题名：Spatially gap free analysis of aerosol type grids in China: First retrieval via satellite remote sensing and big data analytics

来源：ISPRS Journal of Photogrammetry and Remote Sensing

发表年代：2022年

作者：Ke Li, Kaixu Bai*, Mingliang Ma, Jianping Guo, Zhengqiang Li, Gehui Wang, Ni-Bin Chang

Abstract：Spatially gap free analysis of aerosol type grids in China: First retrieval via satellite remote sensing and big data analytics    Spatially contiguous aerosol type grids were rarely available for air quality management in the past. To bridge the gap, we developed an integrated remote sensing and big data analytics framework to generate spatially gap-free aerosol type grids between 2000 and 2020 in China. Daily gap-free aerosol fine mode fraction (FMF) data were derived via a data-driven regression model based on remote sensing big data. Aerosols in China were classified into eight major types using empirically determined FMF probability distributions over regions with typical emission sources. The results indicated that the gridded FMF estimates agreed well with AERONET retrievals (correlation coefficient: 0.81, RMSE: 0.13). Long-term variations showed a reduction in typical anthropogenic aerosols (21.38% to 11.76%) and dust aerosols (6.99% to 2.15%) over two decades. Declining trends were linked to reduced coal consumption, improved vegetation cover, and weakened wind speeds. This study provides evidence of emission control effects on haze reduction in China.