Enhancements to AERMOD’s Building Downwash Algorithms based on Wind-Tunnel and Embedded-LES Modeling -BDW-2

This data set is associated with the results found in the journal article: Monbureau et al, 2018. Enjancements to AERMOD's building downwash algorithms based on wind-tunnel and Embedded-LES modeling. Atmospheric Environment, https://doi.org/10.1016/j.atmosenv.2018.02.022. The goal of this study is to improve AERMOD's ability to accurately model important and complex building downwash scenarios by incorporating knowledge gained from a recently completed series of wind tunnel studies and complementary large eddy simulations of flow and dispersion around simple structures for a variety of building dimensions, stack locations, stack heights, and wind angles. This study presents three modifications to the building downwash algorithm in AERMOD that improve the physical basis and internal consistency of the model, and one modification to AERMOD's building pre-processor to better represent elongated buildings in oblique winds. These modifications are demonstrated to improve the ability of AERMOD to model observed ground-level concentrations in the vicinity of a building for the variety of conditions examined in the wind tunnel and numerical studies.

This dataset is associated with the following publication: Monbureau, E., D. Heist, S. Perry, L. Brouwer, H. Foroutan , and W. Tang. Enhancements to AERMOD's building downwash algorithms based on wind-tunnel and Embedded-LES modeling. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 179: 321-330, (2018).