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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Bibliographic Details
Published in:	Atmospheric chemistry and physics Vol. 20; no. 6; pp. 3273 - 3289
Main Authors:	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
Format:	Journal Article
Language:	English
Published:	Katlenburg-Lindau Copernicus GmbH 19.03.2020 Copernicus Publications
Subjects:	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
Online Access:	Get full text
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