DOI: 10.1002/jgrd.50479
论文题名: Optimal estimation for global ground-level fine particulate matter concentrations
作者: Van Donkelaar A. ; Martin R.V. ; Spurr R.J.D. ; Drury E. ; Remer L.A. ; Levy R.C. ; Wang J.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期: 11 起始页码: 5621
结束页码: 5636
语种: 英语
英文关键词: AERONET
; AOD
; CALIOP
; MODIS
; Optimal Estimation
; PM2.5
Scopus关键词: Algorithms
; Atmospheric aerosols
; Optimization
; Particles (particulate matter)
; Radiometers
; Reflection
; AERONET
; AOD
; CALIOP
; MODIS
; Optimal estimations
; PM2.5
; Estimation
; algorithm
; concentration (composition)
; error analysis
; estimation method
; MODIS
; optical depth
; optimization
; particulate matter
; photometer
; reflectance
; satellite imagery
; top of atmosphere
; vertical profile
; California
; Europe
; San Joaquin Valley
; United States
英文摘要: We develop an optimal estimation (OE) algorithm based on top-of-atmosphere reflectances observed by the MODIS satellite instrument to retrieve near-surface fine particulate matter (PM2.5 ). The GEOS-Chem chemical transport model is used to provide prior information for the Aerosol Optical Depth (AOD) retrieval and to relate total column AOD to PM2.5 . We adjust the shape of the GEOS-Chem relative vertical extinction profiles by comparison with lidar retrievals from the CALIOP satellite instrument. Surface reflectance relationships used in the OE algorithm are indexed by land type. Error quantities needed for this OE algorithm are inferred by comparison with AOD observations taken by a worldwide network of sun photometers (AERONET) and extended globally based upon aerosol speciation and cross correlation for simulated values, and upon land type for observational values. Significant agreement in PM2.5 is found over North America for 2005 (slope = 0.89; r = 0.82; 1-σ error = 1 μg/m3 + 27%), with improved coverage and correlation relative to previous work for the same region and time period, although certain subregions, such as the San Joaquin Valley of California are better represented by previous estimates. Independently derived error estimates of the OE PM2.5 values at in situ locations over North America (of ±(2.5 μg/m3 + 31%) and Europe of ±(3.5 μg/m3 + 30%) are corroborated by comparison with in situ observations, although globally (error estimates of ±(3.0 μg/m3 + 35%), may be underestimated. Global population-weighted PM2.5 at 50% relative humidity is estimated as 27.8 μg/m 3 at 0.1°× 0.1°resolution. © 2013. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/63678
Appears in Collections: 影响、适应和脆弱性 气候减缓与适应
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作者单位: Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada; Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, United States; RT Solutions Inc., Cambridge, MA, United States; National Renewable Energy Laboratory, Golden, CO, United States; JCET, University of Maryland, Baltimore, MD, United States; Science Systems and Applications, Inc., Lanham, MD, United States; Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, United States; Department of Earth and Atmospheric Sciences, University of Nebraska-Lincoln, Lincoln, NE, United States
Recommended Citation:
Van Donkelaar A.,Martin R.V.,Spurr R.J.D.,et al. Optimal estimation for global ground-level fine particulate matter concentrations[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(11)