Environmental efficiency of electric vehicles in Europe under various electricity production mix scenarios

Decarbonizing residential transportation sector depends on the energy mix. A need for environmental efficiency of electric vehicles considering the life cycle impacts of electricity generation under different mix scenarios is essential. This research aims to present the first empirical analysis on the environmental efficiency of battery electric vehicles across 27 European countries, considering the average electricity mix, marginal electricity mix (2015?2020), and renewable energy-based electricity mix (2030?2040) scenarios. The midpoints environmental impacts per kWh electricity generation were estimated for each country using the latest ecoinvent v3.7 life cycle environmental impact data. Well-to-wheel environmental impacts of battery electric vehicles were calculated for each country based on a functional unit per km traveled. An input-oriented non-restricted and weight restricted frontier models using the panel-based weights obtained from the European Commission's Joint Research Center (JRC) survey was built to model the environmental efficiency. Finally, the footprint efficiency results related to different electricity production mix scenarios and future projections to improve the environmental efficiency of battery electric vehicles were suggested. The results reveal Finland and Netherland as the most environmentally efficient countries using BEVs for all the electricity mix scenarios. It is seen that average mixes cause lower environmental efficiency scores of battery electric vehicles than marginal mixes due to higher shares of renewable electricity sources in marginal mixes.Scopu

Optimal Design in Energy Retrofit Interventions on Building Stocks: A Decision Support System

During the last years, a growing interest has pivoted around strategies and methodologies for energy efficiency in buildings. Nevertheless, the attention has always been primarily directed to single properties, while the scientific research still lacks in solutions for building portfolios. Assets owners, instead, would require reliable decision-support systems in order to implement the most effective retrofit solutions. Hence, this study intends to elaborate a process to identify the optimal allocation of financial resources for energy enhancements in large building portfolios. Some novelties characterize this research. First, the approach developed covers each aspect of energy retrofits, from energy consumption assessment to on-site construction and management. Second, the level of detail requested is not excessively burdensome, ensuring good reliability. Third, the approach is interdisciplinary, connecting energy forecast techniques, economic analyses with operational research. The method developed has been implemented on a portfolio of 25 buildings in North Italy for testing and validation. It was possible to compare several design alternatives and reach for the best outcome, which demonstrated how this decision support system could be successfully used for real applications