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Energy transition scenarios in the transportation sector in Brazil: Contributions from the electrical mobility

Author

Listed:
  • Grangeia, Carolina
  • Santos, Luan
  • Ferreira, Daniel Viana
  • Guimarães, Raphael
  • de Magalhães Ozorio, Luiz
  • Tavares, Arthur

Abstract

During COP 21, the Paris Declaration on Electro-Mobility and Climate Change & Call to Action defined the global goal of reaching 100 million electric vehicles (EV) and 400 million two- or three-wheel vehicles by 2030. As a result, several countries have set national targets for implementing EV as an integral part of low-carbon energy transition. In Brazil, the technological route of biofuels has stood out from the National Alcohol Program (PROALCOOL) in the 1970s to the current National Biofuels Policy (RenovaBio). However, in recent years, the EV market has been gaining a prominent role in business, governmental and academic debates. Thus, this study seeks to analyse the main factors that drive electric mobility in Brazil, from the definition of technical, economic and fiscal parameters, in addition to evaluating hypotheses on the evolution of public policies and prices of EV in the country. Some scenarios were developed to identify the behaviour of the market penetration of EV in the country, based on Bass' technological diffusion model and dynamic systems. Results indicate that the EV purchase price is consolidated as the most relevant variable for the diffusion of electric mobility in Brazil. From the gains derived from economies of scale, a reduction in the price of vehicles is expected given the decrease in the production costs, as well as in price of batteries. We also concluded that the establishment of a regulatory framework and the development of public policies are fundamental to the promotion of electric mobility in the country.

Suggested Citation

  • Grangeia, Carolina & Santos, Luan & Ferreira, Daniel Viana & Guimarães, Raphael & de Magalhães Ozorio, Luiz & Tavares, Arthur, 2023. "Energy transition scenarios in the transportation sector in Brazil: Contributions from the electrical mobility," Energy Policy, Elsevier, vol. 174(C).
    • Handle: RePEc:eee:enepol:v:174:y:2023:i:c:s0301421523000198
    DOI: 10.1016/j.enpol.2023.113434
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    References listed on IDEAS

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    1. Baran, Renato & Legey, Luiz Fernando Loureiro, 2013. "The introduction of electric vehicles in Brazil: Impacts on oil and electricity consumption," Technological Forecasting and Social Change, Elsevier, vol. 80(5), pages 907-917.
    2. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    3. Vasja Roblek & Maja Meško & Iztok Podbregar, 2021. "Impact of Car Sharing on Urban Sustainability," Sustainability, MDPI, vol. 13(2), pages 1-19, January.
    4. Rogers, Everett M, 1976. "New Product Adoption and Diffusion," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 2(4), pages 290-301, March.
    5. Zhang, Xian & Wang, Ke & Hao, Yu & Fan, Jing-Li & Wei, Yi-Ming, 2013. "The impact of government policy on preference for NEVs: The evidence from China," Energy Policy, Elsevier, vol. 61(C), pages 382-393.
    6. Hamed Taherdoost, 2018. "A review of technology acceptance and adoption models and theories," Post-Print hal-03741843, HAL.
    7. Aravena, C. & Denny, E., 2021. "The impact of learning and short-term experience on preferences for electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    8. Kley, Fabian & Lerch, Christian & Dallinger, David, 2011. "New business models for electric cars--A holistic approach," Energy Policy, Elsevier, vol. 39(6), pages 3392-3403, June.
    9. Leonardo Bitencourt & Tiago Abud & Rachel Santos & Bruno Borba, 2021. "Bass Diffusion Model Adaptation Considering Public Policies to Improve Electric Vehicle Sales—A Brazilian Case Study," Energies, MDPI, vol. 14(17), pages 1-19, September.
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    1. Zhao, Congyu & Jia, Rongwen & Dong, Kangyin, 2023. "How does smart transportation technology promote green total factor productivity? The case of China," Research in Transportation Economics, Elsevier, vol. 101(C).

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