Journal of the Korean Society of Urban Environment (한국도시환경학회지)

The Korean Society of Urban Environment (한국도시환경학회)
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A Study on Prediction Model Conformity of Line Source in Urban Area

도시지역에서의 선오염원 예측모델 적합성에 관한 연구

  • Received : 2018.11.12
  • Accepted : 2018.12.21
  • Published : 2018.12.31
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Abstract

Despite the limitations and difficulty in the application of CALINE3 model for air dispersion prediction of roads and tunnels construction businesses in South Korea, the model is being used in all roads construction projects. This study compared the predicted values of CALINE3 and AERMOD model that is suggested by the US EPA, to the values of GRAL model, a Lagrangian particle tracking model developed in Europe, by applying the models to the existing roads of the urban areas. The result showed low relevance to the actual measurement value in the case of CALINE3 model, thus displaying a low trusted value when applying to the urban areas. In the case of using AERMOD model, the predicted values were overly expressed compared to the actual measurement value, thus leading to the need of adding a No2 conversion method to the model in the future. In the case of GRAL model, a Lagrangian particle tracking model, the relevance between the actual and predicted values were high as the model considers the surrounding topography and the buildings all together, thus confirming that the model can be used for air dispersion prediction of the roads in the urban areas. Lastly, the result of this study testing the air prediction models in Jeongneung Measuring Station points that it is necessary for the future studies to expand the testing areas and test the validity of the models continuously.

우리나라 도로건설사업 대기질 예측에 적용되는 CALINE3는 모델의 한계상 도심지역에서 적용이 어려움에도 불구하고 모든 도로 사업에 적용하고 있는 실정이다. 이에 본 연구에서는 CALINE3 및 미국 EPA에서 장래 권장 모델로 사용하고자 하는 AERMOD와 유럽에서 개발된 라그랑지안 입자추적 모델인 GRAL을 실제 도심지역 도로에 적용하여 실측치와 비교하였다. 연구 결과 CALINE3의 경우 실측치와의 상관도가 낮게 나타나 도심지역에 적용시 낮은 신뢰도를 보일수 있는 것으로 분석되었으며, AERMOD의 경우 실측치에 비해 과다하게 예측되는 것으로 나타나 장래 저풍속(1m/s 이하)에 대한 고려방안 마련과 함께 NOx에 대한 변환 방법을 모델 옵션에서 적용할 필요가 있을 것으로 분석되었다. 라그랑지안 입자추적 모델인 GRAL의 경우 주변 지형, 건물 등을 복합적으로 고려하기 때문에 실측치와 모델치의 상관도가 높게 나타나 도심지역 도로변 대기질 예측에 활용할 수 있을 것으로 보인다. 끝으로 본 연구는 정릉로 측정소에 한해 대기 예측 모델의 검증을 실시한 결과로 향후 후속 연구를 통한 검증 지역의 확대와 이에 따른 모델의 타당성 검토가 지속적으로 이루어져야 할 것이다.

Keywords

References

  1. Kim, D. Y. and Choi, S. M., Development of Air Quality Modeling System for Seoul Metropolitan Area, Gyeonggi Research Institute, Korea (2003).
  2. Ministry of Environment (MOE), A Study on the Application Guidelines of Environmental Impact Prediction Model, Korea (2007).
  3. Ministry of Environment (MOE), Guide to Using the Environmental Impact Prediction Model, Korea (2009).
  4. Kang, Y. H., Lee, Y. S., and Park, Y. J., Reduction of Air Pollutants from Tunnels in Automobile Operation, Korea Environment Institute, Korea (2003).
  5. Oke, T. R., "Street design and urban canopy layer climate," Energy and buildings, 11(1), 103-113 (1988). https://doi.org/10.1016/0378-7788(88)90026-6
  6. Jeong, S. J. and Park, O. H., "Development of a New E-${\varepsilon}$ turbulence model for analysing the air flow field within an urban street canyon," Journal of Korean Society for Atmospheric Environment, 15(3) 281-289 (1999).
  7. Britter, R. E. and Hanna, S. R., "Flow and dispersion in urban areas," Annu. Rev. Fluid Mech, 35, 469-496 (2003). https://doi.org/10.1146/annurev.fluid.35.101101.161147
  8. Zhou, Y., Levy, J. I., Evans, J. S., and Hammitt, J. K., "The influence of geographic location on population exposure to emissions from power plants throughout China," Environment International, 32(3), 365-373 (2006). https://doi.org/10.1016/j.envint.2005.08.028
  9. Hwang, M. K., Oh, I. B., and Kim, Y. G., "Numerical Modeling for the Effect of High-rise Buildings on Meteorological Fields over the Coastal Area Using Urbanized MM5," Journal of Korean Society for Atmospheric Environment, 28(5), 495-505 (2012). https://doi.org/10.5572/KOSAE.2012.28.5.495
  10. Psul, E. Benson., CALINE3; A Versatile Dispersion Model for Predicting Air Pollutant Levels Near Hiways and Arterial Streets, Office of Transportation Labotory California Department of Transportation U.S.A (1979).
  11. U.S, Environmental Protection Agency, Revisions to the Guideline on Air Quality Models: Enhancements to the AERMOD Dispersion Modeling System and Incorporation of Approaches To Address Ozone and Fine Particulate Matter, 40 CFR Part 51 (2017).
  12. Ministry of Economy, Trade and Industry, Low Rise Industrial Source Dispersion Model METI-LIS Model Ver. 2.0 Technical Manual. Research Center for Chemical Risk Management National Institute of Advanced Industrial Science and Technology (2005).
  13. Ottl, D., Documentation of the Lagrangian Particle Model GRAL (Graz Lagrangian Model) Vs. 16.8., Government of Styria (2016).
  14. Korea Environment Institute, EIA_Guideline_Series A_II_Ver.1.0., Korea (2015).
  15. U.S. Environmental Protection Agency, User's Guide for the AMS/EPA Regulatory Model (AERMOD), (2018).
  16. Kim, Y. M., Moon, N. K., Ha, J. S., and Kim, M. A., Study on Improvement of Estimation of Emission of Air Pollutants Emitted from Vehicles in Environmental Impact Assessment, Korea Environment Institute, Korea (2017).
  17. National Institute of Environmental Research, Air Pollutant Emission Factor, Korea (2015).
  18. Bruce, Denby., Guidance document for modelling ETC/ACC deliverable (2010).
  19. U.S. Environmental Protection Agency, User's Guide for the AERMOD Meteorological Preprocessor (AERMET) (2018).