Abstract

To prevent damage to human life and health caused by high temperatures and extreme weather and to promote sustainable urban development, it is necessary to optimize the layout of urban development elements to improve the urban wind–heat environment. Taking the high-density urban area of Shanghai as an example, this study used wavelet analysis to investigate the cyclic changes of the average annual temperature of Shanghai from 1950 to 2022 and the average annual wind speed of Shanghai from 2000 to 2020. The correlation between the urban heat environment and the urban development elements was analyzed using geographically weighted regression. The correlation was then examined using BP neural network, and finally, the impacts of different urban spatial patterns on the wind environment were analyzed using CFD numerical simulation. The results show that the average annual temperature of Shanghai city has an overall upward trend, with significant cycles of 44 and 32 years that are shortening over time. The average annual wind speed has a downward trend, with a significant main cycle of 22 years. Greening and water coverage, as well as the floor area ratio, have a significant reducing effect on surface temperature, whereas building density is positively correlated with surface temperature. Building density has a significant reducing effect on wind speed, whereas the effect of floor area ratio is not significant. The effect of building density on wind speed is significantly weakened, whereas the effect of the floor area ratio is not significant. This study provides valuable references for Shanghai and other high-density cities to optimize urban spatial patterns in order to improve the safety and comfort of the urban wind–heat environments. This study is of significant importance and value in promoting sustainable urban development, protecting the health of urban residents, and advancing spatial justice and equal well-being.

Full Text
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