Remote estimation of PM2.5 based on GaoFen-4 satellite data in the Yangtze River Delta urban agglomeration
YAN Ying-ting1, LU Xiao-man1, WANG Jia-jia1, CHEN Ming-nan2, ZHOU Li-guo1,3, MA Yu-chun1
1. Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China; 2. Shanghai Investigation, Design & Research Institute Co., Ltd., Shanghai 200335, China; 3. Institute of Eco-Chongming, Shanghai 200062, China
Abstract：This paper used 6 SV model and dark target algorithm to retrieve AOD with a high spatial resolution based on GaoFen-4(GF-4) geostationary satellite data. Afterwards, combined with the PM2.5 concentration data of the ground air quality observation sites, meteorological factors and other data, physical correction methods and linear mixed effects(LME) model were used to monitor the large-scale and spatial continuous PM2.5 concentration in the Yangtze River Delta urban agglomeration(YRDUA). The results showed that the retrieved GF-4 AOD has good spatial resolution and spatial continuity, and the correlation coefficient(R) with AERONET ground-based monitoring data reached 0.82. The LME model based on GF-4 AOD showed a good agreement between the estimated PM2.5 concentration and the in situ observed values(R2=0.74). The 10-fold cross-validation R2 of spring, summer,autumn and winter were 0.67, 0.59, 0.64 and 0.72, respectively; and the mean absolute error(MAE) were 10.40, 7.42, 10.10 and 13.34μg/m3, respectively, which indicates that GF-4 can be used for regional PM2.5 concentration monitoring.
严莹婷, 陆小曼, 王嘉佳, 陈命男, 周立国, 马蔚纯. 基于GF-4卫星的长三角城市群PM2.5遥感反演[J]. 中国环境科学, 2022, 42(3): 1005-1012.
YAN Ying-ting, LU Xiao-man, WANG Jia-jia, CHEN Ming-nan, ZHOU Li-guo, MA Yu-chun. Remote estimation of PM2.5 based on GaoFen-4 satellite data in the Yangtze River Delta urban agglomeration. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(3): 1005-1012.
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