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The Diffusion of Passive Tracers in Laminar Shear Flow
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Published on: May 1, 2018

Experimental study on flow and gaseous diffusion behind an isolated building.

Mohamed F Yassin1, Masaake Ohba, Hideyuki Tanaka

  • 1Department of Environmental Technology Management, Kuwait University, Safat, 13060, Kuwait. mohamed_f_yassin@hotmail.com

Environmental Monitoring and Assessment
|January 15, 2008
PubMed
Summary

This study experimentally investigated building effects on urban pollution dispersion using a tracer gas. Results show turbulence mixing thickens velocity profiles and smooths concentrations downwind of obstacles.

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Area of Science:

  • Environmental Science
  • Fluid Dynamics
  • Atmospheric Science

Background:

  • Urban environments present complex challenges for air pollution dispersion modeling.
  • Understanding the impact of buildings on airflow and pollutant spread is crucial for accurate predictions.
  • Existing numerical models require experimental validation for urban pollution scenarios.

Purpose of the Study:

  • To experimentally investigate the effect of building obstacles on gaseous diffusion in the wake region.
  • To provide data for validating numerical models of urban pollution dispersion.
  • To analyze flow and diffusion fields in a simulated urban boundary layer.

Main Methods:

  • Utilized a boundary layer wind tunnel under neutral atmospheric conditions.
  • Employed a tracer gas technique with a point source (no buoyancy) and a high-rise building model at a 1:500 scale.
  • Measured velocity fields and turbulence using a hot-wire anemometer and concentration data with a fast flame ionization detector (FID).

Main Results:

  • Observed thickened vertical profiles of longitudinal mean velocity in the obstacle wake region due to turbulence mixing.
  • Found that concentration differences smoothed with increasing downwind distance from the obstacle.
  • Quantified vertical and lateral mean concentrations and concentration fluctuation intensity.

Conclusions:

  • Experimental findings enhance the understanding of pollutant dispersion mechanisms in urban settings.
  • The data generated can be used to validate computational fluid dynamics (CFD) models.
  • Building geometry significantly influences airflow and pollutant dispersal patterns in urban canyons.