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Buildings
Special Issues
Synergy between Mitigation and Adaptation in Buildings
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Synergy between Mitigation and Adaptation in Buildings

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Energy, Physics, Environment, and Systems".

Deadline for manuscript submissions: closed (28 February 2024) | Viewed by 3336

Special Issue Editors

Dr. Takashi Nakaya

E-Mail Website1 Website2
Guest Editor
Department of Architecture, Faculty of Engineering, Shinshu University, Nagano 380-8553, Japan
Interests: climate change impact assessment; thermal comfort; energy saving; passive design strategies; multi-objective optimization
Dr. Sihwan Lee

E-Mail Website
Guest Editor
Department of Environmental Engineering and Architecture, Graduate School of Environmental Studies, Nagoya University, Nagoya 464-8601, Japan
Interests: indoor air quality; particle characteristics; ventilation; thermal comfort; environmental simulation
Dr. Jongyeon Lim

E-Mail Website
Guest Editor
Department of Architectural Engineering, Kangwon National University, Chuncheon-si, Kangwon-do, Republic of Korea
Interests: thermal comfort; building system commissioning; energy-efficient retrofit strategy

Special Issue Information

Dear Colleagues,

As the effects of climate change become more apparent, the need for mitigation and adaptation measures in buildings has never been greater. Integrating these measures can not only reduce greenhouse gas emissions but also increase the resilience of buildings and cities to the impacts of climate change. For example, building insulation and solar radiation control can reduce heat loads and health risks, and the placement of vegetation around buildings may reduce building heat loads and heat islands. It is also important to combine photovoltaic cells with high-performance air conditioning equipment. This Special Issue explores the synergies between mitigation and adaptation in buildings and aims to present the latest research and practice in this area.

A key theme of this Special Issue is the need for an integrated approach to sustainable buildings, combining both mitigation and adaptation measures. In addition, we invite papers that explore the potential of each of these strategic approaches. Potential topics include, but are not limited to:

  • Assessing the impact of climate change on buildings;
  • Designing buildings to adapt to climate change;
  • The effective combination of buildings and facilities;
  • The life cycle assessment of buildings;
  • Thermal comfort assessment;
  • The energy consumption of buildings;
  • Urban heat island;
  • Green roofs and walls;
  • Occupant behavior (e.g., natural ventilation, daylighting);
  • Multi-objective optimization.

We invite researchers and practitioners to submit their original research papers, case studies, reviews and perspectives on the topic of synergies of mitigation and adaptation in architecture. The Special Issue will provide a unique opportunity to share and disseminate knowledge, exchange ideas and inspire new collaborations in this important and timely field.

Dr. Takashi Nakaya
Dr. Sihwan Lee
Dr. Jongyeon Lim
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climate change impact assessment
  • thermal comfort
  • energy consumption
  • solar energy potential
  • passive design strategies
  • urban micro-climate
  • multi-objective optimization
  • façade design
  • ventilation strategies
  • environmental simulation

Published Papers (2 papers)

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Research

30 pages, 11568 KiB  
Article
Study on the Winter Thermal Environment and Thermal Satisfaction of the Post-Disaster Prototype and Vernacular Houses in Nepal
by Barsha Shrestha, Sanjaya Uprety, Jiba Raj Pokharel and Hom Bahadur Rijal
Buildings 2023, 13(10), 2430; https://doi.org/10.3390/buildings13102430 - 24 Sep 2023
Viewed by 1919
Abstract
Post-disaster housing, constructed on a massive scale, often overlooks the indoor thermal environment, despite being a crucial design factor for residential satisfaction. This study examined the indoor thermal environment in post-Gorkha earthquake-reconstructed prototype and traditional vernacular houses in the Dolakha district of Nepal. [...] Read more.
Post-disaster housing, constructed on a massive scale, often overlooks the indoor thermal environment, despite being a crucial design factor for residential satisfaction. This study examined the indoor thermal environment in post-Gorkha earthquake-reconstructed prototype and traditional vernacular houses in the Dolakha district of Nepal. It employed a questionnaire survey and measurement of indoor and outdoor temperature in both house types across two study locations: Panipokhari and Jillu, during the coldest winter month. Despite the indoor temperature in both house types falling below the ASHRAE comfort standard, the study found that prototype houses’ nighttime indoor temperatures were 2.1 °C lower in Panipokhari and 1 °C lower in Jillu compared to vernacular houses. This difference is attributed to the use of local building materials with low U-values, substantial thermal mass in vernacular houses, and a low window-to-wall ratio. Occupants expressed dissatisfaction with the thermal environment in prototype houses compared to vernacular ones. By incorporating climate-responsive features seen in vernacular houses, heating energy could have been reduced by approximately 21% in Panipokhari and 10% in Jillu, easing the economic burden on vulnerable households. These findings hold significance for policy-makers, implementers, designers, and other stakeholders involved in post-disaster resettlement housing programs, offering insights for enhancing long-term satisfaction and sustainability in such programs. Full article
(This article belongs to the Special Issue Synergy between Mitigation and Adaptation in Buildings)
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31 pages, 8108 KiB  
Article
Investigating the Effects of Parameter Tuning on Machine Learning for Occupant Behavior Analysis in Japanese Residential Buildings
by Kaito Furuhashi and Takashi Nakaya
Buildings 2023, 13(7), 1879; https://doi.org/10.3390/buildings13071879 - 24 Jul 2023
Viewed by 899
Abstract
Global warming is currently progressing worldwide, and it is important to control greenhouse gas emissions from the perspective of adaptation and mitigation. Occupant behavior is highly individualized and must be analyzed to accurately determine a building’s energy consumption. However, most of the resident [...] Read more.
Global warming is currently progressing worldwide, and it is important to control greenhouse gas emissions from the perspective of adaptation and mitigation. Occupant behavior is highly individualized and must be analyzed to accurately determine a building’s energy consumption. However, most of the resident behavior models in existing studies are based on statistical methods, and their accuracy in parameter tuning has not been examined. The accuracy of heating behavior prediction has been studied using three different methods: logistic regression, support vector machine (SVM), and deep neural network (DNN). The generalization ability of the support vector machine and the deep neural network was improved by parameter tuning. The parameter tuning of the SVM showed that the values of C and gamma affected the prediction accuracy. The prediction accuracy improved by approximately 11.9%, confirming the effectiveness of parameter tuning on the SVM. The parameter tuning of the DNN showed that the values of the layer and neuron affected prediction accuracy. Although parameter tuning also improved the prediction accuracy of the DNN, the rate of increase was lower than that of the SVM. Full article
(This article belongs to the Special Issue Synergy between Mitigation and Adaptation in Buildings)
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