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Estimating the Energy Demand and Carbon Emission Reduction Potential of Singapore’s Future Road Transport Sector

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  • Shiddalingeshwar Channabasappa Devihosur

    (School of Engineering and Design, Technical University of Munich, 80333 Munich, Germany
    TUM CREATE Ltd., 1 CREATE Way, #10-02 CREATE Tower, Singapore 138602, Singapore)

  • Anurag Chidire

    (School of Engineering and Design, Technical University of Munich, 80333 Munich, Germany
    TUM CREATE Ltd., 1 CREATE Way, #10-02 CREATE Tower, Singapore 138602, Singapore)

  • Tobias Massier

    (TUM CREATE Ltd., 1 CREATE Way, #10-02 CREATE Tower, Singapore 138602, Singapore)

  • Thomas Hamacher

    (School of Engineering and Design, Technical University of Munich, 80333 Munich, Germany)

Abstract

About 20% of the world’s CO 2 emissions originate from transport. Many countries are committed to decarbonizing their transport sector. Singapore pledged to electrify a whole host of its land transportation fleet, which includes private cars, public buses, ride-hail vehicles, and motorcycles. This paper proposes a simple empirical framework to estimate the future energy demand after 100% electrification has been realized for nine selected road transport vehicle sub-classes and to calculate the carbon emission reduction potential based on various scenarios. The present energy demand for each vehicle sub-class is first calculated based on parameters like petrol and diesel consumption, heat value and density of petrol and diesel, population of vehicle type, and average mileage per vehicle sub-class. Several scenarios are presented, and an analysis is carried out to derive a range of emission factors which are used to estimate the carbon emission reduction potential. Relative to the present day, the future energy demand estimates reveal an overall reduction of 73.60%. Full electrification and a “clean” power generation mix could lead to an emission reduction as high as 93.64% across all vehicles sub-classes, with private cars having the highest reduction potential.

Suggested Citation

  • Shiddalingeshwar Channabasappa Devihosur & Anurag Chidire & Tobias Massier & Thomas Hamacher, 2024. "Estimating the Energy Demand and Carbon Emission Reduction Potential of Singapore’s Future Road Transport Sector," Sustainability, MDPI, vol. 16(11), pages 1-16, June.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:11:p:4754-:d:1407817
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    References listed on IDEAS

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    1. Muhammad Muhitur Rahman & Syed Masiur Rahman & Md Shafiullah & Md Arif Hasan & Uneb Gazder & Abdullah Al Mamun & Umer Mansoor & Mohammad Tamim Kashifi & Omer Reshi & Md Arifuzzaman & Md Kamrul Islam &, 2022. "Energy Demand of the Road Transport Sector of Saudi Arabia—Application of a Causality-Based Machine Learning Model to Ensure Sustainable Environment," Sustainability, MDPI, vol. 14(23), pages 1-21, December.
    2. Gallet, Marc & Massier, Tobias & Hamacher, Thomas, 2018. "Estimation of the energy demand of electric buses based on real-world data for large-scale public transport networks," Applied Energy, Elsevier, vol. 230(C), pages 344-356.
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