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Analysis on the Correction Factor of Emission Factors and Verification for Fuel Consumption Differences by Road Types and Time Using Real Driving Data

실 주행 자료를 이용한 도로유형·시간대별 연료소모량 차이 검증 및 배출계수 보정 지표 분석

  • LEE, Kyu Jin (TOD-based Sustainable City Transportation Research Center, Ajou University) ;
  • CHOI, Keechoo (Department of Transportation System Engineering, Ajou University)
  • 이규진 (아주대학교 TOD기반 지속가능 도시.교통연구센터) ;
  • 최기주 (아주대학교 교통시스템공학과)
  • Received : 2015.08.11
  • Accepted : 2015.10.26
  • Published : 2015.10.31

Abstract

The reliability of air quality evaluation results for green transportation could be improved by applying correct emission factors. Unlike previous studies, which estimated emission factors that focused on vehicles in laboratory experiments, this study investigates emission factors according to road types and time using real driving data. The real driving data was collected using a Portable Activity Monitoring System (PAMS) according to road types and time, which it compared and analyzed fuel consumption from collected data. The result of the study shows that fuel consumption on national highway is 17.33% higher than the fuel consumption on expressway. In addition, the average fuel consumption of peak time is 4.7% higher than that of non-peak time for 22.5km/h. The difference in fuel consumption for road types and time is verified using ANOCOVA and MANOVA. As a result, the hypothesis of this study - that fuel consumption differs according to road types and time, even if the travel speed is the same - has proved valid. It also suggests correction factor of emission factors by using the difference in fuel consumption. It is highly expected that this study can improve the reliability of emissions from mobile pollution sources.

현재 교통수요모형 기반의 자동차 배출량 추정 모형에서 교통 활동도 자료는 세부적으로 고려되는 반면, 배출계수는 평균적인 값만 반영되고 있기 때문에 배출량 산정 결과의 정확도를 저하시키는 문제가 있다. 본 연구는 도로유형 및 주행시간대와 무관하게 동일한 배출계수가 적용되는 부분을 개선하기 위해, 도로유형과 주행시간대별 연료소모량 차이에 대한 실증적 분석을 기반으로 각 유형별 배출계수의 보정 지표 제시를 목적으로 한다. 이를 위해, '이동식 차량활동도 모니터링 장비(Portable Activity Monitoring System: PAMS)'를 이용해 도로유형 주행시간대별 실 주행 자료를 수집하였고, 각 유형별 연료소모량을 추정하여 이를 비교하였다. 연구 결과 평균 주행속도가 22.5km/h 일 경우, 도로 유형별 주행차량의 가감속도 변화 등의 차이에 따라 국도에서의 연료소모량(95g/km)은 자동차 전용도로에서(81g/km)보다 약 17.3% 높은 것으로 분석되었고, 첨두시간대의 평균 연료소모량(86.73g/km)은 비첨두시간대(82.84g/km)보다 약 4.7% 높은 것으로 분석되었다. 각 유형별 연료소모량의 차이는 공변량 분석 (ANOCOVA)과 다변량 분산분석 (MANOVA)으로 검증하였으며, 그 결과 "주행속도가 동일할지라도, 도로유형과 주행시간대에 따라 연료소모량의 차이가 있다"는 본 연구가설은 유의한 것으로 나타났다. 마지막으로 연료소모량의 차이를 활용하여 각 유형별 배출계수 보정 지표들을 제안하였다. 본 연구는 기존 차량 중심의 배출계수 연구에서 벗어나, 도로 교통 조건에 따른 배출계수 특성을 분석했다는 점에서 의의가 있으며, 본 연구결과를 활용하여 교통부문의 배출량 추정결과에 대한 신뢰성을 향상시킬 수 있을 것으로 기대한다.

Keywords

References

  1. Boriboonsomsin K., Barth M., Xu K. (2009), Improvements to On-road Emission Modeling of Freeways With High-occupancy Vehicle Facilities, Transportation Research Record: Journal of the Transportation Research Board, 2123(1), 109-118. https://doi.org/10.3141/2123-12
  2. Chen C., Huang C., Jing Q., Wang H., Pan H., Li L., Streets D. G. (2007), On-road Emission Characteristics of Heavy-duty Diesel Vehicles in Shanghai, Atmospheric Environment, 41(26), 5334-5344. https://doi.org/10.1016/j.atmosenv.2007.02.037
  3. Choi K. C., Park J. H., Lee J. T., Kim J. S., Lee K. J., Yi Y. J. (2012), Research on Domestic Driving Pattern for International Standardization of Light-duty Vehicles Emission Test Method, J. Korean Soc. Transp., 30(1), Korean Society of Transportation, 31-43.
  4. Coelho M. C., Farias T. L., Rouphail N. M. (2006), Effect of Roundabout Operations on Pollutant Emissions, Transportation Research Part D: Transport and Environment, 11(5), 333-343. https://doi.org/10.1016/j.trd.2006.06.005
  5. Coelho M. C., Frey H. C., Rouphail N. M., Zhai H., Pelkmans L. (2009), Assessing Methods for Comparing Emissions From Gasoline and Diesel Light-duty Vehicles based on Microscale Measurements, Transportation Research Part D: Transport and Environment, 14(2), 91-99. https://doi.org/10.1016/j.trd.2008.11.005
  6. Darrell B. (2009), Developing Link-based Particle Number Emission Models for Diesel Transit Buses Using Engine and Vehicle Parameters, Transportation Research Part D: Transport and Environment, 14(4), 240-248. https://doi.org/10.1016/j.trd.2009.01.009
  7. De Vlieger I. (1997), On Board Emission and Fuel Consumption Measurement Campaign on Petroldriven Passenger Cars, Atmospheric Environment, 31(22), 3753-3761. https://doi.org/10.1016/S1352-2310(97)00212-4
  8. Ericsson E. (2001), Independent Driving Pattern Factors and Their Influence on Fuel-Use and Exhaust Emission Factors, Transportation Research Part D: Transport and Environment, 6(5), 325-345. https://doi.org/10.1016/S1361-9209(01)00003-7
  9. Frey H. C., Rouphail N. M., Zhai H., Farias T. L., Gonçalves G. A. (2007), Comparing Real-World Fuel Consumption for Diesel and Hydrogen-Fueled Transit Buses and Implication for Emissions, Transportation Research Part D: Transport and Environment, 12(4), 281-291. https://doi.org/10.1016/j.trd.2007.03.003
  10. Frey H. C., Zhang K., Rouphail N. M. (2008), Fuel Use and Emissions Comparisons for Alternative Routes, Time of Day, Road Grade, and Vehicles based on in-use Measurements, Environmental Science and Technology, 42(7), 2483-2489. https://doi.org/10.1021/es702493v
  11. Hart C. (2002), Evaluation of an Empirical Binning Approach for Analyzing on-board Emission Data for Moves, Proceedings of the 12th Coordinating Research Council On-road Vehicle Emissions Workshop, San Diego, CA.
  12. Holmen B. A., Niemeier D. A. (1998), Characterizing the Effects of Driver Variability on Real-World Vehicle Emissions, Transportation Research Part D: Transport and Environment, 3(2), 117-128. https://doi.org/10.1016/S1361-9209(97)00032-1
  13. Jimenez-Palacios J. L. (1999), Understanding and Quantifying Motor Vehicle Emissions With Vehicle Specific Power and Tildas Remote Sensing: Massachusetts Institute of Technology, Dept. of Mechanical Engineering.
  14. Joumard R., Jost P., Hickman J., Hassel D. (1995), Hot Passenger Car Emissions Modelling as a Function of Instantaneous Speed and Acceleration, Science of the Total Environment, 169, 167-174. https://doi.org/10.1016/0048-9697(95)04645-H
  15. Koupal J., Michaels H., Cumberworth M., Bailey C., Brzezinski D. (2002), EPA's plan for MOVES: A Comprehensive Mobile Source Emissions Model, Proceedings: 12th CRC On-Road Vehicle Emissions Workshop, San Diego.
  16. Lee T. W., Lee B. H., Cho S. H., Park J. H., Eom M. D., Kim J. C., Lee D. U. (2009), On-Road Testing and Calculation of Emission Factor and Fuel Economy, Transactions of the Korean Society of Automotive Engineers, 17(3), 90-101.
  17. Sonntag D. B., Oliver Gao H. (2009), Developing Link-Based Particle Number Emission Models for Diesel Transit Buses Using Engine and Vehicle Parameters, Transportation Research Part D: Transport and Environment, 14(4), 240-248. https://doi.org/10.1016/j.trd.2009.01.009
  18. US EPA. (2002), Methodology For Developing Modal Emission Rates for EPA's Multi-Scale Motor Vehicle & Equipment Emission System, EPA Report 420-R-02-027.
  19. Wang H., Fu L., Zhou Y., Li H. (2008), Modelling of the Fuel Consumption for Passenger Cars Regarding Driving Characteristics, Transportation Research Part D: Transport and Environment, 13(7), 479-482. https://doi.org/10.1016/j.trd.2008.09.002
  20. Yu L., Wang Z., Qiao F., Qi Y. (2008), Approach to Development and Evaluation of Driving Cycles for Classified Roads Based on Vehicle Emission Characteristics, Transportation Research Record(2058), 58-67.
  21. Zhai H., Frey H. C., Rouphail N. M. (2008), A Vehicle Specific Power Approach to Speed and Facility Specific Emissions Estimates for Diesel Transit Buses, Environmental Science and Technology, 42(21), 7985-7991. https://doi.org/10.1021/es800208d

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