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Emissions benefits of electric vehicles in Uber and Lyft ride-hailing services

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  • Alan Jenn

    (University of California)

Abstract

The use of plug-in electric vehicles in ride-hailing services is expected to have substantial emission reduction benefits. However, these benefits depend on the energy fuel mix in the grid and vehicle usage. Here we employ high-resolution data from Uber and Lyft in California to provide insights into the use of electric vehicles in ride-hailing. The growth in electric vehicle use has been rapid in the past two years and a proportionally small number of electric vehicles are already using a large share of electricity provided by the public charging infrastructure. Concerns about the ability of electric vehicles to provide the same level of service as gasoline vehicles has been overstated: we found no statistical difference between the two technologies for services provided to ride-hailing companies. Lastly, the potential environmental and emission reduction benefits are approximately three times higher for electric vehicles being used in ride-hailing compared with those of regular vehicle usage in California.

Suggested Citation

  • Alan Jenn, 2020. "Emissions benefits of electric vehicles in Uber and Lyft ride-hailing services," Nature Energy, Nature, vol. 5(7), pages 520-525, July.
    • Handle: RePEc:nat:natene:v:5:y:2020:i:7:d:10.1038_s41560-020-0632-7
    DOI: 10.1038/s41560-020-0632-7
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    Citations

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    Cited by:

    1. Matteo Böhm & Mirco Nanni & Luca Pappalardo, 2022. "Gross polluters and vehicle emissions reduction," Nature Sustainability, Nature, vol. 5(8), pages 699-707, August.
    2. Qiu, Yueming Lucy & Wang, Yi David & Iseki, Hiroyuki & Shen, Xingchi & Xing, Bo & Zhang, Huiming, 2022. "Empirical grid impact of in-home electric vehicle charging differs from predictions," Resource and Energy Economics, Elsevier, vol. 67(C).
    3. Wei Chen & Jian Chen & Guopeng Yin, 2022. "Exploring side effects of ridesharing services in urban China: role of pollution–averting behavior," Electronic Commerce Research, Springer, vol. 22(4), pages 1007-1034, December.
    4. Lai, Zhijie & Li, Sen, 2024. "Towards a multimodal charging network: Joint planning of charging stations and battery swapping stations for electrified ride-hailing fleets," Transportation Research Part B: Methodological, Elsevier, vol. 183(C).
    5. Junchi Ma & Yuan Zhang & Zongtao Duan & Lei Tang, 2023. "PROLIFIC: Deep Reinforcement Learning for Efficient EV Fleet Scheduling and Charging," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    6. Long Chen & Xiaokun Liu & Peng Jing, 2023. "Do Unprecedented Gasoline Prices Affect the Consumer Switching to New Energy Vehicles? An Integrated Social Cognitive Theory Model," Sustainability, MDPI, vol. 15(10), pages 1-25, May.
    7. Li, Yanning & Li, Xinwei & Jenn, Alan, 2022. "Evaluating the emission benefits of shared autonomous electric vehicle fleets: A case study in California," Applied Energy, Elsevier, vol. 323(C).
    8. Doll, Claus & Krauss, Konstantin, 2022. "Nachhaltige Mobilität und innovative Geschäftsmodelle," Studien zum deutschen Innovationssystem 10-2022, Expertenkommission Forschung und Innovation (EFI) - Commission of Experts for Research and Innovation, Berlin.
    9. Shr, Yau-Huo (Jimmy) & Yang, Feng-An & Chen, Yi-Syun, 2023. "The housing market impacts of bicycle-sharing systems," Regional Science and Urban Economics, Elsevier, vol. 98(C).
    10. Rye, Jamie & Sintov, Nicole D., 2024. "Predictors of electric vehicle adoption intent in rideshare drivers relative to commuters," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    11. Alpizar, Francisco & Carlsson, Fredrik & Lanza, Gracia, 2024. "On the perils of environmentally friendly alternatives," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    12. Liang, Jing & Qiu, Yueming (Lucy) & Xing, Bo, 2022. "Impacts of the co-adoption of electric vehicles and solar panel systems: Empirical evidence of changes in electricity demand and consumer behaviors from household smart meter data," Energy Economics, Elsevier, vol. 112(C).
    13. Zhan, Xingbin & Szeto, W.Y. & (Michael) Chen, Xiqun, 2022. "A simulation–optimization framework for a dynamic electric ride-hailing sharing problem with a novel charging strategy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    14. Zhao, Yinan & Wen, Yifan & Wang, Fang & Tu, Wei & Zhang, Shaojun & Wu, Ye & Hao, Jiming, 2023. "Feasibility, economic and carbon reduction benefits of ride-hailing vehicle electrification by coupling travel trajectory and charging infrastructure data," Applied Energy, Elsevier, vol. 342(C).
    15. Atour Taghipour & Mohammad Ramezani & Moein Khazaei & Vahid Roohparvar & Erfan Hassannayebi, 2023. "Smart Transportation Behavior through the COVID-19 Pandemic: A Ride-Hailing System in Iran," Sustainability, MDPI, vol. 15(5), pages 1-23, February.
    16. Wang, Yujie & Zhang, Xingchen & Chen, Zonghai, 2022. "Low temperature preheating techniques for Lithium-ion batteries: Recent advances and future challenges," Applied Energy, Elsevier, vol. 313(C).
    17. Taiebat, Morteza & Stolper, Samuel & Xu, Ming, 2022. "Widespread range suitability and cost competitiveness of electric vehicles for ride-hailing drivers," Applied Energy, Elsevier, vol. 319(C).

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