A quantitative modeling approach to energy justice in electric vehicle adoption
Year: 2025
Type: article
Abstract: Electric vehicle (EV) adoption is a key component of the global low-carbon transition, yet it may also give rise to social and ethical issues derived from its widespread adoption. Nonetheless, there is limited research on how justice issues can be integrated into EV-related decision-making, particularly through quantitative modeling. This study employs a system dynamics model to simulate the effects of various policies on EV adoption and charging infrastructure, incorporating quantitative proxies for distributive justice, an energy justice tenet. The model is parametrized and calibrated for the case of Portugal. The results reveal disparities in charging station distribution and EV ownership between urban and rural areas, with ownership parity delayed in scenarios involving increased vehicle demand. The EV market share is projected to reach 26 % in the baseline scenario and up to 83 % under a policy mix scenario by 2050. Subsidy policies further delay rural ownership parity (2045 vs. 2033 in the base case). The urban-to-rural ratio of public charging stations per unit of area varies from 2 to 7 by 2050. This study contributes to the emerging interdisciplinary field of energy justice by providing insights into the complexities of equitable EV adoption, supporting just and sustainable transitions. • Proposal of quantitative proxies for distributive justice in fleet electrification. • Scrapping policies accelerate electric vehicle adoption and fleet renewal. • There is a gap in public charging stations density between urban and rural areas. • Policies can delay ownership parity but may lead to higher electric car adoption. • Including energy justice in decision-making tools is key for a just transition.
Source: Energy
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,260
OpenAlex ID: W4408569005
