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The Air Quality Modeling According to the Emission Scenarios on Complex Area

복잡지형에서의 배출량 시나리오에 따른 대기질 수치모의

  • Lee, Hwa-Woon (Department of Atmospheric Science, Pusan National University) ;
  • Choi, Hyun-Jung (Department of Atmospheric Science, Pusan National University) ;
  • Lee, Soon-Hwan (Department of Atmospheric Science, Pusan National University) ;
  • Lim, Heon-Ho (Department of Atmospheric Science, Pusan National University) ;
  • Lee, Kang-Yoel (Department of Atmospheric Science, Pusan National University) ;
  • Sung, Kyoung-Hee (Department of Atmospheric Science, Pusan National University) ;
  • Jung, Woo-Sik (Department of Atmospheric Environment Information Engineering, Inje University) ;
  • Park, Jeong-Im (Korea Environment Institute) ;
  • Moon, Nan-Kyung (Korea Environment Institute)
  • Published : 2007.08.31

Abstract

The objective of this work is the air quality modeling according to the scenarios of emission on complex terrain. The prognostic meteorological fields and air quality field over complex areas of Seoul, Korea are generated by the PSU/NCAR mesoscale model (MM5) and the Third Generation Community Multi-scale Air Quality Modeling System (Models - 3/CMAQ), respectively. The emission source was driven from the Clean Air Policy Support System of the Korea National institute of Environmental Research (CAPSS), which is a 1 km x 1 km grid in South Korea during 2003. In comparison of air quality fields, the simulated averaged $PM_{10},\;NO_2,\;and\;O_3$ concentration on complex terrain in control case were decreased as compared with base case. Particularly $PM_{10}$ revealed most substantial localized differences by $(18{\sim}24{\mu}g/m^3)$. The reduction rate of $PM_{10},\;NO_2,\;and\;O_3$ is respectively 18.88, 13.34 and 4.17%.

Keywords

References

  1. 서울 시정 개발 연구원, 2000, 서울시 대기오염 특성연구 120pp
  2. 이화운, 최현정, 이강열, 2005, 상세한 하부 경계조건과 관측값 객관분석이 복잡지형의 대기흐름장 수치모의에 미치는 효과, 한국기상학회지, 41(1), 73-87
  3. 환경부, 2003, 대기오염 배출업소 실태조사표
  4. Byun D. W., Ching J. K. S., 1999, Science algorithms of the EPA Models-3Community Multiscale Air Quality (CMAQ) Modeling System. EPA Report N. EPA-600/R-99/030, Office of Research and Development.US Environmental Protection Agency, Washington, DC. CARB, 2003
  5. Dudhia J., 1993, A nonhydrostatic version of the Penn state-NCAR Mesoscale Model : Validation tests and simulation of an Atlanticcyclone and cold front, Mon. Wea., Rev., 121, 1493-1513 https://doi.org/10.1175/1520-0493(1993)121<1493:ANVOTP>2.0.CO;2
  6. Grell G. A., Dudhia J., Stauffer D. R., 1995, A Description of the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5). NCAR/TN-398+STR, National Center for Atmospheric Research, Boulder, CO, 107
  7. Hong S. Y. Pan H. L., 1996, Nonlocal boundary layer vertical diffusionin a medium-range forecast model, Monthly Weather Rev. 124, 2322-2339 https://doi.org/10.1175/1520-0493(1996)124<2322:NBLVDI>2.0.CO;2
  8. Lee H. W., Choi H. J., Lee K. Y., Lee S. H., Sung K. H., 2006, The Effect of Using Detailed Land-use Conditions for the Photochemical Modeling of Seoul, Korea, JKM, 42(2), 57-73
  9. Reisner J., Rassmussen R. J., Bruintjes R. T., 1998, Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model, Q. J. R., Meteorol. Soc. 124B, 1071-1107
  10. Mlawer, Taubman E. J., S. J., Brown P. D., Iacono M. J., Clough S. A., 1997, Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102 (D14), 16663-16682 https://doi.org/10.1029/97JD00237
  11. Sillman S., 1999, The relation between ozone, NOX and hydrocarbons in urban and polluted rural environment, Atmospheric Environment 33, 1821-1845 https://doi.org/10.1016/S1352-2310(98)00345-8