Institute of Urban Meteorology (IUM), China Meteorological
Administration (CMA), Beijing, 100089, China
Yanjie Li
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, 100029, China
Yulu Qiu
Institute of Urban Meteorology (IUM), China Meteorological
Administration (CMA), Beijing, 100089, China
Fuxin Zhu
Institute of Urban Meteorology (IUM), China Meteorological
Administration (CMA), Beijing, 100089, China
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2,581
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PDF: 750
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Cumulative views and downloads
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Total article views: 2,830 (including HTML, PDF, and XML)
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2,202
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2,830
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PDF: 573
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Supplement: 126
BibTeX: 62
EndNote: 100
Views and downloads (calculated since 10 Jan 2023)
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Total article views: 574 (including HTML, PDF, and XML)
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379
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Total: 574
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BibTeX: 9
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Views and downloads (calculated since 19 Aug 2022)
Cumulative views and downloads
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Total article views: 3,404 (including HTML, PDF, and XML)
Thereof 3,373 with geography defined
and 31 with unknown origin.
Total article views: 2,830 (including HTML, PDF, and XML)
Thereof 2,789 with geography defined
and 41 with unknown origin.
Total article views: 574 (including HTML, PDF, and XML)
Thereof 574 with geography defined
and 0 with unknown origin.
It is important to use weather data to estimate aerosol concentrations. Here, a weather index for aerosol concentration based on deep learning was developed, linking weather and short-term variations in aerosol concentrations over China. The index provides better performance than chemical transport model simulation and other data-based estimation approaches. It can be used as a robust tool for estimating daily variations in aerosol concentrations.
It is important to use weather data to estimate aerosol concentrations. Here, a weather index...