Journal of Environmental Science International (한국환경과학회지)

The Korean Environmental Sciences Society (한국환경과학회)
권호 표지
DOI QR코드

DOI QR Code

A Regional Source-Receptor Analysis for Air Pollutants in Seoul Metropolitan Area

수도권지역에서의 권역간 대기오염물질 상호영향 연구

  • Lee, Yong-Mi (Air Pollution Control Research Division, National Institute of Environmental Research) ;
  • Hong, Sung-Chul (Climate Change Research Division, National Institute of Environmental Research) ;
  • Yoo, Chul (Air Pollution Control Research Division, National Institute of Environmental Research) ;
  • Kim, Jeong-Soo (Air Quality Research Division, National Institute of Environmental Research) ;
  • Hong, Ji-Hyung (Transportation Pollution Research Center, National Institute of Environmental Research) ;
  • Park, Il-Su (Environmental Science, Han-Kuk University of Foreign Studies)
  • 이용미 (국립환경과학원 대기제어연구과) ;
  • 홍성철 (국립환경과학원 기후변화연구과) ;
  • 유철 (국립환경과학원 대기제어연구과) ;
  • 김정수 (국립환경과학원 대기환경연구과) ;
  • 홍지형 (국립환경과학원 교통환경연구소) ;
  • 박일수 (한국외국어대학교)
  • Received : 2010.01.29
  • Accepted : 2010.04.07
  • Published : 2010.05.31
Download PDF
⟨ Previous Next ⟩

Abstract

This study were to simulate major criteria air pollutants and estimate regional source-receptor relationship using air quality prediction model (TAPM ; The Air Pollution Model) in the Seoul Metropolitan area. Source-receptor relationship was estimated by contribution of each region to other regions and region itself through dividing the Seoul metropolitan area into five regions. According to administrative boundary, region I and region II were Seoul and Incheon in order. Gyeonggi was divided into three regions by directions like southern(region III), northern(IV) and eastern(V) area. Gridded emissions ($1km{\times}1km$) by Clean Air Pollicy Support System (CAPSS) of National Institute of Environmental Research (NIER) was prepared for TAPM simulation. The operational weather prediction system, Regional Data Assimilation and Prediction System (RDAPS) operated by the Korean Meteorology Administration (KMA) was used for the regional weather forecasting with 30km grid resolution. Modeling period was 5 continuous days for each season with non-precipitation. The results showed that region I was the most air-polluted area and it was 3~4 times more polluted region than other regions for $NO_2$, $SO_2$ and PM10. Contributions of $SO_2$ $NO_2$ and PM10 to region I, II and III were more than 50 percent for their own sources. However region IV and V were mostly affected by sources of region I, II and III. When emissions of all regions were assumed to reduce 10 and 20 percent separately, air pollution of each region was reduced linearly and the contributions of reduction scenario were similar to those of base case. As input emissions were reduced according to different ratio - region I 40 percent, region II and III 20 percent, region IV and V 10 percent, air pollutions of region I and III were decreased remarkably. The contributions to region I, II, III were also reduced for their own sources. However, region I, II and III affected more regions IV and V. Shortly, graded reduction of emission could be more effective to control air pollution in emission imbalanced area.

Keywords

References

  1. 국립환경연구원, 2003, 대기보전 정책 수립 지원 시스템구축, 국립환경과학원.
  2. 기상청, 2001(a, b), 일기상통계자료집, 기상청.
  3. 김동영, 2001, 수도권 대기환경관리 정책방향, KRI Newsletter.
  4. 박일수, 이석조, 김종춘, 김상균, 유철, 이동원, 이재범, 송형도, 이정영, 김지현, 2005, 수도권지역에서 오염원별 대기오염농도 기여도 평가, 한국대기환경학회지, 21(5), 495-505.
  5. 박일수, 이석조, 김종춘, 김상균, 이동원, 유철, 이용희, 이정영, 김록호, 2004, 서울을 포함한 수도권지역에서 주요 지역간 배출원.피해지 평가, 국립환경과학원.
  6. 환경부, 2004, 수도권 대기환경관리 기본계획, 환경부.
  7. Azzi, M., Johnson, G. M., Cope, M., 1992, An Introduction to the generic reaction set photochemical smog mechanism. In Proc. 11th Int. Clean Air Conf., 4th Regional IUAPPA Conf., Brisbane, Australia.
  8. Hammerle, J. R., 1976, Emission Inventory, Air Pollution, 3, 718-783.
  9. Hurley, P. J., 2001, The Air Pollution Model(TAPM) Version 2. Part 1: Technical Description, CAR Thecnical Paper N. 25. 25-49.
  10. Hurley, P. J., Blockley, A., Rayner, K., 2001, Verification of a prognostic meteorological and air pollution model for year-long predictions in the Kwinana industrial region of Western Australia, Atmospheric Environment, 35, 1871-1880. https://doi.org/10.1016/S1352-2310(00)00486-6
  11. Hurley, P. J., Physick, W. L., Luhar, A. K., Edwards, M., 2002, The Air Pollution Model(TAPM) Version 2., Part 2: Summary of some verification studies, CSIRO Atmosperic Research Technical paper 72.
  12. Hurley, P. J., Physick, W. L., Luhar, A. K., 2005, TAPM: a practical approach to prognostic meteorological and air pollution modelling, Environmental Modelling & Software, 20, 737-752. https://doi.org/10.1016/j.envsoft.2004.04.006
  13. Katatani, N., 1994, Estimation of region-by-region source contribution ratio to the acid deposition in Japan using model calculations. Proceedings of the 7th IUPPA Rdgional Conference on Air Pollution and Waste Issues, November 2-4, 1994, Taipai, Vol. II, 307-315.
  14. Luhar, A. K., Hurley, P. J., 2004, Application of prognostic model TAPM to sea-breeze flows, surface concentrations and fumigating plumes. Environmental Modelling & Software, 19, 591-601. https://doi.org/10.1016/j.envsoft.2003.08.011
  15. Park, I. S., Lee, S. J., Kim,C. H., Yoo, C., Lee, Y. H., 2004, Simulating urban-scale Air pollutants and their predicting capabilities over the Seoul metropolitan area, J. of the Air & Waste Management Association, 54(6), 695-710. https://doi.org/10.1080/10473289.2004.10470942
  16. Venkatram, A., Karamchandani, P., Prasad, P., Sloane, C., Saxena, P., Goldstein, R., 1997, The development of a model to examine source-receptor relationships for visibility on the Colorado Plateau, J. of the Air and Waste Management Assoc., 47(3), 286-301. https://doi.org/10.1080/10473289.1997.10464453