State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing 100081, China
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing 100081, China
Center for Excellence in Regional Atmospheric Environment, IUE,
Chinese Academy of Sciences, Xiamen 361021, China
Ke Gui
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing 100081, China
Jie Liao
National Meteorological Information Center, Beijing 100081, China
Ye Fei
National Meteorological Information Center, Beijing 100081, China
Lipeng Jiang
Earth System Numerical Prediction Center, Beijing 100081, China
Lifeng Guo
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing 100081, China
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing 100081, China
Yaqiang Wang
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing 100081, China
Deying Wang
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing 100081, China
Zijiang Zhou
National Meteorological Information Center, Beijing 100081, China
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5,985
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198
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XML: 150
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Cumulative views and downloads
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Total article views: 6,255 (including HTML, PDF, and XML)
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5,132
998
125
6,255
304
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180
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XML: 125
Total: 6,255
Supplement: 304
BibTeX: 140
EndNote: 180
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853
404
25
1,282
15
18
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Total: 1,282
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Total article views: 7,537 (including HTML, PDF, and XML)
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Total article views: 6,255 (including HTML, PDF, and XML)
Thereof 6,032 with geography defined
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Total article views: 1,282 (including HTML, PDF, and XML)
Thereof 1,200 with geography defined
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Historical long-term PM2.5 records with high temporal resolution are essential but lacking for research and environmental management. Here, we reconstruct site-based and gridded PM2.5 datasets at 6-hour intervals from 1960 to 2020 that combine visibility, meteorological data, and emissions based on a machine learning model with extracted spatial features. These two PM2.5 datasets will lay the foundation of research studies associated with air pollution, climate change, and aerosol reanalysis.
Historical long-term PM2.5 records with high temporal resolution are essential but lacking for...
