Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 22, issue 24
Articles | Volume 22, issue 24
https://doi.org/10.5194/acp-22-15851-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-15851-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 24
Research article
 | 
16 Dec 2022
Research article |  | 16 Dec 2022

Enhanced natural releases of mercury in response to the reduction in anthropogenic emissions during the COVID-19 lockdown by explainable machine learning

Xiaofei Qin, Shengqian Zhou, Hao Li, Guochen Wang, Cheng Chen, Chengfeng Liu, Xiaohao Wang, Juntao Huo, Yanfen Lin, Jia Chen, Qingyan Fu, Yusen Duan, Kan Huang, and Congrui Deng

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Latest update: 23 Apr 2024
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Short summary
Using artificial neural network modeling and an explainable analysis approach, natural surface emissions (NSEs) were identified as a main driver of gaseous elemental mercury (GEM) variations during the COVID-19 lockdown. A sharp drop in GEM concentrations due to a significant reduction in anthropogenic emissions may disrupt the surface–air exchange balance of Hg, leading to increases in NSEs. This implies that NSEs may pose challenges to the future control of Hg pollution.
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