title: Resolving local-scale emissions for modeling air quality near roadways.
abstract: A large body of literature published in recent years suggests increased health risk due to exposure of people to air pollution in close proximity to roadways. As a result, there is a need to more accurately represent the spatial concentration gradients near roadways to develop mitigation strategies. In this paper, we present a practical, readily adaptable methodology, using a "bottom-up" approach to develop a detailed highway vehicle emission inventory that includes emissions for individual road links. This methodology also takes advantage of geographic information system (GIS) software to improve the spatial accuracy of the activity information obtained from a Travel Demand Model. In addition, we present an air quality modeling application of this methodology in New Haven, CT. This application uses a hybrid modeling approach, in which a regional grid-based model is used to characterize average local ambient concentrations, and a Gaussian dispersion model is used to provide texture within the modeling domain because of spatial gradients associated with highway vehicle emissions and other local sources. Modeling results show substantial heterogeneity of pollutant concentrations within the modeling domain and strong spatial gradients associated with roadways, particularly for pollutants dominated by direct emissions.
authors: Office of Transportation and Air Quality, U.S. Environmental Protection Agency, Ann Arbor, MI, USA.
authors: Rich
authors: R
authors: Cook
authors: Vlad
authors: V
authors: Isakov
authors: Jawad S
authors: JS
authors: Touma
authors: William
authors: W
authors: Benjey
authors: James
authors: J
authors: Thurman
authors: Ellen
authors: E
authors: Kinnee
authors: Darrell
authors: D
authors: Ensley
mesh_terms: D000395:Air Pollutants, Occupational / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis*; D002940:Circadian Rhythm; D003237:Connecticut; D003627:Data Interpretation, Statistical; D004782:Environmental Health; D004784:Environmental Monitoring; D015233:Models, Statistical; D001335:Vehicle Emissions / Q000032:analysis*
chemical_list: D000395:Air Pollutants, Occupational; D001335:Vehicle Emissions