한국대기환경학회지 (Journal of Korean Society for Atmospheric Environment)

  • 제21권2호
  • /
  • Pages.169-178
  • /
  • 2005
  • /
  • 1598-7132(pISSN)
  • /
  • 2383-5346(eISSN)
한국대기환경학회 (Korean Society for Atmospheric Environment)
권호 표지

광양만권역에서의 자료동화된 대기 유동장이 대기 오염 물질의 확산장에 미치는 영향에 관한 수치모의

Numerical Simulation of Effects of Atmospheric Flow Fields Using SurFace Observational Data on Dispersion Fields of Air Pollutants in Gwangyang Bay

  • Lee Hwa Woon (Department of Atmospheric Sciences, Pusan National University) ;
  • Won Hye Young (Department of Atmospheric Sciences, Pusan National University) ;
  • Choi Hyun-Jung (Department of Atmospheric Sciences, Pusan National University) ;
  • Kim Hyun Goo (Research Institute of Industrial Science & Technology)
  • 발행 : 2005.04.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

A critical component of air pollution modeling is the representation of atmospheric flow fields within a model domain, since an accurate air quality simulation requires an accurate portrayal of the three-dimensional wind fields. The present study investigated data assimilation using surface observational data in the complex coastal regions to simulate a realistic atmospheric flow fields. Surface observational data were categorized into three groups (Near coastal region, Far coastal region 1, Far costal region 2) by the locations where the sites are. Experiments were designed according to the location of observational stations and MM5/CALPUFF was used. The results of numerical simulation of atmospheric flow fields are used as input data for CALPUFF which predicts dispersion fields of air pollutants. The result of this study indicated that data assimilation using data in the far coastal region 2 provided an attractive method for generating realistic meteorological fields and dispersion fields of air pollutants in Gwangyang area because data in the near coastal region are variable and narrow representation.

키워드

참고문헌

  1. 이화운, 원혜영, 최현정 (2004) 복잡한 해안지역에서의 지상관측 자료를 이용한 대기 유동장 수치모의, 한국대기환경학회지, 20(5), 633-645
  2. Barna, M. and B, Lamb (2000) Improving ozone modeling in regions of complex terrain using observational nudging in a prognostic meteorological model, Atmospheric Environment, 34, 4889-4906 https://doi.org/10.1016/S1352-2310(00)00231-4
  3. Chandrasekar, A., C.R. Philbrick, R. Clark, B. Doddridge, and P. Georgopoulos (2003) Evaluating the performance of a computationally efficient MM5/CALMET system for developing wind field inputs to air quality model, Atmospheric Environment, 37, 3267-3276 https://doi.org/10.1016/S1352-2310(03)00325-X
  4. Elbir, T. (2003) Comparison of model predictions with the data of an urban air quality monitoring network in Izmir, Turkey, Atmospheric Environment, 37, 2149-2157 https://doi.org/10.1016/S1352-2310(03)00087-6
  5. Grell, G.A., J. Dudhia, and D.R. Stauffer (1994) A description of the fifth-generation Penn State/NCAR mesoscale model (MM5), NCAR technical Note TN-398+STR, National Center for Atmospheric Research, Boulder, CO.
  6. Hogrefe, C.. S.T. Rao, P. Kasibhatla, W, Hao, G, Sistla, R. Mathur, and J. MaHenry (2001) Evaluating the performance of regional-scale photochemical modeling systems: Part II-ozone predictions, Atmos. Environ., 35, 4175-4188 https://doi.org/10.1016/S1352-2310(01)00183-2
  7. Kumar, N. and A.G. Russell (1996) Comparing prognostic and diagnostic meteorological fields and their impacts on photochemical a quality modeling, Atmospheric Environment, 30(12), 1989-2010 https://doi.org/10.1016/1352-2310(95)00179-4
  8. Lalas, D.P., V.R. Veirs, G. Karras, and G. Kallos (1982) An analysis of the $SO_{2}$ concentration levels in Athens Greece, Atmospheric Environment, 16(3), 531-544 https://doi.org/10.1016/0004-6981(82)90162-7
  9. Lamprecht, R. and D. Berlowitz (1998) Evaluation of diagnostic and prognostic flow fields over prealpine complex terrain by comparison of the lagrangian prediction of concentrations with tracer measurements, Atmospheric Environment, 32(7), 1283-1300 https://doi.org/10.1016/S1352-2310(97)00189-1
  10. Liu, S.C., M. Trainer, F.C. Fehsenfeld, D.D. Parrish, E.J. Williams, D.W. Fahey, G. Huber, and P.C. Murphy (1987) Ozone production in the rural troposphere and implications for regional ozone distributions, Journal of Geophysical Research, 92, 4191-4207 https://doi.org/10.1029/JD092iD04p04191
  11. McKendry, I.G. (1993) Ground-level ozone in Montreal, Canada, Atmospheric Environment, 278(1), 93-103
  12. Russell, A. (1995) Impact of using prognostic and objective wind fields on the photochemical modeling of Athens Greece, Atmospheric Envirionment, 29(24), 3633 -3653 https://doi.org/10.1016/1352-2310(95)00107-A
  13. Scire, J.S., D.G. Strimaitis, and R.J. Yamartino (2000) A User's Guide Guide for the CALPUFF Dispersion Model. Earth Inc
  14. Stauffer, D.R. and N.L. Seaman (1994) Multiscale four-dimensional data assimilation, Journal of Applied Meteorology, 33, 416-426 https://doi.org/10.1175/1520-0450(1994)033<0416:MFDDA>2.0.CO;2