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.

A modeling framework for characterizing near-road air pollutant concentration at community scales

“…We modified the "bottom-up" strategy (Cook et al, 2008)-under which the emissions are accurately represented by each roadway's actual location-to estimate near-road exposures on a large scale while resolving near-road gradients. The approach has been evaluated with an explicit simulation (the bottom-up method) for Portland (Cumberland County), ME, and the model performance has been evaluated against a near-road monitoring study in Detroit, MI, conducted by the EPA and the Federal Highway Administration (FHWA) (Vallero et al, 2013).…”

Sub-Grid Scale Plume Modeling

“…Examples of hybrid modeling for other urban regions, such as Houston, Texas; Philadelphia, Pennsylvania; New Haven, Connecticut; and Detroit, Michigan are provided in [24,[57][58][59][60]. Cook et al [61] discuss the development of local scale emissions for hybrid modeling to simulate air quality near roadways. Other hybrid modeling approaches are discussed in [62][63][64].…”

Effects of improved spatial and temporal modeling of on-road vehicle emissions

“…However, none of these models have the capability to address all of the factors listed above as being important for accurate onroad inventories. Sensitivity studies have been performed that compare link-based emission inventories using TDM data with more traditional on-road emission modeling approaches; they found significant differences in both the mass of emissions and the spatial distribution of emissions Cook et al, 2006Cook et al, , 2008.…”