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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5,163
1,524
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6,820
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212
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PDF: 1,524
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Total: 6,820
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Cumulative views and downloads
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Total article views: 5,449 (including HTML, PDF, and XML)
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EndNote
4,390
954
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5,449
316
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190
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PDF: 954
XML: 105
Total: 5,449
Supplement: 316
BibTeX: 131
EndNote: 190
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Cumulative views and downloads
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Total article views: 1,371 (including HTML, PDF, and XML)
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773
570
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1,371
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22
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Total: 1,371
Supplement: 204
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Total article views: 6,820 (including HTML, PDF, and XML)
Thereof 4,705 with geography defined
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Total article views: 5,449 (including HTML, PDF, and XML)
Thereof 3,411 with geography defined
and 2,038 with unknown origin.
Total article views: 1,371 (including HTML, PDF, and XML)
Thereof 1,294 with geography defined
and 77 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...
