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Modeling and Impacts of Traffic Emissions on Air Toxics Concentrations near Roadways
Citation:
Venkatram, A., V. ISAKOV, R. L. SEILA, AND R. W. BALDAUF. Modeling and Impacts of Traffic Emissions on Air Toxics Concentrations near Roadways. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 43(20):3191-3199, (2009).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling Division (AMD) conducts research in support of EPA′s mission to protect human health and the environment. AMD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
The dispersion formulation incorporated in the U.S. Environmental Protection Agency’s AERMOD regulatory dispersion model is used to estimate the contribution of traffic-generated emissions of select VOCs – benzene, 1,3-butadiene, toluene – to ambient air concentrations at downwind receptors ranging from 10-m to 100-m from the edge of a major highway in Raleigh, North Carolina. The contributions are computed using the following steps: 1) Evaluate dispersion model estimates with 10-minute averaged NO data measured at 7 m and 17 m [this is consistent with the text below] from the edge of the road during a field study conducted in August, 2006; this step determines the uncertainty in model estimates. 2) Use dispersion model estimates and their uncertainties, determined in step 1, to construct pseudo observations. 3) Fit pseudo observations to actual observations of VOC concentrations measured during five periods of the field study. This provides estimates of the contributions of traffic emissions to the VOC concentrations at the receptors located from 10 m to 100 m from the road. In addition, it provides estimates of emission factors and background concentrations of the VOCs, which are supported by independent estimates from motor vehicle emissions models and regional air quality measurements. The results presented in the paper demonstrate the suitability of the formulation in AERMOD for estimating concentrations associated with mobile source emissions near roadways. This paper also presents an evaluation of the key emissions and dispersion modeling inputs necessary for conducting assessments of local-scale impacts from traffic emissions.
