Advanced SearchSearch Tips
A Study on Sensitivity of Pollutant Dispersion to Inflow Wind Speed and Turbulent Schmidt Number in a Street Canyon
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
  • Journal title : Atmosphere
  • Volume 25, Issue 4,  2015, pp.659-667
  • Publisher : Korean Meteorological Society
  • DOI : 10.14191/Atmos.2015.25.4.659
 Title & Authors
A Study on Sensitivity of Pollutant Dispersion to Inflow Wind Speed and Turbulent Schmidt Number in a Street Canyon
Wang, Jang-Woon; Kim, Jae-Jin;
  PDF(new window)
In this study, sensitivity of inflow wind speed and turbulent Schmidt number to pollutant dispersion in an urban street canyon is investigated, by comparing CFD-simulated results to wind-tunnel results. For this, we changed systematically inflow wind speed at the street-canyon height ( with the increment of ) and turbulent Schmidt number (0.2~1.3 with interval of 0.1). Also, we performed numerical experiments under the conditions that turbulent Schmidt numbers selected with the magnitude of mean kinetic energy at each grid point were assigned in the street canyon. With the increase of the inflow wind speed, the model underestimated (overestimated) pollutant concentration in the upwind (downwind) side of the street canyon because of the increase of pollutant advection. This implies that, for more realistic reproduction of pollutant dispersion in urban street canyons, large (small) turbulent Schmidt number should be assigned for week (strong) inflow condition. In the cases of selectively assigned turbulent Schmidt number, mean bias remarkably decreased (maximum 60%) compared to the cases of constant turbulent Schmidt number assigned. At week (strong) inflow wind speed, root mean square error decreases as the area where turbulent Schmidt number is selectively assigned becomes large (small).
CFD model;pollutant concentration;wind speed;turbulent Schmidt number;street canyon;
 Cited by
Baik, J.-J., J.-J. Kim, and H.-J.-S. Fernando, 2003: A CFD Model for Simulating Urban Flow and Dispersion. J. Appl. Meteorol., 42, 1636-1648. crossref(new window)

Baik, J.-J., Y.-S. Kang, and J.-J. Kim, 2007: Modeling reactive pollutant dispersion in an urban street canyon. Atmos. Environ., 41, 934-949. crossref(new window)

Brzoska, M.-A., D. Stock, and B. Lamb, 1997: Determination of plume capture by the building wake. J. Wind Engineering Industrial Aerodyn., 67&68, 909-922.

Castro, I.-P., and D.-D. Apsley, 1997: Flow and dispersion over topography: a comparison between numerical and laboratory data for two dimensional flow. Atmos. Environ., 31, 839-850. crossref(new window)

Flesch, T.-K., J.-H. Prueger, and J.-L. Hatfield, 2002: Turbulent Schmidt number from a tracer experiment. Agric. Forest Meteor., 111, 299-307. crossref(new window)

He, G., Y. Guo, and A.-T. Hsu, 1999: The effect of Schmidt number on turbulent scalar mixing in a jet-in-cross flow. Int. J. Heat and Mass Transfer, 42, 3727-3738. crossref(new window)

Huang, H., J. Imran, A.-M. ASCE, and C. Pirmez, 2005: Numerical Model of Turbidity Currents with a Deforming Bottom Boundary. J. Hydrauric Engineering, 131, 283-293. crossref(new window)

Kim, J.-J., and J.-J. Baik, 2003: Effects of inflow turbulence intensity on flow and pollutant dispersion in an urban street canyon. J. Wind Engineering Industrial Aerodyn., 53, 309-329.

Kim, J.-J., and J.-J. Baik, 2004: A numerical study of the effects of ambient wind direction on flow and dispersion in urban street canyons using the RNG k-${\varepsilon}$ turbulence model. Atmos. Environ., 38, 3039-3048. crossref(new window)

Kim, J.-J., and J.-J. Baik, 2005: Classification of Flow Regimes in Urban Street Canyons Using a CFD Model. J. Korean Soc. Atmos. Environ., 21, 525-535.

Koeltzsch, K., 2000: The height dependence of the turbulent Schmidt number within the boundary layer. Atmos. Environ., 34, 1147-1151. crossref(new window)

Lee, Y.-S., and J.-J. Kim, 2011: Effects of an Apartment on Flow and Dispersion in an Urban Area. Atmos. Korean Meteor. Soc., 21, 95-108.

Li, Y., and T. Stathopoulos, 1997: Numerical evaluation of wind-induced dispersion of pollutants around a building. J. Wind Engineering Industrial Aerodyn., 67&68, 757-766.

Lien, F.-S., E. Yee, H. Ji, A. Keats, and K.-J. Hsieh, 2006: Progress and challenges in the development of physically-based numerical models for prediction of flow and contaminant dispersion in the urban environment. Int. J. Computational Fluid Dyn., 20, 323-337.

Park, S.-J., D.-Y. Kim, and J.-J. Kim, 2013: Effects of Atmospheric Stability and Surface Temperature on Microscale Local Airflow in a Hydrological Suburban Area. Atmos. Korean Meteor. Soc., 23, 13-21.

Park, S.-J., and J.-J. Kim, 2014: Effects of Building-roof Cooling on Scalar Dispersion in Urban Street Canyons. Atmos. Korean Meteor. Soc., 24, 331-341.

Park, S.-J., J.-J. Kim., M.-J. Kim, R.-J. Park, and H.-B. Cheong, 2015: Characteristics of flow and reactive pollutant dispersion in urban street canyons. Atmos. Environ., 108, 20-31. crossref(new window)

Patankar, S.-V., 1980: Numerical Heat Transfer and Fluid Flow.

Pavageau, M., and M. Schatzmann, 1999: Wind tunnel measurements of concentration fluctuations in an urban street canyon. Atmos. Environ., 33, 3961-3971. crossref(new window)

Riddle, A., D. Carruthers, A. Sharpe, C. McHugh, and J. Stocker, 2004: Comparisons between FLUENT and ADMS for atmospheric dispersion modelling. Atmos. Environ., 38, 1029-1038. crossref(new window)

Tang, W., A. Huber, B. Bell, and W. Schwarz, 2006: Application of CFD simulations for short-range atmospheric dispersion over open fields and within arrays of building. AMS 14th Joint Conference on the Applications of Air Pollution Meteorology with the A&WMA, Atlanta GA, J1.8.

Tominaga, Y., and T. Stathopoulos, 2007: Turbulent Schmidt numbers for CFD analysis with various types of flowfield. Atmos. Environ., 41, 8091-8099. crossref(new window)

Versteeg, H. K., and W. Malalasekera, 1995: An Introduction to Computational Fluid Dynamics: The Finite Volume Method. Longman, Malaysia, 257 pp.

Wang, X., 2006: Numerical Simulation of Wind Induced Dispersion of Emissions From Rooftop Stacks. M.A.Sc. Thesis, Concordia University, Montreal, Quebec, Canada.

Wang, X., and K.-F. Mcnamara, 2006: Evaluation of CFD Simulation using RANS Turbulence Models for Building Effects on Pollutant Dispersion. Environ. Fluid Mech., 6, 181-202. crossref(new window)

Wang, X., T. Stathopoulos, and P. Saathoff, 2006: Numerical evaluation of dispersion of pollutants in the building environment: comparisons with models and experiments. The Fourth International Symposium on Computational Wind Engineering, Yokohama, Japan., 805-808.

Yakhot, V., S.-A. Orszag, S. Thangam, T.-B. Gatski, and C.-G. Speziale, 1992: Development of turbulence models for shear flows by a double expansion technique. Phys. Fluids A, 4, 1510-1520. crossref(new window)

Yimer, I., I. Campbell, and L.-Y. Jiang, 2002: Estimation of the turbulent Schmidt number from experimental profiles of axial velocity and concentration for High-Reynolds-Number Jet Flows. Can. Aeronautics Space J., 48, 195-200. crossref(new window)

Zhang, Y.-Q., S.-P. Arya, and W.-H. Snyder, 1996: A Comparison of Numerical and Physical Modeling of Stable Atmospheric Flow and Dispersion around a Cubical Building. Atmos. Environ., 30, 1327-1345. crossref(new window)