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Novel Parametric Workflow for Simulating Urban Heat Island Effects on Building Energy Performance: A Case Study of Seven U.S. Cities.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Novel Parametric Workflow for Simulating Urban Heat Island Effects on Building Energy Performance: A Case Study of Seven U.S. Cities.
作者:	Hashemi, Farzad.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, 2023
面頁冊數:	107 p.
附註:	Source: Dissertations Abstracts International, Volume: 85-05, Section: B.
附註:	Advisor: Iulo, Lisa Domenica;Poerschke, Ute.
Contained By:	Dissertations Abstracts International85-05B.
標題:	Emissions.
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30720542
ISBN:	9798380730594

Novel Parametric Workflow for Simulating Urban Heat Island Effects on Building Energy Performance: A Case Study of Seven U.S. Cities.
Hashemi, Farzad.

Novel Parametric Workflow for Simulating Urban Heat Island Effects on Building Energy Performance: A Case Study of Seven U.S. Cities. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 107 p.

Source: Dissertations Abstracts International, Volume: 85-05, Section: B.

Thesis (Ph.D.)--The Pennsylvania State University, 2023.

This item must not be sold to any third party vendors.

The urban heat island (UHI) effect is a well-documented phenomenon caused by urbanization, which refers to the difference between urban and rural temperatures. The rise in urban temperatures due to UHI poses a threat to the health and productivity of urban populations, while also affecting building energy usage by increasing energy consumption for cooling and decreasing it for heating. However, there is a lack of research on the specific impact of UHI on energy consumption in buildings using both urban and rural climatic data. The absence of a user-friendly workflow to incorporate this information into weather files used by architects, engineers, and urban planners is one of the primary reasons for this gap in understanding.To fill this gap, this study proposes a novel parametric workflow that combines the Local Climate Zones (LCZs) classification system and the Urban Weather Generator (UWG) tool to generate weather datasets that accurately incorporate the UHI effect. The proposed approach aims to estimate the UHI intensity at the city canopy level more accurately than existing methods. The methodology simulates UHI intensity over a year of simulation using meteorological weather data, and the UWG model provides urban weather data in EnergyPlus Weather format, which can be used for further use such as evaluating the UHI impacts on building energy performance or investigating the efficacy of mitigation strategies.The study investigates the impact of canopy heat islands on the energy consumption of different building types across seven cities in the United States using the proposed workflow. The results show that LCZ 1-Compact high-rise had the highest annual temperature variation, while LCZ 6 - Open low-rise recorded the lowest maximum UHI intensity. The impact of UHI was found to be most severe in cities located in hot-dry regions, while cities in mixed-humid regions experience the least effect. The study also found that heavy industry sites exhibit higher UHI intensity compared to many other LCZs.The results of this study highlight the importance of accounting for UHI impacts in building energy simulations and informs building design and energy management strategies to reduce energy consumption and associated greenhouse gas emissions. The proposed methodology has the potential to significantly contribute to the understanding of UHI effects and inform efforts to mitigate them in urban areas.

ISBN: 9798380730594Subjects--Topical Terms:

915579
Emissions.
Subjects--Index Terms:

Urban heat island

Novel Parametric Workflow for Simulating Urban Heat Island Effects on Building Energy Performance: A Case Study of Seven U.S. Cities.
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520 $a The urban heat island (UHI) effect is a well-documented phenomenon caused by urbanization, which refers to the difference between urban and rural temperatures. The rise in urban temperatures due to UHI poses a threat to the health and productivity of urban populations, while also affecting building energy usage by increasing energy consumption for cooling and decreasing it for heating. However, there is a lack of research on the specific impact of UHI on energy consumption in buildings using both urban and rural climatic data. The absence of a user-friendly workflow to incorporate this information into weather files used by architects, engineers, and urban planners is one of the primary reasons for this gap in understanding.To fill this gap, this study proposes a novel parametric workflow that combines the Local Climate Zones (LCZs) classification system and the Urban Weather Generator (UWG) tool to generate weather datasets that accurately incorporate the UHI effect. The proposed approach aims to estimate the UHI intensity at the city canopy level more accurately than existing methods. The methodology simulates UHI intensity over a year of simulation using meteorological weather data, and the UWG model provides urban weather data in EnergyPlus Weather format, which can be used for further use such as evaluating the UHI impacts on building energy performance or investigating the efficacy of mitigation strategies.The study investigates the impact of canopy heat islands on the energy consumption of different building types across seven cities in the United States using the proposed workflow. The results show that LCZ 1-Compact high-rise had the highest annual temperature variation, while LCZ 6 - Open low-rise recorded the lowest maximum UHI intensity. The impact of UHI was found to be most severe in cities located in hot-dry regions, while cities in mixed-humid regions experience the least effect. The study also found that heavy industry sites exhibit higher UHI intensity compared to many other LCZs.The results of this study highlight the importance of accounting for UHI impacts in building energy simulations and informs building design and energy management strategies to reduce energy consumption and associated greenhouse gas emissions. The proposed methodology has the potential to significantly contribute to the understanding of UHI effects and inform efforts to mitigate them in urban areas.
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