DOI: 10.1016/j.atmosenv.2017.09.023
Scopus记录号: 2-s2.0-85031018723
论文题名: Satellite-based PM2.5 estimation using fine-mode aerosol optical thickness over China
作者: Yan X ; , Shi W ; , Li Z ; , Li Z ; , Luo N ; , Zhao W ; , Wang H ; , Yu X
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2017
卷: 170 起始页码: 290
结束页码: 302
语种: 英语
英文关键词: AOT
; Fine mode fraction
; MODIS
; PM2.5
Scopus关键词: Aerosols
; Deconvolution
; Frequency modulation
; Optical properties
; Radiometers
; Remote sensing
; Satellite imagery
; Table lookup
; Aerosol optical thickness
; Aerosol retrieval algorithms
; Aerosol robotic networks
; Fine mode fraction
; Ground based measurement
; Moderate resolution imaging spectroradiometer
; MODIS
; PM2.5
; Mean square error
; AERONET
; aerosol
; algorithm
; deconvolution
; ground-based measurement
; MODIS
; optical property
; particulate matter
; remote sensing
; aerosol optical thickness
; air pollution
; algorithm
; Article
; boundary layer
; China
; comparative study
; controlled study
; density
; humidity
; meteorology
; particulate matter
; priority journal
; remote sensing
; surface property
; thickness
; China
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: Accurate estimation of ground-level PM2.5 from satellite-derived aerosol optical thickness (AOT) presents various difficulties. This is because the association between AOT and surface PM2.5 can be affected by many factors, such as the contribution of fine mode AOT (FM-AOT) and the weather conditions. In this study, we compared the total AOT and FM-AOT for surface PM2.5 estimation using ground-based measurements collected in Xingtai, China from May to June 2016. The correlation between PM2.5 and FM-AOT was higher (r = 0.74) than that between PM2.5 and total AOT (r = 0.49). Based on FM-AOT, we developed a ground-level PM2.5 retrieval method that incorporated a Simplified Aerosol Retrieval Algorithm (SARA) AOT, look-up table–spectral deconvolution algorithm (LUT-SDA) fine mode fraction (FMF), and the PM2.5 remote sensing method. Due to the strong diurnal variations displayed by the particle density of PM2.5, we proposed a pseudo-density for PM2.5 retrieval based on real-time visibility data. We applied the proposed method to determine retrieval surface PM2.5 concentrations over Beijing from December 2013 to June 2015 on cloud-free days. Compared with Aerosol Robotic Network (AERONET) data, the LUT-SDA FMF was more easily available than the Moderate Resolution Imaging Spectroradiometer (MODIS) FMF. The derived PM2.5 results were compared with the ground-based monitoring values (30 stations), yielding an R2 of 0.64 and root mean square error (RMSE) = 18.9 μg/m3 (N = 921). This validation demonstrated that the developed method performed well and produced reliable results. © 2017 Elsevier Ltd
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/82700
Appears in Collections: 气候变化事实与影响
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作者单位: State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China; Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong; Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, United States; State Environmental Protection Key Laboratory of Satellite Remote Sensing, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China; Department of Geography, San Diego State University, 5500 Campanile Dr., San Diego, CA, United States; College of Resource Environment and Tourism, Capital Normal University, Beijing, China
Recommended Citation:
Yan X,, Shi W,, Li Z,et al. Satellite-based PM2.5 estimation using fine-mode aerosol optical thickness over China[J]. Atmospheric Environment,2017-01-01,170