Seasonal anthropogenic heat fluxes over 200 cities in China: An investigation of driving factors with three-dimensional building forms

• Published in: Sustainable cities and society Vol. 107; p. 105312
• Main Authors: Yang, Meizi, Cao, Shisong, Zhang, Dayu, Liu, Rui, Cui, Ling, Cai, Yile
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.07.2024
• Subjects: City size; Driving factor; Economic zone; Energy-consumption inventory method; Seasonal anthropogenic heat flux; Urban thermal environment monitoring; Seasonal anthropogenic heat flux; City size; Urban thermal environment monitoring; Economic zone; Driving factor; Energy-consumption inventory method
• ISSN: 2210-6707; 2210-6715
• DOI: 10.1016/j.scs.2024.105312

•Yearly and monthly AHFs were estimated using the energy-inventory method and NTL data.•We explored influencing factors of seasonal AHFs over 200 cities using the MGRW model.•How 2D and 3D building form parameters impact seasonal AHF was analyzed.•We evaluated how city size and economic zones alter the composition of dominant factors concerning AHF. Various studies have highlighted substantial the impact of urban development on AHFs. Therefore, it is crucial to investigate the factors that influence AHFs to develop effective development and planning strategies for mitigating urban heat. This study chose 200 cities in China to explore seasonal variations in AHFs, and how anthropogenic activities, natural factors, and urban structures interact to impact AHF changes. We synergistically utilized remotely sensed technology, the energy-consumption inventory method, and meteorological in-situ observation to develop a spatiotemporal downscaling method of AHF. In addition, we utilized the Multi-scale Geographically Weighted Regression (MGWR) model to explore how socioeconomic, blue-green spaces, and urban structures interact to influence AHF variations. We further evaluated how city size and economic zones alter the composition of dominant factors concerning AHF. Results show that cities highest AHF values were observed in north, northwest, and northeast China, where the AHF reached 85.58 W m−2. Vegetation and water body play a crucial role in explaining AH emissions, followed by urban area, building coverage, building volume, and GDP per capital. The modification effects of economic zones were higher than city sizes. The results offer valuable insights for sustainable development strategies geared towards alleviating heat-related challenges in urban environments.