Sustainability in Energy and Buildings 2020 (Smart Innovation, Systems and Technologies, 203) [1st ed. 2021] 9811587825, 9789811587825

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Smart Innovation, Systems and Technologies 203

John Littlewood Robert J. Howlett Lakhmi C. Jain   Editors

Sustainability in Energy and Buildings 2020

Smart Innovation, Systems and Technologies Volume 203

Series Editors Robert J. Howlett, Bournemouth University and KES International, Shoreham-by-sea, UK Lakhmi C. Jain, Faculty of Engineering and Information Technology, Centre for Artificial Intelligence, University of Technology Sydney, Sydney, NSW, Australia

The Smart Innovation, Systems and Technologies book series encompasses the topics of knowledge, intelligence, innovation and sustainability. The aim of the series is to make available a platform for the publication of books on all aspects of single and multi-disciplinary research on these themes in order to make the latest results available in a readily-accessible form. Volumes on interdisciplinary research combining two or more of these areas is particularly sought. The series covers systems and paradigms that employ knowledge and intelligence in a broad sense. Its scope is systems having embedded knowledge and intelligence, which may be applied to the solution of world problems in industry, the environment and the community. It also focusses on the knowledge-transfer methodologies and innovation strategies employed to make this happen effectively. The combination of intelligent systems tools and a broad range of applications introduces a need for a synergy of disciplines from science, technology, business and the humanities. The series will include conference proceedings, edited collections, monographs, handbooks, reference books, and other relevant types of book in areas of science and technology where smart systems and technologies can offer innovative solutions. High quality content is an essential feature for all book proposals accepted for the series. It is expected that editors of all accepted volumes will ensure that contributions are subjected to an appropriate level of reviewing process and adhere to KES quality principles. Indexed by SCOPUS, EI Compendex, INSPEC, WTI Frankfurt eG, zbMATH, Japanese Science and Technology Agency (JST), SCImago, DBLP. All books published in the series are submitted for consideration in Web of Science.

More information about this series at http://www.springer.com/series/8767

John Littlewood Robert J. Howlett Lakhmi C. Jain •

•

Editors

Sustainability in Energy and Buildings 2020

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Editors John Littlewood School of Art and Design, The Sustainable and Resilient Built Environment group Cardiff Metropolitan University Cardiff, UK Lakhmi C. Jain Liverpool Hope University Liverpool, UK

Robert J. Howlett ‘Aurel Vlaicu’ University of Arad Arad, Romania Bournemouth University Poole, UK KES International Sussex, UK

University of Technology Sydney Sydney, Australia KES International Sussex, UK

ISSN 2190-3018 ISSN 2190-3026 (electronic) Smart Innovation, Systems and Technologies ISBN 978-981-15-8782-5 ISBN 978-981-15-8783-2 (eBook) https://doi.org/10.1007/978-981-15-8783-2 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

International Programme Committee

Prof. Mohamed Abbas, UDES/CDER, Algeria Dr. Kouzou Abdellah, Djelfa University, Algeria Prof. Abdel Ghani Aissaoui, University of Bechar, Algeria Dr. Mahmood Alam, University of Brighton, UK Dr. Martin Anda, Murdoch University, Australia Dr. Jo Atkinson, The Active Building Centre, UK Prof. Ahmad Taher Azar, Prince Sultan University, Kingdom of Saudi Arabia, Saudi Arabia Assoc. Prof. Messaouda Azzouzi, University of Djelfa, Algeria Dr. Magdalena Baborska-Narozny, Wroclaw University of Science and Technology, Poland Miss. Hannah Baker, University of Cambridge, UK Dr. Julius Bañgate, Université Le Havre, France Dr. Andrea Bartolucci, Université Clermont, France Ms. Anna Kate Becker, Clemson University, USA Dr. Pablo Benitez, National University of Itapúa, Paraguay Assoc. Prof. Umberto Berardi, Ryerson University, Canada Dr. Gabriele Bernardini, Università Politecnica delle Marche, Italy Dr. Stephen Berry, University of South Australia, Australia Assistant Professor Trevor Butler, Athbasca University, Canada Assoc. Prof. Alfonso Capozzoli, Politecnico di Torino, Italy Dr. Penny Carey, Potakabin, UK Dr. Stefano Cascone, University of Catania, Italy Prof. Francesco Causone, Politecnico di Milano, Italy Dr. Boris Ceranic, University of Derby, UK Prof. Christopher Chao, the University of Hong Kong, Hong Kong Dr. Giacomo Chiesa, Politecnico di Torino, Italy Prof. Dulce Coelho, Polytechnic Institute of Coimbra, ISEC, Portugal Dr. John Cosgove, The Limerick Institute of technology, Ireland Dr. Alessandro D’Amico, Sapienza Università di Roma, Italy Lorenzo Diana, Università di Napoli Federico II, Italy v

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International Programme Committee

Dr. Mahieddine Emziane, MIST, UAE Dr. Diana Enescu, Valahia University of Targoviste, Romania Prof. Youssef Errami, Chouaib Doukkali University, Morocco Prof. Najib Essounbouli, Université de Reims Champagne Ardenne, France Dr. Stefano Fantucci, Politecnico di Torino, Italy Dr. Fatima Farinha, Universidade do Algarve, Portugal Dr. Tiago Miguel Ferreira, University of Minho, Portugal Prof. Donal Finn, University College Dublin, Ireland Dr. Anastasia Fotopoulou, University of Bologna, Italy Prof. Antonio Gagliano, University of Catania, Italy Prof. Waldo Gallo, VUB Architectural Engineering, Belgium Prof. Andrew Geens, The Chartered Institute of Building Services Engineers, UK Prof. George E. Georghiou, University of Cyprus, Cyprus Prof. Roberto Giordano, Politecnico di Torino, Italy Dr. Elisa Di Giuseppe, Università Politecnica delle Marche, Italy Dr. Morten Gjerde, Victoria University, New Zealand Professor Chris Gorse, Leeds Beckett University, UK Prof. Dr.-Ing. Lars-O. Gusig, University of Applied Sciences and Arts Hannover, Germany Dr. Carolyn Hayles, Cardiff Metropolitan University, UK Dr. Pieter Herthogs, Swiss Federal Institute of Technology (ETH), Switzerland Professor Bob Howlett, University of Bournemouth, UK Dr. Mohammad Arif Kamal, Aligarh Muslim University, India Prof. George Karani, Cardiff Metropolitan University, UK Prof. Khalil Kassmi, Mohamed Premier University, Morocco Prof. Mohanlal Kolhe, University of Agder, Norway Prof. Sumathy Krishnan, North Dakota State University, USA Dr. Andreja Kutnar, University of Primorska, Slovenia Dr. Domagoj Leskarac, Planet Ark Power, Australia Dr. John Littlewood, Cardiff Metropolitan University, UK Dr. Ruggiero Lovreglio, Massey University, New Zealand Dr. Sebastiano Maltese, Scuola Universitaria, Italy Prof. Noureddine Manamani, University of Reims, France Prof. Ahmed Mezrhab, University Mohammed 1, Morocco Dr. Mojtaba Moghimi, Jacobs Engineering, USA Mr. Jon Moorhouse, University of Liverpool, UK Dr. Michele Morganti, Politecnico di Milano, Italy Dr. Federica Naspi, Università Politecnica delle Marche, Italy Ms. Consuelo Nava, Mediterranea University, Italy Prof. Francesco Nocera, University of Catania, Italy Dr. Graham Ormondroyd, Bangor University, UK Mr. Emeka Efe Osaji, Leeds Beckett University, UK Dr. Poorang Piroozfgar, University of Brighton, UK Prof. Joao Ramos, Polytechnic Institute of Leiria, Portugal Dr. Eric Roberts, Integrated environmental Solutions Ltd, UK

International Programme Committee

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Prof. Fernanda Rodrigues, University of Aveiro, Portugal Prof. Alessandro Rogora, Politecnico di Milano, Italy Assoc. Prof. Brandon Ross, Clemson University, USA Federica Rosso, Sapienza Università di Roma, Italy Dr. Atul Sagade, Renewable Energy Innovation and Research Foundation, India Dr. Masoud Sajjadian, Edinburgh Napier University, UK Dr. Fausto Sanna, Cardiff metropolitan University, UK Prof. Wilfried Sark, Utrecht University, The Netherlands Prof. Gaetano Antonio Sciuto, University of Catania, Italy Dr. Geraldine Seguela, University of Technology Sydney, Australia Prof. Begum Sertyesilisik, Izmir Democracy University, Turkey Associate Professor Magda Sibley, Cardiff University, UK Dr. Fabiana Silvero Prieto, National University of Itapua, Paraguay Professsor Luca Spalazzi, à Politecnica delle Marche, Italy Dr. Morwenna Spear, Bangor University, UK Dr. Sascha Stegen, Griffith University, Australia Prof. Fionn Stevenson, University of Sheffield, UK Prof. Edward Szczerbicki, University of Newcastle, Australia Prof. Ahmed Tahour, University of Mascara, Algeria Dr. Ali Tahri, University of Sciences and Technology of Oran, Algeria Dr. Anne Templeton, University of Edinburgh, UK Prof. Horia-Nicolai Teodorescu, Institute of Computer Science, Romania Professor Andrew Thomas, University of Aberystwyth, UK Dr. Linda Toledo, UK Dr. Simon Tucker, Liverpool John Moores University, UK Miss. Maria Unuigbe, Leeds Beckett University, UK Prof. Mummadi Veerachary, Indian Institute of Technology, India Prof. Romeu Vicente, University of Aveiro, Portugal Diana Waldron, Cardiff Metropolitan University, UK Dr. Simon Walters, University of Brighton, UK Dr. Water Wayne, Wayne State University, USA Paul Wilgeroth, Cardiff Metropolitan University, UK Professor Sara Wilkinson, University of Technology Sydney, Australia Amber Wismayer, University of Bath, UK Prof. Smail Zouggar, University Mohammed first Oujda, Morocco

Preface

The 12th International Conference on Sustainability and Energy in Buildings 2020 (SEB-20) is a major international conference organised by a partnership made up of KES International and the Sustainable and Resilient Built Environment group, Cardiff Metropolitan University. SEB-20 invited contributions on a range of topics related to sustainable buildings and renewable energy and explored innovative themes regarding building adaptation responding to climate change. The aim of the conference was to bring together university researchers, government and scientific experts and industry professionals to discuss the minimisation of energy use and associated carbon emissions in buildings, neighbourhoods and cities; from a theoretical, practical, implementation and simulation perspective. The conference formed an exciting chance to present, interact and learn about the latest research and practical developments on the subject. For the first time, SEB-20 was organised through KES International’s Virtual Conference platform in response to the COVID-19 pandemic which rose to prominence in 2020. The conference featured two general tracks chaired by experts in the fields: • Sustainable and smart buildings • Sustainable energy technologies In addition, there were seven invited sessions proposed and organised by prominent researchers. It is important that a conference provides high-quality talks from leading-edge presenters. SEB-20 featured two keynote speakers: Prof. Steve Goodhew, University of Plymouth, Plymouth, UK; and Associate Prof. Umberto Berardi, Ryerson University, Toronto, Canada. The conference attracted submissions from around the world. Submissions for the full-paper track were subjected to a two-stage blind peer review process. With the objective of producing a high-quality conference, only the best of these were selected for presentation at the conference and publication in the Springer as book chapters. Submissions for the Short Paper Track were subjected to a ‘lighter-touch’ review and published in an online medium, but not in the Springer book. ix

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Thanks are due to the very many people who have given their time and goodwill freely to make SEB-20 a success. We would like to thank the members of the International Programme Committee who were essential in providing their reviews of the conference papers, ensuring appropriate quality. We thank the high-profile keynote speakers for providing interesting talks to inform delegates and provoke discussion. Important contributors to the conference were made by the authors, presenters and delegates without whom the conference could not have taken place, so we offer them our thanks. Finally, we would like to thank the administrative staff of KES International. It is hoped that you find the conference an interesting, informative and useful experience; and remain connected through the KES International Virtual Conference Experience. Cardiff, UK Arad, Romania/Poole, UK/Sussex, UK Liverpool, UK/Sydney, Australia/Sussex, UK

Dr. John Littlewood Prof. Robert J. Howlett Prof. Lakhmi C. Jain SEB-20 Conference Chairs

Contents

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Analysis of the Spatial Morphology Facing Wind Environment in Harbin Central Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Di Song, Ming Lu, and Jun Xing

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Thermal Comfort Assessment in an Administrative Area of an Industrial Building in Spain . . . . . . . . . . . . . . . . . . . . . . . . . . Iñigo Rodriguez, Xabat Oregi, and Jorge Otaegi

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The Performance Potential of Domestic Heat Pumps in a Temperate Oceanic Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . Richard O Hegarty, Oliver Kinnane, Donal Lennon, and Shane Colclough An Analysis of Design Support Tools for Circular Building Practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Charlotte Cambier, Waldo Galle, Camille Vandervaeren, Ineke Tavernier, and Niels De Temmerman Alternative Municipal Solid Waste Management Systems in Morocco: Energy Savings and GHG Emission Reduction . . . . . . M. Maaouane, S. Dobrović, S. Zouggar, and G. Krajačić

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Quantifying Adaptability of College Campus Buildings . . . . . . . . . Delaney E. McFarland, Brandon E. Ross, and Dustin Albright

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Energy Efficiency in School Buildings: The Need for a Tailor-Made Business Model . . . . . . . . . . . . . . . . . . . . . . . . . Dirk V. H. K. Franco, Janaina Macke, Marleen Schepers, Jean-Pierre Segers, Marijke Maes, and Evelien Cruyplandt

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CFD-Based Analysis of Heat Exchanging Performance of Rotary Thermal Wheels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 H. M. D. P. Herath, M. D. A. Wickramasinghe, A. M. C. K. Polgolla, R. A. C. P. Ranasinghe, and M. A. Wijewardane

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A Simulation Method for Studying Urban Heat Islands at the Urban Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Sara Shabahang, Brenda Vale, and Morten Gjerde

10 A Conceptual Framework for Interpretations of Modularity in Architectural Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 Ineke Tavernier, Charlotte Cambier, Waldo Galle, and Niels De Temmerman 11 Building Energy Simulation of 19th C Listed Dwellings in the UK: A Strategy to Propose and Assess Suitable Retrofit Interventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 Michela Menconi, Noel Painting, and Poorang Piroozfar 12 Can Circularity Make Housing Affordable Again? Preliminary Lessons About a Construction Experiment in Flanders Taking a Systems Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Waldo Galle, Wim Debacker, Yves De Weerdt, Jeroen Poppe, and Niels De Temmerman 13 Challenging Architectural Design Choices with Quantified Evaluations of the Generality and Adaptability of Plan Layouts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Camille Vandervaeren, François Denis, Waldo Galle, and Niels De Temmerman 14 Rapid Identification and Evaluation of Interventions for Improved Water Performance at South Africa Schools . . . . . . . 173 Jeremy Gibberd 15 Four Angles of Using Timber in Tall Buildings . . . . . . . . . . . . . . . 183 Seyed Masoud Sajjadian, Laura Tupenaite, and Chris Barlow 16 A Review of V2-X Solutions by Investigating Different Vehicle Energy Storage Solutions for Nearly Zero Energy Buildings . . . . . 195 Yasaman Balali and Sascha Stegen 17 Occupants’ Behavioral Analysis for the Optimization of Building Operation and Maintenance: A Case Study to Improve the Use of Elevators in a University Building . . . . . . . . . . . . . . . . . . . . . . . 207 Gabriele Bernardini, Elisa Di Giuseppe, Marco D’Orazio, and Enrico Quagliarini 18 Built Environment Resilience to Face Climate Change Effects In Paraguay’s Social Housing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 F. Silvero, M. Goiris, S. Montelpare, and F. Rodrigues

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19 Grid Export Reduction Based on Time-Scheduled Charging of Residential Battery Energy Storage Systems—A Case Study in Cyprus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 Nikolas G. Chatzigeorgiou, Yerasimos P. Yerasimou, Michalis A. Florides, and George E. Georghiou 20 Cross-Fertilization Between Architecture and Agricultural: A Circular Supply Chain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243 Jacopo Andreotti, Denis Faruku, and Roberto Giordano 21 Sensitivity Analysis for Resilient Safety Design: Application to a Bottleneck Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 Valentina Kurtc, Gerta Köster, and Rainer Fischer 22 Concept Design of a Solar Wind Turbine Blade . . . . . . . . . . . . . . . 265 Kathrin Schulte, Prasad Kaparaju, and Sascha Stegen 23 Collaborative Approach for Community Resilience to Natural Disaster: Perspectives on Flood Risk Management in Jakarta, Indonesia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275 Tri Mulyani Sunarharum, Mellini Sloan, and Connie Susilawati 24 Smart Materials for Adaptive Façade Systems. The Case Study of SELFIE Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285 Rosa Romano, Paola Gallo, and Alessandra Donato 25 Understanding Human Behaviors in Earthquakes to Improve Safety in Built Environment: A State of the Art on Sustainable and Validated Investigation Tools . . . . . . . . . . . . . . . . . . . . . . . . . . 297 Enrico Quagliarini, M. Lucesoli, and Gabriele Bernardini 26 Resilient and User-Centered Solutions for a Safer Built Environment Against Sudden and Slow Onset Disasters: The BE S2ECURe Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309 Enrico Quagliarini, Edoardo Currà, Fabio Fatiguso, Giovanni Mochi, and Graziano Salvalai 27 Morphological Systems of Open Spaces in Built Environment Prone to Sudden-Onset Disasters . . . . . . . . . . . . . . . . . . . . . . . . . . 321 M. Russo, M. Angelosanti, Gabriele Bernardini, E. Cantatore, A. D’Amico, Edoardo Currà, Fabio Fatiguso, Giovanni Mochi, and Enrico Quagliarini 28 SLow Onset Disaster Events Factors in Italian Built Environment Archetypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 Graziano Salvalai, Nicola Moretti, Juan Diego Blanco Cadena, and Enrico Quagliarini

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29 Biodiversity, Enabling Technologies and Resilient Tactics for Urban and Rural Scenarios in Transition in the Inner Areas of Calabria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345 Consuelo Nava and Giuseppe Mangano 30 A Proposed Method to Pre-qualify Sustainable Energy-Saving LED Luminaires for Outdoor Urban Lighting Applications . . . . . . 357 U. Thurairajah, J. R. Littlewood, and G. Karani 31 A Novel Approach to Controlling Outdoor Light Pollution by Adopting Smart Science and Technology to Improve Residents Quality of Life in the Built Environment . . . . . . . . . . . . . . . . . . . . 369 U. Thurairajah, J. R. Littlewood, and G. Karani 32 A Conceptual Methodology for Estimating Stored Sequestered Carbon in the Built Environment . . . . . . . . . . . . . . . . . . . . . . . . . . 381 Morwenna J. Spear, Callum A. S. Hill, and Colin Price 33 Fragility of Urban Systems Facing Flooding: Evaluation of Environmental and Social Risk in Antofagasta, Chile . . . . . . . . . 395 Paola Bravo, Massimo Palme, and Gabriella De Angelis 34 Sustainable Housing Units for Emergency: Innovative Materials and Construction Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407 Stefano Cascone, Antonio Gagliano, Francesco Nocera, Renata Rapisarda, and Gaetano Sciuto 35 Evaluation of Three Lighting Software in the Use of Different Light Intensity Spaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419 Eduardo Espinoza Cateriano, Judit Lopez-Besora, Antonio Isalgue Buxeda, Helena Coch Roura, and Isabel Crespo Cabillo 36 Can Architectural Delight Improve Concept Design and Human Sensory Response in Schools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431 P. Grant, J. R. Littlewood, and R. Pepperell 37 Thermal Bridge Analysis for Offsite Manufactured Closed Panel Timber Frame Walls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443 F. Zaccaro, J. R. Littlewood, and C. S. Hayles 38 An Urban Strategy for Adaptive Reuse: Learning from Industrial Heritage in Barcelona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 455 Catalina Valderrama Barrero, Gloria Serra-Coch, Carlos Alonso-Montolio, and Helena Coch 39 Piloting a Management and Evaluation Protocol for Occupant Quality of Life in Welsh Dwelling Retrofits . . . . . . . . . . . . . . . . . . 467 D. Jahic, J. R. Littlewood, and G. Karani

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40 Phytoremediation as Adaptive Design Strategy to Improve Indoor Air Quality. Experimental Results Relating to the Application of a Vertical Hydroponic Biofilter . . . . . . . . . . . 479 Tae-Han Kim, Byung-Ryul An, and Matteo Clementi 41 Heat Flux Balance in Mediterranean Climates: Thermal Insulation Location in Building Enclosures . . . . . . . . . . . . . . . . . . . 491 Natalia Ruiz-Llaneza, Carlos Alonso-Montolio, Antonio Isalgue, and Helena Coch 42 A Pilot Study Evaluating Offsite Manufacturing of Timber Frame Panels Using Lean Manufacturing Principles for Dwellings . . . . . . 503 V. Moorhouse, J. R. Littlewood, and E. Hale 43 UK Care Facilities: Is Climate Change Contributing to Overheating in Dwellings and a Cause of Concern in the Health of Vulnerable Adults . . . . . . . . . . . . . . . . . . . . . . . . . 515 M. Adlington and B. Ceranic 44 New Proposals for Sustainable Design: The Imitation Game as an Experience of Shared Co-design . . . . . . . . . . . . . . . . . . . . . . 527 Alessandro Rogora 45 The Role of Vegetation in Urban Comfort: Surface Temperature Assessment at Street Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 539 Judit Lopez-Besora, Carlos Alonso-Montolio, Antonio Isalgue, and Sayonara Benitez 46 Are We Ready to Evaluate the Smart Readiness of Australian Buildings? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 549 Elena Markoska, Subbu Sethuvenkatraman, Nebojsa Jakica, and Sanja Lazarova-Molnar 47 Earth Tubes—Clean-Tech Method for Improving Occupant Health and Comfort . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 561 T. J. Butler, J. R. Littlewood, and R. Howlett 48 Study on the Top Interface Optimal Design of Landscape Architecture: Case Study of Cold Region Museum Regeneration Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 571 Ligang Shi, Xinyu Cheng, Yuanxue Zhang, and Hongzhe Yan Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 585

About the Editors

Dr. John Littlewood graduated in Building Surveying holds a Ph.D. in Building Performance Assessment and is a Chartered Building Engineer. He is Head of the Sustainable and Resilient Built Environment group in Cardiff School of Art & Design at Cardiff Metropolitan University (UK). He coordinates three Professional Doctorates in Art & Design, Engineering and Sustainable Built Environment, plus contributing to teaching in Architectural Design & Technology. John’s research is industry focused, identifying and improving fire and thermal performance in existing and new dwellings, using innovative materials and construction and also improving occupant quality of life and thermal comfort. He has authored and co-authored 150 peer-reviewed publications and was also Co-Editor for the ‘Smart Energy Control Systems for Sustainable Buildings’ book published in June 2017. Dr. Robert J. Howlett is the Executive Chair of KES International, a non-profit organisation that facilitates knowledge transfer and the dissemination of research results in areas including intelligent systems, sustainability and knowledge transfer. He is a Visiting Professor at ‘Aurel Vlaicu’ University of Arad, Romania, and Bournemouth University in the UK. His technical expertise is in the use of intelligent systems to solve industrial problems. He has been successful in applying artificial intelligence, machine learning and related technologies to sustainability and renewable energy systems; condition monitoring, diagnostic tools and systems; and automotive electronics and engine management systems. His current research work is focused on the use of smart microgrids to achieve reduced energy costs and lower carbon emissions in areas such as housing and protected horticulture. Dr. Lakhmi C. Jain , Ph.D., M.E., B.E. (Hons), Fellow (Engineers Australia), is with the University of Technology Sydney, Australia, and Liverpool Hope University, UK. Professor Jain founded the KES International for providing a professional community the opportunities for publications, knowledge exchange, cooperation and teaming. Involving around 5,000 researchers drawn from

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universities and companies worldwide, KES facilitates international cooperation and generates synergy in teaching and research. KES regularly provides networking opportunities for professional community through one of the largest conferences of its kind in the area of KES.

Chapter 1

Analysis of the Spatial Morphology Facing Wind Environment in Harbin Central Area Di Song , Ming Lu, and Jun Xing

Abstract In this paper, the wind, which affects the urban microclimate environment, is selected as the research perspective, taking the central area of Harbin as an example, on the premise of extracting the basic parameters of space. The development of urban space form includes the selection and construction of analysis parameters in four aspects: building height, plane space, shape space, roof space, and so on. Then, it relies on the analysis of different land use types in order to clarify the basic characteristics of the canopy and underlying surface of urban space. The method formed in this paper will act on the parameterized interpretation of spatial morphology on the urban scale, which is convenient to provide the basic database and analogy basis for the subsequent numerical simulation and spatial design. Keywords Urban spatial form · Analytical method · Land type · Central area · Harbin (China)

1.1 Introduction In the urban construction, the buildings with high and low changes form a sharp contrast with the surrounding natural environment [1]. The artificial environment of dense buildings, streets, and bridges constitutes a special climate type [2]. From the perspective of urban meteorology, the urban canopy is an important influence area of urban wind field changes, which in turn affects the diffusion of atmospheric pollutants and energy conversion efficiency [3]. Therefore, it is necessary to accurately describe the spatial distribution of the urban canopy and the environmental characteristics of the underlying surface for urban planning, environmental management, and spatial model construction. At the same time, the huge amount of data generated by urban space also improves the convenience of analysis tools. D. Song (B) · M. Lu · J. Xing School of Architecture, Harbin Institute of Technology, Harbin 150006, China e-mail: [email protected] Key Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and Technology Ministry of Industry and Information Technology, Harbin 150006, China © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_1

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1.2 Literature Review From the perspective of aerodynamics, the obstruction of the urban canopy formed by high-density construction on wind is very obvious [4]. Therefore, there is a close relationship between the wind environment and the spatial form of the city. Theoretically, the assessment of wind attenuation trends is initially explained by the rough length (z0) and the zero-plane displacement (zd) [5]. Later, the windward area and wind speed ratio were introduced to evaluate the urban ventilation path [6], and then, the city’s ventilation performance was evaluated by the windward area density at different heights [7, 8]. Relying on building typology can reveal the problem of pollutant diffusion caused by high-density construction [9, 10] and improve the environmental improvement of buildings and street spaces by improving the windward area [11] and porosity [12] between buildings. For a city as a complex mega system, the spatial morphological characteristics can directly reflect the dense arrangement of urban buildings and the complexity of individual buildings. This can be achieved by the height, density, and surface size of the spatial structure [13]. In the city, T.R.Oke divides the spatial form into four types and corresponds to the urban density distribution [14]; at the same time, it is found that there is a correlation between wind flow patterns and building spacing in different cities [15]. Mohamed F. Yassin used different roof heights to illustrate the impact on canyon air quality in urban streets [16]. Francisco Toja-Silva et al. The ventilation sensitivity of the roof width and the ventilation effect of the roof distribution at different heights were studied [17]. Steven J. Burian and Michael J Brown developed three-dimensional spatial analysis of major US cities based on ten morphological parameters and correlated with the wind and heat environment. This result summarizes the differences in the morphological characteristics corresponding to different land types, which can be used as a reference for the analysis of spatial morphology at the mesoscale [18]. From the above studies, in the research discipline, the current explanation of urban space wind speed attenuation is mainly based on aerodynamic related parameters. From the perspective of research, a single parameter study can no longer explain the complex urban space, which needs to be comprehensively considered in terms of canopy height, distribution density, and physical differences caused by different use buildings. Based on the existing foundation, this study uses statistical and spatial analysis techniques to analyze the relevant parameters, providing an explanation of the urban spatial morphological characteristics and providing building distribution rules and morphological references for subsequent numerical simulations.

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Fig. 1.1 Analysis framework of urban spatial form

1.3 Methodology 1.3.1 Research Data Base In recent years, electronic map suppliers, including Baidu and Amap, have provided the possibility of information acquisition for buildings through the construction of three-dimensional panoramic maps. As shown in Fig. 1.1, the research obtained by the supplier to obtain the building and road grids for coordinate system conversion and packaged as GIS element files provides convenience for spatial morphology analysis. It should be noted that due to different map construction years and purposes, there are some errors in the data obtained, so it is necessary to review the outline and height of some buildings in combination with remote sensing images and field surveys. In addition, the urban land use refers to the eight types of main land properties listed in the national standard “Urban Land Classification and Planning and Construction Land Standards” to improve the information on the land and its attached buildings [19]. Finally, all the data are sorted, and various data including spatial points, lines, and planes are further extracted to jointly form urban spatial feature classes.

1.3.2 Parameter Selection Same as Fig. 1.1, the description of urban space form is carried out based on the elements of urban space, which is divided into four aspects: building height, plane space, shape space, and roof space. The main results are as follows: (1) Building height, which can directly explain the depth of the urban canopy that affects the atmosphere and in turn can explain the reason for the decrease in air

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velocity due to the heterogeneous distribution of the building. Therefore, the influence range of the urban canopy, the concentration area, and the change of its discrete degree are expressed through the extreme height, mean, standard deviation, and number of buildings in different sections. (2) Planar space, which can intuitively express the surface roughness on different urban cross sections. The surface roughness under the increase of building density also increases, and finally, a roughness threshold can be formed to produce effective resistance to air velocity. Therefore, the planar area fraction λp and the planar area density Ap (z) are introduced to express the change of urban surface roughness. (3) Shape space, which can intuitively reflect the surface area change brought by buildings with different functions and take this into consideration to express the wind speed resistance effect brought by different building shapes. Similarly, the vegetation, terrain, etc., in the site can also produce similar effects. Therefore, the surface area index λb and the complete aspect ratio λc are introduced as a summary of the changes in the rough area of the building and the rough area of the canopy. (4) Roof space. The significance of the roof area of urban buildings as a separate consideration is that the roof of the building not only represents the size of the rough element of the canopy formed at different heights, but also is an important part of urban heat exchange and affects the change of local wind. The combination changes of different forms of roofs will affect the ventilation effect of the building itself and the external space, so the roof area density Ar (z) is introduced to express the changes in roof area at different heights.

1.3.3 Methods of Analysis As shown in Table 1.1, according to the different expression intentions of the spatial morphological parameters, corresponding calculation methods and graphical expressions are constructed, respectively [20]. The research utilizes the advantages of ARCGIS platform in database space visualization, VB data script operation, and Excel function processing under complex rules, etc., to expand the data processing and spatial description of urban spatial forms.

1.4 Urban Spatial Morphology Analysis 1.4.1 Regional Overview Harbin is the capital of Heilongjiang Province and the highest latitude mega-city in China [21]. It has long winters and short summers and short springs and autumns. The cold and warm air alternates frequently, and the climate is complex and changeable.

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Table 1.1 Analysis method of urban spatial shape parameters Parameters

Operational explanation

Expression method

Height extreme value, mean value, standard deviation

Arithmetic mean, maximum (small) value, standard deviation of regional building height

AVERAGE command, sequential command, STDEVP command

Height interval and number

Number distribution of buildings in different heights

STDEV command

Plane area fraction λp

Ratio of the floor area of the building to the area of the site

ARCGIS-VB script operation

Plane area density Ap (z)

Area density is defined as the ratio of the plane area of the building to the area of the site in height increments

SUMIF function command

Surface area index λb

The ratio of the surface area of Analysis tools the building to the area of the site ARCGIS-VB script operation

Full aspect ratio λc

Ratio of all rough elements (building surface and other exposed features) to the site area

Analysis tools ARCGIS-VB script operation

Roof area density Ar (z)

Ratio of roof area to site area in height increment

SUMIF function command

The dominant wind direction throughout the year is the southwest wind, with an average wind speed of 2.5 m/s. Seasonal dominant wind directions are different in winter and summer. Low winter temperatures and high wind speeds aggravate the cold perception of the human body. In summer, the temperature and humidity are high, the wind speed is small, and the heat island effect is obvious, which is not conducive to human comfort [22]. Therefore, it has an overall impact on urban wind, and the rational use of research is of great value. The central area referred to by the institute is shown in Fig. 1.2 [23]. This area is the main political, economic, and cultural area of Harbin. Feature data was imported through ArcMap, and basic feature maps and statistical tables were formed. After approval by statistics and field surveys, the area contains 21,312 buildings with an area of 58.209 km2 . The building function is complex and large in quantity, including most types of useful land classifications. The land use statistics are shown in Table 1.2.

1.4.2 Building Height Analysis Overall, the study based on the national standard “General Rules for the Design of Civil Buildings” for the high classification of residential and other civil buildings is divided into six categories of height intervals and statistics [24]. As shown in the statistics in Fig. 1.3, the maximum value of the building in the central area is 3–173 m,

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Fig. 1.2 Urban spatial morphology parameters

the average height is 20.29 m, and the regional standard deviation is 18.85. From the perspective of proportional distribution, it is mainly that the height of buildings is in the range of 10–24 m. Buildings (low-rise and multi-storey) within this height range account for 70% of the total buildings, constitute the most impact was rough urban wind attenuation. In addition, due to the large number of high-rise residential buildings and commercial office buildings in recent years, more than 1,500 high-rise and super-tall buildings with more than 50 m in the central area will have a negative impact on the air flow in the higher range. Table 1.2 lists the building height statistics of various sites, the administrative office, culture, education, medical care, commercial business, and residential buildings are mostly distributed in multiple layers (less than 36 m), and the construction volume of high-rise buildings larger than 50 m in recent years has increased. Larger. Facilities such as sports, transportation stations, entertainment, industry, and logistics have a large base area, and the height is mostly below 24 m (multi-storey buildings). A very small number of buildings with large heights are used for office or entertainment purposes.

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Table 1.2 Analysis method of urban spatial shape parameters Land use nature

Code

Land area (km2 )

Amount

Average (m)

Height rang (m)

λp

λb

λc

Administration

A1

1.05

517

25.67

3–125

0.34

2.29

2.92

Culture

A2

0.51

94

16.52

3–171

0.25

1.11

1.67

Education and research

A3

5.96

2027

15.90

3–121

0.24

1.27

1.90

Physical culture

A4

0.61

124

12.91

3–33

0.23

0.87

1.31

Medical hygiene A5

0.82

424

17.94

3–103

0.31

1.68

2.22

Ancient artifacts A7

0.16

115

8.09

3–30

0.30

1.25

1.96

0.34

1.66

2.31

Religious facilities

A9

Business

B1

3.70

1970

20.64

3–120

0.40

2.35

2.88

Commercial affairs

B2

1.70

881

28.77

3–173

0.33

2.58

3.15

Entertainment

B3

0.38

238

10.68

3–90

0.42

2.39

2.96

Public facilities

B4

0.24

0.99

1.51

Other services

B9

0.36

1.71

2.35

Public park

G1

0.03

0.11

0.37

Protective green

G2

2.99

384

6.51

3–32

0.00

0.01

0.03

Square

G3

0.04

0.17

0.51

Regional traffic

H2

1.09

130

7.92

3–39

0.03

0.10

0.43

Military facility

H4

0.54

275

11.72

3–69

0.23

1.37

2.07

To be built

H9

2.22

809

9.16

3–86

0.35

1.50

1.98

Shanty Town

R3

0.40

1.31

1.84

Industry

M

1.17

394

13.98

3–104

0.36

1.47

2.00

City traffic

S

0.74

173

10.18

3–56

0.12

0.47

0.80

Residential

R2

26.56

12,571

22.51

3–166

0.33

2.19

2.79

Municipal facilities

U

0.32

186

12.54

3–67

0.32

1.63

2.31

Logistics facilities

W

0.34

1.34

2.00

1.4.3 Planar Spatial Analysis (1) Plane area fraction λp : The total area of the building base in the central area is 153,100 m2 , and the overall density is 0.26. Generally, the urban wind is prone to wake disturbance flow, which affects the area where the city’s downwind direction is located.

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Fig. 1.3 Statistical study overall height range

According to the statistics of the plane area scores of various types of land in Table 1.2, most of the λp values are in the range of prone to wake interference flow, administrative office, monuments and religion, commercial business, entertainment and recreation, industry, residence, Logistics has a relatively high flat area fraction. Other types of land use include a large number of buildings and also have green space or square distribution space λp value is slightly smaller. As shown in Fig. 1.4, most of the plots with isolated roughness flow are located in the city’s main broad roads and major urban green spaces. This part is also

Fig. 1.4 Central area fractional map

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Fig. 1.5 Urban area density map

often a better urban ventilation area. However, a very small number of skimming flow areas are mainly distributed in commercial buildings with dense layout and some un-demolition shanty towns. This part will make it difficult for the urban wind to enter the canyon formed by the building, resulting in poor local space ventilation, affect the comfort of the space. (2) Plane area density Ap (z): The statistical result is shown in Fig. 1.5. Before the building reaches the minimum building height of 3 m, its plane area is constant, which is equivalent to the constant crown roughness, starting from 4 to 30 m, building. The flat area decreases rapidly, the canopy roughness decreases, and the resistance to urban winds also drops significantly. From then on to the highest value of the building in the block, due to the decrease in the proportion of the plane area in the height of the area, the degree of decline in the resistance to the urban wind gradually slowed down and reached zero infinitely. The comparison of the Ap (z) values of various types of land is shown in Fig. 1.6. The administrative office, culture, education, medical care, commercial business, and residential buildings have a high span, a large initial density, and a rapid decline. Sports, monuments, and religious facilities are small in height, entertainment, health, public facilities and other facilities, transportation facilities, military facilities, municipal facilities, and logistics storage density are moderately low, with a slow decline. Green space, regional transportation facilities, low-density initial value is small, and the height changes gently and slowly declines.

1.4.4 Physical Space Analysis (1) Surface area index λb : According to Table 1.2 and Fig. 1.7, most of the building roughness elements are concentrated in the central area, which not only has resistance to urban winds, but also affects urban heat exchange. The areas with

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Fig. 1.6 Plane area density map of all kinds of land

Fig. 1.7 Surface area fraction diagram of central area

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large λb values mainly include the main commercial circles, high-rise residential areas and development areas in the city and also reflect the above areas with the greatest land value. (2) Complete aspect ratio λc : The magnitude of the λc value in the study range does not depend entirely on the surface area of the building in which the block is located. Covering trees or shrub sites is also an important part of its impact. Especially in residential areas, having green space near the house and central greening will also have some resistance to the wind environment [25]. At the same time, the appropriate green area can effectively alleviate the urban heat island effect. According to Table 1.2 and Fig. 1.8, most of the central region has a λc value in the range of 2.5–4, while the larger λc value is mainly located in the commercial center of the city and most of the high-rise residential areas. Administrative offices, commercial commerce, second-class residences, and medical buildings have relatively high λc values (more high-rise buildings). In the case of considering the three-dimensional surface area of greening, the value of residential, educational, and green land and other buildings will be further enhanced.

Fig. 1.8 Complete horizontal and vertical ratio map of the central area

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1.4.5 Roof Space Analysis The statistical results are shown in Fig. 1.9. A large portion of the roof area density is located between 3 and 35 m above the ground (multilayer and small high-rise dominated). Its value is below 3 m, indicating that no building height is less than 3 m (slightly below one floor). In contrast, high-rise buildings have a more uniform roof density distribution and less impact on wind speed. The variation of the roof area density of different nature land is shown in Fig. 1.10.

Fig. 1.9 Roof area density map

Fig. 1.10 Roof area density map of all kinds of land

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In comparison, the administrative office, education, medical, commercial business, residential buildings have a high span, and the roof density varies moderately. Cultural and transportation facilities have a large variation in density due to the presence of exhibition centers and train stations (extreme points). Sports, recreation and recreation, utilities and other facilities, military facilities, municipal facilities, logistics storage height changes and density changes are small. Green spaces, regional transportation facilities, and height and density are the smallest.

1.5 Discussion In this study, multi-parameter considerations are used to explain the spatial morphological changes, which can provide a statistical basis for subsequent models used in numerical simulation. Subsequent research will focus on the coupling relationship between parameters and urban wind to provide suitable spatial development suggestions. The limitation at this stage is that the current situation of the distribution of Chinese urban buildings is usually completed by the relevant surveying and mapping departments, and it is difficult to obtain the right of use due to the land transfer. Therefore, if follow-up research is carried out through cooperation with government departments, the accuracy of the research can be effectively improved. For the future of urban development, the construction of high-rise buildings will become the main method. The urban canopy will be higher, the building surface area will be larger, and the requirements for building form and spatial layout will be more precise. Therefore, the reasonable building form and the layout of the building group will have a more important impact on the effective air circulation in the city.

1.6 Conclusions This study builds statistical methods based on urban spatial morphological parameters to describe the characteristics of the current spatial morphology in Harbin and its impact on wind. Study the following conclusions: The research uses the GIS platform to build models and excel functions suitable for city-scale analysis, which can carry out effective statistical analysis. Harbin Center area as an example, the total urban canopy height 174 m. The height of the building is mainly concentrated within about 30 m above the underlying surface; the distribution of high-rise buildings in the central area of concentration, body building itself also creates urban wind Influence, surface area and the presence of ground objects increase the degree of obstruction. It is difficult to form a comfortable space on some property blocks due to the high density of the building. Most spatial patterns will have an impact on the downwind

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direction of the city. The existence of railways, roads, and green spaces in the city has facilitated air circulation. Acknowledgements This study was supported by the National Natural Science Foundation of China (No. 51878208).

References 1. Shuzhen, Z., Wei, S.: Urban Climatology. Meteorological Press (1994) 2. Xu, X.: Introduction to Urbanization Environmental Meteorology. Meteorological Press (1994) 3. Chong, S., Ao, S., Chunyan, T., Xiaolin, W., Lei, Li., Mingjie, W., Xunlai, C., Qi, F.: Simulation of influence of urban morphological parameters on boundary layer meteorological conditions. China Environ. Sci. 39(1), 72–82 (2019) 4. Li, T.: Research on Urban Wind Tunnel Construction and Planning Method Based on Urban Form and Surface Roughness. Master Thesis, Shenzhen University (2017) 5. Oke, T.R.: Boundary layer climates. Earth-Sci. Rev. 27(3), 265–265 (1987) 6. Wong, M.S., Nichol, J.E., To, P.H., et al.: A simple method for designation of urban ventilation corridors and its application to urban heat island analysis. Build. Environ. 45(8), 1880–1889 (2010) 7. Ng, E., Yuan, C., Chen, L., et al.: Improving the wind environment in high-density cities by understanding urban morphology and surface roughness: a study in Hong Kong. Landscape Urban Plann. 101(1), 59–74 (2011) 8. Yuan, C., Ren, C., Ng, E.: GIS-based surface roughness evaluation in the urban planning system to improve the wind environment—a study in Wuhan China. Urban Clim. 10, 585–593 (2014) 9. Yuan, C.: Building porosity for better urban ventilation in high-density cities—a computational parametric study. Build. Environ. 50, 176–189 (2012) 10. Yuan, C., Ng, E., Norford, L.K.: Improving air quality in high-density cities by understanding the relationship between air pollutant dispersion and urban morphologies. Build. Environ. 71, 245–258 (2012) 11. Li, A.: Research on Wind Environment of Central Harbin City Based on Roughness Theory. Master Thesis, Harbin Institute of Technology (2017) 12. Yaxing, D., Ming, M.C., Bo-Sin, T.: Effects of building height and porosity on pedestrian level wind comfort in a high-density urban built environment. Build. Simul. 11, 1215–1228 (2018) 13. Beixiang, S., Junyan, Y.: A large-scale spatial morphology analysis method based on GIS platform: taking the height, density and intensity of central areas of megacities as examples. Int. Urban Plann. 34(02), 111–117 (2019) 14. Yang, Y.: Research on the Relationship Between CFD Simulation Method and Texture Morphology of Wind Environment in Nanjing Residential Quarters Under the Theory of Urban Roughness. Master Thesis, Nanjing University (2012) 15. Oke, T.R.: Street design and urban canopy layer climate. Energy Build. 11(1–3), 103–113 (1988) 16. Yassin, M.F.: Impact of height and shape of building roof on air quality in urban street canyons. Atmos. Environ. 45(29), 5220–5229 (2011) 17. Toja, F., Lopez-Garcia, O., Peralta, C., et al.: An empirical–heuristic optimization of the building-roof geometry for urban wind energy exploitation on high-rise buildings. Appl. Energy 164, 769–794 (2016) 18. Burian, S.J., Velugubantla, S.P., Brown, M.J.: Morphological Analyses Using 3D Building Databases: Houston Texas. Los Alamos National Laboratory, NM (2003) 19. Code for classification of urban land use and planning standards of development land (GB50137–2011). National Standards of People’s Republic of China (2012)

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20. Song D, Lu M.: Research on urban spatial form for wind environment analysis—Taking Harbin’s main urban area as an example. In: Vibrant urban and rural Dwellings-Proceedings of the 2019 China Urban Planning Annual Meeting (05 Application of New Technologies in Urban Planning), pp. 767–782 (2019) 21. Feifei, Y.: Adjustment of city size division standards More than 10 million people are super-large cities. Stat. Manage. 2015(01), 96 (2015) 22. Sun, L.: Research on Harbin Riverside Residential District Design Strategy Based on Wind Environment Simulation. Master Thesis, Harbin Institute of Technology (2017) 23. Google 2020 HD Map-Google Online Satellite Map. https://www.ugucci.com 24. Uniform Standard for Design of Civil Buildings (GB 50352–2019). National Standards of People’s Republic of China (2019) 25. Wang, Z.H.: Monte carlo simulations of radiative heat exchange in a street canyon with trees. Sol. Energy 110, 704–713 (2014)

Chapter 2

Thermal Comfort Assessment in an Administrative Area of an Industrial Building in Spain Iñigo Rodriguez , Xabat Oregi , and Jorge Otaegi

Abstract This paper reports the indoor air operative temperature and relative humidity outcomes of a sixteen-month monitoring campaign of an administrative area in an industrial building in Tolosa (Spain). In a survey, users reported indoor climate dissatisfaction during the working hours, such as severe discomfort in the conference rooms due to excessive cold or overheating, poor indoor air quality or inadequate response of the HVAC systems. Internal operative temperatures and relative humidity have been analysed with and without environmental conditioning systems to study passive performance and effectiveness of active systems. These two parameters have been analysed in hourly intervals, during summer and winter periods. On the basis of the obtained data, the degree of thermal comfort of the users was evaluated, which allowed a comparison between the users’ self-reported perception obtained through surveys and the monitored data. Three different standards were used to assess thermal comfort, namely the European Standard UNE ISO 7730, the Spanish Regulations for thermal installations in buildings and the criteria established by the National Institute for Occupational Safety and Health. The study has made it possible to detect the main aspects that have a direct influence on user discomfort. Keywords Survey · Monitoring campaign · Thermal comfort · Operative temperature · Relative humidity

2.1 Objective of the Study This study will focus on assessing the thermal comfort of the administrative spaces (offices and meeting rooms) that are located within industrial buildings, which occupy a small surface area and have little productive weight in relation to the building as a whole. As a result, usually, aspects such as energy efficiency or thermal comfort of these rooms remain in the background to prioritize the productive optimization of the industrial process. In this case, the study focuses on evaluating different aspects I. Rodriguez (B) · X. Oregi · J. Otaegi CAVIAR Research Group, Department of Architecture, University of the Basque Country UPV/EHU, Plaza Oñati, 2, 20018 Donostia, San Sebastián, Spain e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_2

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related to the thermal comfort of the administrative areas of PANELFISA, a company dedicated to the manufacture of screws and other fastening elements using cold stamping. As a starting point, the work focused on the perception of the users who usually work in these rooms, who describe a series of problems during the working day such as strong discomfort in the small first floor meeting rooms due to overheating from solar radiation; great discomfort in large first floor meeting rooms due to excessive cold; hot and cold environments at different times on the ground floor offices; poor air quality in general or the poor response of air-conditioning systems to these problems.

2.2 State of the Art The indoor environment, where most people spend a significant amount of their life, can affect human comfort and health depending on its thermal environment quality. There are numerous scientific studies that have evaluated and published different analyses linked to thermal comfort in different types of buildings such as offices [1–4], schools [5–7] or homes [8–10]. Furthermore, there are studies that focus on analysing the state of the art on the analysis of thermal comfort in buildings [11]. The majority of those reviews focus on thermal comfort and providing a regular update on developments [12–16]. However, comparatively few review studies focus on post occupancy evaluation and human comfort [17, 18]. This study covers both aspects for a more effective approach to comfort. Regarding the typology that will be analysed during this document (administrative areas of an industrial building), the thermal comfort of this typology has rarely been analysed in previous studies. However, in regions such as the Basque Country (north of Spain), the weight of the industrial sector reaches 24.2% of GDP, causing 33% of the population to work in industrial buildings [19]. Although currently there are no differentiated data of industry workers among those who carry out workshop and office tasks, it is clear that administrative activities with different range of activity are developed in all these buildings (from single-person to 50 workers as in the case analysed).

2.3 Methodology This work focuses on obtaining a clear picture of the behaviour of the rooms evaluated in the face of the outside climate and the use to which it is intended. For this, two types of actions have been carried out. On the one hand, through online questionnaires, the works of these spaces have been consulted on aspects related to thermal comfort: clothing level, activity level, metabolic rate, satisfaction with the temperature and humidity level and thermal discomfort. On the other hand, the internal air temperature and relative humidity in the administrative areas were monitored using a remote system with access from My Open Hab [20]. These instruments were positioned at

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a height of 1.3 m. At the beginning of the field study, the globe temperature and air velocity of each room were measured. It was confirmed that the difference between the globe temperature and air temperature was below 0.5 °C, and the air velocity was lower than 0.1 m/s, indicating that it can be considered still air. Finally, based on the monitored data, the degree of thermal comfort of the users has been evaluated, which will allow a comparison between the users’ perception obtained through the surveys and the monitored data. To assess and visualize the thermal comfort, it has based on the empirical model of the European standard UNE EN ISO 7730 [21], which is the one in force in Spain implemented by the Technical Building Code. Note that the limits of model EN ISO 7730 are obtained for Category II with a MET of 1.1 and a CLO 1 in winter and 0.5 in summer. In addition, the study will consider two new comfort assessment criteria. The first is the Regulation of Thermal Installations in Buildings—RITE [22]. This regulation establishes the set values for designing thermal installations in buildings. In Spain, the RITE, in its 2009 update, set the air temperature of offices between 23 and 25 °C (summer) and between 21 and 23 °C (winter) and a relative humidity of 45–60% (summer) and 40–50% (winter). The second is the ideal temperature criteria defined by the National Institute of Occupational Safety and Health—INSHT [23]. In order to achieve an office temperature with less than a 10% margin of dissatisfaction, INSHT recommends temperatures of 23–26 °C (summer) and between 20 and 24 °C (winter); and a relative humidity between 30 and 70%.

2.4 Case Study 2.4.1 Description of the Case Study The offices that are the object of this study are located in the city of Tolosa (Spain). The building has the typical construction of an industrial pavilion, made up of a series of parallel frames with a structure of laminated steel profiles and enclosures in lacquered ribbed metal sheets (see Fig. 2.1). On the west facade, there is a body containing the offices, which consists of two floors. The enclosure is made up of facing brick panels combined with vertical openings closed with panned windows. The envelope of these rooms is not thermally insulated. Windows have aluminium frames without thermal break [U = 5.7 W/(m2 K)] with double glazing with a minimum air gap of 6 mm (4 + 6 + 4), with a U = 3.3 W/(m2 K). Solar protection is provided by interior blinds. This does not prevent the entry of heat when there is direct solar radiation. All rooms are connected to a mechanical ventilation system with heat recovery and air conditioning. The spaces that have a facade to the outside have additional natural ventilation through the windows, which are free to operate by the occupants. The air-conditioning installation is carried out by means of two VRF heat pumps of 40 and 25 KW.

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Fig. 2.1 Aerial view of the building, highlighting the administrative area (left) and view of the exterior facade of the administrative area (right). Source Google Maps

Fig. 2.2 Red line defines the scope of the room evaluated on the ground floor

The ground floor offices (see Fig. 2.2) are where most of the daily activity takes place. They are grouped in tables of 4 workers with a typical technical office activity (F0.1). The first floor is used as a meeting space (see Fig. 2.3). It has 3 small meeting rooms (F1.3, F1.4 and F1.5), a medium one (F1.2) and a large one (F1.1). It also

Fig. 2.3 Red line defines the scope of the rooms evaluated on the first floor

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has a kitchen-dining space, computer server room, changing rooms and bathrooms, which are outside the scope of this study.

2.4.2 Surveys The number of workers who have carried out the survey is 34 (17 women and 17 men), out of the approximately 50 who work at the same time. Regarding their daily activity, 68% report that their activity is sedentary, 20% “rest or sitting” and 12% standing light or medium activity. In relation to the clothing used during work (in winter and summer), the results show the use of relatively light and informal clothing typical of office work in general, with a CLO value of between 0.6 and 1. Regarding satisfaction with the levels of temperature, humidity and air quality, the survey allowed to obtain the following conclusions: • Perceived temperature in winter: slightly hot or thermally neutral (67%), slightly cold (18%) and cold or hot (15%). • Perceived temperature in summer: hot or very hot (48%), slightly hot or neutral (33%) and slightly cold (19%). • Perceived relative humidity in winter: neutral (79%) and slightly dry (21%). • Perceived relative humidity in summer: neutral humidity (85%). • Air quality: good nor bad (48%), bad (23%) or very bad (3%). In turn, a section of the survey focused on assessing office spaces from 0 to 9. The results show a general malaise of the spaces, reaching the approved (4.5 points) all spaces, but with a very fair value (5.6 is the maximum score).

2.4.3 Internal Air Temperature and Relative Humidity Monitoring Air temperature. First, the results will be analysed at times when there is no active heating or cooling, on holidays, for example. The analysis is performed on a hot summer day and a cold winter day to assess its behaviour in conditions of extreme outdoor temperature. This allows us to assess the capacity of the building envelope to maintain cold or heat. Subsequently, the same analysis is done on days with occupation and active systems turned on (see Fig. 2.4). This also allows us to find out the responsiveness of active systems (air conditioning). Internal temperature without active systems: The hot day selected was 4 August 2018 (Saturday), a very hot day (with a peak temperature of almost 43 °C). The studies show that the ground floor office (F0.1), with fewer openings, maintains a stable temperature. The minimum temperatures in the offices located on the first floor are between 26 and 27 °C. However, they reach maximum values of almost 44 °C. As

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Fig. 2.4 Example of monitored data (relative humidity and temperature) in the ground floor office (F0.1) during the day of the user survey (04-04-2019)

to the coldest day, 6 January 2019 (Sunday) was selected, a day when the outside temperature fell from 0 °C. The ground floor office is kept in a range between 17 and 19 °C. In relation to the spaces on the first floor, it can be seen that the large meeting room (F1.1) reaches a minimum of 6 °C during the night. This indicates its low thermal insulation and the higher impact of the north facade. Likewise, it is to be assumed that there is a notable impact due to being directly above an unconditioned space. Internal temperature with active systems: For the summer period, 11 September 2018 has been selected, a normal working day when all the spaces are occupied, and there is still a high late summer outdoor temperature (up to 42 °C). The office on the ground floor has remained overnight at about 22 °C, a comfortable temperature in principle. In the first period from 6:00 to 9:00 a.m., there is a rise in temperature, probably due to the occupation and the office equipment. After 9 a.m., there is a drop in temperature, probably because the cooling system is activated. It then rises again to 26 °C. This cycle is repeated in the afternoon until 6:30 p.m. when the system is deactivated. The offices located on the first floor show an even more unstable pattern. The meetings cause a sudden increase in temperature to which is added that caused by solar radiation. At 5:00 p.m., a series of meetings cause the cooling system to turn on, lowering the temperature in all of them uniformly to the minimum of 6:30 p.m. For the winter period, January 8 has been selected, a normal working day in which all the spaces are occupied and the outside temperature drops to 5 °C during the night and has a peak of 9 °C at 14:00 h. The ground floor office activates the heating system at 6:00 h. However, it has trouble going from the initial 13 to 21–22 °C, a value that is reached at 15:00 h. At 16:00 h, the system is stopped, and the temperature drops again to 16 °C. The offices on the first floor undergo the same process as on other days. The meetings cause the heating system to be activated as

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they are very cold and the meeting itself causes the temperature to shoot up to 29 °C in some cases. This causes windows to open and the temperature to drop. Relative Humidity. The behaviour of the relative humidity is closely linked to the type of climate control used, air conditioning. Since the system is not equipped with a humidification system, it will generally always dry out the air it brings in from the outside, whether it cools or heats it. During the summer, this is not a major problem as the indoor humidity is kept within reasonable limits. However, during the winter, the humidity drops to excessively low values, 20% even. It should be taken into account that in buildings constructed with a metal structure, low humidity is more of a problem. In office buildings with many metal parts, low levels of relative humidity can generate particularly in women a disease called “semi-circular lipoatrophy” (SL) [24].

2.4.4 Thermal Comfort Assessment Although during the original study, the degree of thermal comfort of all the previously defined areas has been evaluated, and this section mainly focuses on showing the results of one of the rooms with the highest degree of discomfort according to the results of the user surveys (F1.5). This study does not consider Sunday and Holidays. Winter Behaviour. The temperatures are hardly in the comfort range (see Fig. 2.5). There is a high variation between the minimum (9.7 °C) and maximum (32.1 °C) temperatures. The percentage of hours within the comfort range of 21–23 °C is 16.2% throughout the winter. The humidity limits in winter exceed the inferior limit (49.6%

Fig. 2.5 Analysis of thermal comfort of room F1.5 during the winter and summer

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hours below 40% RH), even more so if we consider the values of the current RITE standard which establishes a margin of 40–50% RH and the values established by the INSHT which limits for this type of space. This is accentuated in the months of March–April (84.1% hours below 40% RH). In the comfort ranges marked by the RITE, the authors find a minimum number of hours throughout the winter within the comfort ranges (79 h, 3.2% of all time). The INSHT range is more often met (546 h, 21.8%), but still far below the desirable comfort level. Summer Behaviour. The behaviour in summer is somewhat better than in winter (see Fig. 2.4). In this case, the comfortable outside environment allows the windows to be opened and to achieve better percentages of temperature and relative humidity within the comfort ranges of the various regulations. The maximum temperature is reached in the month of August with 40.1 °C, the peak values of May and July being 29.9 °C and 36.9 °C, respectively. Even in September, in full industrial activity, value of 32.3 °C is reached. The relative humidity values are closer to the comfort values, with the majority being in the 30–70% range. As for the hours within comfort, in the case of the RITE regulation, we see that in the month for which the most complete data are available and with a regular occupation, September, only 7.6% of hours within comfort limits (UNE EN ISO 7730) are reached, with a 15.5% of the hours within the range of INSHT (Table 2.1). In order to close this section of comfort evaluation, the conclusions obtained after analysing the monitored data from two other relevant rooms of this building are summarized. The first room is the large office on the first floor (F1.1). As it is located in a north-western area and has more contact with unheated spaces, it behaves in a more extreme manner. The minimum temperature reached in winter is 6.3ºC, with a minimum humidity of 23%. Winter comfort according to RITE is only reached in Table 2.1 Summary of the number of hours in relation to different indoor air temperature and relative humidity limits in winter and summer of the office F1.5 Winter period Total hours

Summer period 2506

Total hours

1834

Hours < 21 ºC

1777

Hours < 23 ºC

1227

Hours 21–23 ºC (winter comfort rite)

407

Hours 23–25 ºC (summer comfort rite)

205

Hours > 23 ºC

322

Hours > 25 ºC

402

Hours > 28 ºC

26

Hours > 28 ºC

187

Hours HR 40–50% (winter comfort rite)

705

Hours HR 45–60% (summer comfort rite)

441

Hours HR < 40%

1243

Hours HR < 45%

1296

Hours HR > 50%

558

Hours HR > 60%

97

Comfort UNE

245

Comfort UNE

195

Comfort RITE

79

Comfort RITE

139

Comfort INSHT

546

Comfort INSHT

285

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0.7% of the time (34 h), 15.3% according to INSHT. The environment is very dry as large amounts of air are needed to climate the space. 37.7% of the hours are below 40% RH. The maximum temperature reached is 26.8 ºC. In the summer, we observe that in September, a peak temperature of 29.9 ºC is reached, and 34.0 ºC in August. Comfort in September according to RITE is only reached in 11.2% of the time (81 h), 32.5% according to INSHT. During this period, adequate HR rates were maintained at 30–70% (47.7% of September hours). The second room is the general office on the ground floor (F0.1). The results obtained by the two sensors located in the general office on the ground floor are less extreme. Although data are not available for the whole year, it is noted that the period within RITE comfort range in winter does not exceed 30.6%, being higher in summer, 59.9%. Comfort in September according to RITE is only achieved in 24.4% of the time (176 h), 45.6% according to INSHT. During this period, adequate RH rates are maintained between 45–60% (51.5% of hours in September).

2.5 Discussion Although there is currently no study that has analysed the thermal comfort of administrative areas of industrial buildings, this study has shown how aspects such as thermal performance of the enclosure, orientation or contact with unheated spaces can generate a high degree of discomfort in workers. In order to solve this problem that directly influences working conditions, it is necessary to analyse the level or degree of discomfort and, in turn, detect the origin of this problem. For this, the study work has proposed to work in parallel based on two information collection methodologies: worker surveys and the monitoring of the temperature and relative humidity of administrative spaces. On the one hand, the surveys have allowed us to know the degree of discomfort of the workers and in which aspects their discomfort is greater (in this case, most of the workers focus on the internal air temperature parameter). In parallel, after monitoring the spaces where people who have carried out this survey work, the results have allowed us to quantify the degree of thermal comfort of users based on different comfort models. The data of the office evaluated by this work (F1.5) show how, based on the comfort model defined by Spanish regulations, this area is only within the comfort range of 3.2% of its working hours in winter and 7.6% of working hours in summer. The data according to the INSHT model are a bit better, although the percentage of hours within comfort does not exceed 22% in winter and 16% in summer.

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2.6 Conclusions This work has made it possible, on the one hand, to confirm that the deficient enclosure of the office space generates large heat losses in winter that lead to high consumption by the air-conditioning systems without obtaining adequate comfort in return. Likewise, the high glazed surface area with solar protection systems on the inside causes strong contrasts in the interior temperature, especially in the offices located on the upper floor which the air-conditioning equipment is not capable of managing adequately. All this generates a situation of generalized discomfort in the workers due to temperature and relative humidity values outside the ranges in the regulations. Acknowledgements We would like to thank Mikel Arregi Urkia from Tolosaldea LHII for his assistance with the set-up of the monitoring campaign and useful insight.

References 1. Wagner, A., Gossauer, E., Moosmann, C., Gropp, T., Leonhart, R.: Thermal comfort and workplace occupant satisfaction-results of field studies in German low energy office buildings. Energy Build. 39(7), 758–769 (2007) 2. Alajmi, A.F., Baddar, F.A., Bourisli, R.I.: Thermal comfort assessment of an office building served by under-floor air distribution (UFAD) system—a case study. Build. Environ. 85, 153– 159 (2015) 3. De Vecchi, R., Candido, C., de Dear, R., Lamberts, R.: Thermal comfort in office buildings: findings from a field study in mixed-mode and fully-air conditioning environments under humid subtropical conditions. Build. Environ. 123, 672–683 (2017) 4. Rupp, R.F., Ghisi, E.: Predicting thermal comfort in office buildings in a Brazilian temperate and humid climate. Energy Build. 144, 152–166 (2017) 5. Katafygiotou, M.C., Serghides, D.K.: Thermal comfort of a typical secondary school building in Cyprus. Sustain. Cities Soc. 13, 303–312 (2014) 6. Jindal, A.: Thermal comfort study in naturally ventilated school classrooms in composite climate of India. Build. Environ. 142, 34–46 (2018) 7. Yang, B., Olofsson, T., Wang, F., Lu, W.: Thermal comfort in primary school classrooms: a case study under subarctic climate area of Sweden. Build. Environ. 135, 237–245 (2018) 8. Becker, R., Paciuk, M.: Thermal comfort in residential buildings—failure to predict by standard model. Build. Environ. 44(5), 948–960 (2009) 9. Peeters, L., Dear, R. de, Hensen, J., D’haeseleer, W.: Thermal comfort in residential buildings: Comfort values and scales for building energy simulation. Appl. Energy 86(5), 772–780 (2009) 10. Yu, W., Li, B., Yao, R., Wang, D., Li, K.: A study of thermal comfort in residential buildings on the Tibetan Plateau. China. Build. Environ. 119, 71–86 (2017) 11. Antoniadou, P., Papadopoulos, A.M.: Occupants’ thermal comfort: state of the art and the prospects of personalized assessment in office buildings. Energy Build. 153, 136–149 (2017) 12. Taleghani, M., Tenpierik, M., Kurvers, S., Dobbelsteen, A.: A review into thermal comfort in buildings. Renew. Sustain. Energy Rev. 26, 201–215 (2013) 13. Cheng, Y., Niu, J., Gao, N.: Thermal comfort models: a review and numerical investigation. Build. Environ. 47, 13–22 (2012) 14. Rupp, R.F., Vásquez, N.G., Lamberts, R.: A review of human thermal comfort in the built environment. Energy Build. 105, 178–205 (2015)

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15. Yang, L., Yan, H., Lam, J.C.: Thermal comfort and building energy consumption implications— a review. Appl. Energy 115, 164–173 (2014) 16. De Dear, R.J., Akimoto, T., Arens, E.A., Brager, G., Candido, C., Cheong, K.W.D., Nishihara, B.L.N., Sekhar, S.C., Tanabe, S., Toftum, J., Zhang, H., Zhu, Y.: Progress in thermal comfort research over the last twenty years. Indoor Air 23(6), 442–461 (2013) 17. Gossauer, E., Wagner, A.: Post-occupancy evaluation and thermal comfort: state of the art and new approaches. Adv. Build. Energy Res. 1(1), 151–175 (2007) 18. Frontczak, M., Wargocki, P.: Literature survey on how different factors influence human comfort in indoor environments. Build. Environ. 46, 922–937 (2011) 19. Eustat. Euskal Estatistika Erakundea. Panorama de la Industria Vasca 2018. https://es.eustat. eus/elementos/ele0015400/Panorama_de_la_Industria_Vasca/inf0015432_c.pdf, last accessed 2020/03/01 20. MyOpenHab Homepage, https://www.myopenhab.org/, last accessed 2019/12/16 21. ISO, “ISO 7730: Ergonomics of the thermal environment Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria. Management (2005) 22. Ministerio de Industria, Energía y Turismo: Reglamento de Instalaciones Térmicas En Los Edificios. Boletin Oficial Del Estado (2013) 23. INSHT (National Institute for Safety and Health at Work), website of the INSHT (2020), https:// www.insst.es/, last accessed 2020/01/07 24. Linares-García, R., Cuerda-Galindo, E., Ramiro, J., Naranjo, P., M.A.: Semicircular lipoatrophy: an electrostatic hypothesis. Dermatology 230(3), 222–227 (2015)

Chapter 3

The Performance Potential of Domestic Heat Pumps in a Temperate Oceanic Climate Richard O Hegarty, Oliver Kinnane, Donal Lennon, and Shane Colclough

Abstract Domestic purpose heat pumps are commonly rated based on a manufacturer specified single coefficient of performance (COP). The performance of heat pumps however is known to vary widely for different seasons and for varying climate conditions. This study is part of an in-depth analysis of nZEB homes through the nZEB101 project funded by the Sustainable Energy Authority of Ireland (SEAI). In advance of undertaking a large-scale monitoring project, preliminary studies of nZEB technologies are being undertaken. This paper outlines a simplified method for calculation of the heat pump’s seasonal performance factor over six heating seasons in a modelled nZEB dwelling in Ireland using real hourly weather data. The study has found that while seasonal performance factor (SPF) values of 4.5 (as often claimed by manufacturers) are achievable, favourable operating conditions are required to achieve these high values. In a new building where underfloor heating and modern convective radiators are installed, the primary energy associated with the space heating is approximately 40% that of a natural gas boiler. The total CO2 emissions are also 47% less. However, in a retrofit nZEB building where existing radiators (which require higher outlet temperatures of approximately 65 °C) are used, the difference in CO2 emissions from a heat pump and gas boiler is almost negligible in a nation where the grid’s emission factor is 437 gCO2 /kwh (Irish electricity 2019). The potential for heat pumps can be improved further by decarbonising the grid and improving grid and plant production efficiencies. Keywords Air source heat pump · Coefficient of performance · Energy savings

3.1 Introduction The energy use and CO2 emissions associated with buildings continue to be significant, and solutions are needed to reduce their impact. In the EU, buildings account for approximately 40% of the total final energy consumption and 36% of the total R. O Hegarty (B) · O. Kinnane · D. Lennon · S. Colclough Department of Architecture, Planning and Environmental Policy, University College Dublin, Dublin, Ireland e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_3

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CO2 emissions [1]. Of this building energy consumption, two thirds is made up of residential buildings. In Irish residential buildings, the greatest consumer of energy is space heating [2]. Heat pumps are becoming the standard for the supply of space heating in Irish residential buildings as a result of their high efficiencies and grant to support. Between 2007 and 2008, the total heat pump sales increased by approximately 50% in Europe according to the European Heat Pump Association [3]. They function by moving low-temperature thermal energy from outside to higher temperature thermal energy on the inside of a building using a relatively small amount of external work. This work is powered by electrical energy from the grid and is often three or four times less than the thermal energy supplied to the building. Mackay [4] estimates that replacing fossil fuel heating with heat pumps in conjunction with high performance building envelopes and heating control systems would reduce the primary energy consumption for heating by 75% in the United Kingdom (UK), a promising reduction if achieved. This study presents likely SPF values for a standard air-to-water heat pump operating in an Irish climate by using real hourly weather data. The study also assesses the primary energy requirement and CO2 emissions for the space heating of a sample nZEB building. Five different heating systems are compared including four heat pumps operating at different outlet temperatures and one condensing natural gas boiler. The objective of the study is to identify the conditions for which air-to-water heat pumps are a sustainable solution to provide space heating to Irish buildings.

3.2 Heat Pump Performance The performance of a heat pump system is typically measured by a single coefficient known as the coefficient of performance (COP). This is simply the ratio of heat power output to electric power input under specific conditions. The conditions which determine the COP are presented graphically in Fig. 3.1 and listed below: • • • • • •

The heat pump’s efficiency curve The heat source The application temperature The climate The control system The occupant’s behaviour

As the climate and operating conditions change regularly, the COP will change regularly, and so, this ratio is often averaged over a period of time, which is known as the seasonal performance factor (SPF) [5]. SPF values of 4.5 and more are often quoted by manufacturers. This study investigates if over an average 6 year period this is possible in an Irish climate and, if so, under which conditions.

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Fig. 3.1 Factors affecting the seasonal performance factor

3.2.1 Performance Curve The mechanical performance of the heat pump itself is determined by the refrigerant used and the efficiency of the individual components including the compressor, evaporator, expansion valve and condenser. The limit on heat pump performance is based on the theoretical maximum coefficient of performance or Carnot coefficient of performance. The COP of an actual heating system is approximately half the Carnot value [6]. All heat pumps are tested to evaluate their performance. The test requirements in the EU for an air-to-water heat pump with outdoor unit operating to provide space heating are as follows: • The heat pump should be tested at a dry bulb temperature of 7 °C and a wet bulb temperature of 6 °C as set out in Tables 12–14 of EN 14511-2 [7] for a 35, 45 and 55 °C outlet temperatures for space heating application temperatures. • In Table 3.1 of EN 14511-4 [8], the relationships between wet and dry bulb temperatures are provided for definition of relative humidity. Table 3.1 Sources of energy taken from the SEAI [16]

Energy source

PEF

gCO2 /kWh

Natural gas

1.1

204.7

Electricity

2.06

436.6

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• Test data is required at a minimum of two sink (outlet application) temperatures, but usually at least three are provided by the manufacturer for space heating (35, 45 and 55 °C) with an additional application of 65 °C if domestic hot water (DHW) is to also be supplied by the heat pump. • Additionally, for application use (i.e. most cases), additional data points are required at – – – –

Dry = 2 °C; Wet = 1 °C. Dry = −7 °C; Wet = −8 °C. Dry = 12 °C; Wet = 11 °C. Dry = −15 °C; Wet = NA.

For example, to be listed on the SAP product characteristics database (PCDB), temperatures are required at dry bulb/wet bulb temperatures of 7/6, 2/1 and −7/−8 °C).

3.2.2 Heat Source The source of heating is typically either a ground source or air source and less commonly water. Ground source heat pumps extract heat from the ground with vertical or horizontal heat exchangers and are more efficient than air source heat pumps as a result of the more stable heat source. They are, however, costly, and in areas of high density housing, these heat pumps are not an option. Air-to-water heat pumps are particularly relevant for retrofit, as they do not require a significant amount of space. In the UK, approximately 40% of the housing stock is comprised of high density housing according to Kelly and Cockroft [9].

3.2.3 Distribution Temperature The outlet temperature from the heat pump has a significant impact on its performance with lower temperatures (requiring a smaller temperature lift), resulting in higher COPs. The usual heating supply temperature operation for radiators in Germany is 55 °C [10] and is 80 °C in the UK for old smaller radiator systems [6], while a typical under floor heating system requires an output temperature of approximately 45 °C or less. Results from a study on the performance of a domestic low-temperature heating system with a heat pump [11] showed that the building construction and its dynamic behaviour are of significant importance when opting for a heat pump system. Tight building construction (low infiltration heat losses) with thick insulation (low U-values) allows for low-temperature heat distribution systems. Low-temperature distribution is possible in nZEB buildings which have high thermal performance.

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3.2.4 Control Strategy Due to the thermal inertia typical of an underfloor heating (UFH) system, the heat emission system cannot react fast enough to changing heat loads making room thermostat control unsuitable [12]. Cost savings of 5% were found upon optimising the control strategy, and while this figure appears small, Verhelst et al. [12] concluded the result significant given the widespread application of the system. In this study, a simple control strategy with a constant temperature will be applied.

3.2.5 Climate The outdoor air temperature has an obvious impact on the heat pump’s performance. The performance of heat pumps is rated in terms of their COP against ambient temperature. Humidity can also impact performance. In humid climates such as Ireland, significant periods during the heating season experience close to saturation conditions resulting in wet coil operating conditions. This can lead to frost formation on the evaporation coil. To prevent excessive frost build-up, the heat pump would typically be reversed to free the air-side coil of ice [13] thus reducing its seasonal performance.

3.2.6 In-use Performance Kelly and Cockroft [9] measured the performance of an air source heat pump using field trial data. Results showed that the average annual COP (SPF) was approximately 2.7 (in contrast to its nominal COP of 3). Results also showed that the air source heat pump system alone produced 12% less CO2 than a condensing gas boiler. These figures do not appear promising but are based on the CO2 intensities of 0.19 kg/kWh for gas and 0.54 kg/kWh for grid electricity. The figure of 0.54 kg/kWh has since been reduced with the increasing amount of renewable electricity generation. One recent European study has already assessed the validity of European Labels and found that there were significant differences (of between +80% and −24%) between the real working conditions and test procedures carried out according to regulations [14].

3.3 Methodology To holistically assess heat pumps, considering all these discussed parameters, monitoring of a significant sample of occupied dwellings over long periods is required.

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This is the objective of the SEAI funded project ‘nZEB101’. This study forms the foundation for this greater body of work by assessing the potential performance of a sample air-to-water heat pump’s SPF and the primary energy consumption and CO2 emissions associated to it. The SPF is calculated as follows: • A sample 9 kW heat pump performance curve is taken as the baseline, and the COP is modelled as a linear piecewise function of temperature difference between outside ambient and heat pump outlet (or application) temperature. • A heating period from the beginning of October to the end of April is assumed, and for simplification, it is assumed that the temperature is kept constant for 24 h. • Hourly weather data for Ireland over the past 6 years is used [15]. • The COP at individual hourly intervals is calculated using the linear piecewise model of the heat pump’s performance. • The SPF is calculated by taking the average hourly COP value over the entire heating period. The SPFs are calculated for four different operating conditions (35, 45, 55 and 65 °C), and the associated primary energy consumption (kWh) and CO2 emissions for these four operating conditions are compared with that of a natural gas boiler (91% efficiency). The application temperature is dependent on a number of factors, but primarily, it depends on the type of heaters used, for example, under floor heating or convective wall heaters. The exact outlet temperature can only be estimated on a case study basis with real performance data. To compare the five heating systems (four heat pumps and one gas boiler), the hourly heat demand for a sample nZEB home is simply calculated with Eq. 3.1. The dimensions and specifications used to calculate the dwelling’s specific heat loss coefficient, H (W/K), are taken from [2]. The heat loss is simplified by assuming fabric heat loss only, which for the assumed dwelling equates to a total heat loss of 46.5 W/K. In any case, the heat loss coefficient does not affect the relative differences between the compared heating systems—which is of primary interest. The ambient air temperature, T a , is taken from the hourly weather data, and the base temperature, T b , is set to 15 °C and which is lower than the set point temperature as it accounts for internal gains. Q H = H (Tb − Ta )

(3.1)

The primary energy factor (PEF)and CO2 emissions factors of the two energy sources are presented in Table 3.1. These values are all multiplied by the delivered energy for heating to calculate the total primary energy consumption (kWh) and total carbon emissions (kgCO2 ). The PEF is calculated by the SEAI by dividing the total energy used to generate electricity divided by the total delivered electrical energy. The total energy used is the sum of the gross calorific values (GCV) of the fuels (including an additional 5% for processing and transport to the plants) used and the renewable sources. The PEF is the inverse of the combined efficiency of the grid and Irish generator plant. The PEF

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35

Fig. 3.2 Historical primary energy conversion factors for Ireland

has improved in recent years as shown in Fig. 3.2. The impact of this improvement in Ireland will be assessed in the context of the air-to-water heat pump. The CO2 conversion factor is calculated by the Sustainable Energy Authority of Ireland (SEAI) by dividing the total CO2 emissions from the GCV of the various fuel sources by the total delivered electrical energy. The CO2 figures are calculated for the individual sources of fuel and renewable energy is assumed to have zero CO2 emissions.

3.4 Results Both national energy assessment procedures for Ireland and the UK require a minimum number of data points for assessment of air-to-water heat pumps from test conditions set out in EN 14511-2 [7]. An example of the data for a commercially available high performance 9 kW heat pump is presented in Fig. 3.3; the values of which are extracted directly from the manufacturer’s technical manual. Figure 3.4 Over the six-year period, there is no significant change in average temperature with a six-year average heating period temperature of 6.8 °C. The heat pump performance curves from Fig. 3.3 are compared for these six years to estimate the SPF The performance is compared for six separate heating periods from 2013 to 2018, and the average temperature as well as the six-year average temperature for this heating period is presented in. The SPF for the four different operating conditions for the six years are presented in Fig. 3.5. Six-year average SPFs of 4.53, 3.4, 2.74 and 2.17 are calculated for the four operating conditions (35, 45, 55 and 65 °C, respectively). High SPF values are therefore achievable but specifically when the heat pump operates under optimum

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Fig. 3.3 COP vs ambient temperature for a typical 9 kW heat pump tested to in accordance with EN14511-2 [7]

Fig. 3.4 Average outside air temperature for the heating period in Ireland for six years (2013–2018)

conditions. The total final energy consumed is proportional to the SPFs which, for the air source heat pump running at an outlet temperature of 35°C, is 22% of the energy consumption of a modern gas boiler with a 91% efficiency. In a retrofit scenario where the radiator temperature would be 65 °C or higher, there is a 44% reduction in final energy consumption compared with a gas boiler. However, the sources of energy are different for a natural gas boiler and a heat pump which uses electricity. The primary energy associated to the different systems is

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Fig. 3.5 Average SPFs at four different outlet temperatures for six different years

calculated by applying the conversion factors from final energy consumed to primary energy which is higher for electricity than gas (Table 3.1). The primary energy required by the four heat pump heating systems is compared for a sample dwelling built to nZEB standards and is presented in Fig. 3.6.

Fig. 3.6 Six-year average primary energy consumption for heating using five different heating systems

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In each case, the primary energy requirement is less for the heat pump. The relative difference between primary energy requirement of the heat pumps and the gas boiler is, however, higher than the final energy consumed (as a result of the lower efficiency of the transformation, transmission and distribution process currently for electricity). For the air source heat pump running at an outlet temperature of 35 °C, the total primary energy required is 41% of the energy consumption of a modern gas boiler with a 91% efficiency. In recent years, effort has been made to increase the efficiency of the Irish grid and generation plants as is shown in the trend of reducing primary energy factor over time in Fig. 3.2. The effect of reducing the primary energy factor with primary energy consumption is compared in Fig. 3.7 which shows that only if the primary energy factor is kept low can heat pumps be regarded as more efficient than the gas boiler. The CO2 emissions associated with the heat pumps operating at the various outlet temperatures are presented in Fig. 3.8. The CO2 emission factors, taken from Table 3.1, are applied to the final energy consumption for the five different heating systems. The results reveal that in a retrofit scenario where cast radiators are not replaced (65 °C outlet temperature), there is only a very small difference in the total CO2 emitted for heating with a natural gas boiler. Further effort to decarbonise the grid is required if heat pumps are to provide a sustainable solution for space heating in an Irish climate to combat climate change.

Fig. 3.7 Change in primary energy required for heating consumption with respect to the primary energy factor

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Fig. 3.8 Six-year average CO2 equivalent for heating using five different heating systems

3.5 Discussion The heat pump has been compared on a seasonal basis for different operating conditions using four different metrics: • • • •

Final energy consumption in the dwelling Primary energy consumption CO2 emissions The performance of an optimally operating heat pump and gas boiler is compared using these four metrics in Fig. 3.9 to summarise the findings. The figure shows that • If the heat pump is performing with an SPF lower than 2.0, the CO2 emission for a gas boiler is actually less based on the carbon intensities specified in Table 3.1. • If the SPF is lower than 1.7, the primary energy of a gas boiler is less. • An SPF of 4.1 equates to the air source heat pump supplying an outlet temperature of 35 °C when it is 5 °C.

A heat pump operating with an outlet temperature of 35 °C when it is −15 °C still outperforms the natural gas boiler when comparing both primary energy and CO2 emissions.

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Fig. 3.9 Ratio between the performance of a heat pump and gas boiler for three different metrics: final energy consumption, primary energy and carbon emissions and for different seasonal performance factors

3.6 Conclusion Heat pumps reduce energy consumption and are operated using electricity, meaning that they have great potential as a possible renewable solution for the supply of space heating to buildings. However, this potential can only be fully capitalised on by continuing to increase the grid’s efficiency by switching to greener alternatives such as wind and solar. This study found that, based on a simplified methodology, air-to-water heat pumps are a viable technology for Irish buildings, particularly if operated at low-temperature applications. If operated at high temperatures, they perform similarly to natural gas boilers in terms of total carbon emissions based on current carbon emission factors. Uncertainties still remain over the actual operating conditions such as the impact of relative humidity, installation quality, maintenance, type of heating system and overall building performance. To obtain this information, the monitoring of real case study buildings is required. The nZEB101 project, funded by the Sustainable Energy Authority of Ireland, aims to validate the results of this work by monitoring the performance of heat pumps in-use over a full heating period. Acknowledgements This project is supported by the Sustainable Energy Authority of Ireland under Grant Agreement 18/RDD/358.

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References 1. ADEME: Energy Efficiency Trends and Policies in the Household and Tertiary Sectors. Ministry of Sustainable Development and the French Environment and Energy Management Agency (ADEME). ODYSSEE-MURE 2015:97 2. Fallon, N.: Towards Nearly Zero Energy Buildings in Ireland—Planning for 2020 and beyond. Department of Housing, Planning and Local Government. n.d. 3. Forsen, M., Nowack, T.: European Heat Pump Association. Outlook 2009 (2009) 4. Mackay, D.J.C.: Sustainable Energy—Without the hot air. UIT Cambridge (2008) 5. Huchtemann, K., Müller, D.: Simulation study on supply temperature optimization in domestic heat pump systems. Build. Environ. 59, 327–335 (2013). https://doi.org/10.1016/j.buildenv. 2012.08.030 6. Gupta, R., Irving, R.: Development and application of a domestic heat pump model for estimating CO2 emissions reductions from domestic space heating, hot water and potential cooling demand in the future. Energy Build. 60, 60–74 (2013). https://doi.org/10.1016/j.enbuild.2012. 12.037 7. EN 14511-2: Air conditioners, liquid chilling packages and heat pumps for space heating and cooling and process chillers, with electrically driven compressors—part 2: test conditions. Comité Européen de Normalisation (2018) 8. EN 14511-4: Air conditioners, liquid chilling packages and heat pumps for space heating and cooling and process chillers, with electrically driven compressors—part 4: requirements. Comité Européen de Normalisation (2018) 9. Kelly, N.J., Cockroft, J.: Analysis of retrofit air source heat pump performance: results from detailed simulations and comparison to field trial data. Energy Build. 43, 239–245 (2011). https://doi.org/10.1016/j.enbuild.2010.09.018 10. Huchtemann, K., Müller, D.: Evaluation of a field test with retrofit heat pumps. Build. Environ. 53, 100–106 (2012). https://doi.org/10.1016/j.buildenv.2012.01.013 11. Sakellari, D., Lundqvist, P.: Modelling the Performance of a Domestic Low Temperature Heating System Based on a Heat Pump (2002) 12. Verhelst, C., Logist, F., Van Impe, J., Helsen, L.: Study of the optimal control problem formulation for modulating air-to-water heat pumps connected to a residential floor heating system. Energy Build. 45, 43–53 (2012). https://doi.org/10.1016/j.enbuild.2011.10.015 13. Steiger, L., Buswell, R., Smedley, V., Firth, S., Rowley, P.: An Air Source Heat Pump Model for Operation in Cold Humid Environments. Loughborough University Institutional Repository (2010) 14. Nolting, L., Steiger, S., Praktiknjo, A.: Assessing the validity of European labels for energy efficiency of heat pumps. J. Build. Eng. (2018).https://doi.org/10.1016/j.jobe.2018.02.013 15. Met Éireann: The Irish Weather Service 2019. https://www.met.ie 16. SEAI: Domestic Fuel Cost Comparison, October 2018. Sustainable Energy Authority of Ireland (2018)

Chapter 4

An Analysis of Design Support Tools for Circular Building Practice Charlotte Cambier, Waldo Galle, Camille Vandervaeren, Ineke Tavernier, and Niels De Temmerman

Abstract In 2016, the Flemish Government set the transition to a circular economy (CE) as one of its priorities. Adopting the paradigm of circularity in, amongst others, the building sector has the potential to create more sustainable buildings, where the use of new resources and the production of waste is minimised by closing material flows. However, circular building implies radical changes at different levels: from organisational changes within the sector to new design methods. To support and guide stakeholders in this transition to a CE in the Flemish building sector, different organisations developed design support tools and methods. However, due to the lack of overview of the available tools and their purpose, it is unclear for the stakeholders which tool could fit best for their context. Therefore, this research analyses the potential of the identified tools for circular building practice. Further, the possible impact potential of the tools in a circular design process is assessed by reviewing the needs of circular building stakeholders and by comparing that need with the tools. The tools and needs are classified per building design aspect and per design stage. Subsequently, conclusions can be drawn on opportunities to develop new design support tools for circular buildings and on opportunities to improve existing tools. Keywords Circular economy · Building design · Design support tools

4.1 Introduction In 2016, the Flemish Government appointed the transition to a circular economy as one of its priorities [1]. Likewise, the European Commission identified ‘construction and demolition’ as one of its five priority sectors in its Circular Economy Action Plan of 2015 [2]. Adopting the paradigm of circular economy in the construction sector C. Cambier (B) · W. Galle · C. Vandervaeren · I. Tavernier · N. De Temmerman Department of Architectural Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium e-mail: [email protected] W. Galle Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_4

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has the potential to create more sustainable buildings, where the use of new resources and the production of waste is minimised by closing material loops. The construction sector has a special role in the industry context as it contributes to a large part of the global resource depletion and waste generation [3]. However, circular building implies radical changes at different levels: from organisational changes within the sector to new design methods. These changes bring with them uncertainties and risks, which could be driving forces to decide not to implement circular principles. As an answer to that challenge, there is a rising demand and supply of design tools and methods for supporting and guiding stakeholders in this transition to a CE in the Flemish building sector. From a survey conducted in 2008, almost 30% would like to have more support from decision-supporting tools [4]. Design tools intent to facilitate different aspects of the building design process and can be an important enabler in the transition towards a circular building sector, by, for instance, providing guidance in making technical design choices (reversibility, material choice, etc.). However, due to the lack of overview of the available tools [4] and information about their purpose [5], it is unclear for the stakeholders which tools could fit best with the context of their building projects. This study proposes a general classification that offers a well-structured overview of design support tools and of the current needs for features to support circular design. The tools and needs are classified per building design aspect and per design stage. This way, the tools and the needs can be compared, and the potential impact of the tools becomes visible. Subsequently, conclusions can be drawn on whether the available design support tools meet the needs of circular building practice, on opportunities to develop new design support tools for circular buildings and on opportunities to improve the available tools. The focus area of this study is the Flemish building sector.

4.2 Methodology In the first phase of the research, we collected tools that are available to designers in the Flemish region to support circular building design decisions. In the second phase, six stakeholders were interviewed. They were asked what they think they need in their practice, related to a design support tool or method, to proceed in designing circular buildings and why. The interviewees were Flemish or Dutch building actors and were selected on their familiarity with circular principles and practices. This was assessed by the researchers on the basis of projects they are working on: designers known as experts or with explicit circularity ambitions. In the third phase of the research, a matrix was set up to compare the available tools and the needs of the different stakeholders, and to acknowledge mismatches between those two. On the horizontal axis of the matrix, different building stages are outlined and serve as a timeline. Those building stages are based on the RIBA Plan of Work [6], which is the definitive UK model for the building design and construction process. On the vertical axis, the building design aspects are outlined. The idea

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to categorise the tools into design aspects is based on the research of Lespagnard et al., where five façade design aspects are identified: Functions, structural design, material, inhabited construction and techniques [7]. These aspects originate from design practices observed during three post-war high-rise building renovations. In this research, the seven building design aspects of the matrix are based on the identified building design aspects of Lespagnard et al. on the one hand, and on the purposes of the collected design tools on the other hand. The final seven defined design aspects are as follows: Architectural strategies, calculation/circularity score, technical performance, relevant product/materials, environmental costs, supply chain and exemplary practices and business models. The fourth phase consisted of arranging the needs and tools according to the building design stages and the building design aspects. To determine to which design aspect(s) the various tools belong, the purpose of the tools is matched with the design aspects. To determine to which design phase(s) the tools belong, three questions based on the RIBA Plan of Work are set up: 1. Feasibility design phase: Does the tool assist in making design decisions on project objectives, sustainability aspirations, concept design or programme? 2. Developed design phase: Does the tool assist in making design decisions on the proposals for structural design, building services systems, outline specifications, cost information or project strategies? 3. Detailed design phase: Does the tool assist in making design decisions on the coordinated and updated architectural, structural and building services proposals? Is material and dimension-specific information needed to do the calculations? In the next step, the developed matrix was filled in twice: once with the identified needs and once with the collected tools. The fifth phase was to compare the two matrices and to discuss the similarities and differences between the needs and the tools (Fig. 4.1).

Fig. 4.1 Methodology scheme

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4.3 Design Support Tools for Circular Building The tools are selected by setting following criteria: they should (1) support circular building, (2) be available for use, (3) be relevant in the Flemish building context and (4) be design tools. Design tools address architects and/or advising engineers, include design and evaluation principles and have the aim to support design decisions which result in better-informed design choices. The content of design tools can range from simple checklists to complex simulation software. The 39 tools that met the set criteria are listed in Table 4.1. The table is considered to be non-exhaustive because the available tools and their features in this field change rapidly. Figure 4.2 shows the matrix containing the available design support tools for circular building per design phase and per design aspect. Three design aspects contain a larger amount of tools: the architectural strategies, the calculation/circularity score and the relevant products/materials. Furthermore, there are seven collections of tools identified, which are represented by means of the blue bars in Fig. 4.2. Collections contain tools that serve the same purpose. For example, design principle tools (DP) all have the aim to offer guidance in considering alternative design decisions to develop a circular building through design principles [8]. Other collections are life cycle costing (LCC), life cycle analysis (LCA), material flow analysis (MFA), material passport tools (MP) and reuse material platforms (RM). Although the exact impact and role of each tool might vary from project to project, depending on the adoption by its users, the similarity among the majority of tools raises questions about the tools’ effective complementarity in terms of goal and scope. Moreover, some gaps in the matrix, for example in the design aspect business models in the later design phases, occur. In the next research phase, it is investigated if it is needed to cover those gaps. Next to the available tools, there are many ongoing research tracks for the development of design support tools for circular building design. This trend shows that the circular economy still has a significant traction in academia and in the building practice and that the amount of available tools in this field can change rapidly. Some examples of such research tracks are as follows: • Collaboration tool for circular economy in the building sector: tool to enhance collaboration for circular economy in the building sector [9] • Disassembly Network Analysis: Using network analysis and BIM to quantify the impact of design for disassembly and link it to design improvements [10] • SAGA method: an assessment method that uses weighted graphs to quantify a building’s capacity to support changes [11]

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Table 4.1 Non-exhaustive list of design support tools for circular building, in alphabetical order Tool

Tool

Developer

16 design qualities for BBSM/VUB a circular economy architectural (DP) engineering

Developer

GRO tool

Facilitair Bedrijf

24 design principles for design for change (DP)

OVAM

Harvestmap/Oogstkaart (RM)

Superuse studios

BMIX

Vlaanderen Circulair

Insert marktplaats (RM) Buro Boot

Building circularity index

Alba Concepts

Kernmeetmethode

Platform CB’23

Circular building assessment (MFA)

BAMB

Level(s)

European Commission

C-calc

Cenergie

Life cycle cost tool (LCC)

German Environment Agency

Circular design guide

The Ellen McArthur Madaster (MP) Foundation and IDEO

Circular IQ (MP)

Circular IQ

MarketplaceHUB (RM) World Business Council for Sustainable Development

Circular transition indicators

World Business Council for Sustainable Development

Material EIA for single-family dwellings

Meex, E

Circularity calculator

IDEAL&CO Explore BV

OMAT (MFA)

Metabolism of Cities

Circulator

VITO, Vlaanderen Circulair, TU Delft, Rasboud University

One Click LCA (LCA)

Bionova Ltd.

Cirkeltips

OVAM

Opalis (RM)

Rotor

Closing the loop by design (DP)

Remeha B.V. Netherlands

OpenLCA

GreenDelta

DGNB toolbox (DP)

Deutsche RotorDC Store (RM) Gesellschaft für Nachhaltiges Bauen

RotorDC

Durmisevic’s knowledge method

Elma Durmisevic

Scenario based life cycle costing (LCC)

Waldo Galle

Ecoinvent

The ecoinvent Association

SimaPro (LCA)

PRé

Madaster Services

(continued)

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Table 4.1 (continued) Tool

Developer

Tool

Developer

Ecolizer

OVAM

STAN (MFA)

Institute for Water Quality, Resource and Waste Management, TU Wien

Environmental classifications of construction products

NIBE

Totem

OVAM, Brussels Environment, Wallonie Service Public

Façade identification system (MP)

VMRG, SlimLabs, Tagologic, Root

Werflink (RM)

Floow2

GaBi (LCA)

Thinkstep

Fig. 4.2 Categorisation of the design support tools for circular building per design phase and per design aspect

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4.4 Building Actors’ Needs for Features in Design Support Tools Now that the overview of design tools that support circular building design is developed, the question is if they answer to the actual needs of the actors who are trying to integrate circular principles in the design. Needs are formulated for every design stage and design aspect (Fig. 4.3). They are discussed per design aspect: 1. Practical examples: There is a loud call for practical examples and best cases. The actors long for overviews of practices, where the outcomes and learned lessons are structured and communicated in a coherent way. Convenient information would be technical details together with the context of those details (in the design aspect technical performance), and available products. Also, the failed practices should be shared according to the interviewees. This finding is consistent with the conclusion of Thelen et al. [12], where the lack of demonstration projects is mentioned as a barrier to the transition towards a circular economy. 2. Supply chain (1): There is a need for clear work flow management and monitoring tools to transfer the information between partners in a more efficient way. A study of Weytjens, Verdonck and Verbeeck in 2008 showed that 40% of

Fig. 4.3 The needs in tools for circular design according to building actors, based on quotes stated during the interviews. 1 Researcher sustainable buildings, 2 façade builder, 3 engineering office, 4 engineering office, 5 architect, 6 architect

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4.

5.

6.

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224 surveyed architects in Flanders required additional tools for communication during the design phases [4]. Furthermore, it is likely that more communication tools will be needed in the (near) future, given the growing complexity of the design process [4]. Linked to that, also matchmaking tools are demanded. Even if this demand is partly covered by learning networks and platforms, it seems that they do not fulfil the demand. One interviewee stated that in a matchmaking tool, other than platforms, the professionality of the participants should be checked by experts [5] and should be accessible for organisations of all sizes. Circularity score: The expressed need for a circularity score shows that there is a need for the measurability of circularity. This need follows from the uncertainties and risks associated with the transition to a CE. However, one interviewee also mentioned the possible disadvantages of a circularity score. First, ‘circularity’ could be greenwashed1 and second, each project is different which makes it difficult to quantitatively measure indicators and to compare them as such. Developers of circularity score tools should thus be careful in which indicators they measure and how they do that to avoid greenwashing and to become more circular buildings. Architectural strategies: Multiple interviewees expressed that sufficient general guidelines or principles on circular building are available. However, it has emerged from interview 6 that principles or guidelines for a specific building element would still be useful to have, for example, for the façade. Relevant products/Materials: There is no unified opinion among the interviewees on whether certain building products or materials should be classified in a kind of ‘circular materials/product’ database. The advantage could be a clear overview, and to be able to work faster and more certain. Nevertheless, there is a risk that actors lose their criticality for such categorised materials and that databases are difficult to keep up-to-date in this changing sector. Supply chain (2): Next to the technical support from tools, there is also a need for juridical support: Some interviewees stated the need for guidance to write building permits or contractual terms.

Moreover, multiple actors ignore what they need as features in a tool to achieve a circular building, mainly because of an unclear ideal outcome of a ‘circular building’. It implies the need of critical research to determine which knowledge gaps are the most urgent to tackle and which tools could be the most effective to accelerate the transition towards a CE through design.

4.5 Comparing the Tools and Needs Once the matrices are filled in with the tools (Fig. 4.2) and the needs (Fig. 4.3), the tools and the needs can be compared. Four major findings could be detected. First, 1 Greenwashing

is the practice of falsely promoting an organisation’s environmental efforts (strategies, goals, motivations and actions) to promote the organisation as green [13].

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there is a large need for practical examples and best practices. The current safety net of platforms and learning networks does not seem sufficient, either because only a small ‘expert’ group is allowed, or it requires a financial contribution [5], or it lacks structure. Thus, there is an absence of practical examples and their related technical details [14], learned lessons, etc., in a structured and accessible manner. Second, there is an oversupply of certain tools that are developed with the same purpose, for the same design phase, for the same design aspect and usually also for the same target group. This oversupply is translated in the seven collections of tools (blue bars) in Fig. 4.2 and in the red bars of ‘No Need’ in Fig. 4.3. For example, in Fig. 4.2, there is a collection of design principle tools, and Fig. 4.3 shows that two interviewees expressed that there is no need for more tools that elaborate on theoretical principles of circular design. The two matrices also show that there are some contradictions in the needs of the different interviewees. Some interviewees have the need for an additional circularity scoring tool, while others think a circularity scoring tool is not significant, because it could, for instance, lead to green washing. This shows that the needs are dependent per user and their expertise. However, in order to make any further conclusions, more research is needed on this topic. For some indicated needs, there are already tools available that could fulfil those needs. Possible explanations for these particular tools not being used are: they are not satisfying the users’ expectations, they are too complex, time-consuming or expensive or because the marketing strategies are lacking. According to Weytjens et al., the ease of use, next to the associated costs, is one of the most important criteria when selecting design-supporting tools. User-friendliness of tools could include, for instance, compatibility with other software and compliance with standards and regulations [4]. For example, there are various tools that attempt to calculate a circularity score, but there is still a need. This results in the dismissal of some tools, the remaining need for such tools and the oversupply of certain tools.

4.6 Conclusions Due to the lack of overview of the available tools for circular building and information about their purpose, it is unclear for the building actors which tools could fit best for their context and their needs. This study offers a well-structured overview of the available design support tools for circular building and compares the available tools with the current needs for features in such tools. This way, the impact potential of the different available tools is visible. The completed matrices and the comparison of them enhance the understanding on which design-supporting tools are available, on which ones meet the needs of circular building practice, on opportunities to develop new design support tools for circular buildings and on opportunities to improve the available tools. The main takeaways from this study are:

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1. There are seven collection of tools identified, which means that different tools are developed for the same purpose. These collections are: Design principles tools, material flow analysis tools, life cycle analysis tools, material labels, reused material platforms, material passport tools, life cyclecost tools and sharing platforms, 2. There is a loud call for a structured an detailed overview of practical examples and best practices, 3. There is a need for communication tools to transfer information in a more efficient way, and it is expected that this need will grow with the growing complexity of the design process of circular buildings, 4. There is no more need for general guidelines or principles on circular building, 5. Not all expressed needs are shared among all the interviewees (such as the need for a circularity score or the classification of circular building materials and products), which shows that the needs are dependent per user profile and their expertise, and more elaborated research should be done to clear out how specific contextual aspects play a role in the aspired transition. The matrices are a first attempt to guide the actors towards the right tools, but the guidance should be more specific. Next to categorising the tools and needs per design phase and design aspect, they could also be categorised per user profile, per level of expertise and per kind of building project. This way, the guidance could lead to a more relevant suggestion of tools. This study has examined tools that were developed only to support design decision for circular building. Designing circular buildings will not be guaranteed by supporting tools only. The major basis for design decisions is still experience and the clients demand [4]. Moreover, there are also suggestion in the literature and the public debate for common standards and legislation for the circular building sector, for investments in education, etc. [12, 15]. Furthermore, the tools and the needs in this field can change rapidly as we are in a transition from a linear to a circular economy. As a last recommendation for further research work, the identified necessary and currently missing tools could be developed, albeit with feedback from potential users. This research contributes to a much needed debate within the building sector supply chain to better understand and prioritise the key issues concerning supply and demand of design support tools for circular building practice. Acknowledgements This research is made possible thanks to Fonds Wetenschappelijk Onderzoek—Vlaanderen (Doctoral PhD grant strategic basic research 1S55518N).

References 1. OVAM: Startverklaring Vlaanderen Circulair, https://vlaanderen-circulair.be/nl/kennis/public aties (2016) 2. European Commission: Report on the Implementation of the Circular Economy Action Plan (2019)

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3. Guldager, K., Sommer, J. (eds.): Building a Circular Future. KLS PurePrint, Denmark (2016) 4. Weytjens, L., Verdonck, E., Verbeeck, G.: Classification and use of design tools: the roles of tools in the architectural design process. Des. Principles Pract. Int. J. 3, 289–303 (2009) 5. Interview: Project manager/Engineering Firm: ’Les façades circulaires en pratique: perspectives et défis (2019) 6. RIBA: RIBA Plan of Work 2013, https://www.ribaplanofwork.com/ (2013) 7. Lespagnard, M., Galle, W., De Temmerman, N.: Understanding the Design Process and Impact of Reversible Design Tools and Strategies (2019) 8. Galle, W., Cambier, C., De Temmerman, N., Elsen, S., Lanckriet, W., Poppe, J., Tavernier, I., Vandervaeren, C.: Building a Circular Economy: Design Qualities to Guide and Inspire Building Designers and Clients (2019) 9. Leising, E., Quist, J., Bocken, N.: Circular economy in the building sector: three cases and a collaboration tool. J. Clean. Prod. 176, 976–989 (2018) 10. Denis, F., Vandervaeren, C., De Temmerman, N.: Using network analysis and BIM to quantify the impact of design for disassembly. Buildings 8, 113 (2018) 11. Herthogs, P., Debacker, W., Tunçer, B., De Weerdt, Y., De Temmerman, N.: Quantifying the generality and adaptability of building layouts using weighted graphs: the SAGA method. Buildings 9, 92 (2019) 12. Thelen, D., van Acoleyen, M., Huurman, W., Thomaes, T., van Brunschot, C., Edgerton, B., Kubbinga, B.: Scaling the Circular Built Environment: Pathways for Businesses and Government (2018) 13. Becker-Olsen, K., Potucek, S.: Greenwashing. In: Idowu, S.O., Capaldi, N., Zu, L., Gupta, A.D. (eds.) Encyclopedia of Corporate Social Responsibility, pp. 1318–1323. Springer, Berlin, Heidelberg (2013) 14. Interview: Project architect/Advisory Office: Circulaire gevels in praktijk: inzichten en uitdagingen (2019) 15. Debacker, W., Manshoven, S.: Key barriers and opportunities for Materials Passports and Reversible Building Design in the current system. Brussels (2016)

Chapter 5

Alternative Municipal Solid Waste Management Systems in Morocco: Energy Savings and GHG Emission Reduction M. Maaouane, S. Dobrovi´c, S. Zouggar, and G. Krajaˇci´c Abstract The increasing amount of municipal solid waste and its consequent disposal has been a crucial issue in promoting a sustainable environment according to the Moroccan Ministry of the Environment. The rate of production of municipal waste was about 5.9 million tons/year, or 0.76 kg/citizen/day in urban areas. The controlled landfill rate was only 32% without energy recovery; the rest is transferred to wild dumps. In this study, alternate scenarios of the municipal solid waste (MSW) management are presented and analyzed. These scenarios aim to evaluate the energy savings and greenhouse gases (GHGs) emissions of four different practices of MSW management (recycling, incineration, landfilling and composting) in Morocco. The study reveals composting as the greatest choice when the energy savings and GHG emission reduction were considered since that organic waste constitutes a large share of the total waste in Morocco (65%); however, recycling of non-organic waste is found to be agreeable under the consideration of GHG emission reduction only. The obtained results will help the authorities involved in MSW management in Morocco to prepare more efficient measures. Keywords Waste management · Waste to energy · Greenhouse gas emissions · Recycling · Incineration · Landfilling · Composting

5.1 Introduction Poorly collected or improperly disposed of waste can have a detrimental impact on the environment. The great amount of waste which ends up spreading itself around the globe transported by wind, water or human can easily damage the health of the M. Maaouane (B) · S. Zouggar University Mohammed 1, School of Technology, Laboratory of Electrical Engineering and Maintenance (LEEM), BP 473, 60000 Oujda, Morocco e-mail: [email protected] S. Dobrovi´c · G. Krajaˇci´c Faculty for Naval Architecture and Civil Engineering, University of Zagreb, Ivana Luˇci´ca 5, 10000 Zagreb, Croatia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_5

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animals, people and ecosystems on our planet [1, 2]. Plastics, for example, whether in the ocean or in other natural environments, are ingested by birds, fish and other animals. The plastics in their bodies cause irreparable harm in short term and also a higher damage on the food chain in long term [3]. According to Schwabl et al. [4] and Kontrick [5], the contamination of the food chain affected also humans. Micro plastics (especially polypropylene and polyethylene terephthalate) ranging from 50 to 500 µm have been found in human stools. Bacterial activity causes the wastes in landfills to decompose over time. As these wastes decompose, gas is produced. The amount of gas created varies and depends on factors such as the amount and type of waste, moisture content of the landfill, amount of oxygen present, landfill size and temperature. Also, certain chemical reactions and the evaporation of some chemicals produce landfill gas. Most landfill gas is produced within 20 years after waste is dumped. Landfill gas is typically about 50% methane and 50% carbon dioxide and less than 1% sulfides (e.g., hydrogen sulfide, dimethyl sulfide, mercaptans) and non-methane organic compounds (NMOCs) (e.g., trichloroethylene, benzene and vinyl chloride). Landfill gas generally represents more of an odor nuisance than a community health hazard; however, there are some potential health problems: Some people may experience slight nausea or headache when they smell a bad odor. Certain NMOCs (non-methane organic compounds) are known carcinogens (e.g., vinyl chloride, benzene and chloroform), and some NMOCs may have adverse effects on organ systems such as the kidney, liver, pulmonary, reproductive and central nervous systems [6]. Another problem related to methane gas is explosions. The accumulation of methane gas in structures both within and beyond the landfill (e.g., basements, crawl spaces, utility ducts) has resulted in explosions and fires which have caused personal injury and death. Accumulation is often the result of underground gas migration [7]. Emissions of methane and carbon dioxide from landfill surfaces contribute significantly to global warming or the greenhouse effect. Methane (CH4 ) is regarded as one of the most important greenhouse gases (GHG) because of its global warming potential, which is 28 times higher than that of CO2 [8]. Over the last few centuries, the concentration of CH4 in the atmosphere has increased rapidly. In a span of 260 years, from 1750 to 2010, the concentration of GHG CH4 in the environment has increased from 700 to 1808 ppb. The rate of increase observed during the last few decades is 1–2% per year [9].

5.2 Literature Review To avoid these environmental impacts, it is strongly recommended that each government and municipality must participate in the implementation of effective MSW management systems [10]. In addition to the fact that waste is often considered as harmful, its energy potential cannot be overlooked [11]. In order to help the decision makers to choose wisely the adequate MSW management based on technology, location [12] and also the composition of waste (which is a crucial parameter in

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order to select a suitable WTE technology [13]), many studies have been conducted. For instance, regarding the MSW management in Gaziantep (Turkey), Tozlu, A. et al. quantified the amount of methane that can be produced in the city from MSW for power production. After their description of the existing waste-to-energy (WTE) technology in Gaziantep, the authors presented some recommendations for producing more LFG like installing an incineration plant instead of sanitary landfills [14]. For the MSW management in Malaysia, Tan, S. T. et al. have dealt with the problematic with a different way. The authors compared between anaerobic digestion (AD) and waste incineration. It was found that depending on the needs one of the two technologies provided a better choice: When both electricity and heat were considered, incineration offered better results; but when it comes to electricity production only, it was found that AD presented a better technology choice [15]. In order to illustrate once again the opportunity of MSW in electricity generation, Rajaeifar et al. quantified the amount of electricity per year that could be generated from MSW in Iran using AD technology. The authors calculated also the GHG emissions that could be avoided as a result of collecting and using methane for electricity generation and found that 0.5% of Iran’s annual GHG emissions could be avoided [16]. For the metropolis of Iran, Nabavi-Pelesaraei et al. evaluated the energy consumption impacts for two MSW management practices: landfill and incineration. The authors found that transportation consumes more than 80% of total energy demand to incineration and landfill systems. For that purpose, it is recommended to integrate at least the energy demand of transportation in the calculation of any MSW management scenario [17]. When it comes to Europe, Malinauskaite, J. et al. identified the different practices of MSW management employed in ten different European countries and examined the importance of waste-to-energy technologies in the circular economy. The authors found that the main issues that prevent the development of WtE industries are political [18]. For India, Joshi, R., and Ahmed, S. described and reported also the current MSW management system in the same country. The authors recommended adopting composting alternative for organic waste and recycling for non-biodegradable waste instead of landfilling [19]. Taking the same country as a case study, Gupta, N. et al. dealt mainly with the description of MSW management in India help the decisions makers adopting the most efficient plans [20]. Nevertheless, the data remain the key for any MSW management study. Because of the absence of MSW in Ghana, Miezah, K. et al. did statistical work on the quantity and the composition of MSW in order to inform and help the Guinean government look for an efficient MSW management system [21]. For the case of Morocco, an evaluation has been done on the financial, technical, environmental and social aspects of the Moroccan MSW management system [22]. The energy evaluation of the different technologies seems missing. On the other hand, Naimi, Y. et al. quantified the amount of methane (for electricity generation) that could be produced from landfills situated in Rabat (Morocco) [23]. In order to compare the energy recovery from landfilling practice with recycling and incineration, Saghir, M. et al evaluated the MSW potential in Oujda City (Morocco) [24].

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Since it was noticed that organic waste constitutes a large share of the total waste in Morocco (65%), the authors evaluated the energy that can be saved by producing fertilizers (Nitrogen) for agriculture from organic waste (composting) instead of its production from raw materials. A comparative study was conducted in order to highlight the composting of organic waste as a potential for energy savings and GHG reduction in order to help the decision makers for MSW management in Morocco to prepare more efficient plans. The organization of this paper is as follows. It starts with the presentation of the different technologies used to recover energy from waste. Then, the benefits in energy gains and reduction of GHG emissions are explained. Afterward, four scenarios of transition of municipal waste management in Morocco are described and discussed. Finally, the GHG emission in the four scenarios is calculated and compared.

5.3 Methodology 5.3.1 Waste Management Adopted Options For a better perception of the relationship between municipal solid waste (MSW) and energy use, U.S Environmental Protection Agency (EPA) developed energy factors for three waste management practices (recycling, incineration and landfilling), and explains the relationship between energy savings and GHG benefits [25]. EPA researchers limited the analysis to the following 21 single-material items which are the most common in the MSW: aluminum cans, steel cans, copper wire, glass, three types of plastic (HDPE, LDPE and PET), corrugated cardboard, magazines/thirdclass mail, newspaper, office paper, phonebooks, textbooks, dimensional lumber, medium-density fiberboard, carpet, personal computers, clay bricks, concrete, fly ash and tires. In addition to the materials listed above, EPA examined the energy use and GHG implications of managing mixed plastics, mixed metals, mixed organics, mixed recyclables, mixed MSW and mixed paper.

5.3.1.1

Recycling

Recycling allows using a material in place of virgin inputs in the manufacturing process, instead of being disposed of and managed as waste. As with source reduction of paper products, recycling of paper also results in forest carbon sequestration. The energy factors are based primarily on the amount of energy required to produce 1 ton of a given material. The total energy consumed is a result of direct fossil fuel and the amount of electricity consumed for the acquisition of raw material and manufacturing; fossil fuel consumption for transportation and embedded energy (i.e., energy of the raw material). The process and transportation components are conceptually straightforward, but embedded energy is more complex. Embedded

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energy is the energy contained within the raw materials used to manufacture a product. When any material is recovered for recycling, some portion of the recovered material is improper to be used as a recycled input. This portion is no longer useful either within the recovery stage or within the remanufacturing stage. As a result, less than 1 ton of new material generally is made from 1 ton of recovered material. Material losses are measured and converted into loss rates. Energy savings and GHG emission reductions associated with remanufacture using recycled inputs are calculated by taking the difference between (1) the energy and GHG emissions from manufacturing a material from 100 percent recycled inputs, and (2) the energy and GHG emissions from manufacturing an equivalent amount of the material (accounting for loss rates) from 100% virgin inputs.

5.3.1.2

Incineration

Incineration of MSW with energy recovery in a waste-to-energy (WTE) plant also results in avoided CO2 emissions at utility and metals production facilities. First, the electricity produced by a WTE plant displaces electricity that would otherwise be provided by an electric utility power plant. Because most utility power plants burn fossil fuels and thus emit CO2 , the electricity produced by a WTE plant reduces utility CO2 emissions. This avoided electricity, and GHG emissions are subtracted from the GHG emissions associated with incineration of MSW. Second, most MSW incinerated with energy recovery is incinerated in WTE plants that recover ferrous metals (e.g., steel) and nonferrous materials (e.g., nonferrous metals and glass). The recovered ferrous metals and nonferrous materials then are recycled. Processes using recycled inputs require less energy than processes using virgin inputs. In measuring GHG implications of incineration, the change in energy use due to recycling associated with metals recovery should be considered. The study’s general approach was to estimate the (1) gross energy and emissions of CO2 and N2 O from MSW incineration (including emissions from transportation of waste to the combustor and ash from the combustor to a landfill) and (2) CO2 emissions avoided because of displaced electric utility generation and decreased energy requirements for production processes using recycled inputs. The net GHG emissions were estimated by EPA from waste incineration for each selected material in MSW per ton and for mixed MSW and per ton.

5.3.1.3

Landfilling

EPA estimated the CH4 emissions for energy recovery and transportation-related CO2 emissions that will result from landfilling each type of organic waste and mixed MSW. In this analysis, EPA accounted for (1) the oxidation in the landfill of some portion of landfill CH4 to CO2 , and (2) the capture of CH4 for incineration with energy recovery (the captured CH4 is converted to CO2 ).

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To estimate MSW CH4 emissions from each category of landfill, EPA first estimated the percentage of landfill CH4 that is oxidized near the surface of the landfill. Based on estimates in the literature, EPA assumed that 10 percent of the landfill CH4 generated is either chemically oxidized or converted by bacteria to CO2 and the remaining 90% remains as CH4 . To estimate MSW CH4 emissions from landfills with landfill gas (LFG) recovery, EPA assumed that these landfills have an average recovery efficiency of 75%. EPA then calculated avoided utility GHG emissions from landfills where the CH4 is used for electricity generation. The values of CH4 emissions were given by metric tons of carbon equivalent (MTCE) per ton. These estimates were converted to KWh through incineration of landfill CH4 for electricity generation, assuming that: • 1 MTCE CH4 = 1/((12/44) * 28); because 1 metric ton of CO2 is equal to 12/44 of carbon equivalent (MTCE); 28: GWP (Global Warming Potential) • 1 Metric ton of CH4 = 106 g CH4 ; Physical constant • 1 g CH4 = 1/20 Cubic ft. CH4 ; 20 g per cubic foot of CH4 at standard temperature and pressure • 1 Cubic ft. CH4 = 1000 Btu • 1 Btu = 0,000,293,071 Kwh • It is assumed that electricity generation efficiency is 85%. 5.3.1.4

Composting

On a wet weight basis, EPA found that 21% of compost (organic material) is carbon. The evaluated compost was specified as having 17:1 C:N. In other terms, 1 ton of compost contains 12.35 kg of nitrogen. Composting may result in (1) CH4 emissions from anaerobic decomposition; (2) long-term carbon storage in the form of under composed carbon compounds and (3) non-biogenic CO2 emissions from collection and transportation of the organic materials to the central composting site, and from mechanical turning of the compost pile. Research suggests that composting, when managed properly, does not generate CH4 emissions, but it does result in some carbon storage (associated with application of compost to soils), as well as minimal CO2 emissions from transportation and mechanical turning of the compost piles. Overall, EPA estimates that centralized composting of organics results in net GHG storage of −0.05 MTCE/wet ton of organic compost (sum of the soil carbon storage and transportation-related emissions). The negative value denotes carbon storage. In the other hand, Wood, S. W., and Cowie, A. cited that one kg of nitrogen fertilizer produced in Europe produces 2178.1 g of CO2 -eq as GHG emissions. Therefore, the production of 12.35 kg of nitrogen from conventional methods emitted: 12.35 × 2178.1 × 10–6 = 26.9 × 10–3 MTCE [26]. Regarding the energy intensity, Gellings, C. W., and Parmenter, K. E. found that nitrogen production from conventional methods requires roughly 8.8 kWh per kg [27].

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5.3.2 Municipal Waste Management in Morocco Morocco currently has about 31.8 million inhabitants of which 60% in urban areas. The urbanization rate increased from 51.4% in 1994 to 55.1% in 2004 and to 58% in 2010 [28]. Morocco is experiencing significant development in vital socioeconomic sectors, including agriculture, industry, fisheries, urban development, infrastructure and tourism. This development had negative repercussions on the quality of the environment. Trends in environmental degradation in Morocco are currently estimated at 13 billion dirhams per year (1.2 billion euro) or 3.7% of GDP [29]. There were 391 urban settlements in 2004, of which 55 had more than 100,000 citizens, representing about 68% of the urban population. These cities have, for the most part, delegated waste management services to the private sector [30]. The current production of municipal waste in urban areas in Morocco is estimated at 5.9 million tons per year with a ratio of 0.76 kg/day/capita. In 2015, about 6.3% of the waste was recycled, 28.1% was landfilled; while 70% of the collected waste was disposed in wild dumps and in streams without any treatment or control, with serious consequences for public health and for the environment [29, 30]. The largely recycled waste is those with a significant economic value, such as metals, glass, paper and cardboard. However, this sector suffers from a total lack of recognition at the institutional, legal and regulatory levels. Recycling remains dominated by the informal sector [30]. The quantities of municipal wastes generated are expected to reach 13.3 Mega Tons (MT) by 2050 [30]. Since the projection of the production (Fig. 5.1) and the composition of MSW are available, the study concerned the whole country of Morocco. The reference year was chosen to be 2015 due to the lack of data between 2015 and 2020. Though, the

Fig. 5.1 Projection of the production of municipal waste (Mt) [30]

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authors assume that the composition rate of waste in Morocco does not change over time.

5.3.3 Applying Energy and GHG Emissions Factors The energy and GHG emission factors presented in the Appendix may be used by organizations interested in quantifying energy savings and GHG emissions associated with waste management practices. In order to apply the energy and GHG emission factors presented in this report, one must first establish a baseline scenario that represents current management practices; and an alternative scenarios that represents the alternative management practices. The energy and GHG emission factors developed by EPA researchers can then be used to calculate energy consumed or avoided (and GHG emissions produced or avoided) under both the baseline and the alternative management practices. Next, one should calculate the difference between the alternative scenario and the baseline scenario. The result represents the energy consumed or avoided and GHG emission that are attributable to the alternative waste management practice. For instance, recycling 1 ton of plastics rather than landfilling it reduces the energy consumed by 15.77 MWh and GHG emissions by 0.43 MTCE. The calculations used to generate this result are shown below. The negative value indicates that energy consumption is avoided, and GHG emissions are reduced. Baseline: landfill 1 ton of plastics (without energy recovery) 1 ton × 0.16 MWh/ton = 0.16 MWh 1 ton × 0.01 MTCE/ton = 0.01 MTCE Alternate: recycle 1 ton of plastics 1 ton × −15.61 MWh/ton = −15.61 MWh 1 ton × −0.42 MTCE/ton = −0.42 MTCE Energy Savings −15.61 MWh−0.16 MWh = −15.77 MWh GHG Emissions Avoided −0.42 MTCE − 0.01 MTCE = −0.43 MTCE

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5.3.4 Definition of Multiple Scenarios of Transition of Municipal Waste Management in Morocco Scenario I: Scenario I (Fig. 5.2) is the current situation (baseline scenario); waste is collected and moved to landfills (30% of non-recycled materials which is equivalent to 28.1% of total waste) without any form of energy recovery, and the remaining part to wild dumps (63.7%). The municipal waste recycling rate by material is given in Table 5.2. The table’s values indicate that the recycling rate compared to the total waste is around 6.3% in 2015. Scenario II: Scenario II (Fig. 5.3) focuses on energy recovery from landfills, dealing with 30% of the waste. It is assumed that gasification and composting are the main treatments for the municipal waste (which contains organic waste, paper and plastic and garden waste). The recycling rate is the same as in Scenario I (6.3%), and the remaining waste is sent for thermal treatment. Finally, the residue is removed to landfill. Scenario III: Scenario III (Fig. 5.4) focuses on recycling. A sorted collection has been assumed for recyclable materials. According to EPA, with good recycling facilities,

Fig. 5.2 Waste flow of Scenario I

Fig. 5.3 Waste flow and energy recovery of Scenario II

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Fig. 5.4 Waste flow and energy recovery of Scenario III

Fig. 5.5 Waste flow and energy recovery of Scenario IV

the ratio of recycled waste can easily reach 22.4%. The maximum municipal waste recycling rate by material is given in Table 5.2. The table’s values indicate that the recycling rate compared to the total waste could achieve 22.4%. The landfill (with energy recovery) rate remains the same as Scenario II. Finally, all the residue and bottom ash from incineration are moved to a sanitary landfill. Scenario IV: Scenario IV (Fig. 5.5) focuses on composting organic waste which constitutes a very large rate of total waste in Morocco (65%). The recycling rate remains the same as Scenario II. Finally, all other wastes that could not be sorted (14% other) are incinerated.

5.4 Descriptive Results The major results and conclusions obtained by the calculation are presented. The basic input data for all the scenarios are given in Tables 5.1 and 5.2. The most common GHG emissions and energy factors used in the calculations are presented in Tables 5.3 and 5.4. The input data used in the calculations are directly taken from the

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Table 5.1 Composition of municipal waste (ton) [30] Materials (Mi)

QMi (ton)

Organic (Ml)

3,858,655

M2 paper/cardboard (M2)

593,639

Plastic (M3)

464,316

Glass (M4)

118,727

Metal (M5)

267,138

Other (M6)

633,917

Total

5,936,392

Table 5.2 Recycling rate in Morocco compared to the potential of recycling materials Material

Actual recyclable (Morocco 2015) RMi (%)

Potential of recovered materials according to EPA rMi (%)

Organics

0

0

Paper

20

93

Plastics

25

90

Glass

14.10

90

Metals

46.30

94

Mixed MSW

0

0

Table 5.3 Net energy consumed/saved for waste management options (MWh/Ton) [25] Material

Dump ins

Recycling

Incineration

Organics

0.16

0.17

−0.17

Paper

0.16

−2.67

−0.64

Plastics

0.16

−15.61

−1.55

Glass

0.16

−0.62

0.11

Metals

0.16

−30.18

−1.61

Mixed MSW

0.16

NA

−0.44

Materia1

Landfilling without energy recovery (consumed energy for transportation to landfill only

Landfilling with CH4 recovery (electric generation) + energy for transportation to landfill

Composting

Oreanics

0.16

−0.70

−4.646

Paper

0.16

−0.42

NA

Plastics

0.16

0.16

NA

Glass

0.16

0.16

NA

Metals

0.16

0.16

NA

Mixed MSW

0.16

−0.80

NA

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Table 5.4 Net GHG emissions for waste management options (MTCE/Ton) [25] Material

Dump ins FDMi [311

Recycling FRMi

Incineration FIMi

Oreanics

0.17

NA

−0.05

Paper

0.18

−0.8

−0.18

Plastics

0.01

−0.42

0.27

Glass

0.01

−0.08

0.01

Metals

0.01

−1.84

0.02

Mixed MSW

0.23

NA

−0.03

Material

Landfilling without energy recovery FLMi

Landfilling with CH4 recovery for electric generation flMi

Composting FCMi

Oreanics

0.27

−0.10

−0.05

Paper

0.29

−0.11

NA

Plastics

0.01

0.01

NA

Glass

0.01

0.01

NA

Metals

0.01

0.01

NA

Mixed MSW

0.37

0.01

NA

Moroccan Bureau of Statistics [28], the Moroccan Environment Ministry [29] and the USA Environmental Protection Agency [25]. As shown in the previous chapter, the first step is to calculate the energy consumed (or avoided) and the amount of GHG emitted (or avoided) for each alternative scenario in order to subtract it from the baseline scenario. In this section, all of the equations are derived by the authors. For the baseline scenario (Scenario 1), the quantity of GHG emitted is 1,046,980 MTCE. The calculations used to generate this result are shown below. In this scenario, only 6.3% of the total waste is recycled, knowing that the recycling rate differs for each material contained in the waste. The percentage for each material is given in Table 5.2. 30% of non-recycled waste is sent to landfills (without energy recovery), while the rest is scattered in the wild dumps (Fig. 5.6). Total GHG Emissions(Scenario1) =

i=6 

Q Mi × [R Mi × FR Mi + (100 − R Mi )

i=1

× FL Mi × PL + (100 − R Mi ) × FD Mi × (100 − PL )] With: RMi PL QMi F RMi F IMi

Percent of recyclable material (%). Percent of landfilled waste (%). Quantity of the material contained in waste (ton). Factor of recycled material (MTCE/ton). Factor of incinerated material (MTCE/ton).

(5.1)

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Fig. 5.6 Calculation method for the Scenario 1

f LMi r Mi F LMi F DMi F CMi GM 1

Factor of landfilled material with energy recovery (MTCE/ton). Percent of recyclable material (%) according to EPA. Factor of landfilled material without energy recovery (MTCE/ton). Factor of dumped material (MTCE/ton). Factor of composted material (MTCE/ton). GHG emission to produce 12.35 kg of nitrogen from conventional methods (MTCE/ton).

By taking for example the case of paper (M2) contained in the waste, the total quantity of GHGs emitted by this material is the sum of the GHGs emitted for each waste management option. According to Tables 5.1, 5.2 and 5.3, 20% (RM2 ) of paper was recycled in 2015 in Morocco, 30% of non-recycled paper (PL ) was sent to landfill and 70% (100-PL ) to wild dumpsites. GHG Emissions(M2) = Q M2 × [R M2 × FR M2 + (100 − R M2 ) × FL M2 × PL + (100 − R M2 ) × FD M2 × (100 − PL ) = 593639 (ton) × [20% × −0.8(MTCE/ton) + (100 − 20)% × 0.29 (MTCE/ton) × 30% + (100 − 20)% × 0.18 (MTCE/ton) × (100 − 30)%] = 6173.8 MTCE In the same way, the authors calculate the GHG emitted from other materials (Organic M1, plastic M3, glass M4, metal M5 and others M6). Finally, all the GHGs emitted are obtained by

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Total GHG Emissions =

GHG EMISSIONS (Mi)

i=1

= 678182.5 MTCE The amount of energy consumed or avoided is calculated using the same equation by taking the energy factor (Mwh/ton) instead of the GHG emission factors (MTCE/ton). Total Energy (Scenario 1) =

i=6 

Energy (Mi)

i=1

= −5.01 TWh For the second and third scenario, Eqs. (5.2) and (5.3) are obtained by using the same way as Eq. (5.1) of the first scenario. Total GHG Emissions(Scenario2) =

i=6 

Q Mi × [R Mi × FR Mi + (100 − R Mi )

i=1

× f L Mi × PL + (100 − R Mi ) × FI Mi × (100 − PL )] (5.2) i=6 

Total GHG Emissions(Scenario3) =

Q Mi × [r Mi × FR Mi + (100 − r Mi )

i=1

× f L Mi × PL + (100 − r Mi ) × FI Mi × (100 − PL )]

(5.3)

In the fourth scenario, all of the organic waste (65% of waste) is composted; the other potentially recyclable materials are recycled, while the rest is incinerated. The authors subtract from this term, the amount of GHG emissions avoided (QM1 × GM1 ) due to the production of nitrogen by conventional methods. (Respectively the energy avoided). With GM1 = 26.9 × 10–3 MTCE/ton (previously calculated). Total GHG Emissions(Scenario4) =

i=6 

Q Mi

i=2

× [r Mi × FR Mi + (100 − r Mi ) × FI Mi ] + Q M1 × FC M1 −Q M1 × G M1

(5.4)

The next step is to calculate the difference between the alternative scenario and the baseline scenario. Thus, GHG Emissions avoided (Scenario i) = Total GHG Emissions (Scenario i)—Total GHG Emissions (Scenario 1); and Energy saved (Scenario

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Fig. 5.7 Energy and GHG emissions avoided for alternative scenarios compared to Scenario 1 in 2015

i) = Total GHG Emissions (Scenario i)—Total GHG Emissions (Scenario 1). With: Scenario i refers to Scenario 2, 3 and 4. The results of the calculations in 2015 are presented in Fig. 5.7. Compared to Scenario 1, Scenario 2 reduces the energy consumed by 2.64 TWh and GHG emissions by 1,134,481 MTCE. Regarding the second scenario, it allows to save the energy by −7.5 MWh and to avoid GHG emissions by 0.43 MTCE. In view of Scenario 3, a huge amount of GHG emissions can be avoided (2,026,275 MTCE). The amount of energy saving is also significant than Scenario 2. When it comes to Scenario 4, 35 TWh of energy could be saved. The GHG emissions are sliver more likely to be saved than the previous scenario (2,076,985 MTCE). Fig. 5.8 shows the reduction of GHGs emissions of each scenario compared to Scenario 1 as a function of time, based on the quantity of waste that could be produced until 2050 presented in Fig. 5.1 by applying the previous calculations on the quantity of waste that could be produced up to 2050 [Eqs. (5.1), (5.2), (5.3) and (5.4)]. Fig. 5.9 represents the energy saving according to each scenario compared to Scenario 1 as a function of time, based on the quantity of waste that could be produced until 2050 presented in Fig. 5.1 by applying the previous calculations on the quantity of waste that could be produced up to 2050 [Eqs. (5.1), (5.2), (5.3) and (5.4)].

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Fig. 5.8 Forecasting of GHG emissions avoided for alternative scenarios compared to Scenario 1

Fig. 5.9 Forecasting of energy savings for alternative scenarios compared to Scenario 1

5.5 Discussion Comparing Scenario 1 to Scenario 2 in Fig. 5.7, both energy and GHG emissions decreased firstly due to the incineration of the waste that was destined to wild dumps in Scenario 1 and secondly because of the recovery of methane from landfills. In view of Scenario 3, a biggest amount of GHG emissions and energy savings can be avoided

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by increasing the recycling rate (from 5.5 to 22.4%). When it comes to Scenario 4, it shows the importance of composting organic waste: A huge amount of energy can be saved by producing fertilizers (Nitrogen) for agriculture from organic wastes instead of producing it from raw materials. The GHG emissions are sliver more likely to be saved than the previous scenario even if the organic waste is composted instead of being incinerated. This is explained by the global warming potential of CH4 resulting from composting, which is higher than that of CO2 resulting from incineration. Looking at the slopes in Fig. 5.8 of the trend lines in absolute values, it is found that Scenarios 3 and 4 (which vary quite similarly) seem to offer a better opportunity to reduce GHGs emitted over time than Scenario 2. These results justify the importance of increasing the recycling rate of waste. On the other hand, the fact of composting organic waste instead of incinerating it (by comparing Scenario 3 to Scenario 4) does not seem to have a very significant impact on the reduction of the GHGs emissions. The slopes of trend lines in absolute values in Fig. 5.9 indicate that composting seems to offer the best opportunity in terms of energy savings over time (Scenario 4). Comparing Scenario 2 to Scenario 3, increasing in the recycling rate allows greater energy savings over time. As for Scenario 4, composting is by far the best to offer an energy saving thanks to composting organic waste: A huge amount of energy can be saved by producing fertilizers (nitrogen) for agriculture from organic wastes instead of producing it from raw materials.

5.6 Conclusions There are many ways of evaluating a municipal waste management system. The current municipal waste management situation in Morocco is so poor that its citizens were concerned about it, so government must take action to deal with it. The major problem was open dumping (unsanitary landfill), caused by limited waste treatment capacity and lack of participation (illegal dumping) by citizens. Four scenarios (including the current situation) were suggested in this paper. They focus separately on incineration, landfilling with energy recovery and recycling. When considering environmental impact, recycling of non-organic waste and composting of organic waste seems to have a very significant impact on the reduction of the GHGs emissions in long term and seen to be the best means of addressing the municipal waste management situation in Morocco. Regarding the energy savings, the calculations show that composting offers a significant amount of energy savings. Through this study, the authors hope to help the decision makers for MSW management in Morocco to prepare more efficient plans with the aim of establishing a sustainable society. The study should be based on other indicators (social, technological and economic) as well. On the other hand, the conclusions based on the calculations need to be tested in a further work. Acknowledgements The authors would like to thank Haut Commissariat de Plan (HCP), Moroccan Environment Ministry, and the University of Mohammed 1 for supporting this study.

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References 1. Hoornweg, D., Bhada-Tata, P.: What a Waste: A Global Review of Solid Waste Management, vol. 15, p. 116. World Bank, Washington, DC (2012) 2. Lebreton, L.C., Van der Zwet, J., Damsteeg, J.W., Slat, B., Andrady, A., Reisser, J.: River plastic emissions to the world’s oceans. Nat. Commun. 8, 15611 (2017) 3. Wright, S.L., Kelly, F.J.: Plastic and human health: a micro issue? Environ. Sci. Technol. 51(12), 6634–6647 (2017) 4. Schwabl, P., Köppel, S., Königshofer, P., Bucsics, T., Trauner, M., Reiberger, T., Liebmann, B.: Detection of various microplastics in human stool: a prospective case series. Ann. Internal Med. (2019) 5. Kontrick, A.V.: Microplastics and human health: our great future to think about now (2018) 6. Lee, G.F., Jones-Lee, A.: Impact of Municipal and Industrial Non-Hazardous Waste Landfills on Public Health and the Environment: An Overview. G. Fred Lee & Associates (1994) 7. Kundu, K., Chatterjee, A., Bhattacharyya, T., Roy, M., Kaur, A.: Thermochemical conversion of biomass to bioenergy: a review. In: Prospects of Alternative Transportation Fuels, pp. 235–268. Springer, Singapore (2018) 8. Myhre, G., Shindell, D., Bréon, F.-M., Collins, W., Fuglestvedt, J., Huang, J., Koch, D., Lamarque, J.-F., Lee, D., Mendoza, B., Nakajima, T., Robock, A., Stephens, G., Takemura, T., Zhang, H.: Anthropogenic and natural radiative forcing. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (2013) 9. Nda-Umar, U.I., Ramli, I., Taufiq-Yap, Y.H., Muhamad, E.N.: An overview of recent research in the conversion of glycerol into biofuels, fuel additives and other Bio-Based chemicals. Catalysts 9(1), 15 (2019) 10. Soltani, A., Hewage, K., Reza, B., Sadiq, R.: Multiple stakeholders in multi-criteria decisionmaking in the context of municipal solid waste management: a review. Waste Manage. 35, 318–328 (2015) 11. Mian, M.M., Zeng, X., Nasry, A.A.N.B., Al-Hamadani, S.M.: Municipal solid waste management in China: a comparative analysis. J. Mater. Cycles Waste Manage. 19(3), 1127–1135 (2017) 12. Achillas, C., Moussiopoulos, N., Karagiannidis, A., Banias, G., Perkoulidis, G.: The use of multi-criteria decision analysis to tackle waste management problems: a literature review. Waste Manage. Res. 31(2), 115–129 (2013) 13. Kumar, A., Samadder, S.R.: A review on technological options of waste to energy for effective management of municipal solid waste. Waste Manage. 69, 407–422 (2017) 14. Tozlu, A., Özahi, E., Abu¸so˘glu, A.: Waste to energy technologies for municipal solid waste management in Gaziantep. Renew. Sustain. Energy Rev. 54, 809–815 (2016) 15. Tan, S.T., Ho, W.S., Hashim, H., Lee, C.T., Taib, M.R., Ho, C.S.: Energy, economic and environmental (3E) analysis of waste-to-energy (WTE) strategies for municipal solid waste (MSW) management in Malaysia. Energy Convers. Manage. 102, 111–120 (2015) 16. Rajaeifar, M.A., Ghanavati, H., Dashti, B.B., Heijungs, R., Aghbashlo, M., Tabatabaei, M.: Electricity generation and GHG emission reduction potentials through different municipal solid waste management technologies: a comparative review. Renew. Sustain. Energy Rev. 79, 414–439 (2017) 17. Nabavi-Pelesaraei, A., Bayat, R., Hosseinzadeh-Bandbafha, H., Afrasyabi, H., Chau, K.W.: Modeling of energy consumption and environmental life cycle assessment for incineration and landfill systems of municipal solid waste management-a case study in Tehran Metropolis of Iran. J. Clean. Prod. 148, 427–440 (2017) 18. Malinauskaite, J., Jouhara, H., Czajczy´nska, D., Stanchev, P., Katsou, E., Rostkowski, P., Anguilano, L.: Municipal solid waste management and waste-to-energy in the context of a circular economy and energy recycling in Europe. Energy 141, 2013–2044 (2017) 19. Joshi, R., Ahmed, S.: Status and challenges of municipal solid waste management in India: a review. Cogent Environ. Sci. 2(1), 1139434 (2016)

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20. Gupta, N., Yadav, K.K., Kumar, V.: A review on current status of municipal solid waste management in India. J. Environ. Sci. 37, 206–217 (2015) 21. Miezah, K., Obiri-Danso, K., Kádár, Z., Fei-Baffoe, B., Mensah, M.Y.: Municipal solid waste characterization and quantification as a measure towards effective waste management in Ghana. Waste Manage. 46, 15–27 (2015) 22. Makan, A., Malamis, D., Assobhei, O., Loizidou, M., Mountadar, M.: Multi-criteria decision aid approach for the selection of the best compromise management scheme for the treatment of municipal solid waste in Morocco. Int. J. Environ. Waste Manage. 12(3), 300–317 (2013) 23. Naimi, Y., Saghir, M., Cherqaoui, A., Chatre, B.: Energetic recovery of biomass in the region of Rabat Morocco. Int. J. Hydro. Energy 42(2), 1396–1402 (2017) 24. Saghir, M., Naimi, Y., Laasri, L., Tahiri, M.: Energy recovery from municipal solid waste in Oujda city (Morocco). J. Eng. Sci. Technol. Rev. 12(1) (2019) 25. Environmental Protection Agency: Solid Waste Management And Greenhouse Gases: A LifeCycle Assessment of Emissions and Sinks, 3rd edn. (2006). https://nepis.epa.gov/Exe/ZyPDF. cgi/60000AVO.PDF?Dockey=60000AVO.PDF, last accessed 2020/04/13 26. Wood, S.W., Cowie, A.: A review of greenhouse gas emission factors for fertiliser production (2004) 27. Gellings, C.W., Parmenter, K.E.: Energy efficiency in fertilizer production and use. In: Gellings, C.W. (eds.) Efficient Use and Conservation of Energy; Encyclopedia of Life Support Systems, pp. 123–136 (2016) 28. Haut Commissariat de Plan (HCP): https://www.hcp.ma/Taux-d-urbanisation-en-par-annee1960-2050_a682.html, last accessed 2020/04/13 29. Moroccan Environment Ministry: https://pndm.environnement.gov.ma/situation_gdma, last accessed 2020/04/13. 30. RAPPORT PAYS SUR LA GESTION DES DECHETS SOLIDES AU MAROC Haut Commissariat de Plan (HCP): https://www.abhatoo.net.ma/maalama-textuelle/developpement-econom ique-et-social/developpement-economique/environnement/protection-de-l-environnement/ rapport-pays-sur-la-gestion-des-dechets-solides-au-maroc, last accessed 2020/04/13

Chapter 6

Quantifying Adaptability of College Campus Buildings Delaney E. McFarland, Brandon E. Ross, and Dustin Albright

Abstract While much has been written about adaptable buildings, quantification of adaptability is still in its nascent stage. Little has been published toward validation of quantitative adaptability models. This paper proposes a scoring system for evaluating the design-based adaptability of college campus buildings. This system was created to be a tool to guide future designs. Different physical features (i.e., floor-to-floor height and structural span lengths) of the buildings are considered in the scores. Adaptability scores are calculated for four buildings on Clemson University’s campus. Scores are compared to those from an earlier study of the same buildings; the earlier study quantified adaptability by surveying experts through an Analytic Hierarchy Process (AHP). Both approaches rank the subject buildings in the same order with respect to adaptability. Additionally, scores from both approaches are linearly correlated. These encouraging results suggest that the proposed scoring system is a starting point for quantifying the adaptability of college campus buildings. Keywords Design-based adaptability · Empirical comparisons · Analytic hierarchy process · Quantitative model

6.1 Introduction and Background 6.1.1 Adaptability and Design-Based Adaptability (DBA) Adaptability has been defined as the ease with which a building can be physically modified, deconstructed, refurbished, reconfigured, repurposed and/or expanded [1]. Similar definitions are presented in books by Schmidt and Austin [2] and Cowee and Schwehr [3]. Physical, economic, functional, technological, social, legal and political factors all impact a building’s adaptability [4]. Physical factors that impact adaptability include a building’s age and state of repair, as well as the features of its design. The portion of adaptability based on design features has been described as D. E. McFarland (B) · B. E. Ross · D. Albright Clemson University, Clemson, SC, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_6

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Design-Based Adaptability (DBA) [5]. While DBA is only one contributor to overall adaptability, it is critical because it is the only portion that can be directly impacted (intentionally or otherwise) by design decisions. This paper proposed a quantitative model for scoring DBA of college campus buildings. The model is intended as the first step toward a tool for architects and engineers who are seeking to design more adaptable buildings. Few models and methods have been proposed to quantify adaptability, and even fewer have been empirically validated [6]. Existing models for measuring DBA [5, 7–9] have been created using weighted-sum approaches. In weighted-sum models, a building is first scored for a variety of different parameters (e.g., floor plan openness). Scores are then multiplied by weighting values based on the scale and importance of the parameters, and then products are summed to determine an overall score. The proposed scoring system is also created using the weighted-sum approach, but is distinct from previous models in its use of research data for development and validation.

6.1.2 DBA Strategies This section briefly reviews relevant strategies for increasing a building’s DBA. Words in bold are used as shorthand for describing the strategies. More detailed reviews can be found in the works by Ross et al. [1] and Heidrich et al. [10] and detailed practical examples of each strategy are listed in Table 6.1. The strategy of Layering building systems was examined by Duffy [11] and Brand [12]. Duffy proposed that buildings should be analyzed as they are built and maintained: in layers such as “shell, services and scenery.” Brand observed that building layers are replaced at different rates (Fig. 6.1). He suggested that the layers be designed with physical and functional separation so each layer can be modified without impacting the others. Large floor-to-floor heights and wide structural grids are part of the Open strategy. For example, floor-to-floor height dictates if “ample space for HVAC equipment, etc.” [13] is available. Small floor heights can constrain the possibility of future changes. Similarly, wide open structures present more options for future change than do densely located structures. Reserve capacity is providing additional capacity beyond needs for the original building function. Future changes to a building may result in additional technical requirements, these changes can be facilitated by reserve capacity [1]. This idea is typically described in terms of structural capacity, but the strategy can also be applied to building services and space plans. Plan depth is related to the proximity of interior spaces to exterior walls. In the context of adaptability, access to exterior walls is desirable because many potential building functions, particularly those on college campuses, benefit from exterior windows. While plan depth has been reported as being beneficial to adaptability, other building characteristics are reported more frequently [14].

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Simple designs can reduce uncertainty associated with adaptation projects. Easy to understand load paths, repeating elements and details, orthogonal walls, stacking floor plates all contribute to simplicity [1]. Table 6.1 Examples of DBA strategies Strategy

Practical example

Layering

Use of non-bearing facades or demountable walls to separate the skin and structure layers The picture shows demountable walls in an office [15]

Open

Increasing structural grid size or floor-to-floor heights The warehouse in the picture has large spans and tall ceilings [16]

Picture

Reserve capacity Increasing design live loads or providing overly sufficient services for multiple potential occupancies The picture shows the construction of the raised plenum floors in the Watt Family Innovation Center on Clemson University’s campus [17] Plan depth

Creating a building footprint that allows interior spaces to be in close proximity to exterior walls and windows The building on the right has a shallow plan depth [18]

(continued)

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Table 6.1 (continued) Strategy

Practical example

Simple

Use of standard member sizes or similar grid patterns Buildings shown to the right have repetitive plans and elevations [19]

Picture

Fig. 6.1 Building layers (after Brand [12])

6.1.3 Becker et al. 2020 Becker et al. quantitatively measured DBA of four buildings from the Clemson University campus using an Analytic Hierarchy Process (AHP) [14]. The four buildings were the Watt Family Innovation Center (WFIC), Academic Success Center (ASC), Lee Hall and Stadium Suites (Fig. 6.2). These buildings were selected for study because of their similar size, age, and quality of materials. AHP is a method that separates multifaceted decisions into a series of pairwise comparisons. Pairwise results are aggregated to determine an overall best option. Experts in the Becker study used AHP to compare the subject buildings according to their relative suitability for different potential adaptation schemes. After aggregating the individual pairwise scores, the buildings’ overall adaptability scores were 0.3 for WFIC, 0.23 for ASC, 0.27 for Lee Hall, and 0.2 for Stadium Suites. Higher scores mean that a building is more suited for potential adaptation. Becker et al. also qualitatively evaluated the buildings’ adaptability by asking experts to describe the physical features that made the buildings more or less suitable for potential adaption. Open floor plans and high floor-to-floor heights were the most frequently mentioned features. Some of the other features, listed in order of most-to-least frequently mentioned, included: flexible HVAC systems, overdesigned structure, ease of access/plentiful circulation and building footprint/plan depth that

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Building A (Watt Family Innovation Center) 4 stories + basement, total 6070 m2. Movable glass partitions. Raised plenum HVAC system. Special structure: reinforced concrete cast on metal deck composite with beams and column. Green roof.

• • • • •

Building C (Lee Hall III) 1 story + mezzanine, total 5010 m2. Open studio space, offices, classrooms. Skylights and light sensors. Geothermal well heating system. Green roof.

• • • •

• • • •

• • • •

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Building B (Academic Success Center) 3 stories, total 3720 m2. Classrooms, offices, large lecture room. Structure: load-bearing CMU, concrete beams and columns. Distributed HVAC system.

Building D (Stadium Suites) 4 stories, total 6880 m2. Dorms, community rooms. Structure: load-bearing CMU, steel beams and columns. Distributed HVAC system.

Fig. 6.2 Four buildings used for comparison. (Used with permission from Becker et al. [14])

suits creative uses. Becker et al. engaged separate groups of experts to conduct the qualitative and quantitative portions of their study.

6.2 Scoring System Description The proposed scoring system measures the DBA of college campus buildings. Previous work by Becker et al. [14] measured DBA of existing campus buildings, whereas the scoring system aims to guide the design of future buildings. The choice to evaluate college campus buildings was made partially for the practical reason that the current researchers had access to detailed drawings and information about the buildings. More importantly, campus buildings were chosen because the stakeholders tend to be long-term owners who are interested an elongated life for their facilities. College campuses are always evolving based on new student and faculty needs. The recent transition to classrooms with increased social distancing due to COVID19 is one example. Since abundant land area for new construction is not always a viable asset in these necessary evolutions, the buildings located on these campuses must be able to adapt to new occupancies quickly in order to further the success of

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the university. The four buildings analyzed using the system proposed were chosen based on their similar sizes and ages.

6.2.1 Parameters and Parameter Score

Fig. 6.3 Adaptability scores associated with structural spacing. (1 ft = 0.3 m)

Structural spacing adaptability score

Eight physical features (parameters) are considered in the proposed scoring system. These parameters are similar to the DBA strategies cited in the literature (Sect. 1.2) and observed in the qualitative data collected by Becker et al. (Sect. 1.3). Separate scales are proposed to relate the value of each parameter to an adaptability score between 0 and 10. Individual adaptability scores are then multiplied by weighting factors, and the products are summed to determine an overall DBA score. This section discusses the parameters and their adaptability scales. It has been theoretically argued that there is a limit to the degree to which DBA strategies should be applied [20]. For example, just because reserve structural strength can increase a building’s adaptability, it would be wasteful to design all buildings to the highest and most stringent structural requirements. Scores for the individual parameters reflect this notion. Most of the parameter scores have diminishing returns as the parameters increase in value. Relationships between parameter scores and values are based on the authors’ professional opinions and reasoning. They are presented as a first step but are far from definitive. The authors intend to conduct additional research on this topic in the near future. To the extent possible, relationships between parameter scores and values are continuous mathematical functions. Continuous functions are used in lieu of checklist scoring systems. In a recent conference on adaptable buildings, checklist systems were criticized for promoting “checklist fatigue,” facilitating “gaming” or scores, and for dulling designer’s critical thinking [20]. Structural spacing. Structural spacing is related to the open DBA strategy. Scores for this parameter are determined using Fig. 6.3. It is reasoned that spacings below 10 ft (3 m) severely restrict the types of college campus functions that could be used in such spaces. Accordingly, the scoring for structural spacing begins at 10 ft (3 m). The score increases with increasing structural spacing with slope changes at 30 ft (9 m) and at 60 ft (18 m). The 30 ft spacing is based on the size of a typical classroom. After a structural spacing of 60 ft, the score remains constant because 60 ft is large enough 10 8 6 4 2 0

0

10

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Structural spacing (Ō)

60

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Fig. 6.4 Adaptability scores associated with floor-to-floor height. (1 ft = 0.3 m)

Floor-to-floor adaptability score

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10 8 6 4 2 0 0

5

10

15

20

25

30

35

Floor-to-floor height (ft)

for two typical classrooms and most other occupancies on college campuses. The scale is based on typical structural spacing. If structural spacing varies throughout the building, then the average spacing should be used. Floor-to-floor height. Adaptability score for floor-to-floor height is defined by Fig. 6.4. This parameter is related to the open DBA strategy. The scale begins at 9 ft (3 m) for a floor-to-floor height. Values below this height are impractical and deemed to restrict adaptability. Increasing floor-to-floor height between 9 and 15 ft improves adaptability; this is represented by the relatively steep slope between these heights. A floor-to-floor height of 15 ft (4.5 m) is considered ample for most campus occupancies. Adaptability scores increase more gradually for floor-to-floor heights between 15 and 30 ft. The score reaches the maximum value of 10 for a floor-to-floor height of 30 ft. At this value, the story could be split into two well-heighted floors. The floor-to-floor height used to determine the adaptability score is taken as the average for the building. It is calculated as the elevation difference between top of first floor and top of the roof structure divided by the number of stories. Wall deconstructability. Wall deconstructability refers to how easy it is to remove an interior wall [21]. Adaptability increases as walls are easier to deconstruct. The schedule in Table 6.2 lists the deconstructability score associated with different wall types. Bearing walls are considered the hardest to remove and are assigned a score of 0. Non-bearing walls are easier to remove and have higher scores. The highest score is for “removable” walls that are intentionally detailed to facilitate removal. The wall deconstructability score is based on the average wall deconstructability score across all interior walls in a building (Eq. 6.1). For example, the WFIC (Fig. 6.2) has a combination of bearing, light, and removable walls and has a wall deconstructability score of 7.5. Wall deconstructability is associated with the layer and open DBA strategies. Table 6.2 Unweighted score values associated with different wall types

Wall type

Deconstructability score (D)

Bearing

0

Heavy non-bearing

3

Light non-bearing Removable

7 10

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WDAS =

 L j Dj  Lj

(6.1)

where: WDAS Lj Dj J

Wall deconstructability adaptability score Total length of wall type j Deconstructability score of wall type j Index for wall type.

Fig. 6.5 Adaptability scores associated with design live load. (1 psf = 0.048 kN/m2 )

Design live load adaptability score

HVAC accessibility. Accessibility refers to how readily an HVAC system can be inspected, updated or modified. This parameter is related to the layer DBA strategy; HVAC systems that are highly integrated with or embedded in other building layers tend to be more difficult to adapt. The adaptability score for this parameter is more subjective than for the other parameters. Systems with embedded/rigid designs have a score of 0 while fully exposed/flexible designs have a score of 10. Scores given to the buildings in Fig. 6.2 are demonstrative. The WFIC is given a score of 8. It has raised floors that house the HVAC ductwork. Segments of the floor can be easily removed to inspect, replace or modify the ductwork. Lee Hall is given a score of 6. The ground floor of Lee Hall has a hydronic heating tubes in embedded in a concrete slab-on-grade. Ductwork for cooling is fully exposed below the upper floor and roof structure. The score for Lee Hall reflects the lack of accessibility of the in-slab heating, on the one hand, and positive accessibility of the ductwork on the other. HVAC systems for Stadium Suites and the ASC are typical of many buildings on the Clemson campus. HVAC ducts and chases are in wall/ceiling cavities that are covered by gypsum board. This condition is assigned a 5 and is considered a typical level of HVAC accessibility. Design live load. Design live load is associated with the reserve DBA strategy. Standard 7 from the American Society of Civil Engineers [22] lists uniform design live loads between 20 and 300 psf (1–14 kN/m2 ) for different occupancies. Live loads for most college campus occupancies fall between 20 and 100 psf, and these values form the first segment of the adaptability scale for live loads shown in Fig. 6.5. Live loads over 100 psf have increasing adaptability scores, but with diminishing returns (lower slope on figure) because design loads over 100 psf are only needed for special conditions such as data centers and libraries. 10 8 6 4 2 0

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Fig. 6.6 Adaptability scores associated with plan depth

Plan depth adaptability score

Different design live loads are typically applied across different portions of a building. In these situations, the weighted average design live load is used to determine the adaptability score. For example, the majority of areas in the Stadium Suites building is designed for 40 psf. Common rooms and corridors have higher design loads. The weighted average is 47.5 psf; therefore, the design live load adaptability score is 3.8. Plan depth. The percentage of a floor plate area that is within 12’ (3.7 m) of an exterior wall is an indicator of the plan depth strategy. A relatively skinny building has low plan depth and high percentage of area close to exterior walls. A “big box” store is an example of a building with high plan depth and a corresponding low percentage of space near exterior walls. While interior spaces in “big box” buildings can be adapted for a variety of uses, experts from the Becker et al. [14] study preferred shallower plans. This is because shallow plans provide greater proximity to exterior walls and windows which is desirable for many college campus occupancies. Shallow plan depths facilitate more occupancies making them more adaptable. The scale for determining the plan depth adaptability score is shown in Fig. 6.6. A score of 0 is associated with large plans depths in which 10% or less of the floor area is within 12’ of exterior walls. The score increases with increasing up to a peak at 50%. Scores decrease for percentages above 50% as the plan depth becomes “too thin.” When 100% of the plan area is within 12’ of the exterior, the plan depth is 24 ft (7.3 m). Such plans can facilitate a limited number of campus occupancies and are assigned an adaptability score of 6.0. Orthogonal walls. The adaptability score for this parameter is linearly related to the percentage of walls in a building that are oriented in orthogonal directions (Fig. 6.7). In the Stadium Suites building, there are diagonal wall segments that form the corner tower (Fig. 6.2). The remaining 90% of walls are orthogonal which results 10 8 6 4 2 0

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Fig. 6.7 Adaptability scores associated with percentage of orthogonal walls/stacking floor plates

Orthogonal walls/stacking floor plates adaptability score

Percentage (%)

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in an adaptability score of 9. Orthogonal walls are taken as an indicator of the simple DBA strategy. Stacking floor plates. Stacking floor plates are also related to the simple DBA strategy; stacking floor plates are indicators of simple structures and details. This parameter is calculated as the overall percentage of floor plate areas in a building that match. This percentage is linearly related to the floor plate adaptability score using the same scale as the orthogonal wall adaptability score (Fig. 6.7). An example of this indicator is found in the WFIC in which floor plates get smaller with each story. The floor plate adaptability score is 6 because 60% of the floor plate area stacks. While this indicator is very simple to calculate and apply, the authors are currently considering more rigorous methods for calculating stackability. From an adaptability perspective, it is reasoned that some portions of buildings (i.e., plumbing chases) are more critical to stack vertically than others. More rigorous models could consider which portions of a building stack.

6.2.2 Overall Adaptability Score Adaptability scores for the individual parameters are aggregated to determine the overall adaptability score. This is done by multiplying each parameter score by a weighting factor representative of its level of importance then summing the products: OAS =



PWi PASi

(2)

where: OAS PWi PASi I

Overall adaptability score Parameter weighting factor Parameter adaptability score Index for parameters.

Parameter weighting factors are based on the qualitative data collected from building professionals in Becker et al. [14]. The professionals listed physical features of the subject buildings that would facilitate or impede adaptation. Parameters in the model were assigned to the most similar physical features mentioned by the professionals. Parameters (features) that were more frequently listed are assigned higher weights than those listed less frequently (Table 6.3). The parameter weighting factors are set such that they sum to 1.0. Hence, the overall adaptability score ranges from 0 to 10.

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Table 6.3 Physical features, scoring system parameters and parameter weighting factors From Becker et al. [14]

Associated parameter

Parameter weighting factor

Frequency in data

Physical features cited by professionals

Most frequent

Open/closed floor plans Structural spacing

0.20

Most frequent

Floor-to-floor height

Floor-to-floor height

0.20

Frequent

Reconfigurable floor plans

Wall deconstructability

0.14

Frequent

Flexible HVAC systems HVAC accessibility

0.14

Least frequent

Overdesigned structure

Design live load

0.08

Least frequent

Floor plan facilitates creative uses

Plan depth

0.08

Orthogonal walls

0.08

Stacking floor plates

0.08

6.3 Comparison of Scoring System and AHP Study Overall adaptability scores for the four subject buildings were calculated (Table 6.4) and were compared to the results of the Analytic Hierarchy Process (AHP) study presented by Becker et al. [14]. The scoring system and the AHP study resulted in the same rank order from most to least adaptable. As seen in Fig. 6.8, there is a high degree of linear correlation (R2 = 0.84) between the scoring system and the results of the AHP study. The favorable comparison is encouraging and suggests that the proposed scoring system may have practical value for measuring and comparing adaptability Table 6.4 Adaptability scores of case study buildings Parameter

Weighting factor

Structural spacing

0.20

WFIC

ASC

8.0

8.2

Lee Hall 8.5

Stadium Suites 6.5

Floor-to-floor height

0.20

7.0

6.2

7.3

4.2

Wall deconstructability

0.14

7.5

5.6

7.0

3.3

HVAC accessibility

0.14

8.0

5.0

6.0

5.0

Design live load

0.08

8.0

5.0

7.0

3.8

Plan depth

0.08

3.5

6.8

3.0

8.8

Orthogonal walls

0.08

8.0

9.0

9.0

9.0

Stacking floor plates

0.08

Total Unweighted Score

6.0

9.0

5.0

9.5

56.0

54.8

52.8

50.3

Overall Adaptability Score

7.21

6.75

6.91

5.82

AHP score (Becker et al. [14])

0.30

0.23

0.27

0.20

86 0.5

Score from AHP study

Fig. 6.8 Comparison of the two scoring system results

D. E. McFarland et al.

0.4

y = 0.068x - 0.201 R² = 0.84

0.3 0.2 0.1 0

5

5.5

6

6.5

7

7.5

8

Overall adaptability score

of college campus buildings. Caution is advised, however, as the comparison with the AHP study is a relatively small degree of validation.

6.4 Summary and Conclusions A system is proposed for scoring and comparing the design-based adaptability (DBA, the portion of adaptability associated with a building’s physical design) of college campus buildings. The system considers eight different physical parameters, such as floor-to-floor height and design live load, which can be readily measured. Adaptability scores for the individual parameter scores are aggregated to determine a building’s overall adaptability score. The system is intended as an aid for designing new buildings for adaptability and also for evaluating adaptability of existing buildings. Four case study buildings from the Clemson University campus were used to evaluate the proposed scoring system. DBA of these same buildings has previously been quantitatively determined by Becker et al. [14] using the Analytic Hierarchy Process (AHP). Results from the proposed scoring system and the earlier AHP study are in good agreement (R2 = 0.84). While these results are encouraging, more research on a larger, more diverse group of buildings is recommended to further develop and validate the proposed system. Traditional office buildings and multi-family residential buildings could be a starting point for a new group to test.

References 1. Ross, B.E., Chen, D.A., Conejos, S., Khademi, A.: Enabling adaptable buildings: results of a preliminary expert survey. Procedia Eng. 145(Supplement C), 420–427 (2016) 2. Schmidt, R. III., Austin, S.: Adaptable Architecture: Theory and Practice. Routledge (2016) 3. Cowee, N.P., Schwehr, P.: The Typology of Adaptability in Building Construction. vdf Hochschulverlag AG (2012) 4. Langston, C., Shen, L.: Application of the adaptive reuse potential model in Hong Kong: a case study of Lui Seng Chun. Int. J. Strategic Prop. Manage. 11(4), 193–207 (2007)

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5. Ross, B.: The Learning Buldings Framework for Quantifying Building Adaptability. Presented at the ASCE Architectural Engineering Institute Conference, Oklahoma City, OK (2017) 6. Rockow, Z., Ross, B., Black, A.K.: Review of methods for evaluating adaptability of buildings. Int. J. Building Pathol. Adapt. 37(3), 273–287 (2019) 7. Andrade JB., Luís B.: Assessing Buildings’ Adaptability at Early Design Stages. In: IOP Conference Ser 2019 (2019) 8. Da Fonseca Lamounieri R., Ferreira Saraiva A.M., De Freitas R.R., Morado Nascimeno D.: Adequacy level of brazilian constructive systems to the open building: a research methodology. In: Conference 2018, pp. 123–134. Los Angeles, CA (2018) 9. Geraedts R.: FLEX 4.0, a Practical instrument to assess the adaptive capacity of buildings. Energy Procedia 96, 568–579 (2016) 10. Heidrich, O., Kamara, J., Maltese, S., Re Cecconi, F., Dejaco, M. C.: A critical review of the developments in building adaptability. Int. J. Building Pathol. Adaptation (2017) 11. Duffy, F.: Design and facilities management in a time of change. Facilities 18.10/11/12, 371–375 (2000) 12. Brand, S.: How Buildings Learn: What Happens After They’re Built. Viking, New York, NY (1994) 13. Black, A.K., Ross, B., Rockow, Z.: Identifying physical features that facilitate and impede building adaptation. In: International Conference on Sustainability in Energy and Buildings 2018. Springer, Cham (2018) 14. Becker, A.K., Ross, B., Albright, D.: Evaluating the Weighted-Sum Approach for Measuring Buildings’ Adaptability. Journal of Green Building (Accepted, forthcoming 2020) 15. Pizzolato, M.: www.flickr.com, “Demountable Office Walls Brisbane”. April 14, 2020. April 2, 2018, available for use under license 16. Guth, J.: www.flickr.com, “Warehousing”. April 14, 2020. March 26, 2011, available for use under license 17. Photo owned by Clemson University 18. Joseph.: www.flickr.com, “Skinny Building”. April 14, 2020. April 3, 2013, available for use under license 19. PDArt1.: www.flickr.com, “Skyscraper”. April 14, 2020. January 3, 2011, available for use under license 20. Ross, B.: Notes taken during Open Building for Resilient Cities Conference. Los Angeles, CA, USA (2018) 21. Herthogs, P., et al.: Quantifying the generality and adaptability of building layouts using weighted graphs: the saga method. Buildings 9(4), 92 (2019) 22. American Society of Civil Engineers: Minimum Design Loads and Associated Criteria for Buildings and Other Structures (ASCE/SEI 7–16). Standard 7. Reston, VA, USA (2016)

Chapter 7

Energy Efficiency in School Buildings: The Need for a Tailor-Made Business Model Dirk V. H. K. Franco, Janaina Macke, Marleen Schepers, Jean-Pierre Segers, Marijke Maes, and Evelien Cruyplandt Abstract Energy efficiency (EE) for buildings can be an essential aid to the climate objectives regarding the reduction of greenhouse gas emissions (GHG). More and more, the potential of maintenance and energy performance contract (EPC) is being recognized for this implementation, with the help of an energy service company (ESCO) whether accompanied by a facilitator. Clustering buildings can be an additional asset: since in this way the risks for the ESCO can be spread, the projects with a quick and high return on investment are a catalyst for long-term projects and finally, because of the higher absolute amount of investment these projects become more interested for/in the financial partners, which can be realized through adapted business models. In this article, we discuss two cases related to the pooling of buildings for higher and secondary education institutions. The university of applied sciences PXL with 12 buildings, all under own management and the association of schools in SintNiklaas (54 different location in the city), belongs to four different school communities. For both cases, the limits of the “classical” maintenance EPC are discussed and an adjusted approach with the corresponding business model is reported. As the educational value for both institutions is also of great importance, the link between D. V. H. K. Franco (B) UHasselt Centre for Environmental Sciences, Agoralaan, 3590 Diepenbeek, Belgium e-mail: [email protected]; [email protected] D. V. H. K. Franco · M. Maes PXL, Central Administration, Building A, Elfde Liniestraat 25, 35O0 Hasselt, Belgium J. Macke University of Caxias Do Sul (UCS), Caxias Do Sul, Brazil M. Schepers PXL, Department Green and Tech, Agoralaan, 3590 Diepenbeek, Belgium J.-P. Segers PXL, Business, Elfde Liniestraat 25, 35O0 Hasselt, Belgium Riga Technical University, FEEM Kalku Iela 1, Centra Rajons, Riga, PXL 1658, Latvia HEC-ULg, Rue Louvrex 14, 4000 Liège, Belgium E. Cruyplandt Energycoach Plezantstraat, 135–9100 Sint-Niklaas, Belgium © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_7

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energy efficiency and the didactic component, as well as the interaction with other stakeholders in the buildings (in- and extern) is explained. Keywords Energy efficiency · ESCO · Higher education institution · Sustainable business models

7.1 Introduction The energy consumption for buildings is an important part of the (worldwide) energy consumption [1]. Since fossil fuels are still used in many cases, the associated CO2 emissions together with other pollutants are considerable [1]. The share of the energy sector in the total greenhouse gas emissions fluctuated around 27% in the 2000– 2010 period and remains nearly constant [2]. Moreover, the European Commission has tightened the targets. An important share is provided for energy efficiency and performance in buildings [3, 4]. As Belgium is not on schedule for the share of renewable energy and for total energy consumption, additional efforts must be made especially for existing buildings as only about 1% of the building stock is renovated each year [5, 6]. In this paper, we demonstrate that although an energy performance contract (EPC) with an energy service company (ESCO) leads to effective energy savings for (school) buildings, other aspects play a significant role. For these buildings, an adapted business model is required, which involves/facilitates social and educational aspects, living laboratory facilities, comfort, and interaction with all the building users.

7.2 Background and Related Work 7.2.1 Energy and Buildings The energy reduction (for buildings) and efficiency can be considered as a wicked problem [7]. So, we need a threefold transformation: How we think, how we organize (sustainable and renewable energy, combined with a maintenance EPC), and how we manage things (new business models) [8]. Indeed the saving potential for the buildings is highly dependent on the building and the ambition of the owners [9]. To arrive at large comprehensive energy-efficient projects that can also be profitable for investors and moreover comprise a spread risk, pooling buildings are a successful approach [8, 9].

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7.2.2 Role of (Higher) Education Institutions (HEI) Both HEI in Flanders PXL University College and UHasselt are active in all domains of sustainable development (research, education, campus greening…). The University of Caxias Do Sul (UCS) (IMED Business School) is a center of expertise for innovation, creativity, and entrepreneurship with a focus on sustainability [10].

7.2.3 The Association of Schools in Sint-Niklaas It has 54 different locations in the city, united in four different school communities: GO! Education of the Flemish Community, Municipal Education Sint-Niklaas, the Sint-Niklaas primary, and the Sint-Niklaas secondary school community, both Catholic Education Flanders. These 54 school locations are managed by 11 different authorities (23 000 pupils and 2700 employees) [11].

7.2.4 Business Models 7.2.4.1

Innovation

Business model thinking is grounded on how value is created, captured, and distributed [12]. Business models and business model innovation are related, and research on business model innovation introduces the additional dimension of (open) innovation [13]. The concept of business models is integrated with a variety of academic disciplines [14] such as innovation and strategy [15], value generation [16], business architecture [17], interconnected and interdependent activity systems [18], and managerial and entrepreneurial analysis unit [19]. Publications on new business models have grown exponentially in the literature [20]; although the concept is still fragmented [21, 22]; Increasing concerns about capitalist society and economic institutions have provided the potential for sustainable business models that contribute to sustainable development [23]. Engagement with external stakeholders can tap into knowledge and innovation that can and will happen outside of the project and combine internal and external ideas. Multiple value creation The concepts of corporate social responsibility and sustainability relate well to transitions in government and higher education and are based on a dynamic combination of potential public private partnerships, i.e.:

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• the public part of the new business models that is mostly about societal impact; • the value proposition for the private part that relates to return on investment and financial benefits as a constant motivator.

7.3 Methodology 7.3.1 Output Driven Implementing energy optimization in buildings can be done in various ways. An exciting and increasingly used method for this is to have an energy service company carry out energy optimization. An energy service company or ESCO is, as determined by the directive 2006/32/EC of the European Parliament, “a natural or legal person who provides energy services and/ or other measures to improve energy efficiency in a user are establishments or buildings over a more extended period, usually 5–20 years, and accepts a certain degree of financial risk by doing so” [24]. Typical for ESCO is the provision of performance contracts, where a contractual guarantee is given to the customer on the estimated energy savings, but also comfort or energy delivery can be guaranteed via a performance contract [25, 26]. In addition with new technologies, new business models will be developed [27, 28] (see Fig. 7.1).

Fig. 7.1 Classical EPC and variation with extra investments [24]

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7.3.2 Social Innovation 7.3.2.1

Six Key Factors

The International Energy Agency [29] identified six key factors influencing building energy consumption, 50% of which can be linked to human interaction, including: (a) building operation and maintenance; (b) occupant activities and behavior; and (c) indoor environmental quality. The main areas of interaction between users and buildings include lighting, appliance electrical loads, ventilation, space heating, space cooling, and domestic hot water [30–32]. Knowledge of occupant behavior can lead to better energy prediction models, avoidance or at least minimization of interactions between building occupants, and energy-consuming systems. Occupancy patterns have been shown to have an impact on the energy consumption of buildings [30]. Schools are an impressive target group for carrying out EPC. Schools often do not have the technical knowledge necessary for the application of energy-saving measures. Besides, school buildings are often outdated and the arrangement of existing installations is often sub-optimal.

7.3.2.2

PXL Green andTech

At this moment, the PXL-Tech campus of the PXL University of Applied Sciences is organized as a living laboratory for all occupants in the building and sustainability is a policy in the department because • Innovative answers are needed for many complex societal challenges. • Social themes such as spatial planning, energy, agriculture, nutrition, social inequality, and health care require a new approach. • Since technology plays an important role here, sustainable action is one technological department in a significant core value. • Sustainability is included as a policy theme in the institutional review. • Graduates are more broadly formed and thus have more opportunities on the labor market. • (Sustainable and circular economy). • A growing group of students also expects a university of applied sciences to incorporate sustainability into his policy. • Advantage to the outside world (making an annual sustainability report). In addition the interactions between the physical environment, knowledge, attitudes, and behaviors are crucial for EE projects in HEI. The PXL will therefore undertake an energy literacy survey data on energy-related attitudes and the effects of EE projects on their health and well-being for students and all users/stakeholders of the building. This will be collected through a survey, a self-administered online

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questionnaire [33, 34]. The first results of a campaign of Energetic Quickscans (EQS) in 12 buildings of the PXL University of Applied Sciences are reported.

7.3.2.3

The Association of Schools in Sint-Niklaas

Has 54 different locations in the city, united in four different school communities. Special attention will be given to the unique project for Flanders: the energy coach. Two scenarios were developed for the two cases. A base case and enhanced EPC were calculated for the own PXL buildings. For the school community in SintNiklaas, after thorough preparation of the energy coach, an EPC was calculated for four schools from two scenarios who differ in the investment policy.

7.4 Results 7.4.1 PXL University of Applied Sciences Based on the data collected in the investment matrix, we have two investment scenarios: base case “heating/Sanitair Hot Water (SWH) and lighting” and an investment volume of e 2,610,903 which generates annual savings of e 242,569 e with a simple payback time of 11.5 years and an enhanced case “heating/SHW and lighting” an investment volume of e 4,145,854, which generates annual savings from e 296,581 with a simple payback time of 15.2 years (see Table 7.1). The comparison between the complete investment of the base case and the enhanced case shows that both the regular payback times and the updated payback times, respectively, 18.05 and 22.47, are higher than the possible contract duration of 15 years. Nevertheless, the PXL has the option to even limit the contract duration to 10 years, which has a number of advantages [9, 10].

7.4.2 School Association Based on Sint-Niklaas, there is a unique project/traject which involved an energy coach. The energy coach works for all 54 schools in Sint-Niklaas and has a daring and supportive role, but does not have a mandate or budget to make all schools energyefficient. The goal of the energy coach was that everyone in the school community became familiar with EPC. In total, this amounted to 11 representatives from the four different school communities. At the final stage, four school boards are considering switching to an EPC (details in Table 7.2). Two scenarios have been defined. Scenario 1 limits the yearly investment budget on behalf of the ESCO to e 12,500 per school and per year that the contract is supposed to last.

7 Energy Efficiency in School Buildings: The Need … Table 7.1 Base and enhanced case PXL buildings

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Topic

Base case

Enhanced case

Consumption total (kWh/y)

9.891.356

9.891.356

Consumption total (kWh/m2 /y)

136.9

136.9

Consumption total (e/y)

778.044

778.044

Consumption total (e/m2 /y)

10.8

Total investment (e)

2.610903

10.8 4,145,854

Total investment (e/m2 )

36.1

Savings (kWh/y)

3,329,616

4,156,002

Savings (kWh/m2 /y)

46.1

57.5

Savings (kWh/y)

3.065465

3,869,488

Savings incl rel (kWh/m2 /y)

42.4

53.6

Savings (e/y)

242.569

296.581

57.4

Savings (e/m2 /y)

3.4

4.1

Savings (e/y)

226.720

271.940

Savings (e/m2 /y)

3.1

3.8

Savings total (%)

33.66

42.02

Savings total incl effect rel (%)

30.99

39.12

Payback time (y)

11.5

15.2

Reduction CO2 (ton/y)

606

762

Table 7.2 Characteristics of the chosen schools for EPC School

Electricity

Gas

School 1

e 50,000

e 60,000

Annual consumption

347,852 kWh

1,718,979 kWh

School 2

e 52,296

e 77,101

Annual consumption

347,852 kWh

1,718,979 kWh

Fuel

e 110,000 e 129,397

School 3

e 54,663

e 61,111

e 22,284

Annual consumption

288,545 kWh

1,368,705 kWh

1,205,076 kWh

School 4

e 27,671

e 5627

e 45175

Annual consumption

209,984 kWh

347,131 kWh

692,016 kWh

Total

Total

e 129,397 e 78,473 e 455,928

This budget corresponds to more or less 10% of the average annual energy consumption. Taking into account the average lifetime of 15 years, an investment cost of e 187 500 per school is allowed. Scenario 2 considers an additional investment budget on behalf of the schools of e 200 000 per school throughout of the project, which increases the total investment cost allowed per school to e 387 500 (see Table 7.2).

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7.5 Discussion 7.5.1 PXL University of Applied Sciences The analyzes and comparisons with reference cases show that the energy savings are realistic for the PXL and that the ESCO market must be able to realize these objectives. In addition, there is an opportunity to cluster buildings (65.088 m2 ) all belonging to the university college (Table 7.3). It is however also important to transform the possible resistance of co-workers and users toward an ESCO into ownership. In this way, an intrinsic motivation and enthusiasm will arise for working with an EPC with the help of an ESCO/facilitator. As at the PXL-tech campus, the concept of a living laboratory for all occupants is being applied and sustainability is integrated in the policy, it seems obvious that this campus can function as a pilot project. The learning effects of an EPC introduction are important (curriculum, teachers and students) given the rollout of this approach to another campus. But at this moment, many other sustainability aspects are emerging as well such as circular (materials) and modular construction and circular area development, in combination with other environmental aspects as water reduction and waste prevention. On the other hand, since the rollout of such an EPC (see Fig. 7.2) comprises various steps, which must be done in a chronological order, an introduction of a “classical” EPC in this way has a limited learning effect (only for one generation of students because of time schedule). In addition, we also want to incorporate the results of the energy literacy survey. It is clear that (especially for a higher education institution) the interactions between the physical environment and students’ knowledge, attitudes, and behaviors are crucial for EE. So, the PXL is currently investigating whether an adapted EPC and thus a new business model can be developed in which the before mentioned learning elements (in addition to the measurable energy reduction, of course) can be incorporated (see Fig. 7.1). It is clear that real Table 7.3 Scenario 1 (scenario 2): Results cluster Elec (kWh)

Gas (kWh)

Fuel (kWh)

Annual consumption

1,182,194

3,822,663

2,863,236

Annual savings (%)

14 (32)

9 (15)

9 (9)

Total investment (e)

55,274

(1,227,082)

Annual savings (e/year)

55,551

(96,693)

Payback time (PBT) (year)

9

(11)

Discounted period of payback time (DPBT)(year)

11

(14)

IRR (%)

9.3

(5,7)

Netto Present Value (NPV) (e)

24,894,871

(167,524,64)

Reduction CO2 (ton/year)

167.9

(277,9)

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Fig. 7.2 Different roles in an EPC [28]

(academic) cases also indicate how modified or completely new business models can integrate social and environmental dimensions into business architecture and design. In this vision, the idea is at the same time to help maintain or even increase economic prosperity by incorporating the holistic concept of sustainability. This perspective is called sustainable business models (SBM) or business models for sustainability [35, 36].

7.5.2 School Association At first view due to the limited size of the energy consumption of some schools, the clustering might be an advantage. The preliminary process for implementing an energy performance contract was set. For the schools connected with the heritage of the city, the entrance in a clustering with other schools was too complex. However, because these schools were part of the city, it is easier to form a clustering with other buildings of the city of SintNiklaas (such as the local swimming pool). In addition, the way of decision making is entirely different for the GO! Schools in comparison to those of the Catholic Education Flanders and the framework is also different for these schools. Some of them might have other concerns than working with “big” energy performance contracts. So, the EPC project was started for four schools. Even though not all chosen investments lead to a positive Netto Present Value (NPV) for some schools, the cluster of four schools itself still has a positive NPV [23]. Due to the complex structure differences and the own culture within each school

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board, it is not possible to apply a copy-paste principle and to roll out an identical process in each school. Finally, the EPC was not started because of too low energy consumption as only one (smaller) school had decided to join the project, but it was the start for many other successful start-ups of energy-saving measures in a lot of schools.

7.6 Conclusion There is a great need for pilot projects dealing with EPC, not only to create trust but also to eliminate the unfamiliarity of the ESCO model. Clustering can offer many benefits, both technically and financially depending on the clustered buildings. However, the complexity of the cluster must be considered. In the case of PXL, the maintenance EPC route is the start to develop a tailor-made business model which will include also other sustainable parameters. The PXL will investigate a process for an extended sustainability performance contract, whereby energy saving will only be a limited objective of the process. Equally important are the achievements of other goals: • realization of other sustainability aspects, such as water saving, circular renovation, and waste reduction. • intensive involvement of students and teachers throughout the entire trajectory, over several academic years. • development of KPIs, measurements, and analyses (PXL-Tech as a living laboratory) • stakeholder management: involving other stakeholders on the university campus in Diepenbeek (UHasselt, Vlaamse Confederatie Bouw, etc.) and searching for synergies at the campus level (e.g., 1 central heating network for the entire campus, which the PXL-Tech building can also use) take in) The above relates well to transitions in government and higher education, where the public part of the (new) business models is mostly about societal impact and the private part relates to return on investment as the value proposition. There is a converging idea that it is necessary to focus on innovation (processes, products, or management) as a focus on sustainability, eco-innovation, green innovation, and low-carbon technologies. This is a critical factor for green business models or clean technologies, with an emphasis on reducing a company’s environmental and social impacts, leveraging its economic potential [22]. Also, the results from the survey will be used to determine the KPIs of the project. The link between sustainability and well-being offers the opportunity to shift the attention of students more to corporate social responsibility in combination with the Sustainable Development Goals (SDG). This is very important as these initiatives deal with the involvement and behavior of future generations “decision-makers”: For the school association in Sint-Niklaas, the EPC project was not started, but the intense preparation (a frequent consultation with all stakeholders’ school boards, staff

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members, teachers, pupils, and their parents) was the start for many other energysaving measures (1 on 1 replacements, continuity of energy consumption, and indepth structural measures). Didactic implementation is also of great importance for both educational institutions: for instance, a climate week linked to climate education during the school year (school association) and incorporating the co-creation and living lab aspect in the maintenance EPC project for PXL. Regardless of the structure or variables considered by organizations that created or innovated in sustainable business models, the potential for mutual gains has been verified, both by improving energy efficiency and investor financial returns and by applying small-scale, business-oriented principles, especially for the sufficiency aims. Managed network services are viable avenues for companies to pursue corporate or corporate sustainability and shared value by improving the effectiveness and efficiency of their activities in the spheres of the natural environment, society, and the economy and still profiting from these activities [20–36]. Acknowledgements The views expressed in this article are solely the responsibility of the authors. The authors are very grateful to Christine Schoeters (language), Laura Franco (references), Cas Boyen (inspiration), and Viviane Mebis (lay-out) in finalizing an earlier version of the article.

References 1. European Council 2014 (23 and 24 October 2014).: Conclusions on 2030 Climate and Energy Policy Framework [website]. (z.j.). Consulted on January 10th, 2019 from http://www.consil ium.europa.eu/uedocs/cms_data/docs/pressdata/en/ec/145356.pdf (2014) 2. Technology Roadmap: Energy-efficient Buildings: Heating and Cooling Equipment. OECD, IEA, Paris (2010) 3. European Union.: Entrepreneurship Education: a Road to Success. Final Report & Case Studies. [website]. (z.j.). Consulted on January 10th, 2019 from http://ec.europa.eu/growth/tools-databases/newsroom/cf/itemdetail.cfm?item_id = 8056&lang = nl (2015) 4. European Council.: [website]. (z.j.). Consulted on January 10th, 2019 from https://ec.europa. eu/energy/en/topics/energy-efficiency/energy-efficiency-directive (2016) 5. Van Steertegem, M.: Flanders Environment Report. Flemish Environment Agency. https:// www.eea.europa.eu/publications/air-quality-in-europe-2018, (final editing) (2013) 6. Rittel, H.W.J., Webber, M.M.: Dilemmas in a general theory of planning. Policy Sci. 4(2), 155–169 (1973) 7. Rotmans, J.: Review Change of Era—Our World in Transition. Boom Publishers, Amsterdam, November 2017 EAN 9789024419548 (2017) 8. Langlois, P., Hansen, S.J.: World ESCO Outlook. The Fairmont Press, Lilburn (2012) 9. Franco, D.V.H.K., Kuppens T., Beckers D., Cruyplandt E.: Energy Efficiency in School Buildings? How to Use in a Successful Way the Triple Bottom Line Framework? In: Kaparaju P., Howlett R., Littlewood J., Ekanyake C., Vlacic L. (eds) Sustainability in Energy and Buildings 2018. KES-SEB 2018. Smart Innovation, Systems and Technologies, vol. 131. Springer, Cham (2019) 10. Franco, D., De Vocht, A., Kuppens, T., Martens, H., Thewys, T., Vanheusden, B., Schepers, M., Segers, J.: Sustain. Edu. (2019). https://doi.org/10.1163/9789004396685_022

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11. Podmetina, D., Albats, E., D˛abrowska, J., Kutvonen, A.: Open Innovation and Business Models. The Open Innovation Handbook: http://oi-net.eu/ (2017) 12. Foss, N.J., Saebi, T.: Fifteen years of research on business model innovation: how far have we come and where should we go? J. Manag. 43(1), 200–227 (2017) 13. Vanhaverbeke, W., Chesbrough, H.: A classification of open innovation and open business models. In: H. Chesbrough, W. Vanhaver-beke, & J. West (eds.), New Frontiers in Open Innovation, pp. 50–68. Oxford: Oxford University Press (2014) 14. Chesbrough, H.: Open Innovation: The New Imperative For Creating and Profiting From Technology. Harvard Business School Press, Boston (2003) 15. Magretta, J.: Why Business Models Matter. Harvard Bus. Rev. 80(5), 86–92 (2002) 16. Osterwalder, A., Pigneur, Y.: Aligning profit and purpose through business model innovation. Responsible Management Practices for the 21st Century, pp. 61–76 (2011) 17. Schaltegger, S., Lüdeke-Freund, F., Hansen, E.G.: Business models for sustainability: a coevolutionary analysis of sustainable entrepreneurship, innovation, and transformation. Organiz. Environ. 29(3), 264–289 (2016) 18. Teece, D.J.: Business models, business strategy and innovation. Long Range Plan. 43(2), 172– 194 (2010) 19. Zott, C., Amit, R., Massa, L.: The business model: recent developments and future research. J. Manag. 37(4), 1019–1042 (2011) 20. Lüdeke-Freund, F., Dembek, K.: Sustainable business model research and practice: emerging field or passing fancy? J. Clean. Prod. 168, 1668–1678 (2017) 21. Lüdeke-Freund, F., Massa, L., Bocken, N., Brent, A., Musango, J.: Business Models for Shared Value—Main Report. Network for Business Sustainability—South Africa, Cape Town (2016) 22. Bocken, N., Short, S., Rana, P., Evans, S.: A literature and practice review to develop sustainable business model archetypes. J. Clean. Prod. 65, 42–56 (2014) 23. Lüdeke-Freund, F., Schaltegger, S., Dembek, K.: Strategies and Drivers Of Sustainable Business Model Innovation. In Handbook of Sustainable Innovation. Edward Elgar Publishing, Cheltenham, UK (2019) 24. Energy Performance Contracting. Consulted on January 10th, 2019 https://www.belesco.be/ solutions/energy-performance-contracting 25. Vanstraelen, L., Marchand, G., Casas, M., Creupelandt, D., Steyaert, E.: Increasing capacities in Cities for innovating financing in energy efficiency. In: A Policy Framework for Sustainable Real Estate in the European Union: Multidisciplinary Approaches to an Evolving System (2015) https://doi.org/10.1007/978-3-319-94565-1_5 26. Bertoldi, P., Boza-Kiss, B., Panev, S., Labanca, N.: ESCO Market Report 2013. European Commision, Luxembourg (2014) 27. Bleyl, J. W.: ESCO Market Development: A Role for Facilitators to play. Including national perspectives of Task 16 experts IEA DSM Task 16 discussion paper April. Retrieved from: http://www.ieadsm.org/wp/files/Tasks/Task%2016%20-%20Competitive%20Energy%20S ervices%20(Energy%20Contracting,%20ESCo%20Services)/Publications/Facilitators_Tas k16_Discussion%20paper_incl.%20national%20subchapter_140505.pdf (2014) 28. Facilitators Guideline Consulted on January 10th, 2019 https://guarantee-project.eu/ie/wp-con tent/uploads/sites/6/2013/11/EPC-Facilitator-Guidelines.pdf 29. International Energy Agency: IEA: Total Energy Use in Buildings: Analysis and evaluation methods. Energy in Buildings and Communities, Japan (2013) 30. Demanuelle. C., Twedell, T., Davies, M.: Bridging The Gap Between Predicted and Actual Energy Performance in Schools. World Renewable Energy Congress XI (2010) 31. Hong, T., Lin. H.-W.: Occupant Behavior: Impact on energy use of private offices. In: LAB, B. (ed.) A Sim 2012 (2013) 32. Berardi, U.: Stakeholders’ influence on the adoption of energy-saving technologies in Italian homes. Energy Policy 60, 520–530 (2013) 33. Cotton, D., Miller, W., Winter, J., Bailey, I., Sterling, S.: Developing students’ energy literacy in higher education. Int. J. Sustain. High. Educ. 16(4), 456–473 (2015)

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34. Cotton, D.R.E, Shiel, C., Do Paco, A.: Energy saving on campus: A comparison of students’ attitudes and behaviours in the UK and Portugal. J. Cleaner Prod. 129, 586–595 (2016) 35. Boons, F., Lüdeke-Freund, F.: Business models for sustainable innovation: state-of-the-art and steps towards a research agenda. J. Clean. Prod. 45, 9–19 (2013) 36. Evans, S., Fernando, L., Yang, M.: Sustainable Value Creation—From Concept Towards Implementation. In: Stark, R., Seliger, G., Bonvoisin, J. (eds.) Sustainable Manufacturing Sustainable Production. Life Cycle Engineering and Management. Springer, Berlin (2017)

Chapter 8

CFD-Based Analysis of Heat Exchanging Performance of Rotary Thermal Wheels H. M. D. P. Herath , M. D. A. Wickramasinghe , A. M. C. K. Polgolla, R. A. C. P. Ranasinghe, and M. A. Wijewardane

Abstract The demand for thermal comfort in buildings in hot and humid climates increases progressively. In general, buildings in hot and humid climates spend more than 60% of the total energy cost for the functionality of the air conditioning (AC) system. Hence, it is required to install energy efficient AC systems or integrate energy recovery systems for both new and/or existing AC systems whenever possible, to reduce the energy consumption by the AC system. Integrate a rotary thermal wheel as the energy recovery device of an existing AC system has shown very promising with attractive payback periods of less than 5 years. A rotary thermal wheel can be located in the air handling unit (AHU) of a central AC system to recover the energy available in the return air stream. During this study, a parametric study was performed using a computational fluid dynamics (CFD) software, to determine the optimum design parameters (i.e., rotary speed and parameters of the matrix profile) of a rotary thermal wheel for hot and humid climates. The simulations were performed for a sinusoidal matrix geometry. Variation of sinusoidal matrix parameters, i.e., span length and height, was also analyzed to understand the heat exchanging performance and the induced pressure drop due to the air flow. The results show that the heat exchanging performance increases when increasing the wheel rpm (revolution per minute). However, the heat exchanging performance increment rate decreases when increasing the rpm. As a result, it is more advisable to operate the wheel at a range of 10–20 rpm. For the geometry, it was found that the sinusoidal geometries with lesser spans and higher heights have higher heat exchanging capabilities. Considering the H. M. D. P. Herath (B) · M. D. A. Wickramasinghe · A. M. C. K. Polgolla · R. A. C. P. Ranasinghe · M. A. Wijewardane Department of Mechanical Engineering, University of Moratuwa, Katubedda 10400, Moratuwa, Sri Lanka e-mail: [email protected] A. M. C. K. Polgolla e-mail: [email protected] R. A. C. P. Ranasinghe e-mail: [email protected] M. A. Wijewardane e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_8

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sinusoidal profiles analyzed during the study, the geometry with 4 mm height and 3 mm width shows better performance than the other combinations. Keywords Air conditioning · CFD · Energy recovery · Heat exchangers

8.1 Introduction Air conditioning (AC) systems are essential to provide the required thermal comfort for occupants, to improve the productivity. According to the international standards, the indoor air quality has to be maintained within the acceptable ranges inside the conditioned spaces. Normally, buildings are the conditioned spaces and in developed countries 20–40% of the total energy is consumed by the buildings. In addition, more than 45% of the total energy usage in a building is consumed by the heating ventilation and air conditioning (HVAC) System [1]. In hot and humid climates, the percentage of energy used by building HVAC systems goes up to 60% [2]. In central AC systems, ventilation is provided to the conditioned space by supplying fresh air at the air handling system (AHU). According to the American Society of Heating, Refrigeration and Air Conditioning Engineers (ASHRAE) standards, minimum of 20% fresh air should be supplied for office buildings [3]. Therefore, 20% of the return air (typically, 24 °C and 50% RH in tropical countries) should be exhausted to the ambient environment to allow the provision for the 20% fresh air supply (typically, above 32 °C and 80% RH in Sri Lanka). Thus, it is encouraged to have an energy recovery system to recover the energy in the return air and pre-cool the outside hot air (fresh air) at the AHU. There are many energy recovery options available such as heat pipes, turnaround coils, thermosiphons, and twin towers other than the thermal wheels [4]. From the existing energy recovery systems, rotary thermal wheels can be identified as a good heat recovery technique. Rotary thermal wheels can be classified as heat wheels and enthalpy wheels. Heat wheels exchange only sensible energy in the two air streams while enthalpy wheels exchange both sensible and latent heat between two air streams [5]. Thermal wheels are devices similar to rotating cylinders with small channels. But in enthalpy wheels, additional desiccant coating has been applied to provide the moisture absorbing ability. Generally, the heat exchanging efficiency of thermal wheels is in the range of 50–85%. In rotary thermal wheels, the matrix geometry is complex to analyze with mathematical models and also complex heat transfer mechanism is impossible to simulate with mathematical models. Analyzing the desiccant wheel (rotary thermal wheel incorporated with desiccant material) from mathematical models has already been identified as challenging due to the challenges of modeling the moisture absorbing process in the desiccant material. So, computational fluid dynamics (CFD) models have to be used to study the phenomena in thermal wheels. Thermal wheels induce a pressure drop in the system and the certain amount of air mixing can be seen within the two air streams. In thermal wheels, media exposed to air flow varies from

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300–4000 m2 /m3 [3]. Moreover, the cross-leakages of the thermal wheels have to be analyzed as it causes to fresh air quality. Normally, the cross-leakage of the thermal wheels is about 4% without a purge section, whereas it reduces to 0.04% once the purge section is introduced [4, 6–8]. Çiftçi et al. [9] have investigated the performance of a thermal wheel which has an annulus-shaped microchannels; length of 100 mm and, 17 mm inner and 22 mm outer diameters, respectively. The modeling work was performed for the transient operation using ANSYS Fluent with the pressure-based solver. The results were obtained for with and without introducing the rotary speed for the wheel. It was found that the effectiveness for steady-state conditions (0 rpm) has become 0.3242 whereas the effectiveness for 10 rpm is 0.5262. This shows that the rotation between two air streams improves the heat exchanging efficiency in a thermal wheel. Softah [10] performed a computational study, using ANSYS Fluent, to analyze the performance of the thermal wheel for various materials (i.e., steel, aluminum, nickel, and copper) and various channel geometries (i.e., quadrangle, lozenge, and sinusoidal). Moreover, these studies have conducted for three different Reynolds numbers. The study revealed that the heat transfer performances of the thermal wheel increase when reducing the Reynolds number of the flow and the heat transfer performance of the thermal wheel became highest when the matrix cross section is quadrangle, whereas least performance was found to be for lozenge profile. When considering the channel material, heat transfer rate across the wheel was highest for copper, aluminum, nickel, and least for steel. Mahesh, et al. [11] have also studied on rotary thermal wheels and found that the effectiveness of the rotary thermal wheels reduces with the amount of ‘carryover.’ They have further observed that the effectiveness of the rotary thermal wheels reduces when increasing the rotational speed of the rotary thermal wheel. O’Connor [12] also designed a novel desiccant rotary thermal wheel for a passive ventilation system to reduce the pressure drop across the traditional honeycomb using CFD modeling techniques. This paper presents the summary of the CFD analysis performed to understand the performance of rotary thermal wheel for different sinusoidal matrix geometries and the associated heat transfer rate and fan power consumptions for the fluid flow.

8.2 Methodology 8.2.1 Selection of the Matrix Profile The heat transfer performance of three matrix geometries with same profile height and different widths were studied during this work using ANSYS Fluent CFD software. The length of the profiles was considered as 100 mm long and height and width and the matrix profiles are shown in Fig. 8.1. During the study, the diameter of the thermal wheel was considered as 1 m.

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Fig. 8.1 Three geometries considered for the study which are having various base widths

When considering a wheel, the number of channels in the wheel has to be evaluated and it was evaluated by taking the maximum allowable elements in the length of the aluminum sheet rolled to for the wheel. The length of the sheets used in the thermal wheel was calculated by Eq. 8.1. L=

R2 × π D+C

(8.1)

where R is the diameter of the wheel, D is the sheet thickness, and C is the clearance pitch. Number of elements =

2 × Length Channel Width

(8.2)

Using Eqs. 8.1 and 8.2, the results shown in Table 8.1 were obtained with the number of elements for respective sizes of the element widths. Porosity of the wheel matric was calculated considering the number of elements in the wheel geometry.

8.2.2 Mathematical Expressions The heat transfer rate and the general temperature profiles were obtained from the CFD tool. Apart from the standard parameters, following parameters were calculated using the expressions shown below. Fan power to overcome the pressure drop was calculated by, ˙ Fan Power = d P × Qs

(8.3)

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Table 8.1 Table of geometric parameters of thermal wheels Profile_1

Profile_2

Profile_3

Wheel thickness (m)

0.1

0.1

0.1

Wheel diameter (m)

1

1

1

Sheet thickness (m)

0.0002

0.0002

0.0002

Pitch(m)

0.004

0.004

0.004

Length of wheel profiles (m)

186.99956

186.9995627

186.9995627

Width of channel (m)

0.003

0.004

0.005

Number of channels

62333.188

46749.89068

37399.91254

Length required for a sinusoidal profile (m)

0.0072111

0.008944272

0.01077033

Length for sinusoidal sheet (m)

449.49101

418.143734

402.8093856

Material volume of the wheel (m3 )

0.0127298

0.012102866

0.011796179 0.078539816

Total volume

(m3 )

0.0785398

0.078539816

Air Volume(m3 )

0.06581

0.06643695

0.066743637

Porosity of the wheel (%)

0.837919

0.845901525

0.849806385

Wheel RPM was calculated by, RPM =

60 Simulation Time × 2

(8.4)

Amount of energy absorbed by channel is calculated by, E transf =

Energy Absorbed 2 × time

(8.5)

Energy can be transferred is calculated by, E transf =

Energy Absorbed 2 × time

(8.6)

Power absorbed per channel is calculated by, Wtot channel =

E(Energy absorbed) time

(8.7)

Watts per unit frontal area is calculated by, Wwatts per unit area =

Wtot channel Area equiped by channel

Regenerated power to the fan power ratio is obtained from,

(8.8)

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Rregen/Fan =

Wwatts per area Regenerated Power = Fan Power Fan Power

(8.9)

The ratio of the regenerated power to the fan power (which required to overcome the pressure drop induced due to the geometry) can be used to evaluate the performance of a particular type of a channel element and a rotary thermal wheel. Regenerated power from the geometry can be determined from the total integral heat flux values from the CFD simulations which calculates the net amount of energy absorbed by the geometry. From this method, the net amount of energy absorbed can be evaluated using an integral of the values obtained during the respective time period.

8.2.3 Mesh Figures 8.2, 8.3, and 8.4 show 03 different channel profiles considered during the analysis. ANSYS Fluent in-built mesh generation facility was used to generate the mesh of the above geometries. Mesh independence study was performed for a coarse, fine, and a finer mesh profiles and found that the mesh element variation affects after the second decimal place of the results. Therefore, a fine mesh was selected to generate the mesh of the profiles and obtained 286,626 nodes, 586,317 nodes, and 765,006 nodes for the profile 1, profile 2, and profile 3, respectively. Fig. 8.2 Geometry of channel with 1.5 mm base width

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Fig. 8.3 Geometry of channel with 2 mm base width

Fig. 8.4 Geometry of channel with 2.5 mm base width

8.2.4 CFD Simulation Pressure-based solver was selected as the solver (mass and energy conservation equations were solved simultaneously with the Navier–Stokes equations for the fluid domains), and the laminar model was selected since the air velocity is set to 2 m/s in

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the channel and that is inducting a Reynolds number around 100 in these geometries. The outlet sides were set as pressure outlets. The solution scheme was as SIMPLE for pressure velocity coupling, second order for pressure, and second-order upwind for momentum and energy equations. Also, it was assumed that the initial condition for the channel geometry is 303 K, and the initial temperature of the air domain is 308 K. Further, it was assumed that the channels were made of 0.2 mm aluminum sheets. Symmetric boundary conditions were applied to the left and right sides of the channel geometry. The top and bottom boundaries were defined as convection boundaries. Inlet and outlet were set as velocity inlet and pressure outlet. Also, the inlet side and the outlet side boundary conditions were kept adiabatic. Simulation for these systems were done as transient simulations. Therefore, the heat absorbent time period was considered as 6 s. The size of the time step was considered as 0.1 s. During the simulation, the total integral heat flux through the contact surfaces of fluid and channel was evaluated. Moreover, the pressure drops occurred through the channel geometry was also evaluated separately. In the simulation, the amount of heat transfer into the channel during a considered time period is evaluated. Also, the outlet temperature variation with the flow time has also been evaluated. The flow time was considered as a dimension which can be used to evaluate the time in a single side of a thermal wheel either fresh air side or exhaust air side. So, the wheel rotational speed can be obtained by assuming that in the flow time channel exists in a single side and that is used in calculating rotational speed of the thermal wheel. Using the simulation, the amount of heat absorbed to the channel geometry has been evaluated and that has been used when evaluating the heat exchanging performance.

8.3 Results Heat transfer rate through a single channel of a rotary thermal wheel for varied wheel speeds (rpms) was obtained for three different geometries; profile 1 (1.5 mm width channel), profile 2 (2 mm width channel), and profile 3 (2.5 mm width channel) as shown in Fig. 8.5. Since three geometries have different cross sections, it was required to evaluate the amount of heat absorbed by a unit cross-sectional area of the geometry since it has to be independent from the frontal surface cross-sectional area of the geometry. Thus, Fig. 8.6 shows the amount of heat absorbed per unit frontal area of the geometry. The heat transfer rate per unit frontal area demands another requirement, which indicates that the increment of width of the channel profile causes a reduction of pressure drop across the geometry. So, the effect of the pressure drops has to be considered in this study to comprehensively understand the performance of the geometry. When considering the pressure drop in this study, the fan power has been calculated which is needed to overcome the induced pressure drop. Therefore, a new parameter has been defined as the ratio of heat transfer rate per unit frontal area to fan power required to overcome the pressure drop as depicted in Fig. 8.7 (variation of this parameter with the rotational speed of the wheel is demonstrated).

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0.09 0.08 Heat Transfer Rate (W)

0.07 0.06 0.05 0.04 0.03 0.02 Prof 1-Watts Per Channel Prof 2-Watts Per Channel Prof 3-Watts per Channel

0.01 0

0

10

20

30

RPM

40

50

60

70

Fig. 8.5 Comparison of heat transfer rate versus RPM is profiles considered

Heat Transfer rate per unit cross sectional area (W/mm2)

0.01 0.009 0.008 0.007 0.006 0.005 0.004 0.003 Prof 1-Watts per Unit area equiped Prof 2 -Watts per Unit are equiped Prof 3-Watts Per Unit area equiped

0.002 0.001 0

0

10

20

30

40

50

60

70

RPM

Fig. 8.6 Comparison of profiles in heat transfer rate per unit area (frontal) versus RPM for considered profiles

8.4 Discussion The results from the CFD simulation can be used to identify some performance characteristics of thermal wheels for their critical geometrical parameters. The base width of the matrix channels and the rotation speed of the wheels were basically focused in this analysis. Figure 8.5 shows that the heat transfer rate of the geometry increases with the increment of rpm, nevertheless the rate of increment of the heat

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Heat Transfer rate/Fan Power

30 25 20 15 10 Prof 1 Regenerated Power/Fan Power Prof 2 Regenerated Power/Fan Power Prof 3 Regenerated Power/Fan Power

5 0

0

10

20

30

40

50

60

70

RPM

Fig. 8.7 Comparison in heat transfer rate per unit area (frontal) equipped/fan power versus RPM for considered profiles

transfer rate decreases with the rpm. Moreover, it further shows that the profile with the highest base width has the highest heat exchange rate. Figure 8.6 presents the heat transfer rate per unit cross-sectional area of a thermal wheel for different rotational speeds (rpms). It provides a better insight to the performance of the thermal wheel as it provides the heat exchange rate for unit frontal area. The figure shows that the heat exchange rate per unit frontal area is also increasing with the increment of wheel rotational speed, but the rate of increment is decreasing. Among the analyzed profiles, it can be seen that profile having the smallest base width has a higher heat transfer rate per unit frontal area. However, smaller the base width, higher the pressure drop across the heat exchange channel. Figure 8.7 shows the ratio of heat transfer rate per unit frontal area to the fan power required to overcome the pressure drop across the geometry with the variation of rotational speeds in the thermal wheel. It shows that the ratio of heat exchange rate per frontal area to fan power increases when increasing the wheel rotational speed (rpm), with a decreased rate for the wheel rpm. Results further show that the profile having the largest base width has the highest heat exchange rate per unit cross section for a unit fan power. Moreover, this shows that at lower rotational speeds (below 30 rpm) profile having smallest base width performs better than the other profile and, when the rpm is above 30 rpm, the profile having 2 mm base is performing better than the other profiles.

8.5 Conclusion The results obtained in the study show that the profile having the lowest base width is incapable of regenerating higher amount of heat from the exhaust air flowing through

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a channel in the thermal wheel. When considering the pressure drop induced due to the channels, the smallest base width profile performs better than the other profiles for wheel rotational speeds below 30 rpm. Above 30 rpm, the geometry which is having a 2 mm base width is performing better than the other two profiles. So, it can be recommended that having lower base width profiles for the places where the pressure drop induced is neglectable and to the places where pressure drop has to be considered the profile have to be selected according to the wheel rotational speed.

8.6 Future Work This CFD analysis is carried out only for three matrix profiles and analysis should be extended to analyze the performance for more profiles. Furthermore, the power associated to rotate the thermal wheel also has to be accounted since there is a tradeoff between the optimum rpm of the thermal wheel and the channel profile.

References 1. Pérez-Lombard, L., Ortiz, J., Pout, C.: A review on buildings energy consumption information. Energy Build. 40(3), 394–398 (2008) 2. Katili, A.R., Boukhanouf, R., Wilson, R.: Space cooling in buildings in hot and humid climates—a review of the effect of humidity on the applicability of existing cooling techniques. In: Proceedings 14th International Conference in Sustainable Energy Technology no. August, pp. 25–27 (2015) 3. A. Handbook, Heating, Ventilating, and Systems and Equipment (2012) 4. Pahwa, D.: For Indoor Air Quality (IAQ ) Versus Energy Conservation : Enthalpy Wheels Meet The Challenge 5. de Antonellis, S., Intini, M., Joppolo, C.M., Leone, C.: Design optimization of heat wheels for energy recovery in HVAC systems. Energies 7(11), 7348–7367 (2014) 6. Nia, F.E., van Paassen, D., Saidi, M.H.: Modeling and simulation of desiccant wheel for air conditioning. Energy Build 38(10), 1230–1239 (2006) 7. De Antonellis, S., Intini, M., Joppolo, C.M., Pedranzini, F.: Experimental analysis and practical effectiveness correlations of enthalpy wheels. Energy Build 84, 316–323 (2014) 8. Nóbrega, C.E.L., Brum, N.C.L.: Modeling and simulation of heat and enthalpy recovery wheels. Energy 34(12), 2063–2068 (2009) 9. Çiftçi, E., Sözen, A.: Numerical investigation of a heat wheel performance used for enthalpy recovery applications. Res. Eng. Struct. Mater (2017) 10. Softah, G.J.: A parametric study of the performance of heat recovery wheels in HVAC system engineering 11. Mahesh, S., Jayaraman, B., Madhumitha, R.: Innovative Design, Analysis and Development Practices in Aerospace and Automotive Engineering (I-DAD 2018) (2019) 12. O’Connor, D., Calautit, J.K., Hughes, B.R.: A novel design of a desiccant rotary wheel for passive ventilation applications. Appl. Energy 179, 99–109 (2016)

Chapter 9

A Simulation Method for Studying Urban Heat Islands at the Urban Scale Sara Shabahang, Brenda Vale, and Morten Gjerde

Abstract The urban heat island (UHI) effect is a global issue that can aggravate global warming (GW) and is a major problem in cities in developing countries like Iran. Local adaptation and mitigation strategies based on available data, tools, and resources in parallel with understanding the necessary level of intervention could be a valuable solution for reducing UHI effects in Iran. In this study, the simulation method ENVI-met was examined as a way of modelling potential strategies to predict UHI. This was done through creating different scenarios for selected areas of the city of Mashhad. In order to assess ENVI-met simulation outputs, the default inputs in both the modelled areas and simulation tool were manipulated. As the aim of this research was to see how much the simulation process could be simplified to suit the resources available in Iran, only ground surface temperature (Ts) was considered. The results revealed using local surface materials have a significant effect on the simulation results. In other words, simulating the model area with local materials shows how unevenly surface temperatures could be distributed. It also indicates an increase in average Ts. However, a long simulation period does not make a significant difference in terms of both average Ts and Ts distribution. Therefore, the recommendation to urban designers is to assign local street and paving materials to their model but to model for a shorter time when computing power is limited. These recommendations apply when urban designers need to examine different scenarios for areas and the size of a neighbourhood. Keywords Urban heat islands · Simulation method · ENVI-met

9.1 Introduction During the last decade, much research has been carried out on urban heat islands (UHIs). Land surface temperature (LST) is the main factor in monitoring city climatology, and hence UHIs. Methods for studying UHIs can be categorized into two main S. Shabahang (B) · B. Vale · M. Gjerde Victoria University of Wellington, Wellington 6011, New Zealand e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_9

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groups: simulations and observations [1]. Each approach has benefits and drawbacks. Therefore, it is the responsibility of researchers and urban managers to find out which method would best suit the study aim and available resources. Also, it is critical to have a localized methodology with regard to the accessibility of available data and tools and the level of intervention necessary [2, 3]. This research is thus trying to establish a method for estimating ground surface temperatures in developing countries like Iran where climatic and urban data are either not sufficient, not available, or very expensive to obtain. Urban-scale energy modelling (USEM) at the neighbourhood or urban level has begun to attract more attention [4]. USEM is a new opportunity which enables urban designers to have a general overview of the microclimate of large areas and evaluate strategies [4]. However, this opportunity is both expensive and will consume a large amount of time. It is just possible with the help of powerful computers, which are able to work in parallel [5]. For example, ENVI-met recommends using a computer with a 6–8 core CPU. However, this may not be feasible for developing countries whether the research is practice-based or university-based. Although there are some comprehensive reviews of urban-scale energy modelling in terms of its classification and evaluation [4], fewer studies have been done for the software known as ENVImet. ENVI-met is a simulation tool that has been widely used for investigating urban microclimate and urban surface temperate. It has also been used to look at urban microclimates and UHI mitigation [6–9]. The numerical microscale model is based on the interaction of urban materials and the climate. For instance, it takes account of solar radiation, including direct, diffuse and reflected radiation, along with airflow patterns and heat transfer from the urban surfaces to the air. By March 2018, some 280 ENVI-met-related journal and conference papers were available in the Scopus database, 77% of these studies having been done from 2012 to 2017. Other areas of investigation with ENVI-met include air quality focusing on pollutants [10]. Several researchers have compared ENVI-met results with observed or measured results [9, 11, 12], indicating that the results are very similar. Some of these studies have looked at local climate with different scenarios of urban greening [12–14], global warming effect [15], or urban morphology [16], concentrating on materials that will aid cooling and additional greening. The comparison of the spatial distribution of air temperature and humidity shows that the hotter/drier and cooler/wetter spots predicted by ENVI-met were generally consistent with the observations. Quantitative evaluation shows that the ENVI-met model is capable of predicting the microclimate in terms of its different variables with good accuracy [10]. It seems ENVI-met is a reliable tool if users know its potential and weaknesses and are able to interpret the outputs carefully [10]. When it comes to the detail of using ENVI-met, Perini et al. examined a new method for simulating the microclimate of urban areas. They used ENVI-met and TRNSYS by means of grasshopper. The study showed use of the pair of simulation tools enhanced the accuracy of the results [17]. However, fewer studies have concentrated on assessing model sensitivity to a variety of input data both for modelling and simulation parameters and how these affect the outputs [18]. Policymakers need

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reliable outputs. This study tested material options not in terms of cooling effect but in terms of their effect on Ts. It also looked at simulation start time options and their effect on simulation processing time and ground surface temperature (Ts). The main aim of this study was to explore how much simplification is needed in terms of simulation and the detail of urban areas to have both reliable results and save time and cost. Two different case studies with slightly different input values were simulated and their results evaluated. The input differences concern either simulation variables or material variables. The first case study deals with two different simulation periods and some slight manipulation of materials. The second deals with different surface, wall, and roof materials. Results are compared with the aim of reducing the simulation process both in digitizing and computing times. For all simulations, Ts is the main output. In ENVI-met, Ts means the temperature of the top surface of the soil. For this reason, wherever buildings are located the Ts is minimum [19].

9.2 Method ENVI-met V4.4.3 is a simulation tool that can model the interaction between built environments, green space, and local microclimate, with the ability to parametrize each category based on the ENVI-met database [20]. The database includes a range of different trees and vegetation, and wall, roof and surface materials. According to ENVI-met, the typical resolution starts from 0.5 to 5 m and the time frame takes from 24 to 48 h. However, using new improvements to the software, users are able to import computer-aided design (CAD) and geographic information system (GIS) format files and avoid the raster-based editor. The tool includes several applications for digitizing (Spaces & Monde), creating simulation files (ENVIGuide), simulation (ENVI-met) and presentation (Leonardo) [21]. Few studies have investigated these aspects of this simulation method. Grant et.al indicated that the grid size in the domain area plays an important role for air temperature [8]. Research by Ambersoni et al. shows that although the UHI effects are quite visible in even small areas of 350 × 350 m, ENVI-met mitigation strategies, like installing a green roof, have a small effect on the given area [7]. It, therefore, seems that the size of the model area is an important thing to determine, as well as the simulation duration, in order to achieve reliable results, in other words, the number of hours that should be simulated, given ENVI-met recommends 24 h, and how long it would take to run each simulation. Each application in ENVI-met has variety of setting modes. One task is to find which setting in different applications will most suit each research goal. The goal of this study was to use a model that was as close to the real world as possible, while consuming the minimum time and computing resources. This led to the need to investigate data management in terms of the available data and the required input data. In some cases, city data were very detailed while in others there was not enough data. For example, without a model of the existing trees to input into ENVI-met, which does not exist for Mashhad, it is too time consuming to enter each type of tree

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Fig. 9.1 Images of the selected areas: Ariel satellite views and GIS maps for Monde input

individually. Another thing to test, therefore, is whether tree cover can be simplified and generalized without affecting the results, although this is not reported on in this paper. To decide exactly what model to use for the main study, a small number of scenarios were simulated with ENVI-met V4.4.3 and the results analysed.

9.2.1 Case Study and Data Iran is one of the ten top producers of carbon dioxide (CO2 ) emissions in the world [22]. Mashhad (36.2605° N, 59.6168° E) as the second largest city of Iran with an area of 320 km2 and a population of around 3 million has been simultaneously experiencing urban growth, shortage of green space, and increasing LST [23, 24]. Under the Köppen climate classification, Iran has six different climate zones, these being hot desert climate, cold desert climate, hot semi-arid climate, cold semi-arid climate, hot summer mediterranean and hot dry summer continental climate/mediterranean continental climate [10]. Mashhad is located in the cold semi-arid climate zone [25]. This study is part of PhD research on the relationship of neighbourhood morphology to UHI. Around 10 different neighbourhoods with distinct urban textures were chosen for the Ph.D. study. Different pilot simulations, the subject of this paper, were conducted in two selected neighbourhoods to assess the function and reliability of the ENVI-met software. Each was first modelled and then simulated. Each area is 400 m by 400 m and is located in the centre of the city. Both areas are in the same district and close to each other. For the first area, which was called site 1: Ahmadabad, two different simulations were run. For the second area, which was called site 2: Majd, six different simulations were run (Fig. 9.1).

9.2.2 Model Areas an Input Data More accurate model areas were created with the new ENVI-met application Monde, using the Universal Transverse Mercator (UTM) coordinate system for georeferencing, and then imported shape files from GIS. The GIS shape files of buildings

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had a height tag. Digitizing was then carried out by importing topography from National Aeronautics and Space Administration (NASA) and finally generating ENVI-met model layers. The next step, in Space application, was that trees were added to the model area using aerial photographs from Google Earth. This process helped to achieve almost accurate building height information. No nesting grids were considered for this pilot study. Model Areas Setting: Ahmadabad (Site 1) and Majd (Site 2) Site 1: The model area has 400 × 400 × 73.5 grids with a resolution of 2 × 2 × 3 metres (m) per grid cell. Telescoping starts after 20.00 m. There is no rotation in areas. The highest object in the model area is 14.00 m. The majority of buildings are around 6.8 m high. At this, scale walls between separate buildings are removed automatically by ENVI-met. There are 470 buildings, and 121 Acers, 122 Pines and 149 Fraxinuses were simulated as the tree cover. The types of tree were narrowed down from a list found in the Park and Green Space Organization of the Mashhad City Council website. Site 2: The model area follows the same dimension as site 1. The highest object in the model area is 15.00 m. The majority of buildings are 5.2 m high. There are 943 buildings, and 172 Robinia Pseudoacacia and 113 Pines were simulated as tree cover. The types of tree were narrowed down from a list found in the Park and Green Space Organization of the Mashhad City Council website. Meteorological Input Data The profile for atmospheric boundary conditions was created with data from Mashhad city council, which in turn was extracted from metrological urban climate stations in Mashhad. In order to examine the effects of UHI, the hottest day was selected for simulation. The input data are found in Table 9.1 [26]. When simulation needs to run at the scale of a city, the question is whether the database (soils, plants, buildings and surface materials) needs to be generic or should follow local materials. The ENVI-met database provides a variety of materials for buildings, surfaces and vegetation. For the first model area, the default building wall and roof of ENVI-met values were used. Asphalt was assigned to streets and the yard material was changed to light concrete pavement for the Ahmadabad b and c scenarios (Tables 9.2 and 9.3). However, for the second model area, not only were the surface material changed from one scenario to another, but also the building roof and wall materials were changed. In order to localize materials, brick walls and concrete roofs were used as inputs in order to meet the general Iranian building wall and roof conditions for the last scenario (Tables 9.2 and 9.3). Table 9.1 Main meteorological input data Meteorological settings

Simulation date

Max wind Wind speed (m/s) direction

Min–max temperature (°C)

Min–max humidity

Input data

23 Jun 2018

14

20–30

%13–40

80°

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Table 9.2 Material input data: material: Ahmadabad and Majd Land cover

Material name

Profile

Wall material (default)

Wc

concrete 18cm, insulation 12 cm, 1 cm plaster

Roof material (default)

R

concrete18cm, insulation 12 cm, 1 cm plaster

Ground surface material (default)

Sl

Loamy soil

Surface material (default)

Sa

Asphalt

Surface material (default)

Sc

concrete pavement light

Surface material (default)

Sp

Pavement (concrete), used/dirty

Roof material (custom settings)

Rc

concrete 15 cm, concrete hollow block 30 cm, plaster 3 cm

Wall material (custom settings)

Wb

brick 2.5 cm, brick 20 cm, 1.5 plaster

9.2.3 Simulation Three alternative scenarios were created for site 1 and six alternatives for site 2 (Table 9.3). The main question in site one simulations was about the start time and simulation period. In the second step (site 2), different materials both for buildings and surfaces were modelled to study the basic output character of the model. ENVImet was run on an Intel(R) Core™ i7-6700 CPU @3.40 GHz with 32.0 GB of Ram 64-bit operating system for both sites.

9.3 Results 9.3.1 Site 1: Ahmadabad Figure 9.2 includes the digital maps which show the ground surface materials, the ground surface temperature outputs, and the distribution of ground surface temperature as a bar chart for the first site. All Ts maps are at 15:00. The input data are slightly different (Table 9.3). In all outputs, building areas are the coldest part of the neighbourhood with temperatures mostly around 20 °C. Trees create cooler areas in the streets. The difference between outputs a and b shows use of local materials just for surfaces leads to a drop in Ts (Table 9.3), Fig. 9.2). Average Ts decreases from 26.24 to 23.84 °C. However, comparing output b with output c with the 24-h simulation time difference does not show much difference in Ts (Table 9.3, Fig. 9.2).

Site 2

Site 1

3:00–15:00

3:00–15:00

3:00–15:00

3:00–15:00

3:00–15:00

Majd b

Majd c

Majd d

Majd e

Majd f

121 h

137 h

134 h

133 h

134 h

77 h

82 h

9:00–15:00

Ahmadabad c

7:00–15:00

250 h

Majd a

79 h

9:00–15:00 next day

Computation time (hours)

Ahmadabad b

Start–end time

Ahmadabad a 10:00–15:00

Scenarios name

Table 9.3 Simulated scenarios of two sites and Ts outputs

Wb

Wc

Wc

Wc

Wc

Wc

Wc

Wc

Wc

Wall material

Rc

R

R

R

R

R

R

R

R

Roof material

Sc

Sc

Sl

Sl

Sl

Sl

Sl

Sl

Sl

Soil material

Sa

Sa

Sa

Sa

Sp

Sp

Sa

Sa

Sa

Street material

Sc

Sc

Sc

Sl

Sl

Sl

Sc

Sc

Sl

Yard material

24.32

24.30

23.97

23.03

22.84

22.79

23.53

23.84

26.24

Average Ts (°C)

19.2–48.1

19.2–48.1

19.1–47.8

19.1–46.5

18.7–44.2

18.4–44.1

18.9–46.0

19.1–47-1

18.7–52.1

Min–max Ts (°C)

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Fig. 9.2 Ground surface material maps obtained using Space, Ts maps and bar charts obtained from Leonardo, bar charts show surface temperature distribution in site 1

9.3.2 Site 2: Majd Scenarios Majd a and Majd b are similar in all materials, the only difference between them being the start time of the simulations. For a, the simulation starts at 7:00 while b starts at 3:00. Both outputs are at 15:00, which again does not show much difference. The differences between outputs start to be clearer when the material of the yards is changed from soil to light concrete, the latter being the general material used for those areas in Iran. Bar chart d shows there is a five-degree gap between cool and warm areas. In other words, the temperature was not smoothly changing between areas. Changing surface materials to asphalt and light concrete (output e) are closer to reality, as most foundations in Iran are made of concrete and usually go some metres underground. The final model is the closet one to reality with building wall materials made of brick and roof material of hollow core concrete (Fig. 9.3). Model area 2 (Majd) shows using more realistic materials in the simulation, means the gap between building temperatures and ground surface temperature has increased. The difference between average Ts in Majd a (22.79 °C) and Majd f (24.32 °C) is approximately 2 °C. All simulations for the second study took almost the same time of around 130 h.

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Fig. 9.3 Ground surface material maps obtained using Space, Ts maps and bar charts obtained from Leonardo, bar charts show surface temperature distribution in site 2

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As a result, using materials similar to local materials shows a good surface temperature distribution in the neighbourhood. When ENVI-met is used as tool to compare different urban layouts in parallel, using long simulation periods could be avoided to save time and computing resources.

9.4 Discussion Among the UHI study approaches, simulation gives urban designers and city planners a chance to examine urban microclimate at the early stages of design. Considering all the complexities found in the urban texture and urban climate, simplification in simulation seems inevitable. However, changing a single input, either metrological or material, can affect the final results. While previous studies have placed more emphasis on validation of ENVI-met by comparing simulation outputs to measured data, this study focused on assessing the sensitivity of ENVI-met to input data, in particular input surface materials. Two typical residential neighbourhoods (mid-rise areas) were selected for studying Ts. The finding was as follows: • ENVI-met shows sensitivity to input surface material; therefore, using materials close to local materials results in more realistic outputs. • ENVI-met does not show sensitivity to the simulation start time. It means starting simulation just a couple hours before the target time could be enough. Since Ts maps are only concerned with the top surface of the soil, using local building materials did not show much difference. To understand the role of building materials, studying air temperature could be helpful. Future studies could consider the other aspects of ENVI-met input data, for example, the role of both surface and building materials on air temperature and the role of nesting grids and buffer areas around case studies help reduce computing time but still give reliable results for comparing scenarios.

9.5 Conclusion The ENVI-met simulation tool was tested for sensitivity regarding computation time and surface materials. Comparing the output of different scenarios showed manipulating inputs affected the results. However, these changes were either major or minor depending on what had been manipulated. Understanding the sensitivity of ENVImet to inputs can aid those wishing to undertake urban modelling at the early stages of urban design in order to see the best route to decreasing UHI. Acknowledgements The authors wish to express appreciation to Victoria University of Wellington for supporting this project by buying the science version of ENVI-met, and especially Stewart Millan

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for providing computers so as to run simulations in parallel. This work was supported by Mashhad City Council by providing GIS shape file details and metrological information.

References 1. Mirzaei, P.A., Haghighat, F.: Approaches to study urban heat island–abilities and limitations. Build. Environ. 45(10), 2192–2201 (2010) 2. Shabahang, S., et al.: the problem of lack of green space and rise in surface temperature in the city of Mashhad. In: International Conference on Sustainability in Energy and Buildings. Springer (2018) 3. Shabahang, S., Vale, B., Gjerde. M.: The problem of the modern built environment and enhanced urban warming in Iran. In: International Conference on Sustainability in Energy and Buildings. Springer (2018) 4. Sola, A., et al.: Simulation tools to build urban-scale energy models: a review. Energies 11(12), 3269 (2018) 5. ENVI-met. What are the minimum system requirements to run ENVI-met? Available from: https://www.envi-met.com/buy-now/(2019) 6. Acero, J.A., Arrizabalaga, J.: Evaluating the performance of ENVI-met model in diurnal cycles for different meteorological conditions. Theoret. Appl. Climatol. 131(1–2), 455–469 (2018) 7. Ambrosini, D., et al.: Evaluating mitigation effects of urban heat islands in a historical small center with the ENVI-Met® climate model. Sustainability 6(10), 7013–7029 (2014) 8. Crank, P.J., et al.: Evaluating the ENVI-met microscale model for suitability in analysis of targeted urban heat mitigation strategies. Urban Climate 26, 188–197 (2018) 9. Elnabawi, M.H., N. Hamza., S. Dudek.: Use and evaluation of the ENVI-met model for two different urban forms in Cairo, Egypt: measurements and model simulations. In: 13th Conference of International Building Performance Simulation Association. Chambéry, France (2013) 10. Tsoka, S., Tsikaloudaki, A., Theodosiou, T.: Analyzing the ENVI-met microclimate model’s performance and assessing cool materials and urban vegetation applications–a review. Sustain. Cities Soc. 43, 55–76 (2018) 11. Gusson, C.S., Duarte, D.H.S.: Effects of built density and urban morphology on urban microclimate—calibration of the model ENVI-met V4 for the Subtropical Sao Paulo Brazil. Procedia Eng. 169, 2–10 (2016) 12. Simon, H., et al.: Modeling transpiration and leaf temperature of urban trees—a case study evaluating the microclimate model ENVI-met against measurement data. Landscape Urban Plann. 174, 33–40 (2018) 13. Morakinyo, T.E., Lam, Y.F.: Simulation study on the impact of tree-configuration, planting pattern and wind condition on street-canyon’s micro-climate and thermal comfort. Build. Environ. 103, 262–275 (2016) 14. Elnabawi, M.H., Hamza, N., Dudek, S.: Numerical modelling evaluation for the microclimate of an outdoor urban form in Cairo. Egypt. HBRC Journal 11(2), 246–251 (2015) 15. Huttner, S., Bruse, M., Dostal, P.: Using ENVI-met to simulate the impact of global warming on the microclimate in central European cities. In: 5th Japanese-German Meeting on Urban Climatology (2008) 16. Tsoka, S.: Investigating the relationship between urban spaces morphology and local microclimate: a study for thessaloniki. Procedia Environ. Sci. 38, 674–681 (2017) 17. Perini, K., et al.: Modeling and simulating urban outdoor comfort: coupling ENVI-Met and TRNSYS by grasshopper. Energy Buildings 152, 373–384 (2017) 18. Arnfield, A.J.: Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. Int. J. Climatol. J. Royal Meteorol. Soc. 23(1), 1–26 (2003)

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19. ENVI-met. ENVI-met Output Files. Available from: https://envi-met.info/doku.php?id=filere ference:output:start(2019) 20. Huttner, S.: Further Development and Application of the 3D Microclimate Simulation ENVImet. Mainz University, Germany (2012) 21. ENVI-met. Learning & Support. 2019 2019/11/19]; Available from: https://www.envi-met. com/learning-support/(2019) 22. Nejat, P., et al.: A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting countries). Renew. Sustain. Energy Rev. 43, 843–862 (2015) 23. Rafiee, R., Mahiny, A.S., Khorasani, N.: Assessment of changes in urban green spaces of Mashad city using satellite data. Int. J. Appl. Earth Obs. Geoinf. 11(6), 431–438 (2009) 24. Alavipanah, S.K., Darrehbadami, S.H., Kazemzadeh, A.: Spatial-temporal analysis of urban heat-island of Mashhad City due to land use/cover change and expansion (2015) 25. Rubel, F., Kottek, M.: Observed and projected climate shifts 1901–2100 depicted by world maps of the Köppen-Geiger climate classification. Meteorol. Z. 19(2), 135–141 (2010) 26. Karimi, M.: personal Communication (2019)

Chapter 10

A Conceptual Framework for Interpretations of Modularity in Architectural Projects Ineke Tavernier, Charlotte Cambier, Waldo Galle, and Niels De Temmerman

Abstract In Flanders, circularity is becoming a well-discussed domain in the design and construction sector, in part due to the efforts of the Flemish Government. The ultimate goal of the transition toward a circular economy (CE) is becoming resource independent and reducing the sector’s environmental impact. However, architectural designers still struggle with the implementation of circular design choices in their practice. According to literature, compatibility is put forward as one of the circular design qualities. Compatibility between building components and modular building design go hand in hand. Moreover, recent developments in the CE have led to a renewed interest in modularity by architects, although the way of implementation and thus the interpretation of modularity have changed frequently over time. To foster implementation of this concept, there is a need for a conceptual framework that allows architects to have a clear overview of all different interpretations and to bring forward new ideas of modularity. This paper is not an exhaustive study of the history of all phenomena behind modularity, but rather an explorative approach for a better understanding of modularity in the design process. Therefore, archetypical examples and their related design concepts are presented to be as clear as possible. Finally, a preliminary framework for interpretations of modularity is proposed and this will be used as a starting point for further research. Keywords Modular building design · Modularity · Module · Circular economy

10.1 Introduction Building and rebuilding our houses, schools, and other infrastructure create welfare and well-being, but consume an important part of natural resources and raw materials. I. Tavernier (B) · C. Cambier · W. Galle · N. De Temmerman Department of Architectural Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium e-mail: [email protected] W. Galle Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_10

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By constructing and demolishing buildings, tons of waste are generated. Worldwide, the construction sector is responsible for 40% of the total waste mass [1]. A challenge arises when the growing demand for construction materials is in conflict with the depletion of resources. This challenge is increasingly recognized as a serious public concern and requires us to rethink how we deal with material use [2]. Since the industrialization, our economy is based on a linear ‘Take, Make, Consume, and Dispose’ model, where construction materials often end as waste [3]. In order to go from a linear toward a circular economy (CE) model, building products need to be reused. According to the booklet ‘Building a Circular Economy,’ compatibility is put forward as one of the circular design qualities which enable more effective reuse, recycling, and renewal of buildings and building components. Compatibility is the key principle for modularity. This principle encourages the possibility to recombine interchangeable building components.[4] Modularity is a design concept which is well-known for increasing quality, saving costs, and reducing construction time due to pre-assembled components [5]. Modularity seems promising in the context of the CE. However, it must be emphasized that modularity does not guarantee adaptable, neither ‘circular’ buildings. An example of a fully modular building is the 4th Gymnasium in Houthaven (The Netherlands). This school building was built in 2007 with the aim of being transportable and reusable. Despite the circular ambitions during the design and construction process, it was demolished only ten years later without reclaiming any material due to financial impact of transporting the building components.[6]. There are many applications of modularity within the construction sector with typical examples including volume units (e.g., Skilpod) and kit-of-parts (e.g., WikiHouse). Besides these two well-known applications, modularity has many guises and it can take many forms [7]. Consequently, there seems to be a disagreement about what modularity really covers and architectural designers are struggling with the implementation of this concept in practice. Moreover, for a real architectural project with its own site conditions, it is not clear which interpretation of modularity effectively contributes to the transition toward a CE. Therefore, this paper aimed to set up a conceptual framework to provide insights into incorporating interpretation that architects have been given to modularity. This framework is a first step in a larger research project to guide architects into making environmental-friendly modular design choices in ‘circular’ buildings.

10.2 Method To be clear and consistent, in this paper, ‘modularity’ and ‘modular building design’ can be considered as synonyms. There is neither a coherent understanding nor a clear overview of what modular building design can entail in architectural projects. Thus, the purpose is to set up a conceptual framework for interpretations of modularity to guide architects with the implementation of this concept in practice, in light of the transition toward a CE.

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The first step is to explore interpretations of modularity given by architects, in the past and the present, by means of a literature review. The exploration is based on an exchange between academic publications, books and realized architectural projects, both in retrospective and contemporary perspective. Only publications published between the years 2000 and 2020 and which can answer the question ‘What can modularity look like and how does it work in the entire building?’ are collected by thoroughly analyzing the title, the abstract, the method, and the results of the publications. The second step is to examine those interpretations and set up a conceptual framework. The examination is based on a number of suggestive questions (shown in Chap. 4 Examination) to find out on what the framework of modularity ought to be based. By doing so, a longlist of interpretations for modularity will be classified in a conceptual framework, which is approached from a circular perspective.

10.3 Exploration To understand how architects have interpreted modularity in the past and in the present, various paths can be followed. This explorative study investigates a nonexhaustive list for interpretations of modularity which are explained by means of a theoretical description, a motivation for applying that interpretation (if available), an archetypical example (if available), and related design concepts. The interpretations, indicated by keywords, are presented in a structured way below. In literature, some keywords are repeated in multiple paragraphs, but these words indicate separate discussions. Proportion. The oldest interpretation of modularity probably dates back to the Roman Republic Era. Vitruvius, architect and civil engineer, wrote the treatise ‘The Ten Books On Architecture,’ which served as a guide for building practices [8]. In this major source of classical architecture, modularity derives from the Latin term ‘modulus’ which is a calculation factor to determine the right proportions in temples. The ‘modulus’ is a mathematical approach that relates buildings with human proportions. Recurring terms in literature, related to the use of the ‘modulus,’ are proportion, repetition, scalability, and symmetry [8–10]. Standard measurement. A similar approach can be found in traditional Japanese houses where the ‘tatami’ is the basic proportion module. The ‘tatami’ is usually used as a bed, a seat, a table, or a walkway and determines the layout of the structure, the room dimensions, and the relationship of the elements to each other [8, 11]. This standard measurement helps forming a complete vocabulary and grammar of the entire building [11]. (Dis)Assembly, lightweight, transportable. In military operations, the need and demand for quickly assembled and disassembled, transportable, lightweight construction systems forced the development of modular shelters [8] (Table 10.1).

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Table 10.1 A non-exhaustive list of related design concepts collected from literature review on modularity in architectural designs Accessible

Generic

Pre-assembly

Simple

Adaptable Affordable

Independent

Prefabrication

Stackable

Interchangeable

Proportion

Circular

Standardized

Manageable

Rationalization

Sustainable

Compatible

Mass production

Removable

Symmetry

Consistency

Mobile

Repetition

Temporary

Dimensioned

Modifiable

Retrofitted

Transformable

Durable

Multifunctional

Reused

Standardization

Expandable

Multipurpose

Reversible

Unified

Flexible

Pace-layered

Reused

Varied

Functional

Portable

Scalability

Versatile

Affordability, mass-produced, pre-assembly. Following the American dream of building one’s own house in the last quarter of the nineteenth century, efficiency and affordability have become important characteristics. Richard Buckminster Fuller, an innovative designer, developed the ‘Dymaxion House’ (Table 10.2Fig. 1). This project was accomplished by pre-assembled modular components. These mass-produced, flat-packed, and transportable components minimized the onsite construction time and increased the project’s economic efficiency.[12, 13]. Expandable, standardization. The modular approach of the Crystal Palace (Table 10.2- Fig. 2), designed for the Great Exhibition of 1851 in London by Joseph Paxton, is defined by a strictly rasterized system based on a minimal amount of different standardized components [8]. The limited design, manufacturing, and construction period have led to the necessary choice for using as few different building components as possible. The shape and size of the glass panes are derived from the restrictions of the building process.[8, 14] Moreover, the Crystal Palace was the first multidirectional expandable system [15]. Construction kit, interchangeable, prefabrication. In America, during the Bauhaus era (1919–1933), Walter Gropius was a forerunner for the implementation of construction kit systems in architecture [8]. He was inspired by ‘Towards a New Architecture’ of Le Corbusier and by Friedrich Fröbel, who devised a toy based on basic geometric blocks. Gropius wrote about a ‘construction kit where, dependent upon the number and individual needs of the occupants, different living machines can be put together’ and ‘a house of variable elements that are manufactured in advance and can be combined and joined together much in the manner of a large construction kit’. Industrial principles, such as modularization, serialization, and prefabrication, were addressed due to the acute shortage of affordable homes [15]. An important characteristic of the modular construction kit is a dry-construction process and therefore the interchangeability, i.e., the ability of individual elements to form a whole [15]. This concept is often repeated in practice during and after World War II by,

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Table 10.2 An explorative overview of potentially modular buildings

1/Dymaxion House Richard Buckminster Fuller 1920 (©Bettmann)

5/Unité d’habitation Le Corbusier 1952 (©Lewis Martin)

9/Quinta Monroy Elemental 2003 (©Cristobal Palma)

2/Crystal Palace Joseph Paxton 1851 (©Wikimedia Commons)

6/Nakagin Capsule Tower Kisho Kurokawa 1972 (©Arcspace)

10/Nomadic Museum Shigeru Ban 2005 (©Flickr)

3/Maison Démontable Jean Prouvé 1944 (©Patrick Seguin)

7/Habitat 67 Moshe Safdie 1967 (©Jade Doskow)

11/Grundbau und Siedler BeL 2012 (©Götz Wrage)

(continued)

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Table 10.2 (continued) 4/Eames House Charles and Ray Eames 1949 (©John Morse)

8/SAR zoning 1964 SAR (©Charlotte Delhuvenne)

12/OpenStructures Thomas Lommée 2005 (©OpenStructures)

among others, Jean Prouvé (Maison Démontable, 1944, Table 10.2- Fig. 3), Charles and Ray Eames (Eames House, 1949, Table 10.2- Fig. 4) and Fritz Haller and Paul Schrärer (USM furniture system, 1965).[8, 15]. Proportion. During the postwar reconstruction, the use of a proportional measurement system was introduced in architectural projects as a consequence of architects’ struggles with changing procedures in the construction sector [16, 17]. Le Corbusier invented a system of measurement which became famous as ‘The Modulor.’ The idea behind this invention was to enable mass production and to follow the dimensional logic of industrial building production. This system was the result of an extensive debate about the discourse on proportions and standards. The visual harmony of the Golden Section, the Fibonacci numbers, and the physical dimensions of a human body were unified in ‘The Modulor’ [18]. The graphic translation of this measurement system is a human figure with a raised arm. In many of le Corbusier’s wellknown buildings, e.g., the Chapel at Ronchamp and the Unité d’habitation (Table 10.2- Fig. 5) at Marseille, an underlying dimensional logic based on the hereabove described measurement system can be detected.[8, 16, 17]. Division and multiplication. Modularity is essentially a strategic approach to cope with complexity. One way to manage complexity is by splitting or dividing the whole into smaller measurable parts, called modules [19–22]. Surfaces can be divided into grids, spaces into pieces and by doing so, rationalization enters the design phase [21, 23]. Modular structures can therefore serve as an interface which describes how those pieces or modules interchange with each other and how they fit together [23]. A similar approach can be found in Pallasmaa’s vision on modularity and logical– mathematical thinking in the sixties: ‘Architecture with an emphasis on structure was about the multiplication and division of measurements into equal parts’ [17]. 3D volume. The next interpretation of modularity is the factory-made 3D volumes which embodied an alternative concept to the traditional housing model as an answer to the population explosion. Archetypical examples of this concept are the Nakagin Tower (Table 10.2- Fig. 6) and Habitat 67 (Table 10.2- Fig. 7). The Nakagin Tower, designed by Kisho Kurokawa, was built in 1972 in Tokyo. The prefabricated volumes were slotted into the primary structure and could be exchanged for maintenance if needed [8, 21]. Habitat 67 was developed by Moshe Safdie in 1967 in Montreal. In this project, prefabricated concrete apartments are stacked on top of each other in order to form an organic whole.[8].

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Standard measurements. Stichting Architecten Research (SAR) introduced modular coordination to dimension and position building components in a harmonious way. The aim is to attune producers of building components to one another. Therefore, three zones are defined: a zone for living rooms and bedrooms (alpha), a zone for utility spaces (beta), and a zone for circulation (gamma) (Table 10.2Fig. 8). The modular coordination is based on the standard measurements of 10 and 20 cm.[24]. Adaptability and flexibility. Quinta Monroy (2003) (Table 10.2- Fig. 9), a low-cost housing project in Chile designed by Elemental, was characterized by flexibility through leaving an empty space between two houses. If the family expands, the house can grow with it. The modular approach lies in the adaptability of the empty space.[21]. Reusable, recyclable, temporary, transportable The Nomadic Museum (Table 10.2- Fig. 10) is a temporary construction aimed to travel around the world. The architect Shigeru Ban used cargo containers, which by definition are modular, as main building components.[25] Remarkable is that the museum is constructed out of recycled or recyclable materials [26]. DIY, Versatile. The ‘Grundbau und Siedler’ project (2012) (Table 10.2- Fig. 11), designed by BeL Sozietät für Architektur, relies on self-assembly and versatile possibilities for the building layout. Two construction phases can be distinguished. The first phase is to provide the permanent parts of the building: the load-bearing structure, the vertical circulation, and the services. Second, the inhabitants themselves are involved in the erection of their apartment. A complete kit of construction materials together with a detailed handbook is provided [27]. Kit-of-parts, interchangeable, grid, open building system. The open modular construction system OpenStructures (OS) (Table 10.2- Fig. 12) explores the principles of design for reuse through a generative dimensioning grid. By following the OS grid, interchangeability is guaranteed [4, 28].

10.4 Examination The transition toward a more responsible implementation of modularity in the design and construction sector today requires a conceptual framework to bring forward new interpretations. Modular building design can be fundamentally explained by ‘designing buildings in a modular way.’ According to Merriam-Webster’s online dictionary for English word definitions, modular means: ‘of, relating to, or based on a module’. Thus, in order to make a clear and consistent framework, modular building design must be examined through defining what a ‘module’ could be and what it could mean in relation to the entire building, or in other words, to which module a building can be reduced. Before establishing the framework for interpretations of modularity,

134 Table 10.3 Circular design qualities [4]

I. Tavernier et al. Reused

Recycled

Renewed

Compostable

Safe and healthy

Pure

Durable

Simple

Manageable

Accessible

Reversible

Independent

Compatible

Multipurpose

Varied

Location and Site

some intrinsic conditions must first be set to the artifact of a modular building in the CE: • At least one of the circular design qualities (Table 10.3) is incorporated in the module and/or in its relation to the other modules. This ambition will create new opportunities for closing material loops. • Compatibility rules are underlying the modular design. The module and its relation to the other modules are circumscribed by the system’s compatibility rules. Those rules are there to help the designer in the first place but also as a communication tool between the designer and the manufacturer. • The module only acquires meaning when it is actually used as a module in the entire building. ‘A single piece can never be modular, since modularity always implies a connection with other parts.’ [21] The examination of interpretations for modularity as explored above is based on the following suggestive questions: • • • • • • • • •

What is the smallest possible module? Is the module something abstract or something tangible? How are the modules connected to each other? How do the modules interact with each other? Is the module material or component dependent? What is the function of the module in the entire building? What geometry does the module have? Does the module have a structural importance? Are additional connectors necessary?

Through these questions, the interpretations for modularity can be classified into a framework which is aimed for a better understanding of modular building design. In that sense, a framework can only attempt to grasp interpretations of something that might be potentially modular. The guarantee that a building (or parts of it) is truly modular depends on its application in practice. Therefore, in this paper, only a conceptual approach of a framework is given. Four categories are distinguished: 1/Dimension module. The basic module is a geometric approach that determines the position and the dimensions of modular building components and its relationship to each other. The dimension module provides a distance which is based on a primary measurement system or multiples thereof. From a distance, a grid pattern can then be developed.[8].

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Table 10.4 A conceptual framework for interpretations of modularity in architecture 1/Dimension module

2/Building module

3/Kit module

4/Structure module

Simple, Varied

Reversible, Simple

Manageable, Reversible

Multipurpose, Varied

Examplesa Tatami The modulor SAR OpenStructures

Nakagin Tower Habitat 67

Dymaxion House Crystal Palace Maison Démontable Eames House Shigeru Ban

Unité d’habitation Quinta Monroy Grundbau und Siedler

a

The examples from the exploration phase are divided into four categories, but do not necessarily match the given circular design qualities

2/Building module. The basic module is a flat or volumetric approach and a modular system is allocated to one building module from which the entire building is largely constructed. Typical for this approach is that the entire building can be decreased or expanded by removing or adding building units. Modularity lies in the idea of a potentially expandable structure of interconnected elements.[21]. 3/Kit module. Compared to the second category, a kit module is not allotted to one building unit but is based on the combination of various building components. The building components can be combined as required due to a modular connection system. Lego® is a prominent example here, and building blocks of different sizes are used to create any geometric construction.[8, 21]. 4/Structure module. The basic module is a support structure of a number of floors, one above the other, inspired by Le Corbusier’s and Habraken’s visions [24]. A structure module is characterized by an open layout which is not entirely determined and can anticipate multiple-use scenarios [4] (Table 10.4).

10.5 Discussion and Conclusion The first part of this paper aimed to have a better understanding of the design concept modularity in architectural projects. Based on an explorative analysis of archetypical case studies in response to related design concepts, it can be concluded that the concept has frequently evolved over time. This evolution is driven by changes in society, such as shortage of (affordable) homes and new procedures in the construction sector. By analyzing interpretations for modular building design, this paper has shown how this concept is also gaining importance in the context of a CE. ‘New’ appearing-related design concepts can be cherry picked, such as adaptability, flexibility, interchangeability, recyclability, reusability, and versatility. This research has

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thrown up many questions in need for further investigation. It would be interesting to compare these initial interpretations for modularity with today’s experiences of architects by means of semi-structured interviews. It is important to unravel their concerns, needs, and difficulties according to the implementation of modularity in practice. The goal of the second part of this paper was to set up a preliminary conceptual framework of interpretations for modularity. An examination of the collected interpretations is done through some suggestive questions, which aim to reach the most elementary interpretation. These questions were not only of a geometric, structural, and functional order, but the way of connecting modules to each other and the importance of material choices were included as well, although the framework also requires further research. It was important to propose a first categorization (dimension module, building module, kit module, and structure module) in order to have a starting point which can be further adjusted, redefined, and re-examined by an in-depth analysis of about five case studies. Then, the design phase will be closely observed together with the architect in order to gain insights in the implementation of modular design choices. By doing so, the pitfalls and the strengths of applying modularity in architectural projects will become clear. This paper is to be seen as a contribution to a larger research project which aims for a better understanding how modularity can become a catalyst for a more circular building practice.

References 1. European Environment Agency: The European Environment State and Outlook 2010: Material Resources and Waste, 2012 Update. Publications Office of the European Union, Copenhagen (2012) 2. VRWI: Flanders in Transition, Priorities in Science, Technology and Innovation Towards 2025. Brussels (2014) 3. Vrijders, J., Romnée, A.: Naar een circulaire economie in de bouw. WTCB, Brussels (2018) 4. VUB Architectural Engineering: Building a Circular Economy. Design Qualities to Guide and Inspire Building Designers and Clients. Vrije Universiteit Brussel, Brussels (2019) 5. Bertram, N., Fuchs, S., Mischke, J., Palter, R., Strube, G., Woetzel, J.: Modular Construction: From Projects to Products. McKinsey & Company (2019) 6. Muis, R.: Modulair Gebouwd, Toch Gesloopt, https://architectenweb.nl/nieuws/artikel.aspx? ID=39654. 7. Corcuff, M.P.: Modularity and proportions in architecture and their relevance to a generative approach to architectural design. Nexus Netw. J. 14, 53–73 (2012). https://doi.org/10.1007/s00 004-011-0097-x 8. Staib, G.A., Dörrhöfer, A., Rosenthal, M.: Components and Systems Modular Construction. Birkhäuser, München (2008) 9. McEwen, I.K.: Vitruvius Writing the Body of Architecture. The MITT Press, Cambridge (2003) 10. Miller, T.D., Elgård, P.: Defining Modules, Modularity and Modularization. Presented at the 13th IPS Research Seminar (1998) 11. Tandela, V.: Form and Structure in Traditional Japanese Architecture as an Alternative Grid System Solution for Western Magazine Design, https://lib.dr.iastate.edu/rtd/17545/ (2001). https://doi.org/10.31274/rtd-180813-8327

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12. Lawson, M., Ogden, R., Goodier, C.: Design in Modular Construction. CRC Press, Taylor & Francis Group, Boca Raton (2014) 13. Whitehead, R.: Impediments to Integration: The Divergent Intentions and Convergent Expressions of the Dymaxion House and Demountable Space Structural Design. Presented at the Lowa, Lowa (2012) 14. Kuwayama, M., Käppeler, J.: The Process of Making. Birkhäuser, Basel (2019) 15. Seelow, A.: The Construction Kit and the Assembly Line—Walter Gropius’ Concepts for Rationalizing Architecture. Arts. 7, 95 (2018). https://doi.org/10.3390/arts7040095 16. Cohen, J.-L.: Le Corbusier’s Modulor and the Debate on Proportion in France. Archit. Hist. 2, (2014). https://doi.org/10.5334/ah.by 17. Kaila, A.M.: Moduli 225. Aalto University, Helsinki (2016) 18. Kuroishi, I.: Mathematics for/from Society: The Role of the Module in Modernizing Japanese Architectural Production. Nexus Netw. J. 11, 201–216 (2009). https://doi.org/10.1007/s00004007-0087-1 19. Erikstad, S.O.: Design for modularity. In: A Holistic Approach to Ship Design. p. 31. Norwegian University of Science and Technology, Norway (2019) 20. Langlois, R.N.: Modularity in technology, organization, and society. SSRN Electron. J. (2000). https://doi.org/10.2139/ssrn.204089 21. Meltzer, B., von Oppeln, T.: Rethink the Modular. Thames & Hudson, United Kingdom (2016) 22. Ozman, M.: Modularity. Ind. Life Cycle Open Inn. 6, 13 (2011) 23. Clark, B., Baldwin, C.: Design Rules, Vol. 1: The Power of Modularity. The MITT press (2000) 24. Leupen, B.: Frame and Generic Space. 010 Publishers, Rotterdam (2002) 25. Zheng, H.: The Failures of the Nomadic Museum Presented at the Pennsylvania 26. AD Classics: Nomadic Museum/Shigeru Ban Architects, https://www.archdaily.com/777307/ ad-classics-nomadic-museum-shigeru-ban-architects 27. IBA Hamburg—Basic building and do-it-yourself builders, https://www.internationale-bau ausstellung-hamburg.de/en/projects/the-building-exhibition-within-the-building-exhibition/ smart-price-houses/basic-building-and-do-it-yourself-builders/projekt/basic-building-and-doit-yourself-builders.html 28. Lommée, T.: OpenStructures, www.openstructures.net

Chapter 11

Building Energy Simulation of 19th C Listed Dwellings in the UK: A Strategy to Propose and Assess Suitable Retrofit Interventions Michela Menconi, Noel Painting, and Poorang Piroozfar Abstract Improving energy performance of traditional listed dwellings (TLDs) in the UK is much needed. However, there are issues to overcome due to their heritage value and to the complexity of their thermo-hygrometric behaviour. This on-going research project aims to propose a framework for interventions in TLDs in South East England to improve their energy consumption utilizing dynamic energy simulation (DES) of selected case studies in the city of Brighton and Hove, UK. Providing a brief overview of the methodology adopted in this study, the paper describes the approach devised to select the applicable measures for the dwellings investigated. It aims to improve their energy performance while minimizing the risks of unintended consequences on the fabric and occupants, as well as those of loss of heritage value. Therefore, the proposed strategy balances the need for individual solutions, underpinned by consistency in the rationale behind the choice of interventions and materials. Keywords Retrofit interventions · Traditional listed dwellings · Building envelopes

11.1 Introduction To improve the environmental impact of UK, dwellings is unquestionably an urgent task in order to fulfil the target imposed by the recently revised Climate Change Act [1], and to do so for existing building stock and buildings of cultural value is a challenging commitment. This research aims to propose a framework of interventions in traditional listed dwellings (TLDs) in the South-East of England, to improve the energy performance, thereby reducing their carbon emissions. To assess the benefits

M. Menconi (B) · N. Painting · P. Piroozfar School of Environment and Technology, University of Brighton, Brighton BN24GJ, UK e-mail: [email protected] P. Piroozfar Digital Construction Lab, University of Brighton, Brighton BN24GJ, UK © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_11

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of a range of carefully selected appropriate energy retrofit measures, it utilizes case studies (CSs) and dynamic energy simulation (DES) followed by sensitivity analysis. A methodological approach to help a systematic choice of sensible and safe measures from an array of available retrofit interventions was needed; this is what the paper aims to report on. The outcome of this stage will be used later, when the measures selected will be modelled and tested for condensation, and finally their effectiveness will be assessed, by applying them, individually and combined, to the base-case models created for simulation. The strategy developed for this initial selection of suitable interventions aims to minimize the risk of loss of heritage value, by assessing the risks imposed on the special features which contribute to the significance of the buildings investigated. To achieve this aim, the following objectives have been pursued: 1. A review of existing regulation and guidance, as well as precedent studies, on retrofit measures for buildings of heritage value and traditional construction. 2. An assessment of relevant features contributing to the heritage value of each individual dwelling investigated through desktop research, secondary data collection and walk-in surveys. 3. Verification and confirmation of findings of stages 1 and 2 through expert consultation (in-depth technical interview with conservation officers).

11.2 Background Literature Review 18% of all CO2 emissions in the UK stem from the residential sector [2]; the main source being the use of natural gas for heating [3]. Nevertheless, the UK faces a complex and delicate suite of issues when retrofitting this part of the stock, as it inherits the oldest dwellings in Europe [4], with more than one fifth of the total housing stock having traditional construction [5]. Traditional dwellings (TDs), built before 1919, are characterized by solid, permeable walls, single-glazing, and uninsulated roofs and floors [6], therefore, generally poorly performing, but also often of high architectural or historic value, hence listed. A special approach is necessary when selecting energy retrofit measures for TLDs; one that aims to strike a balance between the need for energy improvements, heritage conservation requirements, and thermo-hygrometric balance of their constructions [7, 8]. The “fabric first” approach, supported by BRE [9] and EST [10, 11] for housing retrofit in general, is not the one recommended by conservation bodies for TLDs. Firstly, because the “fabric” of TDs needs to be treated with careful consideration. Their thick, solid masonry walls are made of porous, breathable materials. Such constructions allow TDs to buffer both humidity and heat fluctuations [8, 12, 13]. Unsympathetic measures can irreparably alter their thermo-hygrometric balance, increasing the risks of unintended consequences, due to moisture accumulating, hence condensation and associated problems for the occupants’ health and for the fabric [6, 12, 14]. Hence, measures must firstly be “moisture-safe”. Secondly, because

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when it comes to TLDs, the fabric is where most of their heritage value is, therefore, any intervention must also be extremely cautious. “Sensible” retrofit measures should be aimed at ensuring that the features that contribute to their special character are maintained, hence, their heritage values are sustained and enhanced [5, 15]. Therefore, a special approach is advocated for TLDs, unanimously by the conservation bodies and previous research; one that, while aiming to improve the energy performance, takes into account their thermo-hygrometric balance, as well as their heritage value [As indicated in almost all of the general guidance and recommendations, for example, 5, 6, 12, 13, 14, 15, 16, 17, 27, 29, 30].

11.3 Methodology The study utilizes a mixed method approach on multiple case studies (CSs) of 19th C listed dwellings in Brighton and Hove, UK, selected as representative of the majority of the TLDs population in the South East England (for details about the CSs selection process please see [31]). The cases are all Regency or early Victorian converted flats, belonging to grand terraces of houses (see Fig. 11.1). Their size ranges from 60 to 200 m2 and they include dwellings on all levels (from lower ground floor/garden flats to top floor flats). The research is focused on building physical determinants with a potential impact on heating energy consumption, therefore, on passive retrofit measures, aimed at the envelope of TLDs only, and does not include behavioural determinants. The study is articulated around successive stages of (DES). Once the models were created (for details please see [32]), the first simulation was run for the dwellings in status-quo conditions and the data output at this stage was used for calibration with metered data (for more detail on this stage please see [33]). The calibrated models were then normalized to simulate their standardized statusquo performance. The normalization process devised, included, firstly: heating season, patterns of use and ventilation habits. Finally, the same heating system was applied to all the CSs, upgrading the status-quo with a high-efficiency boiler, as suggested by English Heritage [17, 34] and confirmed by previous research [35]. This way, a base-case scenario was generated for each CS, where only the physical determinants play a role in the final heating energy consumption output of the simulations.

Fig. 11.1 Brunswick square, one of the earliest regency developments in Brighton

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The following stage of research, described in this paper, was aimed to select the range of interventions applicable to the CSs. The base-case scenarios are then used, to assess the output of the chosen measures, individually and combined, by comparing the heating energy consumption and associated CO2 emissions, pre- and post-intervention.

11.4 Results and Discussion 11.4.1 Retrofit Measures for TLDs This stage of the study was aimed at generating the range of sensible and potentially safe retrofit interventions to be tested in the following stage of research. Developing the checklist of interventions, based on what was proposed by Historic England [15] for buildings of heritage value, and adapting it to the specific contextual conditions investigated in this research, three sets of retrofit options were considered applicable to the selected CSs Section 4: • Low-risk options: those options that can be easily applied, are the least expensive, not disruptive, totally reversible, minimize the risk of unintended consequences and do not require any planning permission and, generally, listed building consent (LBC); • Medium-risk options: those that imply the use of skilled workmanship and some costs, are more intrusive, need assessment of the risks associated with the occupants and fabric’s health and require planning permission, and, most of the times, LBC (although being generally permissible); • High-risk options: those that imply very skilled workmanship, incur higher costs, and cause disruption, have potential high risks for the occupants and fabric’s health and require planning permission and LBC (often not permitted, however, to be assessed case-by-case). In order to decide about the individual applicability of the available measures, an heritage significance assessment was first conducted of the selected CSs by means of visual and measured surveys, complemented by a desktop research, together with secondary data collection, to collect and analyse data about the heritage (architectural and historic) value of the buildings and their specific fundamental features in need of protection [34, 36]. Indoor temperature and relative humidity data logging, together with thermographic surveys, were then added to the previous methods, to aid understanding the composition of the thermal envelopes and the thermo-hygrometric behaviour of their fabric. Finally, an expert interview with a highly experienced senior heritage officer (interview with C.O., 12/12/2019), allowed for further refinement of the list of feasible interventions for the individual CSs investigated, with an overview of the actual applicability of the selected solutions in each specific context.

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A brief description of the measures available for each area of intervention and their applicability on the CSs selected is as follows: Whole Dwelling. Draught-proofing, although easily applicable and potentially beneficial to reduce air leakage and heat loss, and therefore heating energy consumption [37, 38] could potentially alter the breathability of outer envelops of TDs, for which an adequate ventilation is essential [12, 18]. To avoid risks of condensation, a value of 0.5 Ach has been considered desirable, as suggested by guidance and precedent studies [18, 30, 39, 40–43]. Windows. The current body of regulation and guidance agree in considering historic windows significant and irreplaceable features, that constitute an intrinsic part of the listed building and contribute to the character of its elevation [6, 15, 28, 30]. Therefore, in selecting retrofit measures for TLDs, retention of such elements is of fundamental importance, while aiming at upgrading their energy efficiency as much as possible [6, 14]. The low-risk option unanimously encouraged is the use of internal shading devices, such as curtains or blinds [5, 15, 26, 28, 30, 44]. Shutters can be reinstated without need for LBC, when evidence of their previous existence has been found in the dwelling in object or in other dwellings of the same level in the same listed terrace (interview with C.O., 12/12/2019). The greatest reductions in heat loss could potentially come from combining these measures, i.e. shutters and heavy curtains [6, 45]. Secondary glazing, when the internal detailing of the wall around the original window allows for it, is a straightforward option, and is generally encouraged by conservation bodies [5, 6, 14–16, 25, 26, 28, 30]. This intervention is common practice for listed buildings in Brighton and Hove (Interview with C.O., 12/12/2019). The performance achievable by means of secondary glazing can sensibly be increased using low-emissivity glass [13, 28, 34, 45–47] and further improved by opting for vacuum slim profile for the secondary glazing [35]. Although not requiring LBC in general, it is considered a medium-risk option, as it implies some level of disruption, higher costs than draught proofing and adding curtains and more skilled workmanship. While slim double-glazing, is proved to be effective [46] and applicable to listed buildings [48] it is not generally recommended by conservation bodies and is only considered as an extreme measure [15]. Even considering vacuum slimprofile double-glazed units, which can be as thin as 6.5 mm in total, the insertion of the new units in the original frame, requires very skilled workmanship, often needs a few alterations to frame and glazing bars to accommodate the new glazing and support the increased weight of it, and, overall, has a limited lifespan and does not guarantee the expected outcome [26, 28]. Slim-profile double-glazing is extremely unlikely to receive LBC if proposed for an original window in a building of heritage value when the historic frame still retains the original glass [14, 15]. The approach of conservation bodies is generally more flexible when the original window is lost and has been replaced with a new, unsympathetic one or the original glass has already been previously replaced [15].

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External doors. Historic doors, like windows, are considered important elements that contribute to the character of the elevation and to the heritage value of TLDs [6, 15, 18, 28, 30]. Insulating front doors requires LBC and can often be controversial as most of them are original. The decision concerning the actual applicability of such option needs to be taken on a case-by-case basis. Usually, the energy savings achievable with these interventions, are not significant, as front doors are generally made of solid wood and thicker than 60 mm; therefore, performing better than windows in their status-quo. This measure is often out-weighted by draught proofing of doorframes [18]. Furthermore, the intervention may not be straightforward, when the door is paned or glazed, which is the case for many Regency front doors. Ground Floors. When a historic finish is still in place, the range of energy retrofit interventions may be limited and need to be addressed maintaining the moisture equilibrium of the construction and preserving its heritage value [13]. When the floor finishes are not of historic value, adding carpets is a low-risk and easily reversible retrofit option for any type of ground floor construction, as long as the chosen materials are vapour-permeable, to avoid trapping moisture [15]. This solution, however, is considered applicable only when carpets are a practical choice in relation to the use of the space [24, 26] (Interview with C.O., 12/12/ 2019). In addition, the use of a vapour-permeable, thin, and high-performance insulation board is a medium-risk option applicable to solid and timber ground floors [15]. The implications of this intervention need to be carefully considered, as it could cause technical problems in adjoining floor levels [15, 24] and imply the need to shorten the height of internal doors, as well as to lift original skirting boards; therefore, leading to non-permissible changes in the overall proportions of a room (Interview with C.O., 12/12/ 2019). The use of concrete slab and insulation, generally an impermeable material, usually with an added layer of damp protection membrane, to replace historic solid ground floors, was a solution often applied during the last few decades to improve the energy performance while protecting against rising damp. However, it has been excluded as an option for TLDs because it has shown to be detrimental for traditional constructions. In fact, it alters the original breathability of the ground floor, inevitably leading to problems of excessive moisture being diverted and absorbed by the external walls, with negative consequences for the occupants, such as poor indoor air quality, and for the fabric, such as timber decay, infestation, and mould growth [13, 15, 22]. Limecrete floors are considered a safe solution to improve the energy performance of solid ground floors, and/or to repristinate their original thermo-hygrometric behaviour [13]. Lifting and reinstating the solid ground floor finish could be possible without damaging it. However, the complexity of such task makes it a high-risk option and a preferred choice when the floor finishes are not of historic value [14, 15, 22]. Timber ground floors can be insulated between the joists using vapour-permeable materials [13]. This solution, however, is also considered a high-risk one, applicable mainly when the floor-boards are not of historic value as their removal can lead

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to damage of the old timber-boards and irreversibly alter the characteristics of the original flooring [15, 24]. Ceilings. Insulating intermediate ceilings has been excluded as an option in this study because the adjacent dwellings, all occupied and heated, are assumed to be in adiabatic conditions with the dwellings investigated [33]; therefore, no heat exchange takes place between the simulated models and their adjacent properties. Roof. Loft insulation is unanimously considered, by conservation bodies, a low-risk option for pitched roofs, when the loft is not a habitable space, being the simplest, cheapest, and most straightforward approach [5, 6, 12–16, 20, 27, 29, 30, 49]. In fact, it does not involve the costs and disruption caused by insulating between rafters or renewing external roof finishes and the risks for the aesthetic character of the elevation, associated with raising the level of the finished roof. Ventilation should always be considered to reduce moisture risk [12]. Insulating at rafter or ceiling level is considered a medium-risk option, respectively, for pitched (when the loft space is habitable) [15] and flat roofs [15, 19]. It requires skilled workmanship, especially when historic ceilings are in place, to ensure that they will not be damaged [12]. Insulation above rafters and above flat roofs raises the level of the finished roof, which may often be non-permissible; therefore, it is considered a high-risk option. It might still be applicable, as long as the finished roof level does not unacceptably alter the rhythm of the adjoining terraced houses and if the loft space is habitable [15, 19, 21, 13]. Insulation below rafters (for pitched roofs) and below ceiling level (for flat roofs), while compromising internal historic finishes if in place, reduces the internal height, which is already limited in the dwellings investigated. Therefore, this option has been excluded in this study as it would unacceptably compromise the usability of the internal space [15, 19, 21, 13]. For all the solutions, a careful design and detailing, as well as the appropriate choice of materials, are of uppermost importance, in order to avoid risks of interstitial condensation [12]. External walls. New permeable renders and external wall insulation (EWI) have been excluded as retrofit options for both front and back elevations of all the CSs selected, as they would alter the exterior in thickness and, potentially, in color. This would imply a significant change in external appearance, when applied on one single unit within a row of terraced houses [12] and is certainly unacceptable for individual dwellings, occupying just one floor, within a grand terrace of houses. Internal Wall Insulation (IWI) is a particularly delicate intervention whose impact must be first carefully assessed against the heritage value and moisture balance of the construction [5, 6, 8, 12–16, 23, 27–30]. Different solutions should be considered for walls, depending on the type of internal finishing. Most of the front walls, in the selected CSs, are internally finished in plaster on lath. Whenever the room presents decorative elements, such as mouldings and stucco or timber works, in the form of cornices, dados, and skirtings, IWI is generally

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not allowed, with the exception of loose insulation blown behind plaster on lath (considered a medium-risk option). The latter, in fact, does not alter the internal finishing or overall proportions [6, 12, 13, 15, 23]. Alternatively, the high-risk option potentially permissible can be the use of highperformance thin insulation materials [50, 51] on the internal face of the wall. In this case, very limited change in thickness is recommended, not to alter the internal proportions, and in order to keep the decorative elements in place, because removing and reinstating them could pose risks to their integrity [15]. An added thickness of maximum 20 mm could potentially be permissible, if justified by a sensible improvement in the thermal performance of the construction (Interview with C.O., 12/12/2019). For walls without decorative elements, finished in plaster on lath or solid, an alternative high-risk option could be the use of other insulation materials (in boards, batts, or rolls), directly fixed to the internal wall’s face or using timber battens, balancing the need for energy improvement, with the loss of internal space and proportions, and the risks of condensation. The literature considers natural materials as the most applicable for traditional buildings and recommends their use. Indeed, they are the closest to the original materials and constructions, highly breathable by nature and suitable for totally reversible types of applications, available in different forms, capable of achieving thermal performance similar to that of oil-derived materials but also much safer to install, requiring minimal protective clothing and being totally eco-friendly, biodegradable and recyclable [13, 16, 35]. When the internal finish is plaster or plasterboard, the use of insulating plaster has been proposed as medium-risk option (after removing any plasterboard eventually in place) [13, 15]. Alternatively, the high-risk option also for solid walls is the use of high-performance thin insulation materials, that maximise the use of internal space, while providing very good thermal resistance [50, 51]. If applicable without compromising the heritage value of the dwelling, any type of IWI must be carried out providing careful detailing and using qualified contractors to avoid the risk of unintended consequences [12–15, 23], which can be particularly high for this intervention [35, 52–54].

11.4.2 Future Work The solutions defined this way are then utilized in the following stage of research to model new building elements. This will be done modifying the envelope of the base-cases, according to the new materials build-ups that will be devised for each intervention, aiming to achieve the target U-value imposed by the current building regulations for each element of the thermal envelope. Such material build-ups will then be assessed to ascertain the risk of interstitial condensation. Then, the new retrofitted elements will be applied to the base-case models to assess the reduction in energy consumption associated with space heating, and corresponding CO2 emissions, by means of DES. Finally, a sensitivity analysis will aid to assess the efficacy

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of the measures selected, individually or in combination with other measures, to help devise a framework for sensible, safe and effective energy retrofit interventions.

11.5 Conclusion The paper provides a tool that supports the decision process for the selection of applicable sensible interventions for TLDs aimed at the assessment of their effectiveness in reducing heating energy consumption; therefore, improving their environmental impact. The approach proposed, devised from the critical review of literature, stems from a clear understanding of the heritage value of the building, as well as of the behaviour of its traditional construction. It aims to address the need for a validated energy retrofit strategy for TLDs, characterized by the choice of individual measures, that take into account the specific listed building value, conserving and enhancing the original features of the dwelling, while ensuring that the change operated does not adversely affect the thermo-hygrometric balance of its construction and improves the thermal performance of the envelope. The methodological approach devised for this study builds upon that already taken by previous UK, EU, or international projects (e.g. CALEBRE, 3encult, Effesus, RIBuild) [55–58]. Stemming from a similar approach to retrofit to that of the of the CALEBRE project (aiming at improved air tightness and U-values of the external envelope), it filters the range of measures selected through the identification of the specific heritage values to be protected in each CS and the impact assessment of each measure on such values (similar to the 3ENCULT and EFFESUS projects) to come up with a list of sensible measures. The devised methodology then applies a further filtering of the measures selected, assessing the associated mould growth potential (as in the CALEBRE and RIBuild projects) to obtain the sensible-and-safe range of measures and determine in detail materials build-ups for each of those. Finally, it assesses the effectiveness of the interventions devised, by measuring their impact on energy consumption and associated CO2 emissions by means of DES (as in the CALEBRE and 3ENCULT projects). This strategy contributes to the novelty of the study, through a trade-off between the need for individual solutions—accounting for the complexity of all factors involved in each dwelling—and the necessity of consistency in the rationale behind the choice of interventions and materials.

References 1. Climate Change Act 2008 [Online]. Available: https://www.legislation.gov.uk/ukpga/2008/27/ contents. Accessed 10 Dec 2018 2. BEIS: 2018 UK Greenhouse Gas Emissions. Provisional Figures; Statistical Release: National Statistics. Department for Business, Energy and Industrial Strategy (BEIS) (2019)

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3. BEIS: Energy consumption in the UK (ECUK): End Uses Data Table. Department for Business. Energy and Industrial Strategy (BEIS) (2019) 4. Eurofund: Inadequate housing in Europe: Costs and consequences. Publications Office of the European Union, Luxembourg (2016) 5. STBA: Responsible Retrofit of Traditional Buildings. Sustainable Traditional Buildings Alliance (STBA) (2012) 6. England, H.: Energy Efficiency and Historic Buildings - Application of Part L of the Building Regulations to historic and traditionally constructed buildings. Historic England, London (2012) 7. BRE: Solid wall heat losses and the potential for energy saving. Building Research Establishment (BRE) (2014) 8. May, N., Sanders, C.: Moisture in Buildings: An Integrated Approach to Risk Assessment and Guidance. British Standard Institution (BSI) (2018) 9. Stenlund, S.: Applying Fabric First principles: Complying with UK energy efficiency requirements. Building Research Establishment (BRE) (2016) 10. EST: Refurbishing Dwellings – A Summary of Best Practice (CE189). Energy Saving Trust (EST) London (2006) 11. EST: Energy-Efficient Refurbishment of Existing Housing (CE83). Energy Saving Trust London (2007) 12. May, N., Griffith, N.: Planning responsible retrofit of traditional buildings. Sustainable Traditional Buildings Alliance (STBA) (2015). 13. Suhr, M., Hunt, R.: The Old House Eco Handbook: A Practical Guide to Retrofitting for Energy-Efficiency & Sustainability. UK, Frances Lincoln Limited (2013) 14. Scotland, H.: Short Guide - Fabric Improvements for Energy Efficiency in Traditional Buildings. Historic Scotland, Edinburgh (2013) 15. England, H.: Energy Efficiency and Historic Buildings: How to Improve Energy Efficiency. Historic England, London (2018) 16. Heritage, E.: Energy Conservation in Traditional Buildings. English Heritage, London (2008a) 17. Heritage, E.: Heritage counts. English Heritage, London (2008b) 18. England, H.: Energy Efficiency and Historic Buildings: Draught-proofing Windows and Doors. Historic England, London (2016a) 19. England, H.: Energy Efficiency and Historic Buildings: Insulating Flat Roofs. Historic England, London (2016b) 20. England, H.: Energy Efficiency and Historic Buildings: Insulating Pitched Roofs at Ceiling Level. Historic England, London (2016c) 21. England, H.: Energy Efficiency and Historic Buildings: Insulating Pitched Roofs at Raster Level. Historic England, London (2016d) 22. England, H.: Energy Efficiency and Historic Buildings: Insulating Solid Ground Floors. Historic England, London (2016e) 23. England, H.: Energy Efficiency and Historic Buildings: Insulating Solid Walls. Historic England, London (2016f) 24. England, H.: Energy Efficiency and Historic Buildings: Insulating Suspended Timber Floors. Historic England, London (2016g) 25. England, H.: Energy Efficiency and Historic Buildings: Secondary Glazing for Windows. Historic England, London (2016h) 26. England, H.: Traditional Windows: Their Care, Repair and Upgrading. Historic England, London (2017) 27. SPAB: Energy Efficiency in Old Buildings. Society for the Protection of Ancient Buildings (SPAB) London (2014) 28. SPAB: Briefing: Windows and Doors. London: Society for the protection of ancient buildings (SPAB) (2016). 29. STBA: Planning Responsible Retrofit of Traditional Buildings. Sustainable Traditional Buildings Alliance (STBA) (2015).

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30. Trust, T.P.R.: The Green Guide for Historic Buildings: How to Improve the Environmental Performance of Listed and Historic Buildings. Stationery Office, London (2010) 31. Menconi, M., Painting, N., Piroozfar, P.: A Future-Proof Cultural Heritage: A Holistic Mixed Methods Approach. In: Proceedings of 2018 Sustainable Ecological Engineering Design for Society (SEEDS) Conference, Dublin Institute of Technology, Dublin, Ireland, September 2018 (2018) 32. Menconi, M., Painting, N., Piroozfar, P.: Responsible retrofit measures for traditional listed dwellings: An energy simulation validation strategy. In: Proceedings of 2018 Sustainable Ecological Engineering Design for Society (SEEDS) Conference, University of Suffolk, Ipswich, UK, September 2019 (2019) 33. Menconi, M., Painting, N, Piroozfar, P.: Building Energy Simulation of Traditional Listed Dwellings in the UK: data sourcing for a base-case model. In: Littlewood, J., Howlett, R.J.,Capozzoli, A., Jain, L.C. (eds.) Sustainability in Energy and Buildings: Proceedings of SEB 2019, pp. 295–307. Springer, Singapore (2020) 34. England, H.: Conservation Principles. Policies and Guidance. London, Historic England (2008) 35. Rhee-Duverne, S., Baker, P.: A Retrofit of A Victorian Terrace House in New Bolsover: A Whole House Thermal Performance Assessment. Historic England, London (2015) 36. Hermann, C., Rodwell, D.: Heritage significance assessments to evaluate retrofit impacts: from heritage values to character-defining elements in praxis. In: Proceedings of Heritage for the future, 2015, Florence-Lublin (2015) 37. EST: Energy-Efficient Refurbishment of Existing Housing (CE83). Energy Saving Trust (EST) London (2007) 38. EST: Draught-proofing [Online]. Energy Saving Trust (EST). Available: https://www.energy savingtrust.org.uk/home-insulation/draught-proofing. Accessed 23 Sept 2019. 39. BRECSU: General Information Leaflet 9: Domestic Ventilation. Building Research Energy Conservation Support Unit (BRECSU), UK (1996) 40. BRECSU: Good Practice Guide 224: Improving Airtightness in Existing Homes.Building Research Energy Conservation Support Unit (BRECSU), UK (1997) 41. EST: Energy Efficient Ventilation in Dwellings – a Guide for Specifiers. Energy Saving Trust (EST) London (2006) 42. Jaggs, M., Scivyer, C.: A Practical Guide to Building Airtight Dwellings. NHBC Foundation (2009) 43. Ridley, I., Fox, J., Oreszczyn, T., Hong, S. H.: The impact of replacement windows on air infiltration and indoor air quality in dwellings. Int. J. Ventil. 1 (2003) 44. Fitton, R., Swan, W., Hughes, T., Benjaber, M.: The thermal performance of window coverings in a whole house test facility with single-glazed sash windows. Energ. Effi. 10, 1419–1431 (2017) 45. Baker, P.: Historic Scotland Technical Paper 1: Thermal performance of traditional windows. Historic Scotland, Edinburgh (2008) 46. Heath, N., Baker, P., Menzies, G.: Historic Scotland Technical Paper 9: Slim-profile double glazing - Thermal performance and embodied energy. Historic Scotland, Edinburgh (2010) 47. Wood, C., Boardass, B., Baker, P.: Research into the thermal performance of traditional windows: timber sash windows. English Heritage, London (2009) 48. Heath, N., Baker, P.: Historic Scotland Technical Paper 20: Slim-profile double-glazing in listed buildings - Re-measuring the thermal performance. Historic Scotland, Edinburgh (2013) 49. Changeworks: Energy Heritage: A Guide To Improving Energy Efficiency in Traditional and Historic Homes. Changeworks Edinburgh (2008) 50. Fantucci, S., Fenoglio, E., Serra, V., Perino, M., Duto, M., Marino, V.: Hygrothermal characterization of high-performance Aerogel-based internal plaster. In: Littlewood, J., Howlett, R.J.,Capozzoli, A., Jain, L.C.,(eds). Sustainability in Energy and Buildings: Proceedings of SEB 2019, pp. 259–268. Springer, Singapore (2020) 51. Proctor Group LTD: Spacetherm: Aerogel Insulation for Building & Construction (2019) 52. Banfill, P., Simpson, S., Haines, V., Mallaband, B.: Energy-led retrofitting of solid wall dwellings: technical and user perspectives on airtightness. Structural Survey 30, 267–279 (2012)

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53. Harrenstrup, M., Svendsen, S.: Full-scale test of an old heritage multi-storey building undergoing energy retrofitting with focus on internal insulation and moisture. Build. Environ. 85, 123–133 (2015) 54. Little, J., Ferraro, C., Arregi, B.: Historic Scotland Technical Paper 15: Assessing Risks in Insulation Retrofits Using Hygrothermal Software Tools. Historic Scotland, Edinburgh (2015) 55. Bastian, Z., Troi, A.: Energy Efficiency Solutions for Historic Buildings: A Handbook. Walter de Gruyter GmbH, Basel/Berlin/Boston (2014) 56. Eriksson, P., Hermann, C., Hrabovszky-Horváth, S., Rodwell, D.: EFFESUS Methodology for Assessing the Impacts of Energy-Related Retrofit Measures on Heritage Significance, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Uppsala universitet. Routledge, Historisk-filosofiska fakulteten & Konstvetenskapliga institutionen (2014) 57. Giorgi, M., Favre, D., Goulouti, K., Lasvaux, S.: Hygrothermal Assessment of Historic Buildings’ External Walls: Preliminary Findings from the Rebuild Project For Switzerland (2019) 58. Hall, M.R., Casey, S.P., Loveday, D.L., Gillott, M.: Analysis of uk domestic building retrofit scenarios based on the E. ON Retrofit Research House using energetic hygrothermics simulation – Energy efficiency, indoor air quality, occupant comfort, and mould growth potential. Elsevier Ltd (2013)

Chapter 12

Can Circularity Make Housing Affordable Again? Preliminary Lessons About a Construction Experiment in Flanders Taking a Systems Perspective Waldo Galle, Wim Debacker, Yves De Weerdt, Jeroen Poppe, and Niels De Temmerman Abstract Although home ownership is continuously supported by the regional authorities in Flanders, the housing market is not accessible to all. No less than 680,000 inhabitants of Flanders live in poverty and 153,910 are on a waiting list for social housing. In the transition toward the much-discussed circular economy lays, however, an opportunity to make quality-assured housing affordable again. The long-term gains, it promises by reuse and adaptability, could transform houses from a capital-intensive asset into a sustainable, risk-free investment. But although this sounds promising, practice so far has provided little evidence of the feasibility of this model. The question is therefore: how can we exploit the opportunities of the circular economy in construction to make the housing market more accessible? The opportunity to use the real-life context of a small building plot, and construction client, together with a network of research expertise and circularity forerunners was a promising breeding ground for a circular housing experiment and real-life learning. During a dozen team meetings, two large workshops and more than 20 face-to-face discussions with various stakeholders, the team that gathered around this context, and its network defined and refined the potential form and value of the aspired circular housing concept. This 2-year trajectory created a plethora of insights about that concept. Alternatives have been proposed and reviewed, for example, the creation of a Circular Economy Service Company, alternative forms of financing, circular design choices, or a service contract for technical services. In addition, all related questions and system challenges are mapped and structured. In this paper, we summarize this experience in 3 lessons learnt: a lesson about scale, one about values, and one about knowledge. They serve as hands-on advice increasing the “chances of success” of every next effort. W. Galle (B) · J. Poppe · N. De Temmerman Department of Architectural Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium e-mail: [email protected] W. Galle · W. Debacker · Y. De Weerdt VITO Transition Platform, Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_12

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Keywords Circular building · Housing market · Product-service-systems · Sustainability transitions

12.1 Context According to a tradition of private ownership encouraged by regional authorities, about 70% of all Flemish households own the house they call their home [1]— Fig. 2013. Although this may sound fine, reality is harsh. No less than 680 thousand inhabitants of Flanders live in poverty,1 being a threat to the sustainable access to quality-assured housing2 for many families [2, 3]. Figures make this threat tangible. For instance, 13% of those households who take a mortgage to acquire a house or apartment spend more than 40% of their income to it (a situation in which the total housing costs amount to 40% or more of the total available family income is generally regarded as problematic), 8% of the borrowers, spend even more than half of their income to a mortgage [4]. Concretely, this is the case for 16.2% of the Flemish population, and for 35.9% of the population with an income below the at-risk-of-poverty rate (Ibid.). Although home ownership is supported also today by the regional authorities [5] with, for example, low-rate mortgages, fewer and fewer people can buy their own house or apartment. Since 2000, house prices have more than doubled and 8% of the households with a mortgage indicate that they have had problems paying their housing costs during the past year [6]. Nearly 3% of them face these problems every month (Ibid.). A long mortgage term, a high credit amount and a large percentage of the income that goes to the loan: these factors are a real risk, both for borrowers and for banks, confirms also Jan Smets, governor of the National Bank of Belgium [4]. Although in Flanders, the house prices stay in proportion to the borrowing capacity3 [7], and the number of unpaid mortgages has fallen slightly in recent years [1] access to the housing market has not improved structurally. For example, the share of households with an affordability problem according to the residual income method relative to the budget norm remains more or less stable between 2005 and 2013 and decreases slightly between 2013 and 2018 from 10 to 7.6% for owners with a mortgage, but rises from 30.4 to 31.2% for private tenants [8–10]. In addition, 153,910 people in Flanders are on a waiting list for government supported social housing [11].

1 In

Flanders, living in poverty is defined as living with an income below the at-risk-of-poverty rate; i.e., an equivalent household income lower than 60% of the national median. For 2018, the at-risk-of-poverty rate for a single person was e 1,187 per month. For a family of two adults and two children under 14, the poverty risk limit was e 2,493. 2 According to Article 3 of the Flemish Housing Code (Vlaamse Wooncode), qualitative housing can be defined as the “guaranteed availability of a suitable home, of good quality, in a decent living environment, at an affordable price”. 3 The average house is paid about as much as the average family can pay.

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12.2 About WoonC Today, housing is expensive, and a mortgage risky. But imagine if housing could be different. If it could liberate living instead of hypothecating it; with adjustments that are easy and cheap, so the real estate value remains at the same level, and with building components and materials that can be repaired and recovered, so the residual value is highest at all times. That is the kind of housing WoonC wanted to realize. A Growing Network WoonC is a spontaneous network in which many partners joined forces. After all, switching from high-risk loans to more accessible housing is a huge step one cannot take alone. Only by sharing knowledge and experience, such a complex and thus difficult to define challenge can be tackled. Since autumn 2017, a group of researchers, companies, governments, and civil society organizations have been working together on the issue. The core team consisted of the initiators who are at the same time the owners of the plot that was available for experimentation, the future inhabitants as well as the supplier of a dismountable brick facade system. They addressed researchers from VITO and VUB Architectural Engineering, and brought them together with forerunners from business, policy, and architectural practice. Thanks to the broad network, this core team has access to, it was possible to organize many discussions and workshops with dozens of stakeholders. This way WoonC might seem to resonate with sector and stakeholder platforms for the circular economy in the Netherlands such as Platform31 [12] and Platform cb’23 [13]. However, WoonC was a voluntary, non-subsidized, and small-scale initiative made possible only by the personal commitment of all members and the possibility to align this engagement with their professional activities. A Pairing Opportunity: Circular Economy and Affordable Housing Today, a new economy is in sight. Using and reusing construction materials and building components are better for the environment and our wallet than continuously producing, consuming, and wasting them. In this, circular economy lays an opportunity to make quality-assured housing affordable again. Today, we are not dealing too cleverly with our houses; they are worth more than we might think. When, for example, we renovate the roof, we often choose new tiles and simply throw away the old ones. Even though the old roof tile is not broken, and new tiles are not stronger, selling materials is “good for the economy” and everyone likes something new now and then. But that is a missed opportunity. Not only do we create a lot of waste with every renovation, we must also produce new materials and send extra trucks on our already congested highways; that while we could have reused the old roof tiles. Under the right conditions, such reuse or efficient recycling can even save money, reduce environmental impacts, and avoid nuisance. As this example illustrates, we identify in the much-discussed transition to an economy of closed material flows, i.e., the circular economy, opportunities to make

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housing affordable again. Closing material cycles through designing-out waste maximizes the value of buildings and building products over time [14, 25]. This long-term gain could transform houses from a capital-intensive asset into a sustainable, riskfree investment. But although this sounds promising, practice so far has provided little evidence of the feasibility of this model. The question is therefore: how can we exploit the opportunities of the circular economy in construction to make the housing market more accessible? An Experiment There is only one way to find that out: by doing. The opportunity to have access to a small building plot, a construction client and a future inhabitant, together with a network of research expertise and circularity forerunners was a promising breeding ground for a circular housing experiment and real-life learning [15]. Today, reuse is not self-evident. Old windows, for example, are not insulating enough to be reused as such, and internal walls are difficult to recover without damaging them. Fortunately, design principles and qualities that enable future reuse are emerging. Windows could be remanufactured, and walls can be disassembled and rebuilt efficiently if their connections are reversible and materials durable. Therefore, for example, we wonder under which circumstance such choices can be made. By thinking about the second, third, and perhaps fourth life of a roof tile, a window or any other part of a house, the chance increases that that component will be worth more in the future than if it had to be thrown away. By designing for change and building circularly, materials remain useful and valuable. But in the future, will we be talking about material-yields instead of waste-costs? Therefore, we had to question, for instance, under which circumstances materials have a residual value. The challenge is complex. That is why the team worked at two “sites” at the same time, each with its own objective, speed, and collaborators. On the one hand, there is the housing challenge: an economic market that could undergo a slower transition. On the other hand, there was the concrete and agile pilot project: a small terraced house to be built in Wilsele near the city of Leuven, on a lost piece of land giving access to garages on the terrain behind.

12.3 Lessons Learnt With the support of a broad network, the WoonC core team could set up a local transition experiment and tried to give shape to an affordable housing concept aligning with the idea of a circular economy. After a two-year trajectory, the house has not yet been realized; however, mainly objections—not related to the circularity aspect— caused delays when applying for the building permit. Nor have we found a concluding answer to the question “how can we capture the long-term value of a circular house so that today’s housing market would become more accessible to households unable to buy and become the owner of their house or apartment”.

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By focusing “financing” and “ownership” rather than on design aspects and technical challenges, and by wanting to break through a traditional and entrenched housing system, the core team did not make it easy for itself. However, during a dozen core team meetings, two large workshops (in February 2018 with 8 banks and other investors, in April 2018 with developers and service providers), and more than 20 face-to-face discussions with stakeholders (from June 2018 to July 2019 with material producers and suppliers, local authorities and developers), the team and its network defined and refined the potential form and value of circular housing concept. This process created a plethora of insights. In this paper, we summarize this experience in 3 lessons learnt: a lesson about scale, one about values and one about knowledge.

12.3.1 About Scale and Scalability Imagine if private persons, companies, and governments invest together in sustainable, circular houses, and apartments, or if occupants own part of their house and rent another part. Who is at that point responsible for maintenance? What is the most suitable building design? And what housing policy should a municipality adopt? These and similar questions were raised during the many stakeholder discussions and illustrate that the alternative housing solution WoonC was looking for would mean a significant change to many entangled systems and not just our small-scale pilot. Without renewed roles and agreements among the involved actors, such change would not be possible. One way to make those arrangements is to set up a CESCO, or Circular Economy Service Company. Such an organization could match, though performance-based contracts, the diverse demand side of the housing market to the fragmented material supply market and take managerial concerns away—a concern that is often cited as a barrier to switch to circular building solutions [17–19]. When presenting this structure to the WoonC network, we were able to identify two successive barriers. First, we heard “that doesn’t exist, so it’s impossible”. A typical, wait-and-see response of actors who do not face an immediate need for an alternative or do not value its advantages—in the Belgian construction sector, there is generally sufficient demand today, with well-filled order books [16]. At the same time, there is a limited marketing value attached to circular building, the government does not generally enforce it and the interest rate on mortgages remains low [20, 21]. No surprise, of course, that today there is no ready-made offer for housing-as-a-service. However, that is no reason to put it aside as an alternative for that group of households that do not stand a chance of getting a mortgage. So, the next question was: “who can do this”? Posing that, we stumbled upon the second barrier. In the network, sufficient knowledge to do establish a CESCO was present—asset management, monitoring and maintenance are already offered as separate services today. But, when we change our perspective from the general

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interest to the individual one, the question is whether offering housing-as-a-service is also profitable for the involved companies. In any case, setting up a CESCO within the context of this pilot project was clearly not an option. The single small house that we wanted to realize not only had a high material cost per useful surface area, but also the development and organizational cost of operating such as service company would be too high according to the candidate service providers we were able to talk to. We have learned that today, in the given pilot project, it was not possible to increase the affordability through a combination of circular building principles and product-service-systems. Offering the whole house as-a-service was not possible. But, for parts of the house such services are available. The Dutch House Energy Optimum (HEO) concept, whereby the building envelope and heating system are delivered as a package with a long-term performance guarantee and which can be adapted to new energy technologies, could be a step in the right direction. Translating the concept from The Netherlands to Belgium, including its performance guarantee, control system and insurance, is something the design team is still working on today. So, what appeared to be a small and safe experimental set up in the first respect, ultimately turned out to be not big enough to get started. The lack of scale and scalability, of both the project and the evaluated alternative, has been a determining aspect in its implementation possibilities. As far as scale is concerned, our lesson is therefore: choose the project in which the boundary conditions allow you to experiment on one specific aspect. An aspect where change is difficult, but possible.

12.3.2 About Values Although many people could benefit from an alternative to a mortgage, from the discussions, it appeared that an increase of quality and accessibility of the housing market would be hardly appreciated more than conventional ownership. Established systems that perpetuate ownership, such as tax benefits, weigh more heavily in the choice between the conventional and alternative option than the long-term gains of circularity. Uncertainty and risk may play a role in this together with a possibly higher initial cost of a circular building [22, 23]. During the discussions, stakeholders sometimes raised: “there is no such demand”. However, we did have one: we addressed the societal challenge of affordable, highquality housing. This niche and pairing opportunity opened the door to large and small investors and credit institutions, to developers and building managers, nonprofit organizations, social housing companies, contractors, and designers. It is a societal challenge that connects people. But, it is also a challenge that exposes some fundamental pains; that shows how difficult it is to change existing systems, and forces us to ask ourselves “what is really valuable”? That question required the core team to make choices and trade-offs. Two examples. First, when is the housing market accessible enough? Should the monthly housing costs be as low as possible? Should the cost over the entire life span decrease? Or,

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is the quality and security of housing most important and can maintenance and management come at a price? Altogether, the core team agreed on the challenge to develop an alternative that is competitive with the private rental market but offers more quality and participation over time. To evaluate the mere financial aspects of this challenge, a life cycle costing approach was taken. Initial explorations with this method illustrated that such alternative is only feasible if the long-term value of the land and property can be guaranteed (the location plays an important role here, cf. VUB Architectural Engineering [26] and if the residual value of building materials and components is sufficiently large (the circular material and design choices and building techniques play a role here, cf. Ibid.). A second question for the team was: how circular should the pilot project be? It was a trade-off between the financial value of the property, the demonstration value of the experiment and the feasibility of its practical realization. Because it soon became clear that alternatives could not be developed from scratch, and the core team wanted to continue learning and experimenting actively, the team decided to split the experiment into different sub-challenges. One sub-challenge was, for example, the engineering of the load bearing structure to maximize its residual value. To this end, divergent use scenarios were outlined in a close cooperation between the designer, future user and the supplier of the cross laminated timer structure. Another sub-problem, the performance guarantees for the technical services and related collaborations were addressed. To this end, the designer, potential investors, and service providers studied the way in which the Dutch HEO concept could be translated to the Flemish context. This choice put learning back at the forefront and realistically recognized the conclusion that an integral approach was not possible within this pilot. These are all value considerations the team faced. Thereby, affordability has always been the connecting compass. Our lesson is that such a pairing opportunity, what one really wants to achieve with the circular economy, is the basis to rely on.

12.3.3 About Knowledge During the trajectory, we were able to map the conventional housing system and put alternatives forward during workshops and face-to-face conversations [18]. Not only were the hypothetical strengths and opportunities of the circular economy collected, also many questions, challenges, and obstacles were raised by members of the core team and the consulted stakeholders. These challenges, 52 in total,4 have

4 Keep

in mind that these challenges and questions are the result of a mere exploration of the coupling opportunity between circular building and an accessible housing market. When linking circular building with sustainable energy, spatial planning, water consumption or another societal challenge, one can expect many additional challenges.

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been listed and structured by organizing them into 12 “transition tracks”.5 These tracks include (1) Careless housing, (2) Conscious living, (3) Closed loop logistics (4) Circular Construction, (5) Credit-free living, (6) Circular business models, (7) Alternative financing, (8) Real estate legislation, (9) Roles and company structures, (10) Responsible taxation, (11) Renewed socio-ecological values, and (12) New partnerships. Several challenges are related to each other. For example, calculating the life cycle cost (LCC) was proposed to set out alternative financing schemes, but also to compare the long-term gains of different design choices. Further, some challenges are very general, for example, “We look for a definition of the accessibility, affordability and quality of housing”, while others are more concrete, for example, “In order to put a circular financing into practice, risks must be compensated. Therefore, we compare which guarantee mechanisms already exist”. Knowing this, it is not the goal to pinpoint once and for all 12 transition tracks. Rather this categorization helps to generate an overview, divide tasks and set priorities. Identifying 52 challenges was indeed rather overwhelming for the core team. Tackling them all in just one experiment was obviously not feasible. After all, the housing market is a traditional system entrenched with many other systems including construction practices, logistics, legislation, etc., as the 12 tracks illustrate. Moreover, being part of that system ourselves, not knowing what the exact problem is, let alone knowing how the answer could look like, these are typical characteristics of “Wicked Problems” [24]. Under those circumstances the list of challenges was instructive, even only a few questions could be addressed in the experiment. The next step for the market and researcher together, is to find out which answers are already known. And where answers are missing, challenges can be translated into concrete experiments and pilot projects. The related lesson of the WoonC core team is accordingly: do not start from scratch but choose a specific challenge and get to work, while sharing lessons further, for example, through transition networks such as Circular Flanders.

12.4 Conclusion The journey undertaken by the core team and broader network of WoonC brought individual insights and changed practices, not least those of the architects and researchers involved. The ability to experiment within the context of a concrete construction project led to new relationships, shared knowledge, and authentic learning experiences. During a reflection moment among the core team members, it became clear there is a lot of satisfaction about that learning, not in the least because it increases the “chances of success” of every next project. In experiments, and that 5 Due to page limitation, this list of challenges could not be attached to this publication. Nevertheless,

it will soon be made available through the Web site: https://vlaanderen-circulair.be/nl/doeners-invlaanderen/detail/woonc, and can be provided on request.

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is what the WoonC core team has learned, it is most-useful to consider from the beginning the aspects scale, value, and knowledge: • Scale. A lot is already possible, but you must choose the right project in which its size is not a problem but offers opportunities. • Value. Circularity is not an end, but a means. When you get to work, think carefully about what you really want to achieve economically and socially. • Knowledge. And do not start from scratch but choose a specific challenge and build a network in which you learn together with others. However, as a result of these three limitations, there is no concluding answer to the question “how can we exploit the opportunities of the circular economy in construction to make the housing market more accessible?” Nevertheless, alternatives have been proposed and reviewed, for example, the creation of a Circular Economy Service Company and the value network in which it could be situated, alternative forms of financing such as bullet loans or cooperative funds, well-considered design choices at building and material level to maximize the asset value over time through generality and adaptability, or a service contract for technical services. In addition, all related questions and system challenges are mapped, and the potential form and value of the circular housing concept has been refined. Together they provide the starting point for new experiments and pilots. The opportunity to enter many discussions with each other, but also with banks, developers, suppliers and contractors to discuss all alternatives and aspects and codesign took a lot of time and effort but is the reason why we came to new insights. The experimental space and time we have been given and created is a signal to the whole practice and policy that bottom-up experimentation is possible and useful. Acknowledgements The authors wish to express their gratitude for this learning opportunity to the initiator of the transition experiment Patrick Vandenbempt and Jasper Vandenbempt (Speed Building Systems Belgium), their fellow members of the core team including Hilde Carens (Vlaams Energiebedrijf), Lode Goethals (Bast Architects and Engineers) and Meg Scheppers (Flanders’ Agency for Public Waste, Materials and Soil OVAM), as well as all participants to the workshops and face-to-face meetings.

References 1. Heylen, K.: Inkomens- en vermogensverdeling gerelateerd aan wonen. Steunpunt Wonen, Leuven (2018) 2. Federale Overheidsdienst Sociale Zekerheid:. Interfederale armoedebarometer (Interfederal poverty barometer). Retrieved January 2020, from https://enquete.mi-is.be/barometer (2019) 3. Luyten, D., Emmery, K., Pasteels, I., Geldof, D. (eds.): De sleutel past niet meer op elke deur: dynamische gezinnen en flexibel wonen. Garant, Antwerp (2015) 4. De Cort, G.: Gezinnen lenen weer hogere bedragen. De Standaard. (2017) 5. Flemish Government.: Beleidsnota Wonen 2019–2024 ingediend door Matthias Diependaele, Vlaams minister van Financiën en Begroting, Wonen en Onroerend Erfgoed (policy brief). Brussels. (2019)

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6. Heylen, K.: Starters op de eigendomsmarkt. Evolutie tussen 2003 en 2013. Steunpunt Wonen, Leuven (2013) 7. Vastmans, F., Buyst, E., Helgers, R., Damen, S.: Woningprijzen: woningprijsmechanisme & marktevenwichten, pp. 1–89 (2014) 8. Heylen, K., Le Roy, M., Vanden Broucke, S. Winters, S.: Wonen in Vlaanderen, de resultaten van de woonsurvey 2005. Departement Ruimtelijke Ordening, Woonbeleid En Onroerend Erfgoed, Woonbeleid, Brussel (2007) 9. Heylen, K., Vanderstreaten, L.: Wonen in Vlaanderen anno 2018. Steunpunt Wonen, Leuven (2019) 10. Vanderstreaten, L., Vanneste, D., Ryckewaert M.: Grote Woononderzoek 2013. Transitie en continuïteit in het Vlaamse woonmodel. Trends in woningtypologie, grootte en -bezetting tussen 2001 en 2013. Steunpunt Wonen, Leuven (2016) 11. Santens, T.: Wachtlijsten voor sociale woning nemen fors toe en zetten Vlaamse onderhandelingen op scherp. Retrieved January 2020, from https://www.vrt.be/vrtnws/nl/2019/08/19/ sociale-woningen/ (2019) 12. Platform31.: Circulaire woningbouw. Retrieved January 2020, from https://www.platform31. nl/thema-s/energietransitie/circulaire-woningbouw (2019) 13. Platform cb’23.: Framework circulair bouwen. Retrieved January 2020, from https://platformc b23.nl/ (2019) 14. Ellen MacArthur Foundation: Towards the Circular Economy, an economic and business rationale for an accelerated transition. Ellen MacArthur Foundation, Cowes (2012) 15. Geels, F., Grin, J., Loorbach D., Grin J.: Transitions to Sustainable Development : New Directions in The Study of Long Term Transformative Change. Routledge, New York (NY) (2011) 16. Atradius.: Market monitor, focus op de bouwsector - prestaties en vooruitzichten. Antwerp (2019) 17. Debacker, W., Manshoven S.: State of the Art, Key Barriers and Opportunities for Materials Passports and Reversible Building Design in the Current System (Synthesis report No. D1). The BAMB2020 Consortium, Brussels (2016) 18. Galle, W., Debacker, W., De Weerdt, Y., De Temmerman N.: Housing in the circular economy, lessons from value network mapping as a transition experimentation tool. In: Proceedings of the International Sustainability Transitions Conference 2019. Ottawa: Carleton University (2019) 19. Vandenbroucke, M., De Temmerman, N., Paduart, A., Debacker, W.: Opportunities and obstacles of implementing transformable architecture. In: Proceedings of the International Conference on Sustainable Building. University of Minho, Guimarães (2013) 20. ING Bank: Rethinking Finance in a Circular Economy. Financial Implications of Circular Business Models (2015) 21. ING bank: De circulaire corporatie, naar volledig duurzame huisvesting. Amsterdam (2018) 22. Galle, W.: Scenario Based Life Cycle Costing, an Enhanced Method for Evaluating the Financial Feasibility of Transformable Building (Doctoral Thesis). Vrije Universiteit Brussel, Brussels (2016) 23. Galle, W., De Troyer, F., De Temmerman N.: The strengths, weaknesses, opportunities and threats of open and transformable building related to its financial feasibility. In: Proceedings of the International conference on the Future of Open Building. ETH-Zürich, Zürich (2015) 24. Vandenbroeck, P.: Working with Wicked Problems. King Baudouin Foundation, ShiftN, Brussels (2012) 25. Ellen MacArthur Foundation.: Intelligent Assets: Unlocking the Circular Economy Potential. Ellen MacArthur Foundation and World Economic Forum as Part of Project MainStream, Cowes (2016) 26. VUB Architectural Engineering: Building a Circular Economy. Design Qualities to Guide and Inspire Building Designers and Clients. Vrije Universiteit Brussel, Brussels (2019)

Chapter 13

Challenging Architectural Design Choices with Quantified Evaluations of the Generality and Adaptability of Plan Layouts Camille Vandervaeren, François Denis, Waldo Galle, and Niels De Temmerman Abstract Buildings’ obsolescence and inefficient use can be prevented by designing general and adaptable plan layouts. General plan layouts accommodate different needs without being altered, while adaptable plan layouts can be easily altered thanks to, for example, demountable walls. A design-support method to quantify the generality and adaptability of plan layouts is the Spatial Assessment of Generality and Adaptability (SAGA) method Herthogs (Doctoral thesis. Vrije Universiteit Brussel, Brussels, 2016 [1]). To the knowledge of the authors, SAGA has not been used yet in a real design assignment. To understand how the method can support architectural decisions in a real design process, we applied an adapted version of SAGA in the transformation of a Brussels row house. In this paper, we describe the method’s relevance in validating the architect’s intuition by comparing the results of the method on the initial and future states of the house. Secondly, we evaluate the method’s added-value to guide the optimization of the plan layout, by comparing the future state with three alternative plan layouts. In this case, the architect considers the quantitative assessment as useful to evaluate and improve his architectural design, but the results are hardly interpretable without prior expertise. In conclusion, the method has potential in validating design choices fostering general and adaptable plan layouts. Depending on the expertise of the assessor, it can also support the optimization of the plan. In the future, implementing automatic checks or suggestions could bypass this reliance on expertise.

C. Vandervaeren (B) · F. Denis · W. Galle · N. De Temmerman Architectural Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussel, Belgium e-mail: [email protected] F. Denis Building, Architecture and Town Planning, Université Libre de Bruxelles (ULB), Avenue Franklin Roosevelt 50, 1050 Brussel, Belgium W. Galle Transition Platform, Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_13

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Keywords Generality · Adaptability · Design for disassembly · Building obsolescence · Assessment tool · SAGA

13.1 Introduction In view of the current ambitions toward a more sustainable building stock, the obsolescence and inefficient use of buildings is a major issue which rises when buildings are unable to accommodate different and evolving needs. Already in 1999, Stephen Kendall stated: ‘One of the most urgent issues in contemporary urban architecture concerns constructing buildings with the inbuilt capacity to adapt over time to changing uses and preferences, with minimal conflict’ [2]. This inbuilt adaptable capacity of buildings can be translated as generality and adaptability, two different approaches for extending the service life of buildings and for improving the way they meet user needs. As defined by Galle and Herthogs [3], a general (or multi-functional) building can accommodate different and evolving needs and requirements without requiring physical alterations. Generality emerges from characteristics such as room size, room shape, daylighting, and spatial layout. Distinct from a general building, an adaptable building can be efficiently altered to support changing needs and requirements [3]. In an adaptable building, some elements are purposefully designed to be disassembled, adapted, or relocated. In a review of the concept of adaptability by Heidrich et al. [4], generality corresponds to ‘how the users adapt to a building,’ while adaptability relates to ‘how the fabric of the building changes.’ Despite the rising interest in these two approaches, few methods exist to quantify the generality and adaptability of buildings [5]. A possible method to quantify the generality and adaptability of spatial layouts is the Spatial Assessment of Generality and Adaptability (SAGA) method, developed by Herthogs [1] and adapted by Herthogs et al. [6]. SAGA is built on the assumption that a building’s characteristic influencing its generality and adaptability is the spatial connectivity of its plan layout [1]. SAGA uses plan graphs and mathematically derived indicators to quantify how well the spaces are presently connected and how they can become connected in the future (Sect. 13.2). SAGA’s ability to compare different plan layouts has been illustrated by several case studies [1, 6–9], but has never been applied to a real-life design project. When the design is not fixed yet, the SAGA results can still have an impact on the building plan layout. Evaluating this impact can be beneficial for the development of the method and its translation into a design-support tool. The present research explores SAGA’s ability and relevance in guiding an architect in a real-life project designed for spatial generality and adaptability. Based on SAGA’s illustrated potential to compare plan layouts and to optimize a single plan layout [1], we defined two research questions. The first research question relates to validation of the designer’s intuition: how can SAGA (in)validate an architect’s intuition in designing for general and adaptable space layouts? In other words, we check whether the architect’s efforts are accordingly reflected by SAGA graphs and indicators. The

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second research question goes beyond validation and relates to design optimization: how can SAGA guide an architect in optimizing a space layout toward more generality and adaptability? Here, we assess how SAGA can be used by an architect and by assessors (here: the authors) to detect hotspots for design improvements. For both questions, we first identify the necessary information and skills required for drawing conclusions with the SAGA indicators, then we evaluate the (perceived) relevance of these conclusions. This research is conducted in the context of a row house renovation and transformation, the ‘Dethy’ house, by the architect Lionel Bousquet. In this paper, we firstly introduce the SAGA method and its adaptation as a Building Information Modelling (BIM) software tool, called SAGABIM (Sect. 13.2). Secondly, we describe the Dethy house case study and the evaluated plan variants (Sect. 13.3), and we report the results of the SAGABIM, i.e., the generated graphs and calculated connectivity indicators (Sect. 13.4). Then, we describe the information exchanged between the architect and the assessors (Sect. 13.5). Finally, we draw conclusions on the generality and adaptability of the Dethy house, on the insight provided by the flow of information exchanged during the assessment process and finally on SAGABIM’s added-value during the design of general and adaptable buildings and possible improvements of the tool (Sect. 13.6).

13.2 SAGA Method and SAGABIM In the first part of this section, we briefly presents how the SAGA method, as developed in 2016 [1], converts a plan layout in plan graphs and calculates five spatial configuration indicators. For the complete calculation details, we refer to Herthogs’ doctoral thesis from 2016 [1]. The second part of this section lists the differences between the SAGA method and the SAGABIM tool.

13.2.1 Spatial Assessment of Generality and Adaptability (SAGA) Herthogs [1] developed the Spatial Assessment of Generality and Adaptability (SAGA) method to quantify a building’s spatial connectivity, by using weighted graphs. In SAGA, a plan layout is converted in three graphs (with nodes and edges). From each graph, three indicators are derived (expressed in percentages), based on the shortest distance between nodes. The first indicator, Generality (G), is derived from the graph wherein the nodes represent convex rooms and the edges represent the existing connections between rooms (i.e., doors, openings, sliding walls…) with a weight of 1 (Fig. 13.1). The second indicator, Adaptability (A), is derived from the same graph, but wherein potential connections are added with weights superior to 1 depending on the difficulty in creating an opening between the two spaces (Fig. 13.1,

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Fig. 13.1 The connectivity of a plan layout (left) represented as a plan graph wherein nodes are rooms and black edges are existing connections between rooms (right). The green dotted edge represents a potential future connection. Image taken from [8]

green dotted edge). The third indicator, Maximum Adaptability (MA), is based on the graph where all potential connections are considered realized (i.e., all dotes edges become continuous). Next to these three indicators, two other relative indicators, Normalized Generality (Gn ) and Adaptability (An ), evaluate how much generality and adaptability have been achieved in the plan layout relative to the maximum achievable score. They are calculated as follows: Gn = An =

G−

1 3

MA −

1 3

A−G MA − G

(1) (2)

13.2.2 SAGA Implemented in an Autodesk Revit Environment: SAGABIM In this research, we have adapted and implemented the SAGA method in visual programming software Dynamo to be used in a Building Information Modelling (BIM) Revit environment: SAGABIM. When Dynamo is used in combination with a Revit model, we can extract information from a BIM model, process it and send it back to the model or, in this case, visualize it in Dynamo. There are some differences between SAGA method and SAGABIM software: • SAGABIM uses the building metadata to automatically detect the shape of the rooms, and the presence of doors and staircases. This feature reduces the risk for errors due to the redrawing of the rooms and connections, a necessary step in the original implementation SAGA in Rhinoceros and Grasshopper software. • Originally, SAGA requires to divide non-convex rooms into several convex areas following a set of rules defined in [1]. SAGABIM offers the possibility to follow these rules or to use functional spaces.

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• Originally, SAGA requires to analyze multistory buildings floor by floor in different graphs. SAGABIM offers the possibility to also analyze all floors at once (in a single graph). • To ease the analysis of the plan graphs, SAGABIM generates justified graphs: the nodes are arranged vertically according to their depth and the size of the node corresponds to the number of associated edges (Fig. 13.2, above). Importantly, the SAGABIM tool used in this case study is based on the 2016 version of SAGA as defined in [1], which was updated in 2019 [6] and from then uses a different normalization method. Henceforth, the conclusions drawn from nonnormalized scores remain independent from the chosen SAGA version and we expect the normalized scores to only be slightly affected by the method update.

13.3 Dethy Project: Initial and Future States In the present study, the SAGABIM tool is applied to the Dethy house. Started in 2015, the Dethy project consists of the renovation and transformation of a row house located in Saint-Gilles, Brussels, Belgium, by the architect Lionel Bousquet for his personal use. This study takes place before the start of the works. Above the commercial ground floor, the house has currently two residential floors (Fig. 13.2). On the street level, two doors give access to the house: one door to the commercial space and one door to the residential spaces. Initially, the commercial space is not partitioned in different rooms, but we considered that the space could be used in different (convex) areas. Modelling this space as one or four space(s) will lead to different graphs and indicators. In this case, we modelled and analyzed both options: the space as one large room (initial state I) and as four connected rooms (alternative initial state I’). In the calculation of the Adaptability score, all existing wall partitions have a probability of new connections estimated to 0.3 (resulting in a weight of 3.33). A staircase situated next to the party wall gives vertical access to all floors. In the planned future state of the house, the ground floor will host the architect’s own office and the upper floors will host his family. Aware of the evolving needs of his office and household, the architect paid attention to the generality and adaptability of the plan layout. The transformation of the house (modelled as option F) includes the addition and replacement of partitioning walls, the removal of the existing roof and the addition of an extra floor, while the main characteristics of the plan layout are maintained. To assess how the plan layout could become more general and adaptable (second research question), we modeled two additional plan layouts improving generality (F_IG), by adding new doors, and improving adaptability (F_IA), by using adaptable partitions where possible in the building. A last considered option is the plan layout with an additional staircase (F_AS) between the first and second floor. This staircase is needed for an independent duplex on the two upper floors. All options modelled for the initial and future states are summarized in Table 13.1 (Sect. 13.4).

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We made a set of modelling assumptions and deviations from the original SAGA method. The probability of new connections in the partitions differs according to the partition type: it ranges from 0.3 for fixed partitions where creating an opening would be difficult, to 0.6 for fixed partitions with a feasible opening and 0.9 for demountable walls (respectively resulting in edges’ weights 3.33, 1.66, and 1.11), as shown by the different colors in Fig. 13.3. Unlike recommended in the original SAGA method [1], all floors, including the basement, are combined in the same plan graph and we use functional spaces, regardless of their concavity.

13.4 Generated Indicators and Graphs with SAGABIM The justified plan graph of the initial state (I) shows that the building plan layout is already well-connected, thanks to the many doors and the staircase. The importance of the connection hubs is visible on the graph as large dots (Fig. 13.2). We can divide the graph in two independent graphs: one with nodes 1, 3, 4 and 5, the other with all other nodes, likewise the commercial and private spaces can be easily separated. All calculated SAGA indicators for each design option are presented in Table 13.1. In the initial state (I), Generality (G) and Adaptability (A) indicators are equal because the addition of potential connections does not affect the shortest path between the spaces. Because G equals A, the Normalized Adaptability (An , see Eq. 13.2) indicator is zero. Modelling the ground floor room as one large room or four small rooms has an impact on the I and I’ options values: all I’ indicators are higher than I indicators. Intuitively, two of the architect’s design choices might reduce the connectivity of the plan layout, hence its generality: the additional floor (the number of rooms and the depth of the graph increase) and the separation of the professional and private area (e.g., deletion of a door between the hall on the ground floor and the middle space). Nevertheless, G is slightly higher in the future state F (78.77) than the initial ones I (76.47) and I’ (77.49), thanks to the conservation of the circulation hubs and to the use of demountable and folding walls. On the ground floor plan layout, the architect decided to make the front room (Fig. 13.3, room 5) only accessible form the street, which completely isolates it from the rest of the building. This isolation is clearly visible on the Generality graph (Fig. 13.3, above left). In the future, using this room as part of the private residential area seems impossible. Fortunately, the wall separating this room from the rest is a demountable partition. To alleviate the isolation of Room 5, the future state (F) is compared to the improved generality (F_IG) option wherein the partition between the street-side room and the middle room becomes a folding partition and a new door connects the middle room and the staircase (Fig. 13.3, wall indicated in blue). Comparing indicators in F and F_IG options, G only slightly increases from 78.77 to 80.02 (+1.59%), while Gn increases from 95.89 to 98,50 (+2.72%). Because of the limited use of adaptable partitions in the F_IG plan, G and A indicators are almost identical. Notably, An drops from 50.29 to 11.11 (−77.91%), mainly because when a plan becomes more general, there are less options for adaptable elements.

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Fig. 13.2 SAGA analysis of the initial state (I); (below) plan graph, (above) justified graph. Potentially, new connections are indicated in green. The most connected rooms are visible in the above graph as large dots (staircase in rooms 2, 7, 13) Table 13.1 Calculated SAGA indicators of generality (G), Adaptability (A), Maximum adaptability (MA), Normalized generality (Gn ), and Adaptability (An ), in percentage (%) for six plans Option

Description

G

A

MA

Gn

An

I

Initial state—Ground floor as one room

76,47

76,47

76,80

99,24

0

I’

Initial state—Ground floor as four rooms

77,79

77,79

77,99

99,55

0

F

Future state

78,77

79,75

80,72

95,89

50,29

F_IG

F with improved generality

80,02

80,10

80,72

98,50

11,11

F_IA

F with improved adaptability

78,77

80,05

80,72

95,89

65,64

F_AS

F with additional staircase (2nd to 3rd floors)

78,85

79,86

80,85

95,80

50,57

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Fig. 13.3 SAGA analysis of the future state (F); (below) plan graph, (above) justified graphs of Generality and Adaptability. Potential and desired connections are indicated in green. The most connected rooms are visible as large dots (staircase in rooms 4, 11, 15, 20)

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In an attempt to improve the adaptability of the plan, we replace all fixed partitions with possible opening by demountable ones (F_IA option). Comparing indicators in F and F_IA options, An increases, as expected, from 50.29 to 65.64 (+30.52%). In the last design option (F_AS), a staircase is added between the second and third floors to create a separate housing unit. Nevertheless, the increase in Generality and Adaptability indicators is low (+0.10 and + 0.14%). The new connection between the two highest floors barely affects the shortest path from the street entrance to these rooms which are already connected by the main staircase. We can nevertheless question whether it is practically acceptable to use a staircase shared by different families as a vertical circulation within one duplex. The SAGA method only evaluates connectivity regardless of qualitative aspects of the rooms and their connections.

13.5 Information Exchange During the Assessment The connectivity assessment of the Dethy project has been initiated by the architect during the design phase of the project. In a preliminary design of the house (in 2015– 2018), the architect aimed to maximize the generality and adaptability of the house. He evaluated his design qualitatively by imagining alternative uses for the professional space on the ground floor and of the residential upper floors. As expressed during a preparatory interview with the authors (November 2018), he wanted, firstly, a quantitative evaluation of the improvements made to a plan layout before and after transformation and, secondly, some support for improving the generality and adaptability of the plan, including guidance in the implementation of an additional stairway connecting the two upper floors. The information required to use SAGABIM and compare different plan layouts is: the shape of the rooms, their size and use, the existing connections between the rooms (i.e., wall openings, doors, and staircases), and the different partition types sorted according to the difficulty of introducing a new opening. Without fixed rules to define the probability of new openings in partitions, the architect and assessors jointly estimated these values based on previous SAGA case studies. To calculate the Adaptability (A) indicator, the assessors must add new doors to the initial plan layout, following the rules defined in [1]. No more information nor expertise is required to validate whether Generality and Adaptability indicators have increased. Nevertheless, to check the coherence of the results, a good understanding of the SAGA calculation rules and experience with analyzing plan graphs is needed. Finding optimization measures is more complicated than simple checks. To identify the cause of a variation in the SAGA indicators and to imagine further improvements of a plan, the assessors’ experience with SAGA and design for generality and adaptability is crucial. In this case study, we propose two other plan layouts (F_IG and F_IA), and the architect suggests an extra one with an additional stairway (F_AS). Interestingly, the extra stairway plan layout is not translated in a significant increase in indicator values (Table 13.1), probably because we chose to assess the connectivity of the whole building at once (rather than floor-by-floor) and because

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SAGA does not account for the practicality of a connection. For the architect, the SAGABIM results combined with the technical complexity added by this feature, restrain its implementation in the final plan layout. Because the assessors detected a potential weakness in the ‘isolation’ of Room 5 (Fig. 13.3), the architect decided to reconnect this room to the rest of the building. The suggested new connection between Rooms 3 and 4 cannot be directly implemented due to fire regulations.

13.6 Conclusions This study illustrates on a real design assignment (transformation of a Belgian row house ‘Dethy’) how the generality and adaptability of a plan layout can be evaluated with the SAGABIM tool, an adapted BIM implementation of the SAGA method. With a limited information input from the architect, the assessors could validate the architect’s intuition (Generality and Adaptability scores are higher after rather than before transformations) and formulate several design recommendations. For instance, the assessors advised the architect to reconsider the absence of door between the middle room and the street room. Further, the additional staircase in the upper floors does not result in a major increase in generality and the architect should reconsider its added-value. The architect found the assessment process enriching and the results sometimes surprising. In conclusion, SAGABIM’s potential in guiding architects toward designing more general and adaptable buildings now mainly lies in validating the intuition of the designer. Formulating design improvements can hardly be derived from SAGABIM results without former expertise. Future research could compare more rigorously the architect’s expectations with SAGABIM’s quantified results and could evaluate to what extent the graphs and indicators generated by this tool allow the architect to formulate design improvements without support from experienced assessors. To bypass this reliance on expertise, the tool could include automatic checks and suggest modifications to the user. Additionally, a body of reference cases per building or plan type is needed to interpret the score variation between plan layouts. With these improvements, SAGABIM could be used by a wider community of architects and contribute to a lower amount of obsolete assets in cities destined for vacancy or demolition. Acknowledgements Camille Vandervaeren is an FWO-SB PhD fellow at Fonds Wetenschappelijk Onderzoek. François Denis was funded by an IWT grant during the development of SAGABIM. The authors thank the architect Lionel Bousquet, Pieter Herthogs, and the two anonymous reviewers for their valuable comments and suggestions.

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References 1. Herthogs, P.: Enhancing the adaptable capacity of urban fragments: a methodology to integrate design for change in sustainable urban projects. Doctoral thesis, Vrije Universiteit Brussel, Brussels (2016) 2. Kendall, S.: Open building: an approach to sustainable architecture. J. Urban Technol. 6, 1–16 (1999) 3. Galle, W., Herthogs, P.: Veranderingsgericht bouwen: ontwikkeling van een evaluatie- en transitiekader: Een gemeenschappelijke taal. OVAM, p. 23 (2015) 4. Heidrich, O., Kamara, J., Maltese, S., Re Cecconi, F., Dejaco, M.C.: A critical review of the developments in building adaptability. Int. J. Build. Pathol. Adapt. 35, 284–303 (2017) 5. Rockow, Z.R., Ross, B., Black, A.K.: Review of methods for evaluating adaptability of buildings. Int. J. Build. Pathol. Adapt. 37, 273–287 (2019) 6. Herthogs, P., Debacker, W., Tunçer, B., De Weerdt, Y., De Temmerman, N.: Quantifying the generality and adaptability of building layouts using weighted graphs: the SAGA method. Buildings 9, 92 (2019) 7. Wahid, H.: Exploring adaptability and generality in antwerp’s residential types. Masters thesis, Vrije Universiteit Brussel: Brussels (2017) 8. Herthogs, P., Paduart, A., Denis, F., Tunçer, B.: Evaluating the generality and adaptability of floor plans using the SAGA method: a didactic example based on the historical shophouse and gentry house types. In: Proceedings of the UIA 2017 Seoul World Architects Congress, p. 7. Seoul, South Korea (2017) 9. Prizeman, O.E.C., Pezzica, C., Parisi, M., Lorenz, C.-L.: Function should follow form: futures for the radiant logic of Carnegie public libraries (2018)

Chapter 14

Rapid Identification and Evaluation of Interventions for Improved Water Performance at South Africa Schools Jeremy Gibberd

Abstract Many areas of South Africa experience water shortages and unreliable water supplies. Water and sanitation costs at South African municipalities have been steadily rising in the last 5 years and are particularly high in water-stressed areas such as Cape Town. At the same time, public funding for schools is reducing. Schools, therefore, need to understand their water consumption and be able to rapidly identify and evaluate options to reduce water usage, thereby decreasing costs and improving environmental performance. In order to identify the smartest options for reducing water consumption, a rapid identification and evaluation methodology is proposed. Characteristics of existing infrastructure and usage are modelled in a School Water Use Model (SWUM). Results from this modelling are used to identify potential interventions for improved performance. These are evaluated and compared using the SWUM and ranked in terms of impact and applicability. The SWUM-based methodology is tested by applying this to school in Pretoria, South Africa. The application and results of the SWUM-based methodology show promise as a rapid way of identifying, and evaluating, interventions to improve the sustainability performance of water systems in schools in South Africa. Recommendations for further development of the approach are made. Keywords Sustainable School Sanitation · Sustainable School Water Systems

14.1 Introduction South Africa is classified as a water-scarce country [1]. In many areas, there are water shortages and water supplies are unreliable [2]. Water shortages can cause significant problems for schools and may lead to their temporary closure because of health concerns. This can have devastating knock-on effects as learning time is lost and exam results drop [3].

J. Gibberd (B) Council for Scientific and Industrial Research, Pretoria, South Africa e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_14

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Schools that rely on flush toilets also have to pay significant costs for water. Water shortages in many areas of South Africa have resulted in these costs increasing rapidly as municipal tariffs rise. At the same time, public funding for schools has been reducing making it increasingly difficult for schools to absorb additional costs. It is, therefore, increasingly important to understand water systems and waterborne sanitation at schools and identify ways that water consumption can be reduced. Reducing water consumption at schools helps to reduce school operational costs, it preserves limited water resources, and helps ensure that children (and their parents) become more aware of the water scarcity and how water consumption can be reduced. This paper presents work carried out to investigate water consumption in schools. It provides background to the need to address water in schools in South Africa and provides a methodology for the study. Results from the study are presented and discussed to develop conclusions and recommendations. It aims to address the following questions (a) How is water used in the case study school?, (b) Can this water use be modelled to identify options for improvement?, (c) Which options appear to be the smartest and most sustainable solutions? and, (d) What recommendations can be made?

14.2 Water in South Africa Many countries in Africa face very high levels of water scarcity [1]. Studies indicate that 98% of available water supplies in South Africa are already exploited [2]. Major South Africa cities, such as Cape Town and Johannesburg, are vulnerable to water shortages [3]. For instance, in December 2017, water shortages in Cape Town were of an extent that, without rain, water for the city was predicted to run out in May 2018 [4]. Climate change will result in the severity and frequency of droughts in many areas increasing, making water supplies unpredictable [5]. Conservation of water resources and water efficiency has, therefore, become a key issue [6, 7]. Schools can make a significant contribution to reducing water consumption by being more efficient on their premises and by influencing learners and parents [8, 9].

14.3 Methodology A mixed-method research methodology was applied to the study and included the following methods. Analysis of quantitative data was used to understand current water consumption data at the school and develop this as input for a modelling tool. Qualitative data was gathered in interviews and interpreted to understand how the school operated and used water. A process of synthesis and conjecture was

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used to develop a model of water consumption at the school and identify potential interventions that could be used to reduce water consumption. Finally, quantitative analysis was applied to understand, compare results, and draw conclusions and recommendations. The study applies the School Water Use Model (SWUM) to school to identify and evaluate options for reducing water consumption. The SWUM was developed by the author as a way of identifying and testing options to reduce school water consumption. The SWUM and the methodology of applying this have been deliberately designed to be simple and non-technical. This is to ensure that ‘non-professional’ users, such as school principals, teachers, staff, and pupils can use the methodology to identify valuable opportunities to reduce water consumption and school operating costs. This makes the approach different from conventional water audits and water consumption monitoring using water loggers. A diagram of the tool is provided in Fig. 14.1. Data on all equipment and fittings that use water, such as flow rates and water consumption volumes, is entered under equipment inputs. Operational data such as learner, educator and staff numbers, school building areas and the school day and school year schedule is then entered under school inputs. This data generates water performance information for the school in the form of a table and graph. Data is finally summarized in key water performance indicators which are compared to targets and benchmarks under normalized performance and benchmarks. The SWUM is applied within a structured methodology which consists of the following steps. Firstly, a case study school was identified and analyzed. The school selected is located in Pretoria, South Africa (25° S, 28° E), as it has waterborne sanitation, grounds with irrigation, is in an urban area, has about 1000 learners and is fairly typical of a large school in a middle-class South African neighbourhood. Secondly, data on the school, including learner and staff populations was obtained from the school. School plans and Google maps were used to acquire school and site areas and other data on school infrastructure. A walkthrough of school facilities was used to obtain data on equipment and fittings that used water. Data gathered in this way is shown in Tables 14.1 and 14.2. A review of literature and green building rating tools was used for the norms and assumptions indicated in Table 14.3. Thirdly, an analysis of municipal utility bills for 12 consecutive months during 2017 and 2018 was used to ascertain water consumption and sewage figures for the school. Data gathered in this way is shown in Table 14.2 and was used to cross-check figures generated by the SWUM. Fourthly, a range of options was identified that could be used to reduce water consumption. These were entered into the SWUM to ascertain their potential impacts. These options were: A. Eliminating irrigated recreational lawns and replacing grass with a surface that did not require irrigation. B. Eliminating all lawns, including sports field laws that required irrigation and replacing with surfaces that do not need irrigation. C. Replacing all WCs with dual flush WCs with a flush rate of 3 l (half flush) and 6 l (full flush).

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SCHOOL WATER USE MODEL (SWUM 1.01) SWUM HEADLINE INDICATORS Modelled litres per person per day Modelled litres per m2 per day

11.15 Target litres per person per day 1.95 Target litres per m2 per day

80.00 Over/under Over/under

Water use in the building Monthly use Annual use (kL) (kL) 252.52 3 030.21 9.35 112.23 18.71 224.46 0.00 0.00 9.35 112.23 0.00 0.00 64.00 768.00 0.00 0.00 0.00 0.00 0.00 0.00 353.93 4 247.13

Water Use Toilets Urinals Wash hand basins Showers Kitchen use Laundry Irrigation Env control Fire testing Cleaning Total

Building details Name of building Gross Internal Area (m2)

Use Use L/m2/day L/person/day Percentage 1.39 7.95 71.35 0.05 0.29 2.64 0.10 0.59 5.28 0.00 0.00 0.00 0.05 0.29 2.64 0.00 0.00 0.00 0.35 2.02 18.08 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.95 11.15 100.00

Occupants Number of full time occupants Full time equivalent occupants

1044 1044.00

Assessment Assessment by

Normalized performance and benchmarks

Water use (L/person/day) 9.00 8.00 7.00 6.00 5.00 4.00 3.00 2.00 1.00 0.00

#REF! Address Site area (m2)

5970

-68.85 L 1.95 L

Date

#REF! Number of weeks occupied Occupancy (hours per week)

43 32.5

Number of part-time occupants Occupancy (0.1 to 0.9)

1070 0

Validation by

Date

Toilets

Female Male

Female Male

Number of users

Full flush rates (L/flush)

Half flush rates (L/flush)

Uses per day

Days per week

Weeks per year

0.00 0.00

6.00 6.00

3.00 3.00

2.00 1.00

5.00 5.00

43.00 43.00

0.00 0.00

0 0

522.00 522.00

Full flush rates only (L/flush) 9.00 9.00

2.00 1.00

5.00 5.00

43.00 43.00

168.35 84.17 252.52

2020.14 1010.07 3030.21

Days per week 5.00

Weeks per year 43.00

Use per month (KL)

Use per year (KL)

Use L/m2/day

0.93 0.46 1.39

Use L/person/day

5.30 2.65 7.95

Urinals Use per Use per year month (KL) (KL) 9.35 112.23

Use Use L/m2/day L/person/day 0.05 0.29

Use per Use per year month (KL) (KL) 18.71 224.46

Use Use L/m2/day L/person/day 0.10 0.59

Weeks per year 43.00

Use per Use per year month (KL) (KL) 0.00 0.00

Use Use L/m2/day L/person/day 0.00 0.00

Weeks per year 43.00 43.00

Use per Use per year month (KL) (KL) 9.35 112.23 0.00 0.00 9.35 112.23

Use Use L/m2/day L/person/day 0.05 0.29 0.00 0.00 0.05 0.29

Weeks per year 43.00

Use per Use per year month (KL) (KL) 0.00 0.00

Use Use L/m2/day L/person/day 0.00 0.00

Times per week 3.00 3.00

Weeks per year 20.00 43.00

Use per Use per year month (KL) (KL) 56.00 672 8.00 96 64.00 768.00

Use Use L/m2/day L/person/day 0.31 1.76 0.04 0.25 0.35 2.02

Flow of water to equipment Duration of (L/min) flows (Min) 0.00 0.00

Times per week 0.00

Weeks per year 43.00

Use per Use per year month (KL) (KL) 0.00 0.00

Use Use L/m2/day L/person/day 0.00 0.00

Flow of water to equipment Duration of (L/min) flows (Min) 0.00 0.00

Times per year 0.00

Use per Use per year month (KL) (KL) 0.00 0.00

Use Use L/m2/day L/person/day 0.00 0.00

Flow of water (L/min) 0.00 0.00

Times per week 0.00 0.00

Use per Use per year month (KL) (KL) 0.00 0.00 0.00 0.00 0.00 0.00

Use Use L/m2/day L/person/day 0.00 0.00 0.00 0.00 0.00 0.00

Male

Number of users 522.00

Flush rates (L/flush) Uses per day 1.00 1.00

Number of users 1 044.00

Flow rates (L/minute) 5.00

Duration (minutes) 0.10

Uses per day 2.00

Days per week 5.00

Number of users 0.00

Flow rates (L/min) 14.00

Duration (minutes) 4.00

Times per week 7.00

Number of users 1 044.00

Water used per activity (L) 0.50 10.00

Times per day 1.00 3.00

Days per week 5.00 5.00

Number of users 0.00

Water use per wash (L) 70.00

Times per week 1.00

Area 50.00 20.00

Duration of flows (Min) 60.00 60.00

Performance in a table and graph School inputs including school day and year schedules, building areas and learner and staff numbers

Wash hand basins Weeks per year 43.00

Showers

Users Kitchen use

Drinking Washing Laundry

Washing Irrigation

Sports Decorative Env control

Equipment Fire testing

Equipment Cleaning

Equipment 1 Equipment 2

Duration (Min) 0.00 0.00

Weeks per year 0.00 0.00

Fig. 14.1 School water use model (by Author)

Equipment inputs including quantities, flow rates and flush volumes and operating schedules

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Table 14.1 Infrastructure data Aspect

Data

Site area

3.33 ha

Building area

5970m2

Irrigated sports grounds

7000m2

Irrigated recreational lawn

2000m2

Wash-hand basin flow rates

10 l/min

Urinal flush rates WC flush rates

1 l/flush 9 l/flush

Table 14.2 Operational data Aspect

Data

Learner numbers Staff numbers School operational schedule School year Water tariff Sanitation tariff Combined tariff

980 64 07:30–14:00 weekdays (32.5 h per week, 100% school population), sports (14:00–16:00, weekdays (10 h per week, 10% school population) 43 weeks R24.37/kl R3.84kl R28/kl [10]

Table 14.3 Assumptions and norms Aspect

Data

Sex WC usage Wash-hand basins Drinking water

There are equal numbers of male and female learners and staff Female learners will use the WC three times a day, males will use WC once a day, and use urinals twice a day Users wash their hands every time they visit the toilet and will open the tap for 6 s An average of 500 ml of water per day will be consumed by all occupants

D. Installing a rainwater harvesting system and using water from this to flush toilets. E. Installing composting toilets and waterless urinals.

14.3.1 Input Data Used in the School Water Use Model. Infrastructure and operational data entered into the SWUM are shown in Tables 14.1 and 14.2. Table 14.3 shows the assumptions and norms used in the model.

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14.4 Results The analysis of municipal utility bills indicated that water consumption at the school for a full calendar year was 4167kl. This is an average of 347kl per month. Sewage flows on utility bills are indicated as the same as water flows. Entering the data listed in Tables 14.1, 14.2 and 14.3 into the School Water Use Model provided the following figures. Annual water consumption was 4247kl. This was within 2% of the actual water consumption figures. A report from the SWUM in Fig. 14.2 indicates that this equals 11.15 L per person per day and 1.95 L per m2/day. It shows that most water (71%) is used by toilets, followed by irrigation (18%), and wash-hand basins (5%).

14.4.1 Interventions Water consumption impacts of proposed interventions as modelled in the SWUM are described below.

14.4.2 A. Eliminating Irrigated Recreational Lawns Eliminating irrigated recreational lawns at the school can be achieved by replacing this with ground cover that does not irrigation. This intervention reduces overall water consumption from 4247 to 4151kl per year, a 2.36% reduction in water consumption.

Water Use Toilets Urinals Wash hand basins Showers Kitchen use Laundry Irrigation Env control Fire testing Cleaning Total

Monthly use Annual use (kL) (kL) 252.52 3 030.21 9.35 112.23 18.71 224.46 0.00 0.00 9.35 112.23 0.00 0.00 64.00 768.00 0.00 0.00 0.00 0.00 0.00 0.00 353.93 4 247.13

Use Use L/m2/day L/person/day Percentage 1.39 7.95 71.35 0.05 0.29 2.64 0.10 0.59 5.28 0.00 0.00 0.00 0.05 0.29 2.64 0.00 0.00 0.00 0.35 2.02 18.08 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.95 11.15 100.00

Fig. 14.2 Consumption analysis report from the school water use model (SWUM)

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14.4.3 B. Eliminating All Irrigated Lawns Eliminating all irrigated lawns, including sports fields, at the school can be achieved by replacing these surfaces with an alternative that does not require irrigation. Possible alternatives are planted xeriscape ground covers or an ‘AstroTurf’ type surface that does not require irrigation. This intervention results in water consumption dropping from 4247 to 3479kl per year, an 18% reduction.

14.4.4 C. Replacing All WCs with Dual Flush WC Replacing conventional toilets with dual flush toilets reduces water consumption from 4247 to 2378 kl per year. This reduces water consumption in the school by 44%.

14.4.5 D. Installing Dual Flush WC and a Rainwater Harvesting System Annual average rainfall at the school location is about 600 mm. This amount of rain (0.6 m) combined with the roof area (approx. 5000 m2) indicates that sufficient rainwater (approx. 3000kl) could be harvested to meet the water volume requirements (1161kl) to flush the toilets throughout the year. Monthly water volumes required to flush toilets (dual flush toilets) are 96kl/month. Given that the longest period without rain is 3–4 months, the volume of water harvested and stored would have to be 4 × 96kl, which is approximately 384kl. This intervention would reduce mains water consumption by 3031kl from 4247 to 1216 kl, a 71% reduction in consumption.

14.4.6 E. Installing Composting Toilets and Waterless Urinals Installing composting toilets privies and waterless urinals could be used to reduce water consumption associated with toilets. This intervention would reduce main water consumption by 3031kl from 4247 kl to 1216 kl, a 71% reduction in consumption.

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14.5 Discussion A review of the interventions indicates that Intervention A (eliminating recreational lawns) has a relatively small impact and only reduces water consumption by about 2%. Eliminating all irrigation (Intervention B) has a greater impact and leads to savings in water consumption of about 18%. Converting inefficient WCs to more efficient dual flush WCs (Intervention C) has a significant impact and reduces water consumption by 44%. Intervention D, which includes using harvesting rainwater to flush toilets results in a saving of water of 71%. Intervention E, replacing existing water-based sanitation with a composting toilet system also achieves water savings of about 71%. The SWUM provides water consumption data in a form that can be used to compare performance with other schools and to set targets for the management of the school [10]. For instance, water consumption at this school (4kl/person/year) can be compared to schools in Taiwan where consumption 12.83kl/person [11]. An annual measure, however, does not reflect differences that may occur in the length of the school year and, therefore, comparing consumption in terms of litres/person/day may be more accurate. Comparing the school’s performance (11 l/person/day) with Italian schools performance (18–56 l/person/day) indicates consumption is far lower in the case study school [10]. While the methodology is rapid and cost-effective, it may not be highly accurate as it based on school facilities audits, field observations and assumptions and not on actual water consumption data within the different areas of the school. Highly accurate data of this nature could be achieved by logging water consumption in the different areas and recording this for a year. This, however, would be expensive as it would require metering and would take some time to undertake. The methodology also does not take into account behaviour-based approaches which aim to reduce water consumption through actions which aim to conserve water, such as turning wash-hand basin taps on for shorter periods. This approach has been successfully integrated into school curricula [9]. It could, however, be argued that the primary purpose of the SWUM-based methodology is not to be highly accurate but to provide a simple and rapid way of identifying and evaluating possible ways of reducing water consumption in schools [12]. By basing the model on readily available data, the approach can be used by non-professionals, including school principals, school staff, and school governing bodies (SGBs) who can use it to rapidly identify possible ways of improving their water consumption. In this way, it provides valuable early guidance to schools on ways water consumption may be reduced so that they can engage and instruct external parties such as water engineers, landscaping firms, and plumbing contractors appropriately. A recommendation, therefore, would be the further development and testing of the SWUM at more schools to refine the approach. This should include a representative sample of the type of schools that exist in South Africa including rural schools.

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14.6 Conclusion The application of the School Water Use Model methodology to the case study school is used to identify and evaluate interventions to reduce water consumption. The methodology proves effective at enabling possible interventions to be identified and tested to identify the most promising options. A critical review indicates that the approach is suitable as an early stage, feasibility and decision-support tool rather than a precise modelling, diagnostic, or predictive tool. Application of the methodology as an early stage decision-support tool shows significant promise. By being simple to use and only requiring readily available data, the tool is highly suitable for ‘non-professional’ users, such as school principals and staff who can use this to identify valuable opportunities to reduce water consumption and school operating costs. It is recommended that the methodology is refined further and tested at a range of schools. This could be supported by converting the current Excel-based tool to an online tool which schools could pilot. Feedback from this process could be used to develop a final online tool which could be used by schools to reduce water consumption. Acknowledgements The author would like to thank Gauge for providing access to the tool, the school for data and the reviewers for their feedback on the paper.

References 1. United Nations Environment Programme: Africa water atlas Vol. 1. UNEP/Earthprint (2010) 2. Department of Environmental Affairs: World Cup Legacy Report (2011) 3. Jasper, C., Le, T.T., Bartram, J.: Water and sanitation in schools: a systematic review of the health and educational outcomes. Int. J. Environ. Res. Public Health 9(8), 2772–2787 (2012) 4. City of Cape Town: Day Zero. https://coct.co/water-dashboard/ last Accessed 22 Jan 2020 5. Makki, A.A., Stewart, R.A., Beal, C.D., Panuwatwanich, K.: Novel bottom-up urban water demand forecasting model: revealing the determinants, drivers and predictors of residential indoor end-use consumption. Resour. Conserv. Recycl. 95, 15–37 (2015) 6. Dolnicar, S., Hurlimann, A., Grün, B.: Water conservation behavior in Australia. J. Environ. Manage. 105, 44–52 (2012) 7. Willis, R.M., Stewart, R.A., Giurco, D.P., Talebpour, M.R., Mousavinejad, A.: End use water consumption in households: impact of socio-demographic factors and efficient devices. J. Cleaner Prod. 60, 107–115 (2013) 8. Cheng, C.L., Hong, Y.T.: Evaluating water utilization in primary schools. Build. Environ. 39(7), 837–845 (2004a) 9. Middlestadt, S., Grieser, M., Hernandez, O., Tubaishat, K., Sanchack, J., Southwell, B., Schwartz, R.: Turning minds on and faucets off: water conservation education in Jordanian schools. J. Environ. Educ. 32(2), 37–45 (2001) 10. Farina, M., Maglionico, M., Pollastri, M., Stojkov, I.: Water consumptions in public schools. Procedia Engineering 21, 929–938 (2011)

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11. Cheng, C.L., Hong, Y.T.: Evaluating water utilization in primary schools. Build. Environ. 39(7), 837–845 (2004b) 12. Borgstein, E.H., Lamberts, R., Hensen, J.L.: Evaluating energy performance in non-domestic buildings: a review. Energy Build.128, 734–55 (2016)

Chapter 15

Four Angles of Using Timber in Tall Buildings Seyed Masoud Sajjadian, Laura Tupenaite, and Chris Barlow

Abstract Increasing attention to utilise more sustainable materials in the construction industry has made timber-based building elements more desirable. The advantages of timber in prefabrication and sustainable development are widely known, and recent investigations are looking at using timber for high-rise buildings. Until this point, many tall buildings are already built by timber, and new proposals to use it in design and as a prefabricated component are being made from academics and industry every year. This paper looks at four angles of using timber in high-rise buildings on structural capacity, construction practice, environmental and acoustic performance. A case study is also used to quantify the operational performance of a high-rise building in London, UK, and through a BIM tool, a costing is also accomplished to compare the cost of a high-rise building in CLT with steel and concrete. The study reveals the potential, challenges and advantages of using timber from four perspectives that have rarely been investigated. Keywords Timber · Tall buildings · Structural capacity · Construction practices · Environmental performance · Acoustic performance

15.1 Introduction The negative impact of construction sector on environment is widely known and quantified. Figures show the industry is accounting for 40% of all energy used in the world [1], 3 billion tons of raw material [2] and one-third of global greenhouse gas emissions [3]. In Europe, 4.8 tonnes of minerals per person per year are extracted just for construction [4]. Therefore, dematerialisation and decarbonisation in the industry seem to be crucial for sustainability targets. S. M. Sajjadian (B) · C. Barlow Southampton Solent University, Southampton, UK e-mail: [email protected] L. Tupenaite Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, 10223 Vilnius, Lithuania © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_15

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Within the built environment, tall buildings are one of the biggest consumers of energy and raw materials. Construction of tall buildings requires a large amount of raw materials, and tall building of a certain usable area will likely use more materials compared to low-rise building. Use of more raw materials induces more energy in production and transportation, more consumption of natural resources, more waste, and more CO2 emissions [5]. Tall buildings are also a prominent element of the modern cities which create an identity and image for people attraction. There is no explicit and universally agreed definition for the term “tall building”. According to the Council on Tall Buildings and Urban Habitat (CTBUH), the definition is subjective, considered against one or more of the following categories: height relative to context, proportion, embracing technologies [6]. In Europe, since the twentieth century, most tall buildings are built with concrete and steel. However, recent technological development and aligning of building regulations with a greater understanding of performance at the beginning of twenty-first century have created a possibility to use more sustainable and environmentally friendly materials like timber for structural elements too (see Fig. 15.1). Energy and environment are important factors to consider in tall buildings, but other engineering aspects of using timber such as structural capacity and acoustic performance are also equally influential in design decision-making and users perception in buildings. This study aims to look at using timber in high-rise buildings from four different perspectives of structural capacity, construction practices, environmental and acoustic performance. A case study is also used in Sect. 15.4 to quantify operational energy performance and to provide an indication of costing differences compared to concrete and steel.

Fig. 15.1 Structural materials of tall buildings in Europe from 2000–2019 on the left and from 1900–2000 on the right. Source [6]

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15.2 Structural Capacity EN 1090 [7], EN 13,670 [8] and EN 1995 [9] are EU regulations for minimum requirements for the execution of steel, concrete and fabrication, assembly, transport, and erection of timber structures, respectively. The standards are intended to achieve sufficient strength, stability and durability. Durability of timber products is determined by the environment where any timber component may be used. If the product is not exposed to weather, then the risk is lower. EN 350:2016 [10] classified five categories for timber durability from not durable to very durable in terms of fungi, wood-boring beetles, termites and marine organisms, and British Standards provided recommendations outside the European standard for treatments of engineered wood products and wood-based panels. The recommendation suggests all engineered timber products are at high failure risk and are normally required to be treated. Deviation from straightness and inhomogeneity of materials are two important factors in the design of wood structures. For the former, because wood is a naturally grown material, it has structural inhomogeneity which creates additional uncertainty in the structural analysis compared to steel and concrete. There are few coverages of literature in structural analysis of timber compared to well-established concrete and steel in high-rise buildings. Most available materials focus on lightweight timber for low-rise buildings. However, the low weight-to-strength ratio for timber in general is widely analysed as advantage under collapse and its inherent brittleness as major disadvantage [11]. In 2011, Hansson [12] surveyed and analysed failures of 127 timber structures. He reported the most common errors on lack of strength design followed by poor construction practice in erection, on site alterations and lack of design with respect to environment. The structural analysis errors have been observed in 34% of studied cases. His study confirms lack of guidelines and low coverage and knowledge of robustness in timber construction. The results of this survey are referred to as Nordic study. Some observations have been made by Cabrero et al. [13]. According to the authors, the most common failure mode of timber structures—instability—is often due to absence or insufficient bracing. Authors also emphasise the importance of control of tensile stresses, moisture-induced shrinking and swelling-related problems, careful design of structural timber joints.

15.3 Construction Practices The advantage of using timber in renewability, malleability and adaptiveness is well known for decades [14]. The moderately lower weight of wood compared to steel and concrete (the typical softwoods in a modern multi-storey timber building have about 20% of the density of concrete [15]) can accelerate construction processes with relatively less in situ equipment requirement. This could also make assemblies easier

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in comparison with steel structures. The easier fabrication process could promote prefabrication and offsite manufacturing with lower cost, higher safety, easier planning, etc. Even though building in timber is very traditional but building tall buildings in timber is relatively new and one of the first modern samples is known to be built in Hackney, London in 2008 [16]. The most common use of timber products in buildings and their applications are shown in Table 15.1. Detailing is a vital part of any form of architecture, and timber is no exception, the quality of building is determined by good detailing. Fire protection, sound proofing and acoustic, heat transfer and thermal performance, protection from moisture and timber preservation are determined by a combination of technology and innovation in timber structures. The façade construction creates a key role in protecting timber and the structure from external sources of moisture. Figure 15.2 shows the typical detailing for CLT in high-rise buildings. Insulation thickness could vary but an overall thickness of about 350 mm for a U-Value of 0.152 W/m2 K is a typical sample. Table 15.1 Summary of most common timber products as elements in buildings Product

Application

Glulam

Structural elements, columns, beams, trusses, etc. (The only system used for a building above 10 storey height [17])

Cross-laminated timber (CLT)

Beams, columns, roofs, floor slabs, load-bearing walls, etc

Laminated veneer lumber (LVL)

Beams, columns, trusses, structural decking, etc

Laminated strand lumber (LSL)

Beams and columns

Structural insulating panel (SIP)

A composite structure which uses timber studs as a structural support

I-Joists

Cladding support, load-bearing studs, etc

Structural plywood

Beams and internal structures

Box beams

Beams, columns and roofs

From left to right: Plasterboard

Thickness: 10 mm

Insulation

Depends on the R-Value

Fire resistant layer

Normally 12.5 mm

CLT (load-bearing layer)

From 140 mm

Fire resistant gypsum plasterboard normally 2*18 mm

Fig. 15.2 Solid timber structure with thermal insulation

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15.4 Environmental Performance Considerate selection of construction materials can have significant influence on environment. Studies [18–20] compared the environmental performance in terms of greenhouse gas emissions of timber to concrete and reported significant advantage of timber. Skullestad et al. [21] reported that the timber structures cause lower climate change impact (CC) than the reinforced concrete structures. However, considering the primary energy demand and global warming impact, timber products do not show advantage in primary energy and water demand in comparison with concrete (see Fig. 15.3). Even though for environmental performance of a material, life cycle assessment (LCA) is widely used [22] and such assessment deliver a valuable insight about materials, but the LCA does not include the operational performance of using a material, it also does not include the construction time and labour intensity. For timber structures, a study by Gustavsson et al. [23] shows a block of flats built in timber with biomass-based energy supply system can have a considerable negative life cycle emission of CO2 (–62 kg CO2 /m2 for life span of 50 years, excluding household tap water and electricity). The study by Goverse [24] on four houses during their life cycle in Netherlands reveals that a 12% CO2 emission reduction is possible by replacing traditional materials with wood; however, energy supply system is not considered. In order to understand how timber performs in terms of operational energy, a case study is designed and simulated in London. It is pertinent to note the low level of thermal mass for timber may cause lower performance compared to concrete. An admittance and decrement factor are normally used to refer to thermal mass in most studies even though other factors such as effusivity and diffusivity are also noticed influential. These two factors are compared in Fig. 15.4, which shows a relatively low performance of timber in comparison with heavyweight systems.

Fig. 15.3 Admittance and decrement factor. Data from [25]

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Fig. 15.4 LCA for concrete, steel and timber. Graphic by authors, data from [26]

15.4.1 Operational Energy and Cost: Case Study of London A 13-storey model is used as a case study with an overall floor area of 3903.17 m2 . The building includes residential flats from 29.35 m2 to 168.46 m2 . The model is designed by a BIM application in a graduate student projects in the centre of London, UK. The costing and dynamic thermal simulations are used by the BIM application which uses EnergyPlus as its calculation engine. Figure 15.5 shows the model. Three different, most common prefabricated systems are used for simulation to compare their performance. HVAC systems, heating and cooling set points remained

Fig. 15.5 Model used for simulation and costing in a BIM application with a typical layout on the right. The building includes four types of flats from one bedroom to four bedrooms with parking on ground floor

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Fig. 15.6 Operational energy (kWh/m2 /year) and cost (GBP/m2 ) of SF, CLT and ICF for the case study. Source

the same for all the systems. All of them met the U-Value of 0.11 W/m 2 K. The description of each construction system and the materials used are as follows: • Steel Frame (SF). From out to in: 5 mm rendering, 200 mm extruded polystyrene (EPS), 10 mm plywood, 90 mm rockwool, 12.5 mm plasterboard • Cross Laminated Timber (CLT). From out to in: 110 mm brick outer leaf, 50 mm air gap, 140 mm rockwool, 10 mm plywood, 200 mm Rockwool, 12.5 mm plas-terboard • Insulating Concrete Formwork (ICF). From out to in: 5 mm rendering, 120 mm extruded polystyrene (EPS), 160 mm heavyweight concrete, 100 mm extruded polystyrene (EPS), 12.5 mm plasterboard. Each material is fully costed as per instructions of the suppliers in 2019, and the results demonstrate that operational energy usage is the highest for CLT (80.3 kWh/m2 /year) and the lowest for ICF (74.9 kWh/m2 /year), difference 6.7%. On the other hand, the cost for is ICF is 192 GPB/m2 –9.9% higher compared to CLT (see Fig. 15.6).

15.5 Acoustic Performance The design of all buildings needs to take into account a number of core acoustic considerations, which can all be classified under the general heading of “acoustic comfort” [27]. This is the well-being and feeling of a building occupants regarding the acoustic environment and can have a significant impact on a building’s users or inhabitants, with poor acoustics contributing to loss of productivity in offices, loss of privacy and security issues, and increased levels of stress and related diseases such as coronary heart disease [28]. There are several interlinked acoustic considerations which affect the acoustic comfort of a building. These include the geometry of the space, sound absorption, transmission and reflection of materials, and the presence sources of sound both inside and outside of the space. For high-rise buildings, wind

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noise at the façade and noise from entertainment areas (bars, restaurants, etc.) create particular challenges. Furthermore, indoor environmental quality (IEQ) is widely used as an indicator for thermal, acoustic and visual comfort and indoor air quality. For a place to be considered healthy for users, achieving a high level of IEQ is essential and acoustic comfort is one of the most important factors. Essential requirements are to prevent noise breaking into or out of a space—via airborne or structure borne paths, and to manage the internal acoustic. As acoustic insulation of materials directly correlates with mass, wooden structures will tend to have relatively poor airborne sound insulation in comparison to brick, concrete block or gypsum. Typical methods to improve acoustical performance of an assembly include adding mass such as mineral fibre in wall or panel cavities, or by adding concrete or gypsum boards of a panel assembly [29]. Decoupling the surfaces of the assembly to reduce direct sound transmission also increases performance significantly. By using multi-layered structures with panels of different densities separated by air gaps or resilient mounts, significant improvements in performance can be achieved while still using sustainable materials. Figure 15.7 shows the increase in sound transmission class ratings for a simple wooden stud wall using increases in mass and decoupling. One of the most common noise and vibration problems in multi-storey buildings is the transmission of noise through the structure of the building. This is particularly caused by impact noise from footfall, vibrations from plant and machinery directly coupled to the building structure and through floor deflection generated by movement varying the loading [30]. A key parameter in the transmission of sound through any medium is the speed at which it travels—the faster the speed the more efficient the sound transmission. Within mass-timber structures, CLT structures generally have improved acoustic performance compared to other timber structures, [31] as the cross-orientation of laminations inhibits sound transmission due to reduced transmission across the grain. Decoupling structural joints by using resilient materials

Fig. 15.7 Acoustical progression in wood framed walls STC 63. Data from [29, p. 5]

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such as acoustic caulk or neoprene pads also helps to reduce structure borne noise [30]. A common feature in timber high-rise buildings is the use of exposed beams and ceilings and wooden floor surfaces [32]. Although wooden panels generally have higher absorption rates brick or concrete, the wooden structures are typically varnished and polished, resulting in low absorption coefficients and high reverberation times, which in turn amplify noise in the space. The use of absorbent acoustic materials to reduce reverberation has been common in reverberant spaces for a long time, but many of these materials are based on non-sustainable materials such as melamine, expanded polyethylene or mineral fibre. However, there are increasing numbers of sustainable absorption materials available on the market, using materials such as bamboo fibre, cork, sheep’s wool or coconut fibre, which can provide effective reduction of reverberation in a space [33].

15.6 Discussion A growing interest in designing high-rise buildings in timber has made us look at different angles of using timber in high-rise buildings, namely structural capacity, construction practices, environmental performance and acoustics. In terms of structural capacity, literature is still limited in structural analysis of timber compared to well-established concrete and steel in high-rise buildings. Some research indicates the lack of guidelines and low coverage and knowledge of robustness in timber construction [12, 13]. Timber is an environmentally friendly material. The advantages of using timber are renewability, malleability, adaptiveness, the moderately lower weight compared to steel and concrete, easier fabrication process [14, 15]. Our findings show timber does not necessarily guarantee higher environmental performance in terms of operational energy and primary energy demand for construction even though in water usage; there is a considerable advantage in using timber compared to steel frame systems. More detail analysis of environmental performance in terms of material embodied energy requires future research. Furthermore, the cost of building in CLT could be considerably higher compared to the steel frame systems in the UK in order to meet UK standards in energy efficiency and that might slow down the usage of timber in high-rise structures. However, these findings have limitations as results are based on a single set of three case studies. Designing high-rise building in timber also creates challenges in acoustic performance as the higher sound transmission of timber structures needs careful attention in construction detailing. There is a lack of guidance in European standards about timber and building high rise from it mainly on acoustic and robust detailing and that might be the cause for a significantly high level of design errors in timber buildings as found by the Nordic study [12].

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15.7 Conclusion The drivers of using timber in high-rise building are widely known, but challenges and barriers have rarely been investigated. This study looked at the timber in highrise buildings from structural capacity, construction, environmental performance and acoustic perspective. Three case studies revealed the benefits of using timber in terms of LCA and operational energy even though with no advantage compared to concrete. This study also reveals the challenge of using timber in terms of structural capacity and acoustic performance. The findings of this study could be indicative for designers, but more detailed information from scientific research, case studies and practical studies about using timber in high-rise buildings are required to improve our knowledge in this area. Acknowledgements The present research has been financed under the EU ERASMUS+ projects “Sustainable High-Rise Buildings Designed and Constructed in Timber” (HiTimber) (Project No: 2017-1-DK-01-KA203-034242) and “Knowledge Alliance for Sustainable Mid-Rise and Tall Wooden Buildings” (KnoWood) (Project No: 600903-EPP-1-2018-1-DK-EPPKA2-KA).

References 1. Liu, B., Wang, D., Xu, Y., Liu, C., Luther, M.: A multi-regional input-output analysis of energy embodied in international trade of construction goods and services. J. Clean Prod. 201, 439–451 (2018) 2. Martin, L., Perry, F.: Sustainable construction technology adoption. Chapter 11 In: Sustainable Construction Technologies. Life Cycle Assessment, pp. 299–316. Butterworth Heinemann (2019) 3. Gan, V.J.L., Chan, C.M., Tse, K.T., Lo, I.M.C., Cheng, J.C.P.: A comparative analysis of embodied carbon in high-rise buildings regarding different design parameters. J. Cleaner Prod. 161, 663–675 (2017) 4. Wadel Raina, G.: Sustainability in industrialized architecture: modular lightweight construction applied to housing. PhD thesis. Universitat Politècnica de Catalunya (2009). 5. Al-Kodmany, K.: New suburbanism: sustainable tall building development. Routledge (2016) 6. CTBUH.: Global tall building database of the CTBUH. https://www.skyscrapercenter.com/ compare-data. last Accessed 05 Nov 2019 7. European Committee for Standardization (CEN).: EN 1090: Execution of steel structures and aluminium structures (3 parts). Brussels (2019). 8. European Committee for Standardization (CEN).: EN 13670: Execution of concrete structures. Brussels (2009) 9. European Committee for Standardization (CEN).: EN 1995: Design of timber structures (Eurocode 5). Brussels (2004) 10. European Committee for Standardization (CEN).: EN 350: 2016 Durability of wood and woodbased products—testing and classification of the durability to biological agents of wood and wood-based materials. Brussels (2016) 11. Huber, J.A.J., Ekevad, M., Girhammar, U.A., Berg., S.: Structural robustness and timber buildings—a review. Wood Mater Sci Eng 14(2), 107–128 (2019) 12. Hansson, E.F.: Analysis of structural failures in timber structures: typical causes for failure and failure modes. Eng. Struct. 33(11), 2978–2982 (2011)

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13. Cabrero, J. M., Iraola, B., Yurrita, M.: Failure of timber constructions. Chapter 7 In: Handbook of Materials Failure Analysis with Case Studies from the Construction Industries, pp. 123–152. Butterworth Heinemann (2018) 14. Fridley, K.: Wood and wood-based materials: current status and future of a structural material. J. Mater. Civ. Eng. 14(2), 91–96 (2002) 15. Arup. Rethinking timber buildings. London: Arup (2019). 16. Hackney Council. Hackney council puts wood first. https://www.charteredforesters.org/2012/ 05/hackney-council-puts-wood-first, Last Accessed 04 Nov 2019 17. Abrahamsen, R.B., Malo, K.A.: Structural design and assembly of “Treet”—a 14-storey timber residential building in Norway. In: World Conference on Timber Engineering (WCTE 2014), Quebec City, Canada (2014) 18. Gustavsson, L., Sathre, R.: Variability in energy and carbon dioxide balances of wood and concrete building materials. Build. Environ. 41(7), 940–951 (2006) 19. Durlinger, B., Crossin, E., Wong, J.: Life cycle assessment of a cross laminated timber building. FWPA, Melbourne (2013) 20. Crawford, R.H., Cadorel, X.: A framework for assessing the environmental benefits of mass timber construction. Procedia Eng. 196, 838–846 (2017) 21. Skullestad, J.L., Bohne, R.A., Lohne, J.: High-rise timber buildings as a climate change mitigation measure—a comparative LCA of structural system alternatives. Energy Procedia 96, 112–123 (2016) 22. International Organization for Standardization (ISO).: ISO 14040: Environmental management—life cycle assessment—principles and framework. Geneva (2006) 23. Gustavsson, L., Joelsson, A., Sathre, R.: Life cycle primary energy use and carbon emission of an eight-storey wood-framed apartment building. Energy Build. 42(2), 230–242 (2010) 24. Goverse, T.: Wood innovation in the residential construction sector; opportunities and constraints resources. Res. Conserv. Recycl. 34 (2001) 25. Sajjadian, S. M.: Future proofing UK sustainable homes under conditions of uncertainty. PhD thesis. University of Liverpool (2015) 26. Bribián, I.Z., Capilla, A.V., Aranda-Usón, A.: Life cycle assessment of building materials: comparative analysis of energy and environmental impacts and evaluation of the eco-efficiency improvement potential. Build. Environ. 46(5), 1133–1140 (2011) 27. Paradis, R.: Whole building design guide: acoustic comfort. National Institute of Building Sciences, Washington (2016) 28. WHO: Burden of disease from environmental noise: quantification of healthy life years lost in Europe. WHO Regional Office for Europe, Copenhagen (2011) 29. Thorburn, S.: Acoustical Considerations for Mixed-Use Wood-Frame Buildings. WoodWorks, Washington DC (2014) 30. Long, M.: The acoustics of floors in condominiums, Acoustics Today. pp. 35–40, Jan (2007) 31. National Research Council of Canada: Acoustic testing of CLT and gluelam floor assemblies. National Research Council of Canada, Ottawa (2016) 32. McLain, R.: Acoustics and mass timber: room-to-room noise control. WoodWorks, Washington DC (2018) 33. Desarnaulds, V., Costanzo, E., Carvalho, A., Arlaud, B.: Sustainability of acoustic materials and acoustic characterization of sustainable materials. In: Twelfth International Congress on Sound and Vibration, Lisbon (2005)

Chapter 16

A Review of V2-X Solutions by Investigating Different Vehicle Energy Storage Solutions for Nearly Zero Energy Buildings Yasaman Balali and Sascha Stegen Abstract Combining sustainable electric vehicle (EV) technologies with renewable energy sources in building and transportation sectors is an effective approach for reducing energy consumption, in order to meet nearly zero energy buildings (NZEBs) concepts. To this end, the integration of EVs through bidirectional converters with smart buildings, which are supplied by renewable energy sources such as photovoltaic systems, has gained noticeable attention from researchers around the world. In order to meet and optimize the energy requirement of smart buildings with V2GH-B (V2-X), which includes vehicle-to-home (V2H), vehicle-to-building (V2B), and vehicle-to-grid (V2G) technologies, an energy management strategy is needed. Plug-in battery-based EVs, plug-in hybrid EVs, and hydrogen fuel cell EVs are automobiles proposed for implementing the integrative approaches. The main purposes of this study are to review the proposed approaches for the integration of smart buildings and EVs, in order to introduce the possible future integration of hybrid fuel cell-based EVs to buildings and power grids. Previous studies demonstrated the limitations of battery life, because of the large number of charging and discharging requirements, which cause battery degradation. Wireless converters or wire-connected bidirectional converters are the components which are required for transferring energy from vehicle to grid/building/home, vice versa. This study will suggest the use of hydrogen-based hybrid electric vehicles as an energy transfer or in V2-X solutions. Keywords Vehicle-to-home/building/grid · Plug-in electric vehicles · Hydrogen fuel cell electric vehicles · Nearly zero energy buildings

Y. Balali (B) · S. Stegen School of Engineering and Built Environment, Griffith University, Brisbane, QLD 4111, Australia e-mail: [email protected] S. Stegen e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_16

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16.1 Introduction Building energy performance enhancement as a solution for reducing energy demand and increasing sustainability led to the introduction of the nearly zero energy buildings (NZEB) concepts, which evaluate whether the annual generated energy by renewable resources is matching annual building energy demand from the power grids [1]. The integration of electric vehicles (EVs) with buildings as an alternative source of energy provider has a significant role to play in reducing energy consumption, in order to move toward NZEB [2], and reducing power grid dependency [3]. The developments in home energy management systems (EMSs) and smart meters for infrastructures have been essential to evaluating the energy demand response and suggesting the optimal use of home appliances [4]. EVs can operate in various modes, such as vehicle-to-grid/home/building (V2G-H-B/V2-X) and G-BH2V, while a noticeable reduction in power losses caused by long-distance transmission lines in V2G systems is achieved through the use of V2H [5]. Plug-in electric vehicles (PEVs) are a common configuration for V2H-B options with a need for bidirectional energy flow between the vehicle and house/building [6, 7]. The connection of the EV to the home can be utilized for recharging the battery or transferring the stored energy in the battery to the home loads which introduces the H2V and V2H concepts [8, 9]. Heating, ventilation, and air conditioning (HVAC) systems consume high amount of energy in buildings. Therefore, consideration of HVAC as well as other appliances are important to evaluate whether V2-X systems are beneficial approaches for meeting the NZEB concepts. In order to find the best-optimized solution which can increase the battery life of EVs integrated to homes/buildings, this paper reviews the concepts and experiments implemented in this area. Moreover, the technology of PEVs as well as hydrogen fuel cell EVs is reviewed for their potential to be connected to power grid and buildings. This study is divided into sections focusing on V2-X solutions, with a short explanation of V2G concept as the primary investigation of using EVs as energy suppliers and the prominent focus on buildings and homes, followed by a short case study of different types of bidirectional converters that are used in these systems. Furthermore, various suitable EVs which can be suitable for these technologies are introduced.

16.2 V2G Solution The introduction of the smart grid has made a significant contribution toward connecting EVs to the grid, in order to benefit from using reactive power consumption, regulating the power network, spinning reverse functionality (provision of extra energy generation for unplanned load demand [10]), and shifting the required energy demand from peak-load to off-peak-load [11, 12]. The prominent components for V2G/G2V technologies are EVs, aggregator controllers, with the responsibility of

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controlling the safety of charging and discharging of batteries, as well as charging and discharging equipment [13]. In order to convert power from AC to DC/DC to AC, a bidirectional converter needs to be added to the infrastructure [14], which can support the active power required from the grid by managing the load peak demand [11]. In bidirectional category, based on the state-of-charge (SOC) level in a battery, EVs are acting as mobile energy storage and can be charged from the grid or supply the energy back to the grid [14]. In this technology, the local controller collects energy from different EVs and manage energy flow without negative influences on EVs and power grid operations [13].

16.3 V2H and V2B Technologies The V2H concept refers to the storage of extra generated energy in the battery of a vehicle during off-peak hours to reuse it as a source of power during peak demand [15]. Additionally, V2H-B can be considered as the backup energy source in the situation of a power outage or grid failure [16], when EV acts as a voltage source to supply power for the home [17]. On the positive side, fewer complex transmission line structures from the grid, higher level of grid stability, and lower grid energy requirement are achieved in V2H [18]. Conversely, the grid power losses, stabilization of load, and demand for energy should be taken into consideration in this technology [19]. The minimum components required for V2H technology are an EV/PEV, a bidirectional charger, smart meters, home EMSs, home electric appliances, and a small-scale distributed energy generation [20, 21]. The combination of renewable energy sources with EVs as a power source in homes/buildings can increase energy efficiency [7, 15]. Based on the SOC level in the battery of EV, electrical appliances receive energy as long as the vehicle is plugged into the smart home, using the uninterruptible power supply (UPS) [22]. V2H applications can be authorized for both linear and nonlinear electric appliances and contain two divisions which are the use of EV in isolated systems as a voltage source and its operation in the gridconnected case as offline UPS, respectively [23]. The AC–DC/DC–AC and DC–DC power converters which are part of bidirectional EV chargers are connected to a DC-link in V2H systems [22]. The DC–AC converter section has the functionality of working as a voltage source with four-quadrant conversion static synchronous compensator (STAT-COM) functionality and can control the frequency and amplitude of 50 Hz loads in addition to synthesizing with the grid voltage. At the same time, the DC-link regulation is conducted by the DC–DC converter section [22]. Moreover, if the vehicle is connected to home, both converters act as an AC–DC/DC–AC converter, which can switch quickly between H2V/V2H modes [21, 24]. The notion of V2H-B can be extended to multiple numbers of houses and buildings providing EVs and roof-mounted PV systems with the advantages of a wide-spreading provision of energy to other grid-connected houses [25].

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In building-to-vehicle-to-building (V2B2 ) solution, the energy is exchanged among different buildings by EVs [26]. This concept for the first time was considered in an office located in another building in addition to the V2H technology, and was proposed in [19]. The comparison between the proposed cases for V2B2 in [19] demonstrated that the existence of swappable extra battery pack with that of EV in the selected home which has roof-mounted PV systems reduced the required energy [19]. The sensitivity analysis of V2B2 scheme in Naples, Italy, with Mediterranean climate is conducted in [26], with the prominent idea of exploiting the off-site renewable energy from smart home via EV, which transfers battery-stored energy to buildings. In this investigation, the office in the building, as well as the home both, has HVAC systems and appliances, while the installation of building-integrated PV panels is on the tilted roof of the home or south façade of the office. And the swappable battery packs are located inside the home. It is concluded that the highest percentage of energy saving is related to the situation when the battery swap option was added and the PV panels were installed in the home [26]. An integrated FCEV to grid system including 4 kW PV panels, a residential house, and Hyundai ix35® as a FCEV with a hydrogen storage capacity of 5.6 kg was conducted and tested during winter time in a village situated in the Netherlands [27]. The main difference in FCEV is that in addition to battery energy, the remaining energy from the chemical conversion of hydrogen to electricity would be sent back to the grid/house/building. The proposed scenario concluded that from 3 kW up to 10 kW electricity production of FCEV was efficient; however, hydrogen requirement increased linearly with a rose in power output [27].

16.3.1 Bidirectional EV Chargers and Wireless Systems The bidirectional charger combined in PEVs permits the transmission of power in both directions (V2H and H2V) [28]. Different types of bidirectional chargers such as DC–DC converters, high gain non-isolated converters, and isolated converters are reviewed in [29]. These converters charge the battery of the vehicle in low SOC by the power grid or by home renewable energy sources, while the energy can be transferred back to the grid/home in high SOC of the battery [28]. The DC–DC halfbridge converter functions as a buck converter, which controls the battery current in charging mode and operates as a boost converter in discharging mode [23]. With these converters, a lithium-ion battery of the EV charges up to 80% of the battery capacity under constant current and then charges the remaining 20% with constant voltage [23]. The difficulties and complicated configuration of these wire-dependent, conventional bidirectional V2H systems resulted in the design of wireless topologies [30, 31]. Wheel wireless charging systems are installed in the tire of the wheels, with the parallel connection structure of coils, in order to reduce the size of the air gap created between the receiver coils of vehicles and transmitter coils installed in the floor area

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of buildings or parking lots [32]. The coils have ferrite core bars and are circular with the existence of an air gap in the middle with the functionality of transmitting and receiving the power from the vehicle to home and the other way around [31].

16.4 Proposed Electric Vehicle Technology for V2H, V2B, V2G Plug-in battery-based EVs, plug-in hybrid EVs, and hydrogen FCEVs have the potential to be connected to the electric power grid, residential houses, and/or other buildings. However, the use of fuel cell-based EVs is not widely tested in real situations. The following sections provide details of EV technologies.

16.4.1 Battery-Based EVs The battery electric vehicle (BEV) includes a battery pack for on-board or off-board charging [33], which powers the electric motor [34]. The main deficiency with regards to PEVs is that the total required electric energy for propulsion of the electric motor should be obtained through electrochemical energy conversion [35]. The key issue with battery-based EVs is battery degradation which can significantly affect the benefits of extending the V2-X technologies. Calendar aging, SOC, depth of discharge (DOD), and temperature are some factors which cause battery degradation [36–38]. The physical battery degradation leads to a capacity fade, which causes a reduction in vehicle efficiency and increases in internal resistance [38]. As a result, the reduction in battery capacity reduces the driving range of vehicles and the remaining energy for V2H-B systems [10]. Over time a chemical side reactions capacity in the battery lead to capacity fade up to a three-fourth of its initial value in 16 years and eight months, without being used in battery-based cars [39]. An eight hours vehicle battery usage for V2H system showed two years reduction in pack lifetime compared to the use of battery packs solely for mixed-cycle driving [39]. Installation of a 50–150% larger battery capacity in the examined EV led to an extension of battery life with a year and seven months of life reduction in the proposed V2H system [39]. As a result, a controlling strategy that optimizes the demand for battery storage energy usage can reduce degradation and increase the battery life [40].

16.4.2 Plug-In Hybrid EVs The limitations of BEVs such as long charging time and a fast discharge rate led to the design of plug-in hybrid electric vehicles (PHEVs) [41]. The battery pack is

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connected to the electric motor and can power the vehicle during the conventional engine operation or alone [42]. In PHEVs compared to hybrid electric vehicles, an additional battery charger and socket are added to obtain energy from the power grid [42]. PHEV, when the SOC of the battery is low, the conventional motor powers the vehicle until the battery replenishes to its maximum SOC level [42]. Also, during a low SOC, the battery pack in the process of the recuperation of the kinetic energy operates as a buffer in order to increase engine efficiency [43]. As high energy density and power density of installed energy storage systems (ESSs) are the main requirements for PHEVs, and the combination of supercapacitors (SCs) and batteries is an effective way to extend the battery life [44] and increase the overall performance of the vehicle [44]. However, optimization of the battery size and the SC, as well as the implementation of an EMS, are necessary to ensure the battery is protected [44], from capacity and power fading [45].

16.4.3 Hydrogen-Based EVs Fuel cell-based EVs power the vehicle by electrical energy generated from the chemical conversion of hydrogen [46]. Moreover, the fuel cell can be combined with other ESSs such as battery packs and SCs as an auxiliary energy source, which introduces fuel cell hybrid electric vehicles (FCHEVs) technology [47]. A novel fuel cell/battery/ SC hybrid electric vehicle using PWM technique was proposed in [48], in order to provide three-phase current demonstrated a power efficiency of 96.2%. Different combinations of the fuel cell with SC and battery packs are explained in [33, 49]. The combination of SC and battery reduces hydrogen fuel consumption [50], and the size of fuel cell stack [49]. Also, this combination enables the provision of instantaneous power required during acceleration and regenerative braking process [51]. Algorithms for various hybrid energy integration and interaction of proposed electric vehicles as well as a conventional and bio-based vehicle to buildings are evaluated and discussed in [52]. The technical interaction of different vehicles including hydrogen FCEVs, biofuel-based vehicles, battery electric vehicles, and gasolinebased vehicles with buildings was presented in [52]. However, the investigation and implementation of these scenarios are not examined and compared in the existing buildings, in order to find the most optimal system.

16.5 Recommendation for Future V2H, V2B, and V2G Systems Based on the review, the following recommendations can be provided for a comprehensive V2-X solution:

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Integration of V2-X solutions with FCHEVs, including fuel cell as well as ESSs (SC/battery pack), can be the subject for future research. The consumption of hydrogen would be reduced in comparison with the integration of FCEV in the same situation. This is because the hybridization of fuel cell and SC/battery can improve the driving range and fuel economy of vehicles. However, the availability of hydrogen refueling stations can influence the decision about the reduction of hydrogen fuel requirement. Such a consideration can limit the advantages of fuel cell-based vehicles as a better solution for V2-X compared to PEVs. Further research should be conducted in order to evaluate the need for a swappable battery for V2B2 system integrated with FCEVs/FCHEVs. Furthermore, in FCHEVs with both SC and battery pack, the size of the battery pack is smaller compared to that of FCEV. As a result, the integration of V2-X solutions with FCHEV reduces the size of swappable battery required for the situations when the EVs provide power for a house and an office in another building. This reduction in the size of battery energy storage reduces the cost of the battery pack. However, an investigation is required to evaluate whether the smaller size of the battery pack can be used as an alternative to an energy storage system in terms of storing the generated energy by PV systems. The swappable battery is suggested for the scenario considering the energy demand of a residential house and an office in a large building. The idea can be expanded to combine these vehicles with large commercial buildings such as universities with sustainable renewable energy systems. As the energy requirements of these buildings are much greater than residential buildings, the minimum number of EVs should be identified, in order to meet the NZEB concepts. Furthermore, the construction of parking lots creates the possibility of connecting vehicles-to-vehicles, which would enable vehicles to supply power to other vehicles and large buildings in addition to the residential houses of their owners. However, in this case, a combination of EVs (PHEVs, PEVs, FCEVs, and FCHEVs) can be used. Further research is needed to carry out the number of required swappable batteries when large buildings are taken into consideration. Furthermore, the use of swappable batteries would not be the best option, which increases the need for other storage solutions such as large energy storage systems as well as the existence of electrolyzer/fuel cell stack in the building system.

16.6 Conclusion Various types of EVs used for V2-X is operating as an auxiliary energy supplier in addition to renewable energy systems for smart houses and buildings. Integrating electric vehicles with buildings benefits from the use of off-site energy sources. These sources can be EV battery packs in addition to on-site renewable energy systems such as PV panels. The main aim of this integration was to shift the peak energy requirement of buildings to off-peak, meet the NZEB concepts, and provide backup power during a grid power outage. Problems such as power quality and power losses caused by a long transmission line of V2G technologies led to the

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introduction of V2H (for a residential house) and V2B (for both residential and commercial buildings) solutions. Some studies introduced EVs as an alternative to large battery energy storage systems in buildings. While a few studies concluded the existence of a swappable battery pack similar to that of the vehicle was the best option. These studies expanded the V2H-B concepts by considering the energy demand of an office in a large building along with a residential house. Furthermore, local climate conditions should be taken into consideration, as the amount of generated energy from PV systems is significantly dependent on solar radiation. The FCEV was integrated with the grid, a PV system, and a house. The conclusion of this combination was that the hydrogen-fueled vehicle could reduce the negative impacts on the installed battery pack. This is because the battery was not the primary energy source and the main energy was provided by hydrogen. The combination of V2-X technologies with EVs can be expanded to a greater number of houses, buildings, and the power grid. Consequently, recommendations have been made in regard to further studies which evaluate whether fuel cell-based vehicles, and swappable batteries are the best solutions for larger buildings by considering economic, required services, technology, and environmental impacts concerns.

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Chapter 17

Occupants’ Behavioral Analysis for the Optimization of Building Operation and Maintenance: A Case Study to Improve the Use of Elevators in a University Building Gabriele Bernardini , Elisa Di Giuseppe , Marco D’Orazio , and Enrico Quagliarini Abstract The impact of the users’ behavior on the building performance is largely recognized, especially considering most of common building operation and management (O&M) tasks. Predictions of human-building interactions are essential to improve building efficiency by decreasing wastes and costs connected to O&M while satisfying the comfort level required by the occupants. At this regard, building technological systems, which status depends on the users’ movement inside the buildings, like elevators, represent one of the critical spots, especially in high-density buildings. According to a “user-centered” approach, this paper moves toward the assessment of behavioral drivers which can influence the use of elevators in public buildings to define a probability use model useful to set specific maintenance policies. In situ evaluations are performed in a university building, where flows of people are highly dependent on the indoor activities scheduled, as lessons. A multinomial logit model for the probability of elevators’ use is built depending on factors such as: floors number, movement in group, direction (upwards, downwards). Users’ fruition patterns in the university building are detected using eye-tracking techniques and questionnaires. Results show how the elevators’ use probability increases when the number of floors to cross increases, also because of perceived movement comfort, while individuals’ attention is mainly affected by posters and signage systems placed along the way. The model could be implemented in building simulation models, to predict the elevators use during the time under different circumstances, hence to optimize related O&M measures. Keywords Building operation and maintenance · Elevators · Condition-based maintenance · Buildings users’ behavior · In situ evaluation · Behavioral models

G. Bernardini (B) · E. Di Giuseppe · M. D’Orazio · E. Quagliarini Università Politecnica Delle Marche, via Brecce Bianche, 60130 Ancona, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Littlewood et al. (eds.), Sustainability in Energy and Buildings 2020, Smart Innovation, Systems and Technologies 203, https://doi.org/10.1007/978-981-15-8783-2_17

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17.1 Introduction The improvement of buildings sustainability could be reached by defining the effective interactions between the building and its users, over time and space, to evidence the possible criticalities within the overall system and promote possible mitigation and performance-increasing design strategies [1, 2]. This approach is essential in the initial design phase, as well as in the building lifecycle, when the building Operation and Maintenance (O&M) issues occur [2–4]. Indeed, effective and expected building conditions could be different because of real users’ behavior, especially in public and mixed-use buildings and in existing buildings [2, 5]. The possibility to adopt a “usercentered approach” to predict human-building components interactions can improve building efficiency, by decreasing wastes and costs of O&M tasks, thus moving from “planned” and “corrective” approaches to proactive and predictive ones [1, 6, 7]. In this sense, elevators are critical systems in multi-story public buildings, where the interactions with the users strongly depend on buildings’ occupancy patterns [1]. According to a “user-centered” approach, this work intends to assess the behavioral drivers which can influence the use of elevators in such a context. The behavioral patterns are investigated through an in situ evaluation campaign in a real university building case study. Main man–environment relationships related to the flows in the building are assessed through eye-tracking techniques. Experimental data are organized to define a probability model for the elevator use. Survey and eye-tracking data are also analyzed to outline possible individual-related factors which can influence the proposed model significance.

17.2 Literature Review User-building interaction models play a pivotal role in this “user-centered” approach [6–9]. Their implementation in building simulation models and Building Automation Systems (BAS) eases the following steps in O&M [6]: (a) trace dependencies among building components and occupants’ behaviors (presence, actions, level of satisfaction); (b) derive in situ and time-dependent variations in the building use; (c) combine data from real-time monitoring and simulations in a platform for building O&M; (d) move toward a direct communication and interaction among the platform, buildings’ users and stakeholders. Literature works generally focused on modeling the users’ behavior related to buildings’ energy use (e.g., lighting, heating, air conditioning systems) [2, 10, 11]. This allows developing proactive, condition-based, data-driven methodologies to improve building performances [1, 12]. On the contrary, the impact of occupants’ movement on O&M issues is less investigated [1, 6, 12]. Elevators represent one of the most critical systems within a building, especially if considering multi-story public buildings [1]. General criteria for the design of elevators and for the definition of related O&M actions generally take into account standard passengers’ flows scenarios [13]. Recently, real-time monitoring systems

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and simulation models have been developed to improve the elevators management (e.g., the optimization of the users’ waiting time) [14–17]. This allows evaluating the impact of different strategies in relation to [1, 13, 17–20]: (a) operation, e.g., energy consumption under recurring conditions; (b) maintenance, e.g., life cycle of composing elements and organization of maintenance activities; (c) safety. Current approaches to real-time monitoring propose Internet of Things (IoT)based systems to detect the conditions, use and faults of the elevators [8, 9, 20]. Although such systems support “corrective maintenance” and allow detecting data to move toward “condition-based” maintenance, they are quite complex to be introduced in existing buildings and limitedly consider the passengers’ flows in a direct manner, since they are focused on the mechanical components monitoring [1, 17]. Moreover, they provide limited information to support a “predictive maintenance” plan to be integrated into “time-based” maintenance actions [6]. To move toward such direction, this work would like to adopt an approach based on simple data to be collected and managed concerning the real use of the elevators by the building occupants. In situ evaluations are useful to this end [21, 22], also combining data from IoT systems implemented in the elevators [1, 17]. Some researches were conducted to derive models on the probability of stairs/elevators use [22], by additionally investigating the trend of elevators use (moving upwards and downwards) during the daytime in respect to the building occupancy [21]. Results suggest that the dilemma if using stairs or elevators is essentially driven by occupancy and passengers’ flows-related factors (i.e., estimated travel time, estimated delay time), as well as by additional social norms and individual perception-related factors (e.g., laziness, habits, etc.) [22, 23]. In addition, wayfinding aspects (e.g., interaction with elevator button and signaling) are also important, especially if considering individuals who are not familiar with the building [24, 25]. Nevertheless, the combination among such elements is rarely investigated, and evaluations in public buildings are needed to correlate the variables. To reach this goal, data from monitoring campaign are correlated in this work according to logistic regression approaches (also combined to discrete choice models). In fact, literature works underline how such kind of elevator operations models seem to be one of the best choices in terms of model complexity, data requirement and level of implementation [1, 22].

17.3 Methodology The work is organized in the following main phases. The first one concerns a survey campaign to detect the use of elevators in the main multi-story public building, hosting classrooms of the University Politecnica delle Marche-Faculty of Engineering (Ancona, Italy).1 The building has six floors and five elevators with a capacity of eleven people. 223 students (moving freely inside the building) were randomly 1 www.ingegneria.univpm.it

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selected and involved in the study, with an age ranging from 20 to 32 years. Each student was surveyed and asked to claim: (a) if they were moving by using the elevators or the staircases or both of them (and for how many floors); (b) the total number of floors they rode; (c) if they were moving in a group and, if yes, the number of individuals in the group2 ; (d) reasons about their choice to use the elevator (i.e., moving faster, familiarity with the use of the elevator/habits, perceived comfort) or not the elevator (i.e., healthy habits), according to the main drivers identified in literature on social norms and personality factors [22, 23]. 40 students within the whole sample (randomly selected) were asked to wear an eye-tracking system to detect which elements they looked at while moving. The second phase concerns the development of a model to determine the probability to use elevators while moving (Sect. 17.3.1). Finally, this phase also involves the definition of the main elements in the architectural space that attracted the individuals’ attention while moving, according to the eye-tracking data, and as discussed in Sect. 17.3.2.

17.3.1 Modeling Elevators Use Survey data are organized to derive a model for estimating the probability to use the elevators while moving inside the building. The approach is based on a joint Logistic Regression Model (LRM)-Discrete Choice Model (DCM) [22, 26], since this allows to derive the probability of the user to perform a choice while interacting with a building component. This joint approach was previously proposed to estimate the probability of using stairs in relation to the height to be traveled [22]. In the DCM, only two available status are possible: interacting (U iq =1), that is using the elevator; not interacting (U iq =0), that is using stairs. The utility function U iq evaluates which of these alternatives will be chosen by the individual according to Eq. 17.1: Uiq = Viq + εiq

(17.1)

where V iq [−] represents “the expected value of the perceived utility” and εiq [−] represents “the deviation of the average utility from the real value” [26]. According to the survey data, V iq is assumed to be dependent on the following variables: • the number of floors to be traveled x floor [−], represented by positive integer values; • the motion direction x dirfloor [-], that is considered equal to 1 for individuals “moving upwards” and −1 for individuals “moving downwards”; • the dimension of the group x group in which the individual moves. This value is considered equal to 1 in case of an isolated pedestrian. 2 People

items.

in group were sampled only once, to avoid affecting the dataset with multiple correlated

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Two generalized linear regression models are proposed to derive Eq. 17.1 values: in Eq. 17.2, V iq linearly depends on x floor ; in Eq. 17.3, V iq linearly depends on the logarithm of x floor , by testing the hypothesis that the influence of this variable should converge while x floor increases. The multinomial logistic regression according to a binomial distribution is applied to calculate the coefficients afloor , adir and agroup for each model, and the variable-related standard errors and p-values are calculated to verify the model significance. Additionally, the overall p-value for the model is assessed and the analysis of questionnaires data (i.e., point (d) in Section 17.3) is used to verify possible differences between effective and predicted behavioral patterns. Uiq = afloor xfloor + adir xdir + agroup xgroup + εiq

(17.2)

Uiq = afloor ln(xfloor ) + adir xdir + agroup xgroup + εiq

(17.3)

Finally, the elevator use probability U iq is calculated according to the inverse LRM by considering different combinations between the independent variables, offering related graphical representations [26].

17.3.2 Eye-Tracking Analysis The eye-tracking system used in this study is the Tobii Pro Glasses 2,3 that is a wearable eye tracker with four eye cameras and a full HD wide angle scene camera placed in the head unit (glasses). The user can unrestrictedly move around the spaces while the eye-tracking data are recorded by the device (gaze sampling frequency of 50 Hz) [27, 28]. Eye-tracking data are analyzed through the Analysis Software Tobii Pro Lab, to define the fixation of objects and areas in the space, thus the user’s engagement in respect to the perceived element. All the fixations equal or longer than 560 ms are considered as significative [28]. The main objects that have been considered for the fixation analysis were those providing information on the space configuration (i.e., signage systems to identify the classrooms; evacuation signage), on the building use (i.e., posters on events at the university) and on the elevators status (i.e., elevator display, near to the elevator button) [22, 23, 29]. Percentages of such objects fixated by the individual along his/her path are calculated in respect to their overall number to define each typology influence. Finally, the individuals were also asked if they decide to adopt special motion choices because they focused the attention on such objects. Videotapes of the tests were checked to confirm such individual’s perception.

3 https://www.tobiipro.com/siteassets/tobii-pro/brochures/tobii-pro-glasses-2-brochure.pdf/?v=6,

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17.4 Results Raw statistics for the survey data are provided. In particular, the percentages of people using the elevators according to the different surveyed conditions were identified to outline the main behavioral patterns within the sample (Table 17.1 and Fig. 17.1). Results firstly evidence that individuals seem to generally prefer using the elevators while moving upwards. This trend grows with the x floor increase. Data for x floor =4 can be considered as limitedly significant because of the sample dimension in respect to the other x floor values, as shown by Fig. 17.1b. Although the sample dimension is limited, data show a great preference of the elevators for the widest groups (i.e., x group =5), while smaller groups are characterized by similar use percentages in respect of isolated users, as shown by Fig. 17.1a. Anyway, the possibility to use the elevators for wide groups can be affected by the effective free capacity of the car when the users call the elevator. Only 4% of surveyed people stated to have traveled by using both elevator and stairs (“also staircases” rows in Table 17.1). On these bases, both the proposed models show a direct correlation with the considered variables, as shown by the positive coefficients in Table 17.2. Hence, the probability to use the elevators increase while increasing the considered values, as shown by Fig. 17.2, in each of the considered conditions. In particular, the elevator use is higher in the case of moving upwards (Fig. 17.2a) and while the group dimension is maximized in respect to the experimental conditions (Fig. 17.2b). Figure 17.2d Table 17.1. Basic statistics of survey data, including notes to results (pref = preferring using elevators; av.fl. = average number of floor; up = moving upwards; down =moving downwards). Condition

Secondary condition

Upwards

Downwards

Group

x floor

Using elevator (notes)

Sample dimension (notes)

Percentage [%]

-

51

139

37

Also staircases

5 (pref:5; av.fl.:3)

10

50

-

23

104

22

Also staircases

5 (pref:2; av.fl.:3)

10

50

All directions

27

72

38

Upwards

16

33

48

Downwards

11

39

28

1

7 (up:3; down:4)

50 (up:30; down:20)

14

2

37 (up:29; down:8)

109 (up:65; down:44)

34

3

30 (up:19; down:11)

76 (up:39; down:37)

39

4

0 (up:0; down:0)

8 (up:5; down:3)

0

17 Occupants’ Behavioral Analysis for the Optimization …

213

Fig. 1. Basic statistics of use of elevators depending on: a group dimension x group (S defines the related sample dimension in terms of the number of groups with the specific x group value); b-the number of floors to be traveled, including total sample, and upwards/downwards subsamples. Table 17.2. Coefficients for the proposed DCM models according to Eqs. 17.2 and 17.3, and related statistics (SE=standard error; p-value). Coefficient

Equation 17.2

SE

p-value

Equation 17.3

SE

p-value

afloor

0.15

0.19

0.43

0.53

0.39

0.16

adir

0.46

0.16