Air pollution has been proven as a significant risk factor for multiple health conditions. A major portion of urban air pollution is attributed to vehicle emissions. In this study, a high school which is close to an interstate highway is numerical simulated to estimate the impact of traffic emissions on air quality. Two probability density functions, Weibull distribution and Rayleigh distribution, were used in wind data statistical analysis. A numerical method was used to estimate the wind speed at study site based on the wind data in meteorology stations. Both indoor and outdoor environment were simulated using computational fluid dynamics (CFD). The airflow and the dispersion of particulate air pollutants emitted from the highways surrounding the high school building were analyzed. The wind flow was simulated using Reynolds-Averaged Navier Stokes (RANS) model. The particulate matters are tracked using Lagrangian model. For the indoor simulation, the standard k-ε model is employed to model the air-phase turbulence. Discrete phase model (DPM) and Eulerian multiphase model were utilized for the particle phase, respectively. The comparison shows that the Lagrangian approach has better agreement since the dispersed-phase volume fractions are less than 10%.

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