Using satellite remote sensing data to estimate the high-resolution distribution of ground-level PM2.5

摘要: Although ground-level monitoring can provide accurate PM2.5 measurements, it has limited spatial coverage and resolution. In contrast, satellite-based aerosol optical depth (AOD) products with higher resolution continuous coverage, but cannot directly measure concentration. Observation-based simulation-based approaches have been actively developed to retrieve concentrations from satellite AOD sparse observations. However, the effect of characteristics (e.g., composition size distribution) on AOD–PM2.5 relationship is seldom considered in observation-based methods. these are methods, results still suffer model uncertainties. this study, we propose an algorithm that considers main characteristics. Their related effects hygroscopic growth, particle mass extinction efficiency, distribution estimated incorporated into relationship. The method applied quantify China. Good agreements between satellite-retrieved ground-observed annual monthly averages identified, significant correlations 0.90 0.76, respectively, at 565 stations suggest approach large scale PM distributions verified least as good those estimations. also show method's capacity identify high-resolution national, regional, urban scales useful information for air pollution control strategies, health risk assessments, etc.