DOI: 10.1016/j.atmosenv.2015.10.004
Scopus记录号: 2-s2.0-84944034849
论文题名: Estimating daily PM2.5 and PM10 across the complex geo-climate region of Israel using MAIAC satellite-based AOD data
作者: Kloog I ; , Sorek-Hamer M ; , Lyapustin A ; , Coull B ; , Wang Y ; , Just A ; C ; , Schwartz J ; , Broday D ; M
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 122 起始页码: 409
结束页码: 416
语种: 英语
英文关键词: Aerosol optical depth (AOD)
; Air pollution
; Epidemiology
; Exposure error
; High particulate levels
; MAIAC
; PM10
; PM2.5
Scopus关键词: Aerosols
; Air pollution
; Atmospheric aerosols
; Epidemiology
; Estimation
; Forecasting
; Land use
; Optical properties
; Remote sensing
; Aerosol optical depths
; Epidemiological studies
; Exposure errors
; Geographic characteristics
; MAIAC
; Particulate levels
; Spatial and temporal smoothing
; Spatio-temporal resolution
; Satellites
; aerosol
; atmospheric pollution
; calibration
; climatic region
; epidemiology
; integrated approach
; model validation
; MODIS
; optical depth
; particulate matter
; performance assessment
; pollution exposure
; reliability analysis
; remote sensing
; satellite data
; spatiotemporal analysis
; Israel
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: Estimates of exposure to PM2.5 are often derived from geographic characteristics based on land-use regression or from a limited number of fixed ground monitors. Remote sensing advances have integrated these approaches with satellite-based measures of aerosol optical depth (AOD), which is spatially and temporally resolved, allowing greater coverage for PM2.5 estimations. Israel is situated in a complex geo-climatic region with contrasting geographic and weather patterns, including both dark and bright surfaces within a relatively small area. Our goal was to examine the use of MODIS-based MAIAC data in Israel, and to explore the reliability of predicted PM2.5 and PM10 at a high spatiotemporal resolution. We applied a three stage process, including a daily calibration method based on a mixed effects model, to predict ground PM2.5 and PM10 over Israel. We later constructed daily predictions across Israel for 2003-2013 using spatial and temporal smoothing, to estimate AOD when satellite data were missing. Good model performance was achieved, with out-of-sample cross validation R2 values of 0.79 and 0.72 for PM10 and PM2.5, respectively. Model predictions had little bias, with cross-validated slopes (predicted vs. observed) of 0.99 for both the PM2.5 and PM10 models. To our knowledge, this is the first study that utilizes high resolution 1 km MAIAC AOD retrievals for PM prediction while accounting for geo-climate complexities, such as experienced in Israel. This novel model allowed the reconstruction of long- and short-term spatially resolved exposure to PM2.5 and PM10 in Israel, which could be used in the future for epidemiological studies. © 2015 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81400
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: Department of Geography and Environmental Development, Ben-Gurion University of the Negev, Beer Sheva, Israel; Civil and Environmental Engineering, Technion, Haifa, Israel; NASA GSFC, Code 613, Greenbelt, MD, United States; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States; University of Maryland Baltimore County, Baltimore, MD, United States; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States
Recommended Citation:
Kloog I,, Sorek-Hamer M,, Lyapustin A,et al. Estimating daily PM2.5 and PM10 across the complex geo-climate region of Israel using MAIAC satellite-based AOD data[J]. Atmospheric Environment,2015-01-01,122