Effect of Battery Electric Vehicles on Greenhouse Gas Emissions in 29 European Union Countries

Abstract

This analysis explored the effect of battery electric vehicles (BEVs) on greenhouse gas emissions (GHGs) in a panel of twenty-nine countries from the European Union (EU) from 2010 to 2020. The method of moments quantile regression (MM-QR) was used, and the ordinary least squares with fixed effects (OLSfe) was used to verify the robustness of the results. The MM-QR support that in all three quantiles, economic growth causes a positive impact on GHGs. In the 50th and 75th quantiles, energy consumption causes a positive effect on GHGs. BEVs in the 25th, 50th, and 75th quantiles have a negative impact on GHGs. The OLSfe reveals that economic growth has a negative effect on GHGs, which contradicts the results from MM-QR. Energy consumption positively impacts GHGs. BEVs negatively impacts GHGs. Although the EU has supported a more sustainable transport system, accelerating the adoption of BEVs still requires effective political planning to achieve net-zero emissions. Thus, BEVs are an important technology to reduce GHGs to achieve the EU targets of decarbonising the energy sector. This research topic can open policy discussion between industry, government, and researchers, towards ensuring that BEVs provide a climate change mitigation pathway in the EU region.

Effect of Battery-Electric and Plug-In Hybrid Electric Vehicles on PM2.5 Emissions in 29 European Countries

“…Moreover, according to Usman et al [45], this method can capture the unobserved distributional heterogeneity across countries within a panel. Fuinhas et al [46] point out that the MM-QR method has other advantages. According to the authors, this method assumes that the covariate affects only the variables of interest through the location channel.…”

“…where the scalar coefficient α i (τ) = α i + δ i q(τ) denotes the quantileτ fixed effects for an individual country. The distributional impact varies from the classical fixed effect, given that it is not location fixed [46]. Moreover, Machado and Silva [44] state that the distribution impact depicts the time-invariant traits that allow other variables to have diverse effects on investigated countries.…”

“…According to Fuinhas et al [46], the OLS with fixed effects can estimate the slope and intercepts for a set of observations. Moreover, the same authors state that this model can estimate the mean response for the fixed predictors (see Equation (2)).…”

Spatial Premises and Key Conditions for the Use of UAVs for Delivery of Items on the Example of the Polish Courier and Postal Services Market

“…A study published in 2021 on the impact of battery electric vehicles (BEVs) on greenhouse gas emissions in 29 European Union countries indicates that the reduction in energy consumption caused by these vehicles is not sufficient to mitigate greenhouse gas emissions in the European region due to the low share of BEVs in the fleet [9].…”

“…Calculations in the report 'The Future of the Last-Mile Ecosystem' [8] show that by 2030, in the 100 largest cities in the world, the number of delivery vehicles will increase by 36% and exhaust emissions by 32%. Despite the fundamentally positive trends in the pursuit of reducing greenhouse gas emissions in the EU, it is the transport sector, along with the energy production industry and the combustion of fuels by users, that is the most responsible for the persistence of unacceptably high levels of greenhouse gas emissions, and is the only large emitter of CO 2 that increases these emissions [9].…”