The increasing global emphasis on sustainable transportation drives the need for strong electric vehicle (EV) charging networks. While national plans set high targets for EV adoption, translating these into practical infrastructure placement poses a significant hurdle. This study tackles this by creating detailed maps to show suitable locations for EV charging stations (EVCS) across the Attica region of Greece. Our main approach combines Geographic Information System (GIS) with Multi-Criteria Decision-Making (MCDM), specifically using the Analytic Hierarchy Process (AHP). After reviewing existing research to find important location factors, we adjusted these to fit the unique urban and social features of metropolitan Athens. We established four main criteria, accessibility, social, energy, and environmental, which were then divided into nine sub-criteria for our analysis. We developed four different models, each applying a unique weighting to these criteria (basic, energy-focused, environmental, and social) to see how various planning goals affect spatial outcomes. These models generated graded suitability maps, highlighting areas with high potential for new infrastructure. Central Athens consistently showed the highest suitability, which matches current research and confirms our method’s reliability. This work provides a useful, repeatable framework for local governments to strategically deploy EVCS, supporting urban planning and helping meet national goals for decarbonization and air quality.

According to the European Commission, electric vehicles (EVs) remain parked for 95% of their life, which makes them inefficient. In addition, EV sales are forecasted to rise over the following years, which will create additional electricity demand, especially during peak hours. This challenge coincides with the growing trend of homeowners installing renewable energy sources (RES) in their homes. Therefore, a potential solution to managing the increase in electricity costs and peak demand is the use of EVs as a flexible storage system by utilizing vehicle-to-grid (V2G) technology. The successful market penetration of V2G technology hinges significantly on the willingness of current and future EV drivers to participate. Hence, in the broader context of the promotion and transition to electromobility and related technologies (V2G), the main purpose of this paper was to shed light on the hitherto unknown attitudes of Greek drivers towards V2G technology. The adopted methodology involved a survey questionnaire with statements serving as indicators on a 5-point Likert scale. The results show that Greek drivers highly appreciate the positive environmental impact of EVs but are primarily driven by the potential economic incentives they might receive from engaging with V2G technology. In addition, they appear to be skeptical about both V2G technology and electromobility, mainly due to the increased upfront cost of EVs but also due to the immature V2G market.

The transportation sector is responsible for over 20% of Europe’s CO₂ emissions, significantly worsening urban air quality and compromising public health. Electric vehicles (EVs)—namely BEVs and PHEVs—offer some relief by lowering noise and pollution in urban settings. Nevertheless, their effectiveness in benefiting the environment relies on the current electricity generation mix. In accordance with national energy goals, this study evaluates the environmental effects of EV adoption in Greece until 2035, utilizing a scenario-based approach grounded in the forecasts of the Greek National Energy and Climate Plan. Three different electrification pathways are examined to explore how varying levels of electric vehicle adoption and progress in decarbonizing the power sector could reduce air pollution, particularly in cities. By comparing the projected CO₂, CO, NO_x, PM₁₀, and SO₂ pollutant output from BEVs and PHEVs with those of internal combustion engine vehicles, the study highlights the significance of integrating renewable energy sources and assesses the potential for EVs to reduce emissions within Greece’s changing energy mix.

The current study examines an algorithmic solution for the reduction of carbon dioxide emissions resulting from the optimum energy demand coverage of a typical university campus via the contribution of an existing Combined Heat and Power (CHP) unit of 600 kW_e based on natural gas utilization. The application results of the proposed algorithm for the UNIWA Ancient Grove Campus suggest an optimal operation plan for the corresponding CHP unit and achieve a carbon dioxide emission reduction by almost 55% on an annual basis. In this context, the proposed innovative solution may be equally well applied on several other university campuses with similar positive results for the environment.