ESTIMATING PM2.5 IN THE BEIJING-TIANJIN-HEBEI REGION USING MODIS AOD PRODUCTS FROM 2014 TO 2015
Keywords: Air Pollution, PM2.5, MODIS, Aerosol Optical Depth, Geographically Weighted Regression, China
Abstract. Fine particulate matter with a diameter less than 2.5 μm (PM2.5) has harmful impacts on regional climate, economic development and public health. The high PM2.5 concentrations in China’s urban areas are mainly caused by the combustion of coal and gasoline, industrial pollution and unknown/uncertain sources. The Beijing-Tianjin-Hebei (BTH) region with a land area of 218,000 km2, which contains 13 cities, is the biggest urbanized region in northern China. The huge population (110 million, 8% of the China’s population), local heavy industries and vehicle emissions have resulted in severe air pollution. Traditional models have used 10 km Moderate-resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) products and proved the statistical relationship between AOD and PM2.5. In 2014, the 3 km MODIS AOD product was released which made PM2.5 estimations with a higher resolution became possible. This study presents an estimation on PM2.5 distributions in the BTH region from September 2014 to August 2015 by combining the MODIS satellite data, ground measurements of PM2.5, meteorological parameters and social-economic factors based on the geographically weighted regression model. The results demonstrated that the 10 km AOD product provided results with a slightly higher accuracy although the 3 km AOD product could provide more information about the spatial variations of PM2.5 estimations. Additionally, compared with the global regression, the geographically weighed model was able to improve the estimation results.