气候变化领域集成服务门户(CCPortal): Enhanced natural releases of mercury in response to the reduction in anthropogenic emissions during the COVID-19 lockdown by explainable machine learning

CCPortal

DOI	10.5194/acp-22-15851-2022
	Enhanced natural releases of mercury in response to the reduction in anthropogenic emissions during the COVID-19 lockdown by explainable machine learning
	Qin, Xiaofei; Zhou, Shengqian; Li, Hao; Wang, Guochen; Chen, Cheng; Liu, Chengfeng; Wang, Xiaohao; Huo, Juntao; Lin, Yanfen; Chen, Jia; Fu, Qingyan; Duan, Yusen; Huang, Kan; Deng, Congrui
发表日期	2022
ISSN	1680-7316
EISSN	1680-7324
起始页码	15851
结束页码	15865
卷号	22 期号:24 页码:15
英文摘要	The wide spread of the 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 in gaseous elemental mercury (GEM) during the COVID-19 lockdown, while it was not as significant as most of the other measured 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 the boundary layer. In contrast, GEM showed significant correlation with temperature, while the relationship between GEM and the wind speed/boundary layer disappeared during the lockdown, suggesting the enhanced natural emissions of mercury. By applying a machine learning model and the SHAP (SHapley Additive exPlanations) 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 the natural release of mercury could be stimulated to compensate for the significantly reduced anthropogenic GEM via the surface-air exchange in the balance of mercury.
学科领域	Environmental Sciences; Meteorology & Atmospheric Sciences
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000899143400001
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/273063
作者单位	Fudan University; Fudan University
推荐引用方式 GB/T 7714	Qin, Xiaofei,Zhou, Shengqian,Li, Hao,et al. Enhanced natural releases of mercury in response to the reduction in anthropogenic emissions during the COVID-19 lockdown by explainable machine learning[J],2022,22(24):15.
APA	Qin, Xiaofei.,Zhou, Shengqian.,Li, Hao.,Wang, Guochen.,Chen, Cheng.,...&Deng, Congrui.(2022).Enhanced natural releases of mercury in response to the reduction in anthropogenic emissions during the COVID-19 lockdown by explainable machine learning.ATMOSPHERIC CHEMISTRY AND PHYSICS,22(24),15.
MLA	Qin, Xiaofei,et al."Enhanced natural releases of mercury in response to the reduction in anthropogenic emissions during the COVID-19 lockdown by explainable machine learning".ATMOSPHERIC CHEMISTRY AND PHYSICS 22.24(2022):15.