c p,a is the specific heat capacity of air, and Rs The equivalent crust thermal resistance is determined by experience, with a specified value of 0.065 J/K. These values define whether the data centre can effectively maintain servers within the specified range for optimal performance. Total Facility Energy IT Equipment Energy

(1)

Annual IT Equipment Energy Annual HVAC System Energy

(2)

IT Chain Loss + IT Equipment Energy IT Equipment Energy

(3)

PUE = HEI = EEI =

Ts = Tin +

Tout − Tin − Rs ×N1s ×cp,a

1−e

(4)

4.2 Formulas and Calculations for Quantifying the Effectiveness of Facility Maintenance and Management Preventive maintenance effectiveness may be evaluated in a number of ways, and each organization may use a different method. The next section outlines some common preventive maintenance metrics. The percentage of time spent on scheduled and unscheduled maintenance in a specific period of time is called the maintenance percentage (PMP). You can easily check how your maintenance time is being spent with this straightforward measure. In this equation, pay close attention to the word plan. Other forms of proactive maintenance, such as predictive maintenance, should be included here, even if preventive maintenance may make up the majority, if not the entirety, of scheduled maintenance. Divide the total number of planned maintenance hours by the sum of scheduled and unscheduled maintenance hours to obtain the scheduled maintenance percentage.

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(Eq. 5) then multiplies the result by 100 to provide the percentage. You may find out from the PMP how much maintenance work is planned ahead of time and how much time is spent responding to asset problems. Typically, a low PMP (meaning little time is spent on planned maintenance) indicates that an asset may be unreliable and more vulnerable to unplanned outages. Assets assumed to have a high PMP typically face fewer unexpected problems. PMP =

(Planned Maintenance Hours) × 100 (Total Maintenance Hours)

(5)

If preventative maintenance is not done, it is ineffective. Here comes the role of the following preventive maintenance effectiveness indicator. Preventive maintenance compliance (PMC) counts the number of planned preventive maintenance work orders that are finished within a specific time frame. It can show how effectively your PM programme is working and whether the PM schedule is being followed. Equation 6: To calculate the percentage of preventive maintenance compliance, divide the total number of completed preventive maintenance work orders by the total number of scheduled work orders during that time period. Then, multiply the result by 100. Please take note that only work orders that were initially scheduled to be finished within this time limit should be counted as scheduled and completed. PMC =

(Number of Completed PM Work Orders) × 100 (Number of Scheduled PM Work Orders)

(6)

A significant amount of PMS being missed, or a high missed PM number, points to a potential issue that requires more investigation. First, it acts as a gauge of how well the maintenance crew and the party requiring maintenance communicate. For instance, scheduling problems with the production team or renters could prevent the maintenance of an asset. With other departments or individuals, the CMMS can exchange and discuss maintenance plans more simply. Preventive maintenance is performed far too frequently, which is another potential explanation for the high Skipped PM number. Ineffective downtime, labour expenses, and part use occur from performing preventative maintenance on undesirable equipment. It also raises the possibility of decreased dependability as a result of faulty reassembly or other mistakes. Preventive maintenance software makes it easy to change and fine-tune PM schedules. The impact of postponing planned maintenance is measured by the planned Maintenance Critical Percentage (SMCP). This statistic makes it simpler to choose which PM works to do first by quantifying the risk associated with outdated preventive maintenance work orders in relation to their work order cycles. Preventive maintenance that is put off increases the likelihood of breakdowns, their severity, and the maintenance backlog. Knowing what to do first when you are behind on preventative maintenance can be challenging. To simplify this choice, SMCP (Eq. 7) is essential.

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⎞ Number of Days the Work Order is Late ⎜ + Length of the PM Cycle (in days) ⎟ ⎟ ⎜ MCP = ⎜ ⎟ × 100 ⎝ Length of the PM Cycle (in days) ⎠

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⎛

(7)

4.3 Case Study and Validation Scheme of Circular Economy in Hong Kong. To save natural resources, enhance the efficiency of construction projects, and lower material waste, solid waste, and the environmental impact of construction projects [14], Hong Kong is encouraging modular buildings and CE. The adoptionmanufacturing-disposal LE legacy has been recast by CE as a closed-loop material production and building paradigm, allowing for resource and waste recovery and reuse. Reusing and recycling building materials is made easier by recycling design, which also keeps resources and building parts at their best intrinsic value for a longer length of time. It makes it possible for construction materials to continue to go through a cycle of usage, reuse, repair, and recycling. It thus decreases building waste and harmful externalities like CO2 emissions. The modular construction method offers a special way to successfully implement the CE principle since circular architecture demands the integration of circular principles into the design, construction, and deconstruction of structures. Individual integrated volume building components (i.e., modules) are finalized with finishes, fixtures and fittings in an off-site manufacturing setting before being transported to the construction site for installation. The Circular Modular Building Project (MCP) is a modular building project that adheres to CE principles in its design, administration, and construction. Recycling MCPS are planned and constructed to encourage resource conservation, maximize material recovery, and prevent the needless construction of landfills. Recycling MCPS design waste and pollution outside of the construction process reduces the ecological impact, safeguards the location, and preserves the ecology in the area. Because such circular MCPS present the excellent potential for the preservation and enhancement of natural capital, the optimum use of renewable resources, the design out of waste, and the facilitation of building materials, goods, and components to maintain repeated cycles so that they keep the best intrinsic value possible. Based on this case study, we designed an application that integrates the two sets of formulas into a single system to achieve more efficient resource management and environmental goals in modular building projects. This application contains four main modules: a data entry module, a calculation module, a results presentation module, and an optimization recommendation module. Users can enter necessary data such as total facility energy, IT equipment energy, annual HVAC system energy, and the number of PM work orders scheduled and completed. The application will

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then use this data to calculate the values for PUE, HEI, EEI, T_s, PMP, PMC and SMCP. The results of the calculations will be presented and may be compared to industry benchmarks or standards so that users can see how well they are performing. Finally, based on the calculation results, the application will provide optimization recommendations, such as how to increase energy efficiency or improve preventive maintenance programs. To verify the validity and reliability of this application, we propose a three-step validation scheme. First, we will select one or more existing modular building projects for field validation. We will collect the necessary data, input it into our application, and then compare the calculated results with the actual operational results. Second, we will invite experts in facility maintenance and patents to review our application and validate the results. Their expertise and experience will provide us with valuable feedback that will help us improve the application. Finally, once the application is deployed and in use, we will continuously monitor its performance, collect user feedback, and make adjustments and optimizations as needed. This application and validation program is designed to apply the principles of the circular economy more effectively to modular construction projects, resulting in resource savings, increased efficiency of construction projects, and reduced material waste, solid waste, and environmental impact of construction projects.

5 Conclusion From the perspectives of circular economy and sustainable development, facility maintenance and management face new challenges and opportunities. The closedloop design, efficient resource use, and a resource-focused perspective of waste under the circular economy model fundamentally change the way we maintain and manage facilities. The systematic integration of these principles into facility maintenance and management strategies helps to conserve resources, reduce waste and energy consumption, and increase the lifespan of the facilities. By embracing the principles of circular economy in facility design, including using renewable and recyclable materials and energy-efficient systems, we can construct and manage facilities in a more sustainable and responsible way. Applying these principles to waste management and resource utilization encourages the recycling and reuse of waste, promoting a more sustainable, efficient, and eco-friendly approach to facility management. Quantitative methods like the deep reinforcement learning approach and preventive maintenance indicators offer valuable insights for optimizing energy use efficiency and ensuring effective facility maintenance and management. Case studies, such as Hong Kong’s Circular Modular Building Project, also demonstrate the feasibility and benefits of integrating circular economy principles into facility maintenance and management. In conclusion, the circular economy provides a valuable theoretical framework and practical strategies for sustainable facility maintenance and management. As

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we continue to face environmental challenges and resource constraints, it’s more critical than ever to adopt these sustainable approaches in facility maintenance and management. By doing so, we can not only improve our resource efficiency and reduce carbon emissions but also drive our buildings and facilities towards a more sustainable, low-carbon future.

References 1. European Parliament (2015) Circular economy: definition, importance and benefits | News | European Parliament. https://www.europarl.europa.eu/news/en/headlines/economy/201512 01STO05603/circular-economy-definition-importance-and-benefits. Accessed May 25 2023 2. Velenturf PM, Purnell P (2021) Principles for a sustainable circular economy. Sustain Prod Consumption 27:1437–1457. https://doi.org/10.1016/j.spc.2021.02.018 3. O. US EPA (2016) Managing and reducing wastes: a guide for commercial buildings. https://www.epa.gov/smm/managing-and-reducing-wastes-guide-commercial-buildings. Accessed May 25 2023 4. Morseletto P (2020) Targets for a circular economy. Resour Conserv Recycl 153:104553. https://doi.org/10.1016/j.resconrec.2019.104553 5. Hapuwatte B, Jawahir I (2021) Closed-loop sustainable product design for circular economy. J Ind Ecol 25. https://doi.org/10.1111/jiec.13154 6. Purchase CK et al (2021) Circular economy of construction and demolition waste: a literature review on lessons, challenges, and benefits. Materials (Basel) 15(1):76. https://doi.org/10.3390/ ma15010076 7. Abdel-Shafy HI, Mansour MSM (2018) Solid waste issue: sources, composition, disposal, recycling, and valorization. Egypt J Pet 27(4):1275–1290. https://doi.org/10.1016/j.ejpe.2018. 07.003 8. O. US EPA (2016) Sustainable management of construction and demolition materials. https://www.epa.gov/smm/sustainable-management-construction-and-demolition-materials. Accessed May 25 2023 9. Lee HHY, Scott D (2009) Overview of maintenance strategy, acceptable maintenance standard and resources from a building maintenance operation perspective. J Build Apprais 4(4):269– 278. https://doi.org/10.1057/jba.2008.46 10. Akadiri PO, Chinyio EA, Olomolaiye PO (2012) Design of a sustainable building: a conceptual framework for implementing sustainability in the building sector. Buildings 2(2), Art. no. 2. https://doi.org/10.3390/buildings2020126 11. Negrete-Cardoso M, Rosano-Ortega G, Álvarez-Aros EL, Tavera-Cortés ME, Vega-Lebrún CA, Sánchez-Ruíz FJ (2022) Circular economy strategy and waste management: a bibliometric analysis in its contribution to sustainable development, toward a post-COVID-19 era. Environ Sci Pollut Res 29(41):61729–61746. https://doi.org/10.1007/s11356-022-18703-3 12. Mahbod MHB, Chng CB, Lee PS, Chui CK (2022) Energy saving evaluation of an energy efficient data center using a model-free reinforcement learning approach. Appl Energy 322:119392. https://doi.org/10.1016/j.apenergy.2022.119392 13. Bruschi J et al (2011) Best practices guide for energy-efficient data center design. Rumsey Eng Nat Renew Energy Lab 14. Wuni Y, Shen GQ (2022) Developing critical success factors for integrating circular economy into modular construction projects in Hong Kong. Sustain Prod Consumption 29:574–587. https://doi.org/10.1016/j.spc.2021.11.010

Sustainable Urbanism and Architecture

Study on Sustainable Urban Block Form for Urban Ventilation—Nanjing as an Example L. Yao, X. X. Yan, Z. K. Wu, Y. Shi, and B. Wang

Abstract In recent years, the issue of carbon emission has become increasingly important due to the intensification of the urban heat island effect and atmospheric pollution. Buildings, as a primary carrier of human activities, are significant sources of carbon emission problems in cities. The aim of this paper is to address the challenge of achieving carbon neutrality and building a sustainable urban environment from the perspective of urban and building ventilation. To achieve this goal, the study takes the wind environment research in Nanjing as the base point, and collects 3D physical model data of typical urban block samples in each district. A model library of different types of urban block morphological parameters in Nanjing city is then established, and CFD wind environment simulation technology is utilized to evaluate the wind environment of typical urban block samples in Nanjing city from 1.5, 5, 10, and 20 m, and analyzes the influence of different urban block morphological parameters on the urban block ventilation potential and explores the impact of different urban block morphological parameters from the urban perspective and pedestrian traffic. The analysis reveals the impact of different urban block form parameters on the ventilation potential of the urban blocks, and explores the urban and pedestrian scales to identify the urban block forms that are conducive to ventilation, to explore the potential to achieve carbon neutrality by improving carbon absorption and reducing carbon emission. In conclusion, this study provides valuable insights into the relationship between urban block morphological parameters and ventilation potential in the context of urban sustainability. By exploring the relation of different urban block designs to optimize ventilation and achieve carbon neutrality, this study offers guidance and reference for future sustainable new city construction and old city renewal. Ultimately, by prioritizing urban block designs that promote ventilation and air quality, we can build more livable and sustainable cities. Keywords Residential block form · Wind potential · CFD simulation

L. Yao · X. X. Yan · Z. K. Wu · Y. Shi · B. Wang Gold Mantis School of Architecture, Soochow University, Suzhou, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_24

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1 Introduction 1.1 Research Background With the intensification of global climate change and carbon emissions, carbon neutrality is increasingly important globally, including in China. Due to the fact that cities are the primary source of carbon emissions, meanwhile the buildings are the primary carrier of human activity, the construction of numerous buildings will inevitably worsen these emissions and have an impact on the city’s ventilation system, which will lead to the urban heat island effect, air pollution, and an increase in building energy consumption. As an important hub city in eastern China, Nanjing also has environmental and climate issues. The city of Nanjing has already made considerable strides toward carbon neutrality. During the process of achieving carbon neutrality, we could not only make reduction in the energy consumption of the city or rely on the transformation of the energy structure, it is also vital to concentrate on urban ventilation, which can reduce the amount of CO2 that accumulates in the city, promoting air circulation between the city and the suburbs, and increasing the carbon sink by photosynthesis of plants in the suburbs.

1.2 Current Status of Domestic and International Research It’s well known that urban planning and design have great impact in urban wind environment (Bottema 1993; Gao and Lee 2012; Liu et al. 2022). International researchers have used computer-aided simulation to examine the natural ventilation capacity of building layouts under various settings and wind environment features. Li et al. (2003) discovered that enclosed homes had a detrimental impact on natural ventilation. Liu et al. (2015) used the wind speed ratio and age of air as comprehensive evaluation indices to examine the benefits and drawbacks of four popular residential layout techniques in Changsha. 20 residential modules in Tianjin were chosen by Suiping Zeng et al. (2019) to investigate the necessary residential combination patterns for structures in various surroundings. Residential block form is proved to have close interaction with wind potential (Sanaieian et al. 2014; Wang et al. 2022). However, few studies focused on how communities’ architectural designs affect the wind environment, and sample sizes were insufficient, leading to limited recommendations. Therefore, current guidance is not perfect.

1.3 Significance of the Study (1) Improve the living environment

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The stability and sustainability of the living environment may be impacted by natural disasters and ecosystem collapse brought on by climate change brought on by carbon dioxide emissions. People are paying more attention to ventilation and environmental issues in buildings and blocks as a result of the current climate and environmental issues, which are hazardous to human health. It is crucial to improve air flow in order to dilution and degradation of carbon dioxide and pollutants in the air. In order to improve natural ventilation and lessen carbon footprint, this study outlines the relationship between urban block form and wind speed through data collecting and simulation analysis. (2) Optimize architectural design By creating a parametric model library, the study assesses the relationship between urban block morphology and wind environment. This will become a carbon–neutral technology. It could help guide the renovation of existing cities and the construction of new ones, and also help improve residential area design and environment by integrating specific building morphology coefficients to make them more livable, secure, and environmentally friendly. (3) Reduce Urban heat island effect Due to increased energy demand for air conditioning and other equipment as a result of the urban heat island effect, cities may experience greater temperatures, which will increase carbon emissions. The increase in urban ventilation that results from an improvement in the local wind environment contributes to the carbon neutrality by decreasing the development of urban heat islands. (4) Make full use of natural resources A significant amount of carbon dioxide from the city is transported to the suburbs through urban ventilation, where it is used by suburban plants for photosynthesis to break it down into organic matter and release oxygen, lowering the amount of carbon dioxide in the atmosphere and preventing climate change. This can improve the coordination and cooperation between urban and rural environmental management, improve the creation and maintenance of urban ecosystems, and ultimately help achieve the goal of carbon neutrality.

2 Research Methodology This project creates a model library of urban block morphology with wind environment parameters in Nanjing using field and network data collection methods and CFD technology. It aids in assessing wind environments, transforming old urban blocks, and optimizing new block construction. The approach has advantages in urban planning and promising research potential.

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2.1 Map Data Acquisition Using mapping software, residential areas with typical morphology in each urban area of Nanjing were screened, and the plan forms were extracted and drawn in Autodesk CAD, and other graphic data such as building heights and elevations were collected according to field research and live maps for later physical model simulation and morphological coefficient collation.

2.2 CFD Software Simulation Based on the data collection, the primary software selected for this research is VENT, one of green building simulation tool given by GBSWARE company. The fundamental formula of fluid dynamics, such as the law of conservation of momentum, the law of conservation of flow mass, the law of conservation of energy, etc., serve as the foundation for CFD principles. CFD can forecast the dynamic properties of fluid motion (wind environment) by numerically resolving these equations and taking into account the interplay between fluid and solid interfaces.

2.3 Morphological Index Analysis A set of measures called Architectural Form Indicators (AFIs) is used to evaluate the shape of a building’s exterior. They discuss topics like geometry, scale, proportion, and the arrangement of buildings. The evaluation of building shapes can be used as the basis for an analysis of the variations in their wind environment. After collecting map data to create plans for typical Nanjing blocks, morphological indicators are utilized to evaluate the physical model data with analytical parameters.

3 Experimental Data and Simulation Conditions Setting 3.1 Sample Selection We chose 20 urban blocks from each district in Nanjing for the study using a scattered sampling technique (see Fig. 1 for an axonometric map). Of these, 3 are multi-storey residential buildings, 4 are mid-rise residential buildings, and 13 are high-rise residential buildings. They are mostly situated in urban high-density building clusters

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with more serious urban heat island issues. We have compiled urban morphological parameters that are highly connected with wind environment parameters from physical models of their neighbourhoods: block plot area (Area), building coverage ratio (BCR), floor area ratio (also called plot ratio, PR), typical building height (H0 ), average building height (H ), standard deviation of building height (σh ), coefficient of variation of building height (σh /H), average building volume (Vb), relative roughness (Rr), full height to width ratio (λc ), porosity (Po), average building width (W), building aspect ratio (L/W), average distance to height ratio in the vertical section of the building (D/H), minimum distance ratio (D/Hmin ), and number of typical building stories (N0 ). For detailed information on the indicators, see Wang et al. (2017). For better evaluation of an overall presentation, different type of urban block form is considered. The randomness of the selected samples is visible according to the radar plot (Fig. 2).

Fig. 1 Morphological map of 20 urban blocks in Nanjing

Fig. 2 Intercomparison radar map of selected urban block morphology parameter values

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3.2 Modeling the Wind Field (1) Wind field size To control the variables, the same beginning wind environment circumstances for each block model were employed. The inlet wind speed use summer wind which was selected as the wind field to deal with the urban heat island problem. The typical summer wind speed in Nanjing is 3m/s. We use it as the specified wind speed applied to the gradient wind function. (2) Wind field boundary The morphology of the building complex, the Building Ventilation Effectiveness Test and Evaluation Standard JGJ/T 309-2013, as well as data and guidelines from domestic and international research, are used by VENT to automatically calculate the wind field boundary. (3) Wind field direction Considering that in urban high-density building complexes, the wind direction has multi-directional characteristics due to the interference of the surrounding dense building complexes, we establish a 360° all-round wind field every 45° in VENT in order to more comprehensively analyze the response to the high-density building clusters Ventilation problems. (4) Calculation parameters We chose the calculation parameters of general accuracy (medium speed) for this experiment, i.e., they are suitable for the case where they are used to simulate building ventilation and obtain better calculation results, and the specific simulation parameters are set as in Table 1. Table 1 The specific simulation parameters setting Parameter settings number of iterations Initial grid

Iteration number

Arc division precision

0.18 m

Initial grid

8m

Minimum number of subdivisions

2

Maximum number of subdivisions

3

Ground grid

Far-field number of subdivisions

2

Near-field number of subdivisions

3

Surface layer

Number of layers on ground

4

Number of layers on building surface

1

500

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4 Experimental Results and Analysis 4.1 Average Wind Speed Analysis The general ventilation potential of each block model was evaluated using a general wind simulation that did not account for the local impacts of each model under its unique climatic circumstances. Eight times total, the simulation was run with a 45° angle every time, and the findings were examined. The wind speed contour for the north wind is shown in Fig. 3 plotted on a horizontal plane at a height Z = 10 m above the ground. The average wind speed standard deviation is collected after normalization by gathering the mean wind speed for each model with simulations at various heights from the ground (1.5, 5, 10, and 20 m). Table 2 displays the findings of an average of eight simulations with various wind directions for each block model. Some general results and deduction from the simulations can be drawn as below: I. After averaging each wind direction, the percentage of low wind speed zones (V ≤ 1m/s) is determined, and it is lower when the average building height of the block is higher. The blocks with the lowest average building height are D13, D14, and D19, which also have the highest overall low wind speed percentage among all blocks;

Fig. 3 Simulated wind speed results for the selected block (Z = 10 m, north wind inlet)

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Table 2 The Average wind speed score ranking D1

D2

D3

D4

D5

D6

D7

D8

D9

D10

Score

0.51

0.32

0.40

0.71

0.96

0.87

0.71

0.64

0.43

0.39

Ranking

11

15

13

4

3

2

5

7

12

14

D11

D12

D13

D14

D15

D16

D17

D18

D19

D20

Score

0.62

0.68

0.31

0

1

0.56

0.59

0.25

0.44

0.28

Ranking

8

6

16

20

1

10

9

18

19

17

II. The standard deviation of the mean wind speed for each wind direction can be used to assess the reliability of the wind field in the selected area. Because of the multi-directional nature of wind speed within the city, if the block can only adapt to a specific wind direction, its wind field environment is unstable, the mean wind speed in each wind direction varies widely, and the standard deviation of the mean wind speed of the block is large. In contrast, the smaller the standard deviation, the more adaptable the block is to the wind field environment, and the greater the potential for perfect block form. III. The coefficient of variation of each wind direction at various heights in each block can be analysed. The majority of plots show the trend that the coefficient of variation increases with height. This suggests that the height is correlated with a rise in the mean wind speed for each wind direction. There still exist some exceptions: the typical building heights of D18, D19, and D20 do not exceed 20 m, and their dispersion coefficients at that height do not exhibit the anticipated pattern of rising dispersion coefficients at higher altitudes, but rather a sharp decline. Therefore, it can be concluded that higher heights within the model library below the typical building height have greater variation in mean wind speed in each wind direction. The average wind speed of each block at different heights was calculated, and the score of the average wind speed of each block was obtained through the principal component analysis of SPSS. A higher score indicates that the block has a better wind environment in the city. The score was standardized and sorted in Table 2, which shows that block D15 has the highest average wind speed score and block D14 has the lowest, the average wind speed of each block at various heights was calculated, and the average wind speed score of each block could be obtained by principal component analysis using SPSS.

4.2 Analysis of the Area Share of the Low Wind Speed Zone at Pedestrian Height To evaluate the evacuation capacity of carbon emissions in each block, the ratio of the low wind speed area to the total block wind field area in the wind speed contour

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map for each wind direction in each block near the pedestrian height (Z = 1.5 m) was calculated by C# with grasshopper. The results obtained from the eight wind directions are shown in Figs. 4 and 5. With results from Figs. 4 and 5, some findings can be given: I. After averaging the percentage of low wind speed zones for each wind direction, it can be seen that the percentage of low wind speed zones decreases the higher the block’s typical building height. The blocks with the lowest average building height are D13, D14, and D19, which also have the highest overall low wind speed percentage of any block.

Fig. 4 Average building height and low wind speed zone proportion average

Fig. 5 Percentage of the area of the low wind speed zone in each wind direction in each block

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Table 3 Ranking of the percentage of low wind speed zones Percentage Ranking

D1

D2

D3

D4

D5

D6

D7

D8

D9

D10

0.22

0.35

0.32

0.23

0.22

0.18

0.22

0.18

0.31

0.31

4

15

14

9

7

1

5

2

13

12

D11

D12

D13

D14

D15

D16

D17

D18

D19

D20

Percentage

0.30

0.22

0.44

0.51

0.23

0.26

0.21

0.48

0.44

0.40

Ranking

11

6

18

20

8

10

3

19

17

16

II. In all wind directions, D8 has the most evenly distributed percentage of low wind speed regions, with an average percentage value of 0.18. III. Some blocks (D13, D14, D18, D19, D20) account for less than 35% of the low wind speed area in the vast majority of wind directions. IV. From different wind directions, the north wind is the wind angle that accounts for the largest proportion of the low wind speed zone, and extra attention needs to be paid to the gathering of polluted air in this direction. In conclusion, it is demonstrated that as building height rises, the overall value of the low wind speed zone percentage will decrease. It is important to pay attention to avoid the issue of a higher percentage of the low wind speed zone under certain specific wind directions, in order to choose an appropriate block model. As shown in Table 3, D6 is ranked top and has the smallest share.

4.3 Correlation Analysis Between Block Morphological Coefficients and Wind Environment Parameters A Pearson correlation analysis between the morphological coefficients of urban blocks and two wind environment parameters—the average wind speed score and the percentage of small wind area—was first carried out in order to visualize the influence of each morphological coefficient on the wind environment (Fig. 6).

4.3.1

Correlation Analysis of Morphological Coefficients and Mean Wind Speed Scores

Pearson correlation coefficients between each mean wind speed score and the 16 block morphology coefficients, reflecting the strength of the correlation between the different morphology coefficients and the mean wind speed score and the percentage of area in the low wind speed zone. From strong to weak, the typical building height, average building height, typical number of stories, site density, average volume, and porosity are the morphological coefficients that have a strong association with

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Fig. 6 Correlation between block morphological coefficients and wind environment parameters

the average wind speed score. Site density is the only one of them that significantly correlates negatively with the average wind speed number; the others all do so positively.

4.3.2

Correlation Analysis of the Morphological Coefficient and the Percentage Score of Low Wind Speed Zone

Pearson correlation coefficients for the area share of low wind speed zones scores and 16 block morphology coefficients, reflecting the strength of the correlation between the different morphology coefficients and the area share of low wind speed zones scores. The area share of low wind speed zone is negatively correlated with the wind environment, so in order to more clearly illustrate how block morphology affects the wind environment, the Pearson correlation coefficients between the area share of low wind speed zone and each morphology coefficient are taken as the opposite of the correlation coefficients between the area share of low wind speed zone and the morphology coefficients. It is evident that porosity, building density, and typical building height are the area morphological coefficients with the strongest correlations, going from strong to weak. Building density and low wind speed zone area share score have a strong negative correlation, meaning that the higher the building density, the bigger the low wind speed zone area share, and the worse the wind environment. The remainder is the inverse.

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5 Conclusion For the urban neighbourhood form, the following two suggestions can be summarized in favour of carbon neutrality: I. The following factors should be prioritized when designers try to design a residential district from an urban perspective: typical building height, average building height, typical number of stories, site density, average volume, and porosity. These factors can improve urban ventilation more effectively and aid CO2 diffusion in urban high-density building complexes as well as better plant absorption outside of high-density building complexes, helping to offset the significant amount of CO2 currently produced by intensive human social activities. II. Porosity, building density, and typical building height should receive priority consideration at the pedestrian scale because they can more effectively improve natural ventilation to enhance comfort, which in turn reduces human activities like turning on air conditioners and addressing carbon emissions at the source by reducing carbon emissions and energy consumption. In conclusion, a focused combination of one or two of the above-mentioned points according to the actual situation can help improve urban ventilation in the urban design process. This paper focuses on how to enhance natural ventilation from building form, and these suggestions can be used as one of the scientific aids for designers to achieve carbon neutrality in future urban construction. In addition, designers can also combine other sustainable building design methods, such as passive house and zero-energy buildings, based on focusing on natural ventilation in neighbourhoods to achieve the goal of sustainable development. Acknowledgements This research was funded by National Key R&D Program of China (2021YFE0200100); The 2021 Jiangsu Construction System Science and Technology Project (2021ZD03).

References Bottema M (1993) Wind climate and urban geometry. Technology University of Eindhoven, Eindhoven Gao CF, Lee WL (2012) The influence of surrounding buildings on the natural ventilation performance of residential dwellings in Hong Kong. Int J Vent 11(3):297–310 Li XF, Zhang ZQ, Lin BR et al (2003) An experimental study on the microclimate of closed residential communities. J Tsinghua Univ (Nat Sci Ed) 12:1638–1641 Liu ZX, Han J, Zhou J et al (2015) Study on residential wind environment evaluation based on wind speed ratio and air age. Constr Technol 46(11):996–1001 Liu YS, Yigitcanlar T, Guaralda M et al (2022) Leveraging the opportunities of wind for cities through urban planning and design: a PRISMA review. Sustainability 14(18):11665

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Sanaieian H, Tenpierik M, Linden K et al (2014) Review of the impact of urban block form on thermal performance, solar access and ventilation. Renew Sustain Energy Rev 38:551–560 Wang B, Cot LD, Adolphe L, Geoffroy S, Sun S (2017) Cross indicator analysis between wind energy potential and urban morphology. Renew Energy 113:989–1006 Wang B, Geoffroy S, Bonhomme M (2022) Urban form study for wind potential development. Environ Plan B: Urban Anal City Sci 49(1):76–91 Zeng SP, Tian J, Zeng J (2019) Study on ventilation efficiency and optimized layout of typical residential modules based on CFD simulation. J Arch (02):24–30

Crack Detection of Masonry Structure Based on Infrared and Visible Image Fusion and Deep Learning Y. M. Lu, H. Huang, and C. Zhang

Abstract From the standpoint of protecting and repairing the ancient city walls, this work aims to improve the feasibility and accuracy of crack detection in the brick wall background. Data sets of cracks in the surface of the ancient city walls were created, including RGB and thermal images. By using deep learning techniques, the best combination of data input type and network architecture were explored in the CNNbased training framework. The main contribution of this paper is: (a) a comprehensive dataset of cracks in the background of ancient city walls, including RGB images and infrared images; (b) a comparative analysis of crack detection results of different data fusion methods under different deep learning networks. Based on the results, the optimal data input and training network combination were identified for masonry wall crack identification, which enables an automatic crack damage detection for ancient city wall. Keywords Crack detection · Masonry structure · Infrared and visible image fusion · Deep learning

1 Introduction The protection of ancient city walls is of great significance to the preservation of history and culture. The wall cracks caused by various natural environment and man-made factors are the main reasons for the collapse of the ancient city wall (Gordan et al. 2022; Loverdos and Sarhosis 2023a). Therefore, crack observation is an important concern for the protection of ancient city walls. The existing methods of intrusive observation and analysis of cracks will cause secondary architectural damage to the ancient city wall itself, and the resulting data are subjective and cannot really reflect the physical information of cracks (Hsieh and Tsai Yichang 2020), let alone the research and judgment of crack formation mechanism. In the later stage, with the development of photography and computer hardware and software Y. M. Lu · H. Huang · C. Zhang (B) Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_25

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technology, digital image technology came into being (Kassotakis and Sarhosis 2021; Loverdos and Sarhosis 2023b). It has the ability to achieve more accurate contactless detection and collect more comprehensive building information at a relatively low cost. What’s more, it can convert the image into digital signal with the calculation and processing software, evaluate the index of the processed data results, and provide the best data fusion scheme through accuracy comparison. In this case, image processing and deep learning based on computer vision provide a low-cost and non-contact fast solution for crack identification on the surface of brick wall (Mesquita et al. 2018; Dais et al. 2021). This technology realizes image capture through mobile platform, converts the collected and tracked image information into digital information through Computer Vision (CV) technology (Lee et al. 2013), and then builds an algorithm framework based on convolution neural network with the help of the huge building information database formed by regular collection (Gentile et al. 2016; Nicko et al. 2023). Obviously, this is more effective in predicting the development of structural damage and achieving prevention in advance, and can cover full-scale building information at less cost.

2 Methodology The proposed method mainly contributes to exploring the best combination of data collection and fusion, pixel-level manual labeling, neural network architecture, training methods, and loss functions. The total process is mainly composed of five main parts, namely, data acquisition, image preprocessing, manual labeling, neural network training and result evaluation. The following will carry out the specific process content description (Fig. 1).

3 Crack Image Acquisition The above methodology will be used in a case study of crack detection and testing projects on the walls of Panmen scenic spots, Suzhou city, Jiangsu province, China (Fig. 2). In order to solve the problem of lack of crack data in the background of brick wall blocks in the literature, a data set including both masonry structure background and crack characteristics is collected. Considering that the CNN training method based on deep learning is a data-driven technology (Valente et al. 2019), and its output effect is extremely dependent on the quantity and quality of data (Zhang et al. 2021), the self-collected data sets include crack-free images under various complex backgrounds and different crack types and sizes in order to enhance the learning and induction ability of the training network. A total of 1081 sets of data, including 148 sets of crack-free data and 933 sets of photos of masonry data set with cracks for manual labeling in MATLAB served as

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Fig. 1 Schematic representation of the process and framework of the methodology

Fig. 2 Photographic illustration of the location of the Pan Men station, water and land gates and the cracks in the wall

the fundamental requisite for effectively training the CNN. The data set created here will be called the “Wall Surface Block Data Set”. In general, crack shapes include linear, sawtooth and divergent shapes, crack types include different lengths, widths and shapes, and the areas where the cracks are located include different types of background noise, such as plants and parapets, brick texture and imprint. Therefore, for the following network training process, the input data set is rich and diverse, which is convenient for robust result output. In addition, the dataset can be used to run different networks to evaluate the performance (Fig. 3).

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Fig. 3 Sample of the raw database used for training-evaluation

4 Convolutional Neural Networks In this study, there are three main input ways of data flow for neural network training (as shown in Fig. 4). In this case, two main network architectures are evaluated, namely DeepLab V3 + (Chen et al. 2018) and CMX (Liu et al. 2022) to test their effectiveness in classifying block surface images as cracks and non-cracks. The channel for deep learning work can be opened by completing environment configuration and dataset testing in Python, and the model can be run by entering tagged data and annotated images. So the above 1081 sets of manually labeled crack data will be fed as inputs for CNN network training. For full RGB images, full infrared images and three image types that have been fused before training, DeepLab V3 + architecture is used to establish training channels. In deep neural networks, the task of semantic segmentation is usually accomplished by codecs or spatial pyramid pooling modules. The DeepLabv3 + model, proposed by Chen et al. (2018), utilized an editable Xception model, which mainly realized feature extraction and segmentation through the application of deep separable convolution, thus obtaining the optimized encoder-decoder network. Thus, the three data input types applied to brick wall surface crack identification task based on neural network architecture were to be evaluated. For the fourth way of image input type, that is, RGB data and infrared data, as a group of parallel data input before network training, complete feature fusion and subsequent crack information classification and segmentation in the training process, CMX (Liu et al. 2022) network architecture is used to complete the construction of this mode. The architecture fuses the target contours provided by infrared images and the target details provided by RGB images to complete cross-modal feature fusion for pixel-level semantic segmentation of crack recognition in this research. Among them, RGB image and infrared image are used as information flow at the same time to complete the deployment of cross-modal feature correction (CM-FRM)

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Fig. 4 Diagram of the fusion of different data sources in the neural network. a RGB or Thermal_ Only; b RGB + Thermal_Fused as input; c RGB + Thermal_Mixed as input and fused in training

and feature fusion module (FFM). The two information flows complement each other to complete the matching of information features and improve the accuracy of pixel-level semantic segmentation.

5 Results Analysis As mentioned in the methodology, the performance and results of the model output will be evaluated using the metrics precision, recall, F1-Score, accuracy and IoU metrics to measure the effectiveness and accuracy of crack segmentation. For the methodology used in this case study, a total of four scenarios of image input type scenarios and two network architectures were evaluated, in order to compare the optimal image input type and network model construction for the context of cracks in the ancient city walls. From the segmentation results of the DICE loss function and the Cross-Entropy loss function, as shown in Fig. 5, the DICE loss function shows good adaptation to the learning of this dataset to resist the interference of brick seam noise, and can have better performance in the reproduction of the crack shape. However, the Cross-Entropy loss function has a lot of mis-classification in this binary classification process, and these non-crack feature pixels mainly come from brick joints, the texture of the bricks themselves, and the protrusions between bricks. Therefore, the results provide an excellent suggestion for building a network model for the task of identifying cracks in the context of ancient wall masonry.

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Fig. 5 Demonstration of the effect of crack segmentation with DICE and CE loss functions

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In terms of the optimal training results for each combination (as shown in Table 1), firstly, for the crack category and the background category, the difference between the metrics is above 98% for the background, while the crack classification metrics are much lower than that. This is due to the fact that the area of the cracked region is much smaller than the area of the background region in the data collection, and therefore the number of cracked pixels only accounts for a small proportion of the number of pixels in the background, and the imbalance in the classification of this dataset reduces the performance of the network and the accuracy of the recognition results. Secondly, for the cross-sectional comparison results of these four combined schemes, it was found that the fourth scheme (i.e. the two data sources are then combined in training and the model is run under the CMX network architecture) has the best crack recognition results, with Precision This result shows that it is feasible and reliable to process the acquired dataset without the need to complete the fusion operation before training, but to go directly to the network architecture for training, which is the input method for the images. When assessing the performance of the four combinations in terms of individual metrics (as shown in Fig. 6), it is clear that the fourth combination scenario, although not very dominant in terms of Precision as a metric, achieves higher values for the Accuracy, Recall and F1-Score measurement dimensions. Furthermore, it can be concluded that the full IR image as data input performs the worst for the crack segmentation task, followed by the full RGB image as input image type. The reason for this is that there is an excess of gradients after gray-scaling the IR images, which makes accurate recognition difficult, whereas the RGB images themselves contain Table 1 The optimal result of the four scenarios (a) Only RGB images input into the DeepLab V3 + architecture Class

Precision

Recall

F1-Score

Accuracy

IoU

Crack

58.73

41.83

48.86

41.83

32.33

Background

99.67

99.83

99.75

99.83

99.51

(b) Only thermal images input into the DeepLab V3 + architecture Class

Precision

Recall

F1-Score

Accuracy

IoU

Crack

57.28

33.72

42.45

33.72

26.94

Background

99.63

99.86

99.74

99.86

99.49

(c) Merged RGB and thermal images before training input into the DeepLab V3 + architecture Class

Precision

Recall

F1-Score

Accuracy

IoU

Crack

55.99

45.28

50.07

45.28

33.40

Background

99.72

99.82

99.77

99.82

99.54

(d) RGB and thermal images separately being input into the CMX architecture Class

Precision

Recall

F1-Score

Accuracy

IoU

Crack

67.62

48.54

56.52

48.54

39.39

Background

99.74

99.88

99.81

99.88

99.62

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rich information about the crack details, which brings an improvement in accuracy in the annotation session and facilitates accurate feature recognition and training of the network model. It should be noted that the case where the value corresponding to STEP is 0 in each indicator in Fig. 7, is not a true response, but is caused by the derived results producing a wrong format that is not conducive to the recognition of the original value size.

Fig. 6 Comparison of the values of the four combination scenarios under Accuracy, Precision, Recall, and F1 Score metrics

Fig. 7 Comparison of the values of training loss and DICE loss function for the four combination types

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In terms of the results and performance of the loss function in training, the scenario of “the two integrations in training”, the framework applies a CMX network architecture, is the first to converge under the “Step” learning strategy, and avoids overfitting. In addition, this solution also shows better values and trends than the other solutions with the DICE loss function. In summary, for the four image types of input methods, RGB images perform better as the input layer than full IR image data sources for unimodal sensory data; for cross-modal data fusion, separate input first and then fusion in training is the best choice. Secondly, in terms of neural network architecture, the CMX architecture is an effective operational model for cross-modal data fusion. Therefore, for the task of identifying cracks in the masonry of the ancient city walls, the fusion in training approach with the CMX network architecture is a relatively feasible solution.

6 Conclusion For crack detection, most of the previous studies are based on the relatively smooth and simple background of concrete, asphalt and steel, and lack of datasets under the background of ancient city wall. Previous exploration experience has proved that using CNN model is becoming a powerful crack detection method, but studies on masonry is limited. It is also worth noting that the temperature information of infrared image can be used as additional data source to identify cracks. However, how to integrate RGB and infrared images to obtain better crack detection is less investigated. The present paper proposed a new methodology in masonry crack detection, and established a comprehensive dataset including RGB and thermal images. Investigation has been carried out to explore the best combination of data input type and network architecture based on CNN model, so as to improve the feasibility and accuracy of crack detection. The results show that for the four image input types: full RGB image, full visible image, data fusion before training and data fusion during training, the DeepLab V3 + network architecture based on encoder-decoder model has the highest accuracy of training on fused images. Simultaneously, the CMX network architecture based on multi-feature pyramid feature fusion also shows feasibility in the results of data fusion and crack segmentation. However, this method still needs to be improved to achieve higher accuracy of pixel level crack segmentation. Going back to the starting point of testing the health status of the ancient city wall structure and protecting and repairing it, the future work will focus on investigating more crack types, automating the data collection process, and optimizing the network architecture and integration module. In addition, the crack depth information will be considered (Spencer et al. 2019; Wang et al. 2019; Loverdos and Sarhosis 2022), so as to expand the data types and provide more information for better decision-making. Acknowledgements This research is funded by Xi’an Jiaotong-Liverpool University, Grant number REF-21-01-004.

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References Chen LC, Zhu Y, Papandreou G, Schroff F, Adam H (2018) Encoder-decoder with atrous separable convolution for semantic image segmentation. In: European conference on computer vision Dais D, Bal ˙IE, Smyrou E, Sarhosis V (2021) Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer learning. Autom Constr 125:103606 Gentile C, Guidobaldi M, Saisi A (2016) One-year dynamic monitoring of a historic tower: damage detection under changing environment. Meccanica 51:2873–2889 Gordan M, Sabbagh-Yazdi S-R, Ismail Z, Ghaedi K, Carroll P, McCrum D, Samali B (2022) Stateof-the-art review on advancements of data mining in structural health monitoring. Measurement 193:110939 Hsieh Y-A, Tsai Yichang J (2020) Machine learning for crack detection: review and model performance comparison. J Comput Civ Eng 34:04020038 Kassotakis N, Sarhosis V (2021) Employing non-contact sensing techniques for improving efficiency and automation in numerical modelling of existing masonry structures: a critical literature review. Structures 32:1777–1797 Lee BY, Kim YY, Yi S-T, Kim J-K (2013) Automated image processing technique for detecting and analysing concrete surface cracks. Struct Infrastruct Eng 9:567–577 Liu H, Zhang J, Yang K, Hu X, Stiefelhagen R (2022) CMX: cross-modal fusion for RGB-X semantic segmentation with transformers Loverdos D, Sarhosis V (2022) Automatic image-based brick segmentation and crack detection of masonry walls using machine learning. Autom Constr 140:104389 Loverdos D, Sarhosis V (2023) Geometrical digital twins of masonry structures for documentation and structural assessment using machine learning. Eng Struct 275:115256 Loverdos D, Sarhosis V (2023) Image2DEM: a geometrical digital twin generator for the detailed structural analysis of existing masonry infrastructure stock. SoftwareX 22:101323 Mesquita E, Martini R, Alves A, Antunes P, Varum H (2018) Non-destructive characterization of ancient clay brick walls by indirect ultrasonic measurements. J Build Eng 19:172–180 Nicko K, Vasilis S, Maria-Valasia P, P MJ (2023) Semi-automated discrete-element modelling of arch structures incorporating SfM photogrammetry 176:3–17 Spencer JBF, Hoskere V, Narazaki Y (2019) Advances in computer vision-based civil infrastructure inspection and monitoring. Engineering 5:199–222 Valente M, Milani G, Grande E, Formisano A (2019) Historical masonry building aggregates: advanced numerical insight for an effective seismic assessment on two row housing compounds. Eng Struct 190:360–379 Wang N, Zhao X, Zhao P, Zhang Y, Zou Z, Ou J (2019) Automatic damage detection of historic masonry buildings based on mobile deep learning. Autom Constr 103:53–66 Zhang K, Zhang Y, Cheng HD (2021) CrackGAN: pavement crack detection using partially accurate ground truths based on generative adversarial learning. IEEE Trans Intell Transp Syst 22:1306– 1319

Generating Social Sustainability Through Placemaking: A Study of Everyday Lived Space in Basha Miao Settlement Yuan Xiong and Zhuozhang Li

Abstract This paper explores the role of placemaking in the process of creating social sustainability through the everyday practice of minority ethnic communities in Guizhou. With the rapid development in recent decades, the physical and cultural landscape of traditional communities in Guizhou faces homogenisation and fragmentation problems. From the perspective of everyday life, resonating with Bruno Latour and Henri Lefebvre, this paper examines how social sustainability is generated through the relationships among locals, their practices and the living environment. This study will take the Basha Miao settlement as the case study, investigate the changes in physical spaces and social lives in the village, examine various ways of placemaking and its process, by mapping the practices, the sites and the social networks in the process of placemaking. This study shows how peoples’ everyday life practices (re)produce, (trans)form and (re)configure their public space in Basha, with methods of literature review, fieldwork, spatial analysing, and interviews. Through creating space in everyday life practice, multiple participants integrate local knowledge-like culture and collective memories and needs into shared places. Keywords Everyday practice · Miao traditional settlements · Social sustainability · Placemaking

1 Instructions With rapid socio-economic development, global climate change and environmental issues, as well as frequent disasters in human settlements, the question of how humans can recreate the resilience of settlements through social activities has been a hot Y. Xiong Guizhou Minzu University, Guizhou, China Z. Li University for the Creative Arts, Farnham, UK University of Liverpool, Liverpool, UK © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_26

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topic. Against the context of the two-wheeled development of ‘Rural Revitalisation’ and ‘New-Type of Urbanisation’, while being propelled with opportunities for the development of agricultural and tourism industries, traditional rural communities in China are also facing crises such as changes in traditional industries and population migration. Within such context of modern rural development, in this paper, we explore how practices in traditional vernacular settlements such as placemaking enhance the social sustainability of the community and strengthen the endogenous power. From the ecological aspect, the concept of sustainability has been deeply developed with “social concerns” (Dempsey et al. 2011). In the course of theoretical research on community sustainability, scholars have found that “placemaking serves as visible evidence of the relationship between space and society” (Balassiano and Maldonado 2015). There is, however, a lack of research to clearly define and fully operationalise the concept of urban social sustainability. (Larimian et al. 2021), thus resulting in the real challenge of presenting a clear theoretical framework (Dempsey et al. 2011). Nonetheless, for a rural context, how can we develop a conceptual framework that is aligned but also differing from the urban environment? While exploring these questions and gaps, this paper also attempts to gain insights into the relationship between the rural and the natural environment, which leads to the imagination of an alternative vision of urban development. Situated in an ethnic minority traditional settlement in Guizhou, China, this study examines the process of placemaking by which local residents have been able to preserve their own cultural identity and enhance the sustainability of the community in their everyday lives. Through field research, mapping, and interviews, this study aims to explore how social sustainability in rural areas is generated through the sociospatial relationships among local residents, their practices and the living environment. This raises several research questions: RQ1: How can we articulate and investigate this process of placemaking? RQ2: What are local people’s spatial practices and their sites in the settlement? RQ3: How does the social structure affect the process of placemaking and social sustainability? RQ4: How do the local understandings of the natural and built environment manifest themselves in the process?

2 Literature Review 2.1 Social Sustainability in a Rural Context A considerable body of literature has discussed sustainability in a rural context in recent years while mainly focusing on sustainable development (Billington et al. 2008; Marsden 2013; Marsden 2017; Huang and Zheng 2022), and energy technology and building materials (Deng et al. 2018). On the one hand, by foregrounding the relationship between rural and urban areas such as agriculture and tourism, scholars

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seem to examine the rural through an external and urban-centric gaze and consider it as ‘the less significant other’ (Mormont 1990), a supplement of resources and knowledge (Gutierrez-Velez et al. 2022; He and Zhang 2022). On the other hand, the emphasis on local skills/materials in building construction overlooks the social and spatial politics of the community, seeing space as a ‘thing’ (Lefebvre 1991) rather than an outcome of the specific relationship between different groups of people, between human settlements and the nature, between their practices and their understanding of sustainable development. In some cases, drawing sustainable design and low-carbon living without integrating into the local social structure might also lead to a form of social exclusion. Also, as these two strands of discussions both highlight the economic dimension of being sustainable, we need to be aware of the pitfall of ‘productive capitalism’ with the concept of ‘framing everything in terms of the economy’ (Soja 1989; Latour 2020), and neglecting the hidden discourse and the ‘everyday low-carbon practice’ of the locale in generating sustainability. Scholars such as Shirazi and Keivani (2019) and Larimian and Sadeghi (2021) have pointed out that social sustainability, despite its significant role in sustainable development, is given far less attention than the others (environmental and economic). Considering the ever-changing and elusive nature of social structure in each cultural context, it would be difficult to grasp a holistic understanding of the local discourse by conceiving social sustainability as an ‘add-on’ aspect. Larimian and Sadeghi (2021), for example, argue that social sustainability needs to be discussed and examined multidimensionally (including social interaction, sense of place, social participation, safety, social equity and neighbourhood satisfaction). Meanwhile, as such a framework is based upon an urban context and scale, there is a necessity to develop a conceptual framework for the assessment of rural social sustainability within the specific Chinese context.

2.2 Understanding the Locale from an Everyday and Relational Perspective To investigate this overlooked discourse of the locale in generating sustainable development, a discourse that is largely based upon their practice and their relationship with both the built environment and nature, we have to register the lived ‘reality’ of the rural inhabitants before projecting and imposing a more sustainable future on them. As Lefebvre argues, ‘the space of the everyday activities’ differs from ‘the space of experts (architects, urbanists, planners)’, for which the former ‘has an origin’ (Lefebvre 1991). That is to say, the local discourse of sustainability and their ‘everyday low-carbon practices’ is a ‘subjective’ outcome of their own history, culture, belief and geography. Such local knowledge, expressed in the socio-spatial order of their living environment and their everyday practice, has to be registered and revealed through ‘everyday reality’, as it is hidden in the technocratic order of the space and overlooked by scientific knowledge (Lefebvre 1991; de Certeau 1984).

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At the same time, this emphasis on everyday life is not about examining these practices individually but understanding them as a collective discourse, a ‘shared vision’ (Li 2021), within the specific context. Drawing on the argument of Highmore (2010), everyday can be seen as a field of negotiation, and a point of confluence between ‘microscopic levels’ (the commonly recognised everyday practices and objects) and ‘macroscopic levels of the totality’ (societal understanding of sustainability, culture, national policies, natural environment, etc.) as discussions on sustainability in urban studies have often focused on either ‘top-down’ policy and sustainable design, or ‘bottom-up’ individual behaviours (Li 2021; Schäfer et al. 2018), a holistic conceptual framework needs to be explored to avoid the pitfall of any unilateral narrative. Scholarships on sustainability have provoked the understanding of a pluriverse and the politics of Gaia. With his Actor-Network Theory (ANT) being increasingly referenced in planning theory and practice (Rydin 2012), Latour’s writing continuously reminds scholars of the ‘thread-like character’ of modern societies that connects not only ‘human’ but also any other ‘non-human’ that is ‘granted to be the source of an action’ (Latour 1996)—a thread that does not foreground neither ‘the personal’ nor ‘the collective’ but an entity through the notion of network (Latour 2020). In this study, such a relationist perspective can lead us stepping forwards to understand the everyday practice ‘beyond their performance’ and see it within a ‘network of things, norms, and embodied know-how’ (Schäfer et al. 2018). And for Chinese rural communities, this relational nature of everyday space and practice tends to be more apparent due to a relation-based ‘acquaintance society’ (Ruan et al. 2022).

3 Methods To understand the relationship between social sustainability and the everyday practice of placemaking, a set of methods were combined to investigate different metadimensions of social sustainability through a critical cartographical perspective (Kim 2015).

3.1 Data Collection . Literature research to understand the general background of Basha village, and the documentary collection of local planning documents and policies. . Fieldwork, including on-site observation, documentation, and Cognitive mapping of everyday practice with semi-structured interviews. . Interviews with other key stakeholders of the settlements.

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3.2 Fieldwork The research formed three pairs of field teams, each consisting of two assistants from the major of urban planning. One of them was raised in a nearby area and is also Miao or Dong, and can communicate with most people in the village. The other is an outsider, who can hold an objective perspective in observation and choosing interviewees. The field teams conducted fieldwork in the villages, documenting the activities of 61 groups of indigenous residents, and completed face-to-face interviews and cognitive maps with 20 of them.

3.3 Observation and Documentation The research teams used walking and observation as the main methods to explore the village, they were asked to record every local activity they met in the village by taking photos through the outdoor app 2bulu with GPS function, which could record the walking trace of the research team and the precise location of each photo they took. They were asked to record their interview content and focus on those factors through observation: (1) Who are the actors conducting everyday practice? (The number of activators, gender, approximate age, potential relationships, length of time) (2) what are the activities? (Purpose, process, results, and potentially derivative activities) (3) what is the related spatial condition? (Stools, facilities, transformed furniture, etc.)

3.4 Cognitive Mapping and Interview Besides observation and recording actors, activities and the spatial condition of everyday practice, the field team asked local people to draw a cognitive map of their everyday lives. As most residents found it difficult to directly describe their everyday life, the mapping process would be guided by the following interview framework (Table 1).

3.5 Interviews on Other Stakeholders Besides local residents, face-to-face interviews conducted with people who work in village committees and the tourism company are essential to understand the social structure, general policies and the followings: (1)the traditional and transformed organisation structure of the community; (2)policies and regional planning from local authorities related to the community; (3)the influence of tourism development.

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Table 1 Interview framework for cognitive mapping Practice

What are your daily routines outside? What do you do outside every day? What do you play with? Where do you usually play? What do you see while playing or working outside your house?

Site

Where are these activities happens? Can you descript the space for me? How do you usually get to this space? Will you cross somewhere to go? Is there any other practice may happen in the site?

Time

When did all these activities take place? How often is it? How many times a day or a week? Does everyone else do this every day? How long will it last?

Social network Who will participate in these activities? How many people will be involved in? What is the relationship between you? What do they have to do with you? Will you be involved in their other activities? Like what?

4 Context: Basha Miao Settlement Spatial Characteristics: The relationship between the settlement and nature is reflected in its name, Basha (岜沙), literally ‘a place with lots of silver grass and cedar trees’ in the local language. Throughout the Miaos’ history of migrations, each time the community has moved deeper into the mountains of the karst region, where the terrain is more fragmented (Zhou and Feng 2015). After several migrations, the Miao community settled at the foot of Moon Mountain, a branch of the Ninety-thousand Mountain Range, where the mountain slopes from the ridge to the southeast and northwest with complex variations in elevation. The Miao people built their houses on high ground due to the defence purpose in the past. The houses in Basha are built on the mountain’s slopes, along the contours of the ridge and the hillside. The transition between nature (cedar trees, the bamboo forest) and the buildings in the undulating hills creates a dynamic border. The Basha people have developed a common perception of the collective resources of the settlement over a long period, which is reflected during the cultivation and other practices. In a challenging setting that is not conducive to agricultural development, the Basha people have carefully inhabited the local environment and created a collective living space with shared spatial characteristics due to its geographical features, and a high degree of communal identity (Su 2018). Cultural Identity: In addition to the highly coherent spatial characteristics of the built environment, the abundance of cultural activities and community exchanges, guided by a harmonious landscape and shared community belief, has also helped to shape a strong sense of ethnic identity. Without external influences, the Basha people spend a great deal of time producing materials for major festivals with their cultural identity as “Miao”. Several significant families in Basha have forged close blood relations through intermarriage between families, while other families need to gain the trust of local people through the act of “brotherhood” to become a part of the main society in the village (Su 2018). The Basha people’s strong sense of community is reflected in their costumes, working patterns, and the richness of their collective

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activities and lifestyle. For example, known as the “last gunman’s tribe”, dresses and gowns in Basha have a unique ethnic significance. Social Structure: Since the founding of P.R.China, the village rules and people’s covenant formulated by the Zhailao (the social leader), Ghost Master (the spiritual leader) and the village committees based on the consensual local codes have effectively maintained the social order and social relations of Basha for a long time. The first secretary and cadres stationed in villages appointed by higher-level governments, and the members of village committees elected by villagers, have become agents for managing village administrative affairs and important development resolutions, gradually replacing the administrative duties of Zhailao and the Ghost Master. As the original important spiritual and cultural symbols of the community, with the changes in the relationship between organisation and tourism development, Zhailao and the Ghost Master, have also been integrated into the new diversified organisational structure in various ways, such as the current Zhailao Gun Lawang served as the former director of the village committee, and has been actively participating in the decision-making of the village after leaving office. Since the development of tourism in Basha, it has established a mechanism for linking the interests of ‘company + village collectives + cooperatives + farmers’ with the tourism company and hidden management relationships have been generated from multiple dimensions such as village construction, scenic spot management, ticket revenue, and performance dividends. However, this new organisational relationship did not make a huge difference in the traditional social relations of the community, and the social structure of Basha remained relatively intact. (Su and Sun 2017).

5 Case Studies: Everyday Lived Spaces in Basha 5.1 Sitting Spaces in Alleys While the men tend to go to the fields or the city to work, local women usually stay at home for maternal care and domestic activities, as well as pulp dyeing and embroidery making. They often gather in groups and make traditional costumes together in the space outside the residential buildings due to the limited lighting inside the building and the local dry climate. As the settlements are densely arranged and appear in clusters due to local geographical features and early defence needs (Huang and Dong 2019), these gatherings are not concentrated or projected; rather, they occur spontaneously and become an embodiment of social relations. Most of the gathering spaces are located next to the streets and alleys in several adjacent residential buildings or an open field in front of the house, surrounded by varied elements such as walls, eave, corridor, piled firewood and the tool shed—all enhancing the sense of enclosure of the space. The centre of the gathering space usually defines the theme of the gathering: food, charcoal braziers, barbecue grills, or a small foldable table. Bamboo racks, used for drying silk thread and strips of dyed cloth, could be

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moved onto the border of the space in order to provide shade. When the gathering space coincides with the tourist route, the informal structure also creates a flexible barrier for local women to escape from the external gaze and avoid communication with strangers. Internally, this type of everyday space provides a welcoming environment for local women in the village where they make traditional costumes through weaving, dyeing, hammering and sewing, a complete process that requires multiple women to complete together. They often bring their own wooden stools, sitting together for needlework, barbecues, chatting, or producing tools. With their children and infants playing around, observing the process of embroidery and pulp dyeing, and learning from their mothers, it is through this informal way of everyday gathering on the street that local knowledge (of cooking, cloth making) is produced, exchanged and passed on to the next generation.

5.2 Water Well Due to the perennial shortage of water in the region, local residents carry buckets to the well everyday to fetch springs from the mountain. According to the interview, local villagers would put the buckets along the road queuing for the water due to the slow fetching process. While they are waiting for the water or on the way to the well, people often greet each other and share information related to their everyday life. With pavilions, stoves and other structures for people to stay near the well and gather together, the well and its surrounding area have been gradually transformed from a water fetching point into a public space for varied activities. Before planting seedlings in March of the lunar calendar, for example, a large pot will be set up on the stove by local people to boil water to boost the sprouting. In June and July of the lunar calendar, local women will meet near the wells to rinse the dyed cloth. Women also gather around the well on a more daily basis to wash their hair and clothes, for which the wooden rails of the well pavilion become temporary drying racks. Along with their mother, children also play in the open field near the well, echoing the character of gathering spaces on the streets. The importance of well for local residents is reflected not merely in these daily activities, but also in their cultural practices which are related to their faith in nature. Near one well, there are huge rocks tied with bamboo baskets and straws for rituals. Different materials will be added to the rocks according to the requirements of the ghost master for blessing activities. Accommodating varied practices at different rhythms throughout the year, the well (the pavilion and the water) becomes a material ground that maintains and expands the social relationship of the local community. It is a space with the character of publicness where daily practices, production works, and cultural activities overlap, all being closely aligned with the social structure, local climate, and the transformation of the natural environment in different seasons.

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5.3 Lusheng Ping Redeveloped and planned in the typical form of a public square, the Lusheng Square was originally used as a gathering place for major events such as Lusheng Festival, where local villagers would assemble there for ceremonies such as the Lusheng Dance. The square is recognised as a key public space in local tourism maps and topdown planning documents, as well as the centre of cultural activities in many Pashabased literates (Huang 2019; Zhuang 2005). In recent years, driven by tourism development, the square has been transformed into a stage for cultural performances from local people, which are managed and operated by one tourism company. However, in daily life, local residents rarely use this area as the square deviates from their routines. During their performance with the tourism company, villagers who participate in the performance often gather in a closed group of acquaintances waiting for the show to start, and then, the crowd will retreat from the square after the performance without further stay. The square is also not very popular among the young generation, as young men and women of the Miao ethnic group are also prohibited to date in the square based on their customs (Wu and Jia 2017). From our survey and interview, the presence of villagers in the square was seen only during major festivals and tourism performances. Most interviewees pointed out that few villagers would visit the square on a daily basis. Shaded by huge trees and covered with pavements, the Lusheng Square as a public space recognized by planners somehow fails to integrate into the everyday life of local residents with its underused status.

6 Discussion and Conclusion 6.1 Parallel Spaces: From Developers to the Locale There is a difference between the important nodal spaces perceived by the outside world and the spaces where the villagers of Basha gather for their daily activities. From the tourism map, the traditional village conservation planning, and the research of previous scholars, the important spaces in Basha perceived by the outside world are the village square, the Lusheng ping, and other spaces that are related to important ceremonial activities and the development of the tourism industry. However, from the cognitive maps, our observation and interviews, it is the everyday space produced by local residents that accommodate most of their daily activities. From sitting spaces in the alleys to the wells, these spaces may find no traces in the tourism map or official documents. Yet, with drying racks, stoves and dyed cloth, local residents with varied tools and resources produce their own social space in a clever and participatory way and generate a great sense of social sustainability through their everyday low-carbon practices and their shared understanding of the settlement (Fig. 1).

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Fig. 1 A comparison between planning public spaces (Left) and local’s everyday living space (Right)

6.2 Beyond the Built Environment: Society and Nature The traditional production methods of Basha are highly dependent on nature and the Basha people claim to be the descendants of maple trees. Hence, the territory of their home is seen beyond the scope of the human settlement or the walled gate, but the land among mountains, rivers and forests. Their tree worship, high symbiosis with nature, and ecological maintenance behaviours are all part of the indigenous understanding and knowledge of the relationship between human settlement and nature. Human society here stands nowhere near the centre of the land and nature is not merely a resource for production but an ‘absolute and alive field (the trees) to breathe together (Lefebvre 1991). Basha, then, being far away from the system of urban development, reminds us that the idea of ‘framing everything in terms of the economy is a new thing in human history’ (Latour 2020).

6.3 Placemaking: A Space of Kinship and Care From everyday gathering spaces to the activities around the wells, local residents, especially women, overcome the spatial condition of the clustered settlements and the emotional isolation, strengthen their mutual relationship through these everyday practices, and eventually, transform the settlement environment into a place for themselves. The notion of accompaniment and care acts as a key element throughout the

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process of placemaking. The accompaniment is not merely demonstrated in the partnership of making costumes and embroidery or taking care of children collectively, but also through non-production-related actions such as ‘watching mountain and water together’. Thus, it also implies nature as another layer of the accompaniment, which goes beyond the narrow understanding of accompaniment as an action between humans and humans. The everyday space of Basha, therefore, becomes an embodiment of the alternative relationship between ‘human groups with each other and with the environment’, a potential answer to the call from the World Commission on Environment and Development in ‘Our Common Future’ (1987).

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Study on the Design Method of Urban Renewal Based on Carbon Emissions and Carbon Sinks Calculation: A Case Study of Environmental Improvement Project of Suzhou Industrial Investment Science and Technology Innovation Park L. Zhang, Y. Q. Cai, S. D. Song, and L. L. Sun

Abstract Under the guidance of the dual-carbon policy, low-carbon design has gradually become one of the important indicators for evaluating urban design solutions. Taking the environmental enhancement project of Suzhou Industrial Investment Science and Technology Innovation Park as an example, this paper constructs a design-oriented carbon estimation system in terms of carbon emissions and carbon sinks of buildings and landscape by calculating the quantity of architectural components and plants with the carbon factors, aiming to quantitatively assess the carbon reduction benefits of design solutions and provide timely design feedback for solution comparison and optimization. Finally, four low-carbon design strategies are summarized for urban renewal projects: rational demolition and construction, threedimensional parking, low-carbon materials, and carbon sequestration by plants. This study incorporates low-carbon indicators into the evaluation of design schemes of urban renewal project, providing a scientific basis and practical guidance for practicing the concept of sustainable development and contributing to achieve the dual-carbon goal. Keywords Design method · Urban renewal · Carbon emissions · Carbon sinks · Suzhou

L. Zhang · Y. Q. Cai · S. D. Song · L. L. Sun School of Architecture, Suzhou University, Suzhou, China L. Zhang · L. L. Sun Suzhou Research Institute of Chinese Historical and Cultural Cities, Suzhou, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_27

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1 Introduction In response to climate change, President Xi Jinping announced at the United Nations General Assembly in September 2020 that “carbon dioxide emissions will strive to reach the peak by 2030 and achieve carbon neutrality by 2060.” The report of the 20th Party Congress re-emphasized China’s dual carbon target, setting the keynote for the sustainable development of society and the industry. The construction industry is one of the important industrial sectors of China’s national economy, and the energy consumption of the construction industry accounts for more than 30% of the total. (Wang et al. 2021). How to steadily promote low-carbon urban regeneration under the guidance of the dual-carbon goal is an urgent issue for urban designers and builders to address. Urban regeneration projects generally include several main objectives, such as functional sorting, image enhancement, environmental upgrading and traffic optimization, which involve the organization of site flow, the optimization and adjustment of plan and facade and the landscape design. Therefore, the exploration of lowcarbon path for urban regeneration should mainly start from these aspects. Taking the environmental enhancement project of Suzhou Industrial Investment Science and Technology Innovation Park as an example, this paper constructs a design-oriented carbon estimation system in terms of carbon emissions and carbon sinks of both buildings and landscape, aiming to discuss the prediction and assessment of architectural and environmental impacts in the urban design scheme stage and investigate the path to reduce carbon emission and increase carbon sink.

2 Theoretical Basis In the research related to carbon revenue and expenditure calculation in the building industry, the general view is to establish a comprehensive evaluation system based on the whole life cycle to quantify the energy consumption and environmental impact of buildings in order to reduce carbon emissions throughout the life cycle. In the inventory era, the renewal of buildings is no longer a simple repair, but a largescale renovation and rebuilding, which could be regarded as the process of partial termination of life and reconstruction. The author believes that the renewal of a buildings is the circulation from the termination stage to the materialization stage in the life cycle, which consists of two steps, demolition and construction (Fig. 1). This study focuses on the estimation method of carbon emissions and carbon sinks in the renewal process of buildings. At present, there are three main types of methods for calculating the carbon emission of building construction in the world, which are the method of processbased inventory analysis (Shao et al. 2014), input–output analysis(Nässén et al. 2007) and the hybrid method of the both (Guan et al. 2016). However, all three types of data-intensive methods rely on precise data which are often used to account for

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Fig. 1 Diagram of building life cycle

carbon emissions after a building is constructed (Martin et al. 2018), but difficult to be used to provide feedback for the optimization of design solutions in the preproposal phase. On this basis, Luo Zhixing taking “building components” as the basic unit as well as the method based on the list of “ten major building materials”, so as to build a “design-oriented” carbon emission calculation method system of the construction of buildings (Luo et al. 2021). The core of this study is the calculation of carbon emission in the conceptual design phase of building renovation projects. Considering the convenience of the calculation of carbon emission, we propose to calculate the amount of “demolition” and “construction” of each building component by the Building Information Modeling (BIM), multiply which by the carbon emission factor of the corresponding material, finally get the total carbon emission of the building. Unlike existing literature, which often treats buildings and landscape as separate objects, this study considers both as a whole in the project of urban renewal from the perspective of design practice. The calculation of carbon sequestration per unit time of plants is an important component of the calculation of landscape carbon revenue and expenditure. Jin Lihao’s study reflected the carbon sink capacity of plants in landscape by calculating the carbon stock of average single plant using the method of multiplying biomass by the conversion factor of carbon stock (Jin 2019). This study proposed to calculate plant biomass taking trees, shrubs and grasses as the major categories, and then multiply which by the carbon storage coefficient of per unit plant, at last derive the total carbon sink of the landscape.

3 Method 3.1 Project Overview The project is located at No. 483, Changxu Road, on the west side of the old city of Suzhou, close to the moat, near the Shilu business district, which was the Suzhou Washing Machine Factory formerly. The site covers an area of 12,560 square meters, with the gross floor area of about 21,872 square meters. In 2006, the Factory was transformed into the current Suzhou Industrial Investment Science and Technology Innovation Park, which consisted of seven office buildings and a row of commercial

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space along Changxu Road. However, after nearly 20 years, the development of the Park has gradually lagged behind. Besides, the existing 200 parking spaces occupy almost the entire outdoor space, resulting in traffic congestion, the lack of green landscape, which is difficult to adapt to the development of modern science and innovation industry with new business forms and new requirements for space. It is a typical project in urban renewal, the following demands were put forward by the user: the building area should not be reduced, the number of parking spaces should be kept, and some building with low use efficiency can be considered for demolition, e.g. Building 8. Taking this project practice as an example, this study proposed to construct an estimation method system of carbon emissions and carbon sinks, aiming to take the carbon revenue and expenditure calculation as the basis for the comparison and adjustment of scheme design and explore low-carbon strategies for urban renewal design.

3.2 Model Construction In this study, carbon emissions and carbon sinks during the demolition and construction of buildings and landscape in urban renewal projects are considered in the scheme design phase. The total carbon emissions involve the expenditure in the demolition and construction of buildings, structures and components and in the process of landscape construction (Fig. 2). The calculation of carbon sink is obtained by summing up the effect of carbon sequestration of different types of plants, such as trees, shrubs and grasses. The overall carbon balance of the project is obtained by adding up the carbon emissions and carbon sinks (Eq. 1). Since the carbon sequestration benefits of plants are superimposed year by year, the overall carbon balance of the project will also change with time. This study focuses on the strategy of carbon reduction in the phase of schematic design taking the results of carbon accounting as the basis for program selection and evaluation. Therefore, only the carbon emission in the materialization stage of the buildings and landscape is considered in this study. The carbon emission in the operation and maintenance process in the stage of buildings’ usage is not included in the studying scope, because it is uncertain and influenced by human factors. The accounting method of carbon emission using “building components” as the basic unit in the stage of materialization is adopted (Cang et al. 2020). The building components are divided into eight categories: foundation, walls, columns, beams, slabs, roofs, stairs and ramps, doors and windows. Firstly, the unique code of corresponding building components is set in the Revit model with BIM technology, and the statistical list of quantities for building components is generated. Then, the database of carbon emission factor is constructed by referring to the existing research results. Finally, the carbon emission of the construction of buildings can be calculated by associating the list of quantities for building components with corresponding carbon emission factor.

Study on the Design Method of Urban Renewal Based on Carbon … Fig. 2 Calculation method and flow of total carbon revenue and expenditure

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Project Information Import

Building Information Model (Revit) Export

Landscape section

Architectural section Building components quantity list

Hard matter: Material usage statistics

Soft matter: Plant statistics Carbon sequestration factor

Carbon emission factor

Total carbon sinks

Total carbon emissions

Total project carbon balance

QCm = T × Y +

n  i=1

QCm T Y CBci bci Cj Nj

C Bci × bci −

n 

Cj × Nj

(1)

j=1

refers to the total carbon balance of the project, kg·CO2 e; refers to the total area of demolished buildings, m2 ; refers to the CO2 emission for demolishing per unit area, kg·CO2 e/m2 ; refers to the carbon emission factor of the components of building or landscape, kg·CO2 e/unit; refers to the quantity of the components of building or landscape; refers to the amount of carbon sequestered by the plant; refers to the number or area of the plant;

Regarding to the accounting of landscape carbon emissions and carbon sinks, the landscape is divides into two parts, hard matter and soft matter. The hard part is mainly classified into several categories based on the amount of the major material, such as asphalt and concrete, stone, paving brick, etc. The accounting of carbon emission is obtained by combining with corresponding carbon emission factor. The soft part is mainly composed by landscape plants. The total carbon sinks in the program are obtained by combining the number or area of trees, shrubs and grasses with the average carbon sequestration of per unit plant. Trees are counted by the number. The quantity of shrubs is inverted based on the quota from Jiangsu, 25 plants per square meter and taking up 25% of the lawn area. Ground covers and herbs are estimated on basis of taking up 50% of the lawn area. The lawn is not included in the carbon sink calculation, since it is low in carbon sequestration and needs to be mowed frequently.

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4 Results Based on the above methods, the calculation of carbon revenue and expenditure for different schemes are carried out as the basis for the comparison and selection of design. Different strategies are proposed respectively by the two schemes in response to the current problems of the site. The above equation was substituted into the two schemes to obtain the estimated values of carbon emissions and carbon sinks. In Scheme A, the Building 8 was demolished, two sets of parking buildings in steel structure were added, the area of green landscape was maximized in the site and the walking area was covered by membrane roofs. There is less modification in Scheme B, the Building 8 was retained, the facades of buildings were decorated by the same technique as Scheme A, the ground was still used for parking, a secondlevel platform system for walking was added to separate the flow of pedestrian and vehicle, the form of which was the same as the membrane roofs in Scheme A but with common reinforced concrete structure and material, and only a small amount of greenery along the road was retained because the ground parking occupied most of the site. The statistics of quantity of the demolition and construction of buildings and landscape works are output by the Revit software by comparing models of the two schemes with the current model of the site (Figs. 3 and 4). The overall carbon accounting results of the two scheme are finally obtained with calculating the total amount of carbon emissions and carbon sinks by substituting into the formula. Tables 1 and 2 show the total carbon emissions for Scheme A and B, including the demolition part as well as the newly construction part, in which carbon emissions in the materialization process of buildings and landscape was mainly counted. The demolition part is estimated by multiplying the carbon emission factor by the Fig. 3 Model of Scheme A

Fig. 4 Model of Scheme B

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buildings’ floor area. For the newly construction part, the carbon emissions are calculated by linking the amount of component derived from the Revit with the carbon emission factor extracting from the existing literature (Yan 2011). Each component corresponds to a unique code for easily calculation. Finally, the total carbon emissions of the two schemes are summed up separately. By comparison, the total carbon emissions of Scheme A are larger than that of Scheme B, with the difference of about 72.8 t. The reason for this difference is that in Scheme A there is larger amount of demolition and construction than in Scheme B. Tables 3 and 4 respond to the total amount of carbon sinks for the two schemes. Trees and shrubs are calculated by the number of plants, and ground covers and herbaceous plants are calculated by the covered area. The quantity of landscape plants is counted in this way. Then, the average annual carbon sink per unit plant or unit area is summarized based on the existed literature (Shi et al. 2011; Yin et al. 2020). At last, the two sets of data are multiplied and summed up to arrive at the total annual carbon sink. After comparison, it is shown that the annual carbon sinks of Scheme A are much larger than that of Scheme B, which is roughly 5 times, with a difference of about 4.91 t per year. The main reason is that in Scheme A the three-dimensional intensive parking is adopted to release a large amount of ground space, which can be used for large area of greening and is especially suitable for the allocation of trees and shrubs with high carbon sequestration capacity. To compare the difference between the total carbon emissions and carbon sinks of the two schemes (carbon emissions minus carbon sinks to get the value of carbon revenues and expenditures), it is shown that although the total carbon emission of Scheme A is higher than that of Scheme B during the renovation stage, the carbon sink of Scheme A is much higher than that of Scheme B in one year. The carbon sinks of plants accumulated year by year. As shown in Fig. 5, the difference between the carbon balance of the two schemes tends to be zero in the 16th year after the completion of renovation, and the advantage of Scheme A becomes more obvious in the next 30 years. The carbon emission from buildings and landscape in the operation and maintenance stages is not included in the study. For the part of building, the difference of carbon emissions in operation and maintenance is negligible because the total floor area is basically the same for the two schemes after completion. In terms of the landscape, the difference between the two schemes is mainly reflected in the maintenance process of plants which will generate some carbon emission. But the proportion of this part is very small compared to that in the materialization stage. Therefore, it will have no impact on the judgment of the overall difference. Finally, we could draw the conclusion that Scheme A is the better choice considering the dual-carbon targets.

Landscape

Total

Architectural construction

Total

Architectural demolition

14.10.10.03.03

14–10.10.06.03

Brick

14–20.30.21

14–10.20.03.06

14.10.10.03.03

Perforated metal

Facade of Parking building

14–10.20.15

Stone

Corrugated steel

Roofs of Parking building

14.20.30.06

Asphalt concrete

Steel

Beams of Parking building

14.20.30.03

Pedestrian pavement

Steel

Columns of Parking building

14.10.20.18

Parking pavement

Metal perforated plate

Floors of Parking building

14-10.20.03.06

Tensile membrane

Metal perforated plate

Architectural facade

14-10.20.03.03

–

Code

Membrane structure

Concrete masonry

–

Materials

Architectural wall

–

Components

Table 1 Estimated statistics of total carbon emissions for Scheme A

42.70

24.99

121.10

2.48

2.45

50.30

37.68

30.14

17.91

193.76

236.86

847.00

39.89 t

439.00 m3

1765.00 t

t

2150.00

267. 70

m3 t

1789.06

1789.06

1789.06

2150.00

177. 00

t

t

t

t

m3

105.00

m2

1221.06

kgCO2 e/t

kgCO2 e/m3

kgCO2 e/t

kgCO2 e/t

kgCO2 e/t

kgCO2 e/m3

kgCO2 e/t

kgCO2 e/t

kgCO2 e/t

kgCO2 e/t

kgCO2 e/m3

kgCO2 e/m3

Unit

Carbon factor Data

Unit

Quantity Data

(continued)

36,166.90

996.85

53,162.90

4377.20

630,617.14

5267.50

13,465.31

67,411.78

53,922.27

32,042.06

416,584.00

41,924.22

128,211.30

128,211.30

Carbon emissions (Unit: kg)

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Unit

Data

Unit

Carbon factor

Carbon emissions (Unit: kg)

Data sources for carbon factor: (Luo 2016; Luo et al. 2021; Yan 2011)

853,532.29

Data

Quantity 94,703.85

Code

Total

Materials

Aggregate

Components

Table 1 (continued)

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Reinforced concrete 14-20.20.09

Reinforced concrete 14-20.20.03

14.10.10.03.03 14.10.10.03.03

Asphalt concrete

Stone

Brick

Columns of Platform

Floors of Platform

Parking pavement

Pedestrian pavement

kgCO2 e/t

36,158.43

1435.64

71,126.78

220,691.79

14,113.44

20,528.64

416,584.00

416,584.00

Data sources for carbon factor: (Luo 2016; Luo et al. 2021; Yan 2011)

780,638.72

847.00

kgCO2 e/m3

kgCO2 e/t

kgCO2 e/m3

kgCO2 e/m3

kgCO2 e/m3

kgCO2 e/t

Aggregate

t

39.89

297.00

m3

m3

297.00

m3

439.00

297.00

m3

t

2150.00

t

Carbon emissions (Unit: kg)

364,054.72

42.69

35.99

162.02

743.07

47.52

69.12

193.76

Unit

Carbon factor Data

Unit

Quantity Data

Total

14-10.10.06.03

Reinforced concrete 14-20.20.06

Beams of Platform

Total

14-10.20.03.06

Landscape

Metal perforated plate

Code

Architectural facade

Materials

Architectural construction

Components

Table 2 Estimated statistics of total carbon emissions for Scheme B

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Table 3 Estimated statistics of total carbon sinks for Scheme A Plant species

Carbon sequestration per unit plant of average annual

Quantity

Data

Data

Unit

Trees

156.65

–

Shrubs

61.78

–

Ground cover/herbs

0.40

m2

Total carbon sinks (Unit: kg) Unit

20.00

–

3133.00

42.00

–

2594.76

891.73

m2

Aggregate

356.69 6084.45

Data sources for carbon sequestration: (Shi et al. 2011; Yin et al. 2020)

Table 4 Estimated statistics of total carbon sinks for Scheme B Carbon sequestration per unit plant of average annual

Quantity

Data

Unit

Data

Trees

156.65

–

4.00

–

626.60

Shrubs

61.78

–

7.00

–

432.46

m2

112.88

Plant species

Ground cover/herbs

0.40

m2

282.19

Total carbon sinks (Unit: kg) Unit

Aggregate Data sources for carbon sequestration: (Shi et al. 2011; Yin et al. 2020) Fig. 5 Comparison of carbon emissions and carbon sinks in 50 years for Scheme A and B

1171.94

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5 Discussion Based on the carbon accounting process and results above, it can be found that some key decisions in the scheme design have an important impact on the overall carbon revenue and expenditure of the project. The low-carbon strategies in urban renewal can be summarized from several aspects as follows.

5.1 Reasonable Demolition and Construction to Avoid High Carbon Emissions from Non-essential Demolition There are large number of urban renewal projects in the city today. Some components should be reserved preferentially in the design process to minimize the high carbon emissions generated by indiscriminate demolition. The recycling of construction waste is important in the demolition of buildings, especially for some highly polluting and energy-intensive building materials, which should be treated in a hierarchical manner to maximize the recycling rate.

5.2 Three-Dimensional Parking, Saving and Intensive Use of Land The land resource is deficient in our country, while traditional parking spaces in cities and towns occupy a larger land resource. The unreasonable placement for vehicles can cause waste of land resource and various unnecessary carbon emissions. In the context of urban renewal, various mechanized, three-dimensional and intelligent parking facilities have been created driven by space constraints of old cities and new technologies. These parking facilities have the advantages of small footprint, high space utilization and strong adaptability, which can save urban land and urban space to the maximum extent. At the same time, green landscape space can be reserved for the site to maximize the carbon sink benefits of plants.

5.3 Low-Carbon Materials, Optimizing the Using Structure and Production Process of Building Materials The main carbon emissions from renewal projects originate from the material output of the buildings and landscape in the materialization stage. Carbon emissions from the materialization stage of buildings mainly come from two kinds of high energyconsuming building materials, cement and steel, the proportion of which is over 95%. Therefore, the key point for energy saving and emission reduction in the construction

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industry lies in optimizing the using structure of building materials and improving the production technology of cement and steel. It is mentioned that 20–30% of landscape materials should be recyclable in relevant standards for landscape material such as the Singapore Park Evaluation Criteria and the Sustainable Sites Initiative (Ji et al. 2015). In landscape construction, we also need to choose materials with higher production technology and lower carbon emissions as much as possible. Local materials are preferred, with the advantage of shortening the transportation distance, thus reducing the carbon emissions in the construction process.

5.4 High Carbon-Sequestration Plants to Increase Carbon Sinks Carbon sinks mainly originate from the carbon sequestration of plants in the green space. Although there is a certain amount of carbon emissions in the stage of landscape construction and maintenance, the amount of carbon sequestered by plants will reach a certain equilibrium with the carbon emissions in a few years. A higher positive ecological feedback will be obtained over time. How to make this equilibrium point earlier and generate longer-term carbon sink benefits is a key issue in the scheme design. The amount of carbon sequestered by plants is closely related to the diameter at breast height (DBH), the crown width and the species of plants. Under the same conditions, plants with strong carbon sequestration should be selected as the backbone species. In addition, replacing the lawn with perennial herbaceous plants is also a way to increase carbon sequestration, because the lawn itself has a low-carbon sequestration capacity and needs to be mowed frequently, while groundcovers and perennial herbaceous plants do not need to be mowed, with better carbon sequestration benefits than the lawn (Ji et al. 2020). If permitted, a certain amount of three-dimensional greening can also be added to the roof and outer skin of the building to generate more carbon sinks.

6 Conclusion It is an important basis and prerequisite for urban renewal projects to calculate carbon revenue and expenditure in the early stage of scheme design. This paper constructs a design-oriented estimation method system from both architectural and landscape aspects, aiming at quantitative assessment of the carbon reduction benefits of design solutions and timely design feedback for scheme selection and optimization. In the context of stock development and urban renewal, this study has implications for controlling carbon footprint and achieving the “double carbon” target. There are still some limitations in this study. Firstly, the carbon balance accounting for buildings and landscape is limited to the materialization stage of the whole life

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cycle in the renewal process, and further research on the carbon balance of the operation and maintenance stage is needed to complement. Secondly, in the BIM model of this study, only the quantities of some basic materials are counted, and there are inconsistencies or missing in the carbon emission factor data from the existing studies, which both affects the accuracy of the research results to some extent. In addition, the geographical factors have not been taken into account in the existing database of carbon emission factor. The final calculation results will be more scientific and adaptable with the local database that is more suitable for the project site.

References Cang YJ, Luo ZX, Yang L et al (2020) A new method for calculating the embodied carbon emissions from buildings in schematic design: taking “building element” as basic unit. Build Environ 185:107306 Guan J, Zhang Z, Chu C (2016) Quantification of building embodied energy in China using an input-output-based hybrid LCA model. Energy Build 110:443–452 Ji YY, Luo JW, Wang T et al (2020) Quantification of carbon sources and sinks in the whole life cycle of the landscape based on low-carbon concept–Tianjin Silingyuan residential area as an example. China Garden 36(08):68–72 Ji YY, Luo JW, Wang T (2015) Research on the evaluation system of landscape gardening under the concept of sustainability. China Garden 31(2):51–55 Jin LH (2019) Research on carbon storage and carbon sink benefits of landscape plants. Zhejiang University of Agriculture and Forestry Luo (2016) Research on the calculation method and emission reduction strategy of life-cycle carbon dioxide emissions of buildings. Xi’an University of Architecture and Technology Luo ZX, Cang YJ, Yang L et al (2021) Research on building-based carbon emission calculation method for the whole design process. Build Sci 37(12):1–7+43 Martin R, Alexander H, Guillaume H et al (2018) LCA and BIM: visualization of environmental potentials in building construction at early design stages. Build Environ 140:153–161 Nässén J, Holmberg J, Wadeskog A et al (2007) Direct and indirect energy use and carbon emissions in the production phase of buildings: an input-output analysis. Energy 32(9):1593–1602 Shao L, Chen GQ, Chen ZM et al (2014) Systems accounting for energy consumption and carbon emission by building. Commun Nonlinear Sci Numer Simul 19(6):1859–1873 Shi HW, Qin Q, Liao JX, Chen GQ, Ding ZQ (2011) Study on carbon sequestration and oxygen release capacity of 10 dominant garden plants in Wuhan. J Central South Univ Forest Sci Technol 31(09):87–90 Wang J, Huang Y, Teng Y et al (2021) Can buildings sector achieve the carbon mitigation ambitious goal: case study for a low-carbon demonstration city in China. Environ Impact Assess Rev 90:106633 Yan Y (2011) Study on the evaluation of energy consumption and CO2 emissions in the whole life cycle of buildings in Zhejiang Province. Zhejiang University Yin LH, Hang T, Xu YR (2020) A study on the performance of carbon sink in the blue-green space of Wuhan Garden Expo Park. South Architect (03):41–48

Implementation-Oriented Renewal Planning of Suburb Townlet in South Jiangsu: A Case Study of Zhangpu Old Town in Kunshan H. T. Wang, S. Q. Gao, and W. Z. Lu

Abstract High quality development of suburban townlets is one of the important ways to promote new urbanization and achieve sustainable development. Based on in-depth analysis of developing distinctiveness of suburban townlets in southern Jiangsu, four realistic dilemmas these outskirts towns have encountered are pointed out—unclear positioning, obscure characteristics, insufficient space and poor quality. From the perspective of urban renewal, this paper creatively puts forward a fourin-one renewal framework of “positioning reshaping—comprehensive evaluation renewal scheme—implementation plan”. With fulfilling actual demands of Zhangpu old town as the starting point, implementing planning as orientation, and building a compound and dynamic community in southern Kunshan as the goal, this paper builds a road to the revival of the old town that integrates “humanism, liveliness and livability”, providing reference for sustainable development of other suburban townlets. Keywords Sustainable development · Suburban townlet · Urban renewal

1 Introduction In the context of new-type urbanization, China’s urbanization process is stepping forward from speed to quality. The high-quality development of small-town construction is one of the important ways to promote new-type urbanization and achieve sustainable development. With the gradual formation of the national territorial spatial planning system and the delineation of “three zones and three lines”, small town construction as represented by Southern Jiangsu, has entered an era of development from large-scale incremental expansion to co-existence of stock renewal and incremental restructuring, where urban renewal is in full swing. As the first hinterland for urban spatial expansion, suburban small towns have rapidly emerged as an important carrier of southern Jiangsu’s economy. However, due to fierce external competition, H. T. Wang · S. Q. Gao · W. Z. Lu Tus-Design Group Co., Ltd, Suzhou, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_28

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the shortage of urban land space and the exposure of their own institutional defects, the traditional development model is no longer sustainable. Thus, demand for urban renewal is increasingly urgent and transformation has become an inevitable trend. The current research on suburban small towns mainly contains three aspects. First is clarification of research objects, including the definition of relevant concepts (Zhang et al. 2022), connotation analysis (Zhang and Dong 2005), and characteristics combing (Zhang et al. 2012). Second is the study of relevant mechanisms, ranging from developing models to driving mechanisms (Xu and Zhang 2004; Zhao et al. 2018). Third is clarification of development strategies and paths in combination with empirical research, such as “town-industry” development strategy (Wang et al. 2017), the flexible urbanization path of “four synchronization” (Lin et al. 2015), and the two new urbanization paths of “top-down town spatial path and bottom-up village social unit” (Zhang and Xiao 2016), etc. Whereas there are fewer studies from the perspective of urban renewal. In this study, we thoroughly analyzed the development characteristics and dilemmas of suburban small towns in southern Jiangsu, then combined relevant theoretical and empirical studies to construct an exploratory framework for the regeneration of suburban small towns, and finally developed an implementation-oriented planning scheme based on the actual demands of Zhangpu Old Town in Kunshan, with a view to providing experience and reference for the sustainable development of suburban small towns.

2 Dilemma Faced by Small Suburban Towns in Southern Jiangsu 2.1 Unclear Positioning: Disorderly Construction Under the Game of Multiple Subjects As a transition zone between urban and rural areas, suburban small towns play a more diverse and complex role. On the one hand, industrial development, residential properties, and public facilities in city center are gradually spreading to the periphery under the trend of urban expansion, accelerating the passive urbanization of small suburban towns in the form of project development, and making their positioning more functional and specific. On the other hand, in order to expand developing capacity and accelerate the urbanization process, most small towns blindly seek to high, fast, and comprehensive growth. What’s more, dual models of top-down and bottom-up work together in small towns. The game of interests between the city (county), town, village, and other multiple subjects leads to unclear positioning of town development and disorderly construction.

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2.2 Lack of Characteristic: The Lack of Humanities Under Rapid Urbanization Thanks to the superior location, most suburban small towns have a long history of development, a deep historical heritage and excellent resource endowments. However, due to a lack of cultural preservation awareness during the development process, a large number of cultural relics and historical folklore have been destroyed under the crude development model. As a result, many historical buildings and literati houses in traditional old streets have either been transformed beyond recognition or are hard to find. In their place, a uniform urbanized look during the rapid urbanization process lacks heritage, humanity and distinctive features.

2.3 Insufficient Space: Inefficient Development Under Extensive Space Growth Since the reform and opening, small towns in southern Jiangsu have flourished (Chang 2022). From the “blossoming” township enterprises to the construction of township industrial parks, the accelerating industrialization has driven the rapid development of urbanization. However, a serious disconnect between urbanization and industrialization as well as the problem of low spatial efficiency have arisen because of the unilateral pursuit of economic benefits and the lack of systematic planning, with small suburban towns being particularly distinctive. During the pre-mid urbanization process, small suburban towns have experienced rapid spatial expansion and land enclosure, but as the new urbanization demands high quality development, the problems arising from the crude model are gradually exposed. On the one hand, there is a lack of space for back-up development due to blind expansion in the early stage, and on the other hand, the overall landuse efficiency and the development intensity is quite low, especially for traditional industrial enterprises, which are mostly one-storey factory buildings with floor area ratios of less than 0.8. Thus, how to ask for space from the stock has become an important entry point for suburban small towns to break through the existing dilemmas, which is becoming increasingly urgent.

2.4 Poor Quality: Spatial Collage Under the Urban–Rural Dichotomy Influenced by both urban and rural areas, small suburban towns in southern Jiangsu present a spatial pattern both urban and rural. In terms of spatial layout, land uses are intermingled and lack of reasonable zoning, with mixed functions of industry and residence. In the field of traffic organization, there is an inadequate road hierarchy,

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including bypass networks shortage, abundant end roads and cut-off roads, together with poor internal accessibility, confusing parking spaces and frequent traffic accidents. As to public services, contradictions between supply and demand stand out, with low levels of service facilities and insufficient per capita indicators. In terms of ecological environment, there lacks systematic planning, open space and sufficient public green space. What’s worse, the absence of environmental awareness among savagely growing township enterprises has led to serious damage to ecology. In a word, under the influence of the dual structure of urban and rural areas, small suburban towns have a mixed and collaged internal space, where the overall quality needs to be improved and upgraded.

3 A Framework for Regeneration of Small Suburban Towns in Southern Jiangsu As an important path to lead high-quality urban development, urban renewal has been on the rise in recent years. However, most relevant research and practice focus on urban space, such as “Urban Renewal Unit” in Shenzhen, “Three Old Transformation” in Guangzhou and “Reduction Planning” in Shanghai. Planning researches of small towns in the suburbs are still insufficient. Based on real-life dilemmas of small suburban towns in southern Jiangsu, the study takes urban renewal as an entry point and combines it with the practical exploration in small townlets to build a fourin-one renewal framework of “repositioning—comprehensive assessment—renewal plan—implementation plan” (Fig. 1).

Fig. 1 The four-in-one regeneration framework

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3.1 Repositioning Under the Dual Orientation of “Challenge” and “Opportunity” Scientific grasp of town development positioning is core of the renewal framework. In the traditional planning system, positioning is largely target-oriented or problemoriented, but small suburban towns are more complex and special. Thus, their regeneration and development must take dual orientation of “challenge” and “opportunity” into account systematically. The “challenge” indicates the reality of predicament, which the renewal positioning should firstly solve according to the intrinsic characteristics of each town. “Opportunity” means development chances, including external factors such as policy strategy, location pattern and regional transportation, as well as internal factors like infrastructure layout, location of large-scale construction projects and exploitation of human and ecological resources.

3.2 Comprehensive Assessment of the Current Situation from a Multi-Factor Overlay Precisely identified town space is the carrier of the renewal framework of small suburban towns. As a “collection of resources”, the town space is a container full of multi-dimensional resources such as architectural space, public facilities, ecological environment, social and humanities, etc. How to objectively assess the existing resources and accurately identify the town space is a prerequisite for regeneration planning. With the objective of realizing regeneration positioning, the study uses factor analysis and Delphi method to build a construction space evaluating system. Besides, the study also applies multifactor overlay analysis of the current situation elements with ArcGIS as a tool, to form a comprehensive evaluation map of construction space. Eventually, it identifies four types of regeneration space: preservation, renovation, demolition and reconstruction, as well as new construction land. This will lay a spatial foundation for the subsequent regeneration scheme, implementation path, renewal timeline and project placement.

3.3 Organic Renewal Guided Regeneration Planning Scheme The quality of the regeneration scheme is key to building a regeneration framework. Proposed by Professor Wu Liangyong, the organic renewal theory advocates that from the city to buildings, all parts should be as organically connected and harmonious as living organisms, and that the regeneration and development of the town must follow the original town fabric and comply with its inherent order and development laws. Based on this concept, the study raises three core issues. First is characteristics manifestation—taking the differences in development motivation,

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resource endowment and town construction into account. Second issue is spatial optimization. Starting from the current spatial base of the small town, system planning theory is used to sort out the spatial chain, optimize the functional layout and improve the system organization, so as to change the disorderly spatial collage into orderly spatial association. The last issue is quality improvement. In the view of humanism, the scheme builds a multi-level living circle and improve public services to meet residents’ diversified needs.

3.4 Key Project-Oriented Regeneration Implementation Plan Identifying key projects and implementing regeneration plans is an important way to promote the regeneration of small towns with high quality. Compared to traditional planning, regeneration planning places more emphasis on the practicality and implementability, so it is particularly important to advance the implementation plan in an orderly manner. Firstly, the specific implementation path and regeneration mode of each plot should be clarified and a detailed study should be carried out on key plots. Secondly, it is necessary to coordinate multiple departments with diverse stakeholders to build a regeneration platform and clarify the implementation mechanism. Finally, the regeneration plan should be translated into specific implementation projects, containing refined content, regenerated timeline, and construction mode.

4 Regeneration Planning Practice in Zhangpu Old Town, Kunshan Zhangpu Old Town, Kunshan, is in the core hinterland of the Yangtze River Delta. Driven by the dividends of reform and opening, Zhangpu has rapidly grown into a typical representative of small suburban towns in southern Jiangsu. Behind the rapid urbanization, a series of problems have arisen in Zhangpu, such as interweaved urban and rural areas, mixed industry and residence, sloppy land use as well as environmental damage. In order to reshape the new pattern of waterside towns of Southern Yangtze and realize high-quality and sustainable development of Zhangpu Old Town, a four-in-one regeneration framework is constructed (Fig. 2).

4.1 Strategic Repositioning: Reviving the Old Town and Creating a Vibrant Community The plan starts with a regional value review of Zhangpu Old Town from multiple aspects. Combined with site investigation and questionnaire survey, the plan further

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Fig. 2 Technical route for renewal planning of Zhangpu Old Town

analyses the real dilemma of the site. Firstly, the traditional township development mode is not in line with the regional position. Secondly, Zhangpu Old Street is lack of effective protection and restoration. Thirdly, numerous traditional township enterprises and urban villages are built spontaneously, lacking systematic planning and spatial order. Fourthly, low-level township supporting facilities, together with a broken ecological system, results in poor space quality. Based on the regional value and realistic dilemma, the plan re-examines its strategic positioning and establishes a shift in thinking from “town” to “city”. A general vision of “revitalizing the old town and creating a vibrant community” is proposed. Furthermore, a triple definition of “vibrant community” is given, namely, a humanistic and leisure community, a fun and inclusive community and a low-carbon and livable community.

4.2 Comprehensive Assessment of Current Situation: Spatial Evaluation and Identification of Differentiated Regeneration Spaces A multi-factor evaluation system is constructed to make a comprehensive assessment of the town space in order to clarify the spatial base for planning scheme. Firstly, a multi-factor selection process is carried out to evaluate the selected six elements:

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Fig. 3 Comprehensive assessment of the current situation in Zhangpu Old Town

land use, industrial efficiency, road transportation, building quality, ecological environment and supporting facilities. Secondly, each single factor is assigned different weights by using the Delphi method to clarify the importance of each factor to the regeneration scheme. Finally, the GIS multifactor overlay analysis is applied to accurately identify current space and form the base of a comprehensive assessment of the construction space (Fig. 3). Ultimately, four types of regeneration space are defined: preservation and upgrading, renovation and transformation, demolition and redevelopment, and conversion of non-construction land to construction land.

4.3 Renewal Planning Scheme: The Revival of Zhangpu Old Town 4.3.1

A Catalyst to Inherit History and Culture and Create a Humanistic and Leisure Community

Respecting the spatial texture and humanistic memory of Zhangpu Old Street, the scheme optimizes the spatial pattern and implants new cultural and leisure business forms which integrates with tourism, art as well as commercial functions, hoping to interpret Zhangpu Humanistic New IP. The first strategy is reshaping the spatial structure of “fishbone vein + open nodes” in order to create a pedestrian-friendly open neighborhood. And then, open space nodes are laid out at the intersection of main street and secondary lanes, where public activity scenes are set up. The second strategy is about empowering revitalization and gathering diverse functions. Five major functions are planned: “residence, tourism, retail, exhibition and innovation”

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to create differentiated functions and hierarchical consumption, enhancing the appeal and maximizing the vitality of neighborhoods.

4.3.2

K1 Rail Line as Opportunity for Mixed Development and Shaping an Inclusive Community

Consider K1 rail line as a bridge for regional factors and talents, promote mixed and integrated development based on surrounding land uses with the rail station as the core, strengthen vertical transport interchange, stimulate the vitality of the old town, promote the level of town services, and shape a diverse and vibrant community. Firstly, TOD mode leads the way to create a living center in the old town. Based on gathering effect of the rail hub, the plan is going to implant new lifestyle services such as “health service+”, “elderly service+”, “sports+” and “property+”, which encourages people to stay longer and enhance the vitality of the area. In addition, it is significant to build a comprehensive transport network and efficient linkages of supporting facilities. One tactic is to optimize the bus network system by connecting the regular bus system and micro-bus loop with the rail line K1 stations. Another tactic is to choose the location of bus stations with full consideration of the supporting facilities, so that previously scattered supporting facilities can be organically linked through the bus network for higher accessibility.

4.3.3

Building a Low-Carbon and Livable Community with an Ecological Green Ring as a Link, Supporting by People-Oriented Design and Complementary Facilities

In this strategy, the vital attempt of improving the living quality of the old town of Zhangpu, is to connect existing water system and parks, contributing to a green, lowcarbon and rich ecological green ring. Besides, the “neighborhood + community” mode is used to build living units, by improving public services and optimizing the spatial organization of the community, to achieve vision of building a model community in the new riverside town of Jiangnan. One tactic is to set greenery network for ecological ring. Based on the current water system, disconnected rivers are dredged to connect with the regional water network. Another is to improve the supporting facilities and build a livable living circle. A two-level service system of “neighborhood level and community level” is created.

4.3.4

“Humanistic, Lively and Livable” Trinity to Build a Vibrant Community in Kunnan

From the perspective of organic regeneration, the plan is dependent on the development background of old Zhangpu and draws up a general spatial structure of “two axes, two rings, and two centers, intertwined with water and greenery” in order to

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Fig. 4 Urban design scheme for Zhangpu Old Town

realize the overall vision of “revitalizing the old town and building a complex and vibrant community in Kunnan”. What’s more, the regeneration plan also proposes a trinity model of “ humanity, activity and livability”, which aims to build a humanistic and leisure community, an inclusive community, as well as a low-carbon and livable community (Fig. 4).

4.4 Renewal Implementation Plan: Multi-Pronged and Project-Based Approaches 4.4.1

Demolition and Construction in Parallel, Unified Planning and Step-By-Step Regeneration

The renewal implementation plan puts forward a regeneration principle of “unified planning, phased implementation, easy to difficult, dynamic renewal”. Based on the urgent needs and long-term development goals of the old township of Zhangpu, the plan defines a clear time sequence for regeneration, sets the goals and tasks of each phase of regeneration, and implements them in order (Table 1). In the short run, renewal purpose is to highlight humanistic characteristics of Zhangpu and build a demonstration standard of livable community. Mid-term objective is to improve public services and enhance the quality of ecological environment. As to long-term vision, the plan aims to create a living center in old town as well as a vibrant and multi-functional community.

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Table 1 Renewal timetable of Zhangpu Old Town Renewal timeline

Renewal objectives

Key tasks

Short-term (2022–2025)

Highlighting the humanistic characteristics of Zhangpu Constructing a model standard for livability

(1) Upgrading the garden community of Anqiantou and Tangjiajiao and the new Zhangpu Community of Pujiang River; (2) Renovating the granary in Zhangpu Old Street to guide the humanistic gathering and build a cultural base; (3) Developing the area east of the Miaowan River as a model of livable community; (4) Relocating the Sixth Kunshan Hospital to strengthen regional public service support

Mid-term (2026–2030)

Improving public (1) Developing and constructing north-west side service support areas of the Zhipu River to create a riverfront livable community; (2) Building an ecological Enhancing the quality of ring to improve the quality of public ecological environment environment; (3) Developing the image of north side of Haihong road

Long-Term (2031–2035)

Creating the center of life in the old town Shaping a complex vibrant community

4.4.2

(1) TOD combined with the rail; (2) Improving public service support and southern livable community construction

Refined Design of a Block in Retention, Renovation, and Demolition

Firstly, blocks are numbered by the boundary of roads, canals and green area according to the layout plan. Secondly, three types of renewal modes are defined, including retention, renovation and demolition. Then, these blocks are settled by current cadasters, land use, renewal mode and renewal time sequence. Finally, taking block as unit, a summary table of neighborhood regeneration is formed and a refined urban design is expected as a sequence. Taking Zhangpu Old Street and Granary as an example, the project straddles block NO. 5 and NO. 7, with the current cadaster of Puxi Village, Xujia Alley, Zhangpu Cultural Station, Rujia Hotel and Zhangpu Grain Management Office. Current landuse, including R3, A22, B1 and W1, interlocks with each other. The plan integrates various land uses into A22, B1 and B9, and adapts two types of renewal modes: renovation together with reconstruction, in order to gather diversified humanistic resources and create a cultural and creative leisure district (Fig. 5).

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Fig. 5 Zhangpu old street business type layout

4.4.3

Coordinating the Interests of Multiple Subjects, Building a Regeneration Platform to Co-Ordinate Development and Operation

The plan proposes to establish a coordinating body under the leadership of the town government—the “Renewal Development Committee”—as a platform for the renewal of the old town area of Zhangpu, with the deputy mayor in charge of urban and rural construction as the director. Then a joint regeneration team will be set up with Natural Resources and Planning Bureau in charge of land acquisition and planning, Urban Construction and Administration Bureau in charge of demolition, relocation, and project construction, Finance Bureau in charge of project creation and fund raising, and Business Promotion Bureau in charge of project management and investment operation. At the same time, each department has occasion to actively communicate with all stakeholders, and then hand over resolution to the “Regeneration and Development Office”, an executive body set up under the department, for concrete implementation. The establishment of the regeneration platform will ensure the co-ordination of all departments, the participation and joint development of multiple interests, and the efficient implementation of the plan.

4.4.4

From Planning to Projects, Four Types of Action Plan Are Constructed to Implement the Area Renewal

The regeneration plan is implementation-oriented, translating the planning design of old Zhangpu into 29 subdivision projects. Furthermore, a key-project pool of annual construction plan is established, which contains four categories of upgrading actions: livelihood services, infrastructure, ecological environment, as well as industrial and

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residential construction. Through the four types of upgrading action plan, annual key projects will be orderly implemented and sustainably promoted within high quality.

5 Conclusion The practice of regeneration planning in the old Zhangpu is of exemplary significance for suburban towns. Undoubtedly, urban regeneration is a long-term action and a complex subject, and the regeneration framework set by the study is more oriented towards spatial upgrading and renewal. Due to the complex dilemmas faced by small suburban towns, it is necessary to extend the framework in multiple areas such as policy protection and institutional mechanisms in the future. Only a more complete renewal system is established to systematically guide urban renewal.

References Chang Y (2022) Establishing an evaluation system for urban regeneration planning programme based on ERG theory. Planners 38(11):58–64 Lin KX, Zhou M, Huang YP (2015) ‘The study of suburan towns’ development momentum and mode in the context of “four modernizations synchronization”: the case study of Wulijie in Wuhan. Mod Urban Res 08:85–91 Wang HT, Chen X, Lei C (2017) Study on the town-industry integration development model and strategy of town in south of Jiangsu: a case study of Qiandeng Town in Kunshan City. Modern Urban Res 05:82–89 Xu SJ, Zhang XK (2004) Literature review on small towns since 1990s. Urban Plann Forum (03):79– 83 Zhang XH, Dong YW (2005) Environmental protection and ecological construction of suburban small towns—A case study of Ganquan Town Hanjiang District, Yangzhou City. Dev Small Cities Towns 04:80–81 Zhang L, Bai YX, Pang L (2022) The research progress and prospect of small town development and planning in China since 2000. Urban Rural Plann 01:61–85 Zhang ZJ, Xiao SY (2016) Study on new urbanization path of suburban towns under urban expansion. In: Proceedings of 2016 China urban planning annual conference, pp 134–145 Zhang L et al (2012) Practice of general planning of small suburban towns based on characteristics: a case study of general planning of Caiji Town, Suqian City. In: Proceedings of 2012 China urban planning annual conference, pp 790–798 Zhao H, Zou XL, Li GC (2018) Spatial optimization of suburban townlet in the pearl river delta based on the perspective of urban agglomerations: a case study of Shaxi Town in Zhongshan. Modern Urban Res 09:56–63

Research on ‘5–10–15 Minutes Life Circle’ Planning in Urban Boundary Based on Landscape—Led Method—A Case Study in Beiqiao Town, Xiangcheng District, Suzhou Lingyi Xiang, Shuyi Wang, and Liuxiulin Zou

Abstract To attract more young people return to urban-rural fringe areas, this research aims to shed light on the regeneration of Beiqiao District. Using Beiqiao village as a pilot study, this research combines landscape-led regeneration principle with 5–10–15 minutes life circle to optimize the living facilities. Previous research in this field indicated that facilities and other resources allocated within the 5–10–15minutes life circle in residential areas had an important impact on people’s quality of life. However, the current layout of facilities are mainly designed based on the accessibility of the facilities, while the ecological matrix of the city has not been properly taken into account in urban planning and design. Based on onsite observation, questionnaire and interview, the information of landscape layout, life facilities status and people’ s satisfaction were collected. It was found from this survey that the existing facilities, especially those related to cultural and sporting activities, did not fully meet the needs of residents. In addition, the distribution of this facilities was unbalanced. As for landscape, there has a variety of types as Ezhen Lake, farmland, interlaced river and green space without a specific purpose. Based on these findings, it is recommended that facilities should be not only upgraded according to the age composition of residents and daily activity but also be integrated with landscape in order to setting up a spatial pattern. Keywords Life circle · Landscape-led method planning · Urban regeneration · Urban planning

L. Xiang · S. Wang Urban Planning and Design, Xi’anJiaotong-LiverpoolUniversity, Design School, Suzhou 215028, China L. Zou Economics and Finance, InternationalBusinessSchool, Xi’an Jiaotong-Liverpool University, Suzhou 215028, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_29

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1 Introduction 1.1 Research Background 1.1.1

Industry Clusters in City

Urbanization is a necessary process for mankind to transform from an agrarian society to a modern society (Zhao 2007). According to Chinese Statistical Yearbook 2021 published by National Bureau of Statistics of China, from 1949 to 2020 (National Bureau of Statistics of China 2021), the percentage of urban proportion increased from 10.64 to 63.89%, which means urbanization is seen as an important strategy for developing in China. Industry clusters often defined as the concentration of the same or different types of industries within a certain geographical area in order to obtain productive benefits (Hu 2021) is considered to be the driving force of the urbanization process, leading to the growth and prosperity of the regional economy (Chen 2012). Zhao (2007) believed that the use of industry clusters guiding urbanization process can achieve the rational allocation of urban resources and targeted optimization of industrial development and the government also has detailed requirements for the infrastructure and sustainability of the industrial park (GB/T 38538-2020 2020). However, due to the attractive income and convenient living surroundings, more and more people are leaving their hometowns for better facilities and opportunities in the industrial clusters area, leading to the challenge of hollowing out and poor development in the non-industrial clusters area as rural area or city boundary.

1.1.2

Establishment of the Life Circle

The concept of ‘Life circle’ originated in Japan. In 1962, based on the central place theory, the idea of “life circle composition” was proposed, which means people enjoying facilities at different spatial and time scales (Dai 2016). The idea was used to restore Japanese cities after World War II and was extended to ‘Wide area living circle’ in 1969 and ‘Settlement circle’ in 2007 (Wu et al. 2021). Based on this, various countries such as South Korea (Ma 2020), United States (Ma 2020) and Paris (Dessin 2022) have incorporated this concept into their own planning to reallocate and manage urban resources because the improper planning in the past has led to the decay of city. In 2018, Chinese government also launching ‘5–10–15 minute Life Circle’ policy to achieve urban regeneration as Standard for Urban Residential Area Planning and Design (GB50180-2018) and patial planning guidance community life unit (TD/T1062- 2021).

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Up−Planning of Beiqiao

Beiqiao is located in the Xiangcheng district of Suzhou, on the border with Changshu. The overall plan of the Xiangcheng district is divided into technology industrial park and ecological service area covered in one-hour traffic circle with Shanghai, Nanjing and Hangzhou. As Fig. 1, Beiqiao has planned to be a city backyard to provide natural resources to the technology industrial park (industry hub and city living room). As the backyard of the city, Beiqiao should strengthen the construction of ecological landscape, in accordance with the people-oriented, comprehensive coordination of green and sustainable development concept, and rely on water resources, green space resources, cultural resources to guide regional construction.

1.2 Literature Review According to a literature review in Figs. 2 and 3, although the two concepts have been widely discussed by scholars, the strategy of establishing 5–10–15 minute Life Circle still does not use landscape-led method. Therefore, this project is focused on whether the landscape-led method is possible to be used in the establishment of 5–10–15 minute Life Circle in Beiqiao.

1.3 Aim Based on the “5–10- 15 minute living circle”, this project takes residential facilities in Beiqiao Town, Xiangcheng District, Suzhou as the research object, to explore the satisfaction of residents while assessing the community living circle. The results of the study are used as a foundation to propose countermeasures and recommendations for urban regeneration in urban boundaries.

1.4 Objective and Method . Object 1: The establishment and operation of the knowledge system. In this section, the background, theories and cases of urban regeneration, ‘5–10–15 minute living circle’ and ‘landscape led approach ’ are cleared by means of literature review. . Object 2: Summary of the factors contributing to the topic. This section is focus on the construct of framework to evaluate the current status of ‘5–10–15 minute living circle’ facilities and landscape in site through literature review.

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. Object 3: Evaluation results of the current state of the site. Firstly, observation is used to record the types of facilities and landscaping of site. Then, interview is used to obtain basic information from government agencies. What’s more, information about the living conditions from local residents also gathered by interview. Fourthly, the questionnaire was used to note the residents’ use and satisfaction with the facilities and perception of the landscape. Finally, the framework and information are combined to conclude the assessment. . Object 4: The outcome of building a ‘5–10–15 minute Life Circle’ with the landscape-led method. The literature review and case study were used to help the optimization of site living circles through a landscape-led method and the recommendation for urban regeneration processes in urban boundary.

1.5 Research Framework In appendix, Fig. 4.

2 Beiqiao 2.1 Background Beiqiao Town is located in the north end of Xiangcheng District, Suzhou City, and connected with Changshu City. It is a town with rich cultural heritage and natural resources. Beiqiao Town borders Wuxi City and Changshu City, with superior geographical location and obvious advantages in traffic location. Regional topography is relatively flat, small elevation difference, are plain landform. The climate is subtropical monsoon climate, warm and humid, for residents to provide a comfortable living environment. Beiqiao Town is rich in water resources. It is bounded by Caohu Lake and Idzhentang Lake in the west, Yechangjing Lake in the south and Wangyu River in the north. There are also two river courses in the middle of the area, which roughly run from northeast to southwest and northwest to southeast, and intersect in the middle of the area (Figs. 5, 6, 7 and 8).

2.2 Determination of Site Covered an area of 0.033 km2 , the study area is the Beiqiao village, which is located in the sijin community, intersecting with the Lianhuazhuang village as Fig. 9. The

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village is overpopulated, resulting in a resident population of less than 100. The Beiqiao village is divided into Beiqiao East Street, Beiqiao West Street, Beiqiao Cross Street and the behind the beiqiao village. Because most of the residential areas at the behind the beiqiao village are spread out next to factories, the three streets with more concentrated residential areas were chosen as research site. The buildings of the Site were built along the Beiqiao River, forming a traditional Jiangnan water town layout. The patriotic fame instrumental music factory and archives are the historical buildings here. Most of the people living here are elderly people and middle-aged people who come to work in the factories around the area. Young people and teenagers have moved out of the site to Xiangcheng District or central Suzhou, which resulting in the Fig. 10.

3 Investigation and Research 3.1 Questionnaire Details Statistics Through field visits, we collected 14 valid questionnaires. The number of people who filled in the questionnaires was 7 women and 7 men, with a ratio of exactly 1:1. Among them, the analysis of the age structure of the survey population shows that the proportion of men over 60 years old and women over 55 years old accounts for exactly half of the survey population, accounting for 50%.

3.2 Analysis on Indicators of Life Circle Combining with the needs of residents, analyzing the importance of various residential public service facilities will help to reasonably allocate supporting facilities from the needs of residents. The questionnaire divides the satisfaction with the facilities into five levels: strong disagree, somewhat disagree, no impact, somewhat agree and strong agree. Through the statistics of the questionnaire data, we can obtain the analysis chart of the degree of satisfaction with the use of facilities (as shown in Fig. 11) and the analysis chart of the satisfaction with the use distance of various facilities (as shown in Fig. 12). The service facilities asked in the questionnaire are health care, sports facilities commercial facilities, sports facilities, education facility, management services and transport facility.

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3.3 Analysis on Indicators of Landscape Guidance The ecological protection in this area is weak. Most residents reflect that the water quality of the river is poor and needs to be improved (Fig. 13). Various facilities in this area need to be built urgently. Residents have a strong desire to build ecological wetlands beside the river and ecological parks with ornamental and beautifying values (Fig. 14).

4 Landscape-Led Method to ‘5–10–15 Minutes Life Circle’ Delineation 4.1 ‘5 Minutes Life Circle’ The ‘5 minutes life circle’ is generally considered to be a walkable circle that meets the daily productive needs of the residents, which is usually divided by the settlement boundary (Zhu 2021). In GB50180-2018, this is a circle with a radius of 300 meters holding 1500–4000 houses and 4000–12,000 people.

4.2 ‘10 Minutes Life Circle’ ‘10 minutes life circle’ focus A Focus on facilities with medium frequency of use and service capacity (Chen 2021). In addition to the facilities required to meet the needs of the residents in ‘5 minutes life circle’, ‘10 minutes life circle’ is an additional space for the necessary activities and spontaneous activities of them (Chen 2021). It can be made up of multiple ‘5 minutes life circle’ to connect the other two levels

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of the community life circle (Zhu 2021). In GB50180-2018, this is a circle with a radius of 500 meters holding 5000–8000 houses and 15,000–25,000 people.

4.3 ‘15 Minutes Life Circle’ ‘15 minutes life circle’ is an ideal that offers a high level of service facilities with comprehensive content meeting the individual needs of residents. It can be used simultaneously with other facilities where the circle of life overlaps (Wu 2021). In GB50180-2018, this is a circle with a radius of 1000 m holding 17,000–32,000 houses and 50,000–10,0000 people.

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4.4 Landscape-Led Method 4.4.1

Landscape

The meaning of landscape is relatively broad, and mainly has two meanings: the first is landscape, that is, human vision can see the surface landscape, expressed in the form of geomorphology, and hydrology, such as mountains, hills, swamps, lakes, oceans and others. The second is the anthropogenic landscape built by man on the surface landscape (Pan 2019). The Encyclopedia of China Geography (1994) summarizes several understandings of landscape in geography: ➀ the comprehensive characteristics of a region, including natural, economic and cultural aspects; ➁ general natural complex; (3) Regional unit, which is equivalent to the smallest first-level natural area in the comprehensive natural zoning grading system; (4) Any regional unit.

4.4.2

Landscape-Led

Landscape-led, the landscape as the base for planning an The concept of ecological urbanism was introduced by Frederick Steiner in 2011. There are three possible research directions of landscape ecological urbanism: the evolution of aesthetic cognition; Ecology’s deep understanding of human agency; Reflective Learning through practice (2011). According to Lin and Wang (2019), ecological urbanism treats cities as an ecosystem and emphasizes urban mobility, which is more conducive to the sustainable development of cities. 1. Optimize the ecology: the current situation of the water landscape is not ideal, so it is necessary to clean and maintain the river first to increase the diversity of animals and plants. 2. Shaping the landscape: build a river walk and set gardens at the nodes to improve the waterfront landscape and enhance its attractiveness of the waterfront landscape.

4.5 Model Construction 4.5.1

‘5–10–15 Minutes Life Circle’

According literature review and the feedback of questionnaire, the framework of the ‘5–10–15 minutes life circle’ is define as Fig. 15.

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Land-Led Method

The planning and design guided by landscape first need to divide the functional areas from the macro aspect. Due to the similar ecological landscape framework, this region is divided: according to the historical causes and relative stability (or relative variability in the dimension of “time”) according to the article of Chen and Yao and Zhang and Chirstian (2020). Related to the geographical circle of the natural and cultural landscape, such as topography, soil, water body, and the related material or immaterial cultural activities), and biosphere-related natural and cultural landscape, such as soil water body, plants, animals, and related material or immaterial cultural activities), related cultural landscape and human culture circle of times characteristics such as a distinctive material or immaterial cultural activities) in Fig. 16.

4.6 Delineation of the Site’s Circle of Life

5 Conclusion 5.1 Faultiness 1. There are too few references on relevant topics. Due to the urgency of time and the different scope of research topics, the references are also limited. 2. Limitations in data collection and survey methods. Because the survey method of field visit is used, the interviewees can only estimate the whole data as contingency data.

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5.2 Further Study 1. A larger volume of questionnaire data is needed to support the research. 2. During the investigation, it is found that residents are not satisfied with the infrastructure, and further investigation is needed. 3. The appearance of living facilities after upgrading needs to be studied again, and long-term observation should be made on the construction after planning.

Appendix See Figs. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 and 16.

Fig. 1 Up-planning of Xiangcheng district 2022–2035. Refer to: Made by Author

Fig. 2 Literature review of life circle. Refer to: Made by Author

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Fig. 3 Literature review of landscape-led method. Refer by Author

Fig. 4 Research framework. Refer to: Made by Aurhor

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Fig. 5 Administrative division map of Beiqiao town in 2021. Refer to: Made by Author

Fig. 6 Population in Beiqiao town. Refer to: Made by Author

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Fig. 7 Density of household population in Beiqiao Town. Refer to: Made by Author

Fig. 8 Problems in site. Refer to: Made by Author

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Fig. 9 Location of Beiqiao village. Refer to: Made by Author

Fig. 10 Details of Beiqiao village. Refer to: Author

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Fig. 11 Analysis of the satisfaction of facility use. Refer to: Made by Author

Fig. 12 Analysis of the satisfaction of facility distance. Refer to: Made by Author

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Fig. 13 The interview of river’s option. Refer to: Made by Author

Fig. 14 The advice of river’s improvement. Refer to: Made by Author

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Fig. 15 Research framework of life circle. Refer to: Made by Author

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Fig. 16 Research framework of landscape. Refer to: Made by Author

References Chen C (2021) Evaluation of the current situation of community public service facilities in the old city of Xuzhou from the perspective of living circle and optimization of their allocation. MA thesis. Urban and Rural Planning Chen N (2012) The role of industrial agglomeration in promoting urbanization in Guanzhong and its policy recommendations. MA thesis. Administration. Available at: https://d-wanfangdatacom-cn.ez.xjtlu.edu.cn/thesis/ChJUaGVzaXNOZXdTMjAyMjA5MDESB0QyNDQ5NzgaCH Bvdm95dWph. Accessed 27 July 2022 Dai J (2016) Exploring and analysing the concept of “living circles” in Japan. Archit Eng Technol Des 21:69. https://doi.org/10.3969/j.issn.2095-6630.2016.21.067 Dessin M (2022) 15-minute city—how do we get there?. Available at: https://www.citiesforum.org/ news/15-minute-city/. Accessed 21 Jul 2022 Hu HY et al (2021) Analysis and optimization of 15-minute community life circle based on supply and demand matching: a case study of Shanghai. Urbanism and Archit 36:13–16. Available at: https://doi.org/10.1371/journal.pone.0256904. Accessed 21 Jul 2022 Lin HW, Wang LC (2019) ‘Biodiversity design and evaluation of urban wetland parks: a case study of liupanshui minghu national wetland park’. J Ecol 39(16):5967–5977. Available at: https://d.wanfangdata.com.cn/periodical/ChlQZXJpb2RpY2FsQ0hJTmV3UzIwMjMxMjI2 Eg1zdHhiMjAxOTE2MDIwGgh0d2cycHlneQ%3D%3D. Accessed 27 July 2022 Ma SY (2020) Residential planning at neighborhood scale: global precedents and China’s neighborhood life-circle planning, MA thesis. Science in Urban Planning National Bureau of Statistics of China (2021) Chinese Statistical Yearbook 2021. Available at: http://www.stats.gov.cn/tjsj/ndsj/2021/indexch.htm. Accessed 4 Sept 2022

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Retrofitting the Old Residential Communities to Save Energy, Reduce Carbon Emissions, and Improve the Microclimate: A Case Study of Panmen Residential Neighbourhood in Suzhou, China X. Chen, S. Deng, B. Chen, and M. Cimillo

Abstract This research aims to explore an innovative approach to retrofit the old residential communities to save energy, reduce carbon dioxide emissions, and improve the microclimate. The urban housing stock in China accounts for almost 1/4 of the national total energy consumption and carbon dioxide emissions. To promote clean and renewable energy and energy-efficient buildings, the Chinese government has promoted the retrofit of old urban residential communities towards energy efficiency. The retrofit of old residential communities has a great potential to improve the microclimate, including thermal performance, neighbourhood wind environment, and air quality. This study takes Panmen Residential Neighbourhood in Suzhou as a case study and investigates the impacts of multiple retrofit measures on the microclimate through an interactive model. This study contributes to a better understanding of microclimate based on the analysis of the building energy performance, outdoor air temperature, relative humidity and ventilation performance at a community level. Keywords Micro-climate · Urban renewal · Energy retrofit · Residential community · Communities retrofit · Building energy simulation

X. Chen · S. Deng · M. Cimillo Department of Architecture, Xi’an Jiaotong-Liverpool University, Suzhou, China X. Chen · S. Deng School of Architecture, The University of Liverpool, Liverpool, UK B. Chen Department of Urban Planning and Design, Xi’an Jiaotong-Liverpool University, Suzhou, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_30

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1 Introduction China’s total urban residential building area accounted for 55.3% of the total national housing area by 2020 (Office of The State Council Leading Group for the Seventh National Census 2022). As Thuberc (2021) predict, the urban housing of China will peak at 35 billion m2 by 2030. Consequently, the gradual slowdown of urban residential building construction has led to the progressive ageing of existing housing stocks in urban areas. Numerous old urban residential areas are faced with problems such as insufficient outdoor activity space, poor sanitary conditions, poor ventilation, mouldy and condensation on building surfaces, and sweltering summer overheating. In addition, a large number of residential stocks and the increasing household energy demand result in extremely high residential operation energy consumption. The building operation sector in China represents 30% of the total national energy consumption and 28% of the total carbon emissions, of which urban residential buildings account for 24% of the energy use in the building sector Thuberc (2021). It is predicted that energy consumption and carbon emissions in the housing sector will increase sharply soon because of the constantly increasing demand for living quality and the use of energy-consuming facilities (Liang 2021). To reduce the energy consumption of the urban housing sector and to avoid energy use caused by the large-scale demolition and reconstruction in the cities, China has started to promote energy-saving retrofit of old urban housing and officially raised it to the national strategic level since 2021 (the State Council of China 2021). The retrofit strategies of old residential communities can potentially affect the microclimate environment of residential areas and thereby further impact the energy demand of the buildings. Microclimate simulation is a validated research method that has been widely used to investigate the thermal performance of outdoor environments of communities and its impact on building energy demand. Previous studies used this method to test the impacts of a single or multiple design or planning strategies on the microclimate performance of residential communities (Castaldo et al. 2018; Shi et al. 2019; Li and Zheng 2021; Zhang and Gao 2021; Zhang et al. 2022a, b), as well as the impacts of retrofit strategies on the thermal environment and the building energy demand of residential and public spaces (Berardi 2016; Li et al. 2022; Shen et al. 2023). This method is considered to have the potential to benefit the development of retrofit strategies in urban residential communities and provide suggestions on establishing retrofit benchmarks. However, the studies on this area are insufficient, especially for the community retrofitting and the impacts on the microclimate of Jiangsu Province. In this study, a case study of Panmenxincun Residential Neighbourhood, located in the southwest corner of Suzhou’s old town, was conducted to explore the potential of multiple retrofit measures that can improve the microclimate and building energy performance of old residential communities.

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2 Methodology 2.1 Tools and Software 2.1.1

ENVI-Met

ENVI-met is a 3D microclimate simulation software that is widely used to simulate multiple climate parameters which inform urban planning, building design, and energy-efficient retrofit. It can simulate not only various climate conditions, such as day- and night-time temperatures, humidity, wind speed, and solar radiation, but also the effects of different building materials on the microclimate of the surrounding environment.

2.1.2

DesignBuilder

DesignBuilder is a user graphical interface software specially developed for EnergyPlus, which not only incorporates all building construction, activities, opening, lighting and HVAC input sections but also features the complete material database, including building and structural materials, lighting units, windows and aerated glass, curtains and shading, etc.

2.2 Meteorological Data The Typical Meteorological Year (TMY) data is used in the microclimate and building energy simulation process. This research used both SWERA and CSWD data of Shanghai obtained from the EnergyPlus website for the simulation, which is very close to Suzhou’s data. The weather data of Suzhou was generated by Meteonorm 7.3, a widely tested and validated software (Meteonorm 2022), where the data was validated with the hourly weather data recorded by the local weather station (i.e. Suzhou weather station).

2.3 Case Study Panmenxincun is a typical case of the old residential community in Suzhou constructed in the 1980s, which consists of five- to six-storey residential buildings in linear shapes with the long façades facing south or north. The simulated area is highlighted in Fig. 1, including five residential buildings, adjacent roads, a section of the river, and surrounding landscapes. The selected area covers an area of 100 m × 100 m, which is a rational range for the microclimate

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Fig. 1 Selected simulation area of the case study residential community

simulation and covers all elements that affect the microclimate (water bodies, landscapes, and constructions). The outdoor air temperatures, relative humidity (RH), wind direction and wind velocity are the key parameters for microclimate simulation. The dynamics of the selected parameters between existing and post-retrofit situations will be quantified, visualised and compared to explore the potential and effect of different retrofit strategies on microclimate. The five buildings in the simulated area are labelled as B1, B2, B3, B4, and B5, among which B3 and B4 are connected at the short sides. The impacts of the building façades on the surrounding microclimate are considered to be consistent due to the same building structure, materials and façade texture. This study also investigates the impacts of the changing microclimate on building energy demand, using the apartments on the first floor of B3 and B4 as samples. Tsang (2020) provided a summary of the average daily usage duration of air conditioners during winter and summer in the hot summer-cold winter zone’s urban housing, revealing an average AC operating schedule of 5.05 h during winter and 8.92 h during summer. To investigate occupants’ preference for using AC during the day, it is necessary to obtain operation schedules for AC during typical summer and winter days. Several studies have quantified the percentage of hourly AC operation for a typical day, utilising selected samples of users from various architectural climate zones (Chen et al. 2010; Chen et al. 2011; Yoshino et al. 2006; Hu et al. 2013). These studies employ a rigorous sampling process that involves selecting representative cities (including Shanghai, Changsha, Chongqing and Maanshan), residential districts, and families to ensure sample representativeness and universality. They have demonstrated that urban residential air conditioning use peaks during summer between the hours of 12:00–5:00 and 18:00–22:00. While the operation rates of AC heating in winter present inconsistencies in specific schedules, they are generally consistent in showing a higher frequency of AC heating operation by occupants during the evening hours of 17:00–23:00 pm. Taking into account the climatic variations between Suzhou and the cities mentioned above, this study utilised literature and statistical data to establish two distinct energy usage scenarios, namely low-energy and high-energy user patterns,

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based on the average usage hours of air conditioning (AC) heating and cooling. Lowenergy user pattern is designed to have 4 h AC cooling in summer and 4 h AC heating in winter, while the high-energy user pattern is 8 h AC cooling in summer and 20 h AC heating in winter.

2.4 Simulated Period Selection Typical dates and time periods are selected in this simulation. To investigate the sensitivity of the changing microclimate on the building heating, cooling and total energy demand, the annual minimum temperature day in winter (January 23rd) and maximum temperature day in summer (July 21st) are selected as the typical dates for simulation. The results of different time slots are observed, which are 10:00, 14:00 and 17:00. Both microclimate conditions at 1.8 and 7 m above the ground are simulated, and the results showed slight differences, which would have minor impacts on the overall energy consumption and subsequent studies. Therefore, this paper focuses on the microclimate at the 1.8 m level of the selected case area, and uses these data to indicate outdoor thermal comfort.

2.5 Retrofit Measures The following retrofit measures are proposed to solve the common issues in the old residential communities and to improve the overall living environment and microclimate. . Demolition: dangerous illegal constructions in the community that block the roads and pedestrians, marked in red colour in Fig. 2, are demolished. . Removal: parts of the walls are removed to enhance the natural ventilation, including: the ground floor (GF) and first floors (1F) of the west section of B1; the GF and 1F of B4; the GFs of the two sections on the east side of B5; and the 1F of the east section of B4. The positions of the removal parts are marked in orange in Fig. 2.

Fig. 2 Demolition, removal and extension of the buildings and the increasing landscapes

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. Extension: building extensions are added at the southwest side to block winter winds from the wide river surface in the south and west directions; another extension is added at the northeast corner of the side to increase the indoor public space for occupants. . Landscaping: Large open spaces are created after demolishing illegal constructions to increase landscaping and greenery (see Fig. 2). Green roofs with rainwater harvesting and recycling systems are also added.

3 Results The microclimate conditions of the study area before and after retrofitting are simulated and visualised. The potential air temperature, RH and wind velocity are used to evaluate the retrofit strategies. Building energy performance and energy reduction are also discussed.

3.1 Air Temperature The potential air temperature of the selected area at 1.8 m above the ground is visualised. As shown in Table 1, there are significant improvements in potential air temperatures in the simulated area at 14:00 in January and July after retrofitting. The maximum air temperature increases in the area between B1 and B3 in January, which reaches 1.5 °C. The temperatures also increase evidently in the areas between B2, B4 and B5. Similar results can be observed in July, with evident air temperature drops in the simulated area. The maximum drop in temperature occurs between B1 and B3, which is 1.5 °C. The ranges of temperature changes at 10:00 and 17:00 in both January and July perform similarly to 14:00, with a maximum temperature rise or drop of 1.5 °C. A small area at 10:00 in July reaches 2 °C drops in a short period of time, but the minimal situation is not considered in this research. Table 1 Potential air temperature of the selected areas, 1.8 m above ground, 14:00

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Table 2 Relative humidity of the selected area, 1.8 m above the ground, 14:00 January July

Pre-retrofit

Post-retrofit

Legend [

]

Pre-retrofit

Post-retrofit

Legend [

]

3.2 Relative Humidity (RH) As shown in Table 2, the post-retrofit RH of the selected areas shows an overall decrease of 4% to 6% from around 56% to 58% in January at 14:00. The most prominent changes are found in the area between B1 and B3, as well as in B3, B4 and B5 and surrounding areas where parts of the wall were removed. At 10:00, the post-retrofit RH in most of the simulated areas decreases between 4 and 6% compared with pre-retrofit; at 17:00, most areas show a 2% to 4% RH drop, and the maximum can reach as high as 6%. However, the opposite situation has been observed in summer. At 14:00 and 17:00 in July, the post-retrofit RH of the area shows an overall maximum increase of 4%, among which the change between B1 and B3 is the most significant. There are small areas between B1 and B3 that have a maximum increase of 6% in RH at 10:00, but most of the area still shows a 4% increase. The observation of increased summer humidity in the selected area may be attributed to the southeasterly winds carrying moisture from the river surface located south of the area. During summer, the elevated water vapor content of the river causes an increase in humidity within the surrounding environment. The natural ventilation from the southeast is enhanced due to the demolition of parts of building walls and illegal constructions, which allows for more moisture to enter the selected area, thus elevating the relative humidity.

3.3 Ventilation Due to the removal of parts of the building walls, the natural ventilation of the postretrofit area is significantly improved in winter. The area between B1, B3, and B5 is poorly ventilated due to illegal constructions. After retrofitting, the wind velocity of these areas can be increased from below 0.2 m/s to 0.8 to 1.2 m/s at 14:00 and 17:00, and the maximum can reach 1.4 m/s in a specific area in winter, which enhances ventilation. Wind speeds are relatively low at 10:00, generally rising to 0.8–1.0 m/ s with a maximum of 1.2 m/s. However, the wind velocity decreased in the area between B2 and B4, which may be caused by the extended building on the east side of B2 blocking the wind from the north direction.

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Table 3 Wind direction and velocity of the selected area, 1.8 m above the ground, 14:00 January July

Pre-retrofit

Post-retrofit

Legend [

]

Pre-retrofit

Post-retrofit

Legend [

]

In July, the ventilation increased significantly. After retrofitting, the overall ventilation of the site has been improved, and the wind speed has been increased from below 0.3 m/s to 1.8 m/s, with the highest increase to 2.7 m/s in some areas. The partial removal of the walls on the east GF and 1Fs of B5 enhances the natural ventilation from the southeast in summer, thus resulting in a significant increase in wind velocity at this location. Adjustable doors or baffles can be set here to block the wind and reduce the wind velocity appropriately if necessary (Table 3).

3.4 Monthly Energy Performance As described in Sect. 2.3, the apartments on the first floor of B3 and B4 are selected for the energy simulation of January and July under the current and predicted postretrofit scenarios. Predicted weather data are made in this research based on the optimal predictions of potential air temperatures that there are 1.5 °C rise and drop in winter and summer, respectively. The predicted monthly energy use per conditioned building area is shown in Table 4 indicates that the microclimate after retrofitting is very effective in reducing the total energy consumption of the selected apartments. For households with lowenergy user pattern, the energy consumption in winter and summer are reduced by 9.59% and 12.83%. The households with high-energy user patterns have higher energy-saving, with the potential to reduce the total energy use by 14.51% and 20.02% in the two seasons, respectively. Although this study assumes that the winter temperature of the selected area will increase by 1.5 °C after retrofitting, which is consistent with the summer temperature Table 4 Predicted heating, cooling and total energy demand reduction of the selected apartments in summer and winter Low-energy user High-energy user

Heating

Cooling

Winter

13.91%

N/A

Total (%)

Summer

N/A

24.34%

12.83

Winter

16.39%

N/A

14.51

Summer

N/A

23.71%

20.02

9.59

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reduction, the effects of outdoor air temperature change on energy consumption reduction in winter and summer is different. The heating, cooling and total energy reduction of the selected apartments in summer and winter in Table 4 suggests that under the circumstance that the outdoor temperature changes are consistent, the energy use reduction of the case apartments will be higher in summer than in winter. Under both low and high-energy user pattern scenarios, the potential energy reduction of winter heating ranges from 13.91% to 16.39%, while summer cooling ranges from 23.71% to 24.34%. This result indicates that the post-retrofit microclimate performance has significant effects on reducing the heating and cooling energy use of the apartments.

4 Conclusion This study utilised ENVI-met and DesignBuilder to assess the impact of retrofit strategies on the microclimate and energy demand of an old residential community. The following conclusions are drawn: . Demolition of illegal constructions, removal of part of building walls, building extensions, and increasing landscaping are suggested as effective retrofit measures. . These retrofit measures can significantly improve outdoor thermal comfort and natural ventilation in both summer and winter. At 10:00, 14:00 and 17:00 in winter, the air temperature at the pedestrian height of the simulated area can increase by an average of 1.5 °C, the RH decreased by 4-6%, and the natural ventilation is enhanced. At the same time and height in the summertime, an average of 1.5 °C and a maximum 2.0 °C drop in air temperature can be achieved, and a 4-6% increase in RH and enhanced ventilation. . The improvement of microclimate can result in a decrease in the heating, cooling and total energy demand of the apartments. It can potentially reduce 13.91% to 16.39% of heating demand in winter and 23.31% to 24.34% of cooling demand in summer after applying the retrofit measures. The total energy demands in winter and summer can be potentially reduced by 9.59% to 14.51% and 12.83% to 20.02%, respectively. . The potential impacts of a retrofit approach on the microclimate could vary between seasons, as observed in this paper. The outcomes of this study may not be universally applicable, as different environmental factors could influence the results in various settings. For instance, in environments where the river’s influences are absent, the demolition of illegal constructions and building walls may lead to enhanced natural ventilation without causing a rise in relative humidity, thereby showing better performance than the current study. The limitation of the current research is that the results are drawn based on digital simulations, which lacks verification against the on-site monitored data. Future studies will focus on the collection of on-site monitoring data, the development and

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improvement of the model, and the design of detailed and feasible retrofit strategies. In addition, this paper focuses on quantifying and analysing one retrofit strategy consisting of four approaches. Future research will broaden the discussion to include multiple retrofit strategies with diverse configurations, and assess their potential in terms of improving microclimate, building internal thermal environment, and reducing building energy consumption.

References Berardi U (2016) The outdoor microclimate benefits and energy saving resulting from green roofs retrofits. Energy Build 121:217–229 Castaldo VL, Pisello AL, Piselli C, Fabiani C, Cotana F, Santamouris M (2018) How outdoor microclimate mitigation affects building thermal-energy performance: a new design-stage method for energy saving in residential near-zero energy settlements in Italy. Renew Energy 127:920–935 Chen S, Li N, Yoshino H (2010) Statistical analyses on summer energy consumption characteristics of residential buildings in some cities of China. Energy Build 42:136–146 Chen S, Li N, Yoshino H, Guan J, Levine MD (2011) Statistical analyses on winter energy consumption characteristics of residential buildings in some cities of China. Energy Build 43:1063–1070 Hu T, Yoshino H, Jiang Z (2013) Analysis on urban residential energy consumption of hot summer & cold winter zone in China. Sustain Cities Soc 6:85–91 Li P, Zheng WU (2021) Microclimate change in public space of residential areas in Beijing city based on numerical simulation: a case study of Min’an Community of Dongcheng district. J Landscape Res 13:103–112 Li R, Zhang W, Qiu L, Zhang H (2022) A numerical study on changes in air temperature around buildings due to retrofits in existing residential districts. Indoor Built Environ 31:1464–1481 Liang J (2021) 建筑领域碳达峰碳中和实施路径研究/Research on the implementation path of carbon peaking and carbon neutralisation in the construction sector. China Architecture & Building Press, Beijing METEONORM (2022) Meteonorm Software [Online]. Available: https://meteonorm.com/en/. Accessed 21 Nov 2022 Office of the state council leading group for the seventh national census (2022) China population census yearbook 2020. China Statistics Press, Beijing, China Shen X, Li J, Wang S, Su L, Li L (2023) The impact of tree-planting location on the microclimate and thermal comfort of the micro-public space. Pol J Environ Stud 32:717–730 Shi L, Luo Z, Matthews W, Wang Z, Li Y, Liu J (2019) Impacts of urban microclimate on summertime sensible and latent energy demand for cooling in residential buildings of Hong Kong. Energy 189 The State Council of China (2021) 国务院关于印发2030年前碳达峰行动方案的通知国发 [2021]23号/Notice of The State Council on the Issuance of a Carbon Peak Action Plan Before 2030 [2021] 23 [Online]. the State Council of China. Available: http://www.gov.cn/zhengce/ content/2021-10/26/content_5644984.htm. Accessed 27 July 2022 THUBERC (2021) 中国建筑节能年度 发展研究报告/Annual report on China building energy efficiency. China Architecture & Building Press, Beijing, China Tsang C (2020) Energy-saving retrofits for residential buildings in the hot summer and cold winter zone in China. Loughborough University Yoshino H, Yoshino Y, Zhang Q, Mochida A, Li N, Li Z, Miyasaka H (2006) Indoor thermal environment and energy saving for urban residential buildings in China. Energy Build 38(11):1308–1319

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Water Quality Inversion of UAV Multispectral Data Using Machine Learning L. Fu, Y. Lo, T. C. Lu, and C. Zhang

Abstract The majority of water quality inversions rely on satellite data with poor spectral resolution. Satellite data is tougher to obtain for a specific date and less timely than UAV data due to transit cycles and weather. This method of inferring water quality from UAV multispectral data is based on the use of machine learning. With high resolution, low flying altitude, low cost, and good performance, UAV multispectral data synchronizes with sampling point water body parameters. Studies on inverting water quality is difficult due to the need for a specific inversion model for each location and set of circumstances. In order to improve water quality inversion results and get around the limitations of linear models, machine learning is being used more and more. For efficient and quick water quality monitoring in Yuandang Lake, use machine learning to invert various water quality indicators, compare the results, and select the appropriate indicators. Keywords Water quality inversion · UAV multispectral data · Machine learning

1 Introduction Nutrient problems in most water bodies in China are serious. Currently, the increased productivity of lake basins and intensified human activities have led to the discharge of large amounts of nitrogen and phosphorus pollutants into water bodies, resulting in severe eutrophication. Cyanobacterial outbreaks are caused by the growth characteristics of planktonic algae, physicochemical characteristics of water bodies, as well as biological, meteorological, and hydrological factors, and the relationship between these factors is very complex and characterized by randomness, uncertainty, and nonlinearity. Traditionally, water quality monitoring of rivers and lakes has been conducted mainly by field sampling and laboratory analysis, etc. Nyambar and Mohan Viswanathan used the Hack test suite to analyze some nutrients in urban lakes in L. Fu · Y. Lo · T. C. Lu · C. Zhang (B) Xi’an Jiaotong-Liverpooliverpool University, Suzhou, Jiangsu, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_31

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an ultraviolet–visible spectrophotometer (Nyambar and Mohan Viswanathan 2023). This monitoring method needs to be carried out at fixed points and profiles within rivers and lakes, and through years of monitoring, recording and laboratory analysis, a certain level of data accuracy can be achieved, but it cannot reflect the overall spatial and temporal conditions of the river and lake water quality, and it is timeconsuming, laborious, and limited in the monitoring area, which is only locally and typically representative and cannot meet the requirements of real-time, rapid, and large-scale monitoring and evaluation. The development and progress of remote sensing technology have opened new ways for monitoring and researching river and lake water bodies. Remote sensing water quality monitoring technology has remarkable characteristics such as high dynamic, low cost and macroscopic, and has irreplaceable advantages of conventional detection in the study of water quality pollution of rivers and lakes. The use of remote sensing technology combined with machine learning to monitor the water quality of Yuan Dang Lake helps to understand the eutrophication status of Yuan Dang Lake and the evolution trend of cyanobacteria. The inversion of the collected data was carried out by using UAV multispectral remote sensing technology and a machine learning-based water quality inversion model. At the same time, the inversion results were compared with the collected water quality data to verify and optimize the machine learning-based water quality inversion model and improve the accuracy of the inversion.

2 Study Area The study area is Yuandang Lake, located in Wujiang District, Jiangsu Province, latitude 31° 4' 57.70'' N to 31° 3' 3.03'' N, longitude 120° 50' 56.53'' E to 120° 54' 37.30'' E. The total area of Yuandang Lake is 12.32 km2 , with a perimeter of 18,634 m, a normal water level of 2.86 m, a lake volume of 25.92 million m3 , mean elevation of the lake bottom of 0.25 m (Fig. 1). Yuandang Lake has various functions such as flood storage, water supply, fishery farming, ecology, landscape and tourism, etc. Especially, fishery farming and human activities will aggravate the eutrophication level of the water body of Yuandang Lake. Domestic sewage is not completely intercepted, the initial rainwater is not completely received, aquaculture, if not properly managed, unconsumed food particles and fish excrement will significantly increase the nitrogen and phosphorus content in the water, exceeding the ability of Yuandang Lake’s water body to self-purify, causing cyanobacteria to proliferate in the summer in Yuandang Lake in recent years.

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Fig. 1 Geographical area of Yuandang Lake: a Jiangsu Province; b Wujiang District; c Satellite photo of Yuandang Lake

3 Data Collection and Preprocessing UAV multispectral images were acquired using the DJI P4 multispectral UAV. Equipped with a colour sensor including one for visible imaging and five monochrome sensors for multispectral imaging. The UAV can collect RGB images simultaneously, Blue, Green, Red, Red-Edge, and Near-Infrared band images with an image resolution of 1600 × 1300 pixels. Water quality sampling includes moving path sampling as well as fixed-point sampling. Water quality sampling unmanned boat need to cooperate with the UAV photo collection time, on the same day to carry out on-site water quality sampling to ensure the synchronization of data and the accuracy of the later inversion. The EXO2S water quality measurement instrument with the positioning function of the UAV continuously and uninterruptedly collect water quality information, a total of seven indicators, PH, NTU (Turbidity), DO (Dissolved Oxygen), Temperature, Conductivity, Chl-a and BGA (Blue-Green Algae). Figure 2 shows the sampling path and fixed sampling locations. Because of the limitations of camera sensor size and lens field of view, the coverage of a single UAV aerial image is small and cannot meet the practical application requirements, so multiple aerial images with a certain overlap rate need to be stitched together to form a seamless large field of view image. The steps to complete image stitching usually include image pre-processing, image alignment and image fusion,

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Fig. 2 Sampling path and fixed sampling locations

among which image alignment is the most critical step. The most used alignment methods can be summarized into two categories: area alignment and feature alignment (Zhu et al. 2022). Since the extraction of feature points on the surface of Yuandang Lake is very difficult, the commonly used image processing software on the market is difficult to complete the stitching, and other methods need to be used to complete the image stitching. The photos taken by the UAV have GPS information, so GPS coordinates are used to stitch the UAV images, and the image element values in the overlapping area are taken as the average value. The stitching effect is shown in Fig. 3. From Fig. 3, some areas have more serious water surface reflections, and the water quality sampling points passing through these areas were removed in the subsequent data processing to avoid the impact of anomalous values on the inversion accuracy. The water quality sampling path is composed of multiple sampling points, each sampling point has GPS coordinates. Based on the GPS coordinates, the reflectance

Fig. 3 UAV image stitching

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of different wavebands of the point locations can be located and obtained on the UAV multispectral images. After obtaining the reflectance values of the 5 bands, they are matched with the water quality sampling data by point-by-point coordination. Specific data on the reflectance of each band and the water quality parameters corresponding to these reflectances were then obtained. In the data set of water quality inversion, the use of different band combination formulas can expand the number of data and improve the accuracy of inversion (Wang et al. 2020).

4 Models and Results Traditional water quality inversion methods can be divided into three kinds: empirical method, semi-empirical method and physical analysis method (Yang et al. 2022). In addition, with the advancement of machine learning technology, the application of water quality inversion is becoming more and more widespread. The empirical method refers to the statistical analysis of remote sensing data and field measurements of water quality parameters, and the construction of quantitative models of remote sensing data and monitoring data in the study area, and the common empirical models are the single-band model and band ratio model (Cui et al. 2022). Since water quality inversion is a highly nonlinear system with a variety of uncertainties such as ambiguity, complexity and randomness, especially rainfall and runoff, the variability in the spatiotemporal domain is very prominent and influenced by human activities, water quality inversion is very difficult and accuracy is difficult to guarantee (Xu and Xu 2022). The empirical method model has low generality, and the model accuracy depends on the measured water quality parameter data (Gao et al. 2022). Some studies proposed a convolutional neural network-based water quality inversion model, which can realize large-scale water remote sensing and cyanobacteria automatic monitoring. The results show that the water quality inversion model based on a convolutional neural network is able to perform water quality inversion with high accuracy (Zhang et al. 2022; Lei et al. 2020). Therefore, this project uses CNN (Convolutional Neural Network) and BP network for water quality inversion.

4.1 CNN Model CNN (Convolutional Neural Network) is a feed-forward neural network that performs well in target recognition and regression, and CNN is used to extract data features. AlexNet (Krizhevsky et al. 2017), VGG-16 (Zhou 2021), Google Net, ResNet, and other classical convolutional neural network models are examples. Although the structures are complex and varied, the basic structures and principles are similar, and they all have an input layer, a hidden layer, and an output layer. A CNN’s hidden layer is made up of a convolutional layer, an activation function layer, a pooling layer, and a fully connected layer. Convolution is the operation of

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extracting features by weighting and averaging the pixel points in the local area of the input image with the convolution kernel’s weight coefficients, pooling is used to compress the extracted features, and the activation function adds nonlinear variations to the neural network model. The CNN model’s training process consists of continuous convolution and pooling, and eventually, the weight parameters of each CNN layer are continuously adjusted to improve the model. The CNN model training process consists of continuous convolution and pooling, and finally, the weight parameters of each layer of CNN are continuously adjusted so that the model can better fit the features of the input data and the loss is minimized. The CNN model used in this study consists of two convolutional layers and one fully connected layer.

4.2 BP Model The BP neural network structure generally consists of three layers of the feed-forward network, input layer, hidden layer (also known as an intermediate layer), and output layer. It is distinguished by the fact that the neurons in each layer are only fully connected with each other and the neurons in adjacent layers, with no connection between neurons in the same layer and no feedback connection between neurons in each layer, resulting in a hierarchical feed-forward neural network system. Each neuron receives input signals from other neurons, and each signal is routed through a weighted connection. The neuron adds these signals together to get a total input value, which is then compared to the neuron’s threshold and finally processed by an activation function to get the final output, which is passed on layer by layer as input to subsequent neurons. The activation function’s purpose is to introduce nonlinearity into the model. Without an activation function, no matter how many layers the neural network has, it is ultimately limited to a linear mapping, resulting in the network’s approximation capability being rather limited, and a simple linear mapping cannot solve the linear indistinguishability problem. Various water quality parameters are processed through the input layer of the BP neural network transmission implicit layer for network operation processing, and the final prediction results are obtained through the output layer output. When the output layer of the BP neural network output results and its pre-set input value of the error is large, the BP neural network enters the backpropagation stage, and the neuron weights are updated, until the output results and the expected result error meet certain conditions. The BP model used in this study has 6 hidden layers and the number of neurons in each hidden layer is 14,14,15,15,15,15,15 respectively.

4.3 Result and Conclusion From Table 1 it can be seen that the number of features in the dataset is too high and some of the features may lead to reduced accuracy of water quality inversion, using

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the ReliefF algorithm to select the features, which is efficient and has unlimited data type features to handle discrete or continuous datasets (Wang et al. 2016). Before inversion using BP and CNN models, five features were selected using ReliefF. CNN and BP were evaluated using the coefficient of determination (R2 ), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) (Table 2). This study found that for the water quality inversion of Yuandang Lake, the overall effect of the BP model was much better than that of the CNN model. Several water quality parameters, such as BGA, pH, Temp and PI, had R2 > 0.6 in the test set, achieving a better inversion accuracy. BGA is closely related to cyanobacterial outbreaks, and by inverting the concentration distribution of BGA in Yuandang Lake, the future location and area of cyanobacterial outbreaks can be inferred to some Table 1 Band combination formula Index

Formula

Index

Formula

Index

Formula

F1

B1

F11

B3 + B1

F21

(B1 − B3)/(B5 + B2)

F2

B2

F12

B3 + B2

F22

(B1 − B4)/(B5 + B2)

F3

B3

F13

B4 + B2

F23

(B1 − B3)/(B2 − B4)

F4

B4

F14

B5 + B2

F24

(B3 + B1)/(B3 + B2)

F5

B5

F15

B2/B3

F25

(B1 + B2)/(B3 + B5)

F6

B1 − B2

F16

B3/B4

F26

(B1 + B2)/(B3 + B4)

F7

B1 − B3

F17

B3/B5

F27

(B1 − B3)/B2

F8

B1 − B4

F18

B1/B5

F28

(B12 − B22 )/(B12 + B22 )

F9

B3 − B5

F19

B1/B4

F29

(B5 − B1)/(B5 + B1)

F10

B5 + B3

F20

B2/B5

F30

B2/B5 − 1

Table 2 The number of officially reported plague cases in the world Model Water quality R2 train R2 test RMSE train RMSE test MAE train MAE test parameter BP

CNN

NTU

0.361

0.313

52.133

55.589

29.147

31.20

BGA

0.634

0.602

2.094

2.152

1.530

1.622

pH

0.750

0.630

0.094

0.118

0.066

0.084

Temp

0.720

0.604

0.736

0.912

0.492

0.572

Chl

0.252

0.206

3.674

3.949

2.672

2.808

PI

0.721

0.672

0.372

0.431

0.281

0.362

NTU

0.392

0.343

48.463

50.322

25.831

27.20

BGA

0.498

0.433

2.681

2.975

1.879

2.037

pH

0.316

0.355

0.157

0.153

0.123

0.120

Temp

0.440

0.379

1.051

1.108

0.722

0.749

Chl

0.203

0.193

3.904

3.644

2.872

2.669

PI

0.666

0.640

0.423

0.386

0.348

0.307

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Fig. 4 Heat map of BGA concentration

extent. As shown in Fig. 4, the calculation of the overall BGA concentration distribution in Yuandang Lake can provide some directions for the future management and control of cyanobacteria. The BGA concentrations are substantially higher near the coast than they are in the center of the lake, as can be seen in Fig. 4. This is consistent with the pattern of cyanobacterial outbreaks, which are caused by human activities on the shore and the buildup of cyanobacteria carried by the wind to the lake shore. The deeper colored regions call for more efforts to be made to intercept, salvage, separate, and treat the cyanobacteria that has accumulated there. In general, the BP model enables higher accuracy water quality inversions and provides a heat map of the concentration distribution over the lake. This makes it easier to identify possible hotspots for largescale cyanobacterial outbreaks in a timely manner. The BGA metric is the one that is being used for the inversion process at the moment; however, in subsequent work, the data collection method and the structure of the CNN and BP models can be enhanced, which will allow for the inversion of additional metrics, which will boost the accuracy and efficiency of the water quality inversion. Acknowledgements This research is funded by Xi’an Jiaotong-Liverpool University Urban and Environmental Studies University Research Center, Grant number RDH-101-2022-0032.

References Cui M, Sun Y, Huang C, Li M (2022) Water turbidity retrieval based on UAV hyperspectral remote sensing. Water 14(1):128 Gao M, Li J, Wang S, Zhang F, Yan K, Yin Z, ..., Shen W (2022) Smartphone–camera–based water reflectance measurement and typical water quality parameter inversion. Remote Sens 14(6):1371 Krizhevsky A, Sutskever I, Hinton GE (2017) Imagenet classification with deep convolutional neural networks. Commun ACM 60(6):84–90

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Lei F, Yu Y, Zhang D, Feng L, Guo J, Zhang Y, Fang F (2020) Water remote sensing eutrophication inversion algorithm based on multilayer convolutional neural network. J Intell Fuzzy Syst 39(4):5319–5327 Nyambar INA, Mohan Viswanathan P (2023) Assessment on urban lakes along the coastal region of Miri, NW Borneo: implication for hydrochemistry, water quality, and pollution risk. Environ Sci Pollut Res 1–23 Wang Z, Zhang Y, Chen Z, Yang H, Sun Y, Kang J, ..., Liang X (2016) Application of ReliefF algorithm to selecting feature sets for classification of high resolution remote sensing image. In: 2016 IEEE international geoscience and remote sensing symposium (IGARSS). IEEE, pp 755–758 Wang L, Yue X, Wang H, Ling K, Liu Y, Wang J, ..., Song H (2020) Dynamic inversion of inland aquaculture water quality based on UAVs-WSN spectral analysis. Remote Sens 12(3):402 Xu Y, Xu T (2022) An evolving marine environment and its driving forces of algal blooms in the Southern Yellow Sea of China. Mar Environ Res 178:105635 Yang H, Kong J, Hu H, Du Y, Gao M, Chen F (2022) A review of remote sensing for Water Quality Retrieval: Progress and challenges. Remote Sens 14(8):1770 Zhang H, Zhang L, Wang S, Zhang L (2022) Online water quality monitoring based on UV–Vis spectrometry and artificial neural networks in a river confluence near Sherfield-on-Loddon. Environ Monit Assess 194(9):630 Zhou J (2021) Dodge or disinfect? Classifying algae in small-scale water bodies via low-cost deep neural networks. In: 2021 IEEE 3rd international conference on frontiers technology of information and computer (ICFTIC). IEEE, pp 263–277 Zhu H, Jiang Y, Zhang C, Liu S (2022) Research on mosaic method of UAV low-altitude remote sensing image based on sift and surf. In: J Phys Conf Ser, 2203(1):012027. IOP Publishing

Green Open Spaces as Catalysts of Culture-Led Urban Regeneration: Case Study of Yuyuan Cultural Heritage Neighborhood, Shanghai Jiemei Luo, Izzy Yi Jian, Edwin H. W. Chan, and Weizhen Chen

Abstract Targeting the fragility of culture-led urban regeneration (CLR), this study aimed to identify a sustainable redevelopment mode using green open spaces (GOSs) as catalysts for neighborhood-level CLR based on a representative case, the Yuyuan Cultural Heritage Neighborhood (CHN) in Shanghai. By summarizing the development trajectory of the Yuyuan CHN, the essential role of GOS is revealed, where GOSs provide settings for diverse cultural activities and social gatherings. Transforming low-efficiency assets into GOSs in Yuyuan has provided a possible “full-aspect” CLR at the community level. GOSs attract various social groups with diverse social or ethnic backgrounds. The previously closed, isolated creative cluster became organically integrated with the urban environment. New GOSs with artistic elements also contribute to providing cultural and leisure activities for marginalized social groups, including the elderly, the poor, and the working classes. The new GOSs in Yuyuan reflect the integration of cultural development and urban planning. They increase the accessibility of various types of culture to residents, visitors, and passersby on the street. GOSs produce a community identity and cohesion by way of collective memory, which is essential for long-term sustainable development. However, GOSs are threatened by problems such as gentrification and therefore require increased government protection. The analysis further identified the forms and landscape elements of GOSs that respond to cultural requirements. Urban furniture, such as seating benches, allows people to have a moment of peace in the urban environment and a chance to talk. The relatively long-term art installations shed light on ordinary life through exploration and fun. Recommendations are provided to explore the full potential of the cultural value of urban regeneration, as opposed to mere rhetorical sloganeering.

J. Luo · W. Chen College of Architecture and Urban Planning, Tongji University, Shanghai 20092, CHN, China J. Luo · E. H. W. Chan Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong, China I. Y. Jian School of Design, The Hong Kong Polytechnic University, Hong Kong, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_32

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Keywords Green open spaces · Urban regeneration · Case study · Sustainable redevelopment mode

1 Introduction Many studies have investigated culture-led urban regeneration (CLR) in relation to urban revival, renaissance, and redevelopment (Evans and Shaw 2004; Miles and Paddison 2005). Various strategies have been introduced in CLR policies. Public art—including street furniture, landscape and environmental art, and participative events—can improve the physical environment while also stimulating community engagement and social cohesion (Belfiore 2002; Lees and Melhuish 2015). Building flagship cultural facilities to attract investment and promote tourism can bring economic benefits. It is well established that hosting cultural festivals or events can serve as a catalyst for regeneration, as with the “Capital of Culture” designation in European cities (Quinn 2005). Individuals, participants, and communities can be affected by various hands-on cultural activities (Evans and Shaw 2004). However, the long-term social effects of large-scale, sometimes international events can vary. As seen in cases of post-Expo and post-Olympics cities, event-based regeneration does not always provide sustainable benefits for residents, as in cities such as Barcelona, Bilbao, Lisbon, Salford, and Sydney (Garcia 2004; Evans 2005). Yet, with the rise of the “creative class” and of creative industries, CLR has also served to build creative clusters (Florida 2005; Miles and Paddison 2005). Cultural policies have been involved in many urban redevelopment projects in China. Typical cases include the 798 Art Zone in Beijing and M50, and Tianzifang in Shanghai (Yung et al. 2014; Niu et al. 2018). Such efforts have aimed to promote the development of cultural-creative industries through economic growth in tandem with the transition of many cities from the industrial to the postindustrial period. However, there are mismatches in the rise of creative industries and clusters, and such clusters often lack a connection with local communities (Gu 2014). Meanwhile, the regeneration of heritage and historic districts has faced issues such as overcommodification (Su 2015). Social issues such as mass displacement also accompany the large-scale urban renewal of traditional housing in historic areas (Yang and Chang 2007). After decades of urbanization in China, the government began to pay attention to the quality of urban development. With the growing appreciation of the historical and cultural value of urban environments and built heritage, the Shanghai Municipal Government (SMG) designated 12 Cultural Heritage Neighborhoods (CHNs) in Shanghai in 2003 (Chen and Ruan 2008) (Fig. 1). The street widths in CHNs are protected from being widened, and many historic buildings are located within CHNs. With the protection of historical human-scale urban features, CLR in Shanghai started to adopt an organic approach that did not use mass demolition. This study took as a case study a representative CLR project, Yuyuan CHN, which is one of the 12 inner-city CHNs in Shanghai and a National-level Tourism and

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Fig. 1 Left: location of 12 CHNs in Shanghai’s inner city (adapted from Chen and Ruan (2008)). Right: plan of the Yuyuan CHN, source: drawn by authors

Leisure District. Yuyuan has many historic buildings and traditional urban patterns from the semi-colonial period. Sycamore trees with sizeable green canopies are a typical landscape feature. Beginning in 2014, Yuyuan adopted an organic regeneration mode without large-scale demolition. Today, after about nine years of regeneration, Yuyuan has become a vibrant area with mixed historic buildings, creative industry clusters, urban gardens, and old and new shops (Luo et al. 2022). There is, nevertheless, a need to further identify Yuyuan’s key strategies for balancing commercial development and ordinary social life. This study aimed to summarize the regeneration phases of Yuyuan and identify the essential role of green urban spaces (GOSs) in CLR. It used evidence obtained from frequent site visits over a period of nine months along with secondary sources. In addition to academic literature, news media and public WeChat accounts were searched for background information and cultural events. This paper argues the cultural and social functions of GOSs have not received sufficient attention in CLR. GOSs could provide an effective way to balance economic benefits and cultural-social impacts for local communities in the process of regeneration.

2 Culture-LED Urban Regeneration in Shanghai 2.1 CLR in Shanghai Many Chinese cities and projects have adopted CLR as a redevelopment strategy. Transforming dilapidated manufacturing sectors into creative clusters through reuse by artists is one approach, as in the M50 and Red Town in Shanghai (Zhong 2016). Spatially, they are transformed from manufacturing spaces with defined boundaries to open spaces. Strategically speaking, producing spaces for artists is the catalyst of such projects (Wang 2009; Zheng 2017). They have mainly focused on creative industry development with economic growth (Zheng 2011; Gu 2014). Yet, even in

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cases where small green spaces exist, the cultural and social functions of GOSs have not been considered in the primary cultural regeneration strategies. In addition to abandoned factories, artists have been attracted to traditional housing with low rent and local characteristics, as in Tianzifang (Yung et al. 2014). Tianzifang is a traditional linong neighborhood with a public open-space network; however, it is too narrow to allow for interactive activities. Xintiandi is another regeneration area transformed from traditional linong but with mass displacement (Yang and Chang 2007). The property development and fake Shikumen façades caused people to regard “culture” as a mere rhetorical instrument in this process. Thus, Xintiandi raised people’s concerns about the social value of regeneration (Yu 2011). There were three preservation periods in Shanghai’s urban regeneration (Zhong and Chen 2017). Xintiandi was rebuilt during the first mass-demolition stage between 1991 and 2000. The conservation policy for the 12 CHNs was announced in the second preservation period from 2001 to 2009. The CLR of Yuyuan began during the strong preservation stage after 2010. The appreciation of cultural value became much stronger after Xintiandi and the 2010 Shanghai Expo (Chan and Li 2017). Urban green spaces serve social and cultural functions by providing various leisure and entertainment options (Schetke et al. 2010; Jian et al. 2020). The quality of the public space environment and buildings is a crucial factor in the regeneration of historic districts (Zhang et al. 2019). Renovating urban green spaces can stimulate the vitality of the community (Ming and Yun 2013). Small parks also contribute to the sense of belonging—“you feel it is your street” (Zukin 2012). Cultural events taking place in open spaces can stimulate “triangulation,” encouraging strangers to talk and have social interactions (Whyte 1980). Unlike cultural industry studios and consumption spaces such as cafés and shops, GOSs are seldom recognized an essential catalyst of CLR. The unique features of urban green spaces, especially small green spaces, may enhance CLR to fully achieve cultural value and enhance social effects.

2.2 Cultural Heritage Neighborhoods in Shanghai With the rising consciousness of the historical and cultural value of historic buildings, the SMG announced 12 CHNs in Shanghai’s inner city (Fig. 1). Compared to modern built environments in Shanghai, roads in the CHNs tend to be narrow. They mostly only have two lanes and are pedestrian-friendly. The 12 CHNs in Shanghai’s inner city have different landscape features. The organic distribution of green spaces within the neighborhood is an outstanding landscape feature of Yuyuan after the CLR.

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3 Culture-LED Urban Regeneration in Yuyuan CHN, Shanghai 3.1 Introduction and Regeneration Phases of Yuyuan Yuyuan CHN is located in Changning District (Fig. 1). The core regeneration Yuyuan road is 900 m long. Yuyuan has the highest proportion of people over age 65 in Changning, and their welfare has become a matter of government concern. Organizations that conduct CLR in Yuyuan include the Jiangsulu Neighborhood Government, private real estate firm Chuangyi, and various social organizations. CLR in Yuyuan has been conducted in three stages based on specific actions, project types, and regeneration effects (Table 1). The early regeneration stage lasted from early 2014 until 2016. Regenerated buildings include the Changning Cultural Center and Chuangyi Creative Cluster. New GOSs, Meadow A (A) and Corner Garden (C), located outside of these buildings, were also produced during this stage (Fig. 2). A in Chuangyi Cluster is a former parking lot that had a wall separating the Cluster from the street. During the regeneration, walls were demolished, and transformed into an open meadow (Luo et al. 2022). C is located in front of the Changning Cultural Center. It is a former street space that was transformed into a garden with meadows and benches along the street. At the end of the first stage, Yuyuan’s reputation had already improved because of its attractive overall environment. Although no new GOSs were built during the second phase, cultural and artistic events regularly took place in A and C. Yuyuan Public Market, across the street from A, receives a large number of visitors and can be seen as a turning point in the second phase of Yuyuan’s CLR, where synergy was generated. Meadow B (B) was built during phase three (Fig. 2). It involved the further regeneration of GOSs, new retail shops, and creative working spaces. Several one-floor buildings with traditional small businesses were demolished to build B. Now, it is a small GOS surrounded by boutiques, cafés, and restaurants (Luo et al. 2022). Table 1 Phases of culture-led urban regeneration in Yuyuan Phase

Time period

GOSs

Stated targets

1

2014–2016

Meadow A, Corner Garden

Overall neighborhood Scattered environment reform; experiments beginning of commercial industrial shifts

2

2017–2019

–

Commercial and industrial space regeneration

Emerging synergy

3

2019–present

Meadow B

Commercial industry space; community regeneration

Further integrated reuse

Stage features

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Fig. 2 Three GOSs in Yuyuan. Source authors

In the three stages of Yuyuan’s regeneration, two essential GOSs were produced at the beginning, along with functional interior updates. Yuyuan’s reputation benefited from the improvements to public-space quality created by GOSs. A government representative noted that “the regeneration started from landscape spaces.” Thus, we can see that the GOSs were produced strategically at the beginning of the CLR process as a catalyst.

3.2 Three GOSs in Yuyuan Yuyuan’s CLR produced three GOSs (Meadow A, Corner Garden, and Meadow B; Table 2). Yuyuan chose to build small-scale GOSs, the urban forms and landscape elements of A and B are quite similar: a square green space with a meadow in the center. One side of the green space faces the main street, allowing pedestrians to quickly move in and out. C, located at the intersection of Yuyuan and Anxi Roads, has an L shape. All three green spaces enjoy the huge canopy provided by giant sycamore trees along Yuyuan street; all seating benches are located under this natural canopy. Table 2 Three GOSs in Yuyuan CHN GOSs in Yuyuan

Total area

Date built

Former function

Surrounding building function

Meadow A

30 × 40 m, 1200 m2

2015.06

Parking lot

Chuangyi cultural-creative cluster, restaurants

Corner Garden

1500 m2

2015.06

Parking for bikes, Street

Public cultural facilities, offices

Meadow B

20 × 30 m, 600 m2

2019.09

Shops

Boutique shops, restaurants, cafés

Zhongshan Park

–

Existing large park

–

A park with walls

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3.3 Public Art and Cultural Events in Yuyuan’s GOSs All essential public artwork and cultural events were recorded and analyzed based on the official Chuangyi WeChat account. These included 17 cases: 10 art installations and seven cultural events in three GOSs. Various unofficial events took place as well but were not announced by official Yuyuan media; these were excluded from analysis. Though 17 cases is not a significant number, given the quality of these events, they had a significant impact in Yuyuan. Most of these events were held on the weekends. When certain city-level festivals—such as Shanghai Urban Space Art Season—choose Yuyuan as the host, A plays a key role because of its relatively large scale (Fig. 3). Some public artworks and events have also been conducted at C and B. These approaches make full use of the GOSs in Yuyuan as public spaces for cultural events. The designers of public installations have multicultural backgrounds, coming from the UK, Germany, and France. Such diverse backgrounds bring culture from all over the world to Yuyuan. Local elderly residents also get a chance to enjoy global cultural artworks. GOSs, typically meadows, can provide temporary settings for multiple types of cultural events, such as festival openings, music festivals, beer festivals, story sharing, and handcraft markets. These events bring various types of culture into the daily life of a traditional neighborhood. For example, an outdoor piano performance held at B in October 2019 (Fig. 3) is a typical case. In this way, a green space served as a link between high art and everyday residents. Cultural events attract people from varied social backgrounds (e.g., elderly, foreigners, trend-conscious Chinese youth). A well-known event is the beer festival (Fig. 3). Most people who enjoy themselves in the meadow are quite young, and many are Westerners. They have picnics or play with their kids or pets. Sometimes, elderly people are attracted to the meadows and stop to look around. The design approach of public art mostly involves interaction encouragement. One noteworthy example is Colorways (Fig. 3). A young boy was observed jumping up to try to touch the low edges of the waving pieces. In C, there is 100 Year’s Alley, a memorial public artwork built in 2018 (Fig. 3). If one takes a photo of this installation with a flash, a unique lighting pattern will appear in the photo. In this way, artists attract people to participate in the reactivation process.

Fig. 3 Opening of Urban Lifestyle Season 2019; 2. Beer Festival in Meadow A; 3. 100 Year’s Alley; 4. piano performance in Meadow B (photos 1 and 4 from Chuangyi)

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Fig. 4 Seating benches in Meadow A; 2. TETROMINOES; 3. semi-indoor shelter; 4. elderly painting watercolors; 5. elderly man sitting with his dog. Source authors

3.4 Everyday Life in Yuyuan’s GOSs Everyday life in Yuyuan involves artistic elements, even when special cultural events are not taking place. Such artistic elements, which may last three to six months, shed light on everyday life in Yuyuan. Even without artistic landscape elements, the landscape elements of the green spaces help generate a better quality of life in terms of leisure and social enjoyment for diverse social groups, especially the working classes. Long-term artistic installation is one way to stimulate daily life, especially for children and tourists. TETROMINOES is an installation in the meadow of C dating from October 2019. It contains three steel structures with shinning colors (Fig. 4). Despite a sign at the bottom prohibiting climbing on the installation, children nevertheless climb and play on it while their parents look on. Public furniture with distinct artistic characteristics can also make a difference in daily life. A piece of urban furniture in C is a semi-indoor shelter often used by working-class people (Fig. 4). It is a shelter with seating and USB chargers, built during the Urban Events Design Festival 2017. Many who use this shelter are uniformed couriers and security guards. Even without artistic elements, green scenery with seating improves leisure and cultural enjoyment in Yuyuan (Fig. 4). C is a lovely green space that is especially attractive to elderly people; a familiar scene is a group of elderly men getting together and talking. Most are retired workers who live in adjacent communities; some will slowly stroll along the L-shape space. One elderly man was observed sitting outside a trendy clothing shop facing Meadow B (Fig. 4). He was smoking while his pet dog stood near him. A group of elderly people and primary school students were observed painting watercolors in C (Fig. 4). In this way, green scenery can provide inspiration for artistic work.

4 Conclusions CLR efforts in Shanghai contributed to national debates that eventually settled into understanding, resulting in strategies and policies for urban regeneration based on the organic reform of heritage neighborhoods involving new GOSs. This study revealed

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the vital role of small GOSs based on a comparison of landscape features in 12 CHNs, an analysis of redevelopment processes, and frequent site observations of three GOSs in Yuyuan. Transforming low-efficiency assets into GOSs in Yuyuan has provided a possible “full-aspect” CLR at the community level. Yuyuan takes advantage of its landscape features and promotes them in the CLR process, along with artistic activities and events. It strategically built GOSs at the very beginning to allow an artistic atmosphere to spread among the whole neighborhood. New GOSs with artistic elements also contribute to providing cultural and leisure activities for marginalized social groups, including the elderly, the poor, and the working classes. The cultural-artistic activities include diverse types, such as public furniture, installations, music performances, markets, and festivals. GOSs provide a way for people to meet as well as a platform for various events. The open spatial feature makes these events easily seen and watched, even by passersby. GOSs produce a community identity and cohesion by way of collective memory, which is essential for long-term sustainable development. Resident’s everyday lives also benefit from the beautiful scenery of the green spaces. Urban furniture, such as seating benches, allows people to have a moment of peace in the urban environment and a chance to talk. The relatively long-term art installations shed light on ordinary life through exploration and fun. Unlike regeneration modes characterized by mass demolition and displacement, or by creative clusters mainly focused on economic growth, the organic regeneration mode, with new, small-scale GOSs, provides a sustainable means of CLR with an emphasis on real cultural value. The Yuyuan mode can provide some new understandings of CLR. First, the cultural and social functions of GOSs can play an essential role in CLR. GOSs attract various social groups with diverse social or ethnic backgrounds. They include local elderly residents, young overseas professionals, creative classes, and tourists. Second, GOSs can serve as a public stage, allowing ordinary residents to become involved in cultural events. The new GOSs in Yuyuan reflect the integration of cultural development and urban planning (Yu et al. 2019). A GOS is simultaneously a site of social and cultural exchange, visible or invisible. Third, the flexible, creative use of green spaces reproduces a vibrant, inclusive scene. The top-down cultural elements can provide inspiration for bottom-up cultural-artistic activities. All of these attributes contribute to “full-aspect” cultural regeneration as opposed to mere rhetorical sloganeering.

References Belfiore E (2002) Art as a means of alleviating social exclusion: does it really work? A critique of instrumental cultural policies and social impact studies in the UK. Int J Cultural Policy 8:91–106 Chan RCK, Li LY (2017) Entrepreneurial city and the restructuring of urban space in Shanghai Expo. Urban Geogr 38:666–686

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Chen F, Ruan YS (2008) A comparative study on conservation planning of cultural heritage neighborhood in Shanghai and the response of conservation planning. Urban Planning Forum 2:104–110 (In Chinese) Evans G (2005) Measure for measure: evaluating the evidence of culture’s contribution to regeneration. Urban Stud 42:959–983 Evans G, Shaw P (2004) The contribution of culture to regeneration in the UK: a review of evidence. DCMS, London, p 4 Florida R (2005) The rise of the creative class. Reg Sci Urban Econom 35:593–596 Garcia B (2004) Cultural policy and urban regeneration in Western European cities: lessons from experience, prospects for the future. Local Econ 19:312–326 Gu X (2014) Cultural industries and creative clusters in Shanghai. City, Culture and Soc 5:123–130 Jian IY, Luo J, Chan EH (2020) Spatial justice in public open space planning: accessibility and inclusivity. Habitat Int 102122 Lees L, Melhuish C (2015) Arts-led regeneration in the UK: the rhetoric and the evidence on urban social inclusion. Europ Urban and Reg Stud 22:242–260 Luo J, Jian IY, Chan EHW, Chen W (2022) Cultural regeneration and neighborhood image from the aesthetic perspective: case of heritage conservation areas in Shanghai. Habitat Int 129:102689 Miles S, Paddison R (2005) Introduction: the rise and rise of culture-led urban regeneration. Urban Stud 42:833–839 Ming D, Yun Z (2013) Renovation of urban green space based on regeneration of historical place-a case study of Jianqiao historical block in Hangzhou. J Landscape Res 5:7 Niu SF, Lau SSY, Shen ZW, Lau SSY (2018) Sustainability issues in the industrial heritage adaptive reuse: rethinking culture-led urban regeneration through Chinese case studies. J Housing and the Built Environ 33:501–518 Quinn B (2005) Arts festivals and the city. Urban Stud 42:927–943 Schetke S, Haase D, Breuste J (2010) Green space functionality under conditions of uneven urban land use development. J Land Use Sci 5:143–158 Su XB (2015) Urban entrepreneurialism and the commodification of heritage in China. Urban Stud 52:2874–2889 Wang J (2009) ‘Art in capital’: shaping distinctiveness in a culture-led urban regeneration project in Red Town, Shanghai. Cities 26:318–330 Whyte WH (1980) The social life of small urban spaces Yang YR, Chang CH (2007) An urban regeneration regime in China: a case study of urban redevelopment in Shanghai’s Taipingqiao area. Urban Stud 44:1809–1826 Yu H (2011) Space production and space narrative of city renovation—case study of Shanghai. Shanghai Urban Managem 20:10–5 (In Chinese) Yu T, Tang Q, Wu Y, Wang Y, Wu Z (2019) What determines the success of culture-led regeneration projects in China? Sustainability 11:4847 Yung EHK, Chan EHW, Xu Y (2014) Sustainable development and the rehabilitation of a historic urban district—social sustainability in the case of Tianzifang in Shanghai. Sustain Developm 22:95–112 Zhang Y, Kang S, Koo J-H (2019) What is the critical factor and relationship of urban regeneration in a historic district?: A case of the Nanluoguxiang area in Beijing, China. Sustainability 11:6772 Zheng J (2017) Toward a new concept of the “cultural elite state”: Cultural capital and the urban sculpture planning authority in elite coalition in Shanghai. J Urban Affairs 39:506–527 Zheng JE (2011) ‘Creative industry clusters’ and the ‘Entrepreneurial City’ of Shanghai. Urban Stud 48:3561–3582 Zhong S (2016) Artists and Shanghai’s culture-led urban regeneration. Cities 56:165–171 Zhong XH, Chen XM (2017) Demolition, rehabilitation, and conservation: heritage in Shanghai’s urban regeneration, 1990–2015. J Architect Urbanism 41:82–91 Zukin S (2012) The social production of urban cultural heritage: identity and ecosystem on an Amsterdam shopping street. City, Cult Soc 3:281–291

Digital Oriented Museum Design Based on Collective Memory—Case Study of Bache Old Town Y. T. Liu, Y. W. Q. Liu, G. S. Y. Liu, and J. Xia

Abstract With socioeconomic development and urbanization, Bache Old Street has undergone significant changes in its spatial structure, cultural features, and traditional way of life. As an ancient canal town in the Grand Canal Cultural Belt, it faces depopulation, inadequate preservation of historic buildings, and the loss of historical and cultural continuity. The erosion of Bache Old Street’s cultural roots as a traditional fishing village has severed the inhabitant’s ties with the area. This report aims to explore the concept, medium, and manifestation of collective memory. By employing methods such as fieldwork, visits, research, and the restoration and digital design of old buildings, it proposes the establishment of a digital museum to preserve and develop the collective memory of Bache Old Street. This study offers innovative ideas for sustainable urban regeneration, presenting a digital-oriented museum as a means to realize and preserve Bache Old Street’s collective memory in the digital space. Keywords Restoration · Digital design · Old buildings · Digital museum

1 Introductions The National New Urbanization Plan (2021–2035) calls for the promotion of historical and cultural heritage and humanistic city construction. The protection and continuation of the city’s historical heritage, and the integration of intangible cultural Y. T. Liu · Y. W. Q. Liu · G. S. Y. Liu · J. Xia (B) Design School, Xi’an Jiaotong-Liverpool University, 111 Ren’ai Road, Suzhou 215123, China e-mail: [email protected] Y. T. Liu e-mail: [email protected] Y. W. Q. Liu e-mail: [email protected] G. S. Y. Liu e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_33

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heritage become essential in urban planning and construction. In most small historical cities, the traditional way of life and transport has changed with the socio-economic and urbanization development, leading to the current situation of a serious hollowing out of the population, improper protection of traditional ancient buildings, and the continuation of its urban historical lineage. Meanwhile, With the development of the information era, the construction of traditional realistic spaces can no longer meet people’s perceived needs for architectural space. The loss of collective memory elements in the creation of architectural space in current urban regeneration has not only resulted in the loss of architectural space memory, space history, and important event space, but more importantly, has prevented the narrative characteristics of the architectural space itself from being highlighted; traditional architecture also creates the memory space of places through only the medium of building materials, light and shadow effects, etc., and people’s experience of space remains at a visual and tactile stage (Fig. 1). In recent years, cities along the Grand Canal have stepped up their efforts to promote the construction of the Grand Canal Cultural Belt. Bache Old Street is located in the northern part of Bache District, Songling Town, Wujiang Region, Suzhou City, Jiangsu Province, and is located in the middle of the waterways of

Fig. 1 Self-portraited site location

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North Harbor and South Harbor, close to the Beijing-Hangzhou Grand Canal. It is an important node of the Grand Canal Cultural Belt. Similar to other small towns, the continuous violation of the cultural roots of the traditional canal town of Bache Old Street, forced the residents to sever their connection with the memory of Bache Old Street. This paper aims to explore how to preserve and develop the cultural heritage collective memory through the design of various dimensions in digital space, collectively, a digital museum. Through the interaction between digital space and real space, digital museums can be built to create scenes of memory and support sustainable urban revitalization, especially from a social perspective. The Bache Old Street will be used as a subject for the case study.

2 Theory 2.1 Collective Memory Collective memory is a social psychological concept introduced by the French sociologist Maurice Halbwachs in 1925, which refers to the memories that are dependent on things and shared or co-constructed by people in modern society (Liu et al. 2018). The formation and transmission of collective memory are subject to certain biases due to subjective assertions (Shi et al. 2014), which also affects its use in architectural design to a certain extent, so in the process of extracting and analysing the collective memory of Bache Old Street, attention needs to be paid to identifying and organizing the common elements that have authenticity. There are different views on the elements that constitute collective memory in different discourses, but they are broadly divided into two main types: material and immaterial. Community fabric and Physical carriers are considered to be two important aspects for the material category. Community fabric is a concept that describes the distribution of buildings, generally with a certain spatial form, which reflects the social lifestyle and gathering patterns of the inhabitants. The historical memory style carried by the buildings that exist in the community is very continuous, as the neighbourhood has a more complete social function and bears a richer memory, including the neighbourhood environment, political economy, history and culture, religious elements, and so on (Liu et al. 2018). While physical carriers refer to architectural elements, styles, forms, and other architectural details that helps residents to form a more uniform image. Other non-architectural elements are also distinctive to the locals, such as boats, fish, markets, and other imagery. Living habits and Folk Culture are frequently referred as immaterial collective memory.

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2.2 Digital Space Technology VR, virtual reality, is a representative technology form of digital space technology, which can fully integrate the human sensory systems, namely, hearing, vision, touch, taste and smell. Through the multi-dimensional stimulation of the human sensory system, the multi-dimensional spatial form is simulated. The basic characteristics of virtual technology are mainly immersion, interactivity, and conceptualization, as well as the multi-sensitivity derived from these three basic characteristics which led to the achievement of the effects that traditional media cannot display (Liu and Zhang 2019). Additionally, the dissemination of intangible culture could be strengthened through digital technology, the storage, collection and analysis of information with the help of digital technology. Meanwhile, ancient towns can be better preserved and presented to achieve the real protection, development and innovation of the material existence, functional form and cultural heritage of historical ancient towns.

3 Research Method 3.1 Desktop Study Similar cases will be studied to familiarise with workflow and investigation procedures, as well as final outcomes.

3.2 Walk-Along Walk-And-Talk Participatory Research Go-along/Walk-along is an in-depth qualitative interview method. The researcher obtains perceptual information about the living environment relevant to the informant in the form of accompanying the informant out and about in their familiar environment (Sun and Lau 2021). The method is innovative, flexible and original in identifying landscape values (Curl et al. 2018). In the Bache Old Street research, the research team adopted a Walk-along approach to capture the memories of the scenes in Bache Old Street by walking and talking with the residents of Bache Old Street. A total of ten individuals were interviewed as part of this study, through a series of stakeholder participatory ‘walk’ interviews. The interviews encompassed various demographic groups, including older individuals, young people from Bache, and students from the Future Campus of Soochow University. The research has been approved by the author’s institution for research ethics.

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3.3 Coding Analysis NVivo12 is a qualitative research approach whose main purpose is to build a theory based on empirical data and to advance deeper research by searching for core concepts that reflect the essence of phenomena based on systematic data collection (Strauss and Corbin 1997). that provides qualitative research support for the application of rooting theory (Shu 2014). In this study, NVivo12 was used to conduct a primary coding comparison of the textual materials generated during the research and interviews in Bache Old Street, and the comparison of word frequencies was used to obtain the main ideas of the relevant stakeholders, thus providing favorable support for the extraction of elements of collective memory in Bache Old Street.

4 Research Outcomes 4.1 Desktop Study 4.1.1

Digital Museum of Jiaozhou Yangge Non-Foreign Heritage

The Jiaozhou Yangge Intangible Cultural Heritage Digital Museum is one of the more successful examples of digital museums, combining digital technology with museums to digitally extract, collect, manage, display, and process intangible cultural heritage such as the Jiaozhou Yangge, and provide users with a variety of services such as digital display, education, and research via the Internet. In the virtual exhibition hall, not only are the characteristics of the intangible cultural heritage of Jiaozhou Yangge itself and its formation process collected and refined but three animations in addition to the basic forms of text, pictures and video are presented in digital form, providing an interactive display of the intangible cultural heritage of Jiaozhou Yangge in all its aspects. In addition, the service window of the Jiaozhou Yangge Intangible Cultural Heritage Digital Museum provides personalised services to all visitors while promoting the content of Jiaozhou Yangge according to the characteristics of different audience groups. For example, there is a different scope and form of visit for the audience with the purpose of entertainment and the audience with the purpose of scientific research, and the introduction of the game interactive mode makes the visitors truly participate in the interaction, truly into the non-heritage, so that the non-heritage can be truly updated in the display, inheritance and protection (Qi 2018).

4.1.2

Changsha Museum

Ito and Morita (1986) proposed that the third generation of museum was to transform its function from collecting, preserving and researching antique to composed space

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that combined the local history, architecture, collection and humanism. It should extend the boundary of culture and service to interact with public and promoting an atmosphere of a specific culture and serve as an activity center (Qian 2018). Therefore, third generations of museums are the center of collecting and creating collective memory. Amongst which, Changsha Museum set an example of integrating technology and culture to somewhat define future collective memory. The various techniques, including AR and VR implemented in the exhibition and the public activities provided the museum a variety of expression and formation. This somehow varied the activity and experience of the tourists. Interactive facilities also enhanced the Perception and vividness of collective memory, and forming a new type of space between real and virtual. On the designing perspective, Changsha museum promoted a free-route touring experience, allowing public to create their own memory and comprehension of the museum history, and is regarded as the demonstration of futuristic manifesto of museum design. The integration of technology and culture in Changsha Museum created a field of interaction between staff and audience, audience and audience, professionals and non-professionals. Combining with the concept of free tour, it constituted a collective memory generator with local characteristics, reflecting modern technology and future ideas (Deng 2021).

4.2 Field Research Interview Content Collated to Extract Collective Memory In cognitive psychology, memory consists of three processes: recognition (encoding), retention (storage), and reproduction or recollection of information (Ren 2018). Therefore, the author divided the interviewees by the concept of time, and the subject of the interviewees was “past-present-future”, which were the elderly people of Bache, the young people of Bache, and the students of the future campus of SU, this research has received ethical approval from the university research ethics committee (13,881,412,720,220,815,070,359). Collective memory is the superposition of the field, item and event of individual memory (Chen and Lu 2019). In the process of “walking” the interview, the interviewee’s relevant living environment was obtained. In the course of the “walk”, the interviewee’s perceptual information about their living environment was obtained, and the “coding comparison” function in the NVivo12 software was used to find that the collective memories of the past were the City God Temple, freshwater fish, water, dragon dances, ancient bridges, wooden houses, etc.; the collective memories of the present were the old people, tea drinking, mahjong, Wujiang, Pi egg, small boats, etc. The collective memories of the future include city living room, AI, co-creation space, online, virtual, public space, etc (Fig. 2). After field research and interviews with several stakeholders, elements of collective memory about the past, present and future of Bache were extracted and formed into a cloud map. Public architectures as the carrier social and moral life, are regarded as the intersection of individual memory and the beginning of collective memory (Yi

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Fig. 2 Sets of self-portraited word clouds

and Xiang 2020). The collective memory of this dimension of Bache Old Street is mainly reflected in the location of the central street as the first street near the south bank, where the prosperity of the canal trade and the influence of water traffic on the lifestyle of the inhabitants is clear. Thus, architectural elements, styles, forms, etc., with highly similar architectural details will give the inhabitants a more uniform image of the Bache. In addition to the references to timber structures, water towns, bridges, etc., the material carriers of non-architectural elements are also very distinctive to the locals, such as the imagery of boats, fish, marketplaces, etc. Public life requires public participation, resulting the key to forming future collective memories lies in proposing a public designed and constructed architecture which holds a public participated activity. Design and integrate new technologies and theories to empower collective memory, express potential future spatial and behavioral patterns, and promote the generation of future collective memory (Lu 2010). In the proposal of the Bache Digital Memory Museum, digital co-creation space is strategized as the carrier of this activity and the generator of future collective memory formation.

4.3 Image Capture Classification The distillation of collective memory requires the specific collection and analysis of images obtained from fieldwork (Zhu 2022). Located in the northern part of Bache Street, Bache Old Street is the central area of the street and is also located midway between the two canal waterways of the North and South Harbors, creating the unique architectural characteristics of the Bache area. Architectural elements such as the City God Temple, the Shen Residence, the ancient bridge, the Bache Pavilion and the canal waterway were selected here as the main targets for the research. In the process of image acquisition in the Bache area, attention was paid to both the real forms of ancient buildings and local dwellings, as well as to the artistic aspects of Bache, reflecting the stylistic characteristics of local traditional architecture comprehensively, with a simple and unified composition, providing perceptive first-hand information for the digital creation. In the post-editing process of the images, the digital information management system is used to complete the process. Through screening, analysis, conversion and artistic processing of different types of image

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Fig. 3 The landscape of Bache

Fig. 4 Self-portraited summary of the architectural styles

materials, they eventually become the basic information resources reflecting the landscape of Bache (Figs. 3 and 4).

4.4 Design Proposal The design of the Digital Memory Museum in Bache covers four main parts: the collective memory elements and characteristic architecture of the area distilled from research conducted in Bache Old Street; the design of the characteristic architectural forms and visual elements within Bache Old Street; the design of the Digital Memory Museum section; and the design of the derivatives of the Digital Memory Museum (Fig. 5). The Museum of Digital Memory is divided into four levels, with the first level simulating the docks and marketplace on both sides of the canal; the marketplace

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Fig. 5 Self-portraited design idea of the digital museum

section is extended to the second level while also adding a display space for the restoration of local ancient architectural forms in Bache; the third level is designed to reflect the habits of local residents in Bache with a tea room and resting space, and the fourth level and above are suspended screens, providing a digital platform for the surrounding university teachers and students to display the co-creation space; the theater spans three levels in the form of a high cylinder, using 3D images and VR technology to build an interactive platform to showcase local cultural activities (such as dragon dances, drama, etc.) of Bache. As the building is a virtual space, there is no physical connection between the various panels, with the ancient bridge acting as a channel to connect the various suspended panels between the different functional areas (Fig. 6). The Bache Digital Memory Museum app combines cultural and architectural elements into the user interface information framework, with a linear structure linking the three functional divisions of “past-present-future”, guiding users to understand and explore the history of Bacha in chronological order and more intuitively experiencing the culture and customs of the area. Using VR technology allows users to interact with virtual buildings and characters in the ‘Bazaar’ section, ‘Exhibition Space’ section and ‘Co-creation’ section, and to participate in the dressing up of the museum and the decoration of exhibits. This approach allows users to switch between visitors and designers, generating interest in travel and consumption, and stimulating new vitality for the region. Meanwhile, through the interactive linkage between online and offline, the digital museum derivative products are developed in-depth, making the app more than a mere display function. The building as a whole presents an innovative combination of technology and traditional culture, fully demonstrating the local cultural and architectural elements of Bache. At the same time, the application of virtual reality technology increases the

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Fig. 6 Self-portraited digital memory museum app

immersive tour experience for visitors, promotes their understanding and inheritance of Bache culture, and realizes sustainable development of future urban regeneration.

5 Conclusions and Reflection As the city’s economy continues to grow and residents look for a higher standard of living, more and more of the once-glorious and prosperous city streets are now facing the problem of how to preserve and revitalize them (Dai and Wang 2021). The whole process of conservation and regeneration of Bache Old Street, based on collective memory, has been carried out through field fieldwork, visits, research, summary, restoration of old buildings, and design of new spaces, the introduction of collective memory in the preservation and regeneration of Bache Old Street, an attempt to overcome the current predicament of the historic heritage and to present a new form of heritage and to promote the local tradition in the digital age. Through the refinement of the collective memory and the innovation of architecture, the development of architecture and the development of cultural tourism are mutually integrated, enabling the user to experience the traditional architecture, folk customs and values of the Bache region in an enjoyable experience. The preservation and development of the collective memory of Bache Old Street will help to revitalize and renew the street and nearby region. Given the limitation of time in this study, in-depth interviews should be conducted in the next related study to further confirm the feasibility and effectiveness of the digital museum design for the renewal and preservation of the collective memory of the ancient canal town. To provide new ideas and starting points for sustainable urban regeneration in the future.

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References Chen X, Lu SM (2019) Public space creation based on memory interpretation: a case study of the reconstruction of the grain station block in Yucheng. Modern Urban Res 11:48–55 Curl A, Tilley S, Van Cauwenberg J (2018) Walking with older adults as a geographical method. Springer International Publishing, Cham Dai J, Wang SS (2021) Research on the activation of Tulou heritage based on collective memory— a case of the renovation design of Jingxun building in Nanjiang Village, Yongding District, Longyan. Urbanism and Architect 1:98–101 Deng Z (2021) Exhibition of cultural memory and local identity—taking changsha museum as an example. J Changsha Univer 35(3):17–44 Ito T, Morita T (1986) Introduction to museums. Education Publishing House, Jilin Liu H, Zhang N (2019) The construction of urban architectural narrative space based on virtual reality technology. J Hunan Institut Sci Technol (Natural Sciences) 32(2):67–72 Liu YF et al (2018) Study on collective memory of the historic urban landscape of Lhasa based on city image. Urban Developm Stud 25(3):77–87 Lu SM (2010) On contemporary architectural narratology: spatial interiority and methods based on narrative, and its enlightenment on innovative education. Architect J 4:1–7 Qi ZY (2018) The tradition of technological innovation: the display of the intangible cultural heritage in the digital museum of China. The Border Econ Cult 4:105–109 Qian ZY (2018) Museum audience service after the merger of cultural and tourism ministries: new ideas, new approaches. Southeast Cult 3:90–94 Ren H (2018) A study of architectural design based on the reproduction of place memory—an example of the Liangjiang film and television city project in Chongqing Shi F et al (2014) The origin of the method of spatial narrative and its application in the urban research. Urban Plann Int 29(6):99–125 Shu ZW (2014) NVivo the guide of science and education. The Guide of Sci Educ 10:153 Strauss A, Corbin JM (1997) Grounded theory in practice. SAGE Sun G, Lau CY (2021) Go-along with older people to public transport in high-density cities: understanding the concerns and walking barriers through their lens. J Transport and Health 21 Yi XY, Xiang YQ (2020) The moral memory bearing functions of architecture. J Hunan Univer (Social Sciences) 34(5):103–110 Zhu X (2022) Research on the design of digital cultural and creative products of traditional architecture in Xuzhou. Design 7:22–25

Heritage BIM for Sustainable Development Based on 3D Reconstruction and Semantic Enhancement Y. Wang, H. Gao, Y. Dong, and C. Zhang

Abstract In contemporary times, Historic Building Information Modeling (HBIM) has become an effective way for the sustainable development of historic buildings. However, lack of reliable document and technical information remain significant obstacles. Furthermore, discrepancies between the ancient construction regulation and real construction process add difficulty to constructing HBIM. To address these challenges, this research proposes a framework that combines practical 3D reconstruction models with standardized HBIM models to obtain practical HBIM models. For the 3D reconstruction process, laser scanning and photogrammetry are combined together to ensure the quality of the point cloud. While for standardized HBIM models, the parameters that determine the geometric information are identified and presented as variables. The framework is verified by a case study of Twin pagodas in Suzhou, providing ideas for the constructing HBIM and sustainable development of historic buildings.

1 Introduction Heritage buildings not only reveal the specific construction of ancient architecture in different historic periods, but also reflecting humanities correspondingly. In recent decades, researchers (Murphy et al. 2009) have been developing heritage building information modeling (HBIM) and establishing frameworks, methodologies, and carrying out case studies to explore effective approaches and mechanisms for its sustainable development. However, lack of reliable document and technical information become a main obstacle. It is found that the documentation relies on both

Y. Wang University of Liverpool, Liverpool, UK H. Gao · Y. Dong · C. Zhang (B) Xi’an Jiaotong-Liverpool University, Suzhou, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_34

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traditional architectural specification promulgated in the ancient times and literature based on onsite investigation. For the former, there exists difficulty in distinguishing the size of the components in documents due to varying size definitions for the same unit of measurement across different historical periods. Meanwhile, when constructing in ancient time, workers may adjust the sizes and shapes based on site constraints and personal skills, which makes the modeling work more challenging. For the latter, the development of new non-contact surveying methods such as laser scanning and photogrammetry are still in preliminary stages, which is easy to result in missing onsite investigation data. Therefore, efforts are required to develop a standardized data processing method, in terms of the efficient data collection, proper interpretation, and accurate modeling for further management usage. Parametric modeling has been used widely to describe geometric rules and patterns followed by the construction (Bagnolo et al. 2019; Capone and Lanzara 2019), which preserves partial semantic information in digital way. The accurately real geometric of the structure can be obtained by a new method of combining laser scanning and photogrammetry together as each of these two methods has the advantage of efficiency and detail (Dey and Sun 2005). But due to the previous mentioned issues, discrepancies usually happen between the parametrically developed and the reconstructed models. Therefore, a hybrid HBIM is needed to meet different purposes by combining a standardized parametrically built model and a point cloud model. This research investigated the approach of constructing a practical HBIM model to provide guidance for the sustainable development of ancient buildings.

2 Methodology As shown in Fig. 1, this paper proposes a framework for a practical HBIM modeling. The framework consists of two parts, which are using point clouds to establish actual three-dimensional models and using ancient documents to build standardized HBIM models. Then the practical HBIM model is obtained by combining the two parts. For the practical 3D reconstruction, a new composite data acquisition method is carried out to ensure the quality. Laser scanning is used to acquire point cloud data of the historic building or components based on the effective range of each station, while photogrammetry-based method is applied by planning paths for the UAV, especially focusing on the areas where the laser scanning cannot reach. Then the two point clouds generated are aligned based on reference points, making all point cloud data transformed into the same coordinate system. Finally, the color and texture information is fused with the point cloud. The standardized HBIM modeling is created based on historical documentation, which corresponds to the construction time of the target architecture. The geometric relationship and related semantic information of the targeted components are translated and represented in modern unit and context. Key parameters of the geometry and related semantic information are identified and modeled in a standard approach.

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Fig. 1 Framework for developing practical HBIM models

Finally the two models are combined together and the dimensions of the standardized HBIM will be adjusted based on the reference of the 3D reconstructed model.

3 Case Study 3.1 Data Collection The twin pagodas in Suzhou, are selected as a case study. Figure 2 demonstrates the data collection by using both terrestrial laser scanner (TLS) and unmanned aerial vehicle (UAV). The TLS used in this research is a Leica P40 TLS with a scanning rate of 100,000 points per second. The station plan was developed by considering the effective scanning range of a single station (Huang et al. 2021). Targets were placed as spatial feature points following the principle of having at least four targets for a single scan and at least three common targets between neighboring scans. Considering that the scene is heavily shaded by trees, a total of seven scan stations were set up inside and outside the twin pagodas to ensure the coverage and the density of the point cloud dataset. Four stations were set up outside the pagodas. Station ➀ was used to record the mid-level data while station ➁, ➂ were used to acquire low-level point cloud data of the twin pagodas. Station ➃ was used to collect the side data and to register the data inside and outside the pagodas. One station was set up inside the East pagoda, while two stations were set up inside the West pagoda due to the obstacles caused by the presence of wooden stairs and the central wooden column.

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Fig. 2 Data collection details

A DJI Genie 4 RTK UAV was used to take images of the twin pagodas with a camera focal length of 8.8 mm. By carrying multiple sensors on the UAV, images can be acquired from different angles, and its own RTK technology enables real-time dynamic positioning based on carrier phase observations, which in turn provides real-time 3D positioning results of the site in a specific coordinate system, breaking through the limitations of traditional photography. For this project, the survey is used to capture details of the twin pogodas and their tops, which were photographed in a wrap-around fashion and maintain an overlap of around 70% by manual calibration (Amiri et al. 2006), collecting a total of 1429 photographs.

3.2 Data Processing and Fusion In term of data process, the laser point cloud data is first processed by using Cyclone to unify the scanned data from different discrete locations into a single coordinate system point cloud, which is then exported into a common point cloud format (pts), thus facilitating data stitching with subsequent the image point clouds. RealityCapture is a 3D reconstruction software that converts image information into point cloud data to build a model. Camera parameters, image information and other data need to be collated before modeling. Then a large number of images acquired by the UAV are converted to point clouds by this software. The integration process starts by importing the 3D laser point cloud data processed by Cyclone into RealityCapture, manually

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Fig. 3 Twin pagodas 3D reconstruction models and its details

selecting common targets in two point clouds as feature points for matching, and subsequently generating dense point clouds and mesh model. The colour and texture information captured by UAV is then mapped onto the model, and finally obtain the point cloud data of the complete building. Figure 3 show the final twin pagodas 3D reconstruction model and some of its details.

3.3 Decoding the Semantic of Twin Pagodas with Architectural Research Two main documents used in this study are Jiangsuwuxian Luohanyuanshuangta on twin pagodas (Liu 1936) and Ying Zao Fa Shi Zhu Shi (Liang 1983). The former especially explains the regulation of twin pagoda with survey drawings and measurement data of basic components. Foundation, columns, beams, Dou, Gong, windows and doors are all recorded and measured, which established one promising reference framework to decode these pagodas. Since the unit in each dynasty are different, there are also one chart in the latter document to compare and contrast the conversion rate between onsite data and data from Ying Zao Fa Shi (Li 1103). Furthermore, Ying Zao Fa Shi Zhu Shi as one official document for construction provides the basic principles and relationships of height, depth and length related to single architectural element. This is regard as program logics for digitalizing the model in Grasshopper after decoding. Therefore, both Liang and Liu’s work are the fundamental guideline and reference for decoding and parametric modeling. Parametric modeling of the pagoda describes the general geometry relationships from Ying Zao Fa Shi and measured onsite dimensions. The process is divided into three steps. Firstly, the regulations from Ying Zao Fa Shi are analyzed. Secondly, they are translated and simplified into surfaces, which then extended with depth. Finally, in

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Fig. 4 Division of Lu Dou

order to combine several elements, reference points are clarified and noted, which enables constructing in a correct position systematically.

3.4 HBIM Components The parametric models are all built by using Grasshopper and Rhino. Lu Dou and Ling Gong are two main fundamental components in traditional bracket construction system. Lu Dou is divided into two main sections to be digitalized, as shown in Fig. 4. The upper one connects with Ling Gong. The lower one is conected with column or beam. Ling Gong is divided into two symmetric parts. As shown in Fig. 5a, each part is an extrusion corresponding to the profile shown in Fig. 5b. The dimensions are decided by following the detailed described in Fig. 5b. Multiple components are assembled by using reference points, therefore, all elements could be connected in accurate and parametric way, as shown in Fig. 6. Finally, a digital model of the ground floor of the pagoda is created, as shown in Fig. 7. The main architectural elements are the structure frame on the surface of pagoda. Specifically, building components includes octagon column, beams, door, windows, Dou and Gong, as well as caisson, as shown in Fig. 8. Based on the first floor, other floors are created using similar parameters, and by decreasing dimension of the cross-section and increasing the height, as shown in Fig. 9.

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Fig. 5 Ling Gong modelling details Fig. 6 Assemble components by using reference points

4 Discussion and Future Work For the HBIM components, both standardized and practical models are beneficial to sustainable development. Standardized models can be created through ancient regulations and therefore have dimensional characteristics and semantic information corresponding to that era, which can be added to the family database as standard components. After accumulating a large number of architectural components in a family database, more detailed classification analysis can be conducted based on the

396 Fig. 7 Isometric view of the ground floor model

Fig. 8 Perspective and isometric view of caisson model

Fig. 9 Parameters modelling example

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data to obtain a genealogy study, which can be used for the restoration or reconstruction of ancient architecture that has been damaged. Additionally, by comparing the same component from different time periods, the evolution of ancient culture can be studied, which is beneficial for cultural preservation. Meanwhile, it is easy to change to the practical model in almost all the historical building at that time by adjusting the variables. For the practical model, it can be exported as models of different sizes for different purposes while maintaining its level of precision. For file sharing between different industries, models can be generated for easy data transmission by user defined requirements. As for the source files, they can be sent to the local cultural heritage bureau for backup and storage purposes. The future work of this research is to combined these two models and investigate an approach for aligning geometric and matching semantic features.

5 Conclusion In order to address the issue of sustainable development of historic architecture, this research proposes a new framework for a constructing HBIM. The framework involves combining actual 3D reconstruction with standard HBIM model to obtain the practical HBIM model. For practical 3D reconstruction, laser scanning and photogrammetry methods are integrated in a new way to solve the problem of missing point clouds due to the complexity of ancient components, thereby ensuring the accuracy and quality of the point clouds. Subsequently, the two types of data are fused together in a heterogeneous manner. Image point clouds with color texture information are fused with laser point clouds for reconstruction, resulting in the practical 3D reconstruction model of the Twin Pagodas. For standard HBIM modeling, it is firstly based on historical documentation, which corresponds to the construction time of the target architecture. Then, with the reference of geometric patterns and related semantics, parameterized modeling is carried out to obtain standardized parameter models. Finally, by comparing the differences between the actual 3D reconstruction model and the standard parameter model, an actual HBIM model is obtained. The framework is demonstrated through a case study of the twin pagodas in Suzhou. The framework successfully obtains the HBIM components such as octagon columns, beams, doors, windows, Dou, and Gong. Finally, they are successfully assembled and integrated, proving the feasibility of the framework. Acknowledgements This research is funded by Suzhou Science and Technology Development Planning Programme, grant number: 2022SS51.

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References Amiri PJ, Gruen A, Cozzani A (2006) High accuracy space structures monitoring by a closerange photogrammetric network. Int Archiv Photogrammetry Remote Sens Spat Inform Sci 36:236–241 Bagnolo V, Argiolas R, Cuccu A (2019) Digital survey and algorithmic modeling in HBIM. towards a library of complex construction elements. Int Arch Photogramm Remote Sens Spat Inf Sci 42:25–31 Capone M, Lanzara E (2019) Scan-to-BIM vs 3D ideal model HBIM: parametric tools to study domes geometry. The Int Archiv Photogrammetry Remote Sens Spatial Inform Sci 42:219–226 Dey TK, Sun J (2005). An adaptive MLS surface for reconstruction with guarantees. In: Symposium on geometry processing, pp 43–52 Huang H, Zhang C, Hammad A (2021) Effective scanning range estimation for using TLS in construction projects. J Constr Eng Manag 147:04021106 Li J (1103) Ying Zao fashi, Shangwuyin shuguan Liang S (1983) Yingzaofashi zhushi [The annotated Yingzaofashi]. Beijing: Zhongguo jianzhu gongye.. 1984. Zhongguo jianzhu zhi liangbu" wenfa keben"[The two" grammar books" of Chinese architecture]. Liang Sicheng wenji, pp 357–363 Liu D (1936) Jiangsuwuxian luohanyuanshaungta. Architectural History Murphy M, McGovern E, Pavia S (2009) Historic building information modelling (HBIM). Struct Surv 27:311–327

Review on Ventilation Efficiency and Planning of Urban Blocks in the Context of Carbon Neutrality X. Y. Liu, B. Wang, Y. T. Qian, J. Z. Li, and Z. J. Xue

Abstract This paper analyzes and compares the research progress of urban block scale ventilation efficiency and planning at home and abroad in the past half century. This paper focuses on the study of the ventilation efficiency index of urban blocks and the comparative analysis of the existing research results on the correlation between the spatial form of urban blocks and ventilation efficiency, and summarizes and analyzes the wind environment characteristics of various low-carbon building layouts through numerical simulation and discussion under different low-carbon design techniques. To provide theoretical support for shaping low-carbon planning and design at block level from the perspective of carbon neutrality. Keywords Ventilation efficiency · Urban blocks · Carbon neutrality

1 Introduction As urbanization continues to accelerate, the replacement of permeable surfaces with impermeable ones has led to the destruction of urban micro-climates and ecological challenges (Zhou and Zhang 1985). In order to create livable urban environments, it is imperative to focus on the development of green and energy-efficient buildings in pursuit of carbon neutrality. At the neighborhood scale, it is crucial to promote good ventilation and green spaces to alleviate the heat island effect, improve the city’s sewage capacity, and enhance the atmospheric environment’s self-cleaning capacity to improve the overall comfort of urban habitats. This paper organizes and summarizes the specific study steps and methods of the ventilation effectiveness and planning of urban blocks in the context of carbon neutrality. Based on a comprehensive search of keywords such as “urban block, ventilation, and carbon” on the Chinese Journal Full Text Database from China national knowledge infrastructure (CNKI), the related keywords in the cross-study

X. Y. Liu · B. Wang · Y. T. Qian · J. Z. Li · Z. J. Xue Soochow University, Suzhou, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_35

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Fig. 1 Keyword mapping on a urban ventilation and carbon neutrality, b wind environment in neighborhood scale, c ventilation efficiency

of urban ventilation and carbon neutrality is visialized with the help of VoSviewer (Fig. 1). This article begins by introducing the concept of urban ventilation and carbon neutrality. It then delves into the technical methods and findings of neighborhoodscale ventilation effectiveness, followed by a summary of research on urban neighborhood ventilation planning. Lastly, it addresses the current shortcomings in this field and suggests future directions for development.

2 Relationship Between Urban Ventilation and Carbon Neutrality Urban ventilation is an important issue in urban planning and a topic that has received increasing attention in recent years. With the intensification of global climate change and the increasing awareness of environmental protection, carbon neutrality has become a development goal for many cities. In this context, the contribution of urban ventilation to carbon neutrality is of great importance (Zeng et al. 2023). First, urban ventilation can reduce the temperature in cities and reduce the use of air conditioning and other energy consumption (Li et al. 2023). Zheng et al. (2022) demonstrated the benefits of urban ventilation planning through the use of weather research and forecasting models combined with urban canopy models. Their study showed that the construction of ventilation corridors in Beijing resulted in lower average temperatures, higher wind speeds, and improved humidity, leading to an overall improvement in the human environment. Second, urban ventilation can improve urban air quality and reduce pollutant emissions (Zhan et al. 2022). Vehicles, factories and buildings in cities produce large amounts of exhaust gases and pollutants, which are extremely harmful to human health and the environment. Reasonable ventilation design and layout can increase air circulation in cities, reduce pollutant concentration and emissions, and improve urban environmental quality. Liu et al. (2022) studied and designed an integrated

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ventilation assessment approach (IAVA), which uses multi-source data to assess the urban wind environment and introduces the effects of topography, vegetation and open space to provide guidance to the government in urban planning and construction. Finally, urban ventilation can improve the natural resource efficiency of cities by utilizing natural wind and air currents to ventilate buildings and purify air, leading to reduced energy consumption and achievement of carbon neutrality (Han 2015). Precise design of the built environment is crucial to achieving energy-efficiency and optimizing natural ventilation, as the urban block form significantly affects ventilation efficiency (Azizi and Javanmardi 2017). In conclusion, urban ventilation plays a crucial role in achieving urban carbon neutrality. McArthur (2020) even studied the benefit–cost of carbon-offset by outdoor ventilation. Therefore, it is essential to prioritize ventilation design and layout in the urban planning and construction process. By taking reasonable measures to optimize the urban environment, we can achieve a greener, healthier, and more sustainable urban development (Ma and Chen 2022).

3 Study of Ventilation Efficiency in Urban Neighborhoods 3.1 Neighborhood Wind Environment Testing Techniques In general, ventilation strategies can be divided into three types: natural ventilation, mechanical ventilation, and mixed ventilation, and mixed ventilation systems are commonly used in urban blocks (Kim and Baldini, 2016). The three primary techniques for testing the wind environment in a neighborhood scale are field measurements of wind data in reality, wind tunnel experiments with scaled-down physical models, and computational fluid dynamics (CFD) simulations for numerical calculations on a computer. Field measurements accurately reflect the coupling relationship between urban neighborhood morphology and ventilation effectiveness, considering factors such as vegetation that are difficult to simulate in ideal models used in wind tunnels or CFD simulations. For instance, Liu et al. (2018) improved the residential wind environment using green space strategies validated by wind measurements and numerical simulations conducted in Tongji University’s Changwu Road dormitory. Similarly, Hong et al. (2014) combined actual measurements and simulations in Beijing’s Heqing Yuan neighborhood and found that optimized winter vegetation adjustment significantly improved the pedestrian wind environment by reducing wind speed in winter. Wind tunnel experiments use downsized similar physical models to simulate the built environment based on the principle of relativity of motion and mobility, commonly used in aerodynamics and aircraft development. Wang et al. (2004) found high northwest winds affecting pedestrian safety and comfort, and southerly winds causing local air pollution in a wind tunnel study of the wind environment in Beijing’s

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CBD. Ma et al. (2008) compared wind speed at pedestrian height with the height of nearby buildings, and found that wind speed decreases in FLUENT software simulated a group building and wind tunnel test values. CFD simulation method is widely used for wind environment testing due to the high cost of field measurements and equipment requirements of wind tunnel experiments. CFD simulations have become the first choice for practitioners and scholars as design programs frequently change. Liu (2021) combined CFD simulation with PHOENICS for wind flow analysis in the factory and surrounding living area of Zhengda Group in Chuzhou City, Anhui Province. Similarly, Kuang et al. (2015) validated wind channel width, direction, and dominant wind angle for urban neighborhood-scale green belts using the urban microclimate simulation software ENVI-met and proposed three recommendations.

3.2 Neighborhood Wind Environment Evaluation Methods Since 1980, a significant number of scholars have utilized CFD numerical simulation software to examine the relationship between urban morphology and wind environment. The market’s primary CFD software comprises Fluent, Phoenics, ANSYSCFX, ENVI-met, MISKAM, etc. Table 1 shows some representative research cases on outdoor wind environment using different CFD numerical simulation software. Different CFD method have different computeation skills and conditions, and can also have different result precision. Besides, numerical simulation is often accompanied with wind tunnel experiment or in-situ measurement for validation.

3.3 Neighborhood Ventilation Efficiency Study The wind environment is mainly studied from the perspectives of urban ventilation, architectural layout, wind speed and pressure changes at building angles, and relatively mature research results have been obtained. Pearlmutter D and other scholars developed a model to quantify the influence of street geometry on pedestrian comfort under various seasonal conditions, proposing that in hot and arid climates, aligning the axis direction of dense street canyons with the north–south direction can greatly reduce overall pedestrian discomfort (Pearlmutter et al. 2007). Adolphe quantified the urban form index and urban built environment to evaluate the ventilation potential of urban environments (Adolphe 2001). Fu (2022) and others studied the relationship between indoor air quality, outdoor air pollution levels, permeability, and resident behavior through on-site measurement and numerical simulation, which can effectively control indoor particle levels. The field of block ventilation efficiency study can be categorized into 6 main areas: urban climate and wind environment, urban ventilation corridors, urban blocks, single high-rise buildings, high-rise buildings, and commercial buildings in central

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Table 1 Example of studies simulating outdoor wind environment with the help of CFD CFD used

Major scholars

Year

Main research contents

Grasshopper and Ladybug

Victoria Patricia López-Cabeza, etc

2023

Thermal inertia and natural ventilation on user comfort in courtyards in Hungary are studied, with help of Building Energy Simulation and CFD (Victoria et al. 2023)

Fluent

Wang Biao, etc

2022

Using fluent to simulate ten typical residential urban forms in Beijing to reduce near-surface pollution (Wang 2022)

OpenFOAM

Shahid Mirza, etc

2022

Studying impact of infrastructure development on wind profile and temperature of the surrounding area along with the cooling effect of vegetation cover in Dhantoli Park (Shahid et al. 2022)

Phoenics

Guo Weihong, etc

2020

Use Phoenix to find ventilation problems in the residential area of Moon Island (Guo et al. 2020)

CFX

Cai Yadong, etc

2020

Use k of ANSYS-CFX- ε Analysis of a university in Changchun (Cai et al. 2020)

ENVI-met

Qin Wencui, etc

2015

Microclimate simulation of typical residential areas in Beijing using ENVI-met model (Qin et al. 2015)

WinMISKAM

Yang Xiaoshan, etc

2016

Comparing the difference between MISKAM and ENVI-met software. The latter is more suitable for wind environment (Yang and Zhao 2016)

districts. Scholar Liu Jiaping and others have found that factors such as geometric scale, street direction, building density, form, and materials greatly influence the thermal environment in street valleys. Numerical simulations of Xi’an streets reveal that the optimal aspect ratio is 1:1.1, and that the geometric scale, street direction, and building form all affect the thermal environment (Zhao and Liu 2007). Chen Qiquan analyzed the impact of spatial form elements on wind environment in cold areas of commercial pedestrian streets through actual measurements. They proposed optimal design strategies for commercial pedestrian streets in Luoyang, including street direction, plane form, aspect ratio, and surrounding building enclosure for a

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square, using computer wind environment simulation for the dominant wind direction in the transition season (Chen 2018).

4 Study on Ventilation Planning in Neighborhoods 4.1 Current Status of Ventilation Planning in Urban Neighborhoods As natural ventilation’s impact on urban energy consumption, pollutant dispersion, and urban heat island alleviation gains attention, ventilation planning at the neighborhood or city scale is becoming a specific planning element. Asfour (2010) analyzed the distribution of wind environment in different building layouts under the same dominant wind direction in hot Gaza region. They also studied the wind environment distribution in the same building layout under different dominant wind directions, and compared and analyzed the optimal building layout modes that promote natural ventilation. Ghiaus et al. (2006) state that urban morphology has a significant impact on the urban environment, affecting factors such as wind speed, noise, and pollutants. Urban models with varying morphologies have been established to quantify the relationship between morphology and environmental impact. These models can be used in early planning and design stages to assess the feasibility of natural ventilation, particularly in street canyons. Van Hooff et al. (2010) conducted a simulation coupling urban and indoor natural ventilation in eight wind directions. They analyzed and studied the effects of wind direction on the urban environment, as well as the impact of the surrounding environment on the building’s internal environment. In summary, research shows that the building form has both direct and indirect impacts on block space ventilation and carbon emissions reduction. The direct model involves the use of sunlight, while the indirect model involves adherence to current energy rules. As such, architects should rationally design the spatial shape of the block, make scientific use of natural resources, and promote low-carbon building in blocks.

4.2 Methods and Techniques of Urban Neighborhood Ventilation Planning The main countries that carry out wind environment project practices at home and abroad include Germany, Japan, the United States, Singapore, Hong Kong, Beijing, Wuhan, Tianjin, and other places. A reasonable building layout can improve the ventilation of the neighborhood. For example, by installing open space, green belts or using staggered design to increase the interval between buildings, air can flow freely

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(Wei et al. 2017). Besides, roads and transportation facilities are also important factors affecting urban ventilation. In the design of roads, the blockage of wind direction by buildings should be reduced as much as possible, as well as in the organization of urban traffic to avoid dense parking and downwind driving and other phenomena (Wang et al. 2023). The choice of suitable vegetation in neighborhood greening can improve the air quality of the neighborhood and avoid obstructing the wind by choosing relatively low green plants and trees (Tang et al. 2023). At the same time, urban wind energy use is also an effective means to enhance urban ventilation planning. For example, in the construction of high-rise buildings, wind turbines can be installed to achieve energy savings (Wen et al. 2022). Computer simulations and other technical means are used to model as close as possible to actual building forms and to analyze the surface roughness of urban neighborhoods in order to identify the locations of potential air-guided pathways in the city so that measures can be targeted at the planning stage. For example, Ying et al. (2023) proposed a GIS-based analysis method combining Comprehensive Ventilation Cost Index (CVCI) and Minimum Cumulative Cost Analysis, which visualizes the ventilation performance of urban areas and realizes macro-scale ventilation analysis from microscopic 3D building forms combined with urban environment. Taking a neighborhood in the old district of Anqing City as an example, Li (2016) used PHOENICS software to simulate the wind environment and suggested using the space between buildings, and demolishing individual buildings if necessary, to build street-level green spaces, which could be connected to the urban green space system to form a green source wind and improve ventilation. In conclusion, urban neighborhood ventilation planning requires comprehensive consideration from multiple perspectives and the use of scientific methods and techniques to achieve the goal of improving urban air quality and human living environment.

4.3 Case Studies of Ventilation Planning in Urban Neighborhoods Currently, many countries and regions around the world have launched urban block ventilation planning projects. In order to improve air pollution, Germany’s Stuttgart has set up ventilation corridors through environmental monitoring and computer simulations, using meteorological networks, aerial photography and thermal imaging technology, and onboard measurement technology to establish macro land use guidelines for later land use planning. Due to the health and energy consumption issues caused by climate change, the Japanese government has been evaluating a five-level wind pathway system since 1990 and has summarized three available wind pathway forms (Architectural Institute of Japan 2002). Through the collection and analysis of meteorological data, the macro wind pathway of the city has been divided. In Japan’s Hashikawa, simulations were carried out to evaluate the ventilation performance of

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(a) Near-surface duct forms

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(b) Use of river and street breezeway forms

(c) The form of introducing sea breeze by using the sinking wind generated by high-rise building

Fig. 2 Three air paths recommended by the architectural institute of Japan (2002)

urban areas on both sides of the river, adjusting the height of buildings along the river and demolishing some buildings to optimize the ventilation environment (Fig. 2). Domestically, wind environment practice projects have also been carried out. In response to the haze pollution in Beijing, the governments of Chaoyang District and Tongzhou District cooperated to conduct urban block ventilation planning. In the planning, they adopted various methods such as staggered building design, setting up open spaces, and increasing green belts to improve the ventilation effect of the block. At the same time, they also used CFD to predict the ventilation effect of different schemes, and finally selected the optimal scheme for implementation (Kwok 2022). Hong Kong has divided the urban climate planning into five zones and formulated control guidelines through grid analysis of multiple factors such as urban land use, construction, terrain, and MM5 wind environment numerical simulation. Wuhan City has used the urban surface roughness theory and cross-sectional algorithm to calculate the windward area density of buildings to delineate the macro wind pathway of the city and guide the building density and development intensity of urban zoning. These cases demonstrate that urban block ventilation planning is a complex and practical engineering project that requires the use of various methods and technologies to improve the urban environment and enhance resident’s quality of life.

5 Conclusion 5.1 Shortcomings of Current Research on Urban Neighborhood Ventilation From the above, it can be seen that wind environment assessment and wind pathway design strategies need to be closely integrated, from the large-scale planning of regional planning to the small-scale design of specific building forms, in order to form an efficient urban "breathing" system. Urban block ventilation is an important issue in the urban environment, but there are still many shortcomings in the current research on urban block ventilation.

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First, the current research on urban neighborhood ventilation mainly focuses on outdoor wind field measurements and single building interior ventilation studies, and there is a lack of in-depth research on ventilation problems at the neighborhood scale. Second, the existing methods and techniques for urban neighborhood ventilation studies still cannot fully cover the different economic, cultural, and climatic differences of cities. Therefore, it is essential to carry out ventilation studies with regional characteristics in different places (Zhong et al. 2023).Finally, the current understanding of the factors influencing ventilation in urban neighborhoods is not comprehensive, and many influencing factors still need to be further explored. All these factors may have important effects on ventilation in urban neighborhoods, and further investigation can provide a better scientific basis for urban planning and environmental protection (Da et al. 2022).

5.2 Methodology and Focus of Future Urban Neighborhood Ventilation Research In the context of carbon neutrality, the approach and focus of future urban neighborhood ventilation research should be closely focused on the following aspects: Energy consumption and climate change aspects: In the context of carbon neutrality, future urban neighborhood ventilation research needs to pay more attention to aspects such as building energy consumption and climate change. For example, the change patterns of parameters such as temperature distribution and humidity distribution inside buildings under different ventilation conditions, as well as the heat exchange between the interior and exterior of buildings under different ventilation conditions can be explored by means of numerical simulations and laboratory experiments. Sustainability aspects: in the context of carbon neutrality, future research on urban neighborhood ventilation needs to pay more attention to sustainability issues. For example, the distribution of air pollutant concentrations inside urban neighborhoods can be explored, the effect of various ventilation schemes on air quality improvement can be analyzed, and methods and measures to improve ventilation effects while ensuring environmental health can be found); at the same time, attention needs to be paid to sustainable development issues in urban greening, water resources management, and waste disposal combined with ventilation. Combination of numerical calculations and laboratory tests: future research on ventilation in urban neighborhoods needs to combine numerical calculations and laboratory tests to achieve more accurate and reliable research results. For example, numerical simulation methods such as computational fluid dynamics (CFD) can be used to study the internal airflow movement patterns of neighborhoods under

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different seasons and meteorological conditions; meanwhile, corresponding largescale neighborhood models can be set up in the laboratory for physical field measurements. In summary, future urban neighborhood ventilation research needs to pay more attention to climate change, energy consumption, and sustainable development in the context of carbon neutrality, emphasizing the combination of numerical calculations, laboratory experiments, data sharing and comprehensive analysis, and other methodological means to provide a more comprehensive and accurate scientific basis for urban planning and environmental protection. Acknowledgements This research was funded by National Key R&D Program of China (2021YFE0200100); The 2021 Jiangsu Construction System Science and Technology Project (2021ZD03).

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Hong B, Lin BL (2014) Research on optimal design of winter vegetation in residential quarters based on measurement and simulation. Chinese Landscape 30(09):104–108 Hooff, Twan VT, Blocken BB (2010) On the effect of wind direction and urban surroundings on natural ventilation of a large semi-enclosed stadium. Pergamon 7 Han L et al (2022) Urban ventilation corridors exacerbate air pollution in central urban areas: evidence from a Chinese city. Sustain Cities and Soc 87:10 Ignatius M et al (2015) Urban microclimate analysis with consideration of local ambient temperature, external heat gain, urban ventilation, and outdoor thermal comfort in the tropics. Sustain Cities and Soc 19:121–135 Kim MK, Baldini L (2016) Energy analysis of a decentralized ventilation system compared with centralized ventilation systems in European climates: based on review of analyses. Energy and Build Kuang XM et al (2015) Evaluation of ventilation efficiency of urban street-scale greenbelts based on computer simulation. Urban Dev Res 22(09):91–95+157 Kwok YT et al (2022) Towards decarbonisation targets by changing setpoint temperature to avoid building overcooling and implementing district cooling in (Sub)tropical high-density Cities—a case study of Hong Kong. Sci The Total Environ 811:152338 Littlefair P (2001) Daylight, sunlight and solar gain in the urban environment. Sol Energy 70(3):177– 185 Liu X et al (2022) Wind environment assessment and planning of urban natural ventilation corridors using GIS: Shenzhen as a case study. Urban Climate 42:101091 Li JY (2016) Research on urban ventilation corridor planning method based on CFD technology. Anhui University of Architecture Li ZJ et al (2023) A screening model for potential urban ventilation corridors based on multi domain POI positioning and dual mitigation wind direction guidance. J Geoinform Sci 25(03):479–494 Liu BY, Runze S (2018) Adaptive strategies for residential wind environment landscape based on data measurement and CFD simulation: a case study of the Zhangwu Road Dormitory area of Tongji University. Chinese Landscape Architect 34(02):24–28 Liu YR (2021) Research on landscape design based on CFD numerical simulation technology for outdoor wind environment of buildings—a case study of Chuzhou Zhengda feed factory. J Xi’an Univer Arts and Sci (Natural Science Edition) 24(03):64–68 Ma J et al. (2008) Simulation study of wind environment in group buildings. Comput Simul (06):296–298+307 Ma T, Chen T (2022) Outdoor ventilation evaluation and optimization based on spatial morphology analysis in Macau. Urban Climate 46:17 McArthur JJ (2020) Rethinking ventilation: a benefit-cost analysis of carbon-offset increased outdoor air provision. Build Environ 169:106551 Okeil A (2010) A holistic approach to energy efficient building forms. Energy and Build 42(9):1437– 1444 Olgyay V, Olgyay A (1963) Design with climate: bioclimatic approach to architectural regionalism, from the personal collection of Ilona Olgyay. Princeton University Press Pearlmutter D et al (2007) Integrated modeling of pedestrian energy exchange and thermal comfort in urban street canyons. Build Environ 42(6):2396–2409 Qin WC et al (2015) Numerical simulation and analysis of microclimate in typical residential areas in Beijing based on ENVI-met. J Meteorol Environ 31(03):56–62 Steemers K (2003) Energy and the city: density, buildings and transport. Energy and Build 35(1):3– 14 Shahid M et al (2022) Studying impact of infrastructure development on urban microclimate: Integrated multiparameter analysis using OpenFOAM. Energy Nexus 6:100060 Takebayashi H, Moriyama M (2007) Surface heat budget on green roof and high reflection roof for mitigation of urban heat island. Build Environ 42(8):2971–2979

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How Sea Level Rise Impacts the Economy: A Study on Elevation’s Impact on Property Value Growth in Pinellas County, FL, USA Wentao Shen

Abstract In the context of accelerating Sea Level Rise (SLR) globally, elevations of coastal properties are becoming a more important factor for homebuyers given their relationship to current and future. This study investigates the impact of elevation on the residential property market of Pinellas County, FL, USA. Single-family properties no higher than an elevation of 4 m are selected as the sample. The research focuses on two aspects of elevation’s impact: elevation’s impact on long-term appreciation and the “price” of this characteristic in property transactions. The first hypothesis tested is that the properties at lower elevation have a slower appreciation rate over time. This hypothesis is tested by constructing price indices at different elevations from 1972 to 2019. The result suggests that the hypothesis applies to the properties no higher than 1 m, and, further, properties at 1 m have the fastest appreciation rate. The second hypothesis tested is that properties at higher elevations can be sold at higher prices over comparable properties. This hypothesis is tested by conducting hedonic regressions on property transactions at different elevations from 1995 to 2019. The results suggest that the hypothesis applies to around a quarter of the areas investigated. All the findings generally indicate that, while homeowners are paying some increasing attention to the elevation of properties in home purchasing, it has not been a significant factor so far in Pinellas County, FL, USA. Keywords Sea level rise · Economy · Property value growth

1 Introduction Sea level rise (hereinafter “SLR”) is no doubt one of the most concerning issues globally, especially given the observed acceleration in the past two decades (Federal Science Steering Committee 2017). State of Florida, as a peninsula located in the south-east of United States, is naturally under the threat of SLR. As a matter of fact,

W. Shen University of Florida, Gainesville, Florida, USA © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_36

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the rate of SLR in some part of the state is even faster than the global average (ValleLevinson et al. 2017). This makes it more revelatory to investigate SLR’s impact on Florida, in order to further evaluate SLR’s global impact. Florida is known for its coastal areas with great access to ocean views, which results in the massive development in these areas. However, the accelerating SLR results in the increasing flood risks, which is a threat for the coastal residents. Such threat is perceivable: the limited mobility during high tide flood events, the increasing cost of flood insurance, and the associated higher taxes or fees to implement risk reduction infrastructures, etc. These factors may possibly drive residents to consider moving to higher ground (Treuer et al. 2018). As a matter of fact, such phenomenon has been seen in Miami—a city under serious influence of the rapid SLR in southeast Florida. Here, researches have found the phenomenon that properties at a higher elevation have been experiencing greater demand by property buyers which has accelerated the housing price growth (Shimberg Center for Housing Studies 2019). Interestingly, in Miami, the communities at higher elevations have been traditionally occupied by low-income neighborhoods where property values are relatively low. The inflow of wealthier developers has caused concerns about “climate gentrification” in poor communities, which may be forcing away low-income residents who cannot afford the fast-growing cost of living (from increased rents or property taxes) (Green 2019; Berger 2018). There is also evidence in Miami that the low-elevation areas become less preferred. The average property appreciation in low-elevation areas has slowed over the past five decades in comparison to the growth in high-elevation areas, although the former includes many coastal houses with relatively better ocean access (Keenan et al. 2018). With the curiosity of determining whether the phenomenon that, SLR is impacting the residential property market as evidenced in Miami, is also happening in other areas exposed to SLR, this study will explore the impact of elevation on the property market in another coastal county in Florida. Pinellas County is selected to be the study area given its overall exposure to SLR and strong housing demand. The county is located in the west of Florida, consisting of a peninsula and a barrier island. Such geography results in the relative high vulnerability to SLR. Since 1995, the flood events have become more frequent in the county (Pinellas County 2015). Such increasingly tangible threat from SLR might affect the residents’ decision making in home-purchasing. Besides, it is the most densely populated county in the state of Florida, with nearly 1 million residents (Pinellas County 2020).

2 Research Questions Given the general assumption that higher ground should be less affected by floodings caused by SLR, as well as the fact that Pinellas County was observed to suffer from increasingly frequent flood events since year 1995, there are two primary hypotheses to be tested in this project:

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1. Properties at lower elevations in Pinellas County have experienced slower growth in value over time than properties at higher elevations. 2. Since 1995, lower elevation reduces property values in Pinellas County as such properties have potentially increased exposure to flooding.

3 Literature Review As the flooding risk in coastal areas increases, more residents may choose to leave their home. In theory, the migration of coastal residents can happen at different scales: intercommunity, intercity, intercounty, interstate, etc. In the long term, due to SLR’s further accelerating and people’s raising concern of it, more and more residents in the coastal areas may migrate to inland areas. The larger, more integrated metropoles may become the preferred destinations. For instance, Orlando-Kissimmee-Sanford, FL is expected to receive at least 370,000 migrants from other coastal cities like Miami by the year 2100 if sea levels rise by 1.8 m (Hauer 2017). However, many other residents may still choose to stay in the same city, even the same district, due to their close ties to their original landscape and access to local common resources, as well as the lack of economic prospects in a new area, inconvenience of seeking new jobs, etc. Their psychological resistance to such a significant life change may also be another reason (Sherbinin et al. 2011). These residents may tend to prefer nearby communities which are more protected against SLR. And this may result in diverse housing demand within a small area. For instance, the occupancy rate of a well-protected community may be much higher than the occupancy of an adjacent less-protected community. These residents tend not to make proactive planning decisions to relocate because of climate change as long as they think the actual threat will not happen within their normal planning horizons. For example, if the actual impact may happen after 30 years, they would not care about it at all. (Akerlof et al. 2017; Spence et al. 2012). Such a myopic view results in the underestimation of future defensive expenditures on climate change mitigation, which keeps them living at their current location or perhaps moving without the consideration of SLR’s threats. Additionally, residents’ lack of knowledge and awareness of climate change is another factor affecting their decision making. For instance, residents who are skeptical about climate change will be less likely to take action to upgrade their houses to resist climate risk (Whitmarsh 2011). These psychologies may partly maintain the housing demand at the lower elevation in short term. However, when the perceivable threat becomes more concrete instead of a vague possibility in the distant future, more people may be able to make proper decisions accordingly (Frederick et al. 2002). An example is that most coastal residents in southern Florida are found to be willing to pay more to keep living in coastal areas in the long-term but they become more interested in moving out as the cost of living grows (Treuer et al. 2018). As the accumulation of appreciable expenditures reaches a certain critical threshold, these homeowners are expected to abandon their property eventually (Mcnamarea and Keeler 2013).

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Overall, the factors above suggest that the general housing demand at coastal areas should not see a dramatic drop in the short term while some part of these areas, with better SLR-protections, may become more preferred in the long-term.

4 Methodology 4.1 Sample Selection: Single-Family Houses no Higher Than an Elevation of 4 M Single-family houses are selected as the sample of this study given its massive supply, relatively high vulnerability towards flood risk, and overall comparability (Keenan et al. 2018). There are 242,000 single-family houses in the county. 786,000 sales transaction records of these properties, dating from 1899 to 2019, were downloaded from Pinellas County Property Appraisers’ website. These records include the information of parcel number, jurisdiction, effective building age, actual building age, living area (i.e. building square footage), sold year, and corresponding sold price. With the usage of ESRI ArcMap, each record was assigned with their elevations and distance to shoreline. Given the elevations of Pinellas County range from 0 to 31 m, there are properties located on high elevations that are much less affected by SLR-caused flood risk. In order to effectively capture the increasing awareness of potential flood risk and its impact on property values and appreciation, a threshold in elevation is calculated to reduce the properties with a lower exposure to SLR. Such an operation also helps to reduce the cumbersomeness in computation as it culls many properties that are less relevant to the above two hypotheses. Special Flood Hazard Area (SFHA) of Federal Emergency Management Agency (FEMA) is used as a reference as the concept is widely promoted to all homebuyers through FEMA’s National Flood Insurance Program (NFIP). The practical regulatory influence of the NFIP is expected to make homebuyers more aware that their long-term cost of living is related to the flood risk, which may affect their decision making. With the usage ESRI ArcMap, 95% of SFHA is found under the elevation of 3.9 m. Elevation of 3.9 m is tentatively considered as the threshold, which indicates that the areas above this elevation are considered less vulnerable to flood risk and where property price appreciation has minor relevance to elevation. Sales transactions of properties above 4 m are thus removed from the dataset. The sample is thus finally reduced to 248,000 rows of sales transaction records.

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4.2 Economic Analysis 4.2.1

Construction of a Price Index

A price index is constructed in order to trace the property appreciation pattern at different elevations. The average price method is selected to construct a price index in this study. Sales transactions occurring in past 47 years (i.e. 1972 to October 2019) are selected to build the price index model. Such a time period is considered to be robust enough to mitigate the long-term impact of real estate cycles on property appreciation (Bailey et al. 1963). To create the price index, the geometric mean of all the properties sold in same year is calculated as the average price of properties sold of any given year. At different elevations, the mean price of each given year is divided by the mean price of base year (i.e. 1972). The result calculated is the price index of given year. Geometric Mean Sales Price = (P1 P2 . . . Pn )1/n P1 , P2 , …, Pn are the actual sales prices of each transaction record. The first hypothesis that, properties at lower elevations have a slower appreciation rate over time, is tested by comparing the price index growth patterns at different elevations over time.

4.2.2

Hedonic Pricing Modeling

Hedonic pricing modeling is used to explore the elevation’s impact on an individual property’s price. This provides a static assessment of how much differences in sales price may result from incremental differences in elevation. With the usage of a multiple linear regression, the numeric relationship between the increment of elevation and increment of sales price is computed to represent the “price” of the increments of elevation. Different from the price index construction, which assesses elevation’s impact on long-term property appreciation across the aggregated property dataset over time, this step statically examines how the sales price of each transaction is related to various property attributes including elevation. With hedonic regression modeling, the sold price of each single-family parcel transaction since 1995, which is roughly the time period that flood events were observed to be increasing across Pinellas County (Pinellas County 2015), is set as the dependent variable. Six parcel attributes are set as independent variables including: effective building age, actual building age, building square footage, elevation, distance to the shoreline, and sold year. The first three variables are considered to be most important physical features that significantly affect a property’s price, according to Keenan et al. (2018). For geographical features, distance to the shoreline is selected, in addition to elevation, given the general assumption that the good water access is a selling point of property that may contribute to the higher sales

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price. The sold year is also added into the regression analysis in order to address the influence from the monetary inflation and the general appreciation of property market. The model is thus represented as below (Anonymous 1997):     Sales Price ∼ β0 + β1 j ∗ elevation + β2∗ e f f ecti ve building age     + β3∗ actual building age + β4∗ building squar e f ootage     + β5∗ distance to shor eline + β6∗ sold year + e β0 is the intercept, and β1 to β6 are the coefficients of each independent variable. Such a model is expected to explain the different factors’ individual impact on the sales price. The hypothesis of the second research question is tested by computing the coefficient of these variables: a positive coefficient represents a positive correlation and vice versa. In order to minimize the influence of locational differences on the validity of results, the regression modeling is conducted at “section” scale. With the usage of ESRI ArcMap, the land and adjacent water feature of Pinellas County is equally divided into 415 quadrate divisions at the area of 1 section (i.e., 1 square mile or 2.6 km2 ). This size is suggested by Harral and Ashley (2005) as the suitable geography that ensures properties’ locational cooperability. Divisions with less than 98 (50 + 8x, x as the number of independent variables) records are excluded as such sample sizes are insufficient for regression analysis (Green 1991).

5 Modeling and Findings 5.1 Price Index Analysis 5.1.1

Findings at County Scale

Figure 1 is the price index growth pattern over time in Pinellas County between 1972 and 2019. This chart suggests that the observed differences in the appreciation rates among elevations started to emerge in the late 1980s. While price appreciation at 1-4m varies, the appreciation rate at 0 m lags the group. It may suggest that the price growth of these most-affected properties is dragged by increasingly perceived flood risk, while the exorbitant housing prices of these ocean-view properties at 0 m can be another significant potential limitation to the appreciation. In addition, greater price appreciation at 1m starts to emerge in the mid-1990s. Properties at 1 m then have clearly outperformed all others since 2000. This may be related to the observed flood events that increased across Pinellas County that began in 1995. In this time, the potential risk of SLR exposure might have become more tangible for residents in the county (Pinellas County 2015). In addition, the first implementation of Florida Building Code in 2000 may have also made potential

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Subprime Mortgage Crisis

Major Flooding Events

Fig. 1 Pinellas County price index by elevation 1972–2019. Source FGDL, 2019; FGDL, 2005; Pinellas County Property Appraisers, 2019

flood risk more salient to homebuyers. As the most appealing properties across the county, ocean-view properties located along the coastline have always been pursued by the homebuyers. And these properties are typically located at an elevation of 0–1 m. However, as the homebuyers’ concern about flood risk increases, properties at 0 m can be less preferred despite their advantageous ocean view. Instead, properties at an elevation of 1 m (as Fig. 2 shows) may become the best choice for homebuyers who want ocean views and are concerned about the flood risk. This may be the major reason that homebuyers have begun to prefer properties at 1 m.

5.1.2

Findings at Municipality Scale

Figure 3 demonstrates the price index growth of two primary property cohorts in property dataset: unincorporated area (70,000 properties, 28% of all samples), St. Petersburg (78,000 properties, 31% of all samples). The price index growth in unincorporated areas is consistent with the overall trend of Pinellas County, while the properties at 1 m saw a stronger momentum in growth than the county’s average rate, a multiple of 27.36 since 1972. This multiple is 63% higher than the 0-m cohort and 40% higher than the 2-m cohort, indicating the majority of housing demand in this area. Besides, with the ongoing population growth of Pinellas County and increasing suburbanization, many new single-family homes are built in unincorporated areas.

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Fig. 2 Elevations of Pinellas County. Source FGDL, 2019; FGDL, 2005; Pinellas County Property Appraisers, 2019

These new constructions tend to have better building quality, which may push up the overall housing price in unincorporated areas. In contrast, the difference in price appreciation according to elevation is found to be more limited in St. Petersburg. The appreciation rates of the 1-m cohort and 2-m cohort are observed to be very similar throughout the timeframe. By 2019, the price index of these two cohorts is recorded at 16.96 and 17.73, which is 15 and 3% lower than the county’s average rate, respectively. The stability in property appreciation may be related to the maturity of the property market—as the city development dates

Fig. 3 Price index in unincorporated area and St. Petersburg. Source FGDL, 2019; FGDL, 2005; Pinellas County Property Appraisers, 2019

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from the nineteenth century-where the urban land has already been mostly developed, and the population profile tends to be more stable. Further, these low-elevation areas (elevation below 2 m) have many older buildings that were initially built before 1974. The flood insurance of these buildings will be considerably higher if they are not qualified as post-FIRM properties through substantial renovation (FEMA 2019). The higher living cost in these areas may be another factor limiting appreciation.

5.2 Hedonic Pricing Modeling As Fig. 4 shows, among all the 207 valid sections investigated, 55 sections (n = 32,270, 25% of all samples investigated) are found to have a positive coefficient of elevation and 137 sections (n = 88,346, 68% of all samples investigated) are found to have a negative coefficient of elevation. There are also 15 sections (n = 7,109, 5% of all samples investigated) found to have a zero coefficient of elevation, meaning elevation generally does not result in the change in property value. Fig. 4 Coefficient of elevation. Source FGDL, 2019; Pinellas County Property Appraiser, 2019

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Fig. 5 Coefficient of elevation at different elevation Cohorts. Source FGDL, 2019; Pinellas County Property Appraiser, 2019

In order to further capture the pattern of the coefficient of elevation distribution at different elevations, samples are split into four elevation cohorts consisting of all properties between two elevation increments. The result is shown in Fig. 5. Among all the properties located at 0–1 m 30 sections (n = 12,467, 20% of all samples investigated) are found to have a positive coefficient and 78 sections (n = 37,519, 61% of all samples investigated) are found to have a negative coefficient, out of 124 valid sections. In the range of 1–2 m, positive correlations and negative correlations are counted 42 (n = 17,001, 28% of all samples investigated) and 73 (n = 31,770, 52% of all samples investigated), respectively, out of 138 valid sections. In the range of 2–3 m, positive correlations and negative correlations are counted 35 (n = 13,246, 28% of all samples investigated) and 73 (n = 28,517, 61% of all samples investigated), respectively, out of 110 valid sections. In the range of 3–4 m, positive correlations and negative correlations are counted 42 (n = 18,641, 33% of all samples investigated) and 65 (n = 29,108, 52% of all samples investigated), respectively, out of 123 valid sections. The portion of sections with positive coefficients is thus found to increase as elevation increases, suggesting that the increment in elevation is becoming more likely to increase the property value as elevation increases in a very localized context. Such a phenomenon may result from the fact that many high-value houses are located

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Fig. 6 Geographical distribution of coefficient of elevation by section at different elevation cohorts. Source FGDL, 2019; Pinellas County Property Appraiser, 2019

exactly at the shoreline, where the elevation is typically 0–1 m. And these oceanview houses are often much more expensive than nearby houses at similar or higher grounds, which may result in the negative coefficient of elevation. When observing elevation cohort increases at section scale, the effects of such high-value coastal houses is more mitigated and more sections can see a positive coefficient. Figure 6 compares the geographical distribution of elevation’s coefficients at different elevation cohorts. Sections with positive coefficients are more commonly seen in the inner land than the coastal areas, which is consistent with the assumption that high-value coastal houses contribute to the negative coefficient of the sections they located in.

6 Summary of Findings This study uses two primary methods to test the two hypotheses. The first hypothesis is that the property appreciations over time are positively related with elevations. This hypothesis is tested by constructing price indices at different elevations from 1972 to 2019. The result suggests that the hypothesis applies to the properties no higher than 1 m, properties at 1 m have the fastest appreciation rate among all properties investigated. Such phenomenon may indicate that the access to the water is still the strongest selling point of single-family houses to make extra premium. On the other hand, concerns about SLR should also be raising given the appreciations at 0 m lags the group although they have the best water access. The second hypothesis is that higher elevations contribute to higher sales prices of properties. This hypothesis is tested by conducting hedonic regressions on property transactions at different elevations from 1995 to 2019. The result suggests that the hypothesis applies to around a quarter of the areas investigated. This indicates that elevation has been a factor to consider for some homebuyers in the county, although these are not the majority of homebuyers. The findings of the two parts generally suggest that people’s concern about SLR may be increasing in Pinellas County, FL. However, such concern has been limited to a minority of the homeowners, given

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only a limited portion of homebuyers’ decisions have been affected by propertie’s elevations. The findings of the two separate methods generally indicate that the SLR may become perceivable, while the current impact of SLR is not significant enough for most homebuyers to make corresponding decisions. In other words, coastal residents in the county are gradually becoming aware of SLR but they choose not to make proactive planning decisions to relocate. Such phenomenon may be related to the coastal resident’s psychological resistance to make significant changes as long as they do not think threat of SLR will happen within their normal planning horizons (Akerlof et al. 2017; Spence et al. 2012).

7 Conclusion Despite the assumption that the accelerating SLR may force people to make decisions to adjust the risk of maintaining the status quo, most homebuyers in Pinellas County seems to be still willing to pay extra cost to live in the coastal area. This study investigated SLR’s perceivable impact on people’s economic activities by analyzing the property’s long-term appreciation and sales value over time caused by different levels of elevation and potential flood risk. The results suggest that SLR’s impact on property market has partially begun to occur in Pinellas County, while the impact is relatively limited so far. The findings of the study may serve as evidence of SLR’s current impact on the property market in Pinellas County, based on which the planning response to SLR can be built up. Besides, as this study compares the different extent of SLR’s impact in different regions, municipality governments can use this study as a reference to evaluate the geographical vulnerability of their cities in order to develop a more localized flood mitigation strategy (e.g. pay extra attention to the sections where elevation shows a negative coefficient). Further, the perspective of property market can be an alternative reference for urban planning as it reflects the resident’s actual economical decisions, and such decisions tend to be relatively reasonable. Future studies may be tasked with further understanding the extent of perceived threat from SLR among local homebuyers in Pinellas County. This may require future researchers to understand the manners in which local homebuyers have experienced or anticipated the impact of SLR, as well as how these perceived threats impact their decision makings. For instance, it may be meaningful to explore whether there is any specific methods (e.g. sea wall construction, drainage improvement, etc.) for coastal homebuyers to mitigate the flood risk, or whether there are some other reasons for them to stay in the low-lying areas (e.g. education, medication, etc.). These diagnostics should help explore the key points of planning response to the future flood risk in Pinellas County.

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Exploring the Role of NGOs in Rural Revitalization of Jiang Village Junyan Zhou and Ying Chang

Abstract As an effective force participating in rural revitalization in addition to the government and villagers, the role of non-governmental organizations (i.e. NGOs) in rural revitalization has also been paid more and more attention. Against the background, this study aims to investigate a case study of the engagement of NGO in rural revitalization in the city of Suzhou. The interview method is employed for data collection (n = 10), and the data are analyzed using the thematic analysis method and SWOT analysis. It is found that Jiang Village NGOs play significant roles in the village environment, village culture, social care, industrial revitalization, organizational cultivation, and democratic deliberation. They cooperate closely with the government and villagers. However, the NGO’s autonomy in rural revitalization was circumscribed, and the scope of contribution was limited. With these findings, this paper contributes to the literature on NGOs’ role in rural revitalization by analysing the current situation and difficulties that Jiang Village’s NGOs are faced with. Keywords Non-governmental organizations · Rural revitalization · Jiang village

1 Introduction According to Li and Dong (2018), Chinese non-governmental organisations (NGOs) are autonomous social organisations founded by individuals independent of corporations and the government, with a common non-profit value aim. Rural NGOs are an influential contributor to rural revitalization as a third-party force in addition to villagers and the government. Recent evidence has demonstrated the critical role of NGOs in participating in economic, cultural, social, and other types of public services (Aldashev and Navarra 2018; Asfaw et al. 2017; Esposito and Antonucci 2022). J. Zhou Warwick Manufacturing Group, University of Warwick, Coventry, UK Y. Chang Department of Urban Planning and Design, Design School, Xi’an Jiaotong-Liverpool University, 111 Ren’an Road, Suzhou, P. R. of China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_37

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However, there is little research on the ways and dilemmas of NGOs’ engagement in rural revitalization. Therefore, this paper attempts to answer the research question of the main means, effectiveness, and dilemmas of NGO engaging in rural revitalization through literature analysis, semi-structured interviews, and SWOT analysis, taking Kaixiangong Village (Jiang Village1 for the rest of the paper) as an example. The study provides important insights into the effectiveness and dilemmas of NGO engagement in rural revitalization.

2 Rural Revitalization and Non-governmental Organisations in Jiang Village 2.1 Rural Revitalization Since the reform and opening up in 1978, China’s urban–rural regional system has undergone significant changes, including economic growth, rural governance, land use change, land system reform, and social and cultural transformation (Liu et al. 2020). When the development of urban land resources is limited, the countryside has vast development potential. But the countryside is faced with challenges such as vacant land and population loss. Therefore, to implement rural revitalization is vital (Chen et al. 2021). China proposed a rural revitalization strategy in 2018 (Wong et al. 2020). Rural revitalization includes revitalization of rural industries, revitalization of rural talents, revitalization of rural culture, revitalization of rural ecology, and revitalization of rural organizations. Rural development in many countries has gone through three stages: infrastructure construction, environmental governance, and development of rural landscape, culture, and tourism. Overall, rural China is currently in the middle of the second stage, the middle of the environmental governance stage. The government has become increasingly aware of the importance of rural areas. It has launched many policies to encourage rural revitalization and put forward indicators for industrial prosperity, ecological livability, rural civilization, effective governance, and better life (Han 2019).

2.2 Non-governmental Organizations in Rural Revitalization Rural NGOs are the products of autonomous rural demands and collective interests, which are essential to the rural social structure (Wang and Liu 2021). Wang (2020) emphasized the significance of NGOs in rural revitalization, such as pinpointing 1

Kaixiangong is the original name. It is the case study village of famous sociologist Xiaotong Fei’s early work on rural society. Xiaotong Fei used Jiang village in his academic writing. Then Jiang village became the second name of Kaixiangong Village and became a brand and IP for rural revitalization of Wujiang district.

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villagers’ cultural needs, filling the gaps between the government and the market, and mobilizing people to participate in rural revitalization. Although NGOs have a significant role in rural revitalization, the development of NGOs in China is significantly constrained by the short history of their development, as well as the inadequate and imperfect social security system and legal regulations in China. Some scholars reviewed the problems Chinese NGOs face in rural revitalization, summarising them as difficulties in resource integration, the complicated model of cooperation, lack of independence, openness and transparency (Lu 2007; Hasmath and Hsu 2020). Li and Zhou (2020) studied Chinese NGOs’ dilemmas in rural revitalization from the social ethics perspective. They argued that NGOs’ ethics, which was originated in the West, was essentially a local knowledge constructed through multiple social realities and encountered multiple dilemmas in governance philosophy, administrative control, interpersonal structure, and semantic representation in entering China’s specific cultural and social environment. In addition, although the number of studies on NGOs’ engagement in rural revitalization has gradually increased, current research on NGOs in China is still focused on governance and related legal issues. The number of studies on NGOs’ engagement in rural revitalization is still relatively small, and most of these studies are theoretical and lack of practical case studies. Considering that the number of NGOs in rural China is currently small and does not meet the data sample for quantitative research, most researchers adopt a qualitative research method to study the role of NGOs. In addition, rural revitalization mainly involves the government, NGOs, and villagers, so most studies interviewed these three parties.

2.3 Jiang Village Jiang Village is located in the west of Wujiang District, Suzhou City, Jiangsu Province, China (Fig. 1). It has five natural villages under its administration. The terrain is flat with a total area of 4.5 km2 the water area accounts for 21.6% of the total area. Economically, the total output value of Jiang Village is relatively high, and the average income per capita was 45,000 yuan (equivalent to 6270 US dollars) in 2022, which is a little bit high among all villages. The population of Kaixiangong Village in 2022 is about 3000. The village has sufficient infrastructure, including convenience stores and an auditorium. Overall, Jiang Village has made achievements in rural revitalization, and is selected as a national model village for rural governance. Currently, the NGOs in Jiang Village are Blue Sky Environmental Protection, Alaai Service Agency and Qinghezhixian. The staff members of these NGOs are the same. Considering that Jiang Village is a typical village in China, and is an example of NGOs’ engagement in rural revitalization, this paper chooses Jiang Village as the case study of study.

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Fig. 1 Location of Jiang village. (Source from Jiang Village Records, accessed at 11th, Sep, 2022)

3 Methods Using in Investigation 3.1 Chosen Method This paper adopts the mixed method of document analysis, semi-structured interviews, and SWOT analysis. The document analysis method is applied to the background, significance, research status, main aspects, and goals of the topic selection. The semi-structured interview method is used to get an in-depth understanding of the operation mechanism, current situation, and main problems of NGOs through interviews with villagers, the government, and local NGOs. Finally, through SWOT analysis, the document analysis results, and the data obtained from the interviews, we sort out the opportunities and challenges Jiang Village’s NGOs face.

3.2 Chosen Reasons There are few studies on the engagement of NGOs in rural revitalization, so most researchers use qualitative research methods to study the role of NGOs. Qualitative research is the approach to unpack the meaning people ascribe to activities, situations, events or artefacts and to build thick descriptions of social contexts, relationships, connections, and tension (Cho and Trent 2014). A disadvantage of quantitative research is a significant demand for samples. There are few examples of NGOs participating in rural revitalization, and data collection is complex. One of the advantages of qualitative research is that it can build a new theory when a prior theory is absent. This paper mainly adopts the semi-structured interview method in qualitative research to determine the role and difficulties NGOs face in rural revitalization. Semi-structured interviews refer to interviews with a pre-determined list of topics and some key questions that may be related to those topics to guide the

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Table 1 Sample details (drawn by the author, 11th, Sep, 2022) Time

Place

Affiliation and number of respondents

2022.8.29 Jiang Government Workers (4) Village Three males (M) and one female (F). Ages range from 20 to 50 years Village Committee Office

Details of respondent Z (M): Member of the Village Committee of Jiang Village S (F): Member of Jiang Village Special Class H (F): Member of Jiang Village Special Class A (M): Secretary

2022.8.25 Alaai service agency studio

Villagers (3) Three females (F). Ages range from 40 to 60 years

Alaai service agency studio

NGO Workers (3) Three females (F). Ages range from 20 to 50 years

L (F): ’Beautiful Garden’ Head of Household; Volunteer Q (F): Volunteer G (F): Volunteer W (F): Secretary General of NGO K (F): NGO Worker X (F): NGO Worker

conduct of each interview. Semi-structured interviews are flexible in topics and have the advantage of being structured and consistent.

3.3 Sampling in the Semi-structure Interview According to the literature review, the engagement of NGOs in rural revitalization involves three stakeholders: NGOs, villagers, and the government. Therefore, the sample is divided into three groups: NGOs’ workers, villagers, and government workers. The principles for selecting the objects are as follows: the number of each group ranges from three to five, the sample has directly participated in the NGO’s rural revitalization-related activities, has a direct connection with the work of the NGOs, and is representative. The research team first interviewed local NGOs, learned the contact information of government workers and village representatives through NGOs, and then conducted one-on-one interviews (Table 1).

3.4 Process of the Semi-structure Interview Each participant will first inform the research purpose, content, research methods and other relevant information and sign the informed consent form. Then they will

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be asked about the current situation of rural revitalization in Jiang Village, the understanding of NGOs’ activities, the difficulties NGOs face, and advice.

3.5 Semi-structure Interview Results Analysis This paper hopes to study the current situation of NGOs’ engagement in rural revitalization in Jiang Village and conduct a SWOT analysis of NGOs’ engagement in rural revitalization. The data analysis method mainly adopts thematic analysis. The steps of topic analysis are as follows: 1. Familiarize with the data. 2. Initially encode the data. 3. Find themes. 4. Reviewing themes. 5. Defining and naming themes. 6. Producing the report. After the analysis, the data is divided into three parts: the current situation of the NGO’s engagement in rural revitalization in Jiang village, the relationship between NGOs and the government and villagers in Jiang village, and SWOT analysis.

4 Effectiveness and Dilemmas of NGOS in Rural Revitalization in Jiang Village 4.1 Current Situation of NGOs’ Participation The local NGOs in Jiang Village are mainly Blue Sky Environmental Protection, Alaai Service Agency and Qinghezhixian. Alaai member Ms. K said ‘Alaai Service Agency was mainly responsible for social care and cultural promotion activities in Jiang Village, while Lantian Environmental Protection was mainly concerned with environmental protection’. Government officer Mr. Z said ‘NGOs had really played a big role in the rural revitalization in Jiang Village.’ Villagers Li, Qiu, and Gu all mentioned different activities NGOs done in Jiang Village. Li said that ‘The Blue Sky Environmental Protection Volunteer Association organised activities such as waste classification training and visits to environmental protection bases, and waste classification was driven by courtyard renovation through waste classification group assessment.’ Both the villagers and the government are appreciative of the contribution of the NGOs in Jiang Village. To conclude, local NGOs participate in rural revitalization in various activities in environmental governance, rural culture, social care, economic revitalization, talent development and democratic consultation (Table 2). ‘Generally speaking, the government and villagers of Jiang Village have a clear division of labor, cooperate with each other and get along well’, said Ms. X, member of local NGOs. The Jiang Village Committee is mainly responsible for the overall infrastructure construction of the village. At the same time, local NGOs carry out embellishment work based on the Village Committee, such as project publicity and

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Table 2 Types of services provided by NGO in Kaixuangong Village (drawn by the author, 11th, Sep, 2022) Aspects

Methods

Photos

Environmental governance • Garbage classification training • Visits to environmental protection bases • Assessment of garbage classification groups • Household assessment and transformation guidance • Beautiful yard Rural Culture

• Publicity activities for the party constitution and culture • Traditional festival celebration Jiang village Wawa summer camp

Social Care

• Home visits • Convenience activities (Knife Sharpening, Hairdressing, Sewing…)

Economic Revitalization

• Homestay service platform • Skill training (Home storage, Cleaning, Courtyard construction, Cooking…)

Talent Development

• Cultivate volunteers • Jiang village girls project

Democratic Consultation

• Democratic consultation platform • Tap into common needs • Foster social responsibility

beautiful courtyards. The Jiang Village Special Class is responsible for the future planning of Jiang Village. ‘The projects of NGOs are mainly carried out and funded by the Wujiang District Women’s Federation’, said Mr. A, government officer. Accordingly, NGOs conduct financial disclosure once a year. During the project, it obtained

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the support of the Jiang Village Committee and the district and town women’s federations. It then completed the entrusted service work set by the government department. At the same time, district and town women’s federations will regularly follow up on NGOs’ projects and suggest improvement suggestions. Rural NGOs often participate in the communication between the government and villagers through intermediaries. NGOs also have different responsibilities at different times. When the policy orientation is inconsistent with the current needs of the people, NGOs will take on the role of advocates, explaining the purpose of the policy by holding large-scale activities and influencing the people’s thinking. When there are differences of opinion when the project is implemented, NGOs can hold consultation and mobilization meetings, build a communication platform, and act as the relationship coordinator between the two. When the policy orientation and the villagers’ needs are agreed upon, NGOs undertake the work of service providers, publicize the knowledge points of policies or projects through lectures, and provide timely assistance to provide counselling to the villagers. The most crucial role of NGOs is that of enablers, that is, to help villagers have the ability to solve their problems, assist in deployment work, use villagers’ influence to expand the influence of projects, and mobilize the driving force of villagers through job competition.

4.2 SWOT Analysis 4.2.1

Strengths

NGOs in Jiang Village hold various activities. NGOs of Jiang Village participated in the rural construction work, carried out various activities, and had a wide range of influences, which provided a suitable environment for rural revitalization. In terms of the village environment, Jiang Village can carry out projects such as beautiful courtyards and garbage classification to improve the village environment and improve the quality of human settlements. Economically, NGOs in Jiang Village have carried out activities such as homestay skills training and cultivator training to improve the employability of the villagers and to publicize local specialty agricultural products, such as smoked bean tea, to boost the village’s economic development. In terms of ideology, the NGOs of Jiang Village guide the villagers to change the concept of relying solely on the government by holding speeches and other activities, cultivating the spirit of ownership, and actively participating in rural revitalization. In terms of culture, the NGOs of Jiang Village actively explore the culture of Jiang Village and strengthen cultural propaganda. In terms of society, Jiang Village NGOs care for the elderly and children in Jiang Village and carry out convenient activities, education classes and other activities to effectively protect and improve people’s livelihood. NGOs get the government’s strong support. The Women’s Federation supports the work of the NGOs in Jiang Village. The village committee is assisted in the process, which can assist government departments in managing social work in rural areas more effectively. Since there is no need to expand the staffing, this collaboration

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saves workforce and management costs. In addition, NGOs, village committees, and special classes in Jiang Village have a clear division of labour and cooperation, and overlapping responsibilities are not problematic. The NGOs of Jiang Village can effectively communicate the villagers’ demands and act as a bridge between the villagers and the government. In the process of rural revitalization, NGOs of Jiang Village often participate in the communication activities between the government and the villagers using an intermediary, conveying the government’s thoughts on rural revitalization to the villagers. They can also use flexible means to promote the implementation of rural policies. At the same time, NGOs collect the villagers’ wishes, submit them to the government regularly, build a negotiation platform, and realize multi-party barrier-free communication. While the government provides the primary support, Jiang Village NGOs has cooperated with other organizations. In the activities of Jiang Village’s Kids, Jiang Village has cooperated with educational and training institutions, which has effectively saved funds. In addition, Jiang Village NGOs also cooperated with several colleges and universities. This multi-party cooperation method enables Jiang Village NGOs to integrate resources efficiently and effectively to promote rural revitalization.

4.2.2

Weaknesses

The scope of engagement in rural revitalization is limited. The main body of Jiang Village’s rural revitalization is still the government. Although Jiang Village has carried out many projects in the village environment and cultural publicity, its engagement in poverty alleviation and development, social welfare, and infrastructure construction is insufficient. The reason is mainly due to the shortage of talents and funds in Jiang Village. At present, the development speed of NGOs in Jiang Village is uneven. Blue Sky Environmental Protection and Alaai Service Agency are relatively mature. However, Qinghezhixian has just been established and has not yet launched activities. The NGOs in Jiang Village has only two permanent staff and one mobile staff. The problem of staff shortage is severe. It often occurs that one person undertakes multiple jobs. In addition, the shortage of funds in Jiang Village is a significant constraint to their activities. At present, the source of funds for Jiang Village’s NGOs mainly comes from government grants, and a small part of it comes from corporate donations. Considering legal issues, it does not accept individual donations. This has led to a shortage of funds for the NGOs in Jiang Village, so the scope of activities to be carried out is limited. Participation in rural revitalization is not very autonomous. Most NGOs’ projects in Jiang Village rely on government support and are highly dependent on the government. Therefore, the activities carried out by NGOs in Jiang Village are mostly an extension of the government’s tasks. In addition, the operation process of the NGOs in Jiang Village is supervised by the District Women’s Federation. At the same time, it is also subject to the evaluation of a third-party monitoring agency, which leads to the low autonomy of the NGOs in Jiang Village to participate in rural revitalization.

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Table 3 Concluded SWOT analysis (drawn by the author, 11th, Sep, 2022) Strengths • Various activities • Government support • Good relationship with the local villagers • Cooperation with other organizations

Weaknesses • Limited scope • Dependent and not autonomous

Opportunities • Rural revitalization strategy

Threats • Vague laws and regulations

4.2.3

Opportunities

The proposal of the rural revitalization strategy shows that the government attaches great importance to rural revitalization. As a third-party force for rural revitalization, NGOs will receive more policy support in the future. In addition, with the improvement of government support and the gradual maturity of NGO operating mechanisms, there will be more hope for NGOs to participate in industrial revitalization.

4.2.4

Threats

Laws and regulations needs to be more supportive Although NGOs have participated in the process of rural revitalization, the current legislation on NGOs’ engagement in rural construction is still incomplete, and the basis of laws and regulations is unclear. In addition, the government still has too many invisible interference factors for the NGOs of Jiang Village at this stage (Table 3).

5 Conclusion and Limitations Taking Jiang village as an example, this research investigated the NGO’s engagement in rural revitalization and conducted a SWOT analysis. It is found that Jiang Village NGOs have a significant impact on the village environment, village culture, social care, industrial revitalization, organizational cultivation and democratic deliberation. They cooperate closely with the government and villagers. In addition, the engagement of NGOs in Jiang Village in rural revitalization also faces some problems. The autonomy level of engagement in rural revitalization is not high, the scope of engagement is limited, and the legislation on NGOs’ engagement in rural revitalization is not yet mature. With the further implementation of the rural revitalization strategy, it is hopeful that Jiang Village will participate in more aspects of rural revitalization with greater extent of autonomy. In terms of theoretical contribution, this study enriches the research on NGOs’ engagement in the rural revitalization and provides a basis for future research.

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References Aldashev G, Navarra C (2018) Development NGOs: basic facts. Ann. Public Cooper. Econ. 89(1):125–155. https://doi.org/10.1111/apce.12188 Asfaw T, Botes V, Mengesha L (2017) The role of NGOs in corporate environmental responsibility practice: evidence from Ethiopia. Int J Corp Soc Responsib 2(1):1–9. https://doi.org/10.1186/ s40991-017-0013-0 Chen M et al (2021) The integration of new-type urbanization and rural revitalization strategies in China: origin, reality and future trends. Land 10(2):207. https://doi.org/10.3390/land10020207 Cho J, Trent A (2014) Evaluating qualitative research. The Oxford handbook of qualitative research, pp 676–696. https://doi.org/10.1093/oxfordhb/9780199811755.013.012 Esposito P, Antonucci G (2022) NGOs, corporate social responsibility and sustainable development trajectories in a new reformative spectrum: “New wine in old bottles or old wine in new bottles?” Corp Soc Responsib Environ Manag 29(3):609–619. https://doi.org/10.1002/csr.2223 Han J (2019) Prioritizing agricultural, rural development and implementing the rural revitalization strategy. China Agric Econ Rev 12(1):14–19. https://doi.org/10.1108/caer-02-2019-0026 Hasmath R, Hsu JYJ (2020) A Community of Practice for Chinese NGOs. J Chin Polit Sci 25(4):575–589. https://doi.org/10.1007/s11366-020-09687-3 Li JH, Zhou Q (2020) 论我国非政府组织伦理的地方性建构’, 湖北大学学报(哲学社会科学版) ‘An argument on the local construction of NGO ethics in China. J Hubei Univ (Philos Soc Sci) 47(6):10–17 Li X, Dong Q (2018) Chinese NGOs are “going out”: history, scale, characteristics, outcomes, and barriers. Nonprofit Policy Forum 9(1). https://doi.org/10.1515/npf-2017-0038 Liu Y, Zang Y, Yang Y (2020) China’s rural revitalization and development: theory, technology and management. J Geog Sci 30(12):1923–1942. https://doi.org/10.1007/s11442-020-1819-3 Lu YY (2007) The autonomy of Chinese NGOs: a new perspective. China Int J 5(2):173–203. https://doi.org/10.1142/s021974720700012x Wang RY, Liu Q (2021) Probing NGO–community interactions through village cadres and principal– agent relationships: local effects on the operation of NGO projects in rural China. J Contemp China 31(135):445–458. https://doi.org/10.1080/10670564.2021.1966904 Wang Y (2020) ‘非政府组织参与环境治理的困境与出路 (Difficulties and solutions of nongovernmental organizations participating in environmental governance). 宿州教育学院学报 (J Suzhou Educ Inst) 23(3):8–11 Wong SW, Tang B, Liu J (2020) Rethinking China’s rural revitalization from a historical perspective. J Urban Hist 48(3):565–577. https://doi.org/10.1177/0096144220952091

Greening the Public Realm: Incorporating Bio-Diversity into City Spaces Y. Q. Xu, W. Dai, and T. Heath

Abstract With the transformation of urban beautification from rapid growth to highquality urbanization and ecology, biodiversity has increasingly become an important indicator for assessing urban living environment. In recent years, with the concept of “green transformation” of cities, people begin to attach importance to incorporating biodiversity into the greening of urban public spaces, especially through planning and design strategies. However, many urban public space design strategies abandon the original idea of “harmonious coexistence” between human and nature, only become one-sided pursuit of benefits in scene construction emphasizing visual effects. In order to promote the green development of urban space, the purpose of this paper is to explore the potential solutions to the deterioration of urban public space environment and problems caused by unreasonable design, and to put forward a variety of new urban public space planning and design strategies which can be used as useful tools for planner based on the unique perspective of biodiversity. Keywords Public realm · Bio-diversity · Urban public space

1 Introduction Urban open space refers to the space between building entities in a city or urban group and is an open place for urban residents to conduct public communication and various activities. Urban biodiversity is the ecological complex formed by organisms (animals, plants, microorganisms) and the environment and the sum of various related ecological processes in the cities (Tian et al. 2021). The Global Biodiversity Assessment issued by the United Nations Environment Programme defines urban Y. Q. Xu Xi’an Jiaotong-Liverpool University, Suzhou, China W. Dai Urban and Environmental Studies University Research Centre in XJTLU, Suzhou, China T. Heath Department of Architecture and Built Environment in University of Nottingham, Nottingham, UK © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_38

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open space as a special carrier of biodiversity, reflecting the complex relationships between life, habitats, ecological environment and human beings in cities. Therefore, urban biodiversity is significant for the sustainability of urban space, but unfortunately, Curtis (2011) warned that Urban greening development faces many problems due to the lack of biodiversity in urban planning and design. The public green space in a city is closely related to everyone’s life. Urban greening not only affects the appearance of the whole city, but also beautifies the urban environment, purifies the urban ecology and expands the urban biodiversity (Mata et al. 2020). With the development of social economy and the modernization of cities, the requirements for urban design will become higher and higher. More and more urban designers choose to optimize the public domain as much as possible in the process of urban space planning and design so as to promote a virtuous cycle of endogenous development of urban space (Webb et al., 2017). At the same time, with the government attaching great importance to improving people’s awareness of natural protection or natural awareness, concepts such as green environment have been gradually melt into the thinking of planning designers (Pickett et al. 2017). In order to better integrate the city and nature, art and life, the integration of biodiversity into urban space has become the current trend of greening public space art (Benton-Short et al. 2019). This paper will comprehensively explore the reasons for unreasonable urban space design, and then objectively and fairly propose and analyze four innovative design methods derived from core urban space planning strategies based on land protection and animal and plant diversity.

2 The Challenges of Greening in Urban Public Areas Due to the destruction of more and more urban ecology in the world, the comfort of some urban public areas has declined significantly. According to a survey of citizen’s satisfaction with the living city by Childers (2019), many urban residents are dissatisfied with the greening and environmental protection of the city. A report was written by the Swiss Representative Office of the world natural Committee on the framework study was released, which showed that the main reason for resident’s dissatisfaction with the urban environment is that the greening level in urban public areas is not up to their expect (Pierce et al. 2020). Among them, land abuse in urban planning and unreasonable urban design are the main problems that destroy public space greening and hinder urban sustainable development.

2.1 Land Abuse and Unreasonable Urban Design Under the background of global warming and urban heat island effect (Riechers et al. 2017), one of the major man-made reasons is land abuse in urban planning and unreasonable urban design, with the development of global urbanization.

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On the one hand, natural floors covered by vegetation and crops have been replaced by concrete, stone and brick buildings in many cities, while public spaces (e.g. squares) are paved with asphalt, cement, ceramics and stone. They have low reflectivity, high heat capacity and large solar energy absorption. In a limited space, unlimited heat accumulation results in the loss of part of water resources. Some plants, such as conifers and broad-leaved plants, that are good for greening the city but suitable for growing in cold areas, do not grow normally in high temperatures and droughts (Hanspach et al. 2020). Therefore, the greening level of these urban spaces has a retrograde trend due to land abuse in urban planning. On the other hand, in urban public space design, not only people’s material desires, but also environmental factors should be fully considered based on land protection and animal and plant diversity. Because if the design of urban space only meets people’s behavioral and psychological needs, then this egoistic design tends to run counter to the protection of urban ecology (Kyriakodis and Santamouris 2018). At present, the improvement of biodiversity and land protection in urban public space design is not very in-depth in China.

2.1.1

The Overall Layout of Public Space is not Uniform

A charming and vibrant city has more high-quality, attractive general layout of public space, enabling people to enjoy a wide range of activities. However, due to the lack of clear management requirements in the process of design and construction of urban public space, the current overall planning layout of urban public space lacks uniformity, and the lack of unified management and systematic control and guidance from the whole to the part of urban public space, resulting in the situation that the actual use value of urban public space is not high and the actual use is extremely inconvenient (Cao 2021).

2.1.2

Lack of Green Concepts in Public Space Design

Urban space is constructed to provide residents with a healthier living environment, not to destroy the ecological environment. At present, many cities have problems in public space design, such as destroying grass-roots plants, removing foundations, changing river bank tracks, etc. Even many city designers have designed and constructed many landscape projects which have no practical value for urban greening environment in order to please leaders and invest a lot of unnecessary funds, which seriously destroys urban ecological environment and seriously wastes social resources.

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Lack of Humanization in Public Space Design

The original purpose of public space design is to provide more places for residents to live, work and leisure, so corresponding equipment and functional buildings must be configured. However, at present, many cities lack of humanized public space design, such as special access for the disabled, night lighting, public toilets, kiosks, water fountains, etc., which makes the utilization of public space low and practical and finally becomes a vase building. In order to change the achievements of space design into professional springboards to upgrade grade grade grade, some designers blindly widen streets, randomly expand buildings, even occupy and destroy existing urban public space, some cities neglect the practical value and practical significance of space and become a springboards, which seriously affects the city image and long-term development (Yin 2021). In order to avoid the loss of human nature, urban designers should understand the relevant data, geography and culture of the city in which a project is designed, and use their wisdom and common sense to optimize public space in a human-centered manner. Physical and non-physical factors are equally important to the success of public space design. Site creation is not only about creating an individual or a physical space, but also about the responsibility of each factor, whether related to sound, light, texture, memory or narration, that may contribute or destroy the humanization of public space from the perspective of biodiversity. City designers need to understand and anticipate how these spaces will develop, connect, lead and provide pleasure.

2.1.4

The Form of Urban Public Space is Single and Lacks Personality

There are a lot of lack of personalized designs in the design and construction of public space in many cities. Some designers intentionally imitate other famous buildings or landmarks. Blind pursuit of large, wide and high leads to the lack of personality and characteristics of public space buildings. Without vitality and living atmosphere, they can neither green the space environment nor meet people’s actual needs. The uniqueness and individuality of public space also seriously affect the image of the city and the original cultural characteristics, resulting in silence and embarrassment of the urban space. The researchers believe that the definition of each location determines the presentation and connectivity of the overall regional style. Each pavement, each square, and each transition point can be combined to form a larger, greener and more ecological narrative logic, describing a future city in which all living beings live in harmony, and sustainable development.

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Lack of Unified Planning and Management Mechanism in Urban Design

Biodiversity conservation of urban public space is an important link in its construction and development of urban public space, which requires unified coordination of urban managers and designers to jointly seek the balanced relationship between urban public space and ecology, activate the unified management mechanism to make the development of urban public space more balanced, healthy and coordinated so as to build more healthy and sustainable urban public space. However, apart from a few countries or regions, apart from urban streets, there is no uniform and clear technical means for design and management of other types of urban space, such as libraries, parks, stadiums, squares, business districts, etc. At present, the design and management of some cities lag behind, which is not conducive to the greening supervision of urban public space. Science and technology help improve and innovate the technical means of urban public space design. Before the beginning of the master plan, designers and researchers need to expand their research to include which areas can become public spaces, which organisms are suitable for planting or cultivating, the images of future space users, and which space usage rates are high.

3 The Solutions of Urban Space Afforest Issues by Integrating Biodiversity into Urban Space 3.1 Planning and Designing Urban Public Space Based on Land Guarantee and Diversity of Animals and Plants As a city designer, greening, beautifying and protecting the city are the original intention of city design. In order to make the public space in which residents live greener and more comfortable, it is the responsibility and obligation of every designer to pay attention to the environmental protection of space. Scott et al. (2016) pointed out that the essence of sustainability of urban design is the protection of urban biodiversity and original ecological water and soil, and applied this green design concept to design practice, as designers are both pioneers and guards in the process of correcting urban biodiversity. Weber and his team (2017) found that urban space planning and design decisions can only be made on the basis of urban biodiversity and land conservation, and that designers can rationalize the start of green space in urban construction and change the lifeblood of a city from its source. Urban greening is an important part of urban design, and the greening degree of space can better reflect the urban biodiversity. The protection rate of urban greening and ecological environment should be the focus of urban public space design and the main problems faced and solved in the early stage of urban design. When planning and designing urban public space, it is suggested that the protection of vegetation and

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original land ecological environment be put in the first place to avoid disturbance and destruction of urban public space construction to ecologically sensitive areas (Sun 2018). The design methods based on land conservation and biodiversity can be roughly summarized into the following four categories.

3.1.1

Optimizing Urban Space Plant Structure and Improving Urban Greening Quality

The optimization of its structure mainly focuses on the vertical structure related to plant community and the time structure relative to season (Sun 2018). Some urban public space green landscape covers a relatively wide area with a wide variety of plant species, but its vertical structure is too simple, the level and structure of space plant landscape are not strong, turf is in the majority, and the grass-shrub two-layer structure is in the majority. Based on this overall development status, the designer should continuously enrich the plant landscape of urban green space in combination with the actual development situation and relying on the principle of plant ecological classification (Liu 2020). On the one hand, the level of urban public space landscape structure should be continuously enriched, and fully consider the four-season change characteristics of plants themselves for timely allocation; On the other hand, the layered construction of urban public space also needs to refer to the utility of public space itself, with emphasis on the ornamental and practical aspects. Therefore, this design method helps to unify the general layout of urban public space.

3.1.2

Stereo Space Vegetation Landscape Design

Stereo greening refers to the greening methods of roof, wall and overhead layer existing in the city. The greening quantity in old urban area is relatively low. For the old urban area with built public space, it can be designed based on vertical space to achieve the comprehensive purpose of saving land, increasing greening quantity and beautifying living environment (Yin 2018), which can be started from the following aspects: Firstly, build multi-level and three-dimensional plant landscape, relying on carriers such as urban public space partition, implement green wall construction, and then replace the original cement wall in the city to realize three-dimensional plant landscape in urban space (Yi 2021). Secondly, improve the use of climbing plants. Climbing plants have strong climbing characteristics. In the process of plant landscape construction in urban public space, designers can use climbing plants such as mountain tigers and ivy to achieve three-dimensional high-wall plant landscape construction. Furthermore, effective urban public space expansion is carried out by using high-rise roof, balcony or overhead floor, and some shallow-rooted trees with strong adaptability such as cold and drought resistance are utilized to gradually expand the existing urban public space. The three-dimensional design of space

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vegetation landscape can make up for the lack of green concept in planning and design.

3.1.3

Combining the Biodiversity Layout of Human Environment, Establishing “Space Culture”

Humanistic and human space is endowed with existence and spiritual connotation by accumulation and inheritance of context. Residents can know where they are, so as to establish their relationship with the environment and gain a sense of security. Identity is about culture. It gains a sense of belonging by recognizing and holding the culture in which we live. In the design of space ecological environment, by combining the layout of urban human landscape, the urban historical human landscape is brought into the modern living space and becomes the place to continue the urban context, precipitate memory and entrust spirit. Space design should have the functions of ecological protection and landscape protection of historical and cultural resources. In terms of ecological protection, it provides habitats for animals, plants and human beings, as well as pathways for species migration, absorbs and stores nutrients, improves biodiversity and improves climate, etc. In terms of protection of historical and cultural resources and protection of cultural landscape features, as a low-intensity development, open space is a buffer between historical and cultural resources in urban environment and urban environment, which can be conducive to urban renewal.

3.1.4

Integration of Biodiversity in Point Space and Linear Space

Point space penetrates into each functional space of the city in a flexible space form while maintaining the individual independence of the space. Linear space, which connects important nodes and regions, is a comprehensive urban system with linear relationship, circulation and landscape generation mechanism. It is of great significance to study the integration of animals and plants in public open space from the space system composed of point and line. Linear space can connect different grades and types of dotted open spaces such as parks, city squares and street greens. Patch fragmentation in “dotted” space often has a negative impact on the spatial pattern of landscape and the aesthetic value of landscape, and the integration of patches is an important way to eliminate the impact of fragmentation (Peng 2007). Through the construction of linear space, fragmented plant landscape can be connected by linear natural elements to realize the transformation of biodiversity from fragmentation to integration. At the same time, linear space can not only provide habitat for animal migration, but also promote the improvement of biodiversity in urban areas. The ecological, entertainment and cultural value of residential areas can be greatly enhanced when environmental sensitive areas are interconnected through the green way network system. In long linear space, the monotony of linear space can be eliminated by incorporating point space such as city square into a certain node. If the rhythm of music, there

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Fig. 1 Greening area of two rivers: cooperative layout of point and linear public space

is a small climax. Point-shaped open space is set at landscape nodes and landmarks to provide an effective link for shaping the overall landscape image, making the open space a static stop point in the process of landscape sequence and enhancing the rhythm of biological sequence. The integrated design of point space and linear space refines the regional personality by enriching the form of urban afforestation. Therefore, the researchers argued that the four design methods above are not independent. Their overlap can better enhance the impact of urban design on land protection and urban biodiversity (Fig. 1).

3.2 To Suit Local Conditions and Fully Explore the Value of Various Plants In terms of geographic environment, the longitude and latitude of each city are different, and the geographic environment and ecological environment are also very different. The composition of biodiversity of different cities also differs. In the construction of urban public space, the local ecological system should be fully considered and the design and planning scheme should be selected on the basis of ecological environment protection. The ecological environment in the city are important spaces for all kinds of living organisms, which are the basic components of urban ecosystem and the basis for establishing urban public space. All kinds of plants in the city have their own values, ranging from a mountain to a grass, which are important components of urban public space (Cilliers et al. 2015). Therefore, in the design of urban public space, the practical value of all kinds of plants should be fully considered and the best use of all the resources should be made, which is not only an vital way to balance urban ecosystems, but also a beneficial measure to integrate biodiversity into urban space.

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3.3 Reasonable Allocation, Multi-Layer Community Structure and Urban Ecosystem Protection Some studies have shown that the multi-layer community structure composed of trees, shrubs and herbs has higher biodiversity (Lovell and Taylor 2013). Therefore, plants covering various types should be planted in the construction of urban greening and public space to increase the composition of plant community structure so that the plant environment can adapt to the survival and development of various organisms, which also avoids the monotony of plant community and ecosystem to a large extent. In addition to protecting various animal and plant ecological environment, urban public space should also pay attention to the protection and supervision of landscape buildings and facilities, so that existing animal and plant living space can be more guaranteed.

3.4 Strengthen Research and Provide Technical and Management Tools However, only the individual efforts of urban planning and designers, without cooperation and control of government agencies and urban policy implementers, no matter how good the design is, this requires the government departments to adopt the correct attitude, take effective policies, actively fill and repair the cities, and strive to improve the urban ecological environment (Pierce et al. 2020). In Nottingham, the government has maximized the protection of animal habitats from human activity and urbanization. For example, the natural and roadside green grass and broad-leaved forest downtown has become a paradise for pigeons, ducks and swans. Protection and establishment of animal and plant habitats Scientific planning and construction of green space, such as urban forest parks, road greening belts, etc., will make urban green space an alternative habitat, minimizing human disturbance and damage to urban ecosystems will be directly affected by human behavior. Winter and Leer (2019) mentioned that the scientific research institution in university of Nottingham has also established an obscure green technology to track animal activity. Connect the original independent and dispersed green space to provide a continuous habitat and flow path for the city. It is of great significance to maintain the normal operation of the city and to protect the ecosystem. Therefore, during the design of urban public space, all kinds of animal and plant ecosystems in the region should be scientifically studied and analyzed, and corresponding databases should be established for storage, sorting and classification, which would promote the uniformity of management measures for public space design (Luo 2018).

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4 Studies of Empirical Cases 4.1 San Jose, Costa Rica – the Optimal Design of the Spatial Plant Structure of “Sweet City” Attracts More Biological Returns In May 2020, researchers accompanied the urban design team of Nottingham University to San Jose for research. The researchers found that urban space design based on land and biodiversity conservation is an important step in protecting the “urban transformation” of Costa Rica’s capital, San Jose. The local government has promulgated the “Sweet City” planning and design scheme, which plans to construct or transform 64 green parks in 21 public districts, turn the asphalt ground into green space, attract bees, butterflies, hummingbirds and so on. Settlement and pollination is achieved by planting a large number of native plants. The designers who developed the plan encouraged residents to plant local plants in their gardens in order to turn each street and block into a healthy ecosystem. Many plants have two-dimensional codes, so people can read relevant information through scanner codes to improve their understanding of plants, as well as their awareness of environmental protection and social participation. According to a survey by Brown (2021), the “Sweet City” plan is based on the protection of urban land, animals and vegetation, planning and designing green urban public spaces, a microcosm of San Jose”s efforts to strengthen urban biodiversity conservation planning. The lack of protection of biodiversity in previous urban designs has led to the destruction of habitats and the weakening of greening of urban space in urban construction. However, with the continuous promotion of the “Sweet City” urban transformation scheme, the greening rate of urban space has increased from 58 to 78%, which has been significantly improved, and even the number of wildlife in some areas has gradually recovered. At present, the design scheme has fallen to the ground, attracting a large number of urban traffic residents into the public space and enjoying the green scenery of parks and roads along the river. The improvement of space greening effectively promotes the restoration of ecological environment and the return of many wildlife. Birds and animals live in large numbers around these public spaces (Fig. 2). San Jose’s successful attempt to take spatial plant structure optimization as the design method has been positively recognized by the government and residents. The Government of Costa Rica commended this design scheme based on urban land protection and animal and plant diversity. The restructuring of urban public space plant structure has also promoted water governance, the development of low-carbon buildings and the restoration of community ecology. This urban design method has become an innovative reference scheme that extends to other surrounding cities, and has established a green space corridor between cities.

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Fig. 2 “Sweet City” attracting more creatures to return

4.2 Milan, Italy – the Three-Dimensional Space Vegetation Design of “Vertical Forest” Creates High-Quality Urban Green Space In Milan’s prime CBD, the well-known Vertical Forest (see Fig. 3 below) has become a real forest. “Vertical Forest” is two apartments in the public commercial square in the city center, 112 m high, on which 800 trees, 15,000 ground cover plants and 5000 shrubs are planted, totaling more than 1200 kinds. It not only provides about 50,000 square meters of living space, but also opens up nearly 30,000 square meters of forest land. According to statistics, there are 1600 kinds of birds and butterflies living in the area. Based on the space planning measures of land protection and biodiversity, the designer has greatly optimized the vertical space greening conditions of the city through the three-dimensional design method of space vegetation, making it a green home for people and nature to live together. The design team selected and cultivated unique trees based on the local environment and climate, which not only naturally filters sunlight and creates a comfortable living environment, but also allows plants to regulate humidity and absorb harmful

Fig. 3 Aerial view of “Vertical Forest” building

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gases and particles. It is understood that the construction cost of the two buildings is 5% higher than that of ordinary buildings, but it reflects the innovative practice in space greening. Vertical forests are the common home of trees, people and birds. In a world of reinforced concrete, such green spaces are also the city’s air purifiers. The design team interviewed many local residents, who admitted that the “vertical forest” not only improved the greening of urban space, but also brought the practice of protecting biodiversity into public life. In recent years, Milan’s urban planning committee has made it clear that ecological environment protection is a priority factor in urban planning and design, and the level of space greening can be upgraded by the design method of three-dimensional space vegetation. The Milan Municipal Government also launched the Milan Charter, which proposed that the rational allocation of multi-level community structure under the premise of ensuring the ecological environment is an important way to integrate biodiversity into urban space. Therefore, the vertical forest has been promoted globally by the Italian government as an example of urban ecological diversity protection (Tian et al. 2021). Currently, Milan is also implementing an artificial afforestation plan called “Milan Forest”, which plans to plant 3 million trees by 2030, reaching the average level of one tree. The Milan Municipal Government is cooperating with the Milan Polytechnic University to study the best tree species selection and the best planting site, and unify the management measures of public space planning while strengthening the planning and design tools.

5 Conclusion As the main concentrated carrier of human activities, Tidball (2020) hold that cities are part of the community of human destiny. However, with the acceleration of urbanization, the greening of urban space is difficult to maintain. In addition to the objective factor of ecosystem imbalance caused by human activities, the researchers argued that land abuse and unreasonable urban design are the main issues that pose challenges to urban spatial greening. The study found that integrating biodiversity into urban space can effectively solve the greening problem of public space. Urban design based on land protection and biodiversity can effectively integrate biodiversity into urban space. There are four specific design methods. Taking San Jose as a representative, the design method of optimizing the spatial plant structure can solve the inconsistency of the overall layout of public space in the unreasonable urban design; Represented by Milan, three-dimensional spatial vegetation design can make up for the lack of green concept in spatial planning in the unreasonable urban design; The space cultural design combined with human environment is beneficial to improve the loss of humanization of space design in the unreasonable urban design; The design method of integrating the biological diversity of point and linear space can cope with the single public space situation and the lack of individuality in the unreasonable urban design. As for the imbalance of ecosystem, urban designers need to

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fully explore the value of various plants suitable for local conditions and reasonably configure the multi-layer community structure. The case of Milan not only shows fruitful practical results in urban biodiversity design and community structure configuration, but also confirms the necessity of strengthening the research of urban planning technology management tools. No matter how changeable the public space will be in the future development pattern of the city, the researchers believe that the bio-diversified urban design means will be able to create countless green urban spaces that are full of vitality, harmonious coexistence and rich and colorful.

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Indoor Thermal Comfort Prediction Model for Patients in Rehabilitation Wards Puyue Gong, Yuanzhi Cai, Bing Chen, Cheng Zhang, Spyros Stravoravdis, and Yuehong Yu

Abstract This paper aims to propose an artificial neural network (ANN) based personal thermal comfort prediction model for inpatients. The indoor thermal environment affects occupant’s physical and psychological health, so it is vital to maintain it within comfort levels in the healthcare environment. Predicted Mean Vote (PMV), as the most popular model, has a limitation in processing various complex parameters and reflecting the individual occupant’s preference in thermal comfort. Some scholars utilized the machine learning (ML) method in exploring personal thermal comfort prediction because of its strong self-study, high-speed computing, and complex problem-solving abilities. However, there was a lack of relevant studies in the healthcare environment due to data collection difficulties and pathology complexity. The present research developed an ANN-based personal thermal comfort prediction model for patients in the healthcare environment. Ten-week fieldwork was conducted in an inpatient room to collect real-world environmental data, personal related information and thermal comfort voting for the model establishment. Additionally, the spatial variables and healthcare-related parameters (personal health information and medical treatment) were represented, and their impact on the model performance was explored. It is found that considering spatial parameters in the ANN-based model development has significantly increased the prediction accuracies compared with the conventional models. In addition, personal healthcare-related parameters also had some effect on the accuracy of model prediction.

P. Gong · B. Chen Department of Urban Planning and Design, Xi’an Jiaotong-Liverpool University, Xi’an, China P. Gong · S. Stravoravdis School of Architecture, University of Liverpool, Liverpool, UK Y. Cai · C. Zhang Department of Civil Engineering, Xi’an Jiaotong-Liverpool University, Liverpool, China Y. Cai School of Engineering, University of Liverpool, Liverpool, UK Y. Yu Department of Rehabilitation, Xuzhou New Health Hospital and North Hospital of Xuzhou Cancer Hospital, Xuzhou, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_39

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Keywords Artificial neural network · Thermal comfort · Prediction model · Healthcare environment

1 Introduction The thermal environment is a crucial design consideration in healthcare facilities, with patient comfort significantly impacting healing outcomes and disease transmission. Existing research investigates indoor thermal comfort using methods like the Prediction Mean Vote (PMV), which considers factors like air temperature, humidity, and velocity (Fanger 1970). However, PMV is inadequate for medical environments due to patient’s unique needs and physical/mental health conditions (Feng et al. 2022). Patients are more sensitive to their surroundings than healthy individuals, and the PMV model neglects to account for individual differences like age, gender, or body mass index (BMI) (Wang et al. 2018). Current personal prediction methods were developed using healthy subjects but have not been validated in a medical setting (U´scinowicz and Bogdan 2022). Conducting control variable experiments on patients is challenging, making traditional thermal comfort investigation methods insufficient for medical research. Therefore, this study aims to develop a thermal comfort prediction model that considers the unique needs of patients in realistic healthcare environments, accounting for factors such as thermal physiology, perception, metabolism, blood flow, and regulatory responses.

2 Thermal Comfort Investigation in the Healthcare Environment Thermal comfort is an important factor in inpatient rooms that can help patients maintain their emotions and promote healing, making it a popular topic for designers and scholars. Previous research has primarily focused on environmental parameters such as room temperature, humidity, and air flow and their effects on overall thermal comfort levels (Khodakarami and Nasrollahi 2012). However, recent studies have expanded to consider the impact of disease type, age, gender, and medication on thermal comfort and sensation (Pereira et al. 2020; Shajahan et al. 2019; El Akili et al. 2021). The Prediction Mean Vote (PMV) model is the most widely used indoor thermal comfort assessment model globally. It was proposed by Fanger in 1970 and takes six influential parameters into account: air temperature, relative humidity, air velocity, mean radiant temperature, occupant metabolic rate, and clothing insulation. Since its first use in a hospital in 1977, the PMV model has been extensively applied to investigate thermal comfort levels in healthcare settings (Smith and Rae 1977). However, several studies have discovered a discrepancy between PMV results and actual thermal sensation (Feng et al. 2022). For example, researchers in an Italian

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health center found that PMV underestimated the subjects’ actual thermal sensation (Fabbri et al. 2019). This is primarily due to the fact that PMV was created using healthy adults without taking patients’ unique physiological characteristics into account (Lan and Lian 2016). In addition, the PMV model cannot process multiple complex parameters in real-time, nor can it predict an individual’s thermal comfort (Ciabattoni et al. 2015). Compared to residential and educational buildings, the discussion on indoor thermal comfort in healthcare settings is lacking, with influential factors confirmed in non-medical settings not thoroughly investigated in healthcare (Grassi et al. 2022). For instance, some studies evaluated the thermal environment in hospitals based on patient age and gender but did not consider the effect of patients’ health condition, while others evaluated health status using subjective phrases rather than specific physical indices or medical treatments (Moola and Lockwood 2011; Khalid et al. 2019). Furthermore, most investigations focus on the influence of physical environmental indices, neglecting the impact of spatial layout on occupants’ thermal comfort (Grassi et al. 2022). Therefore, more research should be conducted to identify and investigate the factors that influence the indoor thermal comfort of patients.

3 Thermal Comfort Prediction Model To obtain more accurate and effective results than the PMV model, a growing number of academics have proposed data-driven prediction models, with machine learning receiving considerable attention (Feng et al. 2022). Machine learning (ML) has selfstudy ability, high-speed computing ability, and complex problem-solving ability (Qian et al. 2020; Wang et al. 2020). It has demonstrated superior performance in developing models for predicting personal thermal comfort in academic, office, and residential environments, with some scholars asserting that, on average, ML-based thermal comfort prediction is 40% more accurate than the PMV model (Kim et al. 2018; Cosma and Simha 2018). A investigation found that the prediction accuracy of PMV model on personal thermal comfort level only could reached 27.63% which was worse than ML-based model by 43% (Gong et al. 2022). Additionally, ML is adept at handling non-standard and nonlinear relationships (Wang et al. 2020). Some studies have utilized machine learning algorithms to establish personal models while accounting for individual diversity. For example, Kati et al. (2020) used Support Vector Machines, Boosted Trees, Bagged Trees, and RUSBoost Trees to establish the personal model in an office building, achieving a mean accuracy of 0.84 using RUSBoosted trees. Another study by Lu et al. (2019) considered skin temperature and clothing surface temperature of subjects when establishing individual thermal models at an academic institution using Random Forest and SVM, with the linear kernel SVM-based model achieving a high degree of accuracy, exceeding 97%. Artificial neural networks (ANNs) have been demonstrated to excel in predicting thermal sensation vote outcomes (Qian et al. 2020), with Shan et al. (2020) proposing an ANN-based personal thermal comfort prediction model based on the average skin

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temperature of occupants, achieving an average prediction accuracy of 89.2%. Additionally, Gong et al. (2022) incorporated spatial impact into an ANN-based prediction model, with the prediction results superior to K-Nearest Neighbors (KNN) and SVM. However, these prediction models have not been validated in healthcare settings, and the establishment of the models has not addressed health-related parameters such as biosignals and medical treatment. Therefore, additional health-related parameters should be incorporated into the patient’s personal comfort model and validated in healthcare environments (Gong et al. 2023).

4 Methodology A methodology, illustrated in Fig. 1, was suggested to investigate the impact of spatial and healthcare-related variables. Following this, the significant variables were incorporated into the personal thermal comfort prediction model to assess their effect on the model’s accuracy.

Fig. 1 The proposed methodology

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The summary of important personal-dependent and environmental parameters was created based on literature. The features were categorized into personaldependent parameters, indoor and outdoor environmental parameters, spatial parameters, and healthcare-related parameters. Personal-dependent parameters included subject’s basic information, such as age, gender, and BMI, as well as metabolic rate obtained using ASHRAE-2010 in Met Units, clothing insulation level in clo, and bedding insulation level (Liu et al. 2021). Indoor environmental parameters consisted of the average indoor air temperature, humidity, and air speed, as well as mean radiant temperature calculated using ASHRAE-2010. Outdoor environment included outdoor temperature, humidity, and weather condition, with weather condition options of sunny (1), cloudy (2), overcast (3), and rainy (4). Spatial parameters included surface temperature of windows, doors, and air conditioning, threedimensional Cartesian coordinates representing the distances of subjects to windows, doors, and heat sources, and orientation (O), with northward and southward rooms recorded as (N) and (S), respectively. Ambient environment included air temperature and humidity. Healthcare-related parameters included personal biosignal data from daily health monitoring reports, including body temperature, heart rate, systolic and diastolic blood pressure, and medical treatment options of no treatment, acupuncture, physical therapy, massage, and infusion, recorded as (0), (1), (2), (3), and (4), respectively. Data were gathered through on-site fieldwork and analyzed statistically utilizing STATA software. Significant variables that impacted subject’s thermal comfort levels were identified as input variables. The data were split into training (70%) and testing (30%) datasets. An ANN-based personal thermal comfort prediction model was then developed, and the influence of various influential parameters on the prediction’s accuracy was examined. The conventional model, which considered personaldependent and indoor environmental parameters, was used as the baseline. Using Eq. 1 to calculate the sensitivity coefficient, the significance of individual and combined influential variables on the prediction model was ranked. Based on the model’s predictive accuracy, optimal parameter combinations were identified. SC = ( A1 − A0 )/ A0

(1)

where, A0 was the predicting accuracy when considering personal-dependent and environmental parameters only; A1 was the predicting accuracy when considering personal-dependent, environmental, spatial and healcare-related parameters.

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5 Case Study 5.1 Study Area Xuzhou is situated in Eastern China at 33° 43' –34° 58' N, 116° 22' –118° 40' E, and experiences a monsoon climate with four distinct seasons. Air conditioning systems are the primary means of cooling during summer in Xuzhou. The research fieldwork was carried out between July 1st and September 3rd, which are typical summer months in the area. The outdoor air temperature during the experimental period ranged from 21 to 37 °C, with an average of 29.92 °C. The weather conditions during the experiment period comprised sunny, cloudy, overcast, and rainy.

5.2 Experimental Setting The rehabilitation department of a hospital was the location for the field experiment, which took place on the fifth floor of the medical facility’s five-story structure. As shown in Fig. 2, eleven wards were used for the experiment, four of which faced north and seven of which faced south. Each ward has a standard configuration that includes three patient beds, one bathroom, four windows, one door, and one air conditioning unit, as depicted in Fig. 3. The southern rooms had a measurement of 3.93 m × 9.93 m × 2.8 m, covering 39 m2 , while the northern rooms measured 3.93 m × 9.09 m × 2.8 m, covering 35.7 m2 . The entire room’s W/W ratio was 0.487. In order to comply with ASHRAE standards, six thermometers were positioned along the walls with some gaps to measure the indoor air temperature. All six thermometers were placed at a height of 1.1 m from the ground. Additionally, three more thermometers were positioned beside the patient’s headrest at the level of their forehead when lying down to determine the ambient air temperature.

Fig. 2 Rehabilitation ward layout plan

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Fig. 3 The layout of the experiment wards

5.3 Experimental Procedure During the field experiment, environmental measurements and individual thermal comfort ratings were recorded at 9 a.m., 12 p.m., 2 p.m., and 4 p.m. each experimental day. The Principal Investigator (PI) and Co-Investigator (Co-I), who was a clinician, collaborated in collecting this data in the wards. The patients’ age, gender, BMI, disease condition, body temperature, heart rate, and blood pressure were provided by their doctor-in-charge. The majority of the subjects with visual impairments and difficulty in reading paper were over 60 years old. As a result, the PI and Co-PI read the thermal voting questions to each participant without providing additional instruction or interference. The instantaneous air temperature and humidity were recorded at each data collection point. Xiaomi Bluetooth thermometers were used to measure indoor air temperature and relative humidity (RH), and the surface temperature of windows, doors, and air conditioners were measured using a FLIR E85 thermal camera. Additionally, Testo 405i anemometers were used to measure air velocity.

5.4 Subjects Twenty-seven Chinese patients with neurological rehabilitation were recruited as subjects, including 6 females and 21 males. Their ages ranged from 46 to 85, and they had various neurological diseases, including 7 with cerebral hemorrhage, 12 with

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cerebral infarction, 5 with hemiplegia, 1 with carotid-cavernous fistula infarction, 1 with thalamic hemorrhage, and 1 with extracerebral hemorrhage. The average length of stay for the subjects was 20.9 days.

5.5 Academic Ethics Consideration Before the beginning of the experiment, the subjects were fully informed of the objective and content of the experiment. The attending physician of the subjects oversaw the data collection process. In addition, the university’s ethics committee approved the experiment (19-02-79).

6 Descriptive Results Analysis During the 10-week data collection period, 1304 individual thermal comfort votes were collected for the research. The majority of patients (67.25%) reported feeling no sensations (0), followed by slightly hot (1) and slightly cold (−1) at 14.57% and 10.51%, respectively. No participants reported feeling extremely hot or cold conditions (3 and −3, respectively), but some reported feeling hot (2) or cold (−2). Based on these experimental results, the statistical model analysis was conducted.

6.1 Statistical Analysis Table 1 displays the regression coefficients, and p-values of an analysis that assesses the impact of various physiological and environmental factors on thermal comfort level. In statistics, the p-value represents the likelihood of observing a sample statistic, such as a regression coefficient, as extreme as the one calculated from the sample, given that the null hypothesis is true (Cumming 2014). Typically, a p-value less than 0.01 is considered highly significant, a p-value less than 0.05 is considered significant, and a p-value less than 0.1 may also be considered significant (Sullivan and Dukes 2019). The study results indicate that several factors, including age, gender, BMI, clothing insulation, air speed, ambient temperature, ambient humidity, and surface temperature of air conditioning outlets, significantly impact thermal comfort (p < 0.01). Clothing insulation and BMI has a positive coefficient (0.1505423). In contrast, age has a negative correlation with thermal sensation, with younger subjects being more tolerant of cold environments than older subjects. Gender has a negative coefficient (−0.2310822), suggesting that women may have a lower thermal comfort level than men. Ambient temperature has a strong positive coefficient (0.3285632). Mean values of air temperature and humidity were not found to be as significant as

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Table 1 Regression analysis results Thermal sensation level

Coefficient

P > |t|

Thermal sensation level

Coefficient

P > |t|

Age

−0.0062864

0.002***

Air speed

−0.6853381

0.001***

Gender

−0.2310822

0***

MRT

0.0265235

0.496

BMI

0.0468946

0***

Location

0.0136744

0.151

Clothing insulation

0.1505423

0***

Temperature_ window1

−0.0116899

0.459

MET

0.3440568

0.018**

Temperature_ window 2

0.0048397

0.053*

Medical activity

0.0261023

0.181

Temperature_ window 3

−0.0028223

0.277

Body Temperature

0.0514406

0.377

Temperature_ window 4

0.016257

0.242

Heart rate

−0.000328

0.47

Temperature_door

0.0000246

0.994

Systolic blood pressure

−0.0001041

0.837

Temperature_air conditioning

−0.0121866

0.002***

Diastolic blood pressure

−0.0061135

0.043**

Ambient temperature

0.3285632

0***

Weather

−0.0445338

0.142

Ambient humidity 0.0162014

0***

Temperature

−0.0041244

0.634

Orientation

0.757

Humidity

−0.0013391

0.438

0.0131528

(*** denotes statistical significance at p < 0.01; ** denotes statistical significance at p < 0.05; * denotes statistical significance at p < 0.1)

ambient temperature. Additionally, it found that the subject’s metabolic rate (MET) and diastolic blood pressure were significant variables affecting thermal comfort (p < 0.05), while the surface temperature of windows had a slightly significant impact on thermal perception (p < 0.1). MET has a strong positive coefficient (0.3440568), indicating that as MET increases, the thermal sensation level also increases. The influence of diastolic blood pressure was found to be more significant than that of systolic blood pressure on thermal comfort. However, the extent to which they affect thermal comfort requires further exploration with more types and a larger number of samples. The study also found that the second window from the west had the greatest impact on thermal comfort, but differences in the impact among windows could not be explored. Therefore, the study concludes that the surface temperature of windows is a significant factor in human thermal comfort.

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Table 2 A summary of the fitted values of different levels of thermal comfort Thermal sensation level

Mean fitted value

Thermal sensation level

Mean fitted value

−2

−0.65426226

1

0.40831739

−1

−0.36699531

2

0.53871875

0

0.09030166

–

–

6.2 Performance of Statistic Model According to the results of a linear regression model, the F-statistic of the model has a p-value of 0, which is less than the significance level of 0.05, indicating that the model is statistically significant and has meaningful predictive ability. The R2 value of the model is 0.3241, explaining about 32.41% of the variance in the target variable. Therefore, although the model is statistically significant, the model’s explanation of the target variable can be further improved. Table 2 summarizes the fitted values of a linear regression model at different levels of thermal comfort. The table displays the thermal comfort level and the mean value of the fitted values at each level. The accuracy of the model’s predictions can be assessed by comparing the predicted values to the actual values. It can be observed that the model’s predicted results tend to be biased towards being too warm when the sample feels cold, and too cool when the sample feels neutral or warm. This indicates an inconsistency between the predicted and actual comfort levels, resulting in prediction errors. Therefore, a more efficient and accurate method is required to handle real-world data and explore the influence of multidimensional variables on user thermal comfort.

7 Results of the Prediction Model 7.1 Model Structure Figure 4 illustrates the general structure of the four-layer ANNs employed in this study. The number of nodes in the input, hidden, and output layers corresponds to the number of input features, forty, and the thermal comfort scale (7), respectively. The size of the ANN was determined by balancing prediction accuracy and processing time, with close-to-saturation prediction accuracy achieved using the current ANN size. Increasing the ANN size only marginally improved prediction accuracy but substantially increased processing time. The ReLU function was used as the activation function, and the cross-entropy function was utilized as the loss function. The dataset was randomly split into a training set (70%) and a test set (30%) for each training session of the ANN, and the ANN was optimized using the scaled conjugate gradient method. To minimize the impact of randomness associated with weight

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Fig. 4 The end-to-end artificial neural network structure

initialization and dataset partitioning, the performance of each feature combination was measured as the average test accuracy of one thousand training sessions.

7.2 The Influence of Influential Variables The study compared the impact of single spatial variables, including windows (W1, W2, W3, and W4 from west to east), door (D), air conditioning (AC), ambient environment (AE), and orientation (O), on prediction accuracy. The combinations of the four windows were treated as a single spatial variable as they were homogeneous. Furthermore, the impact of single biosignal variables, such as body temperature (BT), heart rate (HR), blood pressure (BP), and medical treatment (MT), on prediction accuracy was examined by comparing them with the conventional model. Figure 5 demonstrates that the accuracy of model predictions improved when spatial variables were considered, except for a single consideration of W1 and W2. When all windows were considered, the maximum accuracy reached 0.733, which was 2.21 percentage points higher than the conventional model. The integrated considerations of W1 + W2 + W3 and W1 + W4 also showed improved accuracy, with an accuracy of 0.7322 and 0.7318, respectively. The impact of multiple windows on the accuracy of model predictions was more significant than that of a single window. Single-window prediction accuracy averaged 0.7152, while multiplewindow prediction accuracy reached 0.7281. AC and O also made a substantial contribution to improving the prediction accuracy, with an accuracy of 0.7286 and 0.7272, respectively. In addition, D improved prediction accuracy by 0.76%. However, the

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Fig. 5 Results of ANN-based prediction models

effect of AE was smaller than that of other spatial variables, with an increase of only 0.28% in the conventional model. The single consideration of health-related factors decreased the accuracy of prediction compared to the conventional model. Among the health-related variables, a single consideration of HR had a better performance with accuracy of 0.7144. Individual consideration of MT and BT followed, with an accuracy of 0.7082 and 0.7073, respectively. The involvement of BP decreased prediction accuracy by the most, achieving 0.6999, which was 2.4% lower than the conventional model. Overall, most of the combinations considering multiple health-related variables had a better prediction accuracy than any other single consideration, except for HR. Among the combinations, BT + HR + MT had the best performance, with an accuracy of 0.7134, which was −0.53% lower than the conventional model.

7.3 Top 10 Combinations Among Spatial and Health-Related Parameters Figure 6 demonstrates that the integrated consideration of spatial and health-related variables had a significant impact on increasing prediction accuracy compared to the conventional model, with health-related variables improving the positive effect from spatial impact. When considering W2, W3, W4, AE, O, and BP, the maximum accuracy achieved was 0.7753, representing an improvement of 8.1% compared to the

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Fig. 6 The prediction accuracy of combinations among all parameters with Top 10 accuracy

conventional model. Considering BP increased the performance of spatial impact by 2.53% than the conventional model. The other nine combinations also showed good prediction performance by raising accuracy by more than 7.13%. The involvement of biosignals in these combinations contributed to enhancing the prediction accuracy based on the basis of spatial impact, with the highest improvement being 5.56% and an average increase of approximately 2.1%. Among the ten models, BP had the most significant effect, appearing in the top two combinations and nine times in the top ten combinations. MT also had a positive effect on model prediction accuracy, appearing in half of the top six combinations. Although BT and HR had some influence on the model, it was not as significant as BP and MT.

8 Conclusion This study conducted fieldwork in rehabilitation wards to collect indoor physical environmental indices, patient’s healthcare information, and thermal voting results. A statistical analysis of influential variables was conducted to determine their impact on patient’s personal thermal comfort, and an ANN-based prediction model was subsequently developed to assess the influence of these variables on the model’s prediction accuracy. The study found that the ambient environment (temperature and humidity), surface temperature of windows, air conditioning, and diastolic blood pressure significantly impacted patient’s thermal comfort. Spatial variables, particularly windows,

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had a significant effect on the accuracy of the prediction model. Orientation also had a significant impact when evaluated simultaneously with windows and the ambient environment. Medical treatment had a noticeable impact on model improvement, enhancing the model’s robustness. Incorporation of a single biosignal variable had no positive effect, but blood pressure exhibited its contribution when simultaneously considered with spatial impact. Therefore, the spatial impact of windows and air conditioning, ambient environment, and patient’s blood pressure should be considered in personal thermal comfort investigations. The ANN-based personal thermal comfort prediction model, by considering these parameters, has a higher prediction accuracy compared to the PMV model. As a result, it provides more accurate predictive results to designers during the design stage. After comparing the prediction results with the expected design performance, designers can improve the design by adjusting the position of air outlets and rearranging the location of wards. This contributes to the development of a more scientific design that meets the needs of patients. However, there were several limitations to this research, including the small size of the dataset and the difficulty of on-site data collection in healthcare environments. Additionally, the research was conducted in a four-season city during a typical summer, and the subjects were orthopedic rehabilitation patients, while different diseases had distinct biosignals and medical treatments. As the measurement parameters and data size increase, it is possible that the results may be contested over time. Future research should involve a greater number of investigations on various patients in different healthcare settings during various seasons and incorporate effective biosignal variables into the model.

References El Akili Z, Bouzidi Y, Merabtine A, Polidori G, Chkeir A (2021) Experimental investigation of adaptive thermal comfort in french healthcare buildings. Buildings 11:551.https://doi.org/10. 3390/buildings11110551 Ciabattoni L, Cimini G, Ferracuti F, Grisostomi M, Ippoliti G, Pirro M (2015) Indoor thermal comfort control through fuzzy logic PMV optimization. In: International joint conference on neural networks (IJCNN), (2015), pp 1–6.https://doi.org/10.1109/IJCNN.2015.7280698 Cosma AC, Simha R (2018) Thermal comfort modeling in transient conditions using real-time local body temperature extraction with a thermographic camera. Build Environ 143:36–47. https:// doi.org/10.1016/j.buildenv.2018.06.052 Cumming G (2014) The new statistics: why and how. Psychol Sci 25(1):7–29. https://doi.org/10. 1177/0956797613504966 Fabbri K, Gaspari J, Vandi L (2019) Indoor thermal comfort of pregnant women in hospital: a case study. Evid Sustain 11:6664 Fanger PO (1970) Thermal comfort. Analysis and applications in environmental engineering. Copenhagen, Danish Technical Press Feng Y, Yao R, Sadrizadeh S, Li B, Cao G, Zhang S, Zhou S, Liu H, Bogdan A, Croitoru C, Melikov A, Alan Short C, Li B (2022) Thermal comfort in hospital buildings—a literature review. J Build Eng 45.https://doi.org/10.1016/j.jobe.2021.103463

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Gong P, Cai Y, Chen B, Zhang C, Stravoravdis S, Sharples S, Ban Q, Yu Y (2023) An artificial neural network-based model that can predict inpatients’ personal thermal sensation in rehabilitation wards. J Build Eng 80:108033 Gong P, Cai Y, Zhou Z, Zhang C, Chen B, Sharples S (2022) Investigating spatial impact on indoor personal thermal comfort. J Build Eng 45:103536 Grassi B, Piana EA, Lezzi AM, Pilotelli M (2022) A review of recent literature on systems and methods for the control of thermal comfort in buildings. Appl Sci 12:5473.https://doi.org/10. 3390/app12115473 Jamal K, Nasrollahi N (2012) Thermal comfort in hospitals-a literature review. Renew Sustain Energy Rev 16:4071–4077. https://doi.org/10.1016/j.rser.2012.03.054 Kati´c K, Li R, Zeiler W (2020) Machine learning algorithms applied to a prediction of personal overall thermal comfort using skin temperatures and occupant’s heating behavior. Appl Ergon 85.https://doi.org/10.1016/j.apergo.2020.103078 Khalid W et al (2019) Investigation of comfort temperature and thermal adaptation for patients and visitors in Malaysian hospitals. Energy Build 183:484–499 Kim J, Schiavon S, Brager G (2018) Personal comfort models–A new paradigm in thermal comfort for occupant-centric environmental control. Build Environ 132:114–124. https://doi.org/10. 1016/j.buildenv.2018.01.023 Lan Z, Lian Z (2016) Ten questions concerning thermal environment and sleep quality. Build Environ 99:252–259 Liu J, Liu J, Lai D, Pei J, Wei S (2021) A field investigation of the thermal environment and adaptive thermal behavior in bedrooms in different climate regions in China. Indoor Air 31:887–898. https://doi.org/10.1111/ina.12775 Lu S, Wang W, Wang S, Hameen EC (2019) Thermal comfort-based personalized models with non-intrusive sensing technique in office buildings. Appl Sci 9:1768.https://doi.org/10.3390/ app9091768 Moola S, Lockwood C (2011) Effectiveness of strategies for the management and/or prevention of hypothermia within the adult perioperative environment. Int J Evid Base Healthc 9:337–345 Peeters L, De Dear R, Hensen J, D’Haeseleer W (2009) Thermal comfort in residential buildings: comfort valuesand scales for building energy simulation. Appl Energy 86:772–780 Pereira PFdC, Broday EE, Xavier AAdP (2020) Thermal comfort applied in hospital environments: a literature review. Appl Sci 10(20):7030. https://doi.org/10.3390/app10207030 Qian C, Wang H, Zhai Y, Yang L (2020) Using machine learning algorithms to predict occupants’ thermal comfort in naturally ventilated residential buildings. Energy and Build 217:109937 Shajahan A, Culp CH, Williamson B (2019) Effects of indoor environmental parameters related to building heating, ventilation, and air conditioning systems on patients’ medical outcomes: a review of scientific research on hospital buildings. Indoor Air 29(2):161–176 Shan CC, Hu JW, Wu JH, Zhang A, Ding GL, Xu LX (2020) Towards non-intrusive and high accuracy prediction of personal thermal comfort using a few sensitive physiological parameters. Energy Build 207.https://doi.org/10.1016/j.enbuild.2019.109594 Smith RM, Rae A (1977) Thermal comfort of patients in hospital ward areas. J Hyg 78:17–26 Sullivan LM, Dukes KA (2019) In: Understanding clinical research, 3rd edn. McGraw-Hill Education U´scinowicz P, Bogdan A (2022) Directions of modification of the model of perception of the thermal environment by patients of selected hospital wards. Energies 15:3965. https://doi.org/10.3390/ en15113965 Verheyen J et al (2011) Thermal comfort of patients: objective and subjective measurements in patient rooms of a Belgian healthcare facility. Build Environ 46:1195–1204 Wang Z, de Dear R, Luo M, Lin B, He Y, Ghahramani A, Zhu Y (2018) Individual difference in thermal comfort: a literature review. Build Environ 138:181–193. https://doi.org/10.1016/J.BUI LDENV.2018.04.040

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Deep Learning-Based Semantic Segmentation and 3D Reconstruction Techniques for Automatic Detection and Localization of Thermal Defects in Building Envelopes X. Y. Yan, H. Huang, and C. Zhang

Abstract Building age and extreme weather can cause thermal defects in the building envelope. Failure to inspect and fix these defects can threaten safety, increase energy consumption, and negatively impact the environment. Infrared thermal imaging (IRT) is a popular, non-destructive technique for building diagnostics due to its safety, practicality, and energy efficiency. However, manual IRT detection is time-consuming and imprecise. Therefore, this paper proposes a framework for automatically identifying and localising thermal defects in building envelopes. The outcomes of this study not only offer direction for categorising thermal defects in buildings but also provide a practical approach for automatically detecting and locating them. Keywords Deep learning · 3D reconstruction techniques · Automatic detection · Building envelopes

1 Introduction As the building’s exterior protective structure, the building envelope is vital in excluding adverse weather effects and environmental pollution and providing thermal, cold and sound insulation (Guo et al. 2020). However, the increasing age of the building and the negative environmental impact will result in several thermal defects in the building envelope. These defects not only pose a significant safety risk to people’s daily lives (Wang and Lin 2022), but also reduce the insulation of the external maintenance structure, thereby increasing the energy consumption of the building (Aoul et al. 2021). Therefore, it is necessary to regularly inspect and maintain the building’s envelope throughout its life cycle. Infrared thermography (IRT) is one of the non-destructive testing methods widely used to improve building X. Y. Yan · H. Huang · C. Zhang (B) Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_40

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energy consumption and repair maintenance because of its non-contact nature, accuracy and rapidity (Kirimtat and Krejcar 2018). However, traditional thermal defect determination usually relies on the experience of professionals, which is inefficient and not suitable for the census of large projects (Garrido et al. 2018). With the gradual maturity of image processing algorithms, some research has proposed methods to automatically distinguish the irregularity of temperature distribution from the thermal images of building envelopes (Garrido et al. 2018, 2019), but the data set of these studies have few defect types and no subdivision of thermal defects. In recent years, with the development of photography technology, unmanned aerial vehicle (UAV) has also been widely used to detect visible defects in building envelopes (Chew and Gan 2022). In addition, with the improvement of Geographic Information System (GIS) technology, some studies have tried to combine GIS and drones to locate the location of defects. For example, Zhong et al. used remote sensing infrared images with visible images and data from GIS to locate damaged pipe’s locations. However, the combination of UAV and GIS technology still needs further research to locate thermal defects surrounding building envelopes (Zhong et al. 2019). Based on the above issues, this paper proposes a framework for automatically detecting and localising thermal defects in building envelopes. This paper aims to achieve automatic detection of thermal defects using thermal camera and develop an annotated dataset trained with semantic segmentation based on deep learning. The detected defects are located and visualised using UAV and 3D reconstruction techniques.

2 Framework for Automatic Detection and Localization 2.1 Framework Overview The research framework of this study consists of two parts, which are automatic detection and localization of thermal defects, as shown in Fig. 1. The process of detection is divided into 5 main steps: (1) IRT data collection; (2) Data pre-processing; (3) Data labeling; (4) Deep learning-based semantic segmentation; and (5) Dataset evaluation and analysis. The process of locating thermal defects is divided into 3 steps: (1) UAV data collection and reconstruction of point cloud model; (2) Creating control points and Alignment Point Cloud; and (3) Visualization and positioning of thermal defects in 3D models.

2.2 IRT Data Collection Data were collected during September and October 2023 at dawn (7–9 a.m.) and dusk (5–6.30 p.m.), by using a FLIR E85 thermal imaging camera to capture images

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Fig. 1 Research framework

of the envelopes of various commercial and residential buildings. A total of 1507 sets of data, comprising an infrared thermal map and an RGB map, were collected. The shooting guideline for thermal imaging cameras capturing building envelopes was developed based on technical specifications, literature research, and practical experience (Barreira et al. 2021; Mahmoodzadeh et al. 2022).

2.3 Data Pre-processing The pre-processing of thermal images involves six steps. The first step is converting the infrared images from three channels to a one-channel grey image (Fig. 2), which reduces data processing time (Treptow et al. 2005). Next, camera distortion correction is performed to correct lens distortion, which is a necessary step in pre-processing (Lu et al. 2017). The third step involves filtering image noise, which is achieved using wavelet filtering in this dataset (Chervyakov et al. 2018). The fourth step is image enhancement, which is necessary to address the blurred edges and low contrast in thermal images (Wei et al. 2020). This is done using the ’adapthisteq’ function (Wu et al. 2015). The fifth step involves aligning and cropping the images using a cropping code, internal and external reference coefficients, and an offset single-strain matrix (Bulanon et al. 2009). The final step is image fusion, combining the complementary information in infrared and visible images. The fused image (Fig. 3) combines the

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Fig. 2 Thermal images to grey images

Fig. 3 Images fusion

advantages of both modes and facilitates further data annotation. The pre-processing process results in high-quality images that can be used for further analysis.

2.4 Data Labeling This dataset is annotated using the ‘images Labeler’ function in MATLAB. Each region of interest (ROI) was annotated at the pixel level. There are two base maps for the annotation of this dataset. One is the pseudo-colored grey map and the other is the fused images. The pseudo-colored grey map used as the base map for the first annotation is used for the basic annotation. The second time, the fused images is used as the base map for review to check for misidentification and acceptable annotation type boundaries. A total of 449 images were annotated in this dataset, and the annotations were classified into six categories, including walls, windows, trees and thermal defects. Based on the specifications and literature, this study subdivides thermal defects into the following three categories. Visible wall defects (Fig. 4): This type of defects can be clearly identified in both RGB and thermal images. Furthermore, the color difference between the boundary of this defect and the surrounding environment is noticeable so that the boundary

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Fig. 4 Visible wall defects

line can be clearly seen. The identification of this type can be divided into two cases: a. Material spalling of the exterior wall finish layer; b. Wall cracks. Component thermal anomalies (Fig. 5): This type is characterized by being clearly evident in the thermal images, but is not visible or not apparent in the RGB ones. The identification of this type consists of three types: a. Material anomalies in the building envelopes, which cause a significant temperature shift; b. The bonding of the wall finish layer to the main structure of the wall fails due to the negative impact of the natural environment or the age of the wall, causing separation from each other; c. Damage to the wall around the cracks. Thermal bridges (Fig. 6): This defect is characterized by being visible in the infrared thermogram but not in the RGB graph. Component bridges is nail bonding quality defects. When the wall insulation nail does not meet the specifications or construction errors, it will appear in the infrared images of the wall in more uniformly distributed dotted temperature anomaly areas. Structural bridges: a. Joints in external wall panels in the building envelope; b. Window overhangs.

Fig. 5 Component thermal anomalies

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Fig. 6 Thermal bridges

2.5 Deep Learning-Based Semantic Segmentation There are two commonly used methods to improve semantic segmentation. One is inserting the Transformer into the Convolutional Neural Networks (CNN) backbone network. The results show that the combined network framework improves the accuracy bar and classification task speed (Srinivas et al. 2021; Wang et al. 2022). Another approach is using multiple sources of data as input sources, which takes the advantages of better performance yielded from complementary multimodal models with two data sources. For example, infrared images show the amount of thermal radiation of an object but features such as the texture of the object are lost, while visible images contain rich color and texture information (Liu et al. 2022). Therefore, in this study, semantic segmentation of datasets is trained and tested using the Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers (CMX), which contains CNN and Transformer and can also input multiple data sources as training models (Liu et al. 2022).

2.6 Dataset Evaluation and Analysis We use cross-entropy as the loss function. The Intersection over Union (IoU) and Pixel accuracy rate are used as the main metrics to evaluate the segmentation performance. The IoU refers to the ratio of the overlapping area of the actual area of the object and the presumed area to the total area of the object. The Pixel accuracy rate denotes the proportion of points identified as anomaly domains by the algorithm that are actually true anomaly domains (Wang, Wang and Zhu 2020). After 14 h and 80,000 steps of training, the training results are obtained, as shown in Table 1. It can be seen that the windows, trees and walls are better categorized. They all have an IoU above 80% and a Pixel Accuracy above 90%, which results from the large number of images and the larger area in each image that contains these objects. However, the

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Table 1 The results of training Type

IoU (%)

Pixel accuracy (%)

Window

91.1

96.5

Tree

87.2

93.5

Wall

84.1

83.1

Component thermal anomalies

69.0

59.4

Visible wall defects

50.2

59.4

Thermal bridges

49.1

65.4

MIoU

Mean pixel accuracy

71.8%

81.4%

IoU and Pixel Accuracy of walls are lower than that of windows and trees. That is because most data are captured based on one area of the whole wall so that a wall can take up the whole frame. There are fewer boundary captures for walls, which results in fewer features on walls. Therefore, when photographing a target, it is better to ensure it has an appropriate amount of data and is fully characterized. The ranking of the IoU values for the three thermal defects is component thermal anomalies > visible wall defects > thermal bridges. The low IoU values for thermal bridges and visible wall defects is due to the fact that there are very few images of these two types so they will impact the CNN training results. Figure 7 shows that a high matching level can be achieved between the annotated and training sets. However, the last two images show that the test set cannot correctly identify flower pots, cars, water pipes and floors. The incorrect recognition is because there are fewer data for these categories, a maximum of ten images in total, which leads to the network not performing multi-feature learning.

2.7 UAV Data Collection and Reconstruction of Point Cloud Model To locate the thermal defects, a commercial building is used as a case study. A DJI 4-RTK UAV is used and 5280 photos are taken to reconstruct a 3D model by using RealityCapture software. As shown in Fig. 8.

2.8 Creating Control Points and Alignment Point Cloud Since these two point clouds are cross-source point clouds (i.e. captured with different camera resolution), the 3D model cannot be reconstructed directly in RealityCapture. Therefore, this paper proposes to use common control points to align the two point clouds. The first step is to find appropriate control points on the two-point clouds, which should be set at obvious architectural features, such as sill corners, lights,

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Fig. 7 Presentation of semantic segmentation results, a Thermal images; b RGB; c Test images; d Labelled images

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Fig. 8 3D point cloud model

Fig. 9 Point cloud model

brick joints (Fig. 9a). When creating control points on the two point clouds, note the location and the serial number of the control points. The point clouds with the control points are then aligned to the two point cloud models using RealityCapture software. The new point cloud model includes the spatial coordinates of the UAV camera and the thermal camera RGB camera (Fig. 9b).

2.9 Visualization and Positioning of Thermal Defects in 3D Models Lack of feature points makes it challenging to locate thermal defects using infrared point clouds. Therefore, this study uses the spatial coordinates of the cameras when the images were taken to locate defects. The images projected onto the point cloud by each camera are visible in RealityCapture, and the corresponding thermal images can be found based on the sequence number of the images. The problem of distance

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Fig. 10 Replace the RGB with the corresponding thermal images

between the IR and RGB lens in the thermal camera is solved using the offset matrix obtained during pre-processing. The RGB images are then replaced with the corresponding thermal images to generate a thermal point, clearly showing the location of thermal defects in the building envelope (Fig. 10). Aligning the thermal point cloud with the UAV point cloud through the original common control points to visualise the location of thermal defects on the actual building maintenance structure and determine the 3D coordinates of the thermal defect images in the point cloud.

3 Conclusion In order to detect thermal defects in buildings and determine the location of thermal defects, this paper proposes a framework for the automatic detection and localization of thermal defects in building envelopes. Compared with the traditional handheld thermal camera detection method, the method in this paper has the following contributions: 1. Defining and classifying the types of thermal defects; 2. This paper collects rich data for subsequent multi-defect identification, including multiple building types and thermal defects. 3. Verifying that fusing images from multiple data sources not only help the labelling and achieves better neural network training results. The training results show knots with over 80% IoU for windows, walls and trees, over 69% for component thermal anomalies, and about 50% for thermal bridges and visible wall defects. This lays the foundation for the automatic identification of building thermal defects in the future. However, the thermal camera used in this paper has disadvantages, such as low thermal pixel accuracy and low shooting efficiency, which will impact the training accuracy. In thermal defect localization, the reconstructed high-accuracy UAV point cloud model is the basis for locating thermal defects. The thermal camera’s RGB images are reconstructed, but aligning the two cross-source

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point clouds was difficult due to a lack of common feature points and spatial coordinates in the thermal camera’s RGB point cloud. To solve this problem, the paper proposes using identical control points to align the point clouds. The aligned new point clouds provide accurate spatial coordinates for the thermal camera, allowing the thermal map to be projected onto the point cloud model and aligned using control points. In this way, a thermal point cloud with spatial coordinates can be obtained, and the visualization of thermal defects in the 3D model is also completed. However, the specific point cloud coordinates of the thermal defects are not calculated. Therefore, further research is needed for accurate thermal defect point cloud spatial coordinates. Acknowledgements This research is funded by Xi’an Jiaotong-Liverpool University Urban and Environmental Studies University Research Centre, grant number: UES-RSF-23030605.

References Barreira E, Almeida RMSF, Simões ML (2021) Emissivity of building materials for infrared measurements. Sensors 21(6):1961. Available at: https://doi.org/10.3390/s21061961 Bulanon DM, Burks TF, Alchanatis V (2009) Image fusion of visible and thermal images for fruit detection. Biosyst Eng 103(1):12–22. Available at: https://doi.org/10.1016/j.biosystem seng.2009.02.009 Chervyakov N et al. (2018) Analysis of the quantization noise in discrete wavelet transform filters for image processing. Electronics 7(8):135. Available at: https://doi.org/10.3390/electronics7 080135 Chew MYL, Gan VJL (2022) Long-standing themes and future prospects for the inspection and maintenance of façade falling objects from tall buildings. Sensors (14248220) 22(16):6070– 6070. Available at: https://doi.org/10.3390/s22166070 Garrido I et al. (2018) Thermal-based analysis for the automatic detection and characterization of thermal bridges in buildings. Energy and Build 158:1358–1367. Available at: https://doi.org/10. 1016/j.enbuild.2017.11.031 Garrido I et al. (2019) Automatic detection of moistures in different construction materials from thermographic images. J Therm Anal Calorimetry: An Int Forum for Therm Stud 138(2):1649– 1668. Available at: https://doi.org/10.1007/s10973-019-08264-y Guo J et al. (2020) Façade defects classification from imbalanced dataset using meta learningbased convolutional neural network. Comput Aided Civil and Infrastruct Eng 35(12):1403–1418. Available at: https://doi.org/10.1111/mice.12578 Kirimtat A, Krejcar O (2018) A review of infrared thermography for the investigation of building envelopes: advances and prospects. Energy and Build 176:390–406. Available at: https://doi. org/10.1016/j.enbuild.2018.07.052 Liu H et al. (2022) CMX: cross-modal fusion for RGB-X semantic segmentation with transformers. arXiv. Available at: http://arxiv.org/abs/2203.04838. (Accessed 6 Dec 2022) Lu YB et al. (2017) Study on lens distortion correction target forarray thermal infrared camera. Laser and Infrared 47(8):987–991. Available at: https://doi.org/10.3969/j.issn.1001-5078.2017. 08.012 Mahmoodzadeh M et al. (2022) Infrared thermography for quantitative thermal performance assessment of wood-framed building envelopes in Canada. Energy and Build 258:111807. Available at: https://doi.org/10.1016/j.enbuild.2021.111807

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Smart Construction Engineering and Management

Methods of Managing Construction Information in the Fourth Industrial Revolution Era Peter Adekunle, Clinton Aigbavboa, Opeoluwa Akinradewo, Kenneth Otasowie, and Samuel Adekunle

Abstract The purpose of this study was to present techniques for managing construction information systematically in the fourth industrial revolution (4IR) period. The efficient handling of information is essential to the success of building projects. Information is gathered, kept, distributed, archived, deleted, or destroyed. Effective information management guarantees that the appropriate individuals have access to the appropriate information at the appropriate time, enabling them to make informed decisions. As a result, information collecting, sharing, and storage for construction-related operations will be improved. This research seeks to investigate how various 4IR tools can be used to achieve effective information management. In order to collect information from architecsts, civil engineers, quantity surveyors, mechanical and electrical engineers, construction managers, and project managers, the study used a quantitative survey technique with the use of a questionnaire. With the help of SPSS, the data were analyzed, and the appropriate measure of dispersion and inferential statistics were used. The study found that using cutting-edge materials, applying artificial intelligence, applying quantum computing, and using autonomous vehicles are the top 4 IR techniques that may be used to manage construction information. Additional research showed that the techniques have been successfully used in other industries, such as manufacturing, leading to development in both the economy and industry. The study came to the conclusion that 4IR tools should be used in construction enterprises for effective and efficient information transmission. Keywords Construction industry · Information management · Quantitative survey

1 Introduction Information technology (IT), usually referred to as computing and communication technology (CCT), has been drastically altering how we live, study, work, and play (Froese 2010). The beneficial improvements and benefits that the new technology was P. Adekunle · C. Aigbavboa · O. Akinradewo · K. Otasowie · S. Adekunle Cidb Centre of Excellence, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg 2006, South Africa © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_41

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bringing to businesses in other industries of the economy do not generally seem to have been recognized by many enterprises in the construction industry. Even while the majority of building firms employed computer technology for many of their fundamental operations, such as accounting and pay, in the 1980s, PCs were only used by a small number of construction organizations (Autor 2015). Very few of them developed formal information technology use policies or strategies About eight years after the development of dependable PC hardware, in the latter part of the 1980s, some businesses had reached a point where their staffs on many of their larger projects were benefiting from the new technology through the use of planning, drawing, spreadsheet, and word-processing software packages. Fourth Industrial Revolution (4IR) packages are now accessible to all the disciplines of the building team at every stage of the construction process thanks to digital evolution (Reaves 2019). They assist with a wide range of construction operations, including building visualization, design evaluation, project management, information storage and retrieval, cost estimation, structural analysis, on-site management, and facilities management, among others. Effective information management is essential to lowering the risk of errors and delays on a construction project and ensuring that all stakeholders have access to the information they require to make educated decisions. It is therefore crucial to investigate how well these 4IR tools can be used to manage information in the construction sector.

2 Literature Review The blending of the physical, digital, and biological worlds is referred to as the fourth industrial revolution. It is the driving force behind a variety of goods and services that are quickly turning into necessities for modern living. The 4IR tools that can be used to manage construction information are briefly discussed. The first 4IR through that can employed to manage construction management as reviewed in this study is mobile device management. The practice of monitoring, managing, and safeguarding mobile devices used by businesses, such as laptops, smartphones, and tablets, is known as mobile device management (MDM) (Harris and Patten 2014). The business network is secure thanks to mobile device management solutions that enable IT teams and admins to administer and distribute security policies to the mobile devices accessing critical company data. Another tool is cloud management, an emerging paradigm that is being more and more widely used is cloud computing (Yeboah-Boateng and Essandoh 2014). Compute-on-demand, online storage, online/shared offices, keyvalue store services, and email are just a few of the many cloud services available. Other tools include onsite wearables, building information modelling, artificial intelligence and, automation and robotics. Smart wearables and smart garments are both included in wearable computing. Basically, smart wearables are gadgets with wireless sensors implanted in clothing or accessories that users might leave on all day. Building information modeling, also known as building information management, is referred to as BIM. A structure or building can be planned, designed, and built within a

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single 3D model thanks to this highly collaborative process that involves architects, engineers, real estate developers, builders, manufacturers, and other construction experts. AI-based building solutions can also be useful in many different ways. AI can help with task management, updating construction sequences, and planning the execution of construction projects while keeping all stakeholders updated. Furthermore, the architecture, engineering, and construction (AEC) sector as a whole, as well as the construction industry specifically, stand to benefit greatly from robotics and automated systems. Automation and robotic systems have shown to be quite successful in cutting labor costs while enhancing productivity and quality in various industries (Delgado et al. 2019). Additional 4IR tools identified through extensive literature review that can be employed to effectively manage construction information include augmented reality, innovative materials, autonomous vehicle, 5G network, quantum computing, blockchain-based BIM, big data and smart censor devices. The term “augmented reality” (AR) refers to a live, replicated view of a physical, real-world environment whose elements are "augmented" (or "supplemented") by computer-generated sensory input. Augmented reality is one of the three extended reality (XR) virtual environments, along with virtual reality (VR) and mixed reality (MR). Innovative materials revealed that the development of novel smart materials that can offer effective substitutes for traditional construction materials, increase building energy efficiency, or be used to upgrade, repair, and preserve existing infrastructures is a constant focus of academic and industry efforts around the world. In continuation, autonomous Vehicles (AVs) have the ability to go toward the intended place to carry out some specialized activities, such as the movement of commodities, exploration, and tool manipulation, in areas that are dangerous or distant. Also, a quick, enormous improvement is always required for end users to embrace new technology, as shown by 5G’s remarkable progress when compared to 4G and WiFi. Almost every industry will see a change thanks to quantum computing. These incredibly fast machines give any sector that depends on computing a method to address issues that are beyond the capabilities of even the most advanced supercomputers, to work more quickly, to streamline workflows, and to raise quality (Kanamori and Yoo 2020). Assessing blockchain revealed that it is a distributed database that is virtually hard to alter. It is a technology approach to maintain a trustworthy database through decentralized, trusted methods. Facilities have already begun to produce huge amounts of data throughout the stage of operations and maintenance since the introduction of embedded devices and sensors, eventually leading to increasingly rich sources of Big Data. Finally, smart censor devices is vital in order to transmit and handle big data collections, technologies like radiofrequency identification (RFID), a global positioning system (GPS), general packet radio service (GPRS), Bluetooth, and Zigbee utilise radio waves at various frequencies.

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3 Methodology The focus of this study is the adoption of 4IR tools for managing construction information. In order to achieve this objective, survey research was conducted, and a quantitative approach was employed to collect data from respondents utilizing questionnaires. Professionals working in the built environment, such as civil engineers, construction managers, project managers, architects, quantity surveyors, and mechanical and electrical engineers, made up the study’s target audience. The investigation was carried out in South Africa, one of Sub-Saharan Africa’s most prosperous nations. The study’s structured questionnaire was modeled after one used by Adekunle et al. (2022). The questionnaire was split into two sections: one half was used to obtain background information on the respondent, and the other section included a range of 4IR tools that were taken from the literature and used to determine how much the respondents agreed with managing information. There were 250 questionnaires distributed to participants, and 235 of them were returned, yielding a 94% response rate. Mean item score (MIS) was used to rank the bitcoin platforms, while percentage and frequency were utilized to analyze the background data. In addition, exploratory factor analysis was utilized to analyze the underlying theoretic structure of the phenomenon and to condense the enormous number of variables into a smaller set of summary variables. According to the analysis, the instrument is trustworthy because it had an alpha value of 0.910 for the 14 procedures examined. The structural validity of the computed scale using n was examined using Kaiser–Meyer– Olkin (KMO) and Bartlett test analyses. The results of the Bartlett test produced an estimated chi-square of 1688.892 with 91 degrees of freedom and a significant pvalue of 0.000, and the KMO value of 0.829 confirmed the normality of the data obtained.

4 Discussion of Findings In terms of profession, demographic data also showed that 4.5% of respondents were project managers for construction, 15% were managers of construction, and 13.2% were project managers, with 14.2% of respondents being civil engineers, 13.3% being mechanical and electrical engineers, 24.5% being quantity surveyors, and so forth. Also, the majority of respondents—more than 90%—said they had worked on seven or more projects, while the remaining 10% said they had only completed six or less. The responses were reliable and credible since, on average, more than 90% of respondents—a very high proportion—had over five years of work experience in the South African construction industry. The instrument’s alpha value for the 14 tested methods is 0.910, which denotes its dependability. The structural validity of the computed scale using n was examined using Kaiser–Meyer–Olkin (KMO) and Bartlett test analyses. The results of the Bartlett test produced a KMO value of 0.829

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and an estimated chi-square of 1688.892 with 91 degrees of freedom and a significant p-value of 0.000. Table 1 displays the mean distribution and order of the approaches. From the Table 2 showing the pattern and structure matrices, the fourteen (14) variables identified from the literature were factored into three clusters that are interpreted thus based on the observed inherent relationship among the variables in the cluster. A total of eleven (11) variables were loaded onto cluster 1, as shown in Table 7.21. These variables include ‘Usage of innovative materials’ (92.8%), ‘Artificial intelligent application’ (83.3%), ‘Quantum computing application’ (82.9%), ‘Usage of autonomous vehicle’ (82.5%), ‘Adoption of 5G network’ (73.5%), ‘Usage of robots’ (73.3%), ‘Adoption augmented reality technology’ (73.1%), ‘Implementation of blockchain-based bim’(71.3%), ‘Usage of big data’ (70.6%), ‘Incorporation of building information modelling’ (63.9%) and ‘Usage of cloud storage’ (50.8%). Since all these variables use the internet, they can be termed as ‘Internet of Things’. This cluster has a total variance of 53.280%, making it the highest-ranked method to improve construction information management. Cluster 2 has three (3) variables loaded onto it, and these variables include ‘Adoption of onsite wearables’ (84.0%), ‘Usage of mobile device management’ (66.7%) and ‘Usage of smart Sensor devices’ (40.5%). These variables relates to devices that can be easily handled. Therefore, the cluster is termed ‘Hand-held Devices’ with a variance of 5.465%, which makes it the third classification of the methods of improving construction information management. Eleven factors loaded to this cluster are “Usage of innovative materials’, ‘Artificial intelligent application’, ‘Quantum computing application’, ‘Usage of autonomous vehicle’, ‘Adoption of 5G network’, ‘Usage of robots’, ‘Adoption augmented reality Table 1 Identified methods of managing construction information Identified methods

Mean

Std. Deviation

R

Usage of smart sensor devices

4.97

0.177

1

Adoption augmented reality technology

4.96

0.235

2

Incorporation of building information modelling

4.96

0.198

2

Usage of big data

4.96

0.235

2

Usage of innovative materials

4.96

0.235

2

Implementation of blockchain-based BIM

4.95

0.250

6

Artificial intelligent application

4.95

0.250

6

Usage of mobile device management

4.94

0.232

8

Usage of cloud storage

4.94

0.247

8

Usage of robots

4.92

0.395

10

Usage of autonomous vehicle

4.92

0.374

10

Adoption of onsite wearables

4.92

0.273

10

Quantum computing application

4.91

0.338

13

Adoption of 5G network

4.91

0.383

13

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Table 2 Pattern and structure matrix of the methods Pattern matrix factor

Structure matrix factor

1

1

2

Usage of innovative materials

0.928

0.901

Artificial intelligent application

0.833

0.846

Quantum computing application Usage of autonomous vehicle Adoption of 5G network usage of robots Adoption augmented reality technology

0.829

0.838

0.825

0.826

0.735

0.821

0.733

0.789

0.731

0.782

0.713

0.752

Implementation of blockchain-based BIM Usage of big data

0.706

0.725

Incorporation of building information modelling

0.639

0.671

Usage of cloud storage

0.508

0.541

2

Adoption of onsite wearables

0.840

0.915

Usage of mobile device management

0.667

0.682

Usage of smart sensor devices

0.405

0.566

Extraction method: principal axis factoring Rotation method: oblimin with kaiser normalization a. Rotation converged in 13 iterations

technology’, ‘Implementation of blockchain-based bim’, ‘Usage of big data’, ‘Incorporation of building information modelling’ and ‘Usage of cloud storage’ with a total variance of 53.280%. The findings are consistent with those made by Ayaz et al. (2019), who claim that the term "Internet of Things" (IoT) has recently become more popular as an application. This essentially refers to the use of mechanical hardware, or the Internet of Things, and sophisticated web programming during the development phase in order to have the option to increase the task’s viability. Use of IoT in the construction industry is solely to ensure optimal use of the resources available with proper mechanical preparation, at controlled prices, and with minimal and low risks by applying innovative-based devices and hardware (Adekunle, et al. 2022a). Construction companies are adopting new strategies, methods, and innovations to work more effectively and address the major development business issues as the population grows and the industry develops naturally to meet the demands of the population. IoT allows for a location where the equipment, supplies, and personnel are coordinated to a central server that monitors and manages their activity gradually, ensuring conformity to the most recent pre-planned development data (Yang and Maxwell 2011). In the construction data industry nowadays, there are a ton of devices being developed and operated for various purposes. The development industry is adopting these new innovation and network techniques, but it is far from an underappreciated fact that these final components are undergoing a somewhat

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slower shift. Many developers and contractors lack knowledge about investing in such devices because they fail to recognize their significance (Forell et al. 2011). Yet, when used properly and with awareness, these tools will play a significant role in creating a space where everything is made accessible to a central room and is being documented. Development can prosper with information and technological tools. The implementation of these emerging innovations will fundamentally alter the nature of the firm. The result confirms that IoT tools can support development companies in influencing ongoing information to help them succeed. Three factors loaded to this cluster are ‘Adoption of onsite wearables’, ‘Usage of mobile device management’ and ‘Usage of smart Sensor devices’ with a total variance of 5.465%. These elements are similar in that they are all compact computers that typically weigh under two pounds. Through the integration of handheld devices, workers may manage their duties even while they are not in the office by giving them access to the relevant information (Adekunle et al. 2022b). According to Zervoudi (2020) a portable device complies with official requirements for resource and records management, protection, security, and information interchange as well as government policy. The key feature of the product is its ability to mechanically integrate cell phones into business designs. When done the hard way, it can be a lengthy procedure, but it is full of small errors as opposed to the conventional or manual framework. Remote access makes it simple to get, update, and manage various gadgets with a computerized interaction. A handheld device’s programming may include stock, security, and board programming modules, as well as permission and appropriation strategies. Authorization of strategies is crucial for protecting crucial business data resources. The necessary arrangements, including as encryption, information management, and access restrictions, must be established and defined as a result. So, this serves as a technique for improving construction data management.

5 Conclusion From the reviewed literature, methods to improve construction information management includes usage of smart sensor devices, adoption of augmented reality technology, incorporation of building information modelling, usage of big data, usage of innovative materials, implementation of blockchain-based BIM, artificial intelligent application, usage of mobile device management, usage of cloud storage, usage of robots, usage of autonomous vehicle, adoption of onsite wearables, among others. Primary data retrieved from respondents revealed that factors categorised as “internet of things” are the most proficient methods of improving construction information management. These factors are: usage of innovative materials, artificial intelligent application, quantum computing application, usage of autonomous vehicle, adoption of 5G network, usage of robots, adoption augmented reality technology, implementation of blockchain-based BIM, usage of big data, incorporation of building information modelling and usage of cloud storage. Respondent ranked the following as the most important methods of improving construction

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information management: usage of innovative materials, artificial intelligent application, quantum computing application, usage of autonomous vehicle, adoption of 5G network, usage of robots, adoption augmented reality technology, implementation of blockchain-based BIM, usage of big data and incorporation of building information modelling. The aforementioned conclusions showed that it is impossible to quantify the contributions that construction information management makes to successful and efficient service delivery. The results also showed that various techniques included in 4IR tools can aid in enhancing construction information management. The significance of incorporating these into construction methods has been acknowledged as a crucial element in the development of the construction sector. The respondents believed that the integration of these tools will increase the performance of the construction industry by about 100% since job experiences give students firsthand understanding of the needs of the business. Hence, in order to fully integrate these technologies in construction processes, professional construction bodies must encourage and supply the appropriate rules and working ethics. Using these techniques would also enable the construction sector to become a technology-driven sector and catch up with other sectors, particularly the manufacturing sector, which has advanced in effectively implementing Industry 4.0.

References Adekunle P, Aigabvboa C, Thwala W, Akinradewo O, Oke A (2022) Challenges confronting construction information management. Front Built Environ 8. https://doi.org/10.3389/fbuil. 2022.1075674 Adekunle P, Aigbavboa C, Akinradewo O, Oke A, Aghimien D (2022) Construction information management: benefits to the construction industry. Sustainability 14(18):11366. https://doi.org/ 10.3390/su141811366 Adekunle P, Aigbavboa C, Thwala D, Oke A, Akinradewo O (2022) Construction information management: the role of fourth industrial revolution tools. Human Factors in Architect Sustain Urban Plann Infrastruct 58(Cim):254–261. https://doi.org/10.54941/ahfe1002359 Autor DH (2015) Why are there still so many jobs? the history and future of workplace automation. J Econom Perspect 29(3):3–30. https://doi.org/10.1257/jep.29.3.3 Ayaz M, Ammad-Uddin M, Sharif Z, Mansour A, Aggoune EHM (2019) Internet-of-things (IoT)based smart agriculture: toward making the fields talk. IEEE Access 7:129551–129583. https:// doi.org/10.1109/ACCESS.2019.2932609 Delgado JMD, Oyedele L, Ajayi A, Akanbi L, Akinade O, Bilal M, Owolabi H (2019) Robotics and automated systems in construction: understanding industry-specific challenges for adoption. J Build Eng 26(1):100868. https://doi.org/10.1016/j.jobe.2019.100868 Forell T, Milojicic D, Talwar V (2011) Cloud management: challenges and opportunities. In: IEEE international symposium on parallel and distributed processing workshops and Phd forum, pp 881–889.https://doi.org/10.1109/IPDPS.2011.233 Froese TM (2010) The impact of emerging information technology on project management for construction. Automat Construct 19(5):531–538. https://doi.org/10.1016/j.autcon.2009.11.004 Harris MA, Patten KP (2014) Mobile device security considerations for small- and medium-sized enterprise business mobility. Inf Manag Comput Secur 22(1):97–114. https://doi.org/10.1108/ IMCS-03-2013-0019

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Kanamori Y, Yoo S-M (2020) Quantum computing: principles and applications. J Int Technol Inf Manag 29(2):43–71. https://doi.org/10.58729/1941-6679.1410 Reaves J (2019) 21st-Century skills and the fourth industrial revolution: a critical future role for online education. Int J Innov Online Educ 3(1). https://doi.org/10.1615/intjinnovonlineedu.201 9029705 Yang TM, Maxwell TA (2011) Information-sharing in public organizations: a literature review of interpersonal, intra-organizational and inter-organizational success factors. Governm Inform Quarter 28(2):164–175. https://doi.org/10.1016/j.giq.2010.06.008 Yeboah-Boateng EO, Essandoh KA (2014) Factors influencing the adoption of cloud computing in small and medium enterprises in Jordan. Int J Cloud Appl Comput 2(4):96–110. https://doi.org/ 10.4018/IJCAC.2020070106 Zervoudi EK (2020) Fourth industrial revolution: opportunities, challenges, and proposed policies. In: Grau A, Wang Z (eds) Industrial robotics—new paradigms, pp 1–25. https://doi.org/10.5772/ intechopen.90412

Incorporating Cryptocurrency Platforms for Advancing Financial Transaction Within the Construction Industry Peter Adekunle, Clinton Aigbavboa, Opeoluwa Akinradewo, Kenneth Otasowie, and Samuel Adekunle

Abstract Cryptocurrency is a digital or virtual currency that is secured by cryptography, which makes it nearly impossible to counterfeit or double-spend. Many cryptocurrencies are decentralized networks based on blockchain technology, a distributed ledger enforced by a disparate network of computers. In this era of digital revolution that is aimed at increasing transparency and lowering operational cost, it is essential to incorporated digital finance into the construction industry. The aim of this study is to examine the usability of cryptocurrency platforms for financial transactions in the built environment. In order to collect information from architects, civil engineers, quantity surveyors, mechanical and electrical engineers, construction managers, and project managers, the study used a quantitative survey technique with the use of a questionnaire. With the help of SPSS, the data were analyzed, and the appropriate measure of dispersion and inferential statistics were used. The study revealed the professionals within the built environment agrees that Cryptocurrency platform like avalanche, ethereum, solano, polkadot can serve as a medium of financial transaction within the built environment. The findings also revealed that because they do not use third-party intermediaries, cryptocurrency transfers between two transacting parties are faster as compared to standard money transfers. The study therefore concluded that the use of cryptocurrency platforms should be encourage as it can serve as access to new capital for construction establishments. Keywords Digital finance · Cryptocurrency platform · Financial transaction

1 Introduction The alternative payment method known as cryptocurrency was developed utilizing encryption techniques (Rose 2015). Because of the use of encryption technology, cryptocurrencies can act as both a medium of exchange and a virtual accounting system. A cryptocurrency wallet is required in order to use cryptocurrencies (Flamur P. Adekunle · C. Aigbavboa · O. Akinradewo · K. Otasowie · S. Adekunle Faculty of Engineering and the Built Environment, Cidb Centre of Excellence, University of Johannesburg, Johannesburg 2006, South Africa © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024 K. Papadikis et al., Towards a Carbon Neutral Future, Lecture Notes in Civil Engineering 393, https://doi.org/10.1007/978-981-99-7965-3_42

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et al. 2017). These wallets might be software that is downloaded to a computer or mobile device, or they can be cloud-based services. The wallets are the device used to hold the encryption keys used to verify the user’s identity and connection to cryptocurrencies. The most popular approach to begin trading cryptocurrencies and other digital assets is by doing so through crypto exchanges. Private platforms known as cryptocurrency exchanges enable the exchange of cryptocurrencies for other cryptoassets, such as digital and fiat currencies (Brandvold et al. 2015). Peer-to-peer technology makes it possible for anybody, anywhere, to send and receive payments. Payments made using cryptocurrencies do not exist as actual physical coins that can be transported and exchanged; rather, they only exist as digital entries to an online database that detail individual transactions. When cryptocurrency is used for payment transfers, the transactions are visible to everyone. Digital wallets are where cryptocurrency is kept. Due to the fact that transactions are verified using encryption, cryptocurrency has earned its moniker. This means that the storage, transmission, and recording of bitcoin data to public ledgers all entail sophisticated code. Encryption’s goal is to offer security and protection. Financially speaking, cryptocurrency applications are still developing, and more applications are anticipated in the future. In the future, financial transactions involving bonds, stocks, construction companies, and other types of business could be completed utilizing this technology. Companies in the construction industry are different from most other businesses and confront a variety of particular difficulties that are not experienced by businesses in other sectors (Qin and Ofori 2000). Buildings, roads, and other structures are constructed rather than most other items, even though the construction sector produces a product much like the manufacturing industry does. The financial management methods used in other product-producing businesses frequently need to be changed before being used to the construction industry due to these distinctive qualities; otherwise, they are useless Furthermore, due to the nature of the work, revenue recognition, per-project pricing, job costing, changeable operational costs, and other features of construction projects, financial management for the construction sector is more complicated than it is for other firms (Enshassi et al. 2015). Many criteria are dealt with by construction companies. Hence, they must be able to manage prevailing wage regulations, bid on projects, track precise expenses, and perform a variety of other accounting duties. The introduction of centralized exchange-facilitated crypto transactions can effectively and efficiently do this. The use of cryptocurrencies as a form of payment has been discussed in numerous studies, but the built environment has received less attention. Utilising cryptocurrency platforms has a number of advantages, including protection from inflation, self-governance and management, a decentralized system, and a cost-effective mode of exchange. As there are numerous financial transactions occurring within the construction ecosystem, stakeholders in the industry can also benefit from these advantages. So therefore, by sampling the opinions of construction professionals on the use of various cryptocurrency platforms, this study aims to assess the incorporation of cryptocurrencies for financial transactions inside the built environment.

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2 Literature Review By enabling trustworthy transactions to take place through a decentralized system even between anonymous parties, cryptocurrency, which was first introduced by a mysterious developer named Satoshi Nakamoto, has changed the current financial system (Lee 2019). Cryptocurrencies are intended to revolutionize how financial transactions are carried out online and serve as the underlying technology foundation for the development of a new financial and economic system. With the help of peer-to-peer (P2P) network users, transaction details are exchanged and validated in the distributed ledger system known as cryptocurrency (Siano et al. 2019). Existing blocks can be updated once they have been added to the chain with the transaction information verified by the network’s consensus mechanism. The requirement for a reliable central authority is removed because all transactions inside a crypto system are verified and recorded by consensus of the network nodes. One example of the successful use of digital money—the first worldwide decentralized financial system—is cryptocurrency. It is anticipated that as cryptography advances, digital currency will increase its disruptive potential by tokenizing and decentralizing not only money but also other corporate assets. By distributing encrypted data across network participants, cryptocurrency aims to increase information security and transparency (Nawari and Ravindran 2019). Cryptocurrency is a perfect fit for the financial industry since it places a strong focus on security and trust; nevertheless, up until recently, its public acceptance remained rather low. Cryptocurrency blockchains are based on P2P networks, and anytime a transaction takes place, the consensus process verifies it. The block will contain details on transactions that have been deemed legal by the network agreement, and a node that mines the block will be compensated with the adopted coin. Bitcoin, avalanche, cardano, etherum, poladot, solano, binance smart chain, klatyn, ripple, stellar, or tezos are some of the cryptocurrency options (Sandri et al. 2022). Even in the absence of an intermediary or third party, transactions between anonymous network members remain trustworthy. With the creation of crypto, the financial digital revolution that began with the birth of the internet has now entered a new stage of development. A new crypto-based internet will usher in a period of the internet of value, which will reshape existing business models through improved transparency and reliability of information and transactions. The pre-crypto internet was dedicated to its internet of information function, which merely connects information providers with the consumers who use it. The development of cryptocurrencies will assist in achieving a more impartial and fair consensus through a decentralized procedure that prohibits one institution from having information monopoly. The efficacy and efficiency of cost management are anticipated to increase significantly when cryptocurrency platforms are integrated into financial transactions inside the built environment.

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3 Methodology Incorporating cryptocurrency platforms to advance financial transactions in the construction sector is the subject of this study. For the sake of objectivity, survey research was performed for this aim, and questionnaires were used to collect data from respondents using a quantitative approach. The target audience for this study consisted of those involved in the built environment in the Gauteng province of South Africa, including clients (government, private organizations, and individuals) and construction professionals (civil engineers, construction managers, project managers, architects, and quantity surveyors). The poll was conducted in the province of Gauteng because it is one of South Africa’s most developed. A structured questionnaire utilized in the study was based on one used by Adekunle et al. (2022). The questionnaire was divided into two sections: one section was devoted to gathering background information about the respondent, and the other section contained a wealth of cryptocurrency platforms that were extracted from literature and used to gauge the respondents’ level of support for incorporation. A total of 110 questionnaires were given out to respondents, and 98 of those were returned, representing a response rate of 89.09%. One sample t-test was utilized to ascertain the relative importance of each cryptocurrency site and its significance level. The background data was analysed using percentage and frequency, whereas mean item score (MIS) was used in the ranking of the cryptocurrency platforms.

4 Discussion of Findings According to the report, 37 percent of respondents are clients, followed by 9.3% architects, 9.7% civil engineers, 10.1% project managers, 15.6% construction managers, and 18.3% quantity surveyors. One to five years of construction-related work experience is held by 35.5% of respondents, and six to ten years of work experience is held by 40.2%. While 18.8% of respondents had worked in the construction business for at least 16 years or more, only 5.5% of the population had experience of between 11 and 15 years. Platforms found through a review of the literature were offered to the respondent to score according to their level of agreement for such platform to be adopted, with the goal of examining the incorporation of cryptocurrency platforms for financial transactions within the built environment. The results of a one-sample t-test were then used to determine whether the respondents thought a particular platform should be adopted or not. To provide a comprehensive picture of the respondents’ responses, the means of each platform were sorted and tabulated in Table 1. The summary of the test results is also shown in Tables 1 and 2, and it includes the mean for each detected cryptocurrency platform as well as the standard deviation and standard error. Each cryptocurrency platform had a null hypothesis that it shouldn’t be included (H0: U = U0), and an alternative hypothesis that it should be (Ha: U > U0), where U0

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is the population mean, which was set at 3.5. A driver of mentoring practices was considered to be demonstrated if it had a mean of 3.5 or more on the 5-point Likert rating scale, which was set at 95% in accordance with the usual risk level. The mean with the lowest standard deviation was given the top rating of the exhibition in the case that two or more drivers share the same mean (Otasowie and Oke 2022). The one-sample t-test results show that all of the cryptocurrency platforms recommended for use in built-environment financial transactions should be implemented. Tezos is currently the top cryptocurrency platform, supporting the assertion made by Allouche et al. (2021) that Tezos is becoming more and more well-liked by investors around the world. With the use of technology and industry, cryptocurrencies like Tezos are gaining an advantage over rivals for other cryptocurrency platforms. It is simple to transfer money using Tezos without the intervention of banks or other financial institutions (Bamakan et al. 2022). Etherum, Binance Snartchain, Klatyn, and Bitcoin are some further top-rated platforms. Several currencies lose value as a result of inflation. Financial stakeholders believe that a cryptocurrency platform can provide inflation protection (Abubakar et al. 2019). There is a hard cap on the total amount of coins that will ever be issued for Ethereum, Binance, and Bitcoin. For instance, the price of cryptocurrency will rise when the money supply grows faster than the supply of cryptocurrencies (Ciaian et al. 2018). The same approach is used by several cryptocurrency platforms to limit supply and prevent inflation. Hence, as a result of a surge in demand, the value will increase, which may allow it Table 1 One-sample test of the cryptocurrency platforms Test value = 3.5 t

df

Significance

Mean Difference

One-sided p

Two-sided p

95% Confidence interval of the difference Lower

Upper

Tezos

41.821

98