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Preprints
https://doi.org/10.5194/egusphere-2022-773
https://doi.org/10.5194/egusphere-2022-773
31 Aug 2022
 | 31 Aug 2022

Enhanced Natural Releases of Mercury in Response to Reduction of 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

Abstract. The widespread of coronavirus (COVID-19) has significantly impacted the global human activities. Compared to numerous studies on conventional air pollutants, atmospheric mercury that has matched sources from both anthropogenic and natural emissions is rarely investigated. At a regional site in Eastern China, an intensive measurement was performed, showing obvious decreases of gaseous elemental mercury (GEM) during the COVID-19 lockdown, while not as significant as the other air pollutants. Before the lockdown when anthropogenic emissions dominated, GEM showed no correlation with temperature and negative correlations with wind speed and the height of boundary layer. In contrast, GEM showed significant correlation with temperature while the relationship between GEM and wind speed/boundary layer disappeared during the lockdown, suggesting the enhanced natural emissions of mercury. By applying a machine learning model and the Shapley Additive ExPlanation Approach, it was found that the mercury pollution episodes before the lockdown were driven by anthropogenic sources, while they were mainly driven by natural sources during and after the lockdown. Source apportionment results showed that the absolute contribution of natural surface emissions to GEM unexpectedly increased (44%) during the lockdown. Throughout the whole study period, a significant negative correlation was observed between the absolute contribution of natural and anthropogenic sources to GEM. We conclude that natural release of mercury could be stimulated to compensate the significantly reduced anthropogenic GEM via the surface - air exchange balance of mercury.

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Journal article(s) based on this preprint

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
Atmos. Chem. Phys., 22, 15851–15865, https://doi.org/10.5194/acp-22-15851-2022,https://doi.org/10.5194/acp-22-15851-2022, 2022
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

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By using artificial neural network modeling and an explainable analysis approach, natural...
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