Estimating hourly full-coverage PM2.5 over China based on TOA reflectance data from the Fengyun-4A satellite
2021
Mao, Feiyue | Hong, Jia | Min, Qilong | Gong, Wei | Zang, Julin | Yin, Jianhua
It is challenging to retrieve hourly ground-level PM₂.₅ on a national scale in China due to the sparse site measurements and the limited coverage of Low Earth Orbit (LEO) satellite observations. The new geostationary meteorological satellite of China, Fengyun-4A (FY-4A), provides a unique opportunity to fill this gap. In this study, the Random Forest (RF) algorithm was applied to retrieve hourly PM₂.₅ of China directly from FY-4A Top-of-Atmosphere (TOA) reflectance data. A one-year PM₂.₅ retrieval shows a strong agreement to ground-based measurements, with the averaged R² approaching 0.92, while the RMSE was only 10.0 μg/m³. An analysis of the regional differences of the performance and the dependency on satellite Viewing Zenith Angle (VZA) show that sparse measurements, high VZA, and solar zenith angle (SZA) are the primary sources of the uncertainty. The use of the FY-4A improved 17% spatial coverage compared to the Himawari-8-based PM₂.₅ retrievals, enabling full-coverage, hourly PM₂.₅ monitoring over China, and potentially could improve PM₂.₅ predictions from air quality models after data assimilation.
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