title: Method for Fusing Observational Data and Chemical Transport Model Simulations To Estimate Spatiotemporally Resolved Ambient Air Pollution.
abstract: Investigations of ambient air pollution health effects rely on complete and accurate spatiotemporal air pollutant estimates. Three methods are developed for fusing ambient monitor measurements and 12 km resolution chemical transport model (CMAQ) simulations to estimate daily air pollutant concentrations across Georgia. Temporal variance is determined by observations in one method, with the annual mean CMAQ field providing spatial structure. A second method involves scaling daily CMAQ simulated fields using mean observations to reduce bias. Finally, a weighted average of these results based on prediction of temporal variance provides optimized daily estimates for each 12 × 12 km grid. These methods were applied to daily metrics of 12 pollutants (CO, NO2, NOx, O3, SO2, PM10, PM2.5, and five PM2.5 components) over the state of Georgia for a seven-year period (2002-2008). Cross-validation demonstrates a wide range in optimized model performance across pollutants, with SO2 predicted most poorly due to limitations in coal combustion plume monitoring and modeling. For the other pollutants studied, 54-88% of the spatiotemporal variance (Pearson R(2) from cross-validation) was captured, with ozone and PM2.5 predicted best. The optimized fusion approach developed provides daily spatial field estimates of air pollutant concentrations and uncertainties that are consistent with observations, emissions, and meteorology.
authors.affiliation: School of Civil and Environmental Engineering, Georgia Institute of Technology , Atlanta, Georgia 30332, United States.
authors.forename: Mariel D
authors.initials: MD
authors.lastname: Friberg
authors.affiliation: School of Civil and Environmental Engineering, Georgia Institute of Technology , Atlanta, Georgia 30332, United States.
authors.forename: Xinxin
authors.initials: X
authors.lastname: Zhai
authors.affiliation: School of Civil and Environmental Engineering, Georgia Institute of Technology , Atlanta, Georgia 30332, United States.
authors.forename: Heather A
authors.initials: HA
authors.lastname: Holmes
authors.affiliation: Rollins School of Public Health, Emory University , Atlanta, Georgia 30322, United States.
authors.forename: Howard H
authors.initials: HH
authors.lastname: Chang
authors.affiliation: Rollins School of Public Health, Emory University , Atlanta, Georgia 30322, United States.
authors.forename: Matthew J
authors.initials: MJ
authors.lastname: Strickland
authors.affiliation: Rollins School of Public Health, Emory University , Atlanta, Georgia 30322, United States.
authors.forename: Stefanie Ebelt
authors.initials: SE
authors.lastname: Sarnat
authors.affiliation: Rollins School of Public Health, Emory University , Atlanta, Georgia 30322, United States.
authors.forename: Paige E
authors.initials: PE
authors.lastname: Tolbert
authors.affiliation: School of Civil and Environmental Engineering, Georgia Institute of Technology , Atlanta, Georgia 30332, United States.
authors.forename: Armistead G
authors.initials: AG
authors.lastname: Russell
authors.affiliation: School of Civil and Environmental Engineering, Georgia Institute of Technology , Atlanta, Georgia 30332, United States.
authors.forename: James A
authors.initials: JA
authors.lastname: Mulholland
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis; D004784:Environmental Monitoring / Q000379:methods; D005845:Georgia; D008962:Models, Theoretical; D009589:Nitrogen Oxides / Q000032:analysis; D010126:Ozone / Q000032:analysis; D052638:Particulate Matter / Q000032:analysis; D015203:Reproducibility of Results; D062211:Spatio-Temporal Analysis
chemical_list: D000393:Air Pollutants; D009589:Nitrogen Oxides; D052638:Particulate Matter; D010126:Ozone