High spatial and temporal resolution multi-source anthropogenic heat estimation for China

Qian, Jiangkang; Zhang, Linlin; Schlink, Uwe; Meng, Qingyan; Liu, Xue; Janscó, Tamás

doi:10.1016/j.resconrec.2024.107451

Resources, Conservation and Recycling

2024

DOI: 10.1016/j.resconrec.2024.107451

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High spatial and temporal resolution multi-source anthropogenic heat estimation for China

Jiangkang Qian,

Linlin Zhang,

Uwe Schlink

et al.

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2024

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Cited by 3 publications

References 52 publications

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Driving factors of summer diurnal surface thermal environment in subtropical coastal cities: a Shenzhen case study

Guo,

Lin,

Zhong

et al. 2024

Int. J. Environ. Sci. Technol.

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Driving factors of summer diurnal surface thermal environment in subtropical coastal cities: a Shenzhen case study

Guo,

Lin,

Zhong

et al. 2024

Int. J. Environ. Sci. Technol.

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Impacts of urban expansion on air temperature and humidity during 2022 mega-heatwave over the Yangtze River Delta, China

Zhou,

Zhang,

Wang

et al. 2024

Science of The Total Environment

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Quantifying the Influence of Different Block Types on the Urban Heat Risk in High-Density Cities

Zou,

Fan,

2024

Buildings

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Urbanization and climate change have led to rising urban temperatures, increasing heat-related health risks. Assessing urban heat risk is crucial for understanding and mitigating these risks. Many studies often overlook the impact of block types on heat risk, which limits the development of mitigation strategies during urban planning. This study aims to investigate the influence of various spatial factors on the heat risk at the block scale. Firstly, a GIS approach was used to generate a Local Climate Zones (LCZ) map, which represents different block types. Secondly, a heat risk assessment model was developed using hazard, exposure, and vulnerability indicators. Thirdly, the risk model was demonstrated in Guangzhou, a high-density city in China, to investigate the distribution of heat risk among different block types. An XGBoost model was used to analyze the impact of various urban spatial factors on heat risk. Results revealed significant variations in heat risk susceptibility among different block types. Specifically, 33.9% of LCZ 1–4 areas were classified as being at a high-risk level, while only 23.8% of LCZ 6–9 areas fell into this level. In addition, the pervious surface fraction (PSF) had the strongest influence on heat risk level, followed by the height of roughness elements (HRE), building surface fraction (BSF), and sky view factor (SVF). SVF and PSF had a negative impact on heat risk, while HRE and BSF had a positive effect. The heat risk assessment model provides valuable insights into the spatial characteristics of heat risk influenced by different urban morphologies. This study will assist in formulating reasonable risk mitigation measures at the planning level in the future.

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High spatial and temporal resolution multi-source anthropogenic heat estimation for China

Cited by 3 publications

References 52 publications

Driving factors of summer diurnal surface thermal environment in subtropical coastal cities: a Shenzhen case study

Driving factors of summer diurnal surface thermal environment in subtropical coastal cities: a Shenzhen case study

Impacts of urban expansion on air temperature and humidity during 2022 mega-heatwave over the Yangtze River Delta, China

Quantifying the Influence of Different Block Types on the Urban Heat Risk in High-Density Cities

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