Simulation of Carbon Emission for Heavy-Duty Vehicle Queuing Systems

  • Yao Yu
  • Jia-yu ZhaiEmail author
  • Xue-gang Ban
  • Jin-xian Weng
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 503)


Road traffic pollution has become one of the main sources of atmospheric pollution. Load of single heavy-duty vehicle often reaches tens of tons, and its exhaust pollution is also several times than small vehicles. Taking container truck as an example, which exhaust emission during the process of queuing will seriously aggravate regional air pollution in the port or terminal. Therefore, this paper uses the MOVES model to perform a simulation study for carbon emission in the process of the container truck queuing at the Shanghai port based on the in-depth analysis of the container terminal queuing system, taking into account the vehicle emission standards in China. Furthermore, the M/G/S/∞/∞/FCFS queuing model is utilized to analyze the trend and intrinsic relationship of the three types of truck carbon emissions, such as CO2, CO, and THC under continuous speed variation. The research result can provide important decision-making support for low-carbon management.


Low-carbon Queue length theory Carbon emission simulation MOVES model 


  1. 1.
    Bishop GA, Hottor-Raguindin R, Stedman DH et al (2015) On-road heavy-duty vehicle emissions monitoring system. Environ Sci Technol 49(3):1639–1645CrossRefGoogle Scholar
  2. 2.
    Hudda N, Fruin S, Delfino RJ et al (2013) Efficient determination of vehicle emission factors by fuel use category using on-road measurements: downward trends on Los Angeles freight corridor I-710. Atmos Chem Phys 13(1):347–357CrossRefGoogle Scholar
  3. 3.
    Morais P, Lord E (2006) Terminal appointment system study. Transport Canada Publication No. TP14570E. Transportation Development Center, Montreal, pp 134–140Google Scholar
  4. 4.
    Giuliano G, O’Brien T (2007) Reducing port-related truck emissions: the terminal gate appointment system at the ports of Los Angeles and Long Beach. Transp Res Part D: Transp Environ 12(7):460–473CrossRefGoogle Scholar
  5. 5.
    Murty KG, Wan Y, Liu J et al (2005) Hong Kong International Terminals gain elastic capacity using a data-intensive decision-support system. Interfaces 35(1):61–75CrossRefGoogle Scholar
  6. 6.
    Guan CQ, Liu RF (2009) Container terminal gate appointment system optimization. Marit Econ Logistics 11(4):378–398CrossRefGoogle Scholar
  7. 7.
    Zeng QC, Zhang XJ, Chen WH et al (2013) Optimization model for truck appointment based on BCMP queuing network. J Syst Eng 28(5):592–599Google Scholar
  8. 8.
    Xu QL, Sun LJ, Hu XP et al (2014) Non-stationary arrive terminal set card booking optimization model. J Dalian Univ Technol 54(5):589–596Google Scholar
  9. 9.
    Liu CL, Ji MJ, Yu TL, Qiu J, Gao N (2011) The capacity of the container terminal operation system. Transp Syst Eng Inf 11(4):118–123Google Scholar
  10. 10.
    Dong G, Chen FY (2012) Typical port truck emission reduction measures at home and abroad and enlightenment to Shanghai. Shipping Econ Manage 2012(19):4–7Google Scholar
  11. 11.
    Wang WY, Zhang YC, Tang GL, Peng Y (2013) Calculation method of carbon emission in port container handling. Harb Eng Technol 50(4):6–10Google Scholar
  12. 12.
    Lu YQ, Yang B, Huang YF (2015) Both carbon emissions and efficiency of scheduling multi-objective optimization. Comput Simul 32(6):386–389Google Scholar
  13. 13.
    Department of Industrial Traffic Statistics, National Bureau of Statistics. China energy statistical yearbook. China Statistics Press, Beijing, 2005–2010Google Scholar
  14. 14.
    Hiraishi T, Krug T, Tanabe K et al (2014) 2013 supplement to the 2006 IPCC guidelines for national greenhouse gas inventories: Wetlands. IPCC, SwitzerlandGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Yao Yu
    • 1
  • Jia-yu Zhai
    • 1
    Email author
  • Xue-gang Ban
    • 1
    • 2
  • Jin-xian Weng
    • 1
  1. 1.College of Transport and Communications, Shanghai Maritime UniversityShanghaiChina
  2. 2.Department of Civil and Environmental EngineeringUniversity of WashingtonSeattleUSA

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