title: A method for estimating urban background concentrations in support of hybrid air pollution modeling for environmental health studies.
abstract: Exposure studies rely on detailed characterization of air quality, either from sparsely located routine ambient monitors or from central monitoring sites that may lack spatial representativeness. Alternatively, some studies use models of various complexities to characterize local-scale air quality, but often with poor representation of background concentrations. A hybrid approach that addresses this drawback combines a regional-scale model to provide background concentrations and a local-scale model to assess impacts of local sources. However, this approach may double-count sources in the study regions. To address these limitations, we carefully define the background concentration as the concentration that would be measured if local sources were not present, and to estimate these background concentrations we developed a novel technique that combines space-time ordinary kriging (STOK) of observations with outputs from a detailed chemistry-transport model with local sources zeroed out. We applied this technique to support an exposure study in Detroit, Michigan, for several pollutants (including NOx and PM2.5), and evaluated the estimated hybrid concentrations (calculated by combining the background estimates that addresses this issue of double counting with local-scale dispersion model estimates) using observations. Our results demonstrate the strength of this approach specifically by eliminating the problem of double-counting reported in previous hybrid modeling approaches leading to improved estimates of background concentrations, and further highlight the relative importance of NOx vs. PM2.5 in their relative contributions to total concentrations. While a key limitation of this approach is the requirement for another detailed model simulation to avoid double-counting, STOK improves the overall characterization of background concentrations at very fine spatial scales.
authors.affiliation: Institute for the Environment, University of North Carolina at Chapel Hill, 100 Europa Drive, Suite 490, Chapel Hill, NC 27517, USA. sarav@email.unc.edu.
authors.forename: Saravanan
authors.initials: S
authors.lastname: Arunachalam
authors.affiliation: Institute for the Environment, University of North Carolina at Chapel Hill, 100 Europa Drive, Suite 490, Chapel Hill, NC 27517, USA. valenal@email.unc.edu.
authors.forename: Alejandro
authors.initials: A
authors.lastname: Valencia
authors.affiliation: Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Michael Hooker Research Center, 1305 Dauer Drive, Chapel Hill, NC 27599, USA. akita@email.unc.edu.
authors.forename: Yasuyuki
authors.initials: Y
authors.lastname: Akita
authors.affiliation: Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Michael Hooker Research Center, 1305 Dauer Drive, Chapel Hill, NC 27599, USA. marc_serre@unc.edu.
authors.forename: Marc L
authors.initials: ML
authors.lastname: Serre
authors.affiliation: Institute for the Environment, University of North Carolina at Chapel Hill, 100 Europa Drive, Suite 490, Chapel Hill, NC 27517, USA. omary@email.unc.edu.
authors.forename: Mohammad
authors.initials: M
authors.lastname: Omary
authors.affiliation: National Exposure Research Laboratory, U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA. Garcia.Val@epa.gov.
authors.forename: Valerie
authors.initials: V
authors.lastname: Garcia
authors.affiliation: National Exposure Research Laboratory, U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA. Isakov.Vlad@epa.gov.
authors.forename: Vlad
authors.initials: V
authors.lastname: Isakov
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis* / Q000706:statistics & numerical data; D004784:Environmental Monitoring / Q000379:methods*; D008824:Michigan; D015233:Models, Statistical; D009589:Nitrogen Oxides / Q000032:analysis; D052638:Particulate Matter / Q000032:analysis; D062211:Spatio-Temporal Analysis; D014504:Urban Health
chemical_list: D000393:Air Pollutants; D009589:Nitrogen Oxides; D052638:Particulate Matter