Air pollution dispersion from rooftop emissions around hexahedron buildings was investigated using computational fluid dynamics (referred to hereafter as CFD). The Shear Stress Transport (referred to hereafter as SST) k-ω model in FLUENT CFD code was used to simulate the flow and pollution dispersion around the hexahedron buildings. The two buildings used in the study had the dimensions of H: L: W (where H = height, L = length, and W = width) with the ratios of 1:1:1 and 1:1:2. Experimental data from the wind tunnel obtained by a previous study was used to validate the numerical result of the hexahedron building. Five validation metrics are used to obtain an overall and quantitative evaluation of the performance of SST k-ω models: the fractional bias (FB), the geometric mean bias (MG), the normalized mean square errors (NMSE), the geometric variance (VG), and the factor of 2 of the observations (FAC2). The results of vertical concentration profile and longitudinal surface concentration of the 1:1:2 building illustrate the reasonable performance for all five metrics. However, the lateral concentration profile at X = 3H (where X is the distance from the source) shows poor performance for all of the metrics with the exception of NMSE, and the lateral concentration profile at X = 10H shows poor performance for FB and MG.

This paper presents the performance of a CFD model for the near field dispersion of odor from rooftop emissions. The FLUENT Shear-Stress Transport (SST hereinafter) k-ω turbulence model was used to simulate odor dispersion from a rooftop odor vent. The results were compared with a wind tunnel experiment and the calculated results of ASHRAE 2003 and 2007. The FLUENT SST k-ω turbulence model provided good results for making reasonable predictions about the building rooftop surface normalized dilution. It was found that increasing the vent height (from 1 m to 7 m) reduces rooftop surface normalized dilution. ASHRAE 2003 and ASHRAE 2007 performance measures are generally not as good as FLUENT SST k-ω turbulence model performance measures, with larger MG (the geometric mean bias, VG (the geometric variance), NMSE (the normalized mean square error), FB (Fractional bias), and smaller FAC2 (the fraction of predictions within a factor of two of observations).

In this study we investigated odor (hydrogen sulfide) dispersion around a cubic building by using commercial FLUENT CFD code. The FLUENT Shear-Stress Transport (hereafter SST) k-ω turbulence model was used to simulate odor dispersion from an odor source. The results were compared with a wind tunnel experiment and other simulation results. SST k-ω turbulence model provided good grounds for making reasonable predictions about the building surface concentrations and concentration profiles of selected leeward positions of the cubic building. It was found that a vent, which was positioned 7 m above the top of the square building center, decreased the plume length lower by 0.73 and increased the plume height by 1.43 compared to roof top vents. It was also found that by increasing the vent height there a corresponding decrease in the maximum dimensionless concentration around the roof surface.