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Well-to-wheel life cycle assessment of transportation fuels derived from different North American conventional crudes

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  • Rahman, Md. Mustafizur
  • Canter, Christina
  • Kumar, Amit

Abstract

A life cycle assessment (LCA) is an extremely useful tool to assess the greenhouse gas (GHG) emissions associated with all the stages of a crude oil’s life from well-to-wheel (WTW). All of the WTW life cycle stages of crude oil consume energy and produce significant amounts of GHG emissions. The present study attempts to quantify the WTW life cycle GHG emissions for transportation fuels derived from five North American conventional crudes through the development of an LCA model called FUNNEL-GHG-CCO (FUNdamental Engineering PrinciplEs-based ModeL for Estimation of GreenHouse Gases in Conventional Crude Oils). This model estimates GHG emissions from all the life cycle stages from recovery of crude to the combustion of transportation fuels in vehicle engines. The contribution of recovery emissions in the total WTW GHG emissions ranges from 3.12% for Mars crude to 24.25% for California’s Kern County heavy oil. The transportation of crude oil and refined fuel contributes only 0.44–1.73% of the total WTW life cycle GHG emissions, depending on the transportation methods and total distance transported. The GHG emissions for refining were calculated from the amount of energy use in the refining of crude oil to produce transportation fuels. All the upstream GHG emissions were allocated to gasoline, diesel, and jet fuel. Refining GHG emissions vary from 13.66–18.70g-CO2eq/MJ-gasoline, 9.71–15.33g-CO2eq/MJ-diesel, and 6.38–9.92g-CO2eq/MJ-jet fuel derived from Alaska North Slope and California’s Kern County heavy oil, respectively. The total WTW life cycle GHG emissions range from 97.55g-CO2eq/MJ-gasoline derived from Mars crude to 127.74g-CO2eq/MJ-gasoline derived from California’s Kern County heavy oil.

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  • Rahman, Md. Mustafizur & Canter, Christina & Kumar, Amit, 2015. "Well-to-wheel life cycle assessment of transportation fuels derived from different North American conventional crudes," Applied Energy, Elsevier, vol. 156(C), pages 159-173.
    • Handle: RePEc:eee:appene:v:156:y:2015:i:c:p:159-173
    DOI: 10.1016/j.apenergy.2015.07.004
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    4. Di Lullo, Giovanni & Zhang, Hao & Kumar, Amit, 2017. "Uncertainty in well-to-tank with combustion greenhouse gas emissions of transportation fuels derived from North American crudes," Energy, Elsevier, vol. 128(C), pages 475-486.
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    12. Elham Ziar & Mehdi Seifbarghy & Mahdi Bashiri & Benny Tjahjono, 2023. "An efficient environmentally friendly transportation network design via dry ports: a bi-level programming approach," Annals of Operations Research, Springer, vol. 322(2), pages 1143-1166, March.
    13. Hamidreza Hasheminasab & Yaghob Gholipour & Mohammadreza Kharrazi & Dalia Streimikiene & Sarfaraz Hashemkhani, 2020. "A dynamic sustainability framework for petroleum refinery projects with a life cycle attitude," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(5), pages 1033-1048, September.
    14. Nicoletti, Jack & You, Fengqi, 2020. "Multiobjective economic and environmental optimization of global crude oil purchase and sale planning with noncooperative stakeholders," Applied Energy, Elsevier, vol. 259(C).
    15. Zhao, Shujie & Song, Qingbin & Zhao, Dongfeng & Wang, Yongqiang, 2023. "Identifying the spatiotemporal carbon footprint of the petroleum refining industry and its mitigation potential in China," Energy, Elsevier, vol. 284(C).
    16. Di Lullo, G. & Oni, A.O. & Kumar, A., 2023. "The development of complex engineering models using artificial neural network-based proxy models for life cycle assessments of energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    17. Moretti, Christian & Moro, Alberto & Edwards, Robert & Rocco, Matteo Vincenzo & Colombo, Emanuela, 2017. "Analysis of standard and innovative methods for allocating upstream and refinery GHG emissions to oil products," Applied Energy, Elsevier, vol. 206(C), pages 372-381.
    18. Orsi, Francesco & Muratori, Matteo & Rocco, Matteo & Colombo, Emanuela & Rizzoni, Giorgio, 2016. "A multi-dimensional well-to-wheels analysis of passenger vehicles in different regions: Primary energy consumption, CO2 emissions, and economic cost," Applied Energy, Elsevier, vol. 169(C), pages 197-209.
    19. Di Lullo, Giovanni & Zhang, Hao & Kumar, Amit, 2016. "Evaluation of uncertainty in the well-to-tank and combustion greenhouse gas emissions of various transportation fuels," Applied Energy, Elsevier, vol. 184(C), pages 413-426.
    20. Siavash Khalili & Eetu Rantanen & Dmitrii Bogdanov & Christian Breyer, 2019. "Global Transportation Demand Development with Impacts on the Energy Demand and Greenhouse Gas Emissions in a Climate-Constrained World," Energies, MDPI, vol. 12(20), pages 1-54, October.
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