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A novel calibration approach of MODIS AOD data to predict PM2.5 concentrations
Atmospheric chemistry and physics, 2011-08, Vol.11 (15), p.7991-8002
[Peer Reviewed Journal]
Copyright Copernicus GmbH 2011 ;ISSN: 1680-7316 ;EISSN: 1680-7324 ;DOI: 10.5194/acp-11-7991-2011
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Title:
A novel calibration approach of MODIS AOD data to predict PM2.5 concentrations
Author:
Lee, H J
;
Liu, Y
;
Coull, B A
;
Schwartz, J
;
Koutrakis, P
Is Part Of:
Atmospheric chemistry and physics, 2011-08, Vol.11 (15), p.7991-8002
Description:
Epidemiological studies investigating the human health effects of PM2.5 are susceptible to exposure measurement errors, a form of bias in exposure estimates, since they rely on data from a limited number of PM2.5 monitors within their study area. Satellite data can be used to expand spatial coverage, potentially enhancing our ability to estimate location- or subject-specific exposures to PM2.5 , but some have reported poor predictive power. A new methodology was developed to calibrate aerosol optical depth (AOD) data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). Subsequently, this method was used to predict ground daily PM 2.5 concentrations in the New England region. 2003 MODIS AOD data corresponding to the New England region were retrieved, and PM2.5 concentrations measured at 26 US Environmental Protection Agency (EPA) PM2.5 monitoring sites were used to calibrate the AOD data. A mixed effects model which allows day-to-day variability in daily PM2.5 -AOD relationships was used to predict location-specific PM2.5 levels. PM2.5 concentrations measured at the monitoring sites were compared to those predicted for the corresponding grid cells. Both cross-sectional and longitudinal comparisons between the observed and predicted concentrations suggested that the proposed new calibration approach renders MODIS AOD data a potentially useful predictor of PM 2.5 concentrations. Furthermore, the estimated PM2.5 levels within the study domain were examined in relation to air pollution sources. Our approach made it possible to investigate the spatial patterns of PM2.5 concentrations within the study domain.
Publisher:
Katlenburg-Lindau: Copernicus GmbH
Language:
English
Identifier:
ISSN: 1680-7316
EISSN: 1680-7324
DOI: 10.5194/acp-11-7991-2011
Source:
Geneva Foundation Free Medical Journals at publisher websites
Alma/SFX Local Collection
ProQuest Central
DOAJ Directory of Open Access Journals
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