Evaluation and Comparison of Spatio-Temporal Relationship between Multiple Satellite Aerosol Optical Depth (AOD) and Near-Surface PM2.5 Concentration over China

Given the advantages of remote sensing, an increasing number satellite aerosol optical depths (AOD) have been utilized to evaluate near-ground PM2.5. However, spatiotemporal relationship between AODs and PM2.5 still lacks a comprehensive investigation, especially in some regions with severe pollution within China. Here, we investigated relationships several near-surface concentration across China its 14 representative during 2016–2018 using correlation coefficient (R), PM2.5/AOD ratio (η), geo-detector (q), different aerosol-dominated regimes. The results showed that MODIS AOD from Multi-Angle Implementation Atmospheric Correction (MAIAC) algorithm strongly correlates (R > 0.6) China, particularly Chengyu (CY), Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) regions. close correlations = 0.7) exist VIIRS deep blue (DB) CY, BTH, YRD Under key aerosols affecting (e.g., sulfate dust), there is strong 0.5) MAIAC DB algorithms, higher ground-level per unit these (η 130). (Terra/Aqua) can better explain spatial distribution (q 0.4) than those dark target (DT) algorithms applied over specific seasons. performance Advanced Himawari Imager (AHI) 0.5, q 0.3) was spring summer; however, it far less autumn winter investigation provides instructions for estimating based on