Journal article
Optimal estimation for global ground‐level fine particulate matter concentrations
Journal of geophysical research. Atmospheres, Vol.118(11), pp.5621-5636
06/16/2013
DOI: 10.1002/jgrd.50479
Abstract
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/m3 at 0.1° × 0.1° resolution.
Key Points
Optimal estimation improves global PM2.5 estimates from satellite
CALIOP used to improve AOD to PM2.5 relationships
Significant PM2.5 agreement over North America for 2005 (slope = 0.89; r = 0.82)
Details
- Title: Subtitle
- Optimal estimation for global ground‐level fine particulate matter concentrations
- Creators
- Aaron Donkelaar - Dalhousie UniversityRandall V Martin - Harvard‐Smithsonian Center for AstrophysicsRobert J. D Spurr - RT Solutions IncEasan Drury - National Renewable Energy LaboratoryLorraine A Remer - University of MarylandRobert C Levy - NASA Goddard Space Flight CenterJun Wang - University of Nebraska‐Lincoln
- Resource Type
- Journal article
- Publication Details
- Journal of geophysical research. Atmospheres, Vol.118(11), pp.5621-5636
- DOI
- 10.1002/jgrd.50479
- ISSN
- 2169-897X
- eISSN
- 2169-8996
- Number of pages
- 16
- Language
- English
- Date published
- 06/16/2013
- Academic Unit
- Physics and Astronomy; Chemical and Biochemical Engineering; Civil and Environmental Engineering
- Record Identifier
- 9984104909302771
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