Quantifying the emission changes and associated air quality impacts during the COVID-19 pandemic in North China Plain: a response modeling study

doi:10.5194/acp-2020-522

GSTDTAP > 地球科学

DOI	10.5194/acp-2020-522
	Quantifying the emission changes and associated air quality impacts during the COVID-19 pandemic in North China Plain: a response modeling study
	Jia Xing, Siwei Li, Yueqi Jiang, Shuxiao Wang, Dian Ding, Zhaoxin Dong, Yun Zhu, and Jiming Hao
	2020-07-14
发表期刊	Atmospheric Chemistry and Physics
出版年	2020
英文摘要	Quantification of emission changes is a prerequisite for the assessment of control effectiveness in improving air quality. However, the traditional bottom-up method for characterizing emissions requires detailed investigation of emissions data (e.g., activity and other emission parameters) that usually takes months to perform and limits timely assessments. Here we propose a novel method to address this issue by using a response model that provides real-time estimation of emission changes based on air quality observations in combination with emission-concentration response functions derived from chemical transport modeling. We applied the new method to quantify the emission changes in the North China Plain (NCP) due to the COVID-19 pandemic shutdown, which overlapped the Spring Festival holiday. Results suggest that the anthropogenic emissions of NO₂, SO₂, VOC, and primary PM_2.5 in NCP were reduced by 51 %, 28 %, 67 % and 63 %, respectively, due to the COVID-19 shutdown, indicating longer and stronger shutdown effects in 2020 compared to the previous Spring Festival holiday. The reductions of VOC and primary PM_2.5 emissions are generally effective in reducing O₃ and PM_2.5 concentrations. However, such air quality improvements are largely offset by reductions in NO_x emissions. NO_x emission reductions lead to increases in O₃ and PM_2.5 concentrations in NCP due to the strongly VOC-limited conditions in winter. A strong NH₃-rich condition is also suggested from the air quality response to the substantial NO_x emission reduction. Well-designed control strategies are recommended based on the air quality response associated with the unexpected emission changes during the COVID-19 period. In addition, our results demonstrate that the new response-based inversion model can well capture emission changes based on variations in ambient concentrations, and thereby illustrate the great potential for improving the accuracy and efficiency of bottom-up emission inventory methods.
领域	地球科学
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文献类型	期刊论文
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/284201
专题	地球科学
推荐引用方式 GB/T 7714	Jia Xing, Siwei Li, Yueqi Jiang, Shuxiao Wang, Dian Ding, Zhaoxin Dong, Yun Zhu, and Jiming Hao. Quantifying the emission changes and associated air quality impacts during the COVID-19 pandemic in North China Plain: a response modeling study[J]. Atmospheric Chemistry and Physics,2020.
APA	Jia Xing, Siwei Li, Yueqi Jiang, Shuxiao Wang, Dian Ding, Zhaoxin Dong, Yun Zhu, and Jiming Hao.(2020).Quantifying the emission changes and associated air quality impacts during the COVID-19 pandemic in North China Plain: a response modeling study.Atmospheric Chemistry and Physics.
MLA	Jia Xing, Siwei Li, Yueqi Jiang, Shuxiao Wang, Dian Ding, Zhaoxin Dong, Yun Zhu, and Jiming Hao."Quantifying the emission changes and associated air quality impacts during the COVID-19 pandemic in North China Plain: a response modeling study".Atmospheric Chemistry and Physics (2020).