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Optimization of transit bus fleet's life cycle assessment impacts with alternative fuel options


  • Ercan, Tolga
  • Zhao, Yang
  • Tatari, Omer
  • Pazour, Jennifer A.


Public transportation is one of the most promising transportation modes to reduce the environmental emissions of the transportation sector in the U.S. In order to mitigate the environmental impacts brought by the transit bus system, new energy buses are introduced into the vehicle market. The goal of this study is to find an optimal bus fleet combination for different driving conditions to minimize life cycle cost, greenhouse gas emissions, and conventional air pollutant emission impacts. For this purpose, a Multi-Objective Linear Programming approach is used to select the optimum bus fleet combinations. Given different weight scenarios, this method could effectively provide solutions for decision makers with various budget constraints or emission reduction requirements. The results indicate that in heavily congested driving cycles such as the Manhattan area, the battery electric bus is the dominant vehicle type, while the hybrid bus has more balanced performances in most scenarios because of its lower initial investment comparing to battery electric buses. Petroleum powered buses have seldom been selected by the model. The trade-off analysis shows that the overall greenhouse gas impact performance is sensitive to the life cycle cost after certain points, which could provide valuable information for the bus fleet combination planning.

Suggested Citation

  • Ercan, Tolga & Zhao, Yang & Tatari, Omer & Pazour, Jennifer A., 2015. "Optimization of transit bus fleet's life cycle assessment impacts with alternative fuel options," Energy, Elsevier, vol. 93(P1), pages 323-334.
  • Handle: RePEc:eee:energy:v:93:y:2015:i:p1:p:323-334
    DOI: 10.1016/

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    References listed on IDEAS

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    Cited by:

    1. Harris, Andrew & Soban, Danielle & Smyth, Beatrice M. & Best, Robert, 2018. "Assessing life cycle impacts and the risk and uncertainty of alternative bus technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 569-579.
    2. repec:gam:jeners:v:9:y:2016:i:4:p:230:d:66367 is not listed on IDEAS
    3. Zhao, Yang & Noori, Mehdi & Tatari, Omer, 2016. "Vehicle to Grid regulation services of electric delivery trucks: Economic and environmental benefit analysis," Applied Energy, Elsevier, vol. 170(C), pages 161-175.
    4. Tan, Kang Miao & Ramachandaramurthy, Vigna K. & Yong, Jia Ying, 2016. "Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm," Energy, Elsevier, vol. 112(C), pages 1060-1073.
    5. Lajunen, Antti & Lipman, Timothy, 2016. "Lifecycle cost assessment and carbon dioxide emissions of diesel, natural gas, hybrid electric, fuel cell hybrid and electric transit buses," Energy, Elsevier, vol. 106(C), pages 329-342.
    6. Bitzan, John D. & Ripplinger, David G., 2016. "Public transit and alternative fuels – The costs associated with using biodiesel and CNG in comparison to diesel for U.S. public transit systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 17-30.
    7. Rogge, Matthias & van der Hurk, Evelien & Larsen, Allan & Sauer, Dirk Uwe, 2018. "Electric bus fleet size and mix problem with optimization of charging infrastructure," Applied Energy, Elsevier, vol. 211(C), pages 282-295.
    8. Rupp, Matthias & Handschuh, Nils & Rieke, Christian & Kuperjans, Isabel, 2019. "Contribution of country-specific electricity mix and charging time to environmental impact of battery electric vehicles: A case study of electric buses in Germany," Applied Energy, Elsevier, vol. 237(C), pages 618-634.


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