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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 | 13522310 |
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 |
英文关键词 | Chemical transport model (CTM); North China plain (NCP); PM2.5; Spatial pattern; Time series; Visibility |
学科领域 | 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 |
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
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文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/120826 |
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). |
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