气候变化领域集成服务门户(CCPortal): Assessing local emission for air pollution via data experiments

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DOI	10.1016/j.atmosenv.2021.118323
	Assessing local emission for air pollution via data experiments
	Zhu Y.; Liang Y.; Chen S.X.
发表日期	2021
ISSN	1352-2310
卷号	252
英文摘要	Although air pollution is largely due to anthropogenic emission, the observed pollution levels in a city are confounded by meteorological conditions and regional transportation of pollutants. However, effective air quality management requires measures for local emissions of the city. With a data selection algorithm, we choose calm episodes after strong cleaning processes to measure the growth of three air pollutants (PM2.5, NO2 and SO2) before the arrival of transported pollution in three North China cities. Panel data regression models are used to analyze the episode data from the quasi-experiments to quantify the local emission in three North China cities from March 2013 to February 2019. The study reveals significant reductions in the average hourly growth rates from 5.9 to 11.1 μg/m3 to 2.9–4.5 μg/m3 for PM2.5, 2.2–8.9 μg/m3 to 0.4–2.5 μg/m3 for SO2 from 2013 to 2018, respectively, mounting to 44–70% and 57–82% reductions in the two pollutants in the three cities. However, the hourly growth rate for NO2 was less changed with the annual decrease ranging from −9.4% to 27.9% over the 2013 level in 2018. The study also finds the growth rates of PM2.5 and NO2 in Beijing were comparable to those in the heavy industrialized Tangshan and Baoding, revealing Beijing's substantial emission despite its very low profile on SO2. © 2021 Elsevier Ltd
关键词	Air-quality assessment Calm episodes Meteorological adjustment Panel data regression Quasi-experiment
语种	英语
scopus关键词	Air quality; Growth rate; Nitrogen oxides; Quality management; Air quality assessment; Calm episode; Local emissions; Meteorological adjustment; NO $-2$; North China; Panel data regression; PM$-2.5$; Quasi-experiments; SO$-2$; Regression analysis; nitric oxide; nitrogen dioxide; anthropogenic source; assessment method; atmospheric pollution; data set; growth rate; pollution control; spatiotemporal analysis; urban pollution; air pollution; air pollution control; air quality; Article; boundary layer; China; clinical assessment; comparative study; controlled study; environmental monitoring; exhaust gas; falling; growth rate; mathematical analysis; meteorological phenomena; particulate matter 2.5; priority journal; seasonal variation; spring; summer; time series analysis; wind speed; winter; Baoding; Beijing [China]; China; Hebei; Tangshan
来源期刊	ATMOSPHERIC ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/248503
作者单位	Center for Statistical Science, Peking University, Beijing, 100871, China; School of Information Engineering, Zhengzhou University of TechnologyHenan 450044, China; Guanghua School of Management, Peking University, Beijing, 100871, China
推荐引用方式 GB/T 7714	Zhu Y.,Liang Y.,Chen S.X.. Assessing local emission for air pollution via data experiments[J],2021,252.
APA	Zhu Y.,Liang Y.,&Chen S.X..(2021).Assessing local emission for air pollution via data experiments.ATMOSPHERIC ENVIRONMENT,252.
MLA	Zhu Y.,et al."Assessing local emission for air pollution via data experiments".ATMOSPHERIC ENVIRONMENT 252(2021).