Using the Gompertz method and the elastic coefficient approach, we forecast vehicle ownership and GHG emissions, focusing on Shenzhen City as case study. We also factor in the learning curve associated with EV battery costs into our dynamic cost-benefit model. Scenario analysis reveals that Shenzhen’s incremental car restriction policy decreased the number of cars by 18.7% in 2017 alone. By actively promoting EVs in a net zero carbon scenario, it’s feasible that CO2 emissions might reach their peak as soon as 2020. Our cost-benefit analysis indicates that improving fuel economy policies for vehicles yields higher marginal abatement benefits. Although the initial push for EVs may result in elevated marginal abatement costs due to infrastructure investments, anticipated long-term reductions in battery costs, driven by economies of scale, could offset these costs, potentially even leading to net benefits.
Keywords Electric vehicles, greenhouse gas emissions, scenario analysis, cost-effectiveness