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Uncertainties in Emissions In Emissions Inputs for Near-Road Assessments
Citation:
Snyder, M., V. Isakov, S. Arunachalam, AND R. Cook. Uncertainties in Emissions In Emissions Inputs for Near-Road Assessments. Presented at AGU Fall Meeting, San Franciso, CA, December 09 - 13, 2013.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD 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 AMAD 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:
Emissions, travel demand, and dispersion models are all needed to obtain temporally and spatially resolved pollutant concentrations. Current methodology combines these three models in a bottom-up approach based on hourly traffic and emissions estimates, and hourly dispersion concentrations from individual road links that represent the traffic activity. To model a large urban area, this method can be computationally expensive, but can significantly improve characterization of spatial and temporal variability, and reduce model uncertainties.