Evaluating Fine-Scale Winter Nighttime PM2.5Concentrations and Population Exposure Using SDGSAT-1 Glimmer Imagery

Abstract

A comprehensive understanding of fine particulate matter (PM2.5) distribution is vital for addressing health concerns related to deteriorating air quality. While remotely sensed nighttime light (NTL) observations have proven effective in monitoring PM2.5 concentrations, their coarse resolution limits their ability to capture the fine-scale spatial variations within urban environments. To address this limitation, an improved simple spatial random forest model was employed to estimate PM2.5 concentrations using SDGSAT-1 Glimmer NTL data. The resultant PM2.5 concentration maps, with a resolution of 300 m, were generated for the winter of 2021 (R2 = 0.81) and cover four urban agglomerations (UAs) in China. Two population-weighted indicators were utilized to assess the nighttime population exposure to PM2.5. The findings suggest that population exposure to PM2.5 is highest in the Beijing-Tianjin-Hebei UA (66.84 μgm3), followed by Chengdu-Chongqing (CC) (62.66 μgm3), Yangtze River Delta (52.04 μgm3), and Guangdong-Hong Kong-Macao Greater Bay Area (33.74 μgm3). Notably, the CC UA exhibits the highest levels of exposure among children ($ \leq $ 5 years) and the elderly ($ \geq $ 65 years). These findings provide valuable insights for policymakers to prioritize pollution control strategies and measures.