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The Indirect Carbon Cost of E-Mobility for Select Countries Based on Grid Energy Mix Using Real-World Data

Author

Listed:
  • Nana Kofi Twum-Duah

    (Univ. Grenoble Alpes, CNRS, Grenoble INP*, G2Elab, 38000 Grenoble, France)

  • Lucas Hajiro Neves Mosquini

    (Univ. Grenoble Alpes, CNRS, Grenoble INP*, G2Elab, 38000 Grenoble, France
    University of Applied Sciences of Western Switzerland, Energy Institute, HEIA-FR, 1700 Fribourg, Switzerland)

  • Muhammad Salman Shahid

    (Univ. Grenoble Alpes, CNRS, Grenoble INP*, G2Elab, 38000 Grenoble, France)

  • Seun Osonuga

    (Univ. Grenoble Alpes, CNRS, Grenoble INP*, G2Elab, 38000 Grenoble, France)

  • Frédéric Wurtz

    (Univ. Grenoble Alpes, CNRS, Grenoble INP*, G2Elab, 38000 Grenoble, France)

  • Benoit Delinchant

    (Univ. Grenoble Alpes, CNRS, Grenoble INP*, G2Elab, 38000 Grenoble, France)

Abstract

Electric vehicles are considered by many as an emission-free or low-emission solution to meet the challenge of sustainable transportation. However, the operational input, electrical energy, has an associated cost, greenhouse gasses, which results in indirect emissions. Given this knowledge, we pose the following question: “Are zero-emission transportation targets achievable given our current energy mix?” The objective of this article is to assess the impact of a grid’s energy mix on the indirect emissions of an electric vehicle. The study considers real-world data, vehicle usage data from an electric vehicle, and carbon intensity data for India, the USA, France, the Netherlands, Brazil, Germany, and Poland. Linear programming-based optimization is used to compute the best charging scenario for each of the given grids and, consequently, the indirect emissions are compared to those of a high-efficiency 1.5 L diesel internal combustion engine for the vehicle: a 2019 Renault Clio dCi 85. The results indicate that for grids with low renewable energy penetration, such as those of Poland and India (Maharashtra), an electric vehicle, even when optimally charged, can be classified as neither a low- nor zero-emission alternative to normal thermal vehicles. Also, for grids with elevated levels of variation in their carbon intensity, there is significant potential to reduce the carbon footprint related to charging an electric vehicle. This article provides a real-world perspective of how an electric vehicle performs in the face of different energy mixes and serves as a precursor to the development of robust indicators for determining the carbon reductions related to the e-mobility transition.

Suggested Citation

  • Nana Kofi Twum-Duah & Lucas Hajiro Neves Mosquini & Muhammad Salman Shahid & Seun Osonuga & Frédéric Wurtz & Benoit Delinchant, 2024. "The Indirect Carbon Cost of E-Mobility for Select Countries Based on Grid Energy Mix Using Real-World Data," Sustainability, MDPI, vol. 16(14), pages 1-17, July.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:14:p:5883-:d:1432511
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    References listed on IDEAS

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    1. Kalghatgi, Gautam, 2018. "Is it really the end of internal combustion engines and petroleum in transport?," Applied Energy, Elsevier, vol. 225(C), pages 965-974.
    2. Elsido, Cristina & Bischi, Aldo & Silva, Paolo & Martelli, Emanuele, 2017. "Two-stage MINLP algorithm for the optimal synthesis and design of networks of CHP units," Energy, Elsevier, vol. 121(C), pages 403-426.
    3. Tomáš Skrúcaný & Martin Kendra & Ondrej Stopka & Saša Milojević & Tomasz Figlus & Csaba Csiszár, 2019. "Impact of the Electric Mobility Implementation on the Greenhouse Gases Production in Central European Countries," Sustainability, MDPI, vol. 11(18), pages 1-15, September.
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    Cited by:

    1. Huang, Anzhong & Dai, Luote & Ali, Sajid & Nazar, Raima & Anser, Muhammad Khalid, 2025. "Zero-emission vision: The role of E-mobility technology budgets in carbon mitigation," Transport Policy, Elsevier, vol. 164(C), pages 265-280.

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