Abstract

Focusing on satellite remote sensing of fine particulate matter PM2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM2.5 remote sensing globally, the PCF suite is composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC) together, and will be launched on board the Chinese GaoFen-5(02) satellite in 2021. Since the cross-track polarimetric measurements of POSP fully cover the multi-viewing swath of DPC, the sophisticated joint measurements could be obtained from the PCF suite in the range of 380–2250 nm including intensity and polarization, by the means of pixel matching and the cross calibration from POSP to DPC. Based on the optimal estimation inversion framework and synthetic data of PCF, the retrieval performances of key aerosol parameters are systematically investigated and assessed for the PM2.5 estimation by the PMRS model. For the design of inversion strategy for PCF, we firstly test the retrievals of aerosol optical depth (AOD), fine mode fraction (FMF), aerosol layer height (H) and the fine-mode real part of complex refractive index (mrf) simultaneously with surface parameters from the synthetic PCF data, and then the columnar volume-to-extinction ratio of fine particulates (VEf), the aerosol effective density (ρf) and the hygroscopic growth factor of fine-mode particles (f(RH)) are further obtained by the corresponding empirical relationship. The propagation errors from aerosol parameters to PM2.5 retrieval are investigated with the key procedures of PMRS model. In addition, the influences of improving calibration accuracy of PCF on PM2.5 retrievals are discussed, as well as the retrieval feasibility of PM10 by PCF strategy.

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