Improved 1 km resolution PM2.5 estimates across China using enhanced space–time extremely randomized trees

Fine particulate matter with aerodynamic diameters ≤2.5 µm (PM2.5) has adverse effects on human health and the atmospheric environment. The estimation of surface PM2.5 concentrations has made intensive use of satellite-derived aerosol products. However, it has been a great challenge to obtain high-q...

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Vydáno v:	Atmospheric chemistry and physics Ročník 20; číslo 6; s. 3273 - 3289
Hlavní autoři:	Wei, Jing, Li, Zhanqing, Cribb, Maureen, Huang, Wei, Xue, Wenhao, Sun, Lin, Guo, Jianping, Peng, Yiran, Li, Jing, Lyapustin, Alexei, Liu, Lei, Wu, Hao, Song, Yimeng
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Katlenburg-Lindau Copernicus GmbH 19.03.2020 Copernicus Publications
Témata:	Aerosols Air pollution Algorithms Artificial intelligence Atmospheric correction Atmospheric models Deep learning Environmental health Errors High resolution Humidity Land pollution Land use Metropolitan areas Particulate emissions Particulate matter Pollutants Pollution levels Pollution studies Randomization Resolution Satellite observation Satellites Spatial discrimination Spatial resolution Spectroradiometers Suspended particulate matter Topography Trees Urban areas China
ISSN:	1680-7316, 1680-7324
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