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The recent decision of the U.S. Supreme Court on the regulation of CO2 emissions from new motor vehicles shows the need for a robust methodology to evaluate the fraction of attributable risk from such emissions. The methodology must enable decisionmakers to reach practically relevant conclusions on the basis of expert assessments the decisionmakers see as an expression of research in progress, rather than as knowledge consolidated beyond any reasonable doubt. This article presents such a methodology and demonstrates its use for the Alpine heat wave of 2003. In a Bayesian setting, different expert assessments on temperature trends and volatility can be formalized as probability distributions, with initial weights (priors) attached to them. By Bayesian learning, these weights can be adjusted in the light of data. The fraction of heat wave risk attributable to anthropogenic climate change can then be computed from the posterior distribution. We show that very different priors consistently lead to the result that anthropogenic climate change has contributed more than 90% to the probability of the Alpine summer heat wave in 2003. The present method can be extended to a wide range of applications where conclusions must be drawn from divergent assessments under uncertainty.

The purpose of this work is to quantify key environmental impacts of electric vehicles deployment in the European Union. This is achieved by soft-linking three models (PRIMES-TREMOVE, DIONE and SHERPA) to explore a base and an alternative scenario. The alternative scenario draws on the assessment of the national policy frameworks for alternative fuels infrastructure requested by the Directive (2014/94/EU). Five environmental indicators are examined: tailpipe CO 2 , NO x and PM 2.5 emissions as well as NO 2 and PM 2.5 urban background concentrations. By 2030, car travel activity is simulated to generate ca. 425 MtCO 2 /year in the EU28 under the alternative scenario. Compared to the base scenario, electric vehicles contribute to a 3% reduction in tailpipe CO 2 emissions. Only two countries attain CO 2 emission reductions greater than 10% in the model. The need for a higher level of policy ambition towards the deployment of less polluting vehicles in Europe is highlighted as a conclusion.

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Electric vehicles (EVs) can play an important role in improving the European Union’s (EU)’s energy supply security, reducing the environmental impact of transport, and increasing EU competitiveness. The EU aims at fostering the synchronised deployment of EVs and necessary recharging infrastructure. There is currently a lack of studies in the literature for analysing the societal impacts of EV and infrastructure deployment at continental scale. In our paper, we analyse the likely impact of related plans of the EU member states (MSs). With the help of qualitative and quantitative analyses, we study the impact of plans on recharging infrastructure deployment, contributions to the EU climate and energy goals, air quality objectives, and reinforcement of the EU’s competitiveness and job creation. We soft-link a fleet impact model with a simplified source receptor relationship model, and propose a new model to calculate job impacts. The results overall show modest impacts by 2020, as most member states’ plans are not very ambitious. According to our analysis of the plans, a reduction of CO2 emissions by 0.4%, NOx emissions by 0.37%, and PM2.5 emissions by 0.44%, as well as a gross job creation of more than 8000 jobs will be achieved by 2020. The member state plans are very divergent. For countries with more ambitious targets up to 2020, such as Austria, France, Germany, and Luxemburg, the climate, energy, and air quality impacts are significant and show what would be achievable if the EU would increase its pace of EV and infrastructure deployment. We conclude that more ambitious efforts by the member states’ to deploy electric vehicles could accelerate the reduction of CO2 emissions and lead to less dependence on fossil oil-based fuels, along with air quality improvements, while at the same time creating new job opportunities in Europe. In regards to the ratio of publicly accessible recharging points (RPs) per EV, we conclude that member states have to come up with more ambitious targets for recharging point deployment, as the current plans will lead to only one recharging point per every 20 EVs by 2020 across the EU. This paper can serve as useful input to the further the planning of EV and recharging infrastructure deployment in the EU and elsewhere. Our study highlights that the different strategies that are followed in the EU member states can be a fertile ground to identify best practices. It remains a challenge to quantify how different support policies impact EV deployment. In terms of further research needs, we identify that more detailed studies are required to determine an appropriate level of infrastructure deployment, including fast chargers.

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