ABSTRACT: Mining cities are an important part of China's urban agglomerations, and as mining cities continue to develop, ecological and environmental pollution has become a primary problem. the level of pollutant emissions of mining cities is much higher than that of non-mining cities, and the ability to repair the environment is lower than that of non-mining cities. City structure and air pollution are correlated, and studies of city cluster are different from previous air pollution analyses that have been conducted on regional basis. Particulate matter estimation for city clusters requires high spatial and temporal resolution observations to further understand the mechanisms of model, validate modelling results, and improve the modelling capabilities.
In this study, the aerosol optical depth (AOD) retrieval of major mining city clusters in China from 2013 to 2020 was carried out by using the Gaofen-1 satellite data, and a new hybrid model based on WRF-CHEM and GTWR was proposed for PM_2.5 and PM₁₀ mass concentration estimation. The temporal and spatial analysis of particulate matter characteristics according to the different transformation stages and urban structure of mining cities was carried out in mining city clusters in China in the past two decades. The estimated results for PM_2.5 and PM₁₀ were verified at ground stations with R² of 0.81 and 0.78, and RMSE of 9.52 μg/m³ and 18.09 μg/m³, respectively. The results indicate that PM_2.5 and PM₁₀ have distinct spatial and temporal distribution patterns as mining cities in China are undergoing different types of transformation processes.
 

Mining City Cluster,Remote sensing (RS),Gaofen-1,PM2.5,PM10,AOD