ESTIMATION OF PM2.5 AND PM10 MASS CONCENTRATIONS IN MINING CITY CLUSTER FROM GAOFEN-1 AEROSOL OPTICAL DEPTH DATA AND CHEMICAL TRANSPORT MODEL

Mining cities are an essential part of China's urban agglomerations, and as mining cities continue to develop, ecological and environmental pollution has become a primary problem. In the present study, the Aerosol Optical Depth (AOD) retrieval of major mining urban agglomerations in China from the Gaofen-1 satellite data. Then a new hybrid model based on CTM (chemical transport model) Transport Model 5 (TM5) and GTWR (Geographic Time-Weighted Regression model) is proposed for PM2.5 and PM10 mass concentration estimation. According to the different transformation stages and urban structure of mining cities, the temporal and spatial analysis of particulate matter characteristics is carried out in mining urban agglomerations. The estimated result for PM2.5 is verified at ground stations with R-2 of 0.956 and RMSE (Root Mean Square Error) of 10.377 mu g/m(3). Moreover, the estimated result for PM10 is verified at ground stations with R-2 of 0.926 and RMSE of 16.669 mu g/m(3). The results indicate that PM2.5 and PM10 have distinct spatial and temporal distribution patterns as Chinese mining cities are undergoing different types of transformation processes.