CFD simulation of pollutant dispersion using anisotropic models: Application to an urban like environment under neutral and stable atmospheric conditions

Abstract

Modeling the atmospheric dispersion of pollutants emitted from different types of sources under various atmospheric conditions is an essential prerequisite for risk assessment studies and emergency preparedness. In this study, we evaluate the performance of different turbulence models and velocity-scalar correlation models implemented in the Code_Saturne. The evaluation is done with observations of four trial cases of the Mock Urban Setting Test (MUST) campaign in an urban type environment and in neutral and stable atmospheric conditions. For all of the trials studied, the CFD model with a first-order closure model (k−ɛ) predicts 61.1% of the concentrations within a factor of two of the observations, which is higher than the percentage of predicted points (58.8%) when a second-order closure model (Rij−ɛ) is used. Overall, the CFD model underestimates observed concentrations, regardless of the turbulence model used. For the trial with slightly stable conditions, the results show that the k−ɛ model combined with an algebraic SGDH model predicts 75% concentrations within a factor of two of the observations. The performance of the k−ɛ model is compared to that of the Rij−ɛ model when used with the algebraic SGDH, GGDH models and with the scalar flux transport equation (DFM model). Under slightly stable atmospheric conditions, the DFM model predicts 69% of concentrations within a factor of two of observations, showing promise for modeling under these conditions, despite its relatively high computational cost.