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Energy Consumption and Outdoor Thermal Comfort Characteristics in High-Density Urban Areas Based on Local Climate Zone—A Case Study of Changsha, China

Author

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  • Yaping Chen

    (School of Design and Art, Hunan University of Technology and Business, Changsha 410205, China)

  • Chun Wang

    (School of Information Science and Engineering, Hunan Normal University, Changsha 410081, China)

  • Yinze Hu

    (Hunan Lugu Architectural Technology Co., Ltd., Changsha 410036, China)

Abstract

This study aims to investigate the characteristics of energy consumption and outdoor thermal comfort within the high-density urban fabric of Changsha. Two different types of building (residential and office), as well as three building forms (point, slab, and enclosed) were analyzed under the local climate zone scheme. Utilizing the ENVI-met 5.6.1 and EnergyPlus 23.2.0 software, simulations were conducted to assess the thermal comfort and energy consumption of 144 architectural models. Then, multiple regression and spatial regression were applied to predict the energy consumption characteristics of the study area. The results showed the following: (1) In the high-density urban area of Changsha, the central business district and historic old town adjacent to the Xiangjiang River are identified as areas with high energy use intensity. (2) Among the residential categories, the point-types LCZ-3 and LCZ-6, as well as the slab-type LCZ-4, exhibit the lowest energy use intensity. In contrast, the enclosed office buildings, LCZ-2 and LCZ-5, are characterized by the highest energy use intensity. (3) Urban form parameters such as floor area ratio and building shape coefficient have a significant impact on EUI winter , while EUI summer is highly related to the normalized difference vegetation index and building shape coefficient (BSC). (4) The slab-type LCZ-4 stands out with its notably lower cooling and heating energy use intensity, coupled with excellent thermal comfort, making it particularly well-suited for the climatic conditions of Changsha.

Suggested Citation

  • Yaping Chen & Chun Wang & Yinze Hu, 2024. "Energy Consumption and Outdoor Thermal Comfort Characteristics in High-Density Urban Areas Based on Local Climate Zone—A Case Study of Changsha, China," Sustainability, MDPI, vol. 16(16), pages 1-35, August.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:16:p:7157-:d:1460284
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    References listed on IDEAS

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    1. Toparlar, Y. & Blocken, B. & Maiheu, B. & van Heijst, G.J.F., 2018. "Impact of urban microclimate on summertime building cooling demand: A parametric analysis for Antwerp, Belgium," Applied Energy, Elsevier, vol. 228(C), pages 852-872.
    2. Du, Ruiqing & Liu, Chun-Ho & Li, Xian-Xiang & Lin, Chuan-Yao, 2023. "Effect of local climate zone (LCZ) and building category (BC) classification on the simulation of urban climate and air-conditioning load in Hong Kong," Energy, Elsevier, vol. 271(C).
    3. Javanroodi, Kavan & Mahdavinejad, Mohammadjavad & Nik, Vahid M., 2018. "Impacts of urban morphology on reducing cooling load and increasing ventilation potential in hot-arid climate," Applied Energy, Elsevier, vol. 231(C), pages 714-746.
    4. Limei Liu & Xinyun Chen & Yi Yang & Junfeng Yang & Jie Chen, 2023. "Prioritization of Off-Grid Hybrid Renewable Energy Systems for Residential Communities in China Considering Public Participation with Basic Uncertain Linguistic Information," Sustainability, MDPI, vol. 15(11), pages 1-30, May.
    5. Fonseca, Jimeno A. & Schlueter, Arno, 2015. "Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts," Applied Energy, Elsevier, vol. 142(C), pages 247-265.
    6. Yang, Xiaoshan & Peng, Lilliana L.H. & Jiang, Zhidian & Chen, Yuan & Yao, Lingye & He, Yunfei & Xu, Tianjing, 2020. "Impact of urban heat island on energy demand in buildings: Local climate zones in Nanjing," Applied Energy, Elsevier, vol. 260(C).
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