Neutral Boundary Layer Urban Dispersion in Scaled Uniform and Nonuniform Residential Building Arrays

Dispersion within idealized urban environments was studied in a simulated neutrally buoyant, 1:200 scale boundary layer with the Meteorological Wind Tunnel at the EPA's Fluid Modeling Facility. The measurements are used to offer a baseline of performance for the mechanical turbulence formulation and concentration predictions of AERMOD, the EPA's preferred Gaussian dispersion model. Scaled meteorological conditions and dispersion characteristics were studied for both uniform and nonuniform building arrays oriented at 0° and 30° with respect to the flow and were compared to baseline, "rural", measurements without the presence of buildings. Particle image velocimetry (PIV) measured velocity and shear stress profiles within each model configuration, whereas hydrocarbon analyzers (HCAs) measured ethane concentrations at defined points throughout the model. Four source locations were examined for each building array, with two in the urban core and two in a street canyon, each with a source within and above the building canopy. Experimental profiles, regardless of their shape, were fitted to Gaussian profiles to determine lateral and vertical plume spread and shift from the wind tunnel centerline. These parameters were compared against a no-building reference case. Concentration predictions using the formulations in AERMOD are computed for 3 variations of modeled velocity profiles for each source, using factor of 2 ( $FAC2$ ) and fractional bias ( $FB$ ) as the governing model evaluation parameters. The two urban configurations were found to decrease the $FAC2$ performance by 34.1% and 30.1% from the no-building reference for the uniform and nonuniform cases, respectively, while producing modeled concentrations of only 48.1% and 62.4% of the 10 highest observed concentrations. These results encouraged simple first-order corrections to improve model performance with an emphasis on predicting maximum concentrations for regulatory purposes. These corrections proved successful for the uniform cases, mitigating $FB$ , and improving the $FAC2$ percentage by 11.4% with more mixed results in nonuniform configurations, highlighting the difficulty in applying uniformly derived parameterizations in realistic, nonuniform environments.