6.5
The Influence of Obstacles on the Flow and Pollutant Dispersion in an Urban Environment

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Thursday, 2 February 2006: 12:00 PM
The Influence of Obstacles on the Flow and Pollutant Dispersion in an Urban Environment
A407 (Georgia World Congress Center)
Mohamed Fathy Yassin, Tokyo Polytechnic Univ., Atsugi, Kanagawa, Japan; and M. Ohba and H. Tanaka

Presentation PDF (283.2 kB)

To assist validation of numerical models of urban pollution dispersion, the effect of obstacles on the flow and pollutant dispersion have been investigated experimentally in the boundary layer wind tunnel under neutral atmospheric conditions using a high-raise building model obstacle. The flow and diffusion fields in the boundary layer in an urban environment are investigated in the leeward direction of the obstacle model. The scale of the model experiment is assumed to be at 1:1000. In the experiment, gaseous pollutant is discharged in the simulated boundary layer over the flat terrain. The effluent velocity of the pollutant is set to be negligible. The velocity field and the turbulence characteristics are analyzed and measured using a hot wire anemometer with a split-fiber probe. The experimental technique is involved the continuously release of tracer gas from a ground level source without buoyancy which is located in the downwind of the obstacle and is measured using a fast flame ionization detector (FID). Diffusion characteristics are studied and included both vertical and lateral of mean concentrations fluctuation and turbulence intensity of concentration fluctuation at selected downwind distance. The results of study are demonstrated that the inner boundary layer is very thick around the wake region due to the turbulence mixing and the smoothing of concentration differences is increased with downwind distance from the obstacle. Furthermore, the experimental results can help to improve the understanding of mechanisms of pollutant dispersion in an urban environment and also use to validate the corresponding computational fluid dynamics (CFD) prediction.