Preprints
https://doi.org/10.5194/egusphere-2022-773
https://doi.org/10.5194/egusphere-2022-773
 
31 Aug 2022
31 Aug 2022
Status: this preprint is open for discussion.

Enhanced Natural Releases of Mercury in Response to Reduction of Anthropogenic Emissions during the COVID-19 Lockdown by Explainable Machine Learning

Xiaofei Qin1, Shengqian Zhou1, Hao Li1, Guochen Wang1, Cheng Chen1, Chengfeng Liu1, Xiaohao Wang2, Juntao Huo2, Yanfen Lin2, Jia Chen2, Qingyan Fu2, Yusen Duan2, Kan Huang1,3,4, and Congrui Deng1 Xiaofei Qin et al.
  • 1Center for Atmospheric Chemistry Study, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200433, China
  • 2State Ecologic Environmental Scientific Observation and Research Station for Dianshan Lake, Shanghai Environmental Monitoring Center, Shanghai, 200030, China
  • 3Institute of Eco-Chongming (IEC), Shanghai, 202162, China
  • 4IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200433, China

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.

Xiaofei Qin et al.

Status: open (until 12 Oct 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-773', Anonymous Referee #1, 24 Sep 2022 reply
  • RC2: 'Comment on egusphere-2022-773', Paula Harder, 05 Oct 2022 reply

Xiaofei Qin et al.

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Short summary
By using artificial neural network modeling and an explainable analysis approach, natural surface emission was identified as the main driver of 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 mercury, leading to increase in natural surface emissions. This study implies natural surface release may pose challenge to the future control on mercury pollution.