Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 23, issue 1
Articles | Volume 23, issue 1
https://doi.org/10.5194/acp-23-375-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-375-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 1
Research article
 | 
10 Jan 2023
Research article |  | 10 Jan 2023

Capturing synoptic-scale variations in surface aerosol pollution using deep learning with meteorological data

Jin Feng, Yanjie Li, Yulu Qiu, and Fuxin Zhu

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Latest update: 20 Nov 2024
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Short summary
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.
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