Institute of Carbon Neutrality, Sino-French Institute of Earth System Science, College Urban and Environmental Sciences, Peking University, Beijing 100871, China
Global Change and Earth System Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Jianbao Liu
Institute of Carbon Neutrality, Sino-French Institute of Earth System Science, College Urban and Environmental Sciences, Peking University, Beijing 100871, China
Institute of Carbon Neutrality, Sino-French Institute of Earth System Science, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
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2,128
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2,709
98
167
HTML: 2,128
PDF: 497
XML: 84
Total: 2,709
BibTeX: 98
EndNote: 167
Views and downloads (calculated since 02 Apr 2024)
Cumulative views and downloads
(calculated since 02 Apr 2024)
Total article views: 1,710 (including HTML, PDF, and XML)
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1,465
220
25
1,710
37
78
HTML: 1,465
PDF: 220
XML: 25
Total: 1,710
BibTeX: 37
EndNote: 78
Views and downloads (calculated since 12 Sep 2024)
Cumulative views and downloads
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Total article views: 999 (including HTML, PDF, and XML)
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663
277
59
999
61
89
HTML: 663
PDF: 277
XML: 59
Total: 999
BibTeX: 61
EndNote: 89
Views and downloads (calculated since 02 Apr 2024)
Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 2,709 (including HTML, PDF, and XML)
Thereof 2,641 with geography defined
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Total article views: 1,710 (including HTML, PDF, and XML)
Thereof 1,657 with geography defined
and 53 with unknown origin.
Total article views: 999 (including HTML, PDF, and XML)
Thereof 984 with geography defined
and 15 with unknown origin.
In this study, daily PM2.5 concentrations are estimated from 1959 to 2022 using a machine learning method at more than 5000 terrestrial sites in the Northern Hemisphere based on hourly atmospheric visibility data, which are extracted from the Meteorological Terminal Aviation Routine Weather Report (METAR).
In this study, daily PM2.5 concentrations are estimated from 1959 to 2022 using a machine...