Combined effects of urban forests on land surface temperature and PM2.5 pollution in the winter and summer

Abstract

The interactions and mechanisms among green space patterns, air quality and thermal environments are not well understood. This study aimed to identify co-benefits of urban forest pattern indicators (UFIs) in reducing PM2.5 on highly polluted winter days and providing cooling on hot summer days. We selected urban core areas of seven cities in Jiangsu Province, China as a study case, and obtained data from MODIS, Landsat 8, Sentinel-1 and Sentinel-2 remote sensing images and products. The results showed that on a heavily polluted winter day, all four UFIs (area, patch density, mean shape index and aggregation index) had significantly negative total effects on PM2.5. The effect of area on PM2.5 was suppressed by LST, and other UFIs’ effects on PM2.5 were partially or fully mediated by LST. On a hot summer day, all four UFIs except patch density had significantly negative total effects on LST. The effect of patch density on LST was suppressed by PM2.5, and the effects of other UFIs on LST were partially mediated by PM2.5. This study indicated that increasing area, shape complexity and aggregation level of urban forest patches could reduce PM2.5 on highly polluted winter days and provide cooling on hot summer days.