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Spatiotemporal Prediction of Fine Particulate Matter Using High-Resolution Satellite Images in the Southeastern US 2003-2011Numerous studies have demonstrated that fine particulate matter (PM(sub 2.5), particles smaller than 2.5 micrometers in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM(sub 2.5) to assess personal exposure, however, induces measurement error. Land-use regression provides spatially resolved predictions but land-use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM(sub 2.5) exposures. In this paper, we used AOD data with other PM(sub 2.5) variables, such as meteorological variables, land-use regression, and spatial smoothing to predict daily concentrations of PM(sub 2.5) at a 1 sq km resolution of the Southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 to 2011. We divided the study area into three regions and applied separate mixed-effect models to calibrate AOD using ground PM(sub 2.5) measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors of 2.89, 2.51, and 2.82 cu micrograms for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM(sub 2.5) concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM(sub 2.5). Our model results will also extend the existing studies on PM(sub 2.5) which have mostly focused on urban areas because of the paucity of monitors in rural areas.
Document ID
20170003712
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Mihye Lee (Harvard University Cambridge, Massachusetts, United States)
Itai Kloog (Ben-Gurion University of the Negev Beersheba, El Janūbī, Israel)
Alexandra Chudnovsky (Tel Aviv University Tel Aviv, Israel)
Alexei Lyapustin (Goddard Space Flight Center Greenbelt, Maryland, United States)
Yujie Wang (University of Maryland, Baltimore County Baltimore, Maryland, United States)
Steven Melly (Drexel University Philadelphia, Pennsylvania, United States)
Brent Coull (Harvard University Cambridge, Massachusetts, United States)
Petros Koutrakis (Harvard University Cambridge, Massachusetts, United States)
Joel Schwartz (Harvard University Cambridge, Massachusetts, United States)
Date Acquired
April 20, 2017
Publication Date
June 17, 2015
Publication Information
Publication: Journal of Exposure Science and Environmental Epidemiology
Publisher: Springer Nature
Volume: 26
Issue Publication Date: June 1, 2016
ISSN: 1559-0631
e-ISSN: 1559-064X
DOI: doi:10.1038/jes.2015.41
Subject Category
Environment Pollution
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN41830
Funding Number(s)
CONTRACT_GRANT: NNX15AT34A
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
PM2.5
aerosol optical depth

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