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Sci Total Environ

Title:		Air pollution characteristics in China during 2015-2016: Spatiotemporal variations and key meteorological factors
Author(s):		Li R; Wang Z; Cui L; Fu H; Zhang L; Kong L; Chen W; Chen J;
Address:		"Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai, 200433, PR China. Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai, 200433, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science and Technology, Nanjing 210044, PR China. Electronic address: fuhb@fudan.edu.cn. Laboratoire de PhysicoChimie de l'Atmosphere Universite du Littoral Cote d'Opale 189A, Av. Maurice Schumann, 59140 Dunkerque, France. Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai, 200433, PR China. Electronic address: jmchen@fudan.edu.cn"
Journal Title:		Sci Total Environ
Year:		2019
Volume:		20180816
Issue:
Page Number:		902 - 915
DOI:		10.1016/j.scitotenv.2018.08.181
ISSN/ISBN:		1879-1026 (Electronic) 0048-9697 (Linking)
Abstract:		"With rapid economic development and urbanization, China has suffered from severe and persistent air pollution during the past years. In the work, the hourly data of PM(2.5), PM(10), SO(2), NO(2), CO, and O(3) in all of the prefecture-level cities (336 cities) during 2015-2016 were collected to uncover the spatiotemporal variations and influential factors of these pollutants in China. The average concentrations of PM(2.5), PM(10), SO(2), NO(2), and CO decreased by 19.32%, 15.34%, 29.30%, 9.39%, and 8.00% from 2015 to 2016, suggesting the effects of efficient control measurements during this period. On the contrary, the O(3) concentration increased by 4.20% during the same period, which mainly owed to high volatile organic compounds (VOCs) loading. The concentrations of PM(2.5), PM(10), SO(2), CO and NO(2) showed the highest and the lowest ones in winter and summer, respectively. However, the O(3) concentration peaked in summer, followed by ones in spring and autumn, and presented the lowest one in winter. All of the pollutants exhibited significantly weekly and diurnal cycle in China. PM(2.5), PM(10), SO(2), CO and NO(2) presented the higher concentrations on weekdays than those at weekends, all of which showed the bimodal pattern with two peaks at late night (21:00-22:00) and in morning (9:00-10:00), respectively. However, the O(3) concentration exhibited the highest value around 15:00. The statistical analysis suggested that the PM(2.5), PM(10), and SO(2) concentrations were significantly associated with precipitation (Prec), atmosphere temperature (T), and wind speed (WS). The CO and NO(2) concentrations displayed the significant relationship with T, while the O(3) concentration was closely linked to the sunshine duration (Tsun) and relative humidity (RH). T and WS were major factors affecting the accumulation of PM and gaseous pollutants at a national scale. At a spatial scale, Prec and T played the important roles on the PM distribution in Northeast China, and the effect of Prec on CO concentration decreased from Southeast China to Northwest China. The results shown herein provide a scientific insight into the meteorology impacts on air pollution over China"
Keywords:		Air pollution China Meteorological factors Spatial econometric model;
Notes:		"PubMed-not-MEDLINELi, Rui Wang, Zhenzhen Cui, Lulu Fu, Hongbo Zhang, Liwu Kong, Lingdong Chen, Weidong Chen, Jianmin eng Netherlands 2018/08/26 Sci Total Environ. 2019 Jan 15; 648:902-915. doi: 10.1016/j.scitotenv.2018.08.181. Epub 2018 Aug 16"