China CDC Key Laboratory of Environment and Population Health,
National Institute of Environmental Health, Chinese Center for Disease
Control and Prevention, Beijing, 100021, China
Jie Ban
China CDC Key Laboratory of Environment and Population Health,
National Institute of Environmental Health, Chinese Center for Disease
Control and Prevention, Beijing, 100021, China
Qing Wang
China CDC Key Laboratory of Environment and Population Health,
National Institute of Environmental Health, Chinese Center for Disease
Control and Prevention, Beijing, 100021, China
Yayi Zhang
China CDC Key Laboratory of Environment and Population Health,
National Institute of Environmental Health, Chinese Center for Disease
Control and Prevention, Beijing, 100021, China
Yang Yang
Institute of Urban Meteorology, China Meteorological Administration,
Beijing, 100089, China
Shenshen Li
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China
Wenjiao Shi
Key Laboratory of Land Surface Pattern and Simulation, Institute of
Geographic Sciences and Natural Resources Research, Chinese Academy of
Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy
of Sciences, Beijing 100049, China
Zhen Zhou
China CDC Key Laboratory of Environment and Population Health,
National Institute of Environmental Health, Chinese Center for Disease
Control and Prevention, Beijing, 100021, China
School of Marine Technology and Geomatics, Jiangsu Ocean University,
Lianyungang 222000, China
Jiawei Zang
China CDC Key Laboratory of Environment and Population Health,
National Institute of Environmental Health, Chinese Center for Disease
Control and Prevention, Beijing, 100021, China
School of Marine Technology and Geomatics, Jiangsu Ocean University,
Lianyungang 222000, China
China CDC Key Laboratory of Environment and Population Health,
National Institute of Environmental Health, Chinese Center for Disease
Control and Prevention, Beijing, 100021, China
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5,218
1,570
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6,925
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222
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PDF: 1,570
XML: 137
Total: 6,925
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EndNote: 222
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Cumulative views and downloads
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Total article views: 5,533 (including HTML, PDF, and XML)
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EndNote
4,438
986
109
5,533
340
136
200
HTML: 4,438
PDF: 986
XML: 109
Total: 5,533
Supplement: 340
BibTeX: 136
EndNote: 200
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Cumulative views and downloads
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Total article views: 1,392 (including HTML, PDF, and XML)
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780
584
28
1,392
223
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22
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Total: 1,392
Supplement: 223
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EndNote: 22
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Total article views: 6,925 (including HTML, PDF, and XML)
Thereof 4,811 with geography defined
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Total article views: 5,533 (including HTML, PDF, and XML)
Thereof 3,494 with geography defined
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Total article views: 1,392 (including HTML, PDF, and XML)
Thereof 1,317 with geography defined
and 75 with unknown origin.
We constructed multi-variable random forest models based on 10-fold cross-validation and estimated daily PM2.5 and O3 concentration of China in 2005–2017 at a resolution of 1 km. The daily R2 values of PM2.5 and O3 were 0.85 and 0.77. The meteorological variables can significantly affect both PM2.5 and O3 modeling. During 2005–2017, PM2.5 exhibited an overall downward trend, while O3 experienced the opposite. The temporal trend of PM2.5 and O3 had spatial characteristics during the study period.
We constructed multi-variable random forest models based on 10-fold cross-validation and...
