Study on monitoring surface PM_2.5 concentration in Jing-Jin-Ji regions using MODIS data

Base on meteorological data from a numerical weather prediction model during January to March of 2013, MODIS Deep Blue AOD products were corrected with respect to relative humidity (RH) and vertical heights, and their correlation relationship with ground PM_2.5 concentration was analyzed in order to establish a surface fine particulate concentration monitoring model in Jing-Jin-Ji regions. The results indicate that the Aqua MODIS DB algorithm AOD products are more suitable for establishing an AOD-PM_2.5 linear correlative model in winter, and the R² reaches 0.33. Height of planetary boundary layer and RH extracted from the meteorological model are used to substitute for vertical correction factor. Besides, according to the aerosol hygroscopic characteristic from IMPROVE, relative humidity correction is developed to estimate surface PM_2.5 concentration in different RH ranges, which could improve precision of AOD-PM_2.5 model. Thus, an optimum model of winter remote sensing inversion PM_2.5 concentration is established. Finally, the R² between estimated and observed PM_2.5 cocentration reaches 0.51. Based on the above model, monthly average surface PM_2.5 concentration is calculated. It suggests that monthly average surface PM_2.5 concentration is higher in Janurary, while air quality reaches a severe pollution level in the southern part of Jing-Jin-Ji regions.