In recent years, haze pollution has become a serious environmental problem affecting cities in China. Reducing PM2.5 concentrations through urban planning is a promising method that has been a focus of recent multidisciplinary research. Most existing studies only analyze the relationship between urban planning factors and PM2.5 concentration, and it is difficult to accurately reflect residents' actual air pollution exposure without considering their space-time behaviors. This study uses satellite remote sensing and location service data to measure PM2.5 pollution exposure in Wuhan metropolitan area and explores the effects of urban spatial structure, land use, spatial form, transportation, and green space on pollution exposure. The results show that spatial structure, building density, road density, and green space coverage have a significant impact on PM2.5 pollution exposure. In addition, this study proposes corresponding implications for urban planning to improve public respiratory health.
Keywords: Air pollution; Big data; Particulate matter; Spatial factors.
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