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Dispersion modelling approaches for near road applications involving noise barriers
Citation:
Heist, D., A. Venkatram, M. Snyder, V. Isakov, S. Perry, D. Carruthers, J. Stocker, S. Smith, AND C. Hood. Dispersion modelling approaches for near road applications involving noise barriers. 16th International Conference on Harmonistion within Atmospheric, Varna, BULGARIA, September 08 - 11, 2014.
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:
The talk will present comparisons with two datasets of the barrier algorithms implemented in two different dispersion models: US EPA’s R-LINE (a research dispersion modelling tool under development by the US EPA’s Office of Research and Development) and CERC’s ADMS model (ADMS-Urban). Two databases, a tracer field study (Idaho Falls) and a wind tunnel study (SLLS), provide measurements used in the development and/or validation of algorithms to simulate dispersion in the presence of noise barriers. Both algorithms show encouraging results, producing estimates that fall primarily within a factor of two of the observations and showing reductions in concentration of approximately the same amount as observed. The modelled vertical profiles follow the general trends of the measured profiles.
