A Study on the Comparison of Air Pollutants Emissions according to Three Averaging Methods of Vehicular Travel Speed

자동차 평균통행속도 적용방식에 따른 대기오염 배출량 비교 연구

  • Cho Kyu-Tak (Environmental Planning Institute, Seoul National University)
  • 조규탁 (서울대학교 환경대학원 환경계획연구소)
  • Published : 2005.08.01


This study was conducted to develop a method to be able to estimate the vehicular emissions according to spatial scales-Seoul province, 25 counties and hundreds of grids $(1km{\times}1km)$. First, the emissions at each spatial scale was calculated by using the road network and the travel volume and speed of each link modeled by travel demand model (TDM). Second, the emission at each spatial scale was calculated on the basis of average speeds estimated by using three kinds of averaging method. These are called the provincial, volume-delay function (VDF) and zonal method, respectively. Third, three kinds of emissions and those by TDM are compared each other at three spatial scales. In Seoul (provincial scale), three kinds of emissions are less than those by TDM, but the differences of TDM from three speed averaging methods (SAMs) are small. The relative ratios of three SAMs to TDM are $88\~90\%\;in\;CO,\;99\~100\%\;in\;NOx,\;84\~85\%$ in VOCs. At county scale, NOx among three pollutants showed the highest correlation between TDM and three SAMs and the zonal method among three SAMs was proven to be the highest correlation with TDM. NOx showed the coefficients $(R^2)$ greater than 0.9 in all three SAMs but CO and VOC showed the coefficients $(R^2)$ greater than 0.9 in only zonal method. Slopes of co..elations of all pollutants showed the values close to '1' in zonal method. In the other two SAMs, slopes of NOx showed the values close to '1', but those of CO and VOC showed the values less than 0.85. At grid scale, correlations between TDM and three SAMs were not high. CO showed $0.68\~0.77\;in\;R^2s\;and\;58\~0.68$ in slopes. NOx showed $0.90\~0.94\;in\;R^2s\;and\;0.86\~0.94$ in slopes. VOC showed $0.56\~0.70\;in\;R^2s\;and\;0.48\~0.57$ in slopes. There are not high correlations between TDM and three SAMs in grid scale. This study showed that there is the most suitable method for calculating the average travel speed at each spatial scale and it is thought that the zonal method is more suitable than the VDF or provincial method.


  1. 국립환경연구원(1989) 도시지역 대기질 개선에 관한 연구 (I)
  2. 국립환경연구원(1990) 도시지역 대기질 개선에 관한 연구 (II)
  3. 국립환경연구원(1991) 도시지역 대기질 개선에 관한 연구 (III)
  4. 국립환경연구원 (2004) 대기보전정책수립지원시스템 4차년도 사업 최종보고서 [4. 배출량산정방법론]
  5. 서울시정개발연구원 (1998) 서울시 교통혼잡관리프로그램 실행을 위한 교통수요관리 효과분석체계의 구축, 시정연 98-R-IO
  6. 서울시정개발연구원(1999) 서울시 종합교통분석체계 정립 및 광역통행분석,시정연 99-R-11
  7. 서울특별시 (1996) 2000년대 서울시의 대기오염물질 배출량 예측 및 관리방안연구
  8. 장영기, 최상진, 조규탁, 김태승(2000) 통행량을 고려한 자동 차 대기오염 배출량 산출 조사연구, 대기환경학회 2000 춘계학술대회 논문집,33-35
  9. 조강래, 김양균, 동종인, 염영도, 김종춘, 이영진(1986) 자동차 배출가스에 의한 오염물켈 배출량 산정에 관한 연구(II), 국립환경연구원보 8,151-161
  10. 조강래, 김양균, 동종인, 최병찬, 엄명도(1983) 도심지 자동차 주행패턴에 관한 조사연구, 국립환경연구소보,5, 81-103
  11. 조강래, 김양균, 동종언, 최병찬, 엄명도, 검종춘, 이영진 (1984) 자동차 배출가스에 의한 오염물질 배출량 산정에 관한 연구(I), 국립환경연구소보,6,35-60
  12. 조강래, 김양균, 동종인, 최병찬, 엄명도, 김종춘, 이영진, 주수영, 최양일 (1984) 경유자동차의 오염물질 배출현황 조사연구, 국립환경연구소보,6,61-72
  13. 조강래, 임근상, 동종인, 최병찬, 배정오(1981) 운행중인 자동 차의 일산화탄소 저감대책에 관한 연구, 국립환경연구소보,3,79-85
  14. 조규탁(2002) 자동차 대기오염물질 배출량의 공간해상도 개선을 위한 Nested Top Down Approach 개발, 서울대학교 박사학위논문
  15. 조규탁, 장영기, 최상진(1999) 자동차 오염물질 산정방법 개 선방안, 한국대기환경학회 1999 추계학술대회 논문집,75-76
  16. 한국에너지기술연구원(2001) 자동차 오염물칠 배출량 산출 연구 제3부. 이동오염원(비도혹포함) 배출량 산정
  17. 환경부(1995) 면 및 이동오염원 조사방법 개발 빚 지침서 작성에 관한 연구
  18. 환경부, 국립환경연구원(1998) 대기오염물질배출량('97)
  19. Borrego, C., O . Tchepel, N. Barros, and A.I. Miranda (2000) Impact of road traffic emissions on air quality of the Lisbon area, atmospheric Environment, 34, 4683-4690 https://doi.org/10.1016/S1352-2310(00)00301-0
  20. Brandmeyer, J.E. and H.A. Karimi (2000) Improved spatial allocation methodology for On-road mobile emissions, J. Air & Waste Management Association, 50, 972-980 https://doi.org/10.1080/10473289.2000.10464131
  21. Kuhlwein, J. and R. Friedrich (2000) Uncertainties of modelling emission from road transport, Atmospheric Environment, 34, 4603-4610 https://doi.org/10.1016/S1352-2310(00)00302-2
  22. Lin, K. and D.A. Niemeier (1998) Temporal disaggregation of travel demand for high resolution emission inventories, Transportation research Part D 3(6), 375-387 https://doi.org/10.1016/S1361-9209(98)00003-0
  23. Lindley, S.J., D.E. Conlan, D.W. Raper, and A.F.R. Watson (1999) Estimation of spatially resolved road transport emissions for air quality management applications in the North West region of England, The Science of the Total Environment, 235, 119-132 https://doi.org/10.1016/S0048-9697(99)00200-4
  24. Mensink, C., De I. Vlieger, and J. Nys (2000) An urban transport emission model for the Antwerp area, Atmospheric Environment, 34,4595-4602 https://doi.org/10.1016/S1352-2310(00)00215-6
  25. Niemeier, D.A., K. Lin, and J. Utts (1999) Using observed traffic volumes to improve fine-grained regional emission estimation, Transportation research Part D 4,313-332 https://doi.org/10.1016/S1361-9209(99)00011-5
  26. Samaras, Z., N. Kyriakis, and T. Zachariadis (1995) Reconciliation of macroscale and microscale motor vehicle emission estimates, The Science of the Total Environment, 169,23 1-239 https://doi.org/10.1016/0048-9697(95)04652-H
  27. Sbayti, H., M. El-Fadel, and I. Kaysi (2002) Effect of roadway network aggregation levels on modeling of traffic-induced emission inventories in Beirut, Transportation Research Part D 7, 163-173 https://doi.org/10.1016/S1361-9209(01)00017-7
  28. Sturm, P.J., K. Pucher, C. Sudy, and R.A. Almbauer (1996) Determination of traffic emissions-intercomparison of different calculation methods, The Science of the Total Environment 189/190, 187-196 https://doi.org/10.1016/0048-9697(96)05209-6