IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i2p762-d1319979.html
   My bibliography  Save this article

Greenhouse Gas Emissions Performance of Electric, Hydrogen and Fossil-Fuelled Freight Trucks with Uncertainty Estimates Using a Probabilistic Life-Cycle Assessment (pLCA)

Author

Listed:
  • Robin Smit

    (Transport Energy/Emission Research (TER), Launceston, TAS 7249, Australia)

  • Eckard Helmers

    (Environmental Planning and Technology Department, University of Applied Sciences Trier, Umwelt Campus Birkenfeld, P.O. Box 1380, 55761 Birkenfeld, Germany)

  • Michael Schwingshackl

    (Footprint-Consult e.U., 3335 Weyer, Austria)

  • Martin Opetnik

    (Institute of Thermodynamics and Sustainable Propulsion Systems, Graz University of Technology, 8010 Graz, Austria)

  • Daniel Kennedy

    (Transport Energy/Emission Research (TER), Launceston, TAS 7249, Australia)

Abstract

This research conducted a probabilistic life-cycle assessment (pLCA) into the greenhouse gas (GHG) emissions performance of nine combinations of truck size and powertrain technology for a recent past and a future (largely decarbonised) situation in Australia. This study finds that the relative and absolute life-cycle GHG emissions performance strongly depends on the vehicle class, powertrain and year of assessment. Life-cycle emission factor distributions vary substantially in their magnitude, range and shape. Diesel trucks had lower life-cycle GHG emissions in 2019 than electric trucks (battery, hydrogen fuel cell), mainly due to the high carbon-emission intensity of the Australian electricity grid (mainly coal) and hydrogen production (mainly through steam–methane reforming). The picture is, however, very different for a more decarbonised situation, where battery electric trucks, in particular, provide deep reductions (about 75–85%) in life-cycle GHG emissions. Fuel-cell electric (hydrogen) trucks also provide substantial reductions (about 50–70%), but not as deep as those for battery electric trucks. Moreover, hydrogen trucks exhibit the largest uncertainty in emissions performance, which reflects the uncertainty and general lack of information for this technology. They therefore carry an elevated risk of not achieving the expected emission reductions. Battery electric trucks show the smallest (absolute) uncertainty, which suggests that these trucks are expected to deliver the deepest and most robust emission reductions. Operational emissions (on-road driving and vehicle maintenance combined) dominate life-cycle emissions for all vehicle classes. Vehicle manufacturing and upstream emissions make a relatively small contribution to life-cycle emissions from diesel trucks (<5% each), but these are important aspects for electric trucks (5% to 30%).

Suggested Citation

  • Robin Smit & Eckard Helmers & Michael Schwingshackl & Martin Opetnik & Daniel Kennedy, 2024. "Greenhouse Gas Emissions Performance of Electric, Hydrogen and Fossil-Fuelled Freight Trucks with Uncertainty Estimates Using a Probabilistic Life-Cycle Assessment (pLCA)," Sustainability, MDPI, vol. 16(2), pages 1-38, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:2:p:762-:d:1319979
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/2/762/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/2/762/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Simons, Andrew & Bauer, Christian, 2015. "A life-cycle perspective on automotive fuel cells," Applied Energy, Elsevier, vol. 157(C), pages 884-896.
    2. Oshiro, Ken & Masui, Toshihiko, 2015. "Diffusion of low emission vehicles and their impact on CO2 emission reduction in Japan," Energy Policy, Elsevier, vol. 81(C), pages 215-225.
    3. Apostolaki-Iosifidou, Elpiniki & Codani, Paul & Kempton, Willett, 2017. "Measurement of power loss during electric vehicle charging and discharging," Energy, Elsevier, vol. 127(C), pages 730-742.
    4. Zhou, Boya & Wu, Ye & Zhou, Bin & Wang, Renjie & Ke, Wenwei & Zhang, Shaojun & Hao, Jiming, 2016. "Real-world performance of battery electric buses and their life-cycle benefits with respect to energy consumption and carbon dioxide emissions," Energy, Elsevier, vol. 96(C), pages 603-613.
    5. González Palencia, Juan C. & Sakamaki, Tsukasa & Araki, Mikiya & Shiga, Seiichi, 2015. "Impact of powertrain electrification, vehicle size reduction and lightweight materials substitution on energy use, CO2 emissions and cost of a passenger light-duty vehicle fleet," Energy, Elsevier, vol. 93(P2), pages 1489-1504.
    6. Adelchi Azzalini & Antonella Capitanio, 2003. "Distributions generated by perturbation of symmetry with emphasis on a multivariate skew t‐distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 367-389, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu, Hao & Chen, Feng & Cheng, Jinping & Bai, Yucai & Zhao, Shuqing & Wu, Yiheng & Lu, Yin, 2025. "Hydrogen powered heavy-duty trucks may contribute CO2 emission increase instead of reduction under current hydrogen production structure in China," Energy, Elsevier, vol. 315(C).
    2. Maciej Matczak & Andrzej S. Grzelakowski, 2025. "Impact of EU Decarbonization Policy on Polish International Road Freight Competitiveness," Energies, MDPI, vol. 18(7), pages 1-19, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Robin Smit & Daniel William Kennedy, 2022. "Greenhouse Gas Emissions Performance of Electric and Fossil-Fueled Passenger Vehicles with Uncertainty Estimates Using a Probabilistic Life-Cycle Assessment," Sustainability, MDPI, vol. 14(6), pages 1-29, March.
    2. Zhang, Shaojun & Wu, Ye & Un, Puikei & Fu, Lixin & Hao, Jiming, 2016. "Modeling real-world fuel consumption and carbon dioxide emissions with high resolution for light-duty passenger vehicles in a traffic populated city," Energy, Elsevier, vol. 113(C), pages 461-471.
    3. Hegazy, Omar & Barrero, Ricardo & Van den Bossche, Peter & El Baghdadi, Mohamed & Smekens, Jelle & Van Mierlo, Joeri & Vriens, Wouter & Bogaerts, Bruno, 2016. "Modeling, analysis and feasibility study of new drivetrain architectures for off-highway vehicles," Energy, Elsevier, vol. 109(C), pages 1056-1074.
    4. AlSabbagh, Maha & Siu, Yim Ling & Guehnemann, Astrid & Barrett, John, 2017. "Integrated approach to the assessment of CO2e-mitigation measures for the road passenger transport sector in Bahrain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 203-215.
    5. Chaube, Anshuman & Chapman, Andrew & Minami, Akari & Stubbins, James & Huff, Kathryn D., 2021. "The role of current and emerging technologies in meeting Japan’s mid- to long-term carbon reduction goals," Applied Energy, Elsevier, vol. 304(C).
    6. González Palencia, Juan C. & Otsuka, Yuki & Araki, Mikiya & Shiga, Seiichi, 2017. "Scenario analysis of lightweight and electric-drive vehicle market penetration in the long-term and impact on the light-duty vehicle fleet," Applied Energy, Elsevier, vol. 204(C), pages 1444-1462.
    7. Juan C. González Palencia & Van Tuan Nguyen & Mikiya Araki & Seiichi Shiga, 2020. "The Role of Powertrain Electrification in Achieving Deep Decarbonization in Road Freight Transport," Energies, MDPI, vol. 13(10), pages 1-24, May.
    8. Ali Saadon Al-Ogaili & Ali Q. Al-Shetwi & Hussein M. K. Al-Masri & Thanikanti Sudhakar Babu & Yap Hoon & Khaled Alzaareer & N. V. Phanendra Babu, 2021. "Review of the Estimation Methods of Energy Consumption for Battery Electric Buses," Energies, MDPI, vol. 14(22), pages 1-28, November.
    9. Wang, Kesen & Karling, Maicon J. & Arellano-Valle, Reinaldo B. & Genton, Marc G., 2024. "Multivariate unified skew-t distributions and their properties," Journal of Multivariate Analysis, Elsevier, vol. 203(C).
    10. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016. "Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution," International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
    11. Jorge E. Galán & María Rodríguez Moreno, 2020. "At-risk measures and financial stability," Financial Stability Review, Banco de España, issue Autumn.
    12. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    13. Chen, Qihao & Huang, Zhuo & Liang, Fang, 2023. "Measuring systemic risk with high-frequency data: A realized GARCH approach," Finance Research Letters, Elsevier, vol. 54(C).
    14. Ghotge, Rishabh & van Wijk, Ad & Lukszo, Zofia, 2021. "Off-grid solar charging of electric vehicles at long-term parking locations," Energy, Elsevier, vol. 227(C).
    15. Harasis, Salman & Khan, Irfan & Massoud, Ahmed, 2024. "Enabling large-scale integration of electric bus fleets in harsh environments: Possibilities, potentials, and challenges," Energy, Elsevier, vol. 300(C).
    16. Gloria González‐Rivera & C. Vladimir Rodríguez‐Caballero & Esther Ruiz, 2024. "Expecting the unexpected: Stressed scenarios for economic growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 926-942, August.
    17. Yeap, Claudia & Kwok, Simon S. & Choy, S. T. Boris, 2016. "A Flexible Generalised Hyperbolic Option Pricing Model and its Special Cases," Working Papers 2016-14, University of Sydney, School of Economics.
    18. Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2012. "Bayesian adaptive bandwidth kernel density estimation of irregular multivariate distributions," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 732-740.
    19. Isaac E. Cortés & Osvaldo Venegas & Héctor W. Gómez, 2022. "A Symmetric/Asymmetric Bimodal Extension Based on the Logistic Distribution: Properties, Simulation and Applications," Mathematics, MDPI, vol. 10(12), pages 1-17, June.
    20. Toshihiro Abe & Arthur Pewsey, 2011. "Sine-skewed circular distributions," Statistical Papers, Springer, vol. 52(3), pages 683-707, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:2:p:762-:d:1319979. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.