气候变化领域集成服务门户(CCPortal): Retrieval of surface PM2.5 mass concentrations over North China using visibility measurements and GEOS-Chem simulations

CCPortal

DOI	10.1016/j.atmosenv.2019.117121
	Retrieval of surface PM2.5 mass concentrations over North China using visibility measurements and GEOS-Chem simulations
	Li S.; Chen L.; Huang G.; Lin J.; Yan Y.; Ni R.; Huo Y.; Wang J.; Liu M.; Weng H.; Wang Y.; Wang Z.
发表日期	2020
ISSN	1352-2310
卷号	222
英文摘要	Despite much effort made in studying human health associated with fine particulate matter (PM2.5), our knowledge about PM2.5 and human health from a long-term perspective is still limited by inadequately long data. Here, we presented a novel method to retrieve surface PM2.5 mass concentrations using surface visibility measurements and GEOS-Chem model simulations. First, we used visibility measurements and the ratio of PM2.5 and aerosol extinction coefficient (AEC) in GEOS-Chem to calculate visibility-inferred PM2.5 at individual stations (SC-PM2.5). Then we merged SC-PM2.5 with the spatial pattern of GEOS-Chem modeled PM2.5 to obtain a gridded PM2.5 dataset (GC-PM2.5). We validated the GC-PM2.5 data over the North China Plain on a 0.3125° longitude x 0.25° latitude grid in January, April, July and October 2014, using ground-based PM2.5 measurements. The spatial patterns of temporally averaged PM2.5 mass concentrations are consistent between GC-PM2.5 and measured data with a correlation coefficient of 0.79 and a linear regression slope of 0.8. The spatial average GC-PM2.5 data reproduce the day-to-day variation of observed PM2.5 concentrations with a correlation coefficient of 0.96 and a slope of 1.0. The mean bias is less than 12 μg/m3 (<14%). Future research will validate the proposed method using multi-year data, for purpose of studying long-term PM2.5 variations and their health impacts since 1980. © 2019 Elsevier Ltd
关键词	Chemical transport model (CTM)North China plain (NCP)PM2.5 Spatial pattern Time series Visibility
语种	英语
scopus关键词	Health; Time series; Aerosol extinction coefficient; Chemical transport models; Correlation coefficient; Fine particulate matter (PM2.5); North China Plain; PM2.5; Spatial patterns; Visibility measurements; Visibility; aerosol; atmospheric chemistry; atmospheric transport; concentration (composition); correlation; extinction coefficient; measurement method; particulate matter; public health; regression analysis; spatiotemporal analysis; time series analysis; aerosol; article; China; correlation coefficient; human; information retrieval; latitude; linear regression analysis; longitude; simulation; time series analysis; visibility; China; North China Plain
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/249467
作者单位	State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; University of Chinese Academy of Sciences, Beijing, 100000, China; Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China; Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China; Anhui Institute of Meteorological Sciences, Hefei, 230031, China; Institute for Atmospheric and Earth System Research / Physics, Faculty of Science, University of Helsinki, P.O. Box 64, Helsinki, 00014, Finland; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100000, China
推荐引用方式 GB/T 7714	Li S.,Chen L.,Huang G.,et al. Retrieval of surface PM2.5 mass concentrations over North China using visibility measurements and GEOS-Chem simulations[J],2020,222.
APA	Li S..,Chen L..,Huang G..,Lin J..,Yan Y..,...&Wang Z..(2020).Retrieval of surface PM2.5 mass concentrations over North China using visibility measurements and GEOS-Chem simulations.ATMOSPHERIC ENVIRONMENT,222.
MLA	Li S.,et al."Retrieval of surface PM2.5 mass concentrations over North China using visibility measurements and GEOS-Chem simulations".ATMOSPHERIC ENVIRONMENT 222(2020).