气候变化领域集成服务门户(CCPortal): Fine particulate matter (PM2.5) trends in China; 2013-2018. separating contributions from anthropogenic emissions and meteorology

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DOI	10.5194/acp-19-11031-2019
	Fine particulate matter (PM2.5) trends in China; 2013-2018. separating contributions from anthropogenic emissions and meteorology
	Zhai S.; Jacob D.J.; Wang X.; Shen L.; Li K.; Zhang Y.; Gui K.; Zhao T.; Liao H.
发表日期	2019
ISSN	16807316
起始页码	11031
结束页码	11041
卷号	19 期号:16
英文摘要	Fine particulate matter (PM2.5) is a severe air pollution problem in China. Observations of PM2.5 have been available since 2013 from a large network operated by the China National Environmental Monitoring Center (CNEMC). The data show a general 30%-50% decrease in annual mean PM2.5 across China over the 2013-2018 period, averaging at -5.2μgm-3a-1. Trends in the five megacity cluster regions targeted by the government for air quality control are -9.3±1.8 μgm-3 a-1 (±95% confidence interval) for Beijing-Tianjin-Hebei, -6.1±1.1 μgm-3 a-1 for the Yangtze River Delta, -2.7±0.8 μgm-3 a-1 for the Pearl River Delta, -6.7±1.3 μgm-3 a-1 for the Sichuan Basin, and -6.5±2.5 μgm-3 a-1 for the Fenwei Plain (Xi'an). Concurrent 2013-2018 observations of sulfur dioxide (SO2) and carbon monoxide (CO) show that the declines in PM2.5 are qualitatively consistent with drastic controls of emissions from coal combustion. However, there is also a large meteorologically driven interannual variability in PM2.5 that complicates trend attribution. We used a stepwise multiple linear regression (MLR) model to quantify this meteorological contribution to the PM2.5 trends across China. The MLR model correlates the 10 d PM2.5 anomalies to wind speed, precipitation, relative humidity, temperature, and 850 hPa meridional wind velocity (V850). The meteorology-corrected PM2.5 trends after removal of the MLR meteorological contribution can be viewed as being driven by trends in anthropogenic emissions. The mean PM2.5 decrease across China is -4.6 μgm-3 a-1 in the meteorology-corrected data, 12% weaker than in the original data, meaning that 12% of the PM2.5 decrease in the original data is attributable to meteorology. The trends in the meteorology-corrected data for the five megacity clusters are -8.0±1.1 μgm-3 a-1 for Beijing-Tianjin-Hebei (14% weaker than in the original data), -6.3±0.9 μgm-3 a-1 for the Yangtze River Delta (3% stronger), -2.2±0.5 μgm-3 a-1 for the Pearl River Delta (19% weaker), -4.9±0.9 μgm-3 a-1 for the Sichuan Basin (27% weaker), and -5.0±1.9 μgm-3 a-1 for the Fenwei Plain (Xi'an; 23% weaker); 2015-2017 observations of flattening PM2.5 in the Pearl River Delta and increases in the Fenwei Plain can be attributed to meteorology rather than to relaxation of emission controls. © Author(s) 2019.
语种	英语
scopus关键词	air quality; anthropogenic source; atmospheric pollution; carbon dioxide; confidence interval; emission control; emission inventory; particulate matter; pollution monitoring; sulfur dioxide; trend analysis; China; Guangdong; Jingjinji; Sichuan Basin; Yangtze Delta; Zhujiang Delta
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/144182
作者单位	Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, 210044, China; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, United States; Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, CMA, Beijing, 100081, China; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China
推荐引用方式 GB/T 7714	Zhai S.,Jacob D.J.,Wang X.,et al. Fine particulate matter (PM2.5) trends in China; 2013-2018. separating contributions from anthropogenic emissions and meteorology[J],2019,19(16).
APA	Zhai S..,Jacob D.J..,Wang X..,Shen L..,Li K..,...&Liao H..(2019).Fine particulate matter (PM2.5) trends in China; 2013-2018. separating contributions from anthropogenic emissions and meteorology.Atmospheric Chemistry and Physics,19(16).
MLA	Zhai S.,et al."Fine particulate matter (PM2.5) trends in China; 2013-2018. separating contributions from anthropogenic emissions and meteorology".Atmospheric Chemistry and Physics 19.16(2019).