Abigail Andrews, J. Roth, Rishee K. Jain, J. Mathieu
Growing concerns over climate change and grid reliability have led to widespread adoption of energy efficiency (EE) and demand response (DR) programs at utilities. Despite such adoption, numerous questions exist regarding the interactions between EE and DR, including whether EE diminishes a building’s DR potential. In this brief, we empirically examine the impact a building’s EE level (quantified by traditional EE benchmarking metrics) has on its DR capabilities (quantified by a building’s normalized load shed) for 194 K-12 institutional school buildings in California, USA. We found inconclusive statistical evidence that a building’s EE level has an impact on its DR load shed capabilities. We provide initial evidence countering concerns that EE diminishes DR potential and thus pave the path for future work than can further support synergistic EE and DR strategies which can enhance demand-side management programs.
{"title":"Data-Driven Examination of the Impact Energy Efficiency has on Demand Response Capabilities in Institutional Buildings","authors":"Abigail Andrews, J. Roth, Rishee K. Jain, J. Mathieu","doi":"10.1115/1.4054893","DOIUrl":"https://doi.org/10.1115/1.4054893","url":null,"abstract":"\u0000 Growing concerns over climate change and grid reliability have led to widespread adoption of energy efficiency (EE) and demand response (DR) programs at utilities. Despite such adoption, numerous questions exist regarding the interactions between EE and DR, including whether EE diminishes a building’s DR potential. In this brief, we empirically examine the impact a building’s EE level (quantified by traditional EE benchmarking metrics) has on its DR capabilities (quantified by a building’s normalized load shed) for 194 K-12 institutional school buildings in California, USA. We found inconclusive statistical evidence that a building’s EE level has an impact on its DR load shed capabilities. We provide initial evidence countering concerns that EE diminishes DR potential and thus pave the path for future work than can further support synergistic EE and DR strategies which can enhance demand-side management programs.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125699019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Advancing Climate Change Adaptation and Mitigation Strategies in the Tropics","authors":"","doi":"10.1115/1.4055138","DOIUrl":"https://doi.org/10.1115/1.4055138","url":null,"abstract":"","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132046438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As demand continues to grow throughout the United States, new communities have unique opportunities to take advantage of load-side and generation-side integrations with the goal of reducing energy use, improving the environment, and increasing resilience. Most currently reported literature investigates energy efficiency and reduction of building energy consumption or on-site generation and net zero energy goals without resiliency performance analysis. This study examines the impacts of residential building characteristics and energy sources (i.e. electricity and natural gas) on the capacity of the on-site PV generation required to achieve net-zero energy and resiliency goals for a community in Longmont, Colorado. Six community load designs are shown to impact system sizes and costs for on-site generation and resilience. Gas and electrified minimum cost designs reduce source energy from their baselines by 17% and 47% respectively. Gas minimum cost designs reduce initial and annualized energy costs by 487 and247 per year, whereas electrified minimum cost designs increase initial costs by 4, 991 and reduce annualized energy costs by1,266 per year. Resilience designs show that with various outage durations, the longer the outage design case, the larger the system, but the greater the probability of surviving outages throughout the year, with gas communities representing lower probabilities of survivability than electrified communities.
{"title":"OPTIMAL DESIGNS OF GRID-CONNECTED ENERGY EFFICIENT AND RESILIENT RESIDENTIAL COMMUNITIES","authors":"M. Krarti, Sarah Dafoe, K. Baker","doi":"10.1115/1.4053908","DOIUrl":"https://doi.org/10.1115/1.4053908","url":null,"abstract":"\u0000 As demand continues to grow throughout the United States, new communities have unique opportunities to take advantage of load-side and generation-side integrations with the goal of reducing energy use, improving the environment, and increasing resilience. Most currently reported literature investigates energy efficiency and reduction of building energy consumption or on-site generation and net zero energy goals without resiliency performance analysis. This study examines the impacts of residential building characteristics and energy sources (i.e. electricity and natural gas) on the capacity of the on-site PV generation required to achieve net-zero energy and resiliency goals for a community in Longmont, Colorado. Six community load designs are shown to impact system sizes and costs for on-site generation and resilience. Gas and electrified minimum cost designs reduce source energy from their baselines by 17% and 47% respectively. Gas minimum cost designs reduce initial and annualized energy costs by 487 and247 per year, whereas electrified minimum cost designs increase initial costs by 4, 991 and reduce annualized energy costs by1,266 per year. Resilience designs show that with various outage durations, the longer the outage design case, the larger the system, but the greater the probability of surviving outages throughout the year, with gas communities representing lower probabilities of survivability than electrified communities.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131055703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a review of the current literature in modeling Urban Heat Island (UHI) phenomena including its main causes and effects is summarized. Moreover, the reported analysis results to assess the impacts of UHI on outdoor comfort as well as on urban building energy are discussed. In addition, the limitations and future potential improvements of urban building modeling approaches are also outlined throughout the review. In particular, models and mechanisms for the formation of atmospheric boundary and canopy layers above an urban environment are first described. Then, the main causes of the UHI development and its intensity are presented with specific references to various reported analyses and studies. Major modeling methodologies are identified to evaluate UHI effects including outdoor thermal comfort and energy performance of urban built environment. Finally, UHI mitigation strategies are outlined with their potential effectiveness based on reported evaluation analyses.
{"title":"Review of Urban Heat Island and Building Energy Modeling Approaches","authors":"B. Ameer, M. Krarti","doi":"10.1115/1.4053677","DOIUrl":"https://doi.org/10.1115/1.4053677","url":null,"abstract":"\u0000 In this paper, a review of the current literature in modeling Urban Heat Island (UHI) phenomena including its main causes and effects is summarized. Moreover, the reported analysis results to assess the impacts of UHI on outdoor comfort as well as on urban building energy are discussed. In addition, the limitations and future potential improvements of urban building modeling approaches are also outlined throughout the review. In particular, models and mechanisms for the formation of atmospheric boundary and canopy layers above an urban environment are first described. Then, the main causes of the UHI development and its intensity are presented with specific references to various reported analyses and studies. Major modeling methodologies are identified to evaluate UHI effects including outdoor thermal comfort and energy performance of urban built environment. Finally, UHI mitigation strategies are outlined with their potential effectiveness based on reported evaluation analyses.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125052138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In a heating, ventilation and air conditioning (HVAC) system, a whole building fault (WBF) refers to a fault that occurs in one component but may trigger additional faults/abnormalities on different components or subsystems resulting in impacts on the energy consumption or indoor air quality in buildings. At the whole building level, interval data collected from various components/subsystems can be employed to detect WBFs. In the Part I of this study, a novel data-driven method which includes weather and schedule-based Pattern Matching (WPM) procedure and a feature based principal component analysis PCA (FPCA) procedure was developed to detect the WBF. This article is the second of a two-part study of the development of the whole building fault detection method. In the Part II of the study (this paper), various WBFs were designed and imposed in the HVAC system of a campus building. Data from both imposed fault and naturally-occurred faults were collected through the Building Automation System to evaluate the developed fault detection method. Evaluation results show that the developed WPM-FPCA method reaches a high detection rate and a low false alarm rate.
{"title":"Using Weather and Schedule based Pattern Matching and Feature based PCA for Whole Building Fault Detection — Part II Field Evaluation","authors":"Yimin Chen, Jin Wen, L. J. Lo","doi":"10.1115/1.4052730","DOIUrl":"https://doi.org/10.1115/1.4052730","url":null,"abstract":"\u0000 In a heating, ventilation and air conditioning (HVAC) system, a whole building fault (WBF) refers to a fault that occurs in one component but may trigger additional faults/abnormalities on different components or subsystems resulting in impacts on the energy consumption or indoor air quality in buildings. At the whole building level, interval data collected from various components/subsystems can be employed to detect WBFs. In the Part I of this study, a novel data-driven method which includes weather and schedule-based Pattern Matching (WPM) procedure and a feature based principal component analysis PCA (FPCA) procedure was developed to detect the WBF. This article is the second of a two-part study of the development of the whole building fault detection method. In the Part II of the study (this paper), various WBFs were designed and imposed in the HVAC system of a campus building. Data from both imposed fault and naturally-occurred faults were collected through the Building Automation System to evaluate the developed fault detection method. Evaluation results show that the developed WPM-FPCA method reaches a high detection rate and a low false alarm rate.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131156862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The potential of improving human productivity by providing healthy indoor environments has been a consistent interest in the building field for decades. This research field’s long-standing challenge is to measure human productivity given the complex nature of office work. Previous studies have diversified productivity metrics, allowing greater flexibility in collecting human data; however, this diversity complicates the ability to combine productivity metrics from disparate studies within a meta-analysis. This study aims to categorize existing productivity metrics and statistically assess which categories show similar behavior when used to measure the impacts of indoor environmental quality. The 106 productivity metrics compiled were grouped into six productivity metric categories: neurobehavioral speed, accuracy, neurobehavioral response time, call handling time, self-reported productivity, and performance score. Then, this study set neurobehavioral speed as the baseline category given its fitness to the efficiency-based definition of productivity (i.e., output versus input) and conducted three statistical analyses with the other categories to evaluate their similarity. As results, the categories of neurobehavioral response time, self-reported productivity, and call handling time were found to have statistical similarity with neurobehavioral speed. This study contributes to creating a constructive research environment for future meta-analyses to understand which human productivity metrics can be combined with each other.
{"title":"A Statistical Evaluation of Combining Human Productivity Metrics in the Indoor Environment","authors":"Kevin Keene, Wooyoung Jung","doi":"10.1115/1.4052872","DOIUrl":"https://doi.org/10.1115/1.4052872","url":null,"abstract":"\u0000 The potential of improving human productivity by providing healthy indoor environments has been a consistent interest in the building field for decades. This research field’s long-standing challenge is to measure human productivity given the complex nature of office work. Previous studies have diversified productivity metrics, allowing greater flexibility in collecting human data; however, this diversity complicates the ability to combine productivity metrics from disparate studies within a meta-analysis. This study aims to categorize existing productivity metrics and statistically assess which categories show similar behavior when used to measure the impacts of indoor environmental quality. The 106 productivity metrics compiled were grouped into six productivity metric categories: neurobehavioral speed, accuracy, neurobehavioral response time, call handling time, self-reported productivity, and performance score. Then, this study set neurobehavioral speed as the baseline category given its fitness to the efficiency-based definition of productivity (i.e., output versus input) and conducted three statistical analyses with the other categories to evaluate their similarity. As results, the categories of neurobehavioral response time, self-reported productivity, and call handling time were found to have statistical similarity with neurobehavioral speed. This study contributes to creating a constructive research environment for future meta-analyses to understand which human productivity metrics can be combined with each other.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124964882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jin Wen, B. Becerik-Gerber, Zheng O’Neill, S. Hoque
This editorial provides the background of the special edition. Current understanding of how a built environment, especially an indoor environment, affects human health and wellbeing is briefly summarized. Several recent “Ten Questions” papers on this topic are reviewed. Needs and challenges regarding this topic are discussed.
{"title":"Well-being in the Built Environment","authors":"Jin Wen, B. Becerik-Gerber, Zheng O’Neill, S. Hoque","doi":"10.1115/1.4052871","DOIUrl":"https://doi.org/10.1115/1.4052871","url":null,"abstract":"\u0000 This editorial provides the background of the special edition. Current understanding of how a built environment, especially an indoor environment, affects human health and wellbeing is briefly summarized. Several recent “Ten Questions” papers on this topic are reviewed. Needs and challenges regarding this topic are discussed.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114234699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohamad Awada, B. Becerik-Gerber, Gale M. Lucas, Shawn C Roll
The outbreak of SARS-CoV-2 virus forced office workers to conduct their daily work activities from home over an extended period. Given this unique situation, an opportunity emerged to study the satisfaction of office workers with indoor environmental quality (IEQ) factors of their houses where work activities took place and associate these factors with mental and physical health. We designed and administered a questionnaire that was open for 45 days during the COVID-19 pandemic and received valid data from 988 respondents. The results show that low satisfaction with natural lighting, glare and humidity predicted eye related symptoms, while low satisfaction with noise was a strong predictor of fatigue or tiredness, headaches or migraines, anxiety, and depression or sadness. Nose and throat related symptoms and skin related symptoms were only uniquely predicted by low satisfaction with humidity. Low satisfaction with glare uniquely predicted an increase in musculoskeletal discomfort. Symptoms related to mental stress, rumination or worry were predicted by low satisfaction with air quality and noise. Finally, low satisfaction with noise and indoor temperature predicted the prevalence of symptoms related to trouble concentrating, maintaining attention or focus. Workers with higher income were more satisfied with humidity, air quality and indoor temperature and had better overall mental health. Older individuals had increased satisfaction with natural lighting, humidity, air quality, noise, and indoor temperature. Findings from this study can inform future design practices that focus on hybrid home-work environments by highlighting the impact of IEQ factors on occupant well-being.
{"title":"Associations Among Home Indoor Environmental Quality Factors and Worker Health while Working from Home during COVID-19 Pandemic","authors":"Mohamad Awada, B. Becerik-Gerber, Gale M. Lucas, Shawn C Roll","doi":"10.1115/1.4052822","DOIUrl":"https://doi.org/10.1115/1.4052822","url":null,"abstract":"\u0000 The outbreak of SARS-CoV-2 virus forced office workers to conduct their daily work activities from home over an extended period. Given this unique situation, an opportunity emerged to study the satisfaction of office workers with indoor environmental quality (IEQ) factors of their houses where work activities took place and associate these factors with mental and physical health. We designed and administered a questionnaire that was open for 45 days during the COVID-19 pandemic and received valid data from 988 respondents. The results show that low satisfaction with natural lighting, glare and humidity predicted eye related symptoms, while low satisfaction with noise was a strong predictor of fatigue or tiredness, headaches or migraines, anxiety, and depression or sadness. Nose and throat related symptoms and skin related symptoms were only uniquely predicted by low satisfaction with humidity. Low satisfaction with glare uniquely predicted an increase in musculoskeletal discomfort. Symptoms related to mental stress, rumination or worry were predicted by low satisfaction with air quality and noise. Finally, low satisfaction with noise and indoor temperature predicted the prevalence of symptoms related to trouble concentrating, maintaining attention or focus. Workers with higher income were more satisfied with humidity, air quality and indoor temperature and had better overall mental health. Older individuals had increased satisfaction with natural lighting, humidity, air quality, noise, and indoor temperature. Findings from this study can inform future design practices that focus on hybrid home-work environments by highlighting the impact of IEQ factors on occupant well-being.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125135851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A whole building fault (WBF) refers to a fault occurring in one component, but may cause impacts on other components or subsystems, or arise impacts of significant energy consumption and thermal comfort. Conventional methods which targeted at the component level fault detection cannot be successfully employed to detect a WBF because of the fault propagation among the closely coupled equipment or subsystems. Therefore, a novel data-driven method named weather and schedule-based pattern matching (WPM) and feature based principal component analysis (FPCA) method for WBF detection is developed. Three processes are established in the WPM-FPCA method to address three main issues in the WBF detection. First, a feature selection process is used to pre-select data measurements which represent a whole building's operation performance under a satisfied status, namely baseline status. Secondly, a WPM process is employed to locate weather and schedule patterns in the historical baseline database, that are similar to that from the current/incoming operation data, and to generate a WPM baseline. Lastly, PCA models are generated for both the WPM baseline data and the current operation data. Statistic thresholds used to differentiate normal and abnormal (faulty) operations are automatically generated in this PCA modeling process. The PCA models and thresholds are used to detect WBF. This paper is the first of a two-part study. Performance evaluation of the developed method is conducted using data collected from a real campus building and will be described in the second part of this paper.
{"title":"Using Weather and Schedule based Pattern Matching and Feature based PCA for Whole Building Fault Detection — Part I Development of the Method","authors":"Yimin Chen, Jin Wen, L. J. Lo","doi":"10.1115/1.4052729","DOIUrl":"https://doi.org/10.1115/1.4052729","url":null,"abstract":"\u0000 A whole building fault (WBF) refers to a fault occurring in one component, but may cause impacts on other components or subsystems, or arise impacts of significant energy consumption and thermal comfort. Conventional methods which targeted at the component level fault detection cannot be successfully employed to detect a WBF because of the fault propagation among the closely coupled equipment or subsystems. Therefore, a novel data-driven method named weather and schedule-based pattern matching (WPM) and feature based principal component analysis (FPCA) method for WBF detection is developed. Three processes are established in the WPM-FPCA method to address three main issues in the WBF detection. First, a feature selection process is used to pre-select data measurements which represent a whole building's operation performance under a satisfied status, namely baseline status. Secondly, a WPM process is employed to locate weather and schedule patterns in the historical baseline database, that are similar to that from the current/incoming operation data, and to generate a WPM baseline. Lastly, PCA models are generated for both the WPM baseline data and the current operation data. Statistic thresholds used to differentiate normal and abnormal (faulty) operations are automatically generated in this PCA modeling process. The PCA models and thresholds are used to detect WBF. This paper is the first of a two-part study. Performance evaluation of the developed method is conducted using data collected from a real campus building and will be described in the second part of this paper.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115953855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhihong Pang, B. Becerik-Gerber, S. Hoque, Zheng O’Neill, Giulia Pedrielli, Jin Wen, Teresa Wu
This paper presents the results from an international survey that investigated the impacts of the built environment on occupant well-being during the COVID-19 pandemic when most professionals were forced to work from home (WFH). The survey was comprised of 81 questions focusing on the respondent's profiles, residences, home indoor environmental quality, health, and home working experiences. A total of 1,460 responses were collected from 35 countries, and 1,137 of them were considered complete for the analysis. The results suggest that home spatial layout has a significant impact on occupant well-being during WFH since home-life distractions and noises due to the lack of a personal workspace are likely to prevent productive work. Lack of scenic views, inadequate daylighting, and poor acoustics were also reported to be detrimental to occupant productivity and the general WFH experience. It is also revealed from this survey that temperature, relative humidity, and indoor air quality generally have higher satisfaction ratios compared with the indoor lighting and acoustic conditions, and the home layout. Hence, home design for lighting, acoustics, and layout should also receive greater attention in the future
{"title":"How Work From Home Has Affected the Occupant's Well-Being in the Residential Built Environment: An International Survey Amid the COVID-19 Pandemic","authors":"Zhihong Pang, B. Becerik-Gerber, S. Hoque, Zheng O’Neill, Giulia Pedrielli, Jin Wen, Teresa Wu","doi":"10.1115/1.4052640","DOIUrl":"https://doi.org/10.1115/1.4052640","url":null,"abstract":"\u0000 This paper presents the results from an international survey that investigated the impacts of the built environment on occupant well-being during the COVID-19 pandemic when most professionals were forced to work from home (WFH). The survey was comprised of 81 questions focusing on the respondent's profiles, residences, home indoor environmental quality, health, and home working experiences. A total of 1,460 responses were collected from 35 countries, and 1,137 of them were considered complete for the analysis. The results suggest that home spatial layout has a significant impact on occupant well-being during WFH since home-life distractions and noises due to the lack of a personal workspace are likely to prevent productive work. Lack of scenic views, inadequate daylighting, and poor acoustics were also reported to be detrimental to occupant productivity and the general WFH experience. It is also revealed from this survey that temperature, relative humidity, and indoor air quality generally have higher satisfaction ratios compared with the indoor lighting and acoustic conditions, and the home layout. Hence, home design for lighting, acoustics, and layout should also receive greater attention in the future","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126462886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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