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Modeling lateral plume deflection in the wake of an elongated building
Citation:
Monbureau, E., D. Heist, S. Perry, AND W. Tang. Modeling lateral plume deflection in the wake of an elongated building. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 234:117608, (2020). https://doi.org/10.1016/j.atmosenv.2020.117608
Impact/Purpose:
EPA program offices (e.g., OAQPS) and regional offices, as well as state and local air control agencies, have asked for research to support improvements in AERMOD relative to building downwash. The current research builds upon model improvements delivered in FY17 (Monbureau et al., 2018), and incorporated into AERMOD v. 19191 released in August 2019, by providing improved plume-track parameterizations that better characterize the effects of building downwash on near source air pollutant dispersion that could be considered for inclusion in future releases of AERMOD.
Description:
The plume dispersion model AERMOD provides an efficient method for modeling ground-level pollutant concentrations in wakes of buildings. In recent years, several studies have shown that the downwash algorithms within AERMOD often perform poorly in certain applications. Some studies have proposed modifications to the downwash algorithm in AERMOD to bring the model closer to representing the underlying physical processes associated with building downwash and closer to more accurately modeling observed pollutant concentrations. One such study by Monbureau et al. (2018)made changes to the model that significantly improved its ability to model ground level concentrations for a simple case of a single rectangular building with an elevated, effluent-emitting stack experiencing winds perpendicular to the upwind side of the building. The present study introduces a simple algorithm to enhance AERMOD's ability to appropriately match the dispersion pattern in the complex flow case of non-orthogonal winds. This algorithm, which is based on a rich set of Large-Eddy Simulations (LES), applies to a variety of building dimensions, stack locations, and stack heights. A sensitivity analysis demonstrates how additional modifications to the downwash algorithm may further improve AERMOD in modeling the spatial location of observed ground-level effluent.
