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Int. J. Environ. Res. Public Health 2014, 11(12), 12739-12766; doi:10.3390/ijerph111212739

Creating Locally-Resolved Mobile-Source Emissions Inputs for Air Quality Modeling in Support of an Exposure Study in Detroit, Michigan, USA

1
Institute for the Environment, University of North Carolina at Chapel Hill, 100 Europa Drive, Suite 490, Chapel Hill, NC 27517, USA
2
National Exposure Research Laboratory, U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA
3
Office of Transportation and Air Quality, U.S. Environmental Protection Agency, 2000 Traverwood Drive, Ann Arbor, MI 48105, USA
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 15 August 2014 / Revised: 27 November 2014 / Accepted: 3 December 2014 / Published: 9 December 2014
(This article belongs to the Special Issue Air Pollution Modeling)
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Abstract

This work describes a methodology for modeling the impact of traffic-generated air pollutants in an urban area. This methodology presented here utilizes road network geometry, traffic volume, temporal allocation factors, fleet mixes, and emission factors to provide critical modeling inputs. These inputs, assembled from a variety of sources, are combined with meteorological inputs to generate link-based emissions for use in dispersion modeling to estimate pollutant concentration levels due to traffic. A case study implementing this methodology for a large health study is presented, including a sensitivity analysis of the modeling results reinforcing the importance of model inputs and identify those having greater relative impact, such as fleet mix. In addition, an example use of local measurements of fleet activity to supplement model inputs is described, and its impacts to the model outputs are discussed. We conclude that with detailed model inputs supported by local traffic measurements and meteorology, it is possible to capture the spatial and temporal patterns needed to accurately estimate exposure from traffic-related pollutants. View Full-Text
Keywords: dispersion models; mobile-source emissions; uncertainties in emissions; R-LINE; human exposure; NEXUS dispersion models; mobile-source emissions; uncertainties in emissions; R-LINE; human exposure; NEXUS
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Snyder, M.; Arunachalam, S.; Isakov, V.; Talgo, K.; Naess, B.; Valencia, A.; Omary, M.; Davis, N.; Cook, R.; Hanna, A. Creating Locally-Resolved Mobile-Source Emissions Inputs for Air Quality Modeling in Support of an Exposure Study in Detroit, Michigan, USA. Int. J. Environ. Res. Public Health 2014, 11, 12739-12766.

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