Lidar vertical observation network and data assimilation reveal key processes driving the 3-D dynamic evolution of PM2.5 concentrations over the North China Plain

doi:10.5194/acp-21-7023-2021

	Lidar vertical observation network and data assimilation reveal key processes driving the 3-D dynamic evolution of PM2.5 concentrations over the North China Plain
	Xiang, Yan 1,4; Zhang, Tianshu 1,2,4; Ma, Chaoqun 3; Lv, Lihui 1,4; Liu, Jianguo 2; Liu, Wenqing 1,2,4; Cheng, Yafang 3
刊名	ATMOSPHERIC CHEMISTRY AND PHYSICS
	2021-05-07
卷号	21
ISSN号	1680-7316
DOI	10.5194/acp-21-7023-2021
通讯作者	Xiang, Yan(yxiang@ahu.edu.cn) ; Cheng, Yafang(yafang.cheng@mpic.de)
英文摘要	China has made great efforts to monitor and control air pollution in the past decade. Comprehensive characterization and understanding of pollutants in three-dimensions are, however, still lacking. Here, we used data from an observation network consisting of 13 aerosol lidars and more than 1000 ground observation stations combined with a data assimilation technique to conduct a comprehensive analysis of extreme heavy aerosol pollution (HAP) over the North China Plain (NCP) from November-December 2017. During the studied period, the maximum hourly mass concentration of surface PM2.5 reached similar to 390 mu g m(-3). After assimilation, the correlation between model results and the independent observation sub-dataset was similar to 50% higher than that without the assimilation, and the root mean square error was reduced by similar to 40 %. From pollution development to dissipation, we divided the HAP in the NCP (especially in Beijing) into four phases: an early phase (EP), a transport phase (TP), an accumulation phase (AP), and a removal phase (RP). We then analyzed the evolutionary characteristics of PM2.5 concentration during different phases on the surface and in 3-D space. We found that the particles were mainly transported from south to north at a height of 1-2 km (during EP and RP) and near the surface (during TP and AP). The amounts of PM2.5 advected into Beijing with the maximum transport flux intensity (TFI) were through the pathways in the relative order of the south-west > southeast > east pathways. The dissipation of PM2.5 in the RP stage (with negative TFI) was mainly from north to south with an average transport height of similar to 1 km above the surface. Our results quantified the multi-dimensional distribution and evolution of PM2.5 concentration over the NCP, which may help policymakers develop efficient air pollution control strategies.
资助项目	National Natural Science Foundation of China[42005106] ; National Natural Science Foundation of China[41941011] ; National Key Project of MOST[2017YFC0213002] ; National Key Project of MOST[2018YFC0213101] ; National Key Project of MOST[2018YFC0213106] ; National Key Project of MOST[2018YFC0213201] ; Key Technologies Research and Development Program of Anhui Province[18030801111] ; Natural Science Foundation of Anhui Province[1908085QD160] ; Natural Science Foundation of Anhui Province[1908085QD170] ; Anhui University[Y040418190]
WOS关键词	ATMOSPHERIC BOUNDARY-LAYER ; OPTICAL-PROPERTIES ; WINTER HAZE ; METEOROLOGICAL FACTORS ; REGIONAL TRANSPORT ; POLLUTION EPISODES ; BEIJING INSIGHTS ; AEROSOL ; IMPACT ; SATELLITE
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
语种	英语
出版者	COPERNICUS GESELLSCHAFT MBH
WOS记录号	WOS:000648837700002
资助机构	National Natural Science Foundation of China ; National Key Project of MOST ; Key Technologies Research and Development Program of Anhui Province ; Natural Science Foundation of Anhui Province ; Anhui University
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/121985]
专题	中国科学院合肥物质科学研究院
通讯作者	Xiang, Yan; Cheng, Yafang
作者单位	1.Anhui Univ, Inst Informat Technol, Hefei 230601, Peoples R China 2.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Key Lab Environm Opt & Technol, Hefei 230031, Peoples R China 3.Max Planck Inst Chem, Minerva Res Grp, Mainz, Germany 4.Anhui Univ, Inst Phys Sci, Hefei 230601, Peoples R China
推荐引用方式 GB/T 7714	Xiang, Yan,Zhang, Tianshu,Ma, Chaoqun,et al. Lidar vertical observation network and data assimilation reveal key processes driving the 3-D dynamic evolution of PM2.5 concentrations over the North China Plain[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2021,21.
APA	Xiang, Yan.,Zhang, Tianshu.,Ma, Chaoqun.,Lv, Lihui.,Liu, Jianguo.,...&Cheng, Yafang.(2021).Lidar vertical observation network and data assimilation reveal key processes driving the 3-D dynamic evolution of PM2.5 concentrations over the North China Plain.ATMOSPHERIC CHEMISTRY AND PHYSICS,21.
MLA	Xiang, Yan,et al."Lidar vertical observation network and data assimilation reveal key processes driving the 3-D dynamic evolution of PM2.5 concentrations over the North China Plain".ATMOSPHERIC CHEMISTRY AND PHYSICS 21(2021).