期刊
URBAN CLIMATE
卷 47, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.uclim.2022.101385
关键词
Urban ventilation; Thermal environment; Whale intelligence optimization algorithm; (WOA-LSTM); Circuit model; China
This paper predicts the land surface temperature (LST) of Guangzhou using the whale intelligence optimization algorithm and analyzes the impact of urban ventilation distribution and wind resistance on LST. The study found that the temperature range of >34℃ in winter in Guangzhou has increased by 49.13% from 1990 to 2030. Four main wind resistances were identified in Guangzhou, mainly located in high-rise buildings or densely-built areas. The pearl river basin serves as the main urban ventilation corridor in Guangzhou. The overall contribution of urban ventilation and wind resistance to LST reaches 11.09%. Urban functional areas, particularly commercial land and transportation land, have a significant influence on LST, with temperature ranges above 34℃ reaching 57% and 22%, respectively. This research provides new insights into mitigating the urban thermal environment.
Effectively alleviating the urban thermal environment is an important problem faced by modern urban environment optimization. This paper predicts the land surface temperature (LST) of Guangzhou based on the whale intelligence optimization algorithm. The circuit model is used to analyze the urban ventilation distribution, and the contribution of wind resistance and ventilation effect to LST is examined. We attempt to explore the relationship between the two in combination with urban functional zoning. Results showed that the temperature range of >34.C in winter in Guangzhou increased by 49.13% from 1990 to 2030. Guangzhou has four main wind resistances in the ventilation direction, and the areas with large wind resistance are located in high-rise buildings or densely-built areas. The pearl river basin is the main urban ventilation corridor in Guangzhou. The ventilation coefficient is between 0.560 and 1.605, due to the poor ventilation in the central city. Interestingly, the overall contribution rate of urban ventilation and wind resistance to LST reaches 11.09%. Urban functional areas have a significant influence on LST. We found that the temperature in commercial land and transportation land is high, and the proportion of temperature ranges above 34. C in the functional areas reaches 57% and 22%. This research can provide new insights into the mitigation of the urban thermal environment.
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