Asian Journal of Atmospheric Environment

  • 제11권4호
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  • Pages.270-282
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  • 2017
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  • 1976-6912(pISSN)
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  • 2287-1160(eISSN)
한국대기환경학회 (Korean Society for Atmospheric Environment)
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Numerical Simulations of Dry and Wet Deposition over Simplified Terrains

  • Michioka, T. (Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry) ;
  • Takimoto, H. (Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry) ;
  • Ono, H. (Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry) ;
  • Sato, A. (Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry)
  • 투고 : 2017.06.07
  • 심사 : 2017.08.23
  • 발행 : 2017.12.31
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초록

To evaluate the deposition amount on a ground surface, mesoscale numerical models coupled with atmospheric chemistry are widely used for larger horizontal domains ranging from a few to several hundreds of kilometers; however, these models are rarely applied to high-resolution simulations. In this study, the performance of a dry and wet deposition model is investigated to estimate the amount of deposition via computational fluid dynamics (CFD) models with high grid resolution. Reynolds-averaged Navier-Stokes (RANS) simulations are implemented for a cone and a two-dimensional ridge to estimate the dry deposition rate, and a constant deposition velocity is used to obtain the dry deposition flux. The results show that the dry deposition rate of RANS generally corresponds to that observed in wind-tunnel experiments. For the wet deposition model, the transport equation of a new scalar concentration scavenged by rain droplets is developed and used instead of the scalar concentration scavenged by raindrops falling to the ground surface just below the scavenging point, which is normally used in mesoscale numerical models. A sensitivity analysis of the proposed wet deposition procedure is implemented. The result indicates the applicability of RANS for high-resolution grids considering the effect of terrains on the wet deposition.

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참고문헌

  1. Balogh, M., Parente, A., Benocci, C. (2012) RANS simulation of ABL flow over complex terrains applying an Enhanced ${\kappa}$-${\varepsilon}$ model and wall function formulation: Implementation and comparison for fluent and OpenFOAM. Journal of Wind Engineering and Industrial Aerodynamics 104-106, 360-368. https://doi.org/10.1016/j.jweia.2012.02.023
  2. Franke, J., Hellsten, A., Schlünzen, H., Carissimo, B. (2007) Best practice guideline for the CFD simulation of flows in the urban environment. COST Action 732, 52.
  3. Hendricks, E.A., Diehl, S.R., Burrows, D.A., Keith, R. (2007) Evaluation of a fast-running urban dispersion modeling system using joint urban 2003 field data. Journal of Applied Meteorology and Climatology 46, 2165-2179. https://doi.org/10.1175/2006JAMC1289.1
  4. Janhall, S. (2015) Review on urban vegetation and particle air pollution-Deposition and dispersion. Atmospheric Environment 105, 130-137. https://doi.org/10.1016/j.atmosenv.2015.01.052
  5. Kajino, M., Inomata, Y., Sato, K., Ueda, H., Han, Z., An, J., Katata, G., Deushi, M., Maki, T., Oshima, N., Kurokawa, J., Ohara, T., Takami, A., Hatakeyama, S. (2012) Development of the RAQM2 aerosol chemical transport model and predictions of the Northeast Asian aerosolo mass, size, chemistry, and mixing type. Atmospheric Chemistry and Physics 12, 11833-11856. https://doi.org/10.5194/acp-12-11833-2012
  6. Katata, G., Ota, M, Terada, H., Chino, M., Nagai, H. (2012a) Atmospheric discharge and dispersion of radionuclides during the Fukushima Dai-ichi Nuclear Power Plant accident. Part I: Source term estimation and local-scale atmospheric dispersion in early phase of the accident. Journal of Environmental Radioactivity 109, 103-113. https://doi.org/10.1016/j.jenvrad.2012.02.006
  7. Katata, G., Terada, H., Nagai, H., Chino, M. (2012b) Numerical reconstruction of high dose rate zones due to the Fukushima Dai-ichi Nuclear Power Plant accident. Journal of Environmental Radioactivity 111, 2-12. https://doi.org/10.1016/j.jenvrad.2011.09.011
  8. Kondo, H., Asahi, K., Tomizuka, T., Suzuki, M. (2006) Numerical analysis of diffusion around a suspended expressway by a multi-scale CFD model. Atmospheric Environment 40, 2852-2859. https://doi.org/10.1016/j.atmosenv.2006.01.012
  9. Kurose, R., Anami, M., Fujita, A., Komori, S. (2012) Numerical simulation of flow pass a heated/cooled sphere. Journal of Fluid Mechanics 692, 332-346. https://doi.org/10.1017/jfm.2011.517
  10. Lin, Y.-L., Farley, R.D., Orville, H.D. (1983) Bulk parameterization of the snow field in a cloud model. Journal of Applied Meteorology 22, 1065-1092. https://doi.org/10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2
  11. Michioka, T., Chow, F.K. (2008) High-resolution large-eddy simulations of scalar transport in atmospheric boundary flow over complex terrain. Journal of Applied Meteorology and Climatology 47, 3150-3169. https://doi.org/10.1175/2008JAMC1941.1
  12. Michioka, T., Sato, A., Sada, K. (2013) Large-eddy simulation coupled to mesoscale meteorological model for gas dispersion in an urban district. Atmospheric Environment 75, 153-162. https://doi.org/10.1016/j.atmosenv.2013.04.017
  13. Morino, Y., Nagashima, T., Sugata, S., Sato, K., Tanabe, K., Noguchi, T., Takami, A., Tanimoto, H., Ohara, T. (2015) Verification of chemical transport models for $PM_{2.5}$ chemical composition using simultaneous measurement data over Japan. Aerosol and Air Qualuty Research 15, 2009-2023.
  14. Nakayama, H., Takemi, T., Nagai, H. (2015) Large-eddy simulation of turbulent winds during the Fukusima Daiichi nuclear power plant accident by coupling with a meso-scale meteorological simulation model. Advances in Science and Research 12, 127-133. https://doi.org/10.5194/asr-12-127-2015
  15. Parker, S.T., Kinnersley, R.P. (2004) A computational and wind tunnel study of particle dry deposition in complex topography. Atmospheric Environment 38, 3867-3878. https://doi.org/10.1016/j.atmosenv.2004.03.046
  16. Pesava, P., Aksu, R., Toprak, S., Horvath, H., Seidl, S. (1999) Dry deposition of particles to building surfaces and soiling. Science of The Total Environment 235, 25-35. https://doi.org/10.1016/S0048-9697(99)00187-4
  17. Sada, K., Michioka, T., Ichikawa, Y. (2008) Numerical model for stack gas diffusion in terrain containing buildings-Application of numerical model to a cubical building and a ridge terrain. Asian Journal of Atmospheric Environment 2-1, 1-13. https://doi.org/10.5572/ajae.2008.2.1.001
  18. Santiago, J.L., Martilli, A., Martin, F. (2007) CFD simulation of airflow over a regular array of cubes. Part I: Three-dimensional simulation of the flow and validation with wind-tunnel measurements. Boundary-Layer Meteorology 122, 609-634. https://doi.org/10.1007/s10546-006-9123-z
  19. Seinfeld, J.H., Pandis, S.N. (2006) Atmospheric chemistry and physics: From air pollution to climate change, Second Edition, Wiley, 1203.
  20. Sekiyama, T.T., Kuni, M., Kajino, M., Shimbori, T. (2015) Horizontal resolution dependence of atmospheric simulations of the Fukushima nuclear accident using 15-km, 3-km, and 500-m grid models. Journal of the meteorological society of Japan 93, 49-64. https://doi.org/10.2151/jmsj.2015-002
  21. Slinn, S.A., Slinn, W.G.N. (1980). Predictions for particle deposition on natural waters. Atmospheric Environment 24, 1013-1016.
  22. Terada, H., Chino, M. (2008) Development of an atmospheric dispersion model for accidental discharge of radionuclides with the function of simultaneous prediction for multiple domains and its evaluation by application to the Chernobyl nuclear accident. Journal of Nuclear Science and Technology 45, 920-931. https://doi.org/10.1080/18811248.2008.9711493
  23. Terada, H., Furuno, A., Chino, M. (2004) Improvement of worldwide version of system for prediction of environmental emergency dose information (WSPEEDI), (I) New combination of models, atmospheric dynamic model MM5 and particle random walk model GEARN-new. Journal of Nuclear Science and Technology 41, 632-640. https://doi.org/10.1080/18811248.2004.9715527
  24. Tominaga, Y., Stathopoulos, T. (2007) Turbulent Schmidt numbers for CFD analysis with various types of flow field. Atmospheric Environment 41, 8091-8099. https://doi.org/10.1016/j.atmosenv.2007.06.054
  25. Wesely, M.L. (1989) Parameterization of surface resistances to gaseous dry deposition in regional-scale numerical models. Atmospheric Environment 23, 1293-1340. https://doi.org/10.1016/0004-6981(89)90153-4