Energy Sustainability in Built and Urban Environments PDF

This book covers different aspects of energy sustainability in residential buildings and neighborhoods, starting from the construction and design aspects, and moving on to HVAC systems and lighting, and the applications, harvesting, use and storage of renewable energy. The volume focuses on smart and sustainable use of energy, discussing both the technological advancements and the economic, social and environmental impacts. Novel approaches to recycling of waste and materials in the context of residential buildings are also presented. This volume will be of interest to researchers and policy makers working in the fields of renewable energy, sustainable design and city planning.

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Energy, Environment, and Sustainability Series Editors: Avinash Kumar Agarwal · Ashok Pandey

Emilia Motoasca Avinash Kumar Agarwal Hilde Breesch Editors

Energy Sustainability in Built and Urban Environments

Energy, Environment, and Sustainability Series editors Avinash Kumar Agarwal, Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India Ashok Pandey, Distinguished Scientist, CSIR-Indian Institute of Toxicology Research, Lucknow, Uttar Pradesh, India

This books series publishes cutting edge monographs and professional books focused on all aspects of energy and environmental sustainability, especially as it relates to energy concerns. The Series is published in partnership with the International Society for Energy, Environment, and Sustainability. The books in these series are editor or authored by top researchers and professional across the globe. The series aims at publishing state-of-the-art research and development in areas including, but not limited to: • • • • • • • • • •

Renewable Energy Alternative Fuels Engines and Locomotives Combustion and Propulsion Fossil Fuels Carbon Capture Control and Automation for Energy Environmental Pollution Waste Management Transportation Sustainability

More information about this series at http://www.springer.com/series/15901

Emilia Motoasca Avinash Kumar Agarwal Hilde Breesch •

Editors

Energy Sustainability in Built and Urban Environments

123

Editors Emilia Motoasca Department of Electrical Engineering KU Leuven (Catholic University Leuven) Ghent, Belgium

Hilde Breesch Department of Civil Engineering KU Leuven (Catholic University Leuven) Ghent, Belgium

Avinash Kumar Agarwal Department of Mechanical Engineering Indian Institute of Technology Kanpur Kanpur, Uttar Pradesh, India

ISSN 2522-8366 ISSN 2522-8374 (electronic) Energy, Environment, and Sustainability ISBN 978-981-13-3283-8 ISBN 978-981-13-3284-5 (eBook) https://doi.org/10.1007/978-981-13-3284-5 Library of Congress Control Number: 2018961716 © Springer Nature Singapore Pte Ltd. 2019 This work is subject to copyright. All rights are reserved 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, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional afﬁliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

Energy demand has been rising remarkably due to increasing population and urbanization. Global economy and society are signiﬁcantly dependent on the energy availability because it touches every facet of human life and its activities. Transportation and power generation are two major examples. Without the transportation by millions of personalized and mass transport vehicles and availability of 24 7 power, human civilization would not have reached contemporary living standards. The International Society for Energy, Environment and Sustainability (ISEES) was founded at Indian Institute of Technology Kanpur (IIT Kanpur), India, in January 2014 with the aim of spreading knowledge/awareness and catalysing research activities in the ﬁelds of energy, environment, sustainability and combustion. The society’s goal is to contribute to the development of clean, affordable and secure energy resources and a sustainable environment for the society and to spread knowledge in the above-mentioned areas and create awareness about the environmental challenges, which the world is facing today. The unique way adopted by the society was to break the conventional silos of specializations (engineering, science, environment, agriculture, biotechnology, materials, fuels, etc.) to tackle the problems related to energy, environment and sustainability in a holistic manner. This is quite evident by the participation of experts from all ﬁelds to resolve these issues. ISEES is involved in various activities such as conducting workshops, seminars and conferences in the domains of its interest. The society also recognizes the outstanding works done by the young scientists and engineers for their contributions in these ﬁelds by conferring them awards under various categories. The second international conference on “Sustainable Energy and Environmental Challenges” (SEEC-2018) was organized under the auspices of ISEES from 31 December 2017 to 3 January 2018 at J N Tata Auditorium, Indian Institute of Science Bangalore. This conference provided a platform for discussions between eminent scientists and engineers from various countries including India, USA, South Korea, Norway, Finland, Malaysia, Austria, Saudi Arabia and Australia. In this conference, eminent speakers from all over the world presented their views v

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Preface

related to different aspects of energy, combustion, emissions and alternative energy resources for sustainable development and a cleaner environment. The conference presented ﬁve high-voltage plenary talks from globally renowned experts on topical themes, namely “Is It Really the End of Combustion Engines and Petroleum?” by Prof. Gautam Kalghatgi, Saudi Aramco; “Energy Sustainability in India: Challenges and Opportunities” by Prof. Baldev Raj, NIAS Bangalore; “Methanol Economy: An Option for Sustainable Energy and Environmental Challenges” by Dr. Vijay Kumar Saraswat, Hon. Member (S&T), NITI Aayog, Government of India; “Supercritical Carbon Dioxide Brayton Cycle for Power Generation” by Prof. Pradip Dutta, IISc Bangalore; and “Role of Nuclear Fusion for Environmental Sustainability of Energy in Future” by Prof. J. S. Rao, Altair Engineering. The conference included 27 technical sessions on topics related to energy and environmental sustainability including 5 plenary talks, 40 keynote talks and 18 invited talks from prominent scientists, in addition to 142 contributed talks, and 74 poster presentations by students and researchers. The technical sessions in the conference included Advances in IC Engines: SI Engines, Solar Energy: Storage, Fundamentals of Combustion, Environmental Protection and Sustainability, Environmental Biotechnology, Coal and Biomass Combustion/Gasiﬁcation, Air Pollution and Control, Biomass to Fuels/Chemicals: Clean Fuels, Advances in IC Engines: CI Engines, Solar Energy: Performance, Biomass to Fuels/Chemicals: Production, Advances in IC Engines: Fuels, Energy Sustainability, Environmental Biotechnology, Atomization and Sprays, Combustion/Gas Turbines/Fluid Flow/Sprays, Biomass to Fuels/Chemicals, Advances in IC Engines: New Concepts, Energy Sustainability, Waste to Wealth, Conventional and Alternate Fuels, Solar Energy, Wastewater Remediation and Air Pollution. One of the highlights of the conference was the rapid-ﬁre poster sessions in (i) Energy Engineering, (ii) Environment and Sustainability and (iii) Biotechnology, where more than 75 students participated with great enthusiasm and won many prizes in a ﬁercely competitive environment. More than 200 participants and speakers attended this four-day conference, which also hosted Dr. Vijay Kumar Saraswat, Hon. Member (S&T), NITI Aayog, Government of India, as the chief guest for the book release ceremony, where 16 ISEES books published by Springer, under a special dedicated series Energy, Environment, and Sustainability were released. This is the ﬁrst time that such signiﬁcant and high-quality outcome has been achieved by any society in India. The conference concluded with a panel discussion on “Challenges, Opportunities and Directions for Future Transportation Systems”, where the panellists were Prof. Gautam Kalghatgi, Saudi Aramco; Dr. Ravi Prashanth, Caterpillar Inc.; Dr. Shankar Venugopal, Mahindra and Mahindra; Dr. Bharat Bhargava, DG, ONGC Energy Centre; and Dr. Umamaheshwar, GE Transportation, Bangalore. The panel discussion was moderated by Prof. Ashok Pandey, Chairman, ISEES. This conference laid out the road map for technology development, opportunities and challenges in energy, environment and sustainability domains. All these topics are very relevant for the country and the world in the present context. We acknowledge the support received from various funding agencies and organizations for the successful conduct of the second ISEES conference SEEC-2018, where

Preface

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these books germinated. We would therefore like to acknowledge SERB, Government of India (special thanks to Dr. Rajeev Sharma, Secretary); ONGC Energy Centre (special thanks to Dr. Bharat Bhargava); TAFE (special thanks to Sh. Anadrao Patil); Caterpillar (special thanks to Dr. Ravi Prashanth); Progress Rail, TSI, India (special thanks to Dr. Deepak Sharma); Tesscorn, India (special thanks to Sh. Satyanarayana); GAIL, Volvo; and our publishing partner Springer (special thanks to Swati Meherishi). The editors would like to express their sincere gratitude to a large number of authors from all over the world for submitting their high-quality work in a timely manner and revising it appropriately at short notice. We would like to express our special thanks to Prof. Ahmed Rachid, Arch. Alexis Versele, Dr. Bart Huyck, Prof. Roger Sierens, Dr. Abhishek Dutta, Prof. Giacomo Chiesa, Dr. Ivan Korolija, Mrs. Sien Winters, Prof. Bolanle Ikotun, Mrs. Tran Thanh Vu, Prof. Pham Duc Nguyen, Mr. Bart Merema and Prof. Jos Knockaert, who reviewed various chapters of this book and provided very valuable suggestions to the authors to improve their manuscript. This book covers different aspects of energy sustainability: implementation at macro-scale (nation, city, neighbourhood) and building scale, strategies in relation to buildings, neighbourhoods, systems and energy markets and sustainable energy production, use and storage technologies. Topics include sustainable construction practices, urban planning, energy efﬁciency of residential, school and ofﬁce buildings, how to manage the impact of future climate conditions, control strategies of microgrids and ﬁnancial instruments. Wind energy, thermoelectric materials, concentrated photovoltaic, hydrogen fuel clean energy cycle and renewable energy storage are also presented here through a series of chapters. Ghent, Belgium Kanpur, India Ghent, Belgium

Emilia Motoasca Avinash Kumar Agarwal Hilde Breesch

Contents

Part I

Energy Sustainability Implementation 3

1

Sustainable Construction Practices in West African Countries . . . . Adedayo J. Ogungbile and Ayodeji E. Oke

2

Modelling the Inﬂuence of Urban Planning on the Financial and Environmental Impact of Neighbourhoods . . . . . . . . . . . . . . . . Damien Trigaux, Karen Allacker and Frank De Troyer

17

Achieving Energy Efﬁciency in Urban Residential Buildings in Vietnam: High-tech or Low-tech? . . . . . . . . . . . . . . . . . . . . . . . . Quang Minh Nguyen

39

Recommendations for the Design of an Energy-Efﬁcient and Indoor Comfortable Ofﬁce Building in Vietnam . . . . . . . . . . . Ngo Hoang Ngoc Dung and Nguyen Trung Kien

67

3

4

Part II

Energy Sustainability Strategies 93

5

Linking Neighborhoods into Sustainable Energy Systems . . . . . . . . A. T. D. Perera, Silvia Coccolo, Pietro Florio, Vahid M. Nik, Dasaraden Mauree and Jean-Louis Scartezzini

6

Future Weather Data for Dynamic Building Energy Simulations: Overview of Available Data and Presentation of Newly Derived Data for Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Delphine Ramon, Karen Allacker, Nicole P. M. van Lipzig, Frank De Troyer and Hendrik Wouters

7

Evaluation of a Simpliﬁed Calculation Approach for Final Heating Energy Use in Non-residential Buildings . . . . . . . . . . . . . . 139 Barbara Wauman, Wout Parys, Hilde Breesch and Dirk Saelens

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x

Contents

8

A Review of Fuzzy-Based Residential Grid-Connected Microgrid Energy Management Strategies for Grid Power Proﬁle Smoothing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 Diego Arcos-Aviles, Francesc Guinjoan, Julio Pascual, Luis Marroyo, Pablo Sanchis, Rodolfo Gordillo, Paúl Ayala and Martin P. Marietta

9

Analyzing Alternative Energy Mutual Fund Performance in the Spanish Market . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Carmen-Pilar Martí-Ballester

Part III

Energy Sustainability Technologies

10 Wind Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 J. Peuteman 11 Energy Sustainability Through the Use of Thermoelectric Materials in Waste Heat Recovery Systems Recent Developments and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 Emilia Motoasca 12 Optimization Strategy of Sustainable Concentrated Photovoltaic Thermal (CPVT) System for Cooling . . . . . . . . . . . . . . . . . . . . . . . 255 Muhammad Burhan, Muhammad Wakil Shahzad and Kim Choon Ng 13 Novel Method and Molten Salt Electrolytic Cell for Implementing a Hydrogen Fuel, Sustainable, Closed Clean Energy Cycle on a Large Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277 Alvin G. Stern 14 Renewable Energy Storage and Its Application for Desalination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313 Muhammad Wakil Shahzad, Muhammad Burhan and Kim Choon Ng

Editors and Contributors

About the Editors Emilia Motoasca (Ph.D.) is an assistant professor at Electrical Engineering (ESAT) TC, KU Leuven (Catholic University of Leuven), Belgium. She has previously worked as an assistant professor and postdoc in KU Leuven and Eindhoven University of Technology, the Netherlands, respectively. Her research interests are in the design of electric/hydraulic drive trains, electric motors and other types of actuators; assistive devices and energy-efﬁcient design. She has authored more than 34 research papers and holds 1 patent. Avinash Kumar Agarwal (Ph.D.) is a professor in the Department of Mechanical Engineering at Indian Institute of Technology Kanpur. His areas of interest are IC engines, combustion, alternative fuels, conventional fuels, optical diagnostics, laser ignition, HCCI, emission and particulate control, and large bore engines. He has published 24 books and more than 230 international journal and conference papers. He is a fellow of SAE (2012), ASME (2013), ISEES (2015) and INAE (2015). He received several awards such as prestigious Shanti Swarup Bhatnagar Award-2016 in engineering sciences; Rajib Goyal Prize-2015; NASI-Reliance Industries Platinum Jubilee Award-2012; INAE Silver Jubilee Young Engineer Award-2012; SAE International’s

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Editors and Contributors

Ralph R. Teetor Educational Award-2008; INSA Young Scientist Award-2007; UICT Young Scientist Award2007 and INAE Young Engineer Award-2005. Hilde Breesch (Ph.D.) is an assistant professor in the Department of Civil Engineering, KU Leuven (Catholic University Leuven), and the head of Construction Technology Cluster at Technology Campus Ghent, Aalst. Her research expertise is in energy performance and indoor climate; interaction building and HVAC systems; commissioning and monitoring for sustainable building construction and has previously worked with KAHO Sint-Lieven, Ghent University and Technum NV in Belgium. Hilde Breesch has published over 45 research papers in leading international journals and conference proceedings and has coordinated several guidelines for industry in the HVAC domain.

Contributors Karen Allacker Faculty of Engineering Science, Department of Architecture, KU Leuven, Louvain, Belgium Diego Arcos-Aviles Departamento de Eléctrica y Electrónica, Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador Paúl Ayala Departamento de Eléctrica y Electrónica, Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador Hilde Breesch Department of Civil Engineering, KU Leuven, Construction Technology Cluster, Technology Campus Ghent, Sustainable Building, Ghent, Belgium Muhammad Burhan Water Desalination and Reuse Centre (WDRC), Biological and Environmental Science & Engineering (BESE), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia Silvia Coccolo Solar Energy and Building Physics Laboratory (LESO-PB), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland Frank De Troyer Faculty of Engineering Science, Department of Architecture, KU Leuven, Louvain, Belgium Ngo Hoang Ngoc Dung National University of Civil Engineering, Hanoi, Vietnam Pietro Florio Solar Energy and Building Physics Laboratory (LESO-PB), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

Editors and Contributors

xiii

Rodolfo Gordillo Departamento de Eléctrica y Electrónica, Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador Francesc Guinjoan Department of Electronics Engineering, Escuela Técnica Superior de Ingenieros de Telecomunicación de Barcelona, Universitat Politècnica de Catalunya, Barcelona, Spain Nguyen Trung Kien Vilandco Company. Hanoi, Hanoi, Vietnam Martin P. Marietta Department of Electronics Engineering, Escuela Técnica Superior de Ingenieros de Telecomunicación de Barcelona, Universitat Politècnica de Catalunya, Barcelona, Spain Luis Marroyo Department of Electrical and Electronics Engineering, Public University of Navarre (UPNa) Ediﬁcio de los Pinos, Pamplona, Spain Carmen-Pilar Martí-Ballester Universitat Autònoma de Barcelona, Bellaterra, Spain Dasaraden Mauree Solar Energy and Building Physics Laboratory (LESO-PB), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland Emilia Motoasca Faculty of Engineering Technology, Department of Electrical Engineering, KU Leuven Technology Campus Ghent, Ghent, Belgium Vahid M. Nik Division of Building Physics, Department of Building and Environmental Technology, Lund University, Lund, Sweden; Division of Building Technology, Department of Civil and Environmental Engineering, Chalmers University of Technology, Gothenburg, Sweden; Institute for Future Environments, Queensland University of Technology, Garden Point Campus, Brisbane, QLD, Australia Kim Choon Ng Water Desalination and Reuse Centre (WDRC), Biological and Environmental Science & Engineering (BESE), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia Quang Minh Nguyen National University of Civil Engineering, Hanoi, Vietnam Adedayo J. Ogungbile Department of Quantity Surveying, School of Environmental Technology, The Federal University of Technology, Akure, Nigeria Ayodeji E. Oke Faculty of Engineering and Built Environment, Department of Construction Management and Quantity Surveying, University of Johannesburg, Johannesburg, South Africa Wout Parys Building Physics Section, Department of Civil Engineering, KU Leuven, Heverlee, Belgium Julio Pascual Department of Electrical and Electronics Engineering, Public University of Navarre (UPNa) Ediﬁcio de los Pinos, Pamplona, Spain

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Editors and Contributors

A. T. D. Perera Solar Energy and Building Physics Laboratory (LESO-PB), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland J. Peuteman M-Group (Mechatronics), KU Leuven, Campus Bruges, Bruges, Belgium Delphine Ramon Faculty of Engineering Science, Department of Architecture, KU Leuven, Louvain, Belgium Dirk Saelens Building Physics Section, Department of Civil Engineering, KU Leuven, Heverlee, Belgium; EnergyVille, Genk, Belgium Pablo Sanchis Department of Electrical and Electronics Engineering, Public University of Navarre (UPNa) Ediﬁcio de los Pinos, Pamplona, Spain Jean-Louis Scartezzini Solar Energy and Building Physics Laboratory (LESO-PB), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland Muhammad Wakil Shahzad Water Desalination and Reuse Centre (WDRC), Biological and Environmental Science & Engineering (BESE), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia Alvin G. Stern AG STERN, LLC, Newton, MA, USA Damien Trigaux Department of Architecture, KU Leuven, Louvain, Belgium; EnergyVille, Genk, Belgium; VITO, Unit Smart Energy and Built Environment, Mol, Belgium Nicole P. M. van Lipzig Faculty of Science, Department of Earth and Environmental Sciences, KU Leuven, Louvain, Belgium Barbara Wauman Department of Civil Engineering, KU Leuven, Construction Technology Cluster, Technology Campus Ghent, Sustainable Building, Ghent, Belgium Hendrik Wouters Faculty of Bioscience Engineering, Department of Forest and Water Management, UGent, Ghent, Belgium

Introduction to Energy Sustainability

Abstract The European Union commits itself to develop a sustainable, competitive, secure and decarbonized energy system by 2050. This is not only a European but also a worldwide challenge included in the 17 Sustainable Development Goals of UN, like Goal 7 Ensure access to affordable, reliable, sustainable and modern energy for all, Goal 9 Build resilient infrastructure, promote sustainable industrialization and foster innovation, Goal 11 Make cities inclusive, safe, resilient and sustainable, Goal 12 Ensure sustainable consumption and production patterns and even Goal 13 Take urgent action to combat climate change and its impacts. Energy sustainability is more than restricting the energy use in industry, buildings and systems or the simple use of renewable energy sources. This calls for a multidisciplinary approach in various economic domains and at various scales. This book provides a holistic approach in terms of energy sustainability implementation, technologies and strategies. Keywords Energy efﬁciency • Sustainable energy production and storage Neighbourhood and buildings Meeting the energy efﬁciency (and sometimes the extra energy self-sufﬁciency) criteria is still a worldwide challenge in all applications (industry, buildings, consumer goods and services, etc.). Energy sustainability does not mean only reducing the energy use and using more energy produced from renewable energy sources of increasing the energy efﬁciency of processes and devices, but it implies insight and knowledge in various domains. The publication of this book has been motivated by an increased interaction among various disciplines (electrical, mechanical, construction and material engineering, economics, politics, etc.) in various economic domains (industry, constructions, etc.) and at various scales (worldwide, nationwide, neighbourhoods, buildings, devices) where newest developments in solar, wind and waste heat energy harvesting, hydrogen production and energy storage technologies are applied. Besides the scale level, each country deals with own geographic, economic, politic and legal particularities that influence the way some of the energy sustainability challenges are approached and coped with. Therefore, xv

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Introduction to Energy Sustainability

this book has a broad view and tackles a wide range of topics including energy sustainability implementation, technologies and strategies. Meanwhile, this book shows just a small selection of the multidisciplinary ﬁeld of energy sustainability. In the ﬁrst four chapters, bundled as Part I—Energy Sustainability Implementations, some aspects of the implementation at macro-scale (nation, city, neighbourhood, etc.) and at building scale related to energy sustainability are presented. Chapter 1 investigates the sustainable construction practices in West African countries in the context of recent challenges, drivers and implementation and application measures. The increasing interest in sustainable buildings has been driven by a strong increase among relevant stakeholders including clients, sponsors, construction professionals, government agencies and other concerned regulatory bodies. Chapter 2 studies the influence of urban planning in Belgium on the ﬁnancial and environmental impact of neighbourhoods using a combined life-cycle costing (LCC) and environmental life-cycle assessment (E-LCA). The results reveal substantial impact differences between different neighbourhoods, showing the importance of urban planning to decrease the ﬁnancial and environmental impact of the built environment. Chapter 3 makes a detailed SWOT analysis together with an extended discussion on the application of high-tech and low-tech designs for reaching the energy efﬁciency in residential buildings in Vietnam. Up-to-date carefully chosen data and examples are provided. Chapter 4 further discusses the speciﬁc situation of Vietnam, providing an overview of the actual design practice for ofﬁce buildings in Vietnam together with design recommendations for ofﬁce buildings to achieve high standards of the energy efﬁciency and indoor climate. In the next ﬁve chapters, grouped as Part II—Energy Sustainability Strategies, various energy sustainability strategies are described in relation to buildings, neighbourhoods, systems and energy markets. Chapter 5 focuses on the energy efﬁciency and sustainability on the urban scale and elaborates how to develop a computational platform combining future climate conditions, assessment of energy demand of a building stock and design and assessment of urban energy systems. Chapter 6 also considers the importance of accounting for climate changes, more speciﬁcally in dynamic building energy simulations. This issue is clearly needed when looking for sustainable buildings as buildings have a relatively long lifespan. The chapter discusses widely used methods to predict future weather data and provides an overview of available weather data sets for building simulations. Another essential aspect to achieve energy sustainability in buildings is the application of a reliable and accurate method for the energy use assessment of building designs. Chapter 7 assesses the accuracy of a simpliﬁed calculation method in ofﬁce and school buildings in Belgium by using integrated dynamic building and HVAC system simulations. The simpliﬁed approach as currently applied in the EPR calculation tool in Flanders is shown to be suited for the calculation of the ﬁnal energy use, despite the uncertainties and restrictions of the investigated simulation model. Chapter 8 discusses a fuzzy-based approach to design control strategies for microgrids, where the residential grid-connected microgrids (MGs) that comprise renewable generation and storing capability are constrained to grid operator requirements which include a smooth and bounded grid power proﬁle. Chapter 9

Introduction to Energy Sustainability

xvii

ends Part II with an analysis of the effectiveness of ﬁnancial instruments to invest in renewable energy on the Spanish market. The ﬁnancial performance of various alternative energy mutual funds is compared to conventional market benchmarks. In the last ﬁve chapters, grouped as Part III—Energy Sustainability Technologies, various technologies related to sustainable energy production, use and storage are considered. Chapter 10 provides a detailed overview of basic concepts related to wind energy: energy calculations, design methodology, construction and electrical power generation using wind turbines. Chapter 11 presents the newest developments and challenges related to the use of thermoelectric materials for waste heat recovery in various applications. Thermoelectric generators based on thermoelectric materials have the capability of converting heat energy into electric energy and therefore have an immense potential to increase the energy efﬁciency of various processes and devices. Chapter 12 discusses a sustainable approach for cooling needs using concentrated photovoltaic (CPV) in combination with mechanical vapour compression (MVC) and adsorption chillers. The thermal energy recovered from the cooling of CPV system is used in the absorption chillers, and this leads to a strong increase of the system efﬁciency. Chapter 13 describes an economical, novel method for implementing a complete hydrogen fuel clean energy cycle based on the chemical reaction between salinated (sea) or desalinated (fresh) water and sodium metal with the use of a novel, molten salt electrolytic cell designed to perform electrolysis at a temperature range between 950 °C and 1050 °C. Chapter 14 concludes Part III with a discussion of the use of renewable energy storage at KAUST desalination plant pilot to increase the solar-driven desalination capacity. The topics are organized into three different sections: (i) energy sustainability implementation, (ii) energy sustainability strategies and (iii) energy sustainability technologies. Speciﬁc topics covered in this book include: • Sustainable construction practices in West African countries, • Influence of urban planning on the ﬁnancial and environmental impact of neighbourhoods, • Energy efﬁciency in urban residential buildings in Vietnam, • Recommendations for the design of ofﬁce buildings in Vietnam, • Computational platform linking neighbourhoods to sustainable energy systems, • Future weather data for dynamic building energy simulations, • Simpliﬁed method to assess heating energy use in non-residential buildings, • Microgrid energy management strategies, • Financial instruments to invest in renewable energy in Spanish market, • Overview of basic concepts related to wind energy, • Newest developments and challenges related to thermoelectric materials for waste heat recovery, • Concentrated photovoltaic thermal (CPVT) system for cooling, • Novel method for implementing a complete hydrogen fuel clean energy cycle, • Application of renewable energy storage for desalination.

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Introduction to Energy Sustainability

To summarize, this book contains information about energy sustainability implementation at macro-scale (nation, city, neighbourhood) and building scale, energy sustainability strategies in relation to buildings, neighbourhoods, systems and energy markets and sustainable energy production, use and storage technologies. We sincerely hope that you will enjoy its content! Emilia Motoasca Avinash Kumar Agarwal Hilde Breesch

Part I

Energy Sustainability Implementation

Chapter 1

Sustainable Construction Practices in West African Countries Adedayo J. Ogungbile

and Ayodeji E. Oke

Abstract The quest for sustainable construction practices has been on the increase among relevant stakeholders including clients, sponsors, construction professionals, government agencies and other concerned regulatory bodies. This article examines the level of practice of sustainable development goals in the West African countries’ construction industry with an emphasis on the challenges, drivers and possible measures for improving its implementation and application. Various gaps and neglected issues in sustainable construction in the region were also reviewed to providing necessary information for the expansion of knowledge of relevant stakeholders and ensuring that construction projects are delivered to international standards. Keywords Green economy

1.1

Sustainable development West Africa

Introduction

West Africa is a region on the African continent that experiences developmental activities year in, year out and the type of developments encountered in the area can, however, cannot compete with that obtained in other parts of the word (Adebayo and Adebayo 2000). An overview of developmental standard in place in the West African region and that in the advanced world can be said to be one of the reasons why most countries in the area are classiﬁed as developing countries (Du Plessis 2002). One of the Millennium Development Goals, as seen in the Cities A. J. Ogungbile (&) Department of Quantity Surveying, School of Environmental Technology, The Federal University of Technology, P.M.B. 704, Akure, Nigeria e-mail: [email protected] A. E. Oke Faculty of Engineering and Built Environment, Department of Construction Management and Quantity Surveying, University of Johannesburg, Johannesburg 2028, South Africa e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 E. Motoasca et al. (eds.), Energy Sustainability in Built and Urban Environments, Energy, Environment, and Sustainability, https://doi.org/10.1007/978-981-13-3284-5_1

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A. J. Ogungbile and A. E. Oke

Without Slums initiative, targeted that by the year 2020, more than 100 million slum dwellers would have been signiﬁcantly touched for the good by improving their standard of living through the provision of improved sanitation, clean water and primary health care services. In ensuring that these goals are achieved in West Africa, more developmental initiatives are created, and apparently, the built environment sits as the driver of the whole efforts. Du Plessis (2007) averred that the type of built environment put in place coupled with the nature of its creation will in great ways determine the level of achievement that will be realized by the objectives of the developmental initiatives of the MDGs. Sustainable development strategies are unique (Moon 2013). Every country that has embraced sustainable development has strategies for its operation. There is no agreed strategy to sustainable development. Every country fashioned out strategy that ﬁt into the construction industry and prevailing factors surrounding construction operation of the industry. Sustainable development strategy reflects the priorities and concern of each country (Oke and Aigavboa 2017). The strategies are born out of challenges facing construction operations in the countries. The challenges are indentiﬁed alongside with measures to militating or overcoming them. Major factors to be considered in sustainable development strategy are reflection of local value, the involvement of all stakeholders in the community and acceptance of citizen with high sense of ownership. The dire need for a sound and an ever-growing development in physical infrastructure and the built environment in developing countries around the world (West Africa inclusive) needs to be addressed in an economical and more socially responsible way than what used to be the case in time past in order to ensure that they stand the test of time (Du Plessis 2007). Du Plessis (2007) claimed that the emerging nature of the built industry in the region creates an excellent opportunity to make interventions on sustainability in developments now. Considering the continued rapid rural–urban migration happening in developing countries and the increased rate of infrastructural development as a result of the MDGs intervention, the need for the introduction of sustainable construction, however, cannot be delayed further.

1.2

Sustainable Construction

Du Plessis (2002) averred that virtually all sectors of the society have continually been pursuing and interpreting sustainable development and sustainability in their comprehensive framework arising from the adoption and formulation of the Agenda 21 as a blueprint for sustainable development in the 1992 Rio Earth summit. The construction industry is not left out in keying to the sustainable trend as obtained in other works of life (Ogungbile and Oke 2015). Bond and Perrett (2012) averred that water, energy, materials, and land are the vast amounts of resources on which the built environment flourishes. Chances of reducing destruction to the environment keep resurfacing from inception to completion of the whole process. Sustainable

1 Sustainable Construction Practices in West African Countries

5

development as often described by many requires a long-term and joint outlook by the society which integrates environmental, economic and social objectives (Dearing 2010). Cook et al. (2012) argued that respect for human values and opportunity are the basis on which organizing framework of sustainable development is offered. A wide range of organizational responses to sustainability is evident (Du Plessis 2007). Du Plessis (2007) adduced that while some organizations’ responses could be seen as being pragmatic, some others respond by seeing sustainable development as a vision. Du Plessis (2007) submitted that meeting human values and needs in different ways constitute innovation and sustainable development is all about innovation. Accommodating sustainable development to processes of reinventing business would not result in the desired output as compared to having a clear line of direction supported by right metrics, management backing and adequate resources. Whichever the preferred approach is, innovation has always emanated from being presented with (or continuous presenting) a credible tactical dilemma which can be ﬁxed by creating utterly new approaches. The innovative response of sustainable construction is particularly characterized by its eco-efﬁciency nature. The goal of sustainable construction is targeted towards maintaining the natural balance of the environment and at the same time innovating new approaches to construction. In achieving Eco-efﬁciency, possible ways of eradicating impact right from the origin were targeted as the best response to environmental impact rather than reducing the obvious impact (Dearing 2010). Du Plessis (2007) similarly suggested that assessing sustainability from obligations and cost would give no future to sustainable development. Continuous assessment in this way would only lead to being caught in the commodity trap (Du Plessis 2007). Provision for long-term proﬁtability and growth by sustainable development is needed to become a successful and integral part of business philosophy. However, sustainable construction could have various meanings to the different parties involved in the construction process. These parties are the constructor or the contractor, the clients and the designers. For a client, sustainable construction could mean an improved corporate relationship image with the locals. The positioning of the clients near to the top of the supply chain in construction place them in playing an important role in delivering more sustainable construction. In recent years, forward-looking clients have continuously asked construction companies and design teams for the construction of more sustainable projects (Dearing 2010). Moreover, for clients, sustainability could mean lower life-cycle costs (construction and future maintenance costs) relating to their project when issues of energy efﬁciency are concerned (Häkkinen and Belloni 2011). A reduced energy bill can be an example of the energy efﬁciency feature of sustainable construction (Häkkinen and Belloni 2011). Also, it could signify to a client a better relationship with host communities, i.e. remodel the construction process to be more efﬁcient by involving the local communities more in the whole process; making them an integral part of the project decision-making groups. UNRISD (2013) submitted that the involvement of the local communities in the construction process brings to the process massive beneﬁts such as a smoother planning process devoid of rancour

6

A. J. Ogungbile and A. E. Oke

and enhanced reputation of the project contributors. According to UNRISD (2013), healthy and pleasant environment, economy and time savings are brought about by having a more robust trust, respect and dialogue between the various participants of the construction team including the clients and the local communities. This, in turn, will improve staff retention and productivity in the construction process as a result of having a productive working environment. To the same client, sustainable construction could also be termed to be a reduction in environmental impact through both construction and operation. However, to a constructor, sustainability could be interpreted to mean various meanings to differ from that of the client. It could mean a way to better satisfy the client by getting the best solution for relating with designers, suppliers and even the client (UNRISD 2012). It could also mean creating a better reputation with the host community of the project and the constituted authority in such an area by enhancing positive relationship through social responsibilities and conflict avoidance mechanism put in place by the contractor. Also, to the constructor, the most important meaning that could be read of sustainable as a reduction of cost and wastage. It could also signify a reduction in legal action, risk reduction and better use of resources efﬁciently, improved health and safety and better communication. Sustainable construction has been adjudged to have some compelling advantages some of which are improved well-being; valuable operational costs of sustainable construction; productivity of users and occupants due to improved project performance (Häkkinen and Belloni 2011); use of natural resources and reduced environmental impact as a result of reduced emissions leading to a long-term national economic beneﬁts (Du Plessis 2007).

1.3

Challenges and Barriers to Sustainable Construction in West Africa

All over the world, the face and nature of construction industry keep changing from time-to-time. This is as a result of the continued interest in improving the ways things are being done, and construction projects are being procured, executed and delivered to suit the demanding nature of the ever-changing environment. However, the trend faces some salient and compelling challenges to its success story. Some of these challenges are as follows.

1.3.1

Resistance to New Technologies

In the West African construction industry, one of the major hindrances to achieving a sustainable environment regarding adoption of the sustainable practices as applied in other developed regions of the world is resistance to new technologies (Adebayo

1 Sustainable Construction Practices in West African Countries

7

and Adebayo 2000). Sustainable construction is driven by adherence to new technological systems and procedures. These new technologies are alien to the construction system on the ground in the West African, and this is posing a lot of difﬁculties to the acceptance and of course, the development of sustainability construction environment in the region. Sustainable construction entails an overhaul process change, and it requires new perception to analysing unforeseen costs and possible risks (Häkkinen and Belloni 2011). Learning ways of networking, roles, actors, new tasks and decision-making phases are needed to create new efﬁcient processes for reducing and overcoming these hindrances. Furthermore, Häkkinen and Belloni (2011) stated further that construction clients need to be more educated about the beneﬁts of sustainable construction to enhance their existing knowledge.

1.3.2

Rules of Competition and Tendering Processes

For every process change, there should be a new rule to the game that guides the process. The case is different in the West African construction industry in general. This is perceived in the way construction tendering activities, and procurement is done. Bidding processes still follow the old methods of conventional tendering which is created a limitation to the thriving of sustainable construction in the region.

1.3.3

Lack of Functioning Value Chains

A value chain is a set of activities that a ﬁrm operating in a speciﬁc industry performs to deliver a valuable product or service to the market. In the construction industry, value chain can be the activities that precede construction, done during project execution and also, the post-construction activities expected to be carried out by contractors, consultants, clients and other parties to construction projects to ensure rational acceptability in the market (the built environment). Despite the emerging advocacy for the need for accepting sustainability in the construction industry, the West African region has lagged in the acceptance because of the poor functioning value chain. Until the value chain in the region is improved upon, sustainable construction in the region will continue to be limited in scope and acceptability in the market, and this possesses a massive challenge to the attainment of a sustainable environment in the region.

1.3.4

Possibilities to Apply Integrated Design Team

Sustainable construction is about ideas. It entails more than the usual architectural, structural and aesthetic designs as obtained in the conventional construction as we

8

A. J. Ogungbile and A. E. Oke

are used to. It is majorly teamwork as no one can claim to be an island when it comes to sustainable development. The failure of professionals to work in team continues to be a signiﬁcant challenge to the proper establishment of sustainable concept in the African region (Du Plessis 2007). Majority of the designs are imported ideas from different continents of the world which, in most cases, might not be suitable for adoption in the African region. Häkkinen and Belloni (2011) emphasized that sustainable construction ideas require full adherence to details. This full adherence may not be achieved when working with imported designs. Therefore, a need for a holistic review of the nature of collaboration exists between construction professionals in the region.

1.3.5

Lack of Demand

The nature of the complexity involved in sustainable construction naturally makes it more expensive to procure when compared to the conventional construction system (Bond and Perrett 2012). Due to this costly nature and the ﬁnancial peculiarity of the West African region, there seemed to be a lack of demand on the part of the government who are the largest clienteles of the construction industry. In the UK, only 40% of construction products are owned by the public sector, a contrast of which is obtained in the African region where a considerable percentage of construction activities are owned, ﬁnanced and managed by the government. This needs to be improved upon to ensure that more interest come from the private sector regarding ﬁnancing and ownership of construction activities. Until this is achieved, the demand for sustainable construction would still experience low patronage. The challenges faced by sustainable construction in the West African region are inexhaustible. Some others are lack of adequate knowledge on the part of the constructors, inadequate workforce in handling the new technologies, poor sustainable-focused research, poor marketing process of sustainable construction and so many more.

1.4

Drivers and Enablers of Sustainable Construction in West Africa

Adebayo and Adebayo (2000) alleged that even with the importance of sustainable construction and its contribution to the economy, it had received low attention in Africa. In 2009, The United Nations Environment Programme’s (UNEP) vision for Sustainability in the Building and Construction Sector states that SB is an active process where policies and incentives provided by the government support SB and construction practices, where investors, insurance companies, property developers and buyers/tenants of buildings are aware of sustainability considerations and take

1 Sustainable Construction Practices in West African Countries

9

active roles in encouraging SB and construction practice. The trend has continued in recent years to further preach the need for a sustainable development mentality growth in all parts of the world. Some of the divers of this movement are majorly convened in the advantages that could be derived from the implementation of the sustainable development in the construction industry. The following are some of the beneﬁts of sustainable construction as obtained in advance world where sustainability practice is well established: • Water and energy utility cost savings; • Due to greater occupancy and higher rents in sustainable certiﬁed buildings, there is increased Net Operating Income (NOI) leading to higher value ratings of the buildings; • Reduction in cost of maintenance; and • There is an enhancement in occupiers’ productivity level because of the controlled environment and improved health of the tenants. In furtherance of the above listed, Bond and Perrett (2012) gave some other key drivers of sustainable construction to include; • Demonstration of commitment to sustainability and environmental stewardship; • Recruitment and retention of key employees by the sustainable development actors (which could consist of the clients, contractors, developers, etc.); • Public relation beneﬁts advocacy regarding societal sensitization, especially for managers, building owners, and developers; • Marketing beneﬁts, especially for developers and building owners; • Well-guided sustainable target setting; • Adequacy of sustainable design methods and knowledge; • Availability of proper procurement method that ﬁts into the sustainable plan; • Sufﬁcient monitoring mechanisms and procedures; and • State-of-the-art management practices after construction. All the above listed can be said of the West African region if sustainable thinking can be well accepted, established and harnessed by the governments of these nations who remain the largest policy maker and client of the individual construction industry in their countries.

1.5

Gaps and Neglected Issues in Sustainable Construction in West Africa

In recent years, the United Nations has been one of the principal champions for sustainable development. With the focus on the achievement of sustainable development outcomes, many UN agencies have researched into some other critical gaps that need to be looked into (Du Plessis 2002). In 2015, a historic accord was signed by more than 150 nations of the world including world giants (United States

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A. J. Ogungbile and A. E. Oke

of America, United Kingdom, China, Germany, France and Russia to mention but a few), in the capital city of France, Paris. The pact did not leave out the African contingents as all African countries were also duly represented in the meeting. The deal was named ‘The Paris Agreement’ and has continued to make wave ever since then. Although the United States led by Donald Trump has since pulled out of the agreement, the pact still maintains a full acceptance among the comity of nations. However how encompassing the deal is, the responsibilities lie in the hands of the individual countries of the world to fully comply with the agreements contained in the pact regarding implementation and to locally adopt it to the nature and tradition of her locals, to fully enjoy the beneﬁts of the treaty. In the West African region, it is essential that some areas be critically looked into to ensure full adoption and compliance with the Paris Pact. Until these areas are thoroughly looked into, and necessary machinery are put in place, sustainable construction may remain a thing too difﬁcult to achieve in the region. Some of the areas of the gap and neglects include the following.

1.5.1

Security of Lives and Properties

The sense of freedom from fear and want is deﬁned as Human security. It is characterized as ‘the protection to the vital core of all human lives in ways that enhance human freedoms and human fulﬁlment’ (UNRISD 2013). A sense of protection from danger is a critical tool in sustainable development, and this has for a while, being the advocacy of the UN in preaching for peace all over the world. In the West African region, the depth of human insecurity has been shown by the ongoing and recent multiple crises that have characterized the area in the international news space. Häkkinen and Belloni (2011) testiﬁed that this perceived lack of security reveals the extant inadequacy of structural and systemic reforms which has made an equitable development pathway and a socially inclusive environment challenging to achieve in the region. UNRISD (2013) reported that in the past six decades thereabout, signiﬁcant and substantial progress is being made in many parts of the world in reducing poverty and hardship. Also, it was written in the report that some parts of the world are however left far behind of this substantial progress owing to the presence of conflicts and repeated violent cycles leading to stagnated social indicators and compromise in economic developments. This scenario is being played out in many of West African nations as the lives and properties of citizens are in continued danger. The implication of this to sustainability is of the grave and strong impediments to the attraction of development to the region. A release by the World Bank in 2013 stated that over 1.5 billion people, almost a quarter of the total population of the world, inhabit in parts affected by violence, fragility and conflict, the majority of whom are located in the Asian and African continents (UNRISD 2013). Security concerns associated with these volatile areas have been proven to have large bearings on developmental activities in the regions

1 Sustainable Construction Practices in West African Countries

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(Dearing 2010). Expatriates are not encouraged to invest in the part because of the expensive nature of sustainable construction; it becomes highly not economically advisable to invest in an area of high-security tension and instability. Although, according to Adebayo and Adebayo (2000), there exists a substantial ignorance in the interrelation between development, justice and security in the approach of MDGs (which was claimed to be narrow in scope), the need to reposition human security as a focal of developmental strategies is increasingly gaining recognition. Progress at attaining SDGs is most likely to lag severely without the attention and ensuring security of lives and properties (Adebayo and Adebayo 2000). In furtherance to this, the issue of security is becoming as important as environmental sustainability, social inclusion and economic development in the post-2015 development framework as the concept of sustainable development are being broadened to include more variables (UNRISD 2013). At the centre stage of social policy lies human security. They help in combating social exclusion and in reinforcing social cohesion as more is put into investing and preserving human capital. Du Plessis (2002) held that a number of means could be provided in addressing issues that concern security through various measures of social protection instruments and social policies. This can also be achieved with the enforcement of law and order, ensuring political stability as well as regulation of the labour market. For a country to keep coherent national responses to natural disasters, crises and shocks, as well as ensuring adequate monitoring and reduction of poverty and inequality levels, social security systems are critical Du Plessis (2002). The practice of social security, respect for lives and properties are generally lagging as government apparatus are incapable of achieving these lofty heights as obtained in other parts of the world. For sustainable development to be the order of the day in the West African region, it is necessary that the security of lives and properties of her inhabitants, visitors and expatriates working in the area is well guaranteed to attract sustainable new technologies and investments.

1.5.2

Culture

Culture, considered as ‘the set of distinctive spiritual, material, intellectual and emotional features of a society or a social group’. Culture can be viewed in a broad sense as a critical reflection in deﬁning the constitutive elements of dignity, well-being and sustainable development (Hayashi et al. 2012). Young (1999) acknowledges the exclusion of culture from the MDGs. However, culture as a signiﬁcant role as it is critical to environmental, economic and social impacts of sustainable development (Young 1999). There existed a missing agreement and shared recognition of culture in the core developmental strategies at global, regional and even local levels in spite of the increasing awareness of the signiﬁcance of culture in development (UNRISD 2013). A study done by UNESCO in 2010 showed that cultural assets are one of the fastest growing sectors of many economies Hayashi et al. (2012), which underlines the importance of culture to the

12

A. J. Ogungbile and A. E. Oke

growth of any economy. In developing countries, like West Africa, where there is abundance substantial labour force, cultural and natural resources, sustainable tourism, creative industries as well as cultural infrastructures and heritage can be pivotal to generating revenues. Culture is held esteemed as it ensures the acknowledgement of indigenous people and minorities, most marginalized groups, in creating a conducive, resilient, stable and more inclusive society (Hayashi et al. 2012). Hayashi et al. (2012) averred that promoting support and respect for cultural expressions can pave the way to consolidating the social capital of a community and foster conﬁdence in public establishments. In promoting more productive patterns and sustainable consumption, traditional and cultural activities are very vital. This can be broadly deployed in tackling ecological challenges. Cultural heritage rehabilitation has been used in various post-conflict situations in helping concerned communities rebuild their lost identities and reclaim their lost common interests. Culture is germane in ensuring sustainable and inclusive development by making proactive policies that institutionalize cultural heritage and promote intercultural dialogue. Sustainable development according to UNRISD (2013) should be deeply founded on the involvements of participation of marginalized groups and knowledge of local context. Interpretively, the way of life and the beliefs of the locals should form the basis of any development strategies if it is going to be sustainable. Development or construction that fails to recognize, promote and ensure the continued protection of the cultural heritage of the people has failed the sustainability test even before inception. The cumulative experiences of countries where cultural diversity is a fundamental attribute of society have shown a wide array of policy approaches and all of them represent instances where accommodation of diversity has been a central aspect of government. Apparently, African countries especially the ones in the West have been recognized on the world stage to be rich in culture and traditions. The government of these nations have got a lot to do to preserve her dynamic culture by incorporating any sustainable development plan they have not just to ﬁt into the existing culture of their people but also to complements them. By so doing, sustainable construction and development as a whole would be accepted by the people who are essential drivers of any sustainable endeavour.

1.5.3

Technology

In the sustainable development agenda plans, Moon (2013) attested that there had been increased advocacy for technology as it is an important element in achieving its goals. The term technology includes information and communication technology (ICT) and the process of technology transfer from one sector to another. The global economy is observed to be deepened through the integration of the rapid change in technology, most especially, in ICTs. This trend has provided a means of

1 Sustainable Construction Practices in West African Countries

13

decoupling resource use from growth and creating a new opportunity for the developing countries to join the international production network (SDSN 2013). As to this end, the vital role of technology in the transition process to sustainable consumption and production cannot be overemphasized. In advanced counties of the World, technological innovations have been deployed to improving primary infrastructural development, education, healthcare and general public service deliveries. Even in migration processes, technology has been consistently used to keep things in check. Migrants are enabled to maintain ties with their homelands and making it easy for people to migrate with greater frequency over longer distances (UNRISD 2013). Also, in new media, in reducing corruption, broadening participation, ensuring accountability of public institutions, technology has been helpful (Moon 2013). The importance of technology, especially ICT to all aspects of life in this changing world cannot be underplayed. In spite of the growing trend and contribution of ICT, the African continent as a whole has struggled to meet up with the dynamic movement of the technological world. This failure to meet up with the ICT advancements is a problem to the achievement of sustainable development in the region. In improving access to technologically provided opportunities, it is important to make sure that technological changes are directed to more equitable and sustainable outcomes, particularly in developing countries such as the West African region. It is important to note that the construction industry of the nations of the West African region needs to embrace the technological advances obtained in developed countries by making room for flexibilities in design, execution and monitoring of construction projects.

1.5.4

Green and Fair Economy

In recent years, green economy to a large extent has been at the centre of more of the contemporary efforts to promote sustainable development. Fairhead et al. (2012) opined that a lot of issues had been highlighted by viewing the green economy through a social lens that is infrequently recognized in policy circles. Studies have shown that a win-win assumption about the green economy has taken attention and of which have continued to gather criticism as to its reliability. This has continued to raise serious questioning (Fairhead et al. 2012). It is however suggested that strategies impact social groups and green economy initiatives differently can result in winners and losers’ situation. Schemes and incentives associated with payments for environmental services (PES), monetary pricing and market-based allocation of ecological assets and biofuels often beneﬁt or target the better-off, redistribute assets upwards and favour people and places with the highest purchasing power (UNRISD 2012). Cook et al. (2012) averred that green grabbing which is an extension of land grabbing, a scenario where natural and resources are appropriated for environmental ends. Such ﬁndings suggest that importance must be placed on issues of the green and fair economy to ensure an economic transition that curtails tensions between the

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A. J. Ogungbile and A. E. Oke

environment and economic development. In achieving this, social drivers associated with the community-based development and social policies are put in place. This will ensure more equitability by the government to the people directly affected by the life impacts of the project. In this century, people/host communities have their voices heard. Whereas in this part of the world, the same cannot be said of that feet. For construction to be sustainable, the locals must give the go-ahead before the project commences as they directly involved in the milestone decision-making for the community.

1.6

Conclusion and Recommendation

Sustainable construction is one of the signiﬁcant topical trends in world discuss that is fast becoming a way of life in most of the advanced countries of the world. However, same cannot be said of the West Africa region, and with extension, the African continent as a whole as construction still follows the conventional methods. Apparently, for the region to gain international recognition it deserves and she craves for, efforts need to be made towards full adoption of sustainable development goals in the region and the African continent as an extension.

References Adebayo AA, Adebayo P (2000) Sustainable housing policy and practice-reducing constraints and expanding horizons within housing delivery. In: Paper presented in 2nd South African Conference on sustainable development in the built environment, Pretoria, South Africa Bond S, Perrett G (2012) The key drivers and barriers to the sustainable development of commercial property in New Zealand. J Sustain Real Estate 48–77 Cook S, Utting P, Smith K (2012) Green economy or green society? In: Contestation and policies for a fair transition, occasional paper 10 Dearing A (2010) Sustainable innovation: drivers and barriers. United Nations, Geneva Du Plessis C (2002) Agenda 21 for sustainable construction in developing countries. In: Pretoria: a discussion document, report for CIB and UNEP–IETC (2002) Du Plessis C (2007) Agenda 21 for sustainable construction in developing countries. CSIR, Pretoria Fairhead J, Leach M, Scoones I (2012) Green grabbing: a new appropriation of nature? J Peasant Stud 39(2):237–261 Häkkinen T, Belloni K (2011) Barriers and drivers for sustainable building. Build Res Inf 39 (3):239–255 Hayashi N, Boccardi G, Hassan NA (2012) Culture in the post-2015 sustainable development agenda: why culture is key to sustainable development. Background note for UNESCO’s high-level discussion on culture in the post-2015 sustainable development agenda Moon B (2013) For the role of technology in sustainable development see United Nations technical support team issues brief conceptual issues. In: New York: report of the secretary-general science, technology and innovation, and the potential of culture, for promoting sustainable development and achieving the millennium development goals for ECOSOC’s 2013 annual ministerial review

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Ogungbile AJ, Oke AE (2015) Sustainable facility management practices in public buildings in Nigeria. In: Ogunsemi DR, Awodele OA, Oke A (eds) Confluence of research, theory and practice in quantity surveying profession for a sustainable built environment. The Nigerian Institute of Quantity Surveyors, Akure, pp 830–843 Oke AE, Aigavboa CO (2017) Sustainable value management for construction projects. Springer, Switzerland SDSN (2013) An action agenda for sustainable development. In: New York: report for the secretary-general, prepared by the leadership council of the sustainable development solutions network UNRISD (2013) Emerging issues: social drivers of sustainable development. United Nations Research Institute for Social Development, New York UNRISD (2012) Social dimensions of green economy. Res Policy Brief 12 Young C (1999) The accommodation of cultural diversity: case studies. Palgrave Macmillan, UNIRSD

Chapter 2

Modelling the Influence of Urban Planning on the Financial and Environmental Impact of Neighbourhoods Damien Trigaux , Karen Allacker

and Frank De Troyer

Abstract Urban planning decisions related to the urban form, built density and neighbourhood location may affect the sustainability of neighbourhoods to an important extent. This chapter investigates the influence of urban planning on the ﬁnancial and environmental impact of neighbourhoods. A number of schematic neighbourhood models with various layouts and built densities are analysed using an integrated life cycle approach, combining Life Cycle Costing (LCC) and Environmental Life Cycle Assessment (E-LCA). Furthermore, the influence of the neighbourhood location is assessed by comparing the impact of a rural and urban location. The results reveal substantial impact differences (up to 20–25%) between the neighbourhoods, showing the importance of good urban planning to decrease the ﬁnancial and environmental impact of the built environment. The main reasons for these variations are the lower primary land use, lower energy use for heating and lower material use in high built-density neighbourhoods and compact buildings. Also, the neighbourhood location proved to be a key parameter to decrease the impact of user transport in neighbourhoods, with impact reductions up to 25–30% in an urban area.

Keywords Integrated life cycle approach Life cycle costing Environmental life cycle assessment Neighbourhood layout Building design

D. Trigaux (&) K. Allacker F. De Troyer Department of Architecture, KU Leuven, Kasteelpark Arenberg 1/2431, 3001 Louvain, Belgium e-mail: [email protected] D. Trigaux EnergyVille, Thor Park 8310, 3600 Genk, Belgium D. Trigaux VITO, Unit Smart Energy and Built Environment, Boeretang 200, 2400 Mol, Belgium © Springer Nature Singapore Pte Ltd. 2019 E. Motoasca et al. (eds.), Energy Sustainability in Built and Urban Environments, Energy, Environment, and Sustainability, https://doi.org/10.1007/978-981-13-3284-5_2

17

18

2.1

D. Trigaux et al.

Introduction

The higher scale of the built environment has become an important focus in sustainable decision-making. Urban sprawl, which characterizes the Belgian building stock, has a major impact on required infrastructure, energy use, land use and transport (European Environment Agency 2006). In order to move towards a sustainable built environment, neighbourhoods need to be planned differently, focussing not only on the characteristics of individual buildings but also on the urban layout, built density and relations between buildings and their surroundings. Various studies focused on the urban morphology and its impact on energy consumption in buildings, considering aspects such as building compactness, solar gains, access to daylight and natural ventilation (Ratti et al. 2005; Salat 2009). Compared to these studies, this chapter analyses the influence of urban planning in a wider sustainability perspective, including both the life cycle ﬁnancial and environmental impacts of neighbourhoods. In addition to operational energy use, impacts related to material use, operational water use, neighbourhood land use and user transport are considered. More speciﬁcally, the focus of this research is on the assessment of newly built residential neighbourhoods in the Belgian context. Effects of urban planning decisions related to the urban form, built density and the neighbourhood location are analysed. To investigate these effects, a number of schematic neighbourhood models with various layouts and built densities are assessed, using an integrated life cycle approach, combining Life Cycle Costing (LCC) and Environmental Life Cycle Assessment (E-LCA). Furthermore, a comparison is made between a rural and urban location to gain insight in the influence of the neighbourhood location. The methods and results presented in this chapter are part of a doctoral research on the elaboration of a sustainability assessment method for neighbourhoods (Trigaux 2017). The methods are described in Sect. 2.2 and the results of the analysed neighbourhood models are discussed in Sect. 2.3. Conclusions are formulated in the ﬁnal section.

2.2 2.2.1

Methods Integrated Life Cycle Approach

The ﬁnancial and environmental impact of the neighbourhood models are assessed based on an integrated life cycle approach, combining Life Cycle Costing (LCC) and Environmental Life Cycle Assessment (E-LCA). This integrated approach was originally developed in the context of the SuFiQuaD research project (‘Sustainability, Financial and Quality evaluation of Dwelling Types’) (Allacker 2010; Allacker et al. 2013a) and has been extended from the building to the neighbourhood scale level (Trigaux 2017).

2 Modelling the Influence of Urban Planning on the Financial …

19

The ﬁnancial and environmental impacts are assessed over the entire neighbourhood life cycle, considering a lifespan of 60 years (Trigaux 2017). In accordance with the European standards related to the sustainability of construction works (CEN 2010, 2011, 2015), the life cycle of a neighbourhood is divided into three main stages: the before use stage, use stage and End-Of-Life (EOL) stage. The before use stage covers all processes prior to the use of the neighbourhood, i.e. pre-construction (including land purchase and transformation), production of building materials (including raw material extraction, transport to the manufacture and manufacturing), transport to the construction site and construction activities. The use stage includes processes related to maintenance, replacement of building components, operational energy and water use, land occupation and user transport. Finally, the EOL stage covers the demolition activities, waste transport, waste processing and disposal. A detailed description of the life cycle stages and system boundaries can be found in Trigaux (2017).

2.2.1.1

Life Cycle Costing (LCC)

The ﬁnancial costs during the various life cycle stages are considered in the LCC approach. These include the investment cost, the cost during the use stage and the cost at the end of life. A detailed description of the LCC method used can be found in Trigaux (2017), Allacker (2010), and Allacker et al. (2013a). The ﬁnancial data are collected from various sources. The cost of building elements is mainly based on the Belgian database ASPEN (2015a, b), combined with product speciﬁc data. For the neighbourhood infrastructure, the British Spon’s Price Books (Spon press 2015a, b) are used as a Belgian cost database is lacking. Energy, water and building land prices are based on Belgian statistical data (CREG 2015; Belgian Federal Government 2017a, b; VMM 2015). Concerning the ﬁnancial cost of user transport, a study of Transport and Mobility Leuven is used, including the calculation of consumer prices for different transport modes (Delhaye et al. 2010, 2017). The life cycle ﬁnancial cost is calculated as the sum of the present values (for the reference year 2015) of all costs occurring during the neighbourhood life cycle. The economic parameters—in real terms—are based on Belgian statistical data and are summarized in Table 2.1 (left column).

2.2.1.2

Environmental Life Cycle Assessment (E-LCA)

The environmental impacts generated during the whole lifespan of the neighbourhood are assessed using the E-LCA approach. The assessment is based on the E-LCA method developed within the MMG research project (‘Environmental proﬁle of building elements’), commissioned by the Public Waste Agency of Flanders (Allacker et al. 2013b; De Nocker and Debacker 2015). The MMG method is an update of the E-LCA method developed in the SuFiQuaD project, in

20

D. Trigaux et al.

Table 2.1 Economic parameters applied for the ﬁnancial and environmental costs (real rates above the inflation) (Trigaux 2017) Real Real Real Real

discount rate growth rate material and water growth rate labour growth rate energy

Financial costs (%)

Environmental costs (%)

2 0 1 2

0 0 – 0

order to be in line with recent E-LCA standards and guidelines in Europe (CEN 2011, 2013; EC-JRC 2011). Concerning the Life Cycle Inventory (LCI), the Swiss Ecoinvent database (version 2.2) is used to collect the input–output flows related to the building materials and processes which are required for the environmental impact assessment (Frischknecht et al. 2007). Preference is given to Western European processes to ensure the representativeness for the Belgian context. When generic Western European processes are lacking, Swiss data records are adapted by replacing the Swiss electricity mix and transport processes by corresponding European processes (Allacker et al. 2013b). Regarding the selected environmental indicators, the impact categories in the MMG E-LCA method include the ones deﬁned by the EN 15804+A1 standard (CEN 2013), which are further referred to as CEN indicators (Table 2.2). In addition, seven more impact categories are considered based on the International Reference Life Cycle Data System (ILCD) Handbook (EC-JRC 2011). The additional impact categories are further referred to as CEN+ indicators (Table 2.3). In addition to the individual environmental impact indicators, the MMG method provides an aggregated single-score indicator, expressed in a monetary value (EURO). This aggregated score indicates the external environmental cost, i.e. the cost to avoid, reduce or compensate the damage caused by environmental impacts to a given level considered to be sustainable. The environmental cost is calculated by multiplying the environmental impact indicator values with their speciﬁc monetary value and adding these up to obtain the overall environmental cost (single score). The background for the determination of the monetary values is described in (De Nocker and Debacker 2015). In this research, the MMG monetary values of the central scenario for Western Europe are selected for the E-LCA calculations (Tables 2.2 and 2.3). Compared to other weighting methods, the advantage of expressing environmental impacts in monetary values is the possibility to internalize environmental externalities by calculating the sum of the ﬁnancial and environmental costs. In contradiction to the ﬁnancial cost calculations, no discounting of future environmental costs is applied. A real growth rate and discount rate of 0% are used so that future environmental costs are equally valued as present environmental costs (see Table 2.1—right column). This approach is chosen in order to avoid burden shifting in time (Trigaux 2017).

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Table 2.2 CEN indicators and monetary values (central scenario) (De Nocker and Debacker 2015) CEN indicators

Unit

Monetary value (€/unit)

Global warming Ozone depletion Acidiﬁcation of soil and water Eutrophication Photochemical ozone creation Depletion of abiotic resources—elements Depletion of abiotic resources—fossil fuels

kg CO2 equiv. kg CFC-11 equiv. kg SO2 equiv. kg (PO4) 3-equiv. kg ethene equiv. kg Sb equiv. MJ, net caloric value

0.1 49.1 0.43 20 0.48 1.56 0

Table 2.3 CEN+ indicators and monetary values (central scenario) (De Nocker and Debacker 2015) CEN+ indicators

Unit

Monetary value (€/unit)

Human toxicity—cancer effects Human toxicity—non-cancer effects Particulate matter Ionizing radiation—human health Ionizing radiation—ecosystems Ecotoxicity—freshwater Water scarcity Land occupation—soil organic matter Land occupation—biodiversity Urban Agricultural Forest Land transformation—soil organic matter Land transformation—biodiversity

CTUh CTUh kg PM2,5 equiv. kg U235 equiv. CTUe (per kBq) CTUe m3 water equiv. kg C deﬁcit

665,109 144,081 34 9.7E−04 3.7E−05 3.7E−05 0.067 2.7E−06

m2a m2a m2a kg C deﬁcit m2

0.3 6.0E−03 2.2E−04 2.7E−06 Not available

2.2.2

Element Method for Cost Control

Due to the complexity of neighbourhoods, a well-structured evaluation is required to deal with the huge amount of data. In the SuFiQuaD method, the assessment structure is based on the element method for cost control (Allacker 2010). The basic principle is the hierarchical subdivision of buildings into building elements, such as external walls, roofs and technical services. These building elements can then again be subdivided into several work sections which are composed of one or more building materials (Fig. 2.1). In consequence, an analysis can be made at various scale levels, each higher level building on the lower levels. The following levels are considered: building

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Fig. 2.1 Element method for cost control and scale levels (Trigaux et al. 2014)

materials (e.g. brick, mortar, plaster), work sections (e.g. brickwork, plasterwork), building elements (e.g. external wall including ﬁnishes) and buildings. As deﬁned by Trigaux et al. (2014, 2017), the element method can be extended to evaluate neighbourhoods, which are deﬁned as a combination of buildings, networks (e.g. roads, utilities) and open spaces (e.g. squares, parks and gardens) (Fig. 2.1).

2.2.3

Assessment of Neighbourhood Impact Drivers

The integrated life cycle approach developed by Trigaux (2017) allows to report the neighbourhood life cycle impacts according to ﬁve drivers: material use, operational energy use, operational water use, primary land use and user transport. These drivers are briefly described in the subsequent paragraphs. A detailed description can be found in Trigaux (2017).

2.2.3.1

Material Use

Material use refers to the flows of the construction products during the entire life cycle of the neighbourhood. This includes all the flows related to the production, transport, construction, maintenance, replacement and EOL treatment of the construction products. Scenarios and assumptions used to model the life cycle of the building elements are reported in the publications of the SuFiQuaD and MMG project (Allacker 2010; Allacker et al. 2013a, b). The scenarios used for the road infrastructure and open spaces are deﬁned in Trigaux (2017).

2.2.3.2

Operational Energy Use

The operational energy use includes the energy use for space heating, domestic hot water, ventilation, lighting and appliances. The energy use for space heating is calculated based on simpliﬁed approach to estimate the heating demand during the

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Fig. 2.2 Analysis of the direct and diffuse solar radiation using ray tracing techniques in a SketchUp 3D model (Trigaux et al. 2015)

master planning of neighbourhoods. This approach consists of a design tool to optimize solar radiation and heating energy use in neighbourhoods, requiring limited input (Trigaux 2017; Trigaux et al. 2015, 2017b). Using a plugin implemented in the 3D modelling software SketchUp (2017), detailed information on solar obstructions is extracted from a 3D neighbourhood model (Fig. 2.2). This information is then used to assess the heating energy demand based on the dynamic Equivalent Heating Degree Day (dEHDD) method (Trigaux 2017; Trigaux et al. 2014, 2017b). The energy use for domestic hot water and for ventilation is assessed using a combination of two standards, i.e. the Passivhaus Projektierungs Paket (PHPP) and the Flemish standard for Energy Performance Certiﬁcates (EPC) (VEA 2013; Feist et al. 2001). Finally, the energy use for appliances and lighting is based on average household electricity consumption for Belgium (VREG 2017). When a photovoltaic (PV) system is installed, the electricity production is subtracted from the total electricity consumption.

2.2.3.3

Operational Water Use

The operational water use includes tap water consumption and wastewater and rainwater discharge. Regarding rainwater discharge, only the amount of rainwater which is transported to a wastewater treatment plant is considered. No additional impact for wastewater treatment is calculated for rainwater discharged to the storm sewer or on-site inﬁltration system. The tap water consumption and volumes of wastewater and rainwater discharged are assessed based on an existing water calculation tool, which was developed by the Belgian Building Research Institute (BBRI) (Flemish Government 2011).

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2.2.3.4

D. Trigaux et al.

Primary Land Use

Neighbourhoods are responsible for two types of land use interventions: primary land use, i.e. the neighbourhood spatial footprint and secondary land use, i.e. land use associated with the resource extraction, production, transport and EOL treatment of construction products (Allacker et al. 2014). While the environmental impact of secondary land use is assessed as part of the life cycle assessment of the construction products, the environmental impact of primary land use is calculated separately based on the method deﬁned in Trigaux (2017) and Trigaux et al. (2017a). This method, which considers the footprint of buildings, infrastructure and open spaces, assesses both the impacts of land transformation (at the start of the neighbourhood life cycle) and land occupation (during the neighbourhood lifespan). Concerning the ﬁnancial impact of primary land use, only the initial cost of land purchase is included in the assessment. Land occupation taxes during the neighbourhood life cycle are not assessed due to a lack of statistical data on the cadastral income.

2.2.3.5

User Transport

User transport focuses on the transportation of the inhabitants during the neighbourhood life cycle. This is assessed by deﬁning transport proﬁles based on statistical data on average transport distances per transport mode, as reported in the Research on Transport Behaviour in Flanders (version 5.1) (Declercq et al. 2016). This study includes transport data for the different areas of the Structure Plan Flanders, which are subdivided according to their spatial structure (from rural to more urban areas). A comparison between the transport proﬁles for the different areas allows to investigate the influence of the neighbourhood location on user transport.

2.2.4

Schematic Neighbourhood Models

To analyse the impact of the urban form and built density, four schematic neighbourhood models are assessed, consisting of, respectively, detached houses (Model 1), semi-detached houses (Model 2), terraced houses (Model 3) and apartments (Model 4) (Fig. 2.3). A real neighbourhood case study, including a mix of building typologies, is not considered in this research as the objective is to investigate the influence of the neighbourhood layout and built density based on clearly distinctive models. The neighbourhood models are inspired by representative neighbourhoods located in the Belgian municipality of Leuven. The schematic models are deﬁned using the bottom-up approach of Berghauser Pont and Haupt (2010), which distinguishes various levels of aggregation from the building to the district scale. The

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Fig. 2.3 Schematic neighbourhood models, based on Trigaux (2017)

models differ in built density with a Floor Space Index (ratio of the total building floor area to the land area), ranging from 0.20 in Model 1 to 1.21 in Model 4. More speciﬁcally, the schematic models consist of rectangular buildings which are composed of one or more housing units with a floor area of 150 m2 and four inhabitants per housing unit. The buildings are organized in urban islands around a central public space. In this research, residential neighbourhoods of approximatively 400 dwellings are considered. Furthermore, the roads, footpaths, parking facilities, square, gardens, piped and electrical services are included in the model. A detailed description of the neighbourhood models can be found in (Trigaux 2017). Element buildups are selected which are in line with the current building standards in Belgium (year 2017). The buildings are composed of a solid structure consisting of brick walls, concrete floors and a concrete flat roof. The composition of the building elements is summarized in Table 2.4. Roads and parking facilities consist of an asphalt surface layer, while concrete paving stones are selected for the square and footpaths. The composition of the external elements is summarized in Table 2.5. Regarding the energy performance, the buildings are insulated to fulﬁl the Flemish Energy Performance of Building (EPB) standards of 2017 (Flemish Government 2017) and thermally improved double glazed windows are used. An improved airtightness of 6 m3/h m2 and a ventilation system C (natural supply and mechanical exhaust) are assumed. For space heating, a condensing gas boiler

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Table 2.4 Composition of the building elements (Trigaux 2017) Building element

Composition

U-value (W/m2K)

Floor on grade

Concrete slab 15 cm—PUR board 9 cm—screed mix— ﬁred clay tiles In situ concrete foundation Prefab concrete piles (only in apartment building) Facing brick—PUR board 8 cm—insulating hollow brick 14 cm—gypsum plaster—acrylic paint Acrylic paint—gypsum plaster—hollow brick 14 cm— gypsum plaster—acrylic paint Acrylic paint—gypsum plaster—hollow brick 9 cm— gypsum plaster—acrylic paint Acrylic paint—gypsum plaster—hollow brick 14 cm— stone wool 6 cm—hollow brick 14 cm—gypsum plaster —acrylic paint Acrylic paint—gypsum plaster—hollow core concrete slab 12 cm—pressure layer—screed mix—ﬁred clay tiles Acrylic paint—gypsum plaster—hollow core concrete slab 12 cm—pressure layer—rock wool 3 cm—screed mix—ﬁred clay tiles Concrete staircase—metal banister EPDM—PIR board 10 cm—concrete slope layer— pressure layer—hollow core concrete slab 12 cm— gypsum plaster—acrylic paint PVC frame with thermal interruption—thermally improved double glazing (g-value = 0.61) MDF frame—plain door Condensing gas boiler—panel radiators—coupled instant hot water production—ventilation type C—rainwater collection Electric cables—elevators (only in apartment building)— PV panels

0.24

Foundation Pile foundation External wall Load-bearing internal wall Non-load-bearing internal wall Party wall

Storey floor Party floor

Stairs Flat roof

Window Internal door Piped services

Electrical services

n/a n/a 0.23 n/a n/a n/a

n/a n/a

n/a 0.24

1.44 n/a n/a

n/a

combined with radiators is selected. The overall efﬁciency of the heating system is 92%. For the hot water production, an instant boiler, coupled to space heating is provided. The overall system efﬁciency for domestic hot water is 85%. To fulﬁl the EPB requirements regarding the use of renewable energy (Flemish Government 2017), a photovoltaic (PV) system is installed on the flat roofs. This results in a yearly electricity production of 19 kWh/m2 useful floor area for the models consisting of single-family houses (detached, semi-detached and terraced). Due to the lower roof ratio, the PV electricity production in the apartment model is limited to 8 kWh/m2 useful floor area. Concerning rainwater management, the neighbourhood models are in line with the current Flemish Urban Planning Regulation on Rainwater Management

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Table 2.5 Composition of the external elements (Trigaux 2017) External element

Composition

Road

Geotextile—crushed gravel sub-base—cement bound crushed gravel base— asphalt Geotextile—cement bound crushed gravel base—concrete paving stones Geotextile—crushed gravel sub-base—cement bound crushed gravel base— asphalt Geotextile—crushed gravel sub-base—cement bound crushed gravel base— concrete paving stones Grass and hedges Concrete storm sewer and vitriﬁed clay sanitary sewer—drainage ditches— drinking water and gas pipes (HDPE) Electric and data cables

Footpath Parking facilities Square Gardens Piped services Electrical services

(Flemish Government 2016) and include rainwater collection tanks, separate storm and sanitary sewers and drainage ditches for rainwater inﬁltration and buffering. Concerning the assessment of primary land use, the neighbourhood models are assumed to be built on forest land. As less than 80% of the total neighbourhood area is considered to be sealed in all four neighbourhood models, the land use type ‘urban discontinuously built’ is selected to characterize the land use of the buildings, road infrastructure and open spaces. For the building land price, the Flemish average is assumed (187.79 €/m2—excluding taxes). Furthermore, the impact of the neighbourhood location is investigated by additionally comparing the terraced house model located in an urban area and the detached house model located in a rural area. For the urban area, a location in the city of Leuven is assumed. The transport proﬁle ‘Regional urban area—central municipalities’ (Table 2.6) is selected to characterize the transport of the inhabitants. Furthermore, the average building land price for Leuven (282.63 €/m2) is assumed instead of the Flemish average (187.79 €/m2). For the rural area, a location Table 2.6 Average transport distances for the urban and rural area (Declercq et al. 2016) Transport mode

Regional urban area—central municipalities (km/person/day)

Rural area (km/person/day)

Car Bus Tram/metro Train Bicycle Electric bicycle On foot

24.80 0.33 0.00 2.32 2.24 0.02 0.41

34.99 1.03 0.01 2.12 1.21 0.10 0.61

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D. Trigaux et al.

in Rotselaar, a municipality near Leuven, is considered. The related transport proﬁle ‘Rural area’ (Table 2.6) and building land price for Rotselaar (187.28 €/m2) are assumed.

2.3

Results

In this section, the results of the assessment of the schematic neighbourhood models are discussed. In a ﬁrst step (Sect. 2.3.1), the influence of the urban form and built density is analysed by comparing the neighbourhood models without deﬁning a speciﬁc neighbourhood location. Only the impacts of material use, operational energy use, operational water use and primary land use are analysed. The impact of user transport is not considered in this ﬁrst analysis as it is assumed not to be influenced by the urban form but rather by the neighbourhood location. In a second step (Sect. 2.3.2), the neighbourhood location is altered and the influence of user transport on the life cycle impacts assessed.

2.3.1

Influence of the Urban Form and Built Density

2.3.1.1

Environmental Impact

The life cycle environmental cost of the schematic neighbourhood models, over 60 years and expressed in euro per m2 useful floor area, is shown in Fig. 2.4. Large variations can be noticed between the models: the life cycle environmental cost of the models consisting of terraced houses and apartments is up to about 20% lower compared to the detached house model. Based on a detailed analysis of all impact contributors (Figs. 2.5, 2.6, 2.7 and 2.8), three main reasons, in descending order of magnitude, are identiﬁed for these variations. First, the impact of primary land use decreases signiﬁcantly (up to 80%) for higher built densities. This is a consequence of the high reduction of the land use surfaces for gardens and road infrastructure1 in the terraced house and apartment models (Fig. 2.8). Second, compact buildings such as terraced houses and apartments have lower transmission losses through the building envelope, compared to detached houses. This results in a lower energy use for space heating, which is one of the main contributors to the impact of operational energy use (Fig. 2.6). Compared to the detached house model, the environmental cost of operational energy use is about 15% lower in the terraced house model. Third, a higher built

1

The contributions to the environmental cost of primary land use are proportional to the land use surfaces as the same types of original land use (forest land) and neighbourhood land use (urban discontinuously built) are assumed for the buildings, road infrastructure and open spaces.

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500

Primary land use

450

Operational water use

euro/m2 useful floor area

Operational energy use 400

Material use

350 300 250 200 150 100 50

Model 4_apartment

Model 3_terraced

Model 2_semidetached

Model 1_detached

0

Fig. 2.4 Life cycle environmental cost of the neighbourhood models (excluding user transport), subdivided per driver

180

Electrical services (utilities) Piped services (utilities)

euro/m² useful floor area

160

Gardens

140

Square Parking facilities

120

Footpath Road

100

Electrical services (building) 80

Piped services (building) Internal door

60

Window 40

Flat roof

Stairs

20

Model 4_apartment

Internal wall

Model 3_terraced

Model 1_detached

Model 2_semidetached

Internal floor

0

External wall

Foundation Floor on grade

Fig. 2.5 Environmental cost of material use for the neighbourhood models, subdivided per building and external element

D. Trigaux et al.

euro/m≤ useful floor area

30 200

Road lighting

180

Lighting and appliances Ventilation

160

Domestic hot water Heating

140 120 100 80 60 40 20

Model 4_apartment

Model 3_terraced

Model 1_detached

Model 2_semidetached

0

Fig. 2.6 Environmental cost of operational energy use for the neighbourhood models, subdivided per energy contributor

45

Rainwater discharge from paved areas Rainwater discharge from roofs

euro/m² useful floor area

40

Wastewater discharge

Drinking water consumption

35 30 25 20 15 10 5

Model 4_apartment

Model 3_terraced

Model 2_semidetached

Model 1_detached

0

Fig. 2.7 Environmental cost of operational water use for the neighbourhood models, subdivided per contributor

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31

Land use square Land use parking facilities

90

euro/m² useful floor area

Land use road infrastructure 80

Land use gardens

70

Land use buildings

60 50 40 30 20 10

Model 4_apartment

Model 3_terraced

Model 2_semidetached

Model 1_detached

0

Fig. 2.8 Environmental cost of primary land use for the neighbourhood models, subdivided per contributor

density results mostly in less material use for buildings, networks and open spaces due to lower element ratios (Fig. 2.5). Reductions in material environmental cost of about 10% are noticed between the models consisting of detached and terraced houses. Despite the higher built density, the life cycle environmental cost of the apartment model is similar to the terraced house model (Fig. 2.4). Three reasons are identiﬁed. First, there is a lower potential for PV electricity production in the apartment model due to the lower roof ratio. This results in a higher impact of operational energy use for lighting and appliances for the apartment model compared to the terraced house model (Fig. 2.6). Second, the impact of material use in apartment buildings is similar to the terraced houses due to the additional impact of collective circulation spaces and the high impact of pile foundations (Fig. 2.5). Third, the impact of operational water use is slightly higher for the apartment model due to the lower potential for rainwater reuse from roofs (Fig. 2.7).

2.3.1.2

Financial Impact

When analysing the ﬁnancial cost, a similar picture is obtained regarding the influence of the urban form and built density (Fig. 2.9). The life cycle ﬁnancial cost of the terraced house and apartment models is up to about 25% lower compared to the detached house model. As for the environmental cost, the life cycle ﬁnancial cost of the apartment model is similar to the terraced house model, despite the

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D. Trigaux et al. 8000

Primary land use Operational water use

euro/m2 useful floor area

7000

Operational energy use Material use

6000 5000 4000 3000 2000 1000

Model 4_apartment

Model 3_terraced

Model 2_semidetached

Model 1_detached

0

Fig. 2.9 Life cycle ﬁnancial cost of the neighbourhood models (excluding user transport), subdivided per driver

higher built density. The main difference between the ﬁnancial and environmental cost is the contribution of the various drivers. While operational energy use and material use are the main contributors to the environmental cost, the ﬁnancial cost is dominated by the impact of material use, which contributes to more than 70% of the life cycle cost in all neighbourhood models. A detailed analysis of all contributors to the ﬁnancial impact of material use, operational energy use, operational water use and primary land use can be found in Trigaux (2017). Similar to the environmental cost, the main reasons for the ﬁnancial impact variations (in descending order of magnitude) are the lower material use, lower primary land use and lower energy use for heating in high built-density neighbourhoods and compact buildings.

2.3.2

Influence of the Neighbourhood Location

In this section, the combined effect2 of the built density and neighbourhood location is analysed by comparing the detached house model in a rural area and the terraced

2

The built density and neighbourhood location are not fully independent parameters as rural areas are mainly characterized by a low-built density and urban areas by a high-built density. It is therefore chosen to analyse the combined effect of both parameters.

2 Modelling the Influence of Urban Planning on the Financial … 1000

33 User transport Primary land use

900

euro/m2 useful floor area

Operational water use 800

Operational energy use Material use

700 600 500 400 300 200 100 0 Detached_rural area

Terraced_urban area

Fig. 2.10 Life cycle environmental cost of the detached and terraced house models, located, respectively, in a rural and urban location. The environmental cost is subdivided per main impact driver

12000

User transport Primary land use Operational water use

euro/m2 useful floor area

10000

Operational energy use Material use

8000

6000

4000

2000

0 Detached_rural area

Terraced_urban area

Fig. 2.11 Life cycle ﬁnancial cost of the detached and terraced house models, located, respectively, in a rural and urban location. The ﬁnancial cost is subdivided per main impact driver

house model in an urban area. The life cycle environmental and ﬁnancial costs (including user transport) of both models are shown in Figs. 2.10 and 2.11. The environmental and ﬁnancial cost of the terraced house model is, respectively, 25% and 23% lower, compared to the detached house model. The neighbourhood location has a high influence on the impact of user transport. The environmental and ﬁnancial cost of user transport in an urban area is about 25–30% lower compared to a rural area. This is mainly due to the car transport distances, which are about 30% lower for people living in urban areas (Table 2.6).

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2.4 2.4.1

D. Trigaux et al.

Conclusions Main Results and Conclusions

In this research, the influence of urban planning on the ﬁnancial and environmental impact of newly built residential neighbourhoods is investigated. Four schematic neighbourhood models with various built densities are assessed based on an integrated life cycle approach, combining Life Cycle Costing (LCC) and Environmental Life Cycle Assessment (E-LCA). The proposed approach includes an assessment of the main neighbourhood impact drivers, i.e. material use, operational energy use, operational water use, primary land use and user transport. The hierarchic and modular structure used for modelling the neighbourhoods proves to allow to identify the impact drivers and hence support urban planning decisions. The assessment of the neighbourhood models shows the high influence of the urban form and built density. The life cycle environmental and ﬁnancial costs (excluding user transport) of the terraced house and apartment models are up to, respectively, 20% and 25% lower compared to the detached house model. Higher built densities and compactness lead to a lower primary land use, lower energy use for heating and lower material use for buildings, networks and open spaces. However, the impact reductions tend to flatten for high built densities as the life cycle impacts of the apartment model are found to be similar to the terraced house model. The comparison between a rural and urban location reveals the major influence of the neighbourhood location. The life cycle ﬁnancial and environmental impact of user transport is about 25–30% lower in an urban area. Based on these analyses, it can be concluded that good urban planning, focussing on both urban form, built density and neighbourhood location is one of the key parameters to reduce the ﬁnancial and environmental impact of neighbourhoods.

2.4.2

Further Research

The research presented in this chapter has a number of limitations which should be addressed in further research (Trigaux 2017). The limitations are related to the assessment method, application of the method, result uncertainties and assessment of future changes. Concerning the assessment method, the study is limited to the effects of urban planning on the ﬁnancial and environmental impacts of neighbourhoods. An assessment of the social impacts and neighbourhood qualities is not included although both aspects are also essential when striving for sustainable neighbourhoods. Furthermore, both local climate impacts and heat island effects have not

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35

been considered in this research. Their influence on the operational energy use could be added in further research. Regarding the application of the method, three limitations can be mentioned. First, the scope of the research is limited to newly built residential neighbourhoods. The proposed approach is nevertheless extendable for the assessment of mixed-use neighbourhoods and refurbishment projects. Second, the analysed case studies are schematic neighbourhood models which are selected for their representativeness for the Belgian context. The assessment method nevertheless allows to assess more complex and innovative neighbourhood types. Third, the analysis of the services for space heating and domestic hot water is limited to individual systems. The method should, therefore, be extended to assess collective systems such as district heating and inter-building energy exchanges, as an increasing importance of such systems is noticed in new neighbourhood developments. Concerning the result uncertainties, the life cycle impact calculations are based on a huge number of input data, scenarios and assumptions. To improve the validity of the conclusions, detailed sensitivity analyses should be done considering the economic parameters, the uncertainties related to the environmental and ﬁnancial data, the implemented life cycle scenarios and the calculation methods used. Finally, the assessment focuses on the current Belgian building practice. However, fundamental changes are expected in future such as the rise of a sharing economy, the evolution towards a more circular economy, a decarbonation of the energy production and a shift in more sustainable transport modes. The effect of these future changes should be investigated as they may influence the results importantly.

References Allacker K (2010) Sustainable building, the development of an evaluation method. PhD dissertation, KU Leuven Allacker K, De Troyer F, Trigaux D et al (2013a) SuFiQuaD: sustainability, ﬁnancial and quality evaluation of dwelling types. Belgian Science Policy (BELSPO), Brussels Allacker K, Debacker W, Delem L et al (2013b) Environmental proﬁle of building elements. OVAM, Mechelen Allacker K, Souza DM de, Sala S (2014) Land use impact assessment in the construction sector: an analysis of LCIA models and case study application. Int J Life Cycle Assess 19:1799–1809. https://doi.org/10.1007/s11367-014-0781-7 ASPEN (2015a) ASPENINDEX Regio België—Nieuwbouw (translated title: ASPENINDEX region Belgium—new construction). Antwerpen ASPEN (2015b) ASPENINDEX Regio België—Ombouw (translated title: ASPENINDEX region Belgium—renovation). Antwerpen Belgian Federal Government (2017a) Statistics Belgium—oil prices. http://statbel.fgov.be/nl/ statistieken/cijfers/energie/prijzen/gemid_8/. Accessed 12 Mar 2017 Belgian Federal Government (2017b) Statistics Belgium—building land prices. http://statbel.fgov. be/nl/statistieken/cijfers/economie/bouw_industrie/vastgoed/gemiddelde_prijs_bouwgronden/. Accessed 12 Mar 2017 Berghauser Pont M, Haupt P (2010) Spacematrix. NAi Publishers, Rotterdam

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CEN (2010) EN 15643-1 sustainability of construction works—sustainability assessment of buildings—part 1: general framework CEN (2011) EN 15978 sustainability assessment of construction works—assessment of environmental performance of buildings—calculation method CEN (2013) EN 15804:2012+A1 sustainability of construction works—environmental product declaration—core rules for the product category of construction products CEN (2015) EN 16627 sustainability of construction works—assessment of economic performance of buildings—calculation methods CREG (2015) Overzicht en evolutie van de elektriciteits- en aardgasprijzen voor residentiele klanten De Nocker L, Debacker W (2015) Annex: update monetisation of the MMG method (2014). OVAM, Mechelen Declercq K, Reumers S, Polders E, et al (2016) Onderzoek Verplaatsingsgedrag Vlaanderen 5.1 (2015–2016), Tabellenrapport (translated title: Research displacement behaviour in Flanders 5.1 (2015–2016), Tables report). Instituut voor Mobiliteit, Universiteit Hasselt, Diepenbeek Delhaye E, De Ceuster G, Maerivoet S (2010) Internalisering van externe kosten van transport in Vlaanderen (translated title: Internalisation of external cost of transport in Flanders). VMM, Mechelen Delhaye E, De Ceuster G, Vanhove F, Maerivoet S (2017) Internalisering van externe kosten van transport in Vlaanderen: actualisering 2016 (translated title: Internalisation of external cost of transport in Flanders: actualisation 2016). VMM, Aalst EC-JRC (2011) International reference life cycle data system (ILCD). In: Handbook— recommendations based on existing environmental impact assessment models and factors for life cycle assessment in a European context. Joint Research Centre (JRC) of European Commission—Institute for Environment and Sustainability (IES) European Environment Agency (2006) Urban sprawl in Europe, the ignored challenge. European Environment Agency, Copenhagen, Denmark Feist W, Schnieders J, Loga T, et al (2001) Energiebilanzen mit dem Passivhaus Projektierungs Paket (translated title: Energy balance with the passive house project package). Darmstadt Flemish Government (2011) Duurzame woningbouw—Vlaamse Maatstaf voor Duurzaam Wonen en Bouwen—versie 2.0 (translated title: Sustainable housing—Flemish tool for sustainable living and building—version 2.0). Departement Leefmilieu, Natuur en Energie (LNE) Flemish Government (2016) Regional urban planning regulation on rainwater management. https://www.ruimtelijkeordening.be/Verordeningen/Hemelwater. Accessed 20 Aug 2017 Flemish Government (2017) EPB requirements. www.energiesparen.be/epb/welkeeisen. Accessed 20 Aug 2017 Frischknecht R, Jungbluth N, Althaus H et al (2007) Overview and methodology—ﬁnal report ecoinvent data v2.0, no 1. ecoinvent Centre, Dübendorf Ratti C, Baker N, Steemers K (2005) Energy consumption and urban texture. Energy Build 37:762–776. https://doi.org/10.1016/j.enbuild.2004.10.010 Salat S (2009) Energy loads, CO2 emissions and building stocks: morphologies, typologies, energy systems and behaviour. Build Res Inf 37:598–609. https://doi.org/10.1080/09613210903162126 Spon press (2015a) Spon’s external works and landschape price book 2015, 34th edn. AECOM, London Spon press (2015b) Spon’s civil engineering and highway works price book, 29th edn. AECOM, London Trigaux D (2017) Elaboration of a sustainability assessment method for neighbourhoods. PhD dissertation, KU Leuven Trigaux D, Allacker K, De Troyer F (2014a) Model for the environmental impact assessment of neighbourhoods. In: Passerini G, Brebia CA (eds) Environmental impact II. WIT Press, Ancona, Italy, pp 103–114 Trigaux D, Allacker K, De Troyer F (2014b) A simpliﬁed approach to integrate energy calculations in the life cycle assessment of neighbourhoods. In: Rawal R, Manu S, Khadpekar N (eds) Sustainable habitat for developing societies—book of abstracts. CEPT University Press, Ahmedabad, India, pp 55–55

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Trigaux D, Oosterbosch B, Allacker K, De Troyer F (2015) A design tool to optimize solar gains and energy use in neighbourhoods. In: Cucinella M, Pentella G, Fagnani A, D’Ambrosio L (eds) Architectuur in (R)evolution—book of abstracts. Ass. Building Green Futures, Bologna, Italy, pp 305–305 Trigaux D, Allacker K, De Troyer F (2017a) Life cycle assessment of land use in neighborhoods. Procedia Environ Sci 38:595–602. https://doi.org/10.1016/j.proenv.2017.03.133 Trigaux D, Oosterbosch B, De Troyer F, Allacker K (2017b) A design tool to assess the heating energy demand and the associated ﬁnancial and environmental impact in neighbourhoods. Energy Build 152:516–523. https://doi.org/10.1016/j.enbuild.2017.07.057 VMM (2015) Gemiddelde waterprijs 2015. https://www.vmm.be/data/gemiddelde-waterprijs. Accessed 24 Jan 2017 Trimble Inc. (2017) SketchUp. www.sketchup.com. Accessed 21 Mar 2017 VEA (2013) Energieprestatiecertiﬁcaten voor bestaande residentiële gebouwen in Vlaanderen— Formulestructuur (translated title: Energy performance certiﬁcate for existing residential buildings in Flanders—formula structure) VREG (2017) Electricity use of a household. www.vreg.be/nl/elektriciteitsverbruik-van-een-gezin. Accessed 28 Mar 2017

Chapter 3

Achieving Energy Efﬁciency in Urban Residential Buildings in Vietnam: High-tech or Low-tech? Quang Minh Nguyen

Abstract Vietnam started to go for green rather late, ofﬁcially in 2005 or 2006, shortly before Vietnam Green Building Council was established and the ﬁrst legal documents paving the way for green building development to take root were drafted and then adopted. As the green building is a holistic concept and encompasses a wide range of specialisation, it seems that at the beginning, Vietnam chose energy —the most important component—to focus on before dealing with other measures in a comprehensive package of solutions. In terms of energy, most green, and energy-efﬁcient buildings that Vietnam has constructed and been certiﬁed so far come from public and industrial building sector, such as schools, supermarkets, ofﬁces, showrooms and factories, while in housing which makes up the largest part of the country’s urban building market, this concept has not been properly developed, not only in quality but also in quantity. In order to provide more energy-efﬁcient housing for the public and meet their very high demand, there are two options for architects—high-tech design and low-tech design—to propose in the local context. Furthermore, another possibility—combining the two tendencies —should be considered and discussed, because of its potential and flexibility in practice, as well as appropriateness in Vietnamese conditions. Keywords Urban housing

3.1 3.1.1

Green building Energy-efﬁcient architecture

Introduction Urbanisation

As a developing country centrally located in Southeast Asia, Vietnam has been ranked among the fastest growing emerging economies in the world since 2000. International reports show that the urbanisation rate in Vietnam has increased steadily Q. M. Nguyen (&) National University of Civil Engineering, 55 Giai Phong Road, Hanoi, Vietnam e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 E. Motoasca et al. (eds.), Energy Sustainability in Built and Urban Environments, Energy, Environment, and Sustainability, https://doi.org/10.1007/978-981-13-3284-5_3

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in recent years, estimated at 0.6–0.7% annually, from 27.89% in 2006 to 34.24% in 2016 (Statista 2017). The latest statistics reveal that 35.2% of Vietnam’s total population (33.99 million out of 96.51 million) live in cities and towns (World Bank 2018). This rate is forecast to reach 36.3% in 2020, 41.2% in 2030 and 48.6% in 2050 (Worldometer 2018). Today, there are 813 cities and towns across the country (Ministry of Construction 2018). Ho Chi Minh City (8.2 million residents) and Hanoi (7.4 million residents) are Vietnam’s two largest urban centres (World Atlas 2017), two special-class cities and also the two most important economic hubs in the South and in the North, respectively. The rapid urbanisation rate has caused many social problems and puts a burden on the current underdeveloped technical infrastructure systems. In this circumstance, housing has become a hot spot (Fig. 3.1).

3.1.2

Urban Housing

Urban housing development in Vietnam was ignited in the early 1990s with a number of legal documents and supporting policies, such as Housing Ordinance in 1991, Land Law in 1993, Building Ownership and Certiﬁcate of Individual Land Use Rights in 1994, later reinforced with National Orientation for Housing Development in 2004, Housing Law in 2005 and Real Estate Law in 2006. Today, after almost three decades, housing is reported to make up no less than 70% of all the built floor area in Vietnamese cities, and the actual demand for new housing is estimated at over 500,000 units per year after 2020 or 12.5 million m2 should be annually provided, compared to 325,000 units (6.5 million m2) per year in 2010–2020 and 275,000 units (4.1 million m2) per year before 2010, as the housing area standards of 25, 20 and 15 m2 per person should apply respectively (UN Habitat Vietnam 2014; Ministry of Construction 2011). This demand has often exceeded the supply capacity of the housing construction and building industry in Vietnam over the last 10 years, which was severely affected by the world’s economic and ﬁnancial crisis in 2008 and again by the national frozen real estate market from 2010 until 2014/2015. There is a mixture of three to six housing types in almost all of the current living quarters in major cities like Hanoi and Ho Chi Minh City. This trend began in the late 1980s, after the centrally planned economy was abolished and the long-awaited economic reform also marked a new beginning for urban housing, as it would no longer be a sector monopolised by state-owned building corporations as previously (1954–1986) and the individual property ownership could eventually be recognised for the ﬁrst time by the Government in 1994. Since 2010, this kind of mixing has accelerated. In Hanoi, for example, there are 12 housing types listed in chronological order, as the city expanded: traditional shophouse, traditional garden house, French colonial villa, French colonial shophouse, Soviet collective block of flats, self-built family house (into a row), self-built villa, social rental house, mini-apartment building, standard villa, standard row house and standard apartment building (multistorey or high-rise). Slum is excluded, as it has never been ofﬁcially regarded as formal housing and the city authority is trying to replace it with new

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Fig. 3.1 Vietnam administrative map (mainland) and its city-and-town system. The two archipelagos of Paracel (Hoang Sa) and Spratly (Truong Sa), which Vietnam claims national sovereignty, are not shown on the map due to the frame dimensions. (Nation Online Maps 2018)

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social housing by 2020. Among these 12 housing types, self-built family house was reported in 2014 by UN Habitat Vietnam to make up the largest part (estimated at 70%). Building standard apartments (for both high-end and low-end users) is the fastest-growing sector in mega-cities, because it has been determined a major housing pattern in the future and constructed on a large scale to meet the urgent needs for housing of millions of both permanent dwellers and new immigrants rushing from the countryside as well as from small towns. A very similar situation is noted in Ho Chi Minh City. Much of urban housing in Vietnam’s two mega-cities fails to meet the new housing quality and floor area per capita standard proposed by the Ministry of Construction, particularly in central districts, where the building density is particularly high. Lack of daylight and natural ventilation, extremely low green area per capita, inappropriate use of building materials, abuse of air conditioners, negative influences of polluted air and noise from trafﬁc congestions, insufﬁcient water supply and inadequate sanitation are common housing problems in these areas (Fig. 3.2).

3.1.3

Green Building

Energy efﬁciency has been, and continues to be, the most important component in a truly green building, because both energy production and energy consumption are largely involved in and responsible for the global warming, environmental crisis and other social problems arising from human daily activities. In the face of fossil fuel exhaustion, environmental pollution and increasing demand for energy as a consequence of population boom, rapid urbanisation and machine-based modern life, energy efﬁciency has been regarded as a must, not only in new building projects but also for the conservation of historic buildings worldwide. However, design for energy efﬁciency seems to take place mostly in developed countries in North America, Western Europe, Japan, Australia, New Zealand and Singapore. In other parts of the world, including Vietnam, this trend has not yet (or just) taken its root and people have therefore a long way to go to keep pace with the world’s progress and achievement. Established in 2007 and ofﬁcially recognised by the Ministry of Construction in 2009, Vietnam Green Building Council (VGBC) is responsible for the promotion and development of green buildings in Vietnam by setting up a comprehensive green building rating system and encouraging green building design as well as awarding green building projects across the country. Lotus is a green building certiﬁcate granted by VGBC. The 2018 database of VGBC consists of 43 green building projects, divided into eight categories and ﬁve ranks as follows: Category Category Category Category

1 2 3 4

(Industrial buildings): (Education buildings): (Tourism buildings): (Ofﬁce buildings):

7 8 1 8

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Fig. 3.2 a Housing development in central Ho Chi Minh City (Photos: taken in 2018 by Quang Minh Nguyen). b Housing development in central Hanoi (Photos: taken in 2018 by Quang Minh Nguyen)

Category Category Category Category Total:

5 6 7 8

(Service buildings): (Commercial buildings): (Cultural buildings): (Residential buildings):

1 5 1 12 43

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Rank 1 (Platinum certiﬁcate): 3 Rank 2 (Gold certiﬁcate): 0 Rank 3 (Silver certiﬁcate): 9 Rank 4 (Certiﬁcate): 5 Rank 5 (Provisional certiﬁcate): 26 Total: 43 (Vietnam Green Building Council 2018) It is noticeable that residential buildings (category 8) have not yet been largely constructed for green building certiﬁcates: out of 12 residential buildings listed, only one has been ofﬁcially certiﬁed while the other 11 are still under examination or partially evaluated—thus provisionally certiﬁed. Similarly, most of the buildings (31 out of 43—over 72%) acquire lower ranks. For the next 10 years, it will be necessary to have a greater number of green buildings, particularly in housing, and higher standards (platinum and gold) should be notched up. The statistics from VGBC also reveal that by the end of 2017, 116 buildings and building projects in Vietnam had been awarded green building certiﬁcates by one of the following four bodies: VGBC with Lotus, USGBC with LEED, Building and Construction Authority (BCA) Singapore with Green Mark and International Financial Corporation (IFC)/World Bank with EDGE (Excellence in Design with Greater Efﬁciency). This growth rate is quite positive for the ﬁrst ten years of developing green buildings in Vietnam (2007—2017), but still incomparable to 2,100 green buildings that Singapore had achieved by 2014. The more ambitious plan for BCA to strive for is to have 80% of all buildings qualiﬁed with Green Mark by 2030 (BCA, 2014). Vietnam must make greater efforts in the coming years, if the country does not want to lag behind in the ASEAN in terms of developing green buildings (Fig. 3.3). Certainly, the VGBC database is not a complete list, because there are other green buildings in reality which have not yet been registered for ofﬁcial recognition. Some buildings have become quite well known, even won national/international awards,

Fig. 3.3 Green building growth in Vietnam from 2007 to 2017 (accumulative ﬁgures) (Data: VGBC, 2018—Photos: taken in 2018 by Quang Minh Nguyen)

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Fig. 3.4 Suoi Re Community House (left) and S-House 2 as two of the ﬁrst green buildings in Vietnam. Internationally recognised with grand awards but not yet nationally certiﬁed. (Photo: taken in 2012 by Quang Minh Nguyen) and (Vo Trong Nghia Architects 2018)

such as Suoi Re Community House in Hoa Binh province designed by Architect Hoang Thuc Hao (1 + 1 > 2 Ofﬁce) or Palm tree House (S-House 2) in Long An Province developed by Architect Vo Trong Nghia (VTN Architects) (Fig. 3.4).

3.1.4

Energy Consumption

A high level of energy consumption (and CO2 emission as well) can be seen in many residential buildings in urban agglomerations like Ho Chi Minh City and Hanoi. Two individual investigations into household energy consumption were conducted in 2016 with 110 case studies for row houses and 35 case studies for apartments, because these are the two most typical housing patterns in central Hanoi in terms of thermal discomfort and excessive energy use as a consequence of inappropriate design and construction. The results show that household energy consumption immensely depends on the following three main factors: orientation, design concept and purpose of use. A small number of case studies with the same (or similar) input data, such as gross floor area, family size, location, orientation, etc. have been selected and analysed for comparison purposes. Orientation: A row house and an apartment facing Southeast consume less energy than the same size house and apartment facing Southwest in the same area, 47.7% and 26.8%, respectively. South and Southeast are two optimal directions for residential buildings in Hanoi and the Red River Delta (North of Vietnam), because residents can make full use of warm morning sunlight and cool wind in summer months while avoiding harmful solar radiation in the afternoon and cold winter wind from late November to mid-March. Bio-climatically, a house or an apartment facing West or Southwest are rather uncomfortable. But choosing a better orientation is sometimes not possible in planning. In this case, additional measures must be taken, either architecturally or technically (or both, if necessary) to help minimise the negative influences of the weather conditions on the indoor environment.

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Design concept: Between two row houses or two apartments of the same size facing Southwest as one of the two most disadvantageous directions, the one with simple but efﬁcient design solutions against heat and solar radiation consumes 25.5% less energy (row house) or 22.0% less energy (apartment) than the other that goes without applying such solutions as suggested by architects. Business and service activity: Among three row houses facing the same direction (Southwest), the one for living only consumes 15.4% less energy than the one with a small shop and simple service and 35.3% less energy than the one with a large shop and special service (Author, 2016) (Table 3.1). Generally, there is no rule of the ups and downs in the household energy consumption, because the family’s activities change from time to time or some events may happen suddenly, such as going on holiday or business, welcoming visitors and guests, extreme weather conditions, etc. But it is apparent to notice that the energy consumption in this case study increased over the years. The energy demand becomes much higher in summer months (May to August) due to very hot weather and longer time of air conditioning. Similarly in January or February, when the New Year’s Holiday comes, cooking and washing can be energy-consuming. In February and March, when the air humidity amounts to 95– 100% because of spring drizzles, drying is a major demand, as dehumidiﬁers are switched on 24 h a day. Another survey conducted on a much larger scale by the National Institute of Energy in 2016 reveals that the energy consumption per capita rose continually from 2010 to 2015 (European Chamber of Commerce in Vietnam 2017). This

Table 3.1 Comparative study on household energy consumption in Hanoi (Survey: undertaken in 2016 by Quang Minh Nguyen) Factors and cases A. Orientation (with proper design, no shop) A1. Southeast A2. Southwest Assessment (A1 compared to A2) B. Design concept (same direction—Southwest) B1. With solutions against heat and solar radiation B2. Without solutions against heat and solar radiation Assessment (B1 compared to B2) C. Business and service (same direction—Southwest) C1. No activity (with no shop) C2. With activity (small shop, simple service) C3. With activity (large shop, speciﬁc service) Assessment (C1 compared to C2) Assessment (C1 compared to C3)

Energy consumption (kWh/m2a) Row house Apartment 23 44 47.7% saving

41 56 26.8% saving

35 47 25.5% saving

59 73 19.2% saving

44 52 68 15.4% saving 35.3% saving

– – –

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47

upward trend is in accordance with the individual study results shown in Table 3.2. The values in Fig. 3.5 are calculated on an average basis, between urban and rural areas, thus lower than those in Table 3.2 from Hanoi as a mega-city, considered for 2013, 2014 and 2015 as 3 years in common between the two surveys. The main problem to be tackled for housing development in major cities in Vietnam, especially in Hanoi and Ho Chi Minh City, is energy efﬁciency that can be achieved by applying a number of planning strategies, design concepts and technical solutions. Planning strategies deal with optimal orientation which may be difﬁcult to select for various reasons. For example, one of the two rows of houses in a street running from the North to the South has to face West. Built on a limited land plot, that row house cannot be rotated to face south like a villa in the middle of a large garden. In this case, it is highly recommended to focus on housing design concepts by reorganising the conventional room layout into a new one in view of energy (form follows energy apart from function) and by restructuring the building envelope, so that the external walls and the roofs can be better protected from solar radiation and excessive heat. For the next step, with several technical solutions that will help optimise cooling as well as heating and reduce the dependence on fossil fuel energy sources (coal, oil and gas), it is possible to enhance energy efﬁciency Table 3.2 Household electricity consumption in one typical middle-class family in Hanoi (parents and two children) (Data: collected and analysed in 2018 by Quang Minh Nguyen) Month

Annual energy consumption (kWh) 2013 2014 2015 2016

2017

January February March April May June July August September October November December Total (kWh) Gross floor area (m2) Energy consumption (kWh/m2a) Number of family members Consumption per capita (kWh/ person) Quantiﬁcation

554 593 558 539 602 775 646 535 620 603 512 532 7,069 160 44 4 1,767

663 628 569 576 611 795 861 588 696 642 525 558 7,712 160 48 4 1,928

678 645 580 593 587 844 787 631 915 705 531 527 8,023 160 50 4 2,006

833 625 638 693 591 813 945 907 878 738 553 583 8,797 160 55 4 2,199

959 983 1,103 770 630 689 880 893 679 666 603 589 9,444 160 59 4 2,361

x

1.09x

1.13x

1.24x

1.33x

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Fig. 3.5 Household energy consumption per capita in Vietnam from 2010 to 2015 (Data: European Chamber of Commerce in Vietnam 2017—Graphic: drawn by Quang Minh Nguyen, 2018

considerably. In other words, CO2 emission into the atmosphere can be controlled and global warming will not be going on too fast. To solve this problem, architects have several options in two directions: high-tech solutions and low-tech solution, which will be discussed later at the end of this book chapter. The objectives of developing more energy-efﬁcient housing concepts should be set and highlighted as follows: • To improve indoor thermal comfort for building occupants; • To use energy more efﬁciently and to promote energy efﬁciency in modern housing and building design: the same energy consumption for greater thermal comfort or the same thermal comfort with less energy consumption; • To enhance the awareness of energy efﬁciency and sustainability among the public and decision/policy makers as well as project managers; • To revitalise some of the best traditional housing concepts towards a more comfortable built environment; • To pave the way for a new revolution in urban housing development.

3.2 3.2.1

Energy and Energy Efﬁciency in Vietnam Strengths

Entirely located in the tropical climate zone and with a long coastal lines (over 3,200 km), Vietnam enjoys a huge potential and has very good opportunities to exploit renewable energy sources, especially solar energy and wind energy which are expected to replace conventional forms of energy step by step until 2030. Solar

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49

energy can be produced with high solar energy intensity and annual sunshine hours, as given in Table 3.3 and in Fig. 3.6. Apart from solar energy development plans and construction of two photovoltaic panel factories in Vietnam to reduce the equipment fabrication price and encourage people to start using clean energy by installing solar energy systems at homes, the Government and the Ministry of Industry and Trade have cooperated with Denmark and Germany as two world leaders in wind power development to build some wind power stations along the coastal line. The ﬁrst two large-scale projects in Ninh Thuan province and Bac Lieu province are underway. In addition, tidal energy can be exploited but the potential has not yet been explored and/or assessed. In green building and clean energy development, strategies and policies play a vital role, particularly for a country that has just started to go for green like Vietnam. Understanding this, the Government and the Ministry of Construction have prepared some laws to pave the way for energy efﬁciency to become an obligatory requirement in both industrial and civil construction, as well as for regenerative energy (primarily solar energy and wind energy) to be more popular among city inhabitants. The most signiﬁcant legal documents include Energy Saving and Energy Efﬁciency Law (No. 50/2010/QH12) adopted in 2010 by the National Assembly and the National Energy Efﬁciency Building Code (QCVN09/ 2017/BXD) proposed in 2016 by the Ministry of Construction and approved in 2017 by the Prime Minister. Energy Saving and Energy Efﬁciency Law is applicable to all households, individuals and organisations that use energy for any purpose in Vietnam, consisting of 12 chapters with 48 articles. Key articles include: • Article 15: Recommendations for energy saving and energy efﬁciency in housing construction and operation; • Article 27: Regulations for energy efﬁciency in everyday household activities; • Article 37: Use of standard energy-efﬁcient equipment and devices in line with energy labelling; • Article 38: Establishment and announcement of energy efﬁciency standards; • Article 42: Optimisation of design and utilisation of renewable energy sources, development of innovative energy technologies. Table 3.3 Potential of solar energy production in Vietnam (European Chamber of Commerce in Vietnam Ofﬁce 2017) Region

Sunshine hours per year (h)

Solar radiation intensity (kWh/m2.day)

Assessment of potential

North (with Hanoi, Hai Phong, Nam Dinh, Ha Long) Central (with Da Nang, Hue, Quy Nhon, Nha Trang) South (with Ho Chi Minh City, Bien Hoa, Vung Tau, Can Tho)

1,500–1,700

3.8–4.7

Fairly high

1,800–2,100

4.5–5.3

High

2,000–2,600

5.1–5.6

Very high

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Fig. 3.6 Map of solar radiation intensity and its potential in Vietnam (Vu Phong Solar Power Company 2017)

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Meanwhile, the National Energy Efﬁciency Building Code (upgraded in 2017 on the basis of the previous version in 2013) is applicable to all buildings with gross floor area of 2,500 m2 or above, no matter what kind of building they are. Important requirements and technical speciﬁcations include: • • • • • • • • • • • • • • • • • • • •

Building envelope (roof, external wall, windows and doors); Overall Thermal Transferred Value (OTTV) for different building elements; Solar Heat Gain Coefﬁcient (SHGC) for building elements; Window/Wall Ratio in different orientations; A factor for different sun-shading elements in different building orientations; Natural and mechanical ventilation; Cooling coefﬁcient of performance; Technical speciﬁcations for cooling towers and condensers; Insulation for cooling systems and thickness of insulation layers; Daylighting and minimum illuminance; Productivity and performance of lighting devices; Monitoring and automation of street lighting and lighting for public places; Energy use and electricity distribution systems; Measurement of energy consumption and adjustment of power; Warm water systems; Insulation for warm water systems and thickness of insulation layers; Maximum U value for external walls: 1.8 W/m2K; Maximum U value for roofs: 1.0 W/m2K; Maximum OTTV value for external walls: 60 W/m2; Maximum OTTV value for roofs: 25 W/m2 (Ministry of Construction 2017).

These are two effective instruments for practising energy efﬁciency in buildings. However, the floor area of 2,500 m2 normally applies to medium-size public buildings and large-scale high-rise residential buildings (20 or more apartments per floor). Single-family houses have not yet taken into account, although they exist in a huge number and consume so much energy. Vietnam Green Building Council (VGBC) has developed several detailed rating systems for green buildings and certiﬁcates in general, and in housing in particular, with two categories: multifamily and single family. These rating systems are accompanied by intelligible technical manuals (Table 3.4). The importance of energy efﬁciency is demonstrated in the highest scores (31 out of 118 points for multifamily buildings and 29 out of 100 points for single-family buildings). In both cases, energy efﬁciency has been broken down into eight sub-criteria with corresponding scores. This rating system is quite clear to understand and easy to use for a preliminary qualitative self-assessment of building performance at the design stage. Since 2014, Vietnam Association of Architects (VAA) has used a set of criteria to evaluate and grant awards the best designs within the framework of the annual National Green Building Competition (Table 3.5).

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Table 3.4 a VGBC rating system (and scorecard) for multifamily residential buildings in category Energy (Vietnam Green Building Council 2012). b VGBC rating system (and scorecard) for single-family residential buildings in category Energy (Vietnam Green Building Council 2012) a No. 1

2 3 4 5 6 7 8 9 10 b 1

2 3 4 5 6 7

Criteria and sub-criteria

Maximum point

Energy 1.1 Passive design 1.2 Total building energy use 1.3 Building envelope 1.4 Natural ventilation and air conditioning 1.5 Artiﬁcial lighting 1.6 Energy monitoring 1.7 Lifts 1.8 Renewable energy Water Materials Ecology Waste and pollution Health and comfort Adaptation and mitigation Community Management Innovation Total

31 Prerequisite 14 4 6 3 1 1 2 13 9 9 7 13 10 6 12 8 118

Energy 1.1 Passive design 1.2 Building envelope 1.3 Home cooling 1.4 Artiﬁcial lighting 1.5 Water heating 1.6 Energy-efﬁcient appliances 1.7 Energy monitoring 1.8 Best practice credits Water Materials Local environment Heat and comfort Community management Innovation Total

29 5 4 6 3 2 3 1 5 12 14 17 14 10 4 100

Given point

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Table 3.5 Green architecture criteria with focus on energy set up by vietnam association of architects (Vietnam Association of Architects 2017) No.

Criteria and sub-criteria

Maximum point

1 2

Sustainable site Efﬁcient use of natural resources and energy 2.1 Complying with National Technical Standards and current legal documents regarding land-use indicators, energy use, water use and material use in construction 2.2 Efﬁcient exploitation and use of land in construction 2.3 Efﬁcient exploitation and use of water resources 2.4 Efﬁcient exploitation and use of energy 2.4.1 Finding planning solutions, proposing architectural designs, making good selections of building materials, applying technology and installing equipment to ensure: 2.4.1.1 Efﬁcient use of natural energy sources (sun, geothermal heat, etc.), exploitation and making full use of other renewable energy sources which are locally available and easy to regenerate, etc. Using renewable energy at least 5% of the total energy consumption within a building 2.4.1.2 Making full use of daylight and natural ventilation 2.4.2 Using monitoring and controlling systems in order to manage energy use in a building towards minimisation of energy consumption (such as EMS—Energy Management System, etc.) 2.5 Exploitation and efﬁcient use of materials (building envelopes and interior design) Indoor air quality and environmental quality in urban or rural areas Advanced architecture and identity Social sustainability and humanity Total

15 40 Prerequisite condition

3 4 5

Given point

12 12 10 7

4

3 3

6 13 17 15 100

Compared to the rating systems proposed by VGBC, VAA’s criteria are more complex and comprehensive, because social sustainability has also been integrated. Energy is directly given 10 out of 100 points only, but the actual score for energy amounts to 31, with 21 additional points from several sub-criteria related to energy in Categories 1 and 3.

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Q. M. Nguyen

Opportunities

In the era of globalisation, it is possible to make full use of international cooperation, including the ﬁelds of building science and energy technology, as an outstanding strength for the future development of energy efﬁciency in Vietnam. The country has good opportunities to develop renewable energy based on its high potential and energy-efﬁcient buildings with innovative energy technologies directly transferred from the EU and/or the USA. Germany and Denmark have helped Vietnam build wind turbines in some coastal provinces in the south while Winrock International Corporation from the USAID has been a reliable partner in bringing solar energy to a larger number of people in Vietnam, especially those living in the countryside, and in launching more action programmes for the communities easily affected by climate change so that they can mitigate the impacts of unsustainable development on the environment. In the future, such cooperation activities should be consolidated and new international organisations will be invited to give a further boost to energy-efﬁcient housing in Vietnam.

3.2.3

Weaknesses

High-tech energy production remains a weakness in Vietnam, but that problem can be solved with cooperation and technology transfer as aforementioned. Incomplete understanding of green building design among professionals and lack of awareness of sustainable development among the community are the real hurdles for Vietnam to overcome on the way to sustainability and energy efﬁciency in urban housing. In fact, an energy-efﬁcient building can only be achieved by applying a wide range of design concepts and a combination of technical solutions. However, many architects in Vietnam, even those with more than 10 years of work experience, still imagine a green home simply as a row house with a green roof, an apartment with a green façade, or a villa in the middle of a large land plot with so many shade trees planted all around the house. They consider an energy-efﬁcient building a building with photovoltaic panels (for electricity) and a solar collector (for warm water) installed on the roof. As a consequence, inappropriate design solutions can be found in numerous housing concepts, for example, air-tight corridors and bedrooms without windows (Fig. 3.7). In Artemis Tower—one of the best apartment buildings in Hanoi designed by PTW as a leading Australian company—14 out of 20 apartments in one typical floor plan have one bedroom and one kitchen with inadequate daylight and natural ventilation due to their location, just connected to the open air through a long and narrow loggia (1 m 4.2 m), as marked with red box (bedroom) and yellow box

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Fig. 3.7 Analyse of design shortcomings in Artemis tower as one of the best deluxe apartment buildings in Hanoi (Background floor plan: Artemis Project Management Unit, 2017—Design: analysed by Quang Minh Nguyen, 2018)

(kitchen) in Fig. 3.7. One of the three staircases has no daylight and air exchange which is highlighted with a purple box. A majority of people think about green building/housing almost in the same way as architects do. They admit that green/energy-efﬁcient architecture sounds very nice, but they ﬁnd the price so high that they can hardly (or never) afford it. That is why they feel reluctant to purchase a truly greenhouse or an apartment designed in compliance with the latest energy-saving standard. Instead, most of them choose other options of lower building quality or energy standard that fall within their payability. In their opinion, air conditioning is the only way to ensure thermal comfort in the city with a very high building density and huge impacts of urban heat island like Hanoi or Ho Chi Minh City. People tend to abuse air conditioning, even when it is not necessary to run a mechanical ventilation system. While specialists recommend that the room temperature should be set at 25 or 26 °C for the outside air temperature at 34 or 35 °C at night in the summer months, many occupants select the room temperature mode at 20 °C or even lower from 10 pm to 6 am the following day (8 hours long) which of course consumes a huge amount of electric power. It is important to know that only by turning off all light bulbs that might be unnecessary for use within one hour did the Earth Hour campaigns help Vietnam save 471,000 kWh in 2017 and 485,000 kWh in 2018 (Vietnam News 2018).

3.2.4

Threats

Today, in electricity production, Vietnam still has to depend so much on fossil fuels, such as coal, oil and gas which cause serious environmental pollution. Heat power plants, for this reason, have not been recommended. Hydropower is not as abundant as in the 1970s or 1980s. On-going climate change has resulted in a much lower of

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Fig. 3.8 Energy production in 2015 and energy development scenarios for the future in Vietnam (Data: Vietnam Institute of Energy, 2016—Graphic: drawn by Quang Minh Nguyen, 2018)

rainfall and downstream flow. In addition, China goes on to build huge dams in the upper tributary of the Red River (in Yunnan province) as the most important source of water and hydropower to the northern part of Vietnam. The recent energy production structure (as of 2016) and the future energy development plan (for 2020 and 2030) show that clean energy has not yet been properly developed in Vietnam (Fig. 3.8), even when Vietnamese energy experts and some international organisations advised the Government and the Ministry of Industry and Trade to invest in clean energy instead of low-tech power production imported from China. In 2014, a decision to build and put two nuclear power plants (4,600 MW) into use by 2030 with Russian nuclear power technology in Ninh Thuan province (Vietnam Electricity Corporation 2016)—not so far from the wind power plant supported by Denmark—raised a great public concern, because of a high risk to the local eco-systems and living environment, just 3 years after the nuclear catastrophe in Fukushima (Japan) happened. Although the Government cancelled that controversial plan in 2016 as a result of the public strong reaction, Vietnam will have to face energy insecurity and environmental challenges as far as no bold step towards renewable energy has ever been made. As indicated in Fig. 3.8, three renewable energy sources (solar energy, wind energy and biomass) will contribute only 3.3% to the total energy production in 2020 and increase to 16.1% in 2030—a considerable improvement. However, in view of the urgent need for more renewable energy, this growth rate is still insufﬁcient. Thermo-electricity from fossil fuels (coal, gas and oil) will make up a large part of the energy market in 2020 and even until 2030: approximately 60% (Vietnam Institute of Energy 2016). The treatment of pollution caused by the production of thermoelectricity will cost a great deal of money and put an immense ﬁnancial burden on a developing country like Vietnam. After all, the threats can be seen in the intention of developing nuclear power technology and the policy of using fossil fuels in the electricity production.

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57

Energy Efﬁciency in Urban Housing in Vietnam—The First Two Examples

Building accounts for 36% of the nation’s total energy consumption and 33% of the CO2 emission a year (Vietnam News 2017). Therefore, achieving energy efﬁciency in building should be regarded as a key point in reducing both energy consumption and carbon emission in Vietnam and thereby securing sustainable urban development. In the building sector, housing should be chosen to apply energy efﬁciency ﬁrst, because housing is the largest building market in the city—70% of the total built floor area (UN Habitat Vietnam 2014) with 689 million m2 of the entire urban housing stock as of 2014 (World Bank 2015) and people spend normally at least half a day staying in their houses or apartments. Mulberry Lane is one of the ﬁrst housing projects in collaboration with CapitaLand Singapore and became the ﬁrst residential project in Hanoi to receive a BCA Green Mark award in 2014 for excellence in housing design (overall band score of 79 out of 140 points) along with two national awards that same year for green building performance. All the ﬁve dwelling blocks A, B, C, D and E have been designed in view of tropical architecture with three different housing patterns, of which three blocks B, C and D in the middle have the same floor plan concept (Figs. 3.9 and 3.10). Four essential factors—daylight, cross ventilation, greening and stunning view—are maximised. Over 80% of the 1,487 apartments are regarded as ‘optimal’ in terms of daylight and cross ventilation, hereby reducing energy consumption for artiﬁcial lighting and air conditioning. RSP Architects 2015`` to the end of the paragraph and put into parentheses (RSP Architects 2015). In addition, the following solutions are applied to enhance energy efﬁciency: • • • • • • • •

Cooling with vegetation and vapour; Choosing an optimal orientation (facing North and South); Calculating an appropriate distance between two buildings (at least 20 m); Designing a layer of insulation for roof and all external walls, especially in the West direction; Double-glazing for all windows and doors open to balconies; Using solar energy for warm water systems; Installing energy-efﬁcient HVAC systems and equipment, including lighting; Raising public awareness of saving energy as daily behaviour.

As a result of such a combination, the project can save up to 3.6 million kWh of electricity a year (CapitaLand Singapore 2015). The typical floor plan, in block B for instance, demonstrates a careful consideration in design for thermal comfort based on daylight and cross ventilation, applicable to all main apartment rooms (living room, bedrooms, dining room and kitchen). Instead of having 15–20 apartments per floor as often seen in other high-rise apartment building projects, a Mulberry Lane dwelling unit accommodates 10 or 13 apartments per floor only. Therefore, daylight and airflow can

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Hanoi

Ho Chi Minh City

Case study 1 - Mulberry Lane project (RSP Architects, 2015) Project information: Site: Mo Lao new town - Ha Dong district, Hanoi City Site area: 2.4 ha Population: approximately 6,000 Number of apartment buildings: 5 blocks (from 27 to 35 storeys) Gross floor area: 235,850 m2 Number of apartments: 1,487 Types of apartments: 45 m2, 80 m2, 88 - 114 m2, 123 - 127 m2 and 130 - 154 m2 Date of completion: 2014 Project developers: Hoang Thanh Building Corporation (Vietnam) and CapitaLand (Singapore) Building consultant: RSP Architects Co. Ltd (Vietnam) Certification of VGBC green building: No Recognition of green building design: Yes Case study 2 - Eden villa (XYZ Design Saigon, 2017) Project information: Site: Thao Dien ward, District 2, Ho Chi Minh City Site area: 450 m2 Type: Villa - single family house Building height: Three storeys Date of completion: 2017 Building consultant: XYZ Design Saigon

Fig. 3.9 Project sites for energy-efﬁcient housing (Background map: Wikipedia 2018)

penetrate into some rooms deep inside the buildings, as well as into some parts of the T-shaped or H-shaped corridors. The second example of energy-efﬁcient housing comes from Ho Chi Minh City: Eden Villa. This is a new villa, designed exactly in tropical style, with a simple but elegant philosophy of maximising privacy, inside out view and most notably indoor comfort based on daylight and cross ventilation which have been successfully applied to the previous example and even more clearly reflected in this case.

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N

Fig. 3.10 a Aerial view of Mulberry Housing Project (Ha Dong District—Hanoi City) (RSP Architects Vietnam Co. Ltd. 2015). b Master plan of Mulberry Housing Project (Ha Dong District —Hanoi City) (RSP Architects Vietnam Co. Ltd. 2015). c Typical floor plan of Block B—Mulberry Housing Project (Ha Dong District—Hanoi City) (RSP Architects Vietnam Co. Ltd. 2015)

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Fig. 3.11 a Front view of Eden Villa (District 2—Ho Chi Minh City) (Archdaily Journal of Architecture 2017). b Back view of Eden Villa (District 2—Ho Chi Minh City) (Archdaily Journal of Architecture 2017). c Ground floor of Eden Villa (District 2—Ho Chi Minh City) (Archdaily Journal of Architecture 2017). d First floor of Eden Villa (District 2—Ho Chi Minh City) (Archdaily Journal of Architecture 2017). e Solar protection structure of Eden Villa (District 2— Ho Chi Minh City) (Archdaily Journal of Architecture 2017). f Cross section of Eden Villa (District 2—Ho Chi Minh City) (Archdaily Journal of Architecture 2017)

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Fig. 3.11 (continued)

Meanwhile, outdoor comfort can be secured with cooling effect from the swimming pool and shading from the overhang frame covered with creeping plants. Large blind windows protect the upper floor rooms from solar radiation. The building has recently been nominated for a grand award—Archdaily’s Building of the Year 2018 (Figs. 3.9 and 3.11). The level of energy efﬁciency will soon be veriﬁed because just after a few months in operation, the villa has not yet been energy-audited.

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The following solutions are applied to enhance energy efﬁciency: • Cooling with vegetation and evaporation (from the swimming pool at the back); • Maximising daylight and cross ventilation with four elevations open to the private garden, open structure; • Using sun-shading elements on the west façade; • Installing energy-saving lamps and electrical devices.

3.4 3.4.1

Discussion An Open Question: High-tech or Low-tech to Achieve Energy Efﬁciency?

Today, architects in Vietnam will sooner or later have to answer the following two questions: Question 1: Is green building (or energy-efﬁcient housing) just accessible (or available) to high-income people? and Question 2: Do low-income and marginalised/underprivileged groups have any opportunities to own green/energy-efﬁcient houses/apartments? Professionals will soon have to choose between high-tech pathway and low-tech pathway. Both concepts must be developed ﬁrst and foremost on spatial and structural optimisation as a prerequisite condition in design, because no energy efﬁciency will ever be achieved without a good design concept, both architecturally and structurally considered. Then, technical solutions will only play a supporting role. High-tech housing concept means a house or an apartment that must fulﬁl the requirements for sustainability and energy efﬁciency with innovative (and usually expensive) techniques and equipment, such as triple glazed windows, smart double skin, automatically adjustable sun-shading systems or high-performance photovoltaic panels which may increase the housing price to 1,500 or 2,000 USD/m2. These cutting-edge technologies can only be found in many ofﬁce buildings, such as Deutsches Haus (German House) designed by GMP Architekten in Ho Chi Minh City or VietinBank Tower designed by Norman Foster and Associates in Hanoi. In housing, such high-tech solutions have not been applied so far, mainly due to the very high total building cost—so high that very few house owners can afford. Another reason is that most Vietnamese architects are not so competent in high-tech design. Those who have a good and complete understanding of environmental engineering in architecture often graduated with international qualiﬁcations and go abroad to work. Low-tech housing concept, on the contrary, refers to an investigation into planning and building experience of the past and then an adaptation of such traditional experience to modern housing construction will be implemented. This second option proves to be practical, since the solutions are simple but efﬁcient, and most

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importantly not expensive. This is absolutely appropriate for low-income or other underprivileged groups, exactly what Architect Anna Heringer has done for Indian and Bangladeshi people or Architect Diébédo Francis Kéré has helped villagers realise a better community life in the most remote areas in his home country Burkina Faso. Both architects used ecological and locally available building materials, for instance bamboo, wood, earth, stone, straw, etc. with manual building techniques and mobilised local workforce for construction. As a result, the construction did not cost the local communities so much money and they can enjoy nice and new libraries and schools designed in view of environment-friendly and energy-efﬁcient building. In Vietnam, Architect Hoang Thuc Hao has been recognised in recent years as a pioneer in architectural design for the community and honoured with several awards for his contributions to the thriving social development. However, most of his works in this trend are public buildings, not housing. Learning from the past house planning and building experience is an essential part of applying low-tech design to modern building in order to ensure energy efﬁciency as well as sustainability. There are three housing patterns to explore:

Fig. 3.12 a Cross section of a typical traditional shophouse (Old Quarter, Hanoi, Vietnam) with daylight and cross ventilation effects (Graphic: drawn by Quang Minh Nguyen, 2018). b Cross section of a typical colonial shophouse (French Quarter, Hanoi, Vietnam) with daylight and cross ventilation effects (Graphic: drawn by Quang Minh Nguyen, 2018)

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Table 3.6 Low-tech design for thermal comfort and energy efﬁciency learnt from the past housing concepts (Data: analysed by Quang Minh Nguyen, 2018) Solution

Traditional shophouse

Colonial shophouse

Colonial villa

Daylight gain

Through the front side and three to four courtyards Through courtyards and opposite narrow windows Double layer of traditional hand-made rooﬁng tiles

Through the front side and two to three courtyards Through courtyards and opposite narrow windows ∙ Double layer of factory-made rooﬁng tiles ∙ Gypsum-straw ceiling boards (5– 10 cm in thickness) ∙ Roof and/or window overhang ∙ Shutter windows

All four sides (single villa) or three sides (duplex villa)

Maximisation of cross ventilation Thermal insulation for roofs and external walls

Sun shading

Cooling

∙ Roof and/or window overhang ∙ Blinds or bamboo screens Plants and small aquaria in courtyards

Plants and small aquaria in courtyards

Through opposite large windows ∙ Double layer of factory-made rooﬁng tiles with air space underneath ∙ Gypsum-straw ceiling boards ∙ Thick brick wall (33– 45 cm) ∙ Roof and window overhang, front or side corridor ∙ Shutter windows Shade trees and plants with water surface in front and rear gardens

traditional shophouse, French colonial shophouse and French colonial villa, all of which show some eco-features based on simple-but-efﬁcient solutions as follows (Fig. 3.12 and Table 3.6). Morphologically, traditional and colonial row houses can be revitalised in modern row houses and self-built single-family houses as the two most popular townhouses whereas the colonial villa design experience is good enough to be directly transferred to new villas built in the twenty-ﬁrst century.

3.4.2

Is There Another Way?

Another possibility does exit along with high-tech and low-tech housing concepts. It is worth trying to combine the strengths of the two design tendencies. In terms of achieving energy efﬁciency, if a high-tech housing concept seems to be accepted by high-income groups and a low-tech housing concept tends to serve low-income residents, a middle-of-the-road concept (or an in-between concept) should be targeted to middle-class people as a growing population group in most Vietnamese cities. There are many possibilities (scenarios) to propose, with various levels of high-tech and low-tech combination: 90 % + 10 %, 80 % + 20 %, 70 % + 30 %, 60 % + 40 %, 50 % + 50 %, 40 % + 60 %, 30 % + 70 %, 20 % + 80 % and

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10 % + 90 %. It is necessary to explore how the strengths of the two concepts can be maximised, corresponding to each level, and then to recommend a concrete and detailed guideline for each case. This will be very useful to all those who dream of living in a truly sustainable-but-affordable home.

3.5

Conclusion

Vietnam can make full use of the strengths, take the opportunities, self-correct the weaknesses and learn how to avoid the threats in developing energy efﬁciency in urban housing. Apart from low-tech design and high-tech design, a midpoint concept is appropriate and thus preferred, since the strengths of each solution will be combined. This possibility should be investigated for the future housing development.

References Archdaily Journal of Architecture (2017) Eden villa project. https://www.archdaily.com/874585/ eden-villa-xyz-architects. Accessed 10 July 2018 Artemis Project Management Board (2017) Artemis apartment project. http://chungcuartemis.com/ thiet-ke-can-ho-the-artemis/. Accessed 25 June 2017 CapitaLand (2015) CapitaLand ranks top with most number of BCA Universal Design Mark Platinum Awards. https://www.capitaland.com/international/en/about-capitaland/newsroom/ news-releases/international/2015/may/nr-20150514-CapitaLand-ranks-top-with-most-numberof-BCA-Universal-Design-Mark-Platinum-Awards.html. Accessed 10 July 2018 European Chamber of Commerce in Vietnam Ofﬁce (2017) Green Book—Renewable energy, waste, water, green buildings and smart cities: Best practices and solutions for smart and sustainable development in a new era for Vietnam and the EU, Hanoi, pp 10–11 Ministry of Construction (2011) National strategy for urban housing development towards 2020 with vision towards 2030, Hanoi, approved by the Prime Minister with Decision No 2127/ QD-TTg, Hanoi Ministry of Construction (2017) National Energy Efﬁciency Building Code, Hanoi Ministry of Construction (2018) Smart city as the solution to urban issues. http://www.moc.gov. vn/trang-chi-tiet/-/tin-chi-tiet/Z2jG/64/443323/xay-dung-do-thi-thong-minh-giai-phap-chocac-van-de-do-thi.html. Accessed 16 July 2018 Nation Online Map (2018) Vietnam administrative map. http://www.nationsonline.org/oneworld/ map/vietnam-administrative-map.htm. Accessed 10 July 2018 National Assembly12 (2010) Energy Saving and Energy Efﬁciency Law, Hanoi RSP Architects Vietnam Co Ltd (2018) Mulberry Lane project. http://www.rsp.vn/en/project/ detail/mulberry-lane-8.html. Accessed 10 July 2018 Singapore Building and Construction Authority (2014) Third Green Building Master plan, Singapore, p 3. https://www.bca.gov.sg/GreenMark/others/3rd_Green_Building_Masterplan. pdf. Accessed 10 July 2018 Statista (2017) Urbanisation in Vietnam. https://www.statista.com/statistics/444882/urbanizationin-vietnam/. Accessed 30 Nov 2017 UN Habitat Vietnam (2014) Vietnam housing sector, Hanoi, p 63

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Vietnam Association of Architects (2017) Criteria for National Green Architecture Awards. https:// kienviet.net/2014/10/07/infographic-5-tieu-chi-kien-truc-xanh-viet-nam/. Accessed 04 Oct 2017 Vietnam Electricity Corporation (2016) Press release—Abandoning nuclear power plant in Ninh Thuan province. https://evn.com.vn/d6/news/Thong-cao-bao-chi-ve-viec-dung-thuc-hien-Duan-dien-hat-nhan-Ninh-Thuan-66-142-19153.aspx. Accessed 01 Dec 2016 Vietnam Green Building Council (2012). Green building evaluation in housing. http://vgbc.vn/en/ lotus-en/lotus-homes/, http://vgbc.vn/en/lotus-en/lotus-mfr/. Accessed 12 July 2018 Vietnam Green Building Council (2018) Green building database. http://vgbc.vn/en/vietnamgreen-building-certiﬁcation/. Accessed 10 July 2018 Vietnam Institute of Energy (2016) Vietnam Energy Statistics 2015, Hanoi, pp 29–31 Vietnam News (2017) Green is the way to go for housing in Vietnam, 2nd June 2017 Issue Vietnam News (2018) 485,000 kWh of electricity saved during Earth Hour 2018. https:// vietnamnews.vn/society/425090/485000-kwh-of-electricity-saved-during-earth-hour-2018. html#dZwvb3IjWS1rBcuD.97. Accessed 15 June 2018 Vo Trong Nghia Architect (2018) S-House-2 design. http://votrongnghia.com/projects/s-house-2/. Accessed 03 July 2018 Vu Phong Solar Company (2017) Solar energy in Vietnam. https://vuphong.vn/mien-bac-co-phuhop-de-lap-dien-mat-troi-khong/. Accessed 12 Sept 2017 Wikipedia (2018) Vietnam Background map. https://en.wikipedia.org/wiki/Vietnam. Accessed 10 July 2018 World Atlas (2017) The biggest cities in Vietnam. https://www.worldatlas.com/articles/thebiggest-cities-in-vietnam.html. Accessed 24 Oct 2017 World Bank (2015) Affordable housing in Vietnam—A way forward, Hanoi, p 21 World Bank (2018) Vietnam’s urban population. https://data.worldbank.org/indicator/SP.URB. TOTL.IN.ZS. Accessed 22 May 2018 Worldometer (2018) Vietnam population. http://www.worldometers.info/world-population/ vietnam-population/. Accessed 06 June 2018 XYZ Design Saigon (2017) Eden villa project. http://xyzsaigon.vn/eden-villa/. Accessed 10 July 2018

Chapter 4

Recommendations for the Design of an Energy-Efﬁcient and Indoor Comfortable Ofﬁce Building in Vietnam Ngo Hoang Ngoc Dung and Nguyen Trung Kien

Abstract The practice of energy efﬁciency to buildings requires a variety of interdisciplinary actions which are related to aspects of architecture and building services. To ofﬁce buildings, it is more complicated for the fulﬁllment of energy efﬁciency and indoor comfort as such buildings’ designs are normally oriented in a way that creates mechanically air-conditioned spaces. In the context of Vietnam whose climate feature is classiﬁed as of humid tropical zone, the issue may become more serious and there is a need to look for new improvement in terms of architecture- and building service-related activities. The article provides an overview of actual situation of energy consumption and indoor conditions of ofﬁce buildings in major cities of Vietnam, and, from the perspective of architectural and technical design, it gives ideas in aim of improving the energy efﬁciency and indoor comfort applied to the design concept of ofﬁce buildings.

Keywords Building energy efﬁciency Building energy simulation Ofﬁce building design Climatic features of Vietnam

4.1

Problem Statement

The category of ofﬁce building, together with high-rise apartment, have only emerged for around two decades in Vietnam, but the number of ofﬁce projects has been accelerating in major cities namely Hanoi and Ho Chi Minh City in order to meet the large needs of work ofﬁce for agencies and businesses. According to a report by CBRE Vietnam (CBRE Releases 2018), the total leasable floor area in the sector of ofﬁce in Hanoi market is projected to reach 1.4 million sqm. by the end of N. H. N. Dung (&) National University of Civil Engineering, Hanoi, Vietnam e-mail: [email protected] N. T. Kien Vilandco Company, Hanoi, Vietnam e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 E. Motoasca et al. (eds.), Energy Sustainability in Built and Urban Environments, Energy, Environment, and Sustainability, https://doi.org/10.1007/978-981-13-3284-5_4

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2018, with the presence of approximately 190 buildings, and at the same time, another report on the market of Ho Chi Minh tells a fact that total leasable ofﬁce stock had achieved 1.7 million sqm. late 2017, and continue to grow in the next few years after the completion of projects which are now still under construction (Savills Vietnam 2017). The increasing number of ofﬁce buildings inevitably results in a rapid rise in energy consumption of building sector. As an investigation into energy use of ofﬁce building category conducted in ﬁve cities under the framework of Vietnam Clean Energy Program (VCEP), the largest part of energy consumption is for the operation of HVAC systems and ofﬁce equipment. The HVAC accounts for the highest percentage of energy use of the buildings (statistically about 50%), while ofﬁce equipment consume a smaller amount of electricity as it takes up around 24% of total value. (This information is provided by the USAID/Vietnam funded Vietnam Clean Energy Project implemented by Winrock International). The VCEP also presented energy use data by building applications in average EUI value (Energy use intensity, kWh m−2 year), and it indicates that normal building air conditioning EUI is of 50.66 kWh m−2 year, by far higher than that of lighting purpose (only around 19 kWh m−2 year) (This information is provided by the USAID/Vietnam funded Vietnam Clean Energy Project implemented by Winrock International). This breakdown of electricity consumption shows that energy use distribution of ofﬁce buildings in Vietnam is not signiﬁcantly distinguished to those built in other nations of various climatic conditions such as Australia where HVAC system of ofﬁce building consumes an average amount of 50% of total site energy use (Parlour 2000) (Fig. 4.1). The responsibility of large amount of energy use by HVAC system in high-rise ofﬁce buildings can be given to ‘close’ design characteristic which makes whole building isolated and totally environmentally regulated by air conditioner and mechanical ventilation. The survey data published by VCEP also reveals that the

Elevators 11,1%

Air CondiƟoning 47,8%

LighƟng 17,1% Equipment 24,0%

Fig. 4.1 Share of consumed electricity of a typical ofﬁce building in Vietnam (pie chart is created by authors based on data provided by the USAID/Vietnam funded Vietnam Clean Energy Project implemented by Winrock International)

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energy consumption, represented by BEI (building energy index) of the ofﬁce buildings in Hanoi varies from 60 to 170 kWh m−2 year, while ﬁgure for the market of Ho Chi Minh city is in range from 90 to 220 kWh m−2 year (USAID Vietnam

Fig. 4.2 Energy consumption index of popular building categorizes in Hanoi (USAID Vietnam Clean Energy Program 2016)

Fig. 4.3 Energy consumption index of popular building categorizes in Ho Chi Minh city (USAID Vietnam Clean Energy Program 2016)

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Occupant heat

Lighting

Outdoor air leakage

Solar radiation

Heat transferred through envelop

Fig. 4.4 Distribution of cooling load toward a typical ofﬁce building in Hanoi (Tran Ngoc Quang 2015)

Clean Energy Program 2016). Ofﬁce buildings are normally claimed to be a large energy consumer, raking behind only categorizes of hotel, retail and hospital buildings (Figs. 4.2, 4.3 and 4.4). Taken cooling load into a more detailed examination, solar radiation and heat transferred through building envelope are two main contributors in typical ofﬁce buildings in Hanoi (Quang 2015), so it can be seen that building envelope plays crucial role in determining how much energy that building uses for cooling and heating purpose, though these loads are also influenced by technical system and occupancy schedule. Therefore, this chapter focuses its effort on determining optimized design for purpose of energy efﬁciency and indoor comfort of ofﬁce buildings in Vietnam.

4.2 4.2.1

Analysis of Practical Situation and Scientiﬁc Basis for Recommendation Overview of Actual Design Practice for Ofﬁce Buildings in Vietnam

Building envelope. Following the internationalized trend of contemporary architecture, a majority of modern ofﬁce buildings in Vietnam are designed in a way that facilitates air conditioner use and, therefore, are intensively isolated by large amount of curtain and brick wall. A well-identiﬁed feature in the design of these buildings is glassy façade which intentionally provides sufﬁcient daylight level and broadens occupants’ outlook. Turning back to years ago when insulation glass is hardly available, there was merely only choice to furnish external curtain wall with single clear glass which was already proved to be poorly energy efﬁcient. Today, there is an increasing

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chance for insulation glasses that are more available in the market of Vietnam. The better accessibility of hi-tech glass, on the one hand, provides owners and architects with options to select glass material in accordance with aesthetic expectation of façade design, but, on the other hand, causes a fade in tropically strategic design approach due to a conception that high-performance glass can alternate climate-based architecture to move forward energy saving and indoor comfort. This also causes the emergence of a new trend in ofﬁce building design in Vietnam which is not matched to local climatic condition, and inevitably, less energy efﬁcient. Glass-coated envelope probably brings an apparently modern and flashy appearance to ofﬁce buildings, but is unlikely to solve the energy-related issues to reduce greenhouse gas emission. In addition to the glazing, it is important to take the brick wall into consideration of building envelope performance as it affects the amount of heat transferred into indoor space. Other results of surveys showed a fact that only two among eighteen ofﬁce buildings in survey are furnished with insulated walls whose U-value are below the maximum allowed. A similar situation is recorded in major cities of Vietnam where primary material for brick wall is brick-hollow with thickness of 220 m. Such kinds of wall possess heat conductivity which exceeds maximum value of heat transfer U-value (1.8 W m−2 K) as deﬁned in the National Technical Code on Energy Efﬁcient Buildings (QCVN 09: 2017/BXD) (Ministry of Contruction 2017). Only in a few buildings, external walls are structured with additional insolation layers like lightweight foam concrete with a thickness of 330 mm, or insulated block bricks (provided by the USAID/Vietnam funded Vietnam Clean Energy Project implemented by Winrock International). The total heat transfer value of these wall structure is measured to achieve 1.4–1.5 W m−2 K, which perfectly satisﬁes the requirement by building code. Unfortunately, most of the buildings in the examination are not insulated enveloped, and therefore do not meet the insulation requirements deﬁned by QCVN 09: 2017/BXD.

4.2.2

Climatic Basis for Recommendation

Located in the zone bounded by the Equator and North tropic, Vietnam possesses a typical humid tropical climate which, however, uniquely characterized by cold winter resulted from Monsoon. Despite the fact that hot and humid climate is prevailing the whole country, there are still diversiﬁcation between locations due to different topography. From the perspective of climatic classiﬁcation, the country may be partitioned into two main regions as described below (Ministry of Construction: Vietnam Building Code Natural Physical and Climatic Data for Construction QCVN 02 2009): • The North region (from the latitude of 16° upward to the North part) is influenced by unique cold winter when mean air temperature falls down to between 10 and 15 °C;

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• The South region (from the latitude of 16° downward) is prevailed by typical hot weather in a year round. There are no distinct cold and hot seasons, but signiﬁcant difference in humidity is present, causing dry and rainy periods. Rainy season starts from May to October, and it turns dry and mild from November until next April. There is a great deal of sunny hours though the frequency of such state in the North and South regions are slightly varied. Number of sunny hours in the South exceeds 2000 h, while that of the North is below. Mean air temperature of the North normally is around 24 °C, but it hardly falls below, and may even achieves 28 °C in the South. As of tropical climate zone, the solar radiation intensity is always recorded high in all year round, and it reaches an average value of 586 kJ cm−2. Vietnam is characterized by high amount of humidity which often stays at 77– 87%, and it even goes up to maximum level during February and early of March in the Northeast and coastal Central area. It is important to mention an arid hot weather condition which lasts 10 to 30 days and occupies some mountainous parts of Central and North-west areas due to the operation of local Foehn breeze (Table 4.1). It can be seen that most parts of Vietnam’s territory have a hot season with high temperature, requiring heat insulation approach when it comes to the design practice. Despite the fact that several parts of the country are normally influenced by cold winter, it is demonstrated that air temperature during winter time may not be comparable to that of countries located in Europe and Arctic climate zone since the main cause of the local winter is extreme cold breeze generated by North-East Asian monsoon system, rather than existed low temperature background like European countries. Cold-proof techniques should only be taken into the design of buildings in some areas with very cold winters such as the Northeast, the Northwest and Highlands, and primary approach is simply preventing cold air flow coming into occupied spaces of the building. In the actual situation of Vietnam, high-rise ofﬁce buildings are mainly located in urban areas where climates signiﬁcantly differ from mountainous locations. Most of the cities are affected by hot weather condition identiﬁed by high solar radiation intensity while less influenced by cold winter; therefore, cooling by sun-shading and heat insulation approach are considered essential to the climatic design of ofﬁce buildings. In addition, the high value of air temperature and large amount of water vapour in atmosphere causing high level of humidity is another factor to affect the indoor comfort of buildings. A study on psychrometric analysis for majority of Vietnamese cities by Duc Nguyen et al. (2005) shows a long time of the year when humidity exceeds comfort level despite the availability of climatic comfort time in all year round. Therefore, it is still recommended for ofﬁce buildings to be air conditioned for the proper operation of ofﬁce equipment (Fig. 4.5 and Table 4.2). Another study by Nguyen (2013) also reveals that thermal comfort zone can be extended by the practice of natural ventilation, but the presence of a number of

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Table 4.1 Summarizing of climatic features of subregions in Vietnam (Ministry of Contruction: Vietnam building code natural physical and climatic data for construction QCVN 02 2009) Region

Subregion

Location

Features

North (I)

IA

Northwest and areas bounded by Truong Son mountain range

IB

Mountainous Northeast area

IC

Northern plain

ID

South of Northern region and North of Central region

IIA

Coastal area of southern Central

IIB

Tay Nguyen highland

IIC

South region

Most of the area suffers from extremely cold winter when air temperature may falls below 5 °C. It is also influenced by hot arid weather generated by local breeze in summer time, and may witnesses an up to 40 °C air temperature The area possesses by far coldest winter due to its high altitude compared to surrounding. The lowest temperature ever was recorded below 0 °C, but only appeared in several measure points on the mountain It may turn into a milder summer in comparison to North plain, but in valley locations, air temperature may rise to more than 40 °C. In mountainous locations, buildings are recommended to be cold-proof, rather than isolated from heat. Time when heating practice is needed may be extended to 120 days. Humidity value is always high in a year It also suffers a cold winter but less extreme when compared to the region of IB. The variety of temperature and humidity is lower than those of IA and IB regions. The lowest temperature was caught to go below 5 °C, but the highest one may exceed 40 °C The highest temperature may reach 42 °C due to the presence of arid hot weather condition in summer. Heat insulation is an important approach, but cold-prooﬁng should be taken into consideration during winter The area’s climate is generally a typical case of tropic, except a small northern part of it is influenced by slightly cold breeze. Its lowest temperature is hardly below 10 °C, while the highest one normally exceeds 40 °C. Temperature varies slightly between days and nights, and there is no need for cold-proof practice The weather condition signiﬁcantly differs from regions whose altitudes are varied. While higher location may sometimes have cold weather pattern, rest parts of the whole area always suffer from hot summer, and require heat insulation applied to buildings Its climate condition is typically tropical one with annual temperature of high value in all year round. Only two distinct dry and rainy seasons should be mentioned

South (II)

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N. H. N. Dung and N. T. Kien

Air-conditioning needed time

Fig. 4.5 Hourly plot weather data of Hanoi, Danang and Ho Chi Minh city on Building psychrometric chart at standard atmospheric pressure (101.325 kPa) (Nguyen 2013)

Table 4.2 Results of bioclimatic analysis for a number of cities of Vietnam (Duc Nguyen et al. 2005) City

Very cold

Cold

Moderately cold

Comfort

Dry temperate

Humid temperate

Hot

Very hot and humid

Very hot and arid

Ha Noi

0,60

8,60

18,00

44,60

0

23,40

4,50

0,30

0

Vinh

0,20

5,40

18,70

42,01

0

28,64

4,90

0,15

0

Da Nang

0

0

4,53

85,42

0

8,85

1,20

0

0

Nha Trang

0

0

0

99,08

0

0,58

0,34

0

0

Ho Chi Minh

0

0

0,20

79,50

0

16,70

3,50

0,10

0

Can Tho

0

0

0

61,45

0

38,53

0,02

0

0

hours when humidity is beyond comfort level makes it unable to deﬁnitely depend on ventilation without air conditioning. These studies conﬁrm the essence and relevance of air conditioning operation in ofﬁce buildings of Vietnam. The overview of ofﬁce buildings in Vietnam shows the inappropriateness in actual approach to the design of building envelope which increasingly relies on hi-performance glass material in façade while, at the same time, devalues climatic adaptation through passive sun-shading and heat insulation. There is, accordingly, a need for the removal of misconception and re-valuing of climatic-based design approach to envelope structures of ofﬁce buildings in Vietnam.

4.3

Methodology

For a climatic-based design, the estimation of energy use and indoor comfort are valuable to provide stakeholders with comparison of performance between design options, and then help to determine the optimized approach. This practice is

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75

cooperatively supported by simulation software tools which give proper approximation of energy- and comfort-related parameters. In a practical project, simulation tools are important for designers during ﬁrst steps of design to decide physical properties of building facades in terms of energy efﬁciency and indoor comfort, and simulation is an efﬁcient and persuasive way to urge building owners to pursue the pathway of enhancing building performance. In this chapter, simulation-based method is used with a model of typical ofﬁce building in Vietnam, and the results of simulation work are important basis for recommendation in the ﬁnal section of the chapter. The main purpose of the simulation is to give a comparison in terms of efﬁciency and comfort between various options of glazing wall design for the building envelope. By doing so, there will be factors involving brick walls, occupancy and equipment to be kept remained and considered in ideal condition, while alternation of glass materials and the presence of shading device will be tested by simulation. Normally, the simulation work is carried out to the whole building to ensure the highest level of accuracy. However, this will require much energy and time, and become a real challenge to architecture team during conceptual design phase. Therefore, simulation practice in a way that is less effort-consuming is proposed, which selects a typical floor presenting the whole building layout to be examined in the simulation. The result of model simulation for typical floor will be used as the basis for efﬁciency assessment of the whole building. Although there might be a chance for certain errors due to the probable difference between floors, the uncertainty is acceptable in the very early stage of the project. Once a typical floor is selected, it will be partitioned into various thermal zones in accordance with solar heat gained of each façade before energy simulation starts. In the actual context of Vietnamese cities, ofﬁce buildings are normally located in a land lot which has only one primary side accessible from urban streets, and the other sides are adjacent to surrounded constructions. The primary façade of the building is important factor that makes architectural aesthetic, while there is little requirement for secondary sides to be remarkably aesthetic. Therefore, the next step of simulation is to discover an optimized value of window to wall ratio (WWR) for the secondary facades which meet the target of solar heat gain reduction as well as enhancing daylight comfort. The found optimized value of WWR will be kept remained during the next simulation for the determination of best-matched design of primary façade. Various value of WWR on primary façade will be tested with simulation. The performance of each case will be evaluated upon aspects of energy efﬁciency, thermal comfort and lighting comfort, and cost-effective options will be drawn based on the analysis of simulation results. In particular, energy performance is shown by: • Cooling load and heating load which make senses in determining HVAC capacity and investment cost • Total site energy which combines energy use of all building elements and is useful when it comes to the estimation of operation cost.

76

N. H. N. Dung and N. T. Kien

Thermal comfort is assessed upon total number of unmet hours in a year. This indicator reveals how much time the setpoint of indoor climatic condition is maintained by HVAC operation, with permitted uncertainty is 1.1 °C. Lighting comfort is also taken into consideration by useful daylight illuminance (UDI) value which is deﬁned as the annual occurrence of illuminances across the work plane where all the illuminance values are within the range 100–2000 lux (Nabil and Mardaljevic 2005). The method combining analysis of thermal and lighting comfort for optimized envelope design was once mentioned and performed in a study for ofﬁce buildings of cold climate zone in Belgium by (Dartevelle et al. 2011) (Fig. 4.6). The principle of methodology is additionally illustrated by a diagram shown in Fig. 4.7.

Minimizing simulation work to the level of a typical floor

Thermal zone partitioning

Determining optimized WWR, Shading & Glazing type for secondary facades

Making comparison between options of WWR, Shading & Glazing type for primary facade

Energy efficiency/ savings

Thermal comfort

Heating, Cooling load & Total Energy Consumption Fig. 4.6 Illustration of simulation principle

Radiance Temperature

Daylighting comfort

UDI, sDA & ASE

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77

North direction

Fig. 4.7 Sketch of models to be simulated

4.4

Model Simulation of a Typical Ofﬁce Building in Vietnam

4.4.1

Description of Simulation Model

The model represents a typical 20-storey ofﬁce building in Vietnam whose form is in square-box with dimension of 30 30 m. As mentioned in methodology section, the simulation work is performed to only a selected floor number 13, not to the whole building, for further assessment. Floor’s plan layout is arranged in a way that has gained popularity in ofﬁce building category of Vietnam, in which technical

Zone 5- Office common area

Zone 4- Office area

Zone 1- Technical core

Zone 2- Office area

Fig. 4.8 Illustration of typical floor layout and its thermal zone division

Zone 3- Office area

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N. H. N. Dung and N. T. Kien

Table 4.3 Functions and indoor setpoints of thermal zones No

Zone name

Zone type

Input data

1

Zone 1

Lift & Stair (Unconditioned)

2 3 4 5

Zone Zone Zone Zone

Ofﬁce (Conditioned)

Occupancy rate: Illumination: 110 lux Fresh air supply: 0.3 l/s m2 Heating setpoint: Cooling setpoint: Equipments: Occupancy rate: 8 m2/person Illumination: 300 lux Fresh air supply: 6.9 l/s person Heating setpoint: 22 °C Cooling setpoint: 25 °C Equipments: 11 W/m2

2 3 4 5

Table 4.4 Assumption of M&E operation No

System name

System type

Speciﬁcation

1

Lighting

LED

2

HVAC

VRV (with AHU)

3

DHW

Electric resistant

Luminaire type: recessed LPD: 6 W/m2 No lighting control Capacity: autosize COP: 3.3 (for heating and cooling) No heat recovery equipment Capacity: Autosize Efﬁciency: 0.9

core is well laid to behind edge of the building and usable ofﬁce area is located around the core and along the other edges. Plan layout is illustrated in Fig. 4.8. The simulation work will be run with software tool named DesignBuilder v5.4. Representing a real medium-size ofﬁce building, the model is assumed to have main access from an urban street, while its other sides area next to neighbouring constructions. The primary façade is right southward oriented. Information of functions and setpoints for each thermal zone are summarized in Table 4.3, and assumption data of M&E system is shown in Table 4.4.

4.4.2

Simulation in Search for Optimized Value of WWR on Secondary Facades

The ﬁrst simulation is done with variation in value of WWR on secondary facades to determine what optimized WWR on these sides should be. Various values of WWR as 30, 40, 50, 60, 70, 80 and 90% will be applied to three secondary facades, in one case of no shading, and two other cases of horizontal and box-type shading devices. The overhang of shade in any case is 0.5 m. Another assumption is that

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79

glass type is clear single with 3-mm thickness whose SHGC and VLT are of 0.819 and 0.881, respectively. In this simulation, the model is structured with concrete mansory unit whose U-value is 1.204 W m−2 K. This is a well-insulated brick, and deﬁnitely compliant to insulation requirement as deﬁned by regulation QCVN 09:2017/BXD (Ministry of Construction 2017). Roof structure consists of 4 layers with U-value of 1.589 W m−2 K. All data of building elements are shown in Table 4.5 (Figs. 4.9, 4.10, 4.11 and 4.12). The indicators for determination of optimized WWR are value of heating and cooling loads. Simulation results are illustrated by following diagrams. It can be seen from the chart that cooling and heating load will be minimized in case the value of WWR is 30% (illustrated by the blue color lines in the four charts), regardless whether shading is provided. The presence of shading makes the decrease in both cooling and heating loads, and how much these loads can be reduced depends on the sufﬁciency that shading can achieve. Table 4.5 Input data of building elements No

Structure

Orientation

Speciﬁcation

1

Wall

All

2 3

Roof Floor

– –

4

Glazing

East, West and North

250 mm CMU (Plaster/CMU/Plaster) U-value = 1.204 W/m2 K Ceramic tiles/Concrete slab (0.15)/Air gap (0.3)/Gypsum board U-value = 1.589 W/m2 K Single clear with shading (combine 0.5 m horizontal and vertical shading) Varies with and without shading

South

No shading

0.5m overhang

Overhang + sidefins

Fig. 4.9 The dependence of cooling load on the variation of WWR value and shading types in zone 2

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N. H. N. Dung and N. T. Kien

No shading

0.5m

Overhang

overhang

+ sidefins

Fig. 4.10 The dependence of heating load on the variation of WWR value and shading types in zone 2

No shading

0.5m

Overhang +

overhang

sidefins

Fig. 4.11 The dependence of cooling load on the variation of WWR value and shading types in zone 4

To test the dependence of lighting comfort on the amount of window which may have signiﬁcant influence on human behaviour, the indicator of annual sun expose (ASE) will be simulated and used as the basis for the assessment. The ASE is given to describe how much of space is affected by more than 250 h of direct illumination (higher than 1000 lux) per year (Barbara Gherri 2015), which can cause visual discomfort (glare) or increase cooling loads. Simulation results of ASE in the two cases where WWR is of 30 and 90% on secondary facades (North-, East- and West-oriented) are illustrated in Table 4.6.

4 Recommendations for the Design …

No shading

81

0.5m overhang

Overhang + sidefins

Fig. 4.12 The dependence of heating load on the variation of WWR value and shading types in zone 4

Table 4.6 Result of ASE calculation for deﬁned zones while WWR value and shading type vary WWR (%)

Louvre shading

Zone

Area (m2)

ASE area in area (m2)

ASE area in area (%)

30

Yes

30

No

90

Yes

90

No

2 4 2 4 2 4 2 4

214.926 214.926 214.926 214.926 214.926 214.926 214.926 214.926

63.826 66.31 65.138 67.97 46.505 65.58 50.461 52.31

29.7 30.85 30.31 31.62 21.64 47.538 23.48 24.34

It is clear that shading efﬁciently helps to reduce space affected by exceeding 1000 lux illuminance in both zones (down to 29.7 and 30.85%, compared to 30.31 and 31.62% when no shading is available) if the proportion of window remains at 30%. Even if that amount rises up to 90%, shading still works, but the value of ASE is moderately increased by about up to 1.5 times. The results can lead to a conclusion that a reasonably small value of WWR (30%) may only produce sufﬁcient daylight comfort when coupling with efﬁcient shading by reducing indicator of ASE. Therefore, optimized secondary facades will be set with WWR of 30% and with box-type shading devices as input data for further simulation to determine best-matched properties of primary (South-oriented) façade.

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4.4.3

N. H. N. Dung and N. T. Kien

Simulation for Optimized Primary (South-Oriented) Façade

In practice, the WWR for the main façade is often required to be higher than the secondary façades to create aesthetic highlights for the building. However, there are cases where the owner does not require a large ratio of window, so the WWR of 30% can still be possible. In order to assess the impact of WWR on the main façade to the energy efﬁciency, thermal and daylight comfort will be simulated with various WWR values of 30, 50, 70 and 90%, respectively. Heating load, cooling load and total site energy, which is the total energy consumed by all systems and electrical appliances in the building (HVAC, lighting, domestic hot water—DHW) are taken into consideration. Furthermore, thermal comfort is indicated by the number of hours when comfort target set by the air conditioner system (as stated in the setpoint of thermal zones) is unable to meet (Fig. 4.13). Based on the Sun path diagram of Hanoi (latitude of 21oN), and assuming the south face should be completely sunscreened from 8.00 to 17.00 on a daily basis, best-suited typology of shade can be drawn as of horizontal form whose shading mask is overriding illustrated to shade-needed zone in Fig. 4.14. The overhang of shade is supposed to be in the range of 1.5–2 m long for sufﬁcient shading capacity, but is considered a misbegotten form in terms of structure and aesthetic. Therefore, horizontal shade should be alternated with louvres with both overhang and spacing of 0.5 m to maintain shading efﬁciency and to be more technically suited.

Fig. 4.13 Shade-needed zones and mask of shading devices

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83

Fig. 4.14 Louvers with overhang of 0.5 m (on the right) are more technically possible compared to horizontal shade with overhang of 2 m (on the left)

In addition to testing efﬁciency with variation of WWR, different glass options will also be experimented as an effort to discover a combining way of WWR, shading typology and glass category for optimized efﬁciency and indoor comfort. The types of glass tested in the simulation are shown in Table 4.7. Table 4.7 Types of glass in simulation test No

Glazing type

SHGC (g-value)

VLT

U-value

1 2 3 4

Single clear 6 mm Single low-E 6 mm Double clear 6 mm/13 mm air Double low-E clear 6 mm/13 mm argon

0.819 0.72 0.703 0.373

0.881 0.811 0.781 0.444

5.778 3.779 2.665 1.493

Table 4.8 Southward WWR of 30% with no presence of shading

Single clear 6 mm Single low-E 6 mm Double clear 6 mm/ 13 mm air Double low-E clear 6 mm/13 mm argon

Heating load (kWh)

Cooling load (kWh)

Total site energy (kWh)

Unmet hours

UDI

563.60 552.64 547.49

1853.57 1842.55 1836.09

1961942.22 1964013.53 1955673.88

224 223 213

50.42 49.93 49.49

538.42

1816.78

1925459.75

183

46.55

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N. H. N. Dung and N. T. Kien

Table 4.9 Southward WWR of 30% with presence of shading

Single clear 6 mm Single low-E 6 mm Double clear 6 mm/ 13 mm air Double low-E clear 6 mm/13 mm argon

Heating load (kWh)

Cooling load (kWh)

Total site energy (kWh)

Unmet hours

UDI

563.60 552.64 547.49

1842.31 1839.62 1833.47

1924307.22 1926438.95 1921533.14

177 176 176

44.90 45.83 44.68

538.42

1814.90

1905022.92

173

43.15

Simulation results. Following tables show simulation results with variation of WWR, shading types and glass use on primary façade (Tables 4.8 and 4.9). Simulation results for the WWR of 30% also reveal that what glass type is used does not have signiﬁcant impact on loads. In case shading is absence, double low-E glass helps to reduce only 1.9% in cooling load (1816.78 kWh) when compared to the case that it is replaced by single clear glass (1853.57 kWh). A similar outcome is drawn with the presence of louvre-shading. The effectiveness of sun-shading is not only in reducing cooling load but also in decreasing the number of hours in which comfort is not achieved. Speciﬁcally, comfort level generated by single clear glass with shading (only 177 unmet hours) is even higher than that when alternated with double low-E but no sunscreen attached (183 unmet hours). Louvres shading do not much affect the UDI index, as the maximum difference between two cases of with or without sunshade is only 7% (UDI is 50.42% for single clear glass without sunscreen, and is 43.15% for double low-E). The ﬁgures demonstrate the harmlessness of shading to the quality of daylighting. By increasing window ratio to 50%, the demand for cooling, heating and power consumption also increases, and leads to the rise in number of met hours. However, sufﬁcient sun-shading can be used to provide higher thermal comfort with the presence of only single clear glass in comparison with that generated by double low-E but non-sunscreen attached. A similar effectiveness of sun-shading in terms of loads and comforts is also demonstrated when WWR value is adjusted to 70%.

Table 4.10 Southward WWR of 50% with no presence of shading

Single clear 6 mm Single low-E 6 mm Double clear 6 mm/ 13 mm air Double low-E clear 6 mm/13 mm argon

Heating load (kWh)

Cooling load (kWh)

Total site energy (kWh)

Unmet hours

UDI

577.74 560.00 553.38

1883.42 1881.30 1871.88

2000450.67 2009904.95 1995260.14

349 394 363

54.53 55.09 54.80

538.94

1834.03

1949967.36

208

52.27

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85

The simulation results for WWR of 50 and 70% are presented in Tables numbered 4.10, 4.11, 4.12 and 4.13. For the case where WWR rises to 90%, demand for cooling, heating and power consumption is increased to the highest level, and thermal comfort is affected in the most negative way by maximizing number of unmet hours. In this circumstance, effectiveness of low-E glass is most noticeably recognized, and signiﬁcantly more efﬁcient than low insulated glass. The most common case is the smaller WWR. However, the simulated results in Table 4.14 show that low-E glasses exhibit signiﬁcantly lower thermal and thermal efﬁciency than glass in a single layer. Whereas, if the amount of window on the southern façade is of a much smaller value, energy savings generated by low-E is only slightly differentiated from that resulted from single clear glass. For example, if double low-E glass is applied to the Table 4.11 Southward WWR of 50% with presence of louvers

Single clear 6 mm Single low-E 6 mm Double clear 6 mm/ 13 mm air Double low-E clear 6 mm/13 mm argon

Heating load (kWh)

Cooling load (kWh)

Total site energy (kWh)

Unmet hours

UDI

577.74 560.00 553.38

1879.83 1875.98 1867.14

1939858.67 1945754.71 1937889.82

185 186 185

52.00 49.99 51.72

538.94

1830.66

1913870.81

175

52.36

Table 4.12 Southward WWR of 70% with no presence of shading

Single clear 6 mm Single low-E 6 mm Double clear 6 mm/ 13 mm air Double low-E clear 6 mm/13 mm argon

Heating load (kWh)

Cooling load (kWh)

Total site energy (kWh)

Unmet hours

UDI

590.37 566.60 558.88

1910.06 1908.14 1895.94

2030828.39 2051394.22 2030291.04

499 534 491

58.07 57.59 57.64

539.39

1849.48

1973661.07

286

57.67

Table 4.13 Southward WWR of 70% with the presence of louvers

Single clear 6 mm Single low-E 6 mm Double clear 6 mm/ 13 mm air Double low-E clear 6 mm/13 mm argon

Heating load (kWh)

Cooling load (kWh)

Total site energy (kWh)

Unmet hours

UDI

590.37 566.60 558.88

1905.48 1901.27 1889.99

1954735.92 1967257.47 1955164.61

174 178 183

56.00 56.15 57.37

539.39

1845.07

1925467.46

183

56.82

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N. H. N. Dung and N. T. Kien

Table 4.14 Southward WWR of 90% with no presence of louvers

Single clear 6 mm Single low-E 6 mm Double clear 6 mm/ 13 mm air Double low-E clear 6 mm/13 mm argon

Heating load (kWh)

Cooling load (kWh)

Total site energy (kWh)

Unmet hours

UDI

601.71 572.67 564.00

1934.55 1933.38 1898.85

2054129.33 2088454.08 2008734.47

617 678 418

62.24 59.46 60.10

539.78

1873.13

1996217.55

377

58.63

South façade whose windows take up to 90%, its corresponded cooling load falls by 3% to 1898.85 kWh when compared to that generated by single clear glass (1934.55 kWh), and number of unmet hours contemporaneously decreases by 39% to 377 h. Similarly to cases where the smaller WWR value is applied, shading still provides efﬁciency and indoor comfort even if window ratio is increased to 90%. More noticeably, the number of unmet hour when southward façade is furnished with only single clear glass with shading is (161 h) by far reduced by 74% if no sunscreen is attached (617 h). This also generates a total energy consumption of 13% lower than in the case that double low-E is applied but no sunscreen is attached. Through simulation, it is possible to blame energy loss, inefﬁciency and discomfort in summer for large amount of glazing wall though it may generate an increase in UDI. In condition of North region of Vietnam where cold winter lasts for at three months (taking up to 8.6% of the year time Ministry of Construction: Vietnam Building Code Natural Physical & Climatic Data for Construction QCVN 02 2009), glazing wall is also a contributor to the heat loss for heating operation. A study on the influence of glazing use upon energy efﬁciency by Nguyen Van Muon (Nguyen Van Muon 2015) demonstrates a fact that in all cases of climate condition, large window wall holds main responsibility for energy loss of HVAC system. Low-E glass is useful to reduce loads in both summer and winter, and at the same time reduces the number of unmet hours, but its effectiveness is strongly noticeable in case large amount of glass is incorporated in building façade (WWR of such 70 and 90%). In the case of relatively small value of WWR (30%), the influence of glass on loads and energy use is negligible. Solar shading is the key factor to achieve high performance and indoor comfort regardless how insulation level of glass, which brings an opportunity to replace costly hi-tech glass with more economical one for better savings on investment cost. In a tropical climate condition characterized by high intensity of solar radiation of Vietnam, envelope shading is extremely important and brings about clear opportunity of energy saving and reducing discomfort time. Unlike misconception by a group of project developers, sun-shading does not affect illuminance comfort

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as UDI values still remain reasonable even though it is slightly lower than that in replace hi-tech insulation glass with conventional single glazing while still ensure energy performance.

4.5 4.5.1

Recommendation Recommendation for Energy-Efﬁcient Building Envelope

Building envelope plays a crucial key to energy performance and indoor comfort of a building. Under climate condition of Vietnam, there is always a need for intensive insulation to envelop structure of all building categories, and especially important to high-rise ofﬁce buildings. As a useful approach, reducing solar heat transferred through curtain walls will help to lessen cooling loads on HVAC system, and therefore save more on energy cost. Additionally, insulation for brick walls is also essential for a more efﬁcient design of building envelope. Curtain wall. It is strongly recommended that secondary facades which are not mandated to be aesthetically satisﬁed that the value of WWR should not be set exceed 30% to ensure small cooling load on HVAC and sufﬁcient indoor comfort. However, the value of WWR for primary façade can be differentiated from secondary ones, letting the index reach up to 90% as a way to highlight building’s architectural features, but passive shading by louvres or best-matched shading devices in combination with low-E high-performance glass is always advisable for better energy savings and indoor comfort. In case of modest investment cost, there might be a possibility to replace hi-tech glass with single clear glazing wall, but sufﬁcient shading is always recommended. Low-E glass is obviously effective in terms of insulation, but large proportion of low-E glass without shading on building façade will cause heat loss through envelope as well as thermal and daylight discomfort by increasing number of unmet hours and level of discomfort glare. Incorporating a large amount of glazing wall into building façade without shading is never an effective way to enhance building performance and indoor comfort under the condition of tropical climate of Vietnam. In case that glazing window takes up a rather small part of the façade (WWR = 30–40%), it might be more cost-effective to replace low-E with double, or even single glass while, at the same time, still remain energy efﬁciency and indoor comfort if shading devices is incorporated. Brick wall. Part of brick wall is also factor that affects energy consumption, and therefore should be well-structured to reduce its heat transferred value (U-value). It is advisable to select light-weighted porous concrete unit or multilayered wall structure whose thermal resistant is sufﬁcient to meet the insulation requirement for external walls deﬁned by the National regulation on energy-efﬁcient buildings (QCVN 09:2017/BXD).

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Additional Technical Measures to Enhance Building Energy Performance and Indoor Comfort

In addition to building envelope, the M&E equipment also plays an important part in the determination in energy end use of building. Upon the existing model which is shown in Table 4.15, extra simulation is performed with alternation of HVAC and lighting system whose COP and LPD vary. The result of simulation work with various values of COP and LPD reveals that saving level can be improved when more efﬁcient HVAC (high value of COP) and lighting system (lower value of LPD) are combined with architectural approach (Tables 4.16 and 4.17). Another recommendation in an effort to take advantage of climatic beneﬁts and reduce energy use of air conditioner is to operate the building in a mixed mode. This means the air conditioning system may be automatically adjusted in accordance with outside atmosphere state so that only AHU is in operation (no cooling mode) if outside air falls below setpoint which is already mentioned in the section of input data description. It is possible for the idea to be turned into reality as majority of Vietnamese cities have at least about 40% of the time (Duc Nguyen et al. 2005) in a year when the weather condition is in comfort situation. The simulation results show the total site energy use may decrease by 10.88% to approximately 1755695.01 kWh when only mix-mode is operated, and if all suggested efﬁciency measures are taken into buildings, saving levels will go up to 36%, making a fall in energy use to only 1245193.35 kWh.

Table 4.15 Southward WWR of 90% with the presence of louvers

Single clear 6 mm Single low-E 6 mm Double clear 6 mm/ 13 mm air Double low-E clear 6 mm/13 mm argon

Heating load (kWh)

Cooling load (kWh)

Total site energy (kWh)

Unmet hours

UDI

601.71 572.67 564.00

1929.10 1925.03 1911.27

1970082.09 1990947.14 1973919.08

161 170 174

58.16 57.30 58.65

539.78

1858.68

1939468.15

185

59.24

Table 4.16 The dependence of energy savings on COP COP

3.3

3.6

3.9

4.2

4.5

4.8

Total site energy

1970082.09

1909034.61

1857379.05

1813102.86

1774730.16

1741154.05

Savings (%)

0.00

−3.10

−5.72

−7.97

−9.92

−11.62

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Table 4.17 The dependence of energy savings on LPD LPD

6

4.5

3

Total energy Savings (%) With lighting control Savings (%)

1970082.09 0.00 1710778.73 −13.16

1873395.46 −4.91 1677236.88 −14.86

1777362.52 −9.78 1644107.34 −16.55

These tests also demonstrate a great signiﬁcance of coupling climatic-based design of building envelope with high-performance equipment as an attempt to enhance building energy efﬁciency and indoor comfort under climatic condition of Vietnam.

4.6

Conclusion

The physical feature of ofﬁce building envelope is a key factor to determine its energy use and saving, but how the glazing part is treated is even more important. The simulation results prove that large area of sun-exposed glazing wall on ofﬁce building façade is the main contributor to energy loss and energy inefﬁciency in the condition of Vietnamese tropical climate. Therefore, high-rise ofﬁce building is always recommended to be well-shaded by sufﬁcient external shading which may be in form of louvres as well as sideﬁns, though high-performance glass units (normally coated low-E) can be partly used to enhance capacity of solar heat reduction. However, as demonstrated by simulation results, insulation glass does not always provide building with effective insulation, and therefore cannot alternate external shading for more improved insulation and energy performance of building. A sun-shaded building envelope is also an identity of Vietnamese tropical architecture which was once spontaneously internationalized and now needs reviving. In addition to the energy-efﬁcient building envelope, taking advantages of climatic beneﬁts through practice of mix-mode operation is possible and useful to the enhancement of indoor comfort in the climatic condition of Vietnam. This is even more beneﬁcial to occupants’ health when fresh air flow is possibly increased and likely sick building syndrome may be minimized. For a climatic design of an ofﬁce building, simulation tool is useful for the estimation of building energy performance, and it may give designers ﬁrst comparison between options of concept design and then help in shortlisting best-matched approaches. In early stage of the design, the important point is to determine which envelope option can be proceeded based on energy aspect while primary function and plan layout is normally duplicated to a large number of floors in the building, so simulation can be performed with only a typical floor rather than the whole building in aim of time and effort saving. Efﬁciency-related results of the whole building can be deduced from those of typical floor with reasonable modiﬁcation due to the similarities between building floors.

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References CBRE Releases (2018) Quarterly Report Highlights Hanoi Market. http://www.cbrevietnam.com/ Vietnam-Property/pressrelease/cbre-releases-q2-2018-quarterly-report-highlights-hanoi-market Dartevelle O, Deltour J, Bodart M (2011) Coupling thermal and daylighting dynamic simulations for an optimized solar screen control in passive ofﬁce buildings Duc Nguyen P et al (2005) A ministerial research project on bio-climatic database for construction practice in Vietnam Gherri B (2015) Assessment of daylight performance in buildings. WITpress Ministry of Construction (2017) National technical regulation on energy efﬁciency buildings QCVN 09:2017/BXD Ministry of Construction: Vietnam Building Code Natural Physical & Climatic Data for Construction QCVN 02:2009/BXD Nabil A, Mardaljevic J (2005) Useful daylight illuminance: a new paradigm for assessing daylight in buildings Nguyen AT (2013) Doctoral thesis—Sustainable housing in vietnam: climate responsive design strategies to optimize thermal comfort Quang TN (2015) University Research Project—Influence of Building Services System on Building Architecture and Structure Parlour, R.P.: Building services: a guide to integrated design: engineering for architects. Integral Publishing, Pymble, NSW (2000) Savills Vietnam (2017) Reports on HCMC real estate market in Q4/2017. http://www.savills.com. vn/_news/article/31256/157903-0/1/2018/savills-vietnam-reports-on-hcmc-real-estate-marketq4-2017 USAID Vietnam Clean Energy Program (2016) Annual report FY 2016, 1 Oct 2015–30 Sept 2016 van Muon N (2015) Building with large glazed areas—energy killer

Part II

Energy Sustainability Strategies

Chapter 5

Linking Neighborhoods into Sustainable Energy Systems A. T. D. Perera, Silvia Coccolo, Pietro Florio, Vahid M. Nik, Dasaraden Mauree and Jean-Louis Scartezzini

Abstract Improving the energy efﬁciency and sustainability in the urban sector plays a vital role in the energy transition. Hence, it is important to consider promising ways to design sustainable urban energy hubs linking neighborhoods into energy systems. Improving the efﬁciency and sustainability of urban energy infrastructure is a process with multiple steps. This chapter presents the workflow that is required to be followed in this process. A brief overview about the methods that can be used to consider urban climate, urban simulation, and energy system design are presented in this chapter highlighting the crosslinks among these topics. Finally, the chapter presents the research gaps and promising areas to conduct future research. Keywords Energy systems Climate change

Urban energy modeling Microclimate

A. T. D. Perera (&) S. Coccolo P. Florio D. Mauree J.-L. Scartezzini Solar Energy and Building Physics Laboratory (LESO-PB), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland e-mail: [email protected] V. M. Nik Division of Building Physics, Department of Building and Environmental Technology, Lund University, 22363 Lund, Sweden V. M. Nik Division of Building Technology, Department of Civil and Environmental Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden V. M. Nik Institute for Future Environments, Queensland University of Technology, Garden Point Campus, 2 George Street, Brisbane, QLD 4000, Australia © Springer Nature Singapore Pte Ltd. 2019 E. Motoasca et al. (eds.), Energy Sustainability in Built and Urban Environments, Energy, Environment, and Sustainability, https://doi.org/10.1007/978-981-13-3284-5_5

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Introduction

Over 50% of the world population now live in urban areas and this ﬁgure is expected to rise to above 70% by 2050 (ICLEI 2009) when cities will have to accommodate an additional 2.5 billion inhabitants. Energy sustainability at the urban scale is therefore vital. Building stocks will need to be linked to sustainable energy generation sources to a much greater extent, which makes it important to have a detailed understanding of distributed energy demands, potential for on-site power generation using renewable energy technologies, and optimum energy mix between different energy technologies and their interaction within multi-energy networks (refer to Fig. 5.1). Once the energy infrastructure has been designed or upgraded, it is furthermore important to operate it in an optimum way while minimizing the cost and guaranteeing the stability and reliability of the of energy services provided. Each of the aforementioned points corresponds to a separate research problem as shown using different modules in Fig. 5.1. The most challenging part is to maintain the information flow through these boxes in order to arrive at truly sustainable solutions. This chapter presents the “big picture” on how to manage the workflow when combining several models through a computational platform. Developing a computational platform linking different aspects related to urban energy system design and urban planning is a challenging task. We limit the scope of this chapter, to consider only the design process of distributed energy systems and urban energy simulation without further discussing dispatch optimization and

Fig. 5.1 Linking neighborhoods into sustainable energy systems

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energy networks. This chapter elaborates in detail on how to develop a computational platform combining: • future climate conditions and urban climate using regional and urban climate models (Sect. 5.1.1); • assessment of the energy demand of a building stock considering the urban climate and the interaction among buildings (Sect. 5.1.2); • design and assessment of complex urban energy systems considering the wind speed and solar irradiation (Sects. 5.1.3 and 5.1.4); • research gaps in present state are promising pathways to address the present research gaps are discussed in Sect. 5.1.6.

5.1.1

Bringing up Future Climate Conditions for Energy System Design

To make cities sustainable, it is essential to understand and to model urban metabolism, thereby interconnecting the urban energy fluxes that keep a city alive. Urban Building Energy Modeling (UBEM) is a nascent ﬁeld, based on the application of physical models (heat and mass transfer) inside and outside a group of buildings. UBEM predicts buildings’ energy performance, operation of energy systems as well as indoor and outdoor environmental conditions (Reinhart and Davila 2016). Due to the complexity of the urban environment, several data are required for this purpose. These can be classiﬁed into the following three categories: • Climatic data: (i) meteorological data, for a typical year (Remund et al. 2015) or by monitoring and (ii) microclimatic data, as a function of city design. • Outdoor environment: (i) greening (grass and tree), (ii) water bodies, and (iii) albedo and thermal properties of the urban materials. • Buildings: (i) physical properties of the envelope (e.g., U-value of walls and windows, etc.), (ii) function of the building (appliances, occupant density, and proﬁle), and (iii) renovation scenarios • Energy system: (i) available technologies for power generation and storage, (ii) techno-economic data for renewable energy components, and (iii) regulations for grid integration and building related renewable energy integration.

5.1.1.1

Considering the Urban Complexities

Understanding the urban climate conditions plays a vital role when considering both demand and generation. It is already well known that the presence of buildings and other artiﬁcial surfaces signiﬁcantly influences the weather patterns in urban

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areas. For example, the modiﬁcation of the wind speed and the trapping of heat in cities were described in detail by Oke (1967, 1982) as the Urban Heat Island (UHI) phenomenon. The speciﬁc processes driving the urban climate are mostly due to the following: • Trapping of heat (inter-reflections, albedo). • Modiﬁcation of wind patterns (drag and shear forces). • Lack of evapotranspiration. The study of the climatic conditions began with the need to understand air pollutant dispersion in urban areas but has been extended to include outdoor human comfort, energy system design, and building energy use in the recent years. The energy demand of buildings has an obvious relationship with the meteorological conditions (Kohler et al. 2016). Multiple studies have shown the correlation between the two (Ashie et al. 1999; Wang and Chen 2014). There are however some speciﬁcities when looking at the energy consumption of buildings in urban areas. At midlatitudes, the UHI tends to decrease the energy consumption for heating during the winter time while increasing the need for cooling in the summer time. The increase in the summer time will be further exacerbated in the future due to climate change (Mauree et al. 2018).

5.1.1.2

Considering Future Climate and Extreme Climate Scenarios

Climate projections show changes in average conditions of climate and in its variability, including changes in the frequency and magnitude of extreme events, which will be more frequent and stronger in the future (Field et al. 2012). The sustainability and resilience of energy systems and urban areas require estimating the probable future conditions and adapting to them. A large amount of work exists on assessing the impacts of climate change on buildings as the main energy users in cities and urban areas, focusing on different categories of buildings (e.g., de Wilde and Coley 2012; Kalvelage et al. 2014; Shibuya and Croxford 2016), thermal comfort and indoor conditions (e.g., Alves et al. 2016; Barbosa et al. 2015; Fisk 2015), building envelope and retroﬁtting strategies (e.g., Chow et al. 2013; Nik et al. 2012a; Karimpour et al. 2015), energy saving potentials, and building components (Shibuya and Croxford 2016; Nik et al. 2012a; Pakkala et al. 2014). Beyond energy demand, climate change can also affect energy generation, especially renewable generation such as wind (Pryor et al. 2006; Seljom et al. 2011), hydropower (Kao et al. 2015), and solar energy (Fant et al. 2016). Planning for climate change adaptation is complicated since it is difﬁcult to predict the expected degree and pace of warming (The Global Risks Report 2016). Impact assessment of climate change is usually performed by means of the climate data generated by Global Climate Models (GCMs), which simulate future climate conditions for the spatial resolution of 100–300 km2 (Meehl et al. 2007). Direct use of GCMs’ outputs is not recommended due to recognized biases (Fowler et al.

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2007; Prudhomme et al. 2010) and their coarse resolution (outputs cannot be considered as weather). Therefore, GCMs’ outputs should be downscaled to ﬁner spatial (and temporal) resolutions, using statistical or dynamical downscaling methods. One well-known statistical technique is morphing (Belcher et al. 2005) with the drawback of reflecting only changes in the average weather conditions, underestimating climate variations and neglecting extreme conditions. Dynamic downscaling of GCMs by means of Regional Climate Models (RCMs) has the advantage of generating physically consistent data sets across different variables (CORDEX 2016; Giorgi 2006; Samuelsson et al. 2011). The weather data used in this work has been downscaled using RCA4; the fourth generation of the Rossby Centre regional climate model (Samuelsson et al. 2015). RCA4 downscaled four driving models to the spatial resolution of 12.5 km: CNRM-CERFACS-CNRM-CM5, ICHEC-EC-EARTH, IPSL-IPSL-CM5A-MR, and MPI-M-MPI-ESM-LR (which are called CNRM, ICHEC, IPSL, and MPI hereafter, respectively). The driving models are forced by two Representative Concentration Pathways (RCPs) (Giorgetta et al. 2013); the ﬁrst two are forced by RCP4.5 and RCP8.5 and the other two by RCP8.5, resulting in six future climate scenarios in total. Two major challenges in the impact assessment of climate change are dealing with climate uncertainties and large data sets (e.g., Nik et al. 2012b; Nik 2010). It is not possible to rely on short time spans when working with future climate scenarios; periods of 20–30 years should be considered. Moreover, there are different uncertainties that affect the simulated climate data such as the selected GCM, RCM, emissions scenario, and the spatial resolution (Nik et al. 2012b). Hence, a valid impact assessment should consider several climate scenarios and not just a few (IPCC 2007; Kjellström et al. 2011; Christensen et al. 2010; Kershaw et al. 2011). This means that to have a valid energy assessment, several long-term weather data sets should be used, or statistically representative data sets should be generated, considering extreme climatic conditions. Furthermore, it is important to consider the impact of extreme climate on urban microclimate (Fig. 5.2).

5.1.1.3

Impact of Climate Change and Extreme Climate Events on Urban Climate

Several tools have been developed recently to consider the impact of urban climate on the energy demand of buildings and energy generation (especially considering the wind power generation). These tools have been coupled with meteorological models (Krpo et al. 2010; Pigeon et al. 2014; Salamanca and Martilli 2010). However, considerable computational time is required (Martilli 2007) and the horizontal and vertical resolution of these models remains very coarse and hence does not provide the boundary conditions appropriate for building energy simulation models (Garuma 2017; Mauree et al. 2018). Some studies have tried to reduce this gap with the development of models that can provide a link between regional climate models and micro-scale models (Bueno et al. 2013; Mauree et al. 2015,

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Fig. 5.2 Steps followed to consider climate uncertainty and extreme climate events

2017). These connecting models can be used to transform data obtained either from meteorological models or from monitored stations or typical years to a more localized dataset that would take into account the multiple processes in urban areas. Their inclusion has proved to improve accuracy in the simulation of the energy demand (Mauree et al. 2017) and to determine more precisely the peak energy demand, which can signiﬁcantly affect the energy system sizing (Perera et al. 2018). The methods have been used to calculate the energy demand at both the city and the district scale. Both the local meteorological conditions and the energy use were validated using on-site measurement. The developed tools are currently only working with a one-way coupling (Mauree et al. 2018) and hence still need to be improved to provide a better representation and local-scale feedback in meteorological models.

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99

Urban Energy Simulation

Simulating the energy demand at urban scale is a challenging task due to the climate uncertainty and the influence of urban microclimate. The methods used to model the energy demand of a city, can be classiﬁed into two approaches: top-down and bottom-up. Top-down models often use data such as energy demand, CO2 emissions, ﬁnancial aspects, etc., at national, regional or urban scale in order to quantify the energy performance of single buildings or building stocks (Kavgic et al. 2010). In contrast, bottom-up models estimate the energy consumption at building scale or even ﬁner (such as a zone in a building) and extend the model to consider a city, a region, or a country (Swan and Ugursal 2009). Several programs exist to quantify the energy performance of ediﬁces, from the building to the city scale, such as for example CitySim (Robinson et al. 2009), Urban Modeling Interface (UMI) (Reinhart et al. 2013) and SIMSTADT (Nouvel et al. 2015). The main problem when working with these tools is that each urban simulation engine has its own tailor-made data model, and it is quite difﬁcult to make the models communicate with each other. A ﬁrst step to address this issue was the creation of an Urban Energy Information standard such as the Application Domain Extension (ADE) of the CityGML urban information model (Nouvel et al. 2015; Coccolo and Kämpf 2015). The input data for the analyses should be as precise as possible, from the climate to the occupancy proﬁle. They can be categorized into three typologies: (i) Must-have, (ii) Relevant-to-have, and (iii) Nice-to-have. The Must-have (e.g., year of construction, function, refurbishment, and residence type) should be as precise as possible, since if wrongly entered, they cause a major error of up to 30% in the estimation of the energy demand (Nouvel et al. 2017). Similarly, the occupancy proﬁle of the buildings plays a vital role. Normally, the relevant data can only be obtained from a large database of information related to the corresponding building stock, which is not always available. In order to overcome this difﬁculty, a new direction is the use of an archetype, i.e., a geometrical abstraction of the urban environment. Generally, when working with an existing city, all its physical properties need to be known (climate, geometry, building type, etc.) to perform the analyses. By contrast, when working with archetypes (Ratti et al. 2003), the geometry can be simpliﬁed, by modeling a city as a function of the following parameters: (i) Plot Ratio (-), (ii) Site Coverage (%), and (iii) Form Factor (-). By working with archetypes, the computation time required is drastically reduced, which allows a new way to visualize the city’s energy behavior and to generate solutions for sustainable urban design. Optimization of the energy demand of buildings is essential in the planning of a new district and in the choice of renovation scenarios for existing building stocks. The related energy system design process will be discussed in detail in Sects. 5.1.3– 5.1.5. In addition, it is important to consider the influence of building stock on the urban microclimate; especially in the context of outdoor thermal comfort. Urban energy simulation needs to be coupled with energy system design and urban

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Fig. 5.3 Optimization, by new hybrid evolutionary algorithm (CMA-ES/HDE), of the EPFL campus in Lausanne, focusing on the energy demand and the outdoor thermal comfort (Coccolo 2017)

planning in order to link the building stock in an effective way to the energy infrastructure. A holistic design platform combining different aspects is shown in Fig. 5.3.

5.1.2.1

Sustainable Methods to Cater the Energy Demand

Distributed energy systems incorporating renewable energy technologies will play a vital role in the energy transition. Designing such systems for cities is challenging due to the complexity of urban conﬁgurations that influence the wind pattern and solar irradiation, especially with regard to building envelope elements. Both integration of renewable energy technologies at the building scale and energy system upgrading by installing energy storage and energy conversion methods such as heat pumps, etc., are essential in this context. This implies assessment of the renewable energy integration potential at the building scale, energy system design at neighbourhood and urban scale, and assessment of the energy systems at the neighbourhood and urban scale.

5.1.2.2

Integration of Renewable Technologies at the Building Scale

More than one-third of buildings in the EU27, Switzerland and Norway were built before 1960, when no energy saving policy was in place (Nolte and Strong 2011). To achieve a Nearly Zero annual energy balance, energy needs must be diminished and matched with distributed renewable energy generation: this will reduce energy distribution dispersions and increase awareness, by transforming energy consumers into energy “prosumers”. Building envelopes, when appropriately equipped, can become active and generate energy: as such, envelope surfaces constitute an important resource for an effective transition to renewables. Thermal energy can be produced from Building-Integrated Solar Collectors (BIST) and electricity from Building-Integrated Photovoltaic modules (BIPV), when there is satisfactory solar

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radiation unshaded by the surroundings: the suitable envelope area for solar collection corresponds roughly to 60% of roof areas and 20% of façade areas (IEA 2002). The scientiﬁc literature suggests that up to 50% of low and medium temperature heat in Europe could be delivered by solar thermal technology by 2030 (ESTTP 2009). PV modules could cover between 15 and 60% of the electricity demand in IEA countries. More than half of this capacity is expected to be installed on buildings by 2050 (IEA 2014), helped by the continuous reduction in price of PV technologies (Zhang et al. 2014). In addition, a small amount of renewable electricity may be generated by Building-Integrated Wind Turbines (BIWT), which can provide up to 15% of the electricity demand of a single building (Bošnjaković 2013). The renewable energy potential can be assessed at the territorial scale and reﬁned further to the scale of a single building. The solar energy potential is usually calculated from the solar radiation impinging on a given surface multiplied by its conversion efﬁciency into useful energy (Fath et al. 2015): depending on the technology and on the external air temperature, solar collectors convert up to 80% of solar radiation into thermal energy and PV modules convert up to 22% of solar radiation into electricity (Probst and Roecker 2012). Solar radiation is usually measured in meteorological stations then modeled according to expected shading, tilt from the horizontal plane and azimuthal orientation of the target surface. Wind energy potential, on the other hand, depends on wind velocity as well as on tip-speed ratio and pitch angle as a function of the turbine type (Campos-Arriaga 2009). Wind speed, like solar radiation, is measured in meteorological stations and evaluated through speciﬁc fluid dynamics models.

5.1.3

Integrated Energy Systems Based on Renewable Energy Technologies

Integrated energy systems such as energy hubs, smart microgrids, etc., are getting popular as a method to integrate larger fractions of non-dispatchable energy technologies such as solar PV and wind energy (Perera et al. 2015, 2016, 2017a, b; Guen et al. 2018; Kuehner et al. 2017). It is essential to keep a good balance between renewable energy technologies, energy storage and dispatchable energy sources (Perera et al. 2012, 2013a, b). Hence, a number of different optimization methods have been proposed to design distributed energy systems using various methods (Connolly et al. 2010). In addition to design optimization, it is important to locate the energy system considering the distributed energy demands and opportunities for on-site power generation (Max Bittel et al. 2017). Finally, the energy system should be operated considering the variations in demand, renewable energy potential and grid conditions (Timothée et al. 2017). However, so far, the main focus has been on the optimization of the energy system.

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Incorporating building-integrated energy technologies into the energy infrastructure and planning energy efﬁcient cities combining both urban planning and energy system optimization are challenging tasks. This is mainly due to insufﬁcient information available for urban energy simulation and the fact that extensive computational resources are required for simultaneous optimization of the building stock and the energy system. The process becomes even more difﬁcult due to the impact of the microclimate on the energy demand and generation. A detailed computational platform combining urban climate, building simulation, and energy system optimization would be helpful as suggested in Mauree et al. (2018), Perera et al. (2018). However, the best solution for optimizing urban conﬁguration and energy system design is likely to be a simpliﬁcation of both urban simulation and energy system optimization parts. Urban archetypes can be used to represent the complex urban morphologies (Ratti et al. 2003) (as suggested in Sect. 5.1.2) while meta-models can be used to simplify the optimization process as suggested by Perera et al. (2017), Fig. 5.4.

5.1.4

Assessment of Distributed Energy Systems

Urban energy planning is a broad subject which does not end with optimization. According to Manfren et al. (2011), it consists of ﬁve major phases starting with the collection of basic data, their preprocessing, and energy system design. Once the energy system has been designed, it is important to go through a post-processing phase, evaluating aspects related to energy efﬁciency, economy, environmental

Electricity Demand of the Appliances SPV Panels Wind Turbines

Dense building stock City center

Internal combusƟon Engine

Less dense building stock Periphery

Detailed informaƟon (at the building level) about building stock

AbstracƟng the building model using architypes

Energy system designing problem

Fig. 5.4 Developing a computational platform for the planning of energy sustainable neighborhoods

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Fig. 5.5 Steps to be followed in urban energy planning. The process begins with identifying the energy demand and energy potentials for renewable energy technologies. Subsequently, energy system is designed considering several objective functions. The set of Pareto solutions obtained from the Pareto optimization is ranked based on the priorities and design requirements of the application

impact, and social acceptance as suggested in Fig. 5.5. A number of different methods have been proposed to carry out this task, which will ideally be combined with an impact assessment including a life cycle assessment and local DG planning. Developing design tools to optimize energy systems considering urban context is important. However, post-processing and impact assessment phases should not be neglected in order to complete the process. Combining the design and the post-processing phase is always challenging, especially when trying to come up with the ﬁnal system design. Multiple criteria need to be considered simultaneously in the process. This is where multi-criterion decision-making comes into play. Different methods based on Fuzzy TOPSIS, Analytical Hierarchical Process, etc., can be used (Perera et al. 2013, 2017).

5.1.5

Social Acceptance for Renewable Energy Integration

The deployment of building-integrated renewables is conditioned by their social acceptance, resulting from the local urban context (Probst and Roecker 2015) (Fig. 5.6). This usually cannot be controlled through a linear relationship as explained in Fig. 5.6. A fundamental influence on social acceptance is location-speciﬁc socio-cultural sensitivity, linked with the historical development of the buildings and their appearance, as well as the cultural and vernacular heritage they represent. Other relevant aspects are the traditional space use made by the citizens, the presence of symbols, icons, landmarks, monuments or institutions in which inhabitants reflect their habits, the common predilection, and diffuse well-being for that place. Sensitivity depends also on the resilience of the built environment to the intrusion of renewable systems and the capacity to accumulate their proliferation without losing value: residential and industrial areas are typically

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Fig. 5.6 Example of comprehensive solar development planning, considering social acceptance in relation with its various parameters: Hollande district, Geneva Switzerland. From bottom to top: (i) urban sensitivity issued from land use; (ii) visual interest inferred from a census of remarkable viewpoints or crowd-sourced photographs; (iii) annual solar radiation on a gradient color scale; (iv) visibility of envelope surfaces from the public space; (v) resulting integration strategy: standard modules on non-visible surfaces and high-end products on visible surfaces

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less sensitive than historical settlements. The level of coherence of renewable system designs within existing buildings is determined in relation with (i) the system size, position, and layout; (ii) the visible materials, including textures and colors; (iii) the modular pattern of the single elements composing the array; and (iv) the connections and joints between the system components. Such features can be summarized with the designation of overall system quality (Probst and Roecker 2011). Another relevant factor for social acceptance is the visibility of the renewable systems from the public space. This depends on the visual interest of the zone linked with the number of potential observers, the nature and duration of their viewing experience as well as with the scenic attractiveness of the urban landscape: for instance, visual interest can be assessed by observing the distribution of photographs on a territory (Florio et al. 2017). Beyond this social component, visibility depends also on the impact of the renewable systems on the visual ﬁeld of potential observers, influenced by the local topography, the physical features of the system and its surrounding elements as well as the meteorological, atmospheric, and lighting conditions. It should not be forgotten that building envelopes represent the visible interface of buildings exposed to the public space. Visibility assessment methods of envelope surfaces that could host renewable energy generation plants are needed in the planning or predesign phase, knowing that solar technologies can be coplanar with the relative envelope surface, which is seldom the case for wind turbines. These methods include viewsheds and bi/tridimensional isovists, which identify the surfaces that can eventually be visible from the public space and the number of viewing locations (Hurtado et al. 2004; Fernandez-Jimenez et al. 2015). A ﬁner estimation, providing a magnitude scale of visibility, is constituted by indicators based on solid angles, computing the projection of target surfaces on a spherical ﬁeld of view (Minelli et al. 2014; Rodrigues et al. 2010). In addition, psychophysical considerations on visual acuity can improve assessment methods based on perceptual evidence (Florio et al. 2016). As an alternative, virtual, and augmented reality environments allow immersing observers in a simulated renewable project and tracking their interaction on a computer appliance (Lizcano et al. 2017).

5.1.6

Conclusions and Future Perspectives

This book chapter provides the “big picture” on different important aspects that need to be considered when linking buildings with sustainable energy technologies. It highlights a number of different challenges related to determining energy demand and renewable energy potential in urban context and promising paths to overcome them. Combining the energy system design process and urban planning in order to reach toward energy sustainable neighborhoods is a multi-faceted task. A computational platform that combines several modules related to urban climate, urban simulation, and energy system optimization would be beneﬁcial. However,

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there will always be the difﬁculty of maintaining the information flow. Finally, this chapter has highlighted the importance of assessment of energy infrastructure beyond the design process of energy efﬁcient neighborhoods or districts. Social acceptance of renewable energy integration plays an important role, which might well be beyond the level of control of urban planners or energy system designers.

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Chapter 6

Future Weather Data for Dynamic Building Energy Simulations: Overview of Available Data and Presentation of Newly Derived Data for Belgium Delphine Ramon , Karen Allacker , Nicole P. M. van Lipzig, Frank De Troyer and Hendrik Wouters

Abstract As buildings have a relatively long life span, it is important to consider climate change in energy performance modelling. Good quality weather data are needed to obtain accurate results. This chapter discusses widely used methods to predict future weather data (dynamical downscaling, stochastic weather generators and morphing) and provides an overview of available weather datasets (multi-year, typical years, extreme years and representative years) for building simulations. A Flemish ofﬁce building is used for a comparative analysis of the estimated heating and cooling load making use of 1-year weather ﬁles (typical and extreme future climate conditions) derived from a recently developed convection-permitting climate model for Belgium. Climate models and weather generators are identiﬁed as the most preferred for the estimation of the average energy consumption and thermal comfort in average and extreme situations. Climate models have the advantage to better represent extreme weather events and climate differences due to territorial settings, while weather generators can generate multiple climate realizations. A combination of a typical year with an extreme cold and extreme warm year was found to result in an overall good representation of the energy need for heating and cooling in average and extreme weather conditions. Further, the influence of the methodological choices to extract 1-year weather ﬁles (typical or extreme years) from the 30-year climate data is highlighted as different results were

D. Ramon (&) K. Allacker F. De Troyer Faculty of Engineering Science, Department of Architecture, KU Leuven, Louvain, Belgium e-mail: [email protected] N. P. M. van Lipzig Faculty of Science, Department of Earth and Environmental Sciences, KU Leuven, Louvain, Belgium H. Wouters Faculty of Bioscience Engineering, Department of Forest and Water Management, UGent, Ghent, Belgium © Springer Nature Singapore Pte Ltd. 2019 E. Motoasca et al. (eds.), Energy Sustainability in Built and Urban Environments, Energy, Environment, and Sustainability, https://doi.org/10.1007/978-981-13-3284-5_6

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obtained when different meteorological variables were considered for the creation of the 1-year ﬁles.

Keywords Future weather ﬁles Climate modelling Built environment Convection-permitting climate model Typical year Extreme year

6.1

Introduction

People spend a lot of time in buildings protecting them from the outdoor weather. These buildings are affected to an important extent by the local weather. The heatwave of 2003 caused thousands of excess deaths in France only (Vandentorren et al. 2006), and indoor thermal discomfort is considered as one factor in this excess of deaths. Towards the future, an increase in temperature is expected and in particular an increase in frequency of heatwave periods (Wouters et al. 2017; Kovats et al. 2014; Berger et al. 2014). Heatwaves are also becoming more severe in urban areas due to the urban heat island effect (Wouters et al. 2017), likely leading to comfort and well-being problems for occupants at a regular base and/or to an increase in electricity consumption for active cooling (Crawley 2008). In the past decade, various researchers worldwide investigated the impact of climate change on the building energy performance (Berger et al. 2014; Andrić et al. 2017; Shen 2017; Shibuya and Croxford 2016; Kershaw et al. 2011; Brotas and Nicol 2017; Chow and Levermore 2010; de Wilde and Tian 2010; Farrou et al. 2014; Holmes and Hacker 2007; MBE KTN 2013; Nik and Sasic Kalagasidis 2013; RICS 2015). Buildings should be resilient to these climate changes without leading to comfort issues or structural damage. To investigate the performance of a building in a context of climate change, the full life cycle of the building should be considered. In order to predict the building energy performance in future, two crucial aspects are needed: (1) an appropriate energy simulation model that can accurately predict building performance and (2) good quality future weather data. Three types of building energy simulations are currently used: static, semi-dynamic and dynamic simulations. In a dynamic energy simulation, a thermal balance is calculated for each time step of the simulation. Based on this balance, the heating and cooling demand as well as the thermal comfort can be deﬁned. The thermal balance takes into account internal heat gains (people, appliances, lighting, etc.), outside weather conditions and the building characteristics (thermal capacity, insulation level, heating and cooling systems, etc.). The interaction of these parameters and their hourly variations are hence considered. A static energy simulation does not take into account all these dependencies or time variations. For example, to calculate the monthly heating demand in static simulations, monthly average temperatures are used. Static energy simulations hence allow to assess the average energy performance of a building (in a rather rough way), but do not allow to determine the thermal comfort as the latter requires hourly data and as the variance of the different elements (e.g. internal gains and solar gains) of the thermal balance

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gain importance. Similarly, this variation is important to investigate a building in extreme weather conditions, e.g. when investigating peak energy demands or thermal discomfort. Semi-dynamic simulations take a shorter time step, e.g. instead of monthly average temperature and solar gains, hourly temperature, hourly direct and indirect solar gains for an average day of each month. For these reasons, dynamic building simulations are more appropriate to assess building resilience towards climate change. Dynamic energy simulations require weather data with at least hourly values, using, for example, an epw format (EnergyPlus 2016). These weather ﬁles typically contain information about temperature, radiation (direct and diffuse), wind (direction and speed), rain, snow, humidity and pressure. In addition, it includes among others location-related information such as time zone, elevation or average ground temperatures (EnergyPlus 2016). Depending on the goal of the building energy simulation, weather data should contain information about different weather conditions. If the simulation aims at investigating the overall energy consumption or thermal comfort, weather data representing the typical weather conditions is needed (Barnaby and Crawley 2011; ASHRAE 2017). However, if the aim is to assess the energy consumption or thermal comfort in extreme conditions (i.e. extremely hot or cold), weather data representing those extreme conditions are required (Barnaby and Crawley 2011; ASHRAE 2017). A combination of typical weather data and extreme weather data in one representative dataset could combine both assessments in one simulation (Nik 2016). To size HVAC systems design days or short periods are used (Barnaby and Crawley 2011; ASHRAE 2017). When aiming at climate resilient buildings, future weather data are needed. In order to take into account the inherent uncertainties of climate change, it is important to consider the various possible climate realizations (IPCC 2013). In the past years, appropriate weather data for the assessment of buildings under climate change have been researched (Jentsch et al. 2008, 2013; Jones et al. 2010; Levermoreet al. 2014; Nik 2017; Eames et al. 2011; Struck et al. 2009; Chan 2011; Liu et al. 2016; Narowski et al. 2013). Several future weather ﬁles/datasets and methodologies have been developed. The ﬁrst methodological option is to use a weather ﬁle from a different location, more speciﬁcally from a location which currently has similar climate conditions as expected for the building location in the future (analogue scenario method) (Belcher et al. 2005; CIBSE 2009). The second option, often used in practice, is to select a year from the past that is warmer than normal to represent the future climate. Third, general circulation models (150– 600 km spatial resolution (IPCC 2013; Jacob et al. 2014)) taking into account future climate scenarios can be used. To be useful for building simulations, downscaling to a relevant spatial resolution for building simulations is needed, e.g. by dynamical downscaling, interpolation, stochastic weather generators or morphing (Belcher et al. 2005; Wilby and Wigley 1997). This paper aims at providing insight in the various methods to predict future weather data and in the available weather datasets appropriate for the Belgian context. The aim is moreover to present recently developed data based on dynamical

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downscaling of regional climate models for Belgium and to show their potential to be used in building simulations through a comparative analysis with other datasets (e.g. representative) extracted from these models. The chapter is structured as follows. In Sect. 6.2, widely used methods (Sect. 6.2.1) and available datasets (Sect. 6.2.2) are presented, and their appropriateness to predict the building energy performance in a context of climate change (Sect. 6.2.3) is discussed. In the latter section, the appropriateness is linked to the speciﬁc simulation goal (heating and cooling demand, thermal comfort evaluation) excluding building simulation for sizing of HVAC. Section 6.3 presents the newly developed future weather data and compares these with other weather datasets extracted from these data. The weather data are moreover applied in the energy simulation of a simple case study (ofﬁce building). The ﬁnal section discusses the outlook for weather data and their requirements to assess buildings in the context of climate change.

6.2

Future Weather Data Methods and Data Formats

This section provides an overview of currently available future weather data types. A three-step approach is followed. First, an overview is given of methodologies to obtain future weather data. Second, various weather datasets for building energy simulations are discussed. Finally, the advantages and limitations of the various methods and formats, linked to a certain energy simulation goal, are summarized.

6.2.1

Future Weather Data Methodologies

As discussed before, the analogue scenario method and the selection of a warmer year from the past can be used for building simulations in a future climate context. However, the important role of solar radiation makes it hard to ﬁnd suited weather ﬁles as this depends on the latitude of the location. Moreover, the change of solar radiation seems rather small in current climate change scenarios. Further, both methods assume similar weather behaviour in future as to date while it is expected that frequency of events (e.g. heatwaves) will change in time (Wouters et al. 2017; Kovats et al. 2014; Berger et al. 2014). Therefore, these are not further discussed in this chapter. Ongoing research about future weather data for building simulations typically use of General Circulation Models (GCMs) to gain insights into future climate behaviour (Jentsch et al. 2008, 2013; Jones et al. 2010; Levermore et al. 2014; Nik 2017; Eames et al. 2011; Struck et al. 2009; Chan 2011; Liu et al. 2016). This type of climate models simulates the state and evolution of the atmosphere, including the atmospheric circulation and energy exchanges in terms of radiation, heat and

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moisture. They also simulate the processes related to cloud formation and precipitation, and take into account the interaction with the ocean and the land (IPCC 2013). Climate models are typically used to construct possible trajectories of the future climate. These trajectories particularly take into account the radiative forcing established by the emission of greenhouse gas and aerosols from human activities and natural processes. The most well-known emission scenarios are the Representative Concentration Pathways (RCPs) used by the Intergovernmental Panel on Climate Change (IPCC). They comprise four scenarios, namely, RCP2.6, RCP4.5, RCP6.0 and RCP8.5, which are named after radiative forcing established by the greenhouse gas emissions in the year 2100 relative to pre-industrial values (+2.6, +4.5, +6.0, and +8.5 W/m2, respectively) (Moss et al. 2008). Climate models are also used for studying the climate of the past, e.g. to provide climate information for regions where observations are not available. It should be noted that climate models are not designed to reproduce the order of consecutive weather conditions, as climate models are not constrained by observations. However, they are capable of representing (multi-)decadal climate statistics, such as the mean or variance of temperature of a particular season, or the frequency or mean intensity of heatwaves. Climate models are available for different time spans (up to several decades) but are usually treated for periods of 30 years as the World Meteorological Organization considers that climate statistics converge over this time span (Brisson et al. 2014). GCMs provide climate information on the global scale with a typical spatial resolution of 150–600 km (IPCC 2013; Jacob et al. 2014). When these models are hence used for building energy simulations, the propagation of climate change and related weather extremes at the local level are not taken into account. This is problematic as many buildings are located in cities and are hence affected by urban heat islands. If to be used for building energy simulations, downscaling of the GCMs is needed. To obtain downscaled weather data from GCMs, Belcher et al. (2005) describe four methods: (1) dynamical downscaling; (2) stochastic weather generators; (3) morphing; and (4) interpolation. Wilby and Wigley (1997) further mention regression and weather pattern methods as additional downscaling techniques. In literature review of ongoing research (Jentsch et al. 2008, 2013; Jones et al. 2010; Levermore et al. 2014; Nik 2017; Eames et al. 2011; Struck et al. 2009; Chan 2011; Liu et al. 2016), the ﬁrst three methods are commonly used to create weather data used in building simulations. These are further discussed in the subsequent paragraphs.

6.2.1.1

Dynamical Downscaling

During the past two decades, GCMs were downscaled to regional climate models (RCMs) by making use of a nesting strategy to obtain climate information at a resolution of 10–100 km. The RCM domain (which covers a smaller region of the

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world) is nested in the GCM domain. The RCM domain with a ﬁner grid resolution is run with the GCM as initial condition. During the model run, the GCM provides the boundary of the domain climate information. Downscaling of GCMs typically results in an ensemble of RCMs where for each model simulation the same radiative forcing scenarios are used (IPCC 2013). This approach, however, results in internally generated climate variability different for each member due to small perturbations of the initial conditions, and hence in different climate realizations in one ensemble. RCMs better represent the regional effects from the orography and the heterogeneity of the soil, vegetation cover and coastal effects. Some of these RCMs were implemented in building simulations by among others Nik et al. (2016, 2017) and Kikumoto et al. (2015). Nevertheless, RCMs do not yet fully resolve urban effects, while deep atmospheric convection needs to be parameterized as well. The latter two shortcomings of RCMs have been recently resolved by further downscaling the RCMs by means of convection-permitting models (CPMs) providing the mesoscale climate information at a resolution of 1–4 km. As such, cities and deep convection become explicitly resolved (Brisson et al. 2016; Wouters et al. 2016; Kendon et al. 2017), and as such, these CPMs allow to take such information into account. CPMs are hence promising for building simulations as they provide a better representation of local climate (change) compared to RCMs (Prein et al. 2015). CPMs require a high computational time and they are typically available for only one or a few realizations of the future climate. As such, CPMs lack information on the uncertainty of the climate change signal stemming from either physical parameterizations or climate variability. They furthermore are only available for a few regions in the world (e.g. Belgium, UK, Alps, Kilimanjaro region, northwestern Paciﬁc Ocean, Sahel regions (Prein et al. 2015)).

6.2.1.2

Stochastic Weather Generators

Stochastic weather generators are deﬁned by Wilks and Wilby as ‘statistical models which can ﬁll in missing data or produce indeﬁnitely long synthetic weather series by simulating key properties of observed meteorological records (i.e. daily means, variances and covariances, frequencies, extremes, etc.)’ (Wilks and Wilby 1999: p. 329). Originally, weather generators were mainly used in the ﬁeld of agriculture (e.g. crop production), climate change studies, hydrology and ecology. Later, several weather generators were developed to generate future weather data to be used in building energy simulations, among others by van Paassen and Luo (2002), RUNEOLE by Adelard et al. (2012) and the UKCP09 weather generator by Eames et al. (2010, 2011). Precipitation is most often the primary variable for the stochastic model of the weather generator (Eames et al. 2011; Herrera 2017). Based on the methodology of Hutchinson (Hutchinson 1987) a two-step approach is applied. In the ﬁrst step, the daily precipitation is modelled based on the current climate data. Based on the fact

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if a day is wet or dry and the weather conditions of the previous day, the other weather variables are generated (mostly temperature and radiation). Parameters such as wind are derived from the latter. Different model parameters for each month are used to include the seasonal variations of the meteorological parameters (Eames et al. 2011; Herrera 2017; Hutchinson 1987). An important advantage of the weather generator methodology is that it allows to integrate the distribution used for the climate change signal and to account for potential changes in weather patterns and climate variability. Some weather generators (e.g. UKCP09 weather generator) furthermore allow to investigate the climate change uncertainty by considering various possible climate realizations (Nik 2017; Eames et al. 2011). Multiple climate realizations can be created by randomly selecting a climate change signal at the beginning of the weather generation (Eames et al. 2011). However, statistical relations between variables as well as distributions are based on baseline data given to the model to generate future data from. Hence, large amounts of data are needed to train the model (Belcher et al. 2005). Further, using stochastic weather generators becomes difﬁcult when statistical relations between meteorological variables are missing in the baseline data because weather events did not happen in that period. The mathematical basis can moreover result in a limited representation and parametrization of climate physics, hence possibly leading to meteorological inconsistencies (Belcher et al. 2005). The weather generator allows a high spatial resolution (e.g. up to 5 km in the case of the UKCP09 weather generator). The climate change signal as such however often has a lower spatial resolution (e.g. 25 km) (Jones et al. 2010). Hence, a spatial variance in the climate change signal in the area of 25 by 25 km caused by territorial settings (e.g. urban versus rural area) is not considered when further downscaling (Wouters et al. 2006, 2017; Berger et al. 2014). With this method, there is moreover no correlation between two time series generated for two adjacent grid cells as a point-based process is used (Jones et al. 2010).

6.2.1.3

Morphing

Belcher et al. (2005) present a methodology for the adjustment of time series towards the future, called ‘morphing’. Current weather data are used as baseline, and monthly climate change signals given by a GCM or RCM are used for morphing the current data. Depending on the climate variable and expression of the climate change signal (absolute, relative), three operations are used to morph data: (1) shifting, (2) scaling and (3) shifting and scaling combined (Belcher et al. 2005). Shifting is applied when the change is expressed absolutely, while scaling is used when a change is relatively expressed. Further, scaling is also used for variables that can be ‘switched off’ (e.g. irradiation). If both the mean and the variance of a variable change over time, shifting and scaling are combined. Shifting changes the mean, while scaling has an influence on the variance of the weather variable.

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Some requirements for baseline weather data were pointed out by Belcher et al. (2005). First, the baseline data should represent the weather conditions for that period. Ideally, the baseline data is averaged data for a period of 30 years (Brisson et al. 2014). Second, as the climate change signal is expressed against a certain period in time, the baseline data used should be representative of the same period. If these periods do not correspond, the generated weather data can under- or overestimate the climate change impact as pointed out by Kolokotroni et al. (2012). Third, as the climate change signal is mostly expressed as a mean change signal, it is important to use averaged weather data as baseline to avoid under- or overestimation. The morphing methodology is used among others by Chan (2011), Kolokotroni et al. (2012), CIBSE (2005) and Ferrari et al. (2008). In the UK, the Climate Change Weather Generator tool (CCWeatherGen tool or CCWorldWeatherGen for outside the UK) was created based on this morphing methodology making use of the HadCM31 GCM for the A2 emission scenario2 (Jentsch et al. 2008, 2013). Multiple studies moreover used this tool for climate change impact studies (Farrou et al. 2014; Kolokotroni et al. 2012; Roetzel and Tsangrassoulis 2012). An advantage of the morphing methodology is the low computational time. Various climate change scenarios can hence easily be applied. An important drawback of the morphing method is that the future weather data have the same character and variability as the current weather data (Belcher et al. 2005) and hence any changes in frequency of (extreme) weather events, although expected (Wouters et al. 2017; Kovats et al. 2014), are not considered. In addition, the mathematical basis of the method results in a limited representation and parametrization of climate physics possibly leading to meteorological inconsistencies (Belcher et al. 2005). This mostly leads to a limited representation of extreme weather events (Herrera 2017). Jentsch et al. (2013) furthermore point out that morphing data with GCMs tends to underestimate the climate change and they recommend to use RCM data for morphing if possible.

6.2.2

Weather Datasets

6.2.2.1

Multi-year Datasets

As mentioned before, climate models are typically multi-year datasets, usually covering periods of 30 years. Also, weather generators can result in multi-year datasets (Eames et al. 2011). The advantage of longer periods of data is the likelihood that they are covering both typical and extreme weather conditions for that

1

Hadley Centre Coupled Model, version 3. Medium-high emission scenario. One of the scenarios before the development of RCP scenarios to be used in GCMs for climate change.

2

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period (Brisson et al. 2014). Such multi-year (30) datasets result in a high computational time if used in building simulations. In order to reduce the computational time, weather data ﬁles for selected years can be developed. In building energy simulation, very often 1-year weather data ﬁles are used, representing typical years or extreme years. Additionally, a combination of several 1-year weather data ﬁles can be used. This is, for example, proposed by Nik (2016) who suggests to use a combination of a typical year, an extreme cold and an extreme warm year. The various types of weather data ﬁles for a selected number of years are discussed in the subsequent sections.

6.2.2.2

Typical Years

Typical years are ﬁctive years consisting of representative typical months (Barnaby and Crawley 2011) which are selected by comparing the distribution of each month with the long-term distribution of that month for the observations available (the Finkelstein–Schafer statistics 1971). When deﬁning a typical year, various meteorological variables can be focused on and various relative importances (weighting factor) can be used for those variables. Various methods (Nik 2016; National Climate Data Center and U.S. Department of Commerce 1976; Kershaw et al. 2010; International Organization for Standardization 2005; Didier and Alfred 2002; Huang et al. 2014; Stoffel and Rymes 1998) exist within this type of weather data, and lead to various weather data ﬁles, such as Test Reference Year (TRY) (European Commission 1985), International Weather year for Energy Calculations (IWEC) (Huang et al. 2014; ASHRAE 2002; Thevenard and Brunger 2002) or a Typical Meteorological Year (TMY) (Didier and Alfred 2002). Typical years are often used to estimate the average energy use of a building (Barnaby and Crawley 2011). Typical years can either be based on observational data or data from a climate model. If these are based on observational data, the period for which the weather ﬁles are created depend on the available observational data for that speciﬁc location. Moreover, the locations for which such weather ﬁles can be derived are restricted to locations where observational data are available. Nevertheless, it is possible to create typical year data for locations without observational data by means of interpolation of the observed data of several relevant other locations. This is, for example, the case for the Meteonorm Typical Years (Meteotest 2017). If typical years are derived from climate model datasets, the amount of typical years for a certain region depend on the spatial resolution of the climate model. The Typical Downscaled Year (TDY) developed by Nik (2017) is an example of a typical year based on climate model data. For Belgium, the existing typical years (Test Reference Year or TRY (European Commission (EC) 1985), International Weather year for Energy Calculations or IWEC (ASHRAE 2002; Thevenard and Brunger 2002) and Meteonorm Typical Years (2017) are based on observational data. These cover at least one decade (Levermore and Doylend 2002; Lee et al. 2010) and are available for three locations

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Table 6.1 Selection of typical years used in building simulation Acronym

Complete name

Weather variables + weights (in %)

TRYa

Test Reference Year (National Climate Data Center and U.S. Department of Commerce 1976; Kershaw et al. 2010; International Organization for Standardization 2005) Typical Meteorological Year (Didier and Alfred 2002)

First step equal weighting of T, R and humidity; second step Wspd

TMYa

IWECa

TDYb WYECa

International Weather Year for Energy Calculations (Huang et al. 2014; ASHRAE 2002; Thevenard and Brunger 2002) Typical Downscaled Year (Nik 2016) Weather Year for Energy Calculations (Stoffel and Rymes 1998; Crawley 1998)

Tmin (5%), Tmax (5%), Tmean (30%), TDmin (2.5%), TDmax (2.5%), TDmean (5%), Wspdmax (5%), Wspdmean (5%), R (40%) Tmin (5%), Tmax (5%), Tmean (30%), TDmin (2.5%), TDmax (2.5%), TDmean (5%), Wspdmax (5%), Wspdmean (5%), R (40%) T T, TD, R, precipitation

Notes (1) T = dry-bulb temperature, TD = dew-point temperature, Wspd = wind speed, R = radiation (2) Weather variables and related weighting factors changed over time for some of the methods and/or differ for different locations (3) aMethodology originally based on observations (4) bMethodology originally based on climate models

(Ostend, Uccle and Saint-Hubert) with the exception of the Meteonorm data. The Meteonorm software moreover allows to extract a typical year applying different methodologies (i.e. TMY2, TRY DWD, TRY DWD 1.1 (Deutscher Wetterdienst 2017) and TMY3 (Wilcox and Marion 2008)). A selection of typical year methods used in building simulations is summarized in Table 6.1. The table provides an overview of the meteorological variables considered in the basic dataset to deﬁne the typical year. Originally, the TRY (ﬁrst one in the table) consisted of a selected single year out of a period of observations (National Climate Data Center and U.S. Department of Commerce 1976) and hence not of a combination of representative typical months from different years. Later, it evolved to a compilation of representative typical months, similar to the other methods in the table. For some of the methods, the considered variables and weighting scheme moreover evolved over the years (e.g. Typical Meteorological Year 2 or TMY2 weather format is adjusted from the TMY format adapting the weighting of the dry-bulb temperature and humidity (Marion and Urban 1995)). The variables considered moreover sometimes differ within one method in order to account for the most important variables in a speciﬁc location (e.g. UK-TRY and ISO-TRY) (National Climate Data Center and U.S. Department of Commerce 1976; Kershaw et al. 2010; Eames et al. 2015). Finally, an evolution of methods has been noticed due to the (non-)availability of solar data or more complex solar models to

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generate solar data over time (Didier and Alfred 2002; Huang et al. 2014) (e.g. TMY2 included a more complex solar model than TMY (Marion and Urban 1995)).

6.2.2.3

Extreme Years

To assess the robustness of buildings to extreme weather conditions, to size HVAC systems or to perform climate uncertainty studies, insights into the variability of the climate and the occurrence of more extreme weather events are needed (Berger et al. 2014; Kershaw et al. 2011). An extreme or near-extreme year can be used to assess the building for these purposes. Currently, extreme years are 1-year weather data ﬁles which either include an extreme summer (e.g. Design Summer Year (DSY)) or winter (e.g. Extreme Cold Year (ECY)) or combination of both (e.g. Extreme Meteorological Year (XMY)). There are several ways to select/compose an extreme year. The ﬁrst approach uses a similar methodology as for deﬁning typical years (i.e. making use of the Finkelstein–Schafer statistics). Instead of searching for the most representative typical months, the most deviating months are selected or a certain percentile in the distribution is selected (Nik 2016; Weather et al. 2002). For example, an XMY is deﬁned by using the same approach as for deﬁning a TMY. Although the approaches to deﬁne an XMY and TMY consider the same meteorological variables and weighting scheme (Ferrari and Lee 2008), this is not always the case. The considered meteorological variables and related weighting factors for deﬁning extreme years sometimes differ from the ones used to deﬁne a typical year (e.g. an Untypical Meteorological Year applies the same methodology but different weighting than the Weather Year for Energy Calculations version 2 (Narowski et al. 2013; Stoffel and Rymes 1998)). The Meteonorm software allows to select a P10 (minima) or P90 (maxima) year which has the probability to happen once a decade (Meteotest 2017). The second approach selects the extreme year based on a calculated value. The DSY calculates, for example, the average dry-bulb temperature for the summertime (Weather et al. 2002) while a Hot Summer Year (HSY) calculates the Weighted Cooling Degree-Hours3 (WCDH) (Liu et al. 2016; CIBSE 2014) to select a year. The use of one calculated value has some limitations. The DSY, for instance, represents a year with a warm summer based on the average monthly temperature for April to September and risks to neglect a summer with critical heatwave periods if the average temperatures are lower for the latter (CIBSE 2009, 2014). It should furthermore be noted that an extreme year does not provide insights into the average discomfort to be expected on yearly basis. For example, a DSY is an extreme warm year to be expected to happen once each 8 years (CIBSE 2009).

Deﬁned as “the cumulative squared hourly difference between the outdoor dry-bulb temperature and the adaptive thermal comfort temperature” (CIBSE 2014: p. 1).

3

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Table 6.2 Selection of extreme weather years used in building simulation Acronym

Complete name

Weather variables + weights (in %)

DSYa

Design Summer Year (CIBSE 2014) Extreme Meteorological Year (Ferrari and Lee 2008)

Average T for period April–September

XMYa

UMYa HSYa EWYb ECYb DRYa P10/P90a

Untypical Meteorological Year (Narowski et al. 2013) Hot Summer Year (Liu et al. 2016) Extreme Warm Year (Nik 2016) Extreme Cold Year (Nik 2016) Design Reference Year (Watkins et al. 2013) P10 (cold)/P90 (warm) extreme year (Meteotest 2017)

Tmin (5%), Tmax (5%), Tmean (30%), TDmin (2.5%), TDmax (2.5%), TDmean (5%), Wspdmax (5%), Wspdmean (5%), R (40%) (based on TMY) T, R, Wspd (based on WYEC) Highest WCDH (HSY-1) or most hours of PETc over 23 °C (HSY-2) T T T, R, humidity, wind speed (weather generator combined with weighting scheme) T, R

Notes (1) T = dry-bulb temperature, TD = dew-point temperature, Wspd = wind speed, R = radiation (2) WDCH = weighted cooling degree-hours, PET = physiologically equivalent temeprature (Höppe 1999) (3) Weather variables and related weighting factors changed over time for some of the methods and/or differ for different locations (4) aMethodology originally based on observations (5) bMethodology originally based on climate models (6) cPhysiologically equivalent temperature (Höppe 1999)

Similar as with typical years, extreme years can be created based on observational data, climate models or weather generator output. For Belgium, the existing extreme years are based on observations (the Meteonorm P10 and P90 years for the locations of Uccle, Ostend and Saint-Hubert). A selection of extreme weather years which are commonly used in building simulations is summarized in Table 6.2.

6.2.2.4

Representative Datasets

The above described typical and extreme years are combined by Nik (2016) in so-called representative datasets. Nik synthesizes three years out of a multi-year period, extracting a typical and an extreme cold and warm year from RCMs (multiple if available). A typical downscaled year (TDY) is extracted representing the typical conditions of the full period. Further, the extreme cold and extreme warm years are extracted representing, respectively, coldest and warmest conditions from the considered period. To derive these three years, a similar methodology is used as the one for the TMY, making use of the Finkelstein–Schafer statistics. In this case,

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temperature is considered as variable to select the most extreme/typical months. This approach moreover allows to consider one or several future climate scenarios.

6.2.3

Recommendations for the Use of Future Weather Data for Building Energy Simulations

When aiming at designing climate resilient buildings, various aspects can be investigated, ranging from the average energy consumption and thermal comfort to resilience in extreme weather conditions. Depending on the goal of the study, the most appropriate weather data need to be selected. When investigating the average energy consumption and thermal comfort, typical years are preferred, while to ensure resilience in extreme weather conditions, multi-year datasets or extreme weather years are better suited. It is furthermore recommended that multi-year datasets, whether used directly or used for deriving extreme weather years from them, should cover a sufﬁciently long period (typically 30 years) to include the variability of the climate. When extreme weather data ﬁles are used it is furthermore important to select the appropriate one (s) for the goal of the study as some ﬁles rather represent years with high summer temperatures and not necessarily years with higher occurrence of extreme weather events, or the other way around. As discussed in Sect. 6.2.1, various methods exist to create future weather data from which then typical or extreme years can be derived. Each of the existing methods has its strong points and limitations. It is hence not only important to select the most appropriate weather data ﬁle (typical versus extreme, or a combination of both), but also to select the most appropriate method used to create the future weather data, in line with the goal of the study. While morphing is suited to investigate the average energy performance in a future climate realization, the fact that the baseline data is averaged data and climate change signal a mean change makes it less suited for the assessment in extreme conditions. Dynamically downscaled climate models can be used for both average as extreme assessment purposes. In particular, when downscaled to convection-permitting scale (

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