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동해안의 복잡지형에서 기상장 개선에 따른 CALPUFF 모델의 평가

Evaluation of the CALPUFF Model Using Improved Meteorological Fields in Complex Terrain of East Sea Coast

  • Lee, Chong-Bum (Department of Environmental Science Kangwon National University) ;
  • Kim, Jea-Chul (Department of Environmental Science Kangwon National University)
  • 발행 : 2009.02.28

초록

Donghae city is one of the most representative cement industrial city in Korea. The area is faced with the East Sea to the East and with high montane region of Tae-Back mountain range to the West. Many pollutant sources of air pollution are located near the coast, but the largest point sources of the region are located at the bottom of the mountain area in Donghae city. The local wind is highly affected by local topography and plays an important role in transport and dispersion of contaminants from the pollution sources. This study was designed to evaluate enhancement of MM5 predictions by using Four Dimensional Data Assimilation (FDDA), the SONDE data and the national meteorological station, data only. The alternative meteorological fields predicted with and without FDDA were used to simulate spatial and temporal variations of NOx in combined with Atmospheric Dispersion Models (CALPUFF). For the modeling domain, the alternative meteorological fields with 1.1 km spatial resolution were interpolated to the CALMET with 0.5 km resolution. The vertical layers set to have 35 and 12 layers for MM5 and CALPUFF, respectively. MM5 with the FDDA did not resulted in significant improvement of meteorological field prediction in Donghae region, which is primarily because of complex geography and wind scheme. The result of CALPUFF, however, showed reduction of uncertainty errors by using the interpolation scheme of the actual measurement data.

키워드

참고문헌

  1. 김재철(2006) CALPUFF 모델을 이용한 동해시 지역의 산악지형하에서 대규모 점 오염원에서 배출되는 NOx의 확산현상 모사, 강원대학교 대학원 석사논문, pp. 21-24
  2. 이종범, 김재철, 이강웅, 노철언, 김혜경(2007) 추적기체의 확산 특징과 CALPUFF 모델에 의한 모사, 한국대기환경학회지, 23(4), 405-419 https://doi.org/10.5572/KOSAE.2007.23.4.405
  3. 이종범, 조석연, 전의찬(2006) '광화학 대기오염 생성과정 규명과 저감대책 수립' 최종보고서, 국립환경과학원, pp. 345-347
  4. 이화운, 원혜영, 최현정, 김현구(2005) 광양만권에서의 자료 동화된 대기유동장이 대기오염 물질의 확산장에 미치는 영향에 관한 수치모의, 한국대기환경학회지, 21(2), 169-178
  5. 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(28), 4889-4906 https://doi.org/10.1016/S1352-2310(00)00231-4
  6. Earth Tech, Inc (1999) CALMET model version 5.0 : A User’s Guide for the CALMET, CALPUFF Dispersion Model
  7. Kim, D. and W.R. Stockwell (2007) An online coupled meteorological and air quality modeling study of the effect of complex terrain on the regional transport and transformation of air pollutants over the Western United States. Atmospheric Environment, 41(11), 2319-2334 https://doi.org/10.1016/j.atmosenv.2006.11.031
  8. Seaman, N.L. (2000), Meteorological modeling for air-quality assessments. Atmospheric Environment, 34(12-14). 2231-2259 https://doi.org/10.1016/S1352-2310(99)00466-5
  9. Sistla, G., N. Zhou, W. Hao, J.-Y. Ku, S.T. RaoR, Bornstein, F. Freedman, and P. Thunis (1996) Effects of uncertainties in meteorological inputs on Urban Airshed Model predictions and ozone control strategies. Atmospheric Environment, 30(12), 2011-2025 https://doi.org/10.1016/1352-2310(95)00268-5
  10. Song, Y., M. Zhang, and X. Cai (2006) $PM_{10}$ modeling of Beijing in the winter. Atmospheric Environment, 40(22), 4126-4136 https://doi.org/10.1016/j.atmosenv.2006.03.014
  11. Srinivas, C.V., R. Venkatesan, and A.B. Singh (2007) Sensitivity of mesoscale simulations of land-sea breeze to boundary layer turbulence parameterization. Atmospheric Environment, 41(12), 2534-2548 https://doi.org/10.1016/j.atmosenv.2006.11.027
  12. Willmott, C.J. (1982) Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society, 63(11), 1309-1313 https://doi.org/10.1175/1520-0477(1982)063<1309:SCOTEO>2.0.CO;2
  13. Zhou, Y., J.I. Levy, J.S. Evans, and J.K. Hammitt (2006) The influence of geographic location on population exposure to emissions from power plants throughout China. Environment International, 32(3), 365-373 https://doi.org/10.1016/j.envint.2005.08.028

피인용 문헌

  1. A Status of Atmospheric Environmental Impact Assessment and Future Prospects vol.29, pp.5, 2013, https://doi.org/10.5572/KOSAE.2013.29.5.581
  2. A Study on Effect of Improvement Plan for Wind Energy Forecasting vol.31, pp.1, 2015, https://doi.org/10.5572/KOSAE.2015.31.1.001
  3. Local Wind Field Simulation over Coastal Areas Using Windprofiler Data vol.22, pp.2, 2016, https://doi.org/10.7837/kosomes.2016.22.2.195