Remote sensing of atmospheric PM2.5 from high spatial resolution image of Chinese environmental satellite HJ-1/CCD data

Due to lack of the middle infrared wavelength, it is difficult to employ the classic dark target method to retrieve aerosol optical depth (AOD) from Chinese Environmental satellite HJ1-CCD data. Therefore, focusing on extracting weak information from mixed satellite signals of atmosphere and land surface, we developed the Multi-wavelength, Multi-sensor, Multi-day (3M) approach in order to utilize maximally the observation information, and with the consideration of a prior knowledge, e.g. the surface property changes quickly with location but slowly with time. We present the AOD retrieval algorithm based on HJ1-CCD blue and green bands, based on the look-up table approach constructed using 6S radiative transfer model to provide the simultaneous determination of AOD and the ground reflectance. The aerosol and particle size information obtained from ground-based sun-sky radiometer are then used to estimate PM2.5 on the surface level, while air humidity and height of planetary boundary layer from reanalysis data are employed to improve the correlation between AOD and PM2.5. Validation of the retrieval results with different spatial resolutions (300, 500 and 1000 m), are also performed by comparison with ground-based measurements at three sites of North China regions.