Comparing Multipollutant Emissions-Based Mobile Source Indicators to Other Single Pollutant and Multipollutant Indicators in Different Urban Areas

Michelle M. Oakes, Lisa K. Baxter, Rachelle M. Duvall, Meagan Madden, Mingjie Xie, Michael P. Hannigan, Jennifer L. Peel, Jorge E. Pachon, Siv Balachandran, Armistead Russell and Thomas C. Long
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Michelle M. Oakes: National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Lisa K. Baxter: National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC 2711, USA
Rachelle M. Duvall: National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC 2711, USA
Meagan Madden: National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Mingjie Xie: Department of Mechanical Engineering, College of Engineering and Applied Science, University of Colorado-Boulder, Boulder, CO 80309, USA
Michael P. Hannigan: Department of Mechanical Engineering, College of Engineering and Applied Science, University of Colorado-Boulder, Boulder, CO 80309, USA
Jennifer L. Peel: Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523, USA
Jorge E. Pachon: Program of Environmental Engineering, Universidad de La Salle, Bogota, CO 111711, USA
Siv Balachandran: Department of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
Armistead Russell: Department of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
Thomas C. Long: National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA

IJERPH, 2014, vol. 11, issue 11, 1-26

Abstract: A variety of single pollutant and multipollutant metrics can be used to represent exposure to traffic pollutant mixtures and evaluate their health effects. Integrated mobile source indicators (IMSIs) that combine air quality concentration and emissions data have recently been developed and evaluated using data from Atlanta, Georgia. IMSIs were found to track trends in traffic-related pollutants and have similar or stronger associations with health outcomes. In the current work, we apply IMSIs for gasoline, diesel and total (gasoline + diesel) vehicles to two other cities (Denver, Colorado and Houston, Texas) with different emissions profiles as well as to a different dataset from Atlanta. We compare spatial and temporal variability of IMSIs to single-pollutant indicators (carbon monoxide (CO), nitrogen oxides (NO x ) and elemental carbon (EC)) and multipollutant source apportionment factors produced by Positive Matrix Factorization (PMF). Across cities, PMF-derived and IMSI gasoline metrics were most strongly correlated with CO ( r = 0.31–0.98), while multipollutant diesel metrics were most strongly correlated with EC ( r = 0.80–0.98). NO x correlations with PMF factors varied across cities ( r = 0.29–0.67), while correlations with IMSIs were relatively consistent ( r = 0.61–0.94). In general, single-pollutant metrics were more correlated with IMSIs ( r = 0.58–0.98) than with PMF-derived factors ( r = 0.07–0.99). A spatial analysis indicated that IMSIs were more strongly correlated ( r > 0.7) between two sites in each city than single pollutant and PMF factors. These findings provide confidence that IMSIs provide a transferable, simple approach to estimate mobile source air pollution in cities with differing topography and source profiles using readily available data.

Keywords: multipollutant; air pollution; exposure metrics; source apportionment; mobile sources; emissions-based indicators (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2014
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