The increase in overall electricity demand in recent years, together with the rapid and significant changes in electricity generation has motivated increased research addressing environmental impacts of current and future electricity generation and supply systems. This article presents a comprehensive life-cycle assessment (LCA) of electricity generation and supply for the Italian current mix and future scenarios, for a wide set of environmental impacts and indicators, addressing intra-year variations, and including average and marginal demand impact perspectives. The generation mix was modelled for a 3-year period (2018–2020) with hourly and country-specific data, for the main generation technologies; and two future scenarios (for 2030) were modelled applying the EPLANopt energy system model. While future scenarios - with larger renewable energy shares - resulted in reduced environmental impacts in most categories, they were associated with burden shifts. In particular, increased shares of solar photovoltaic generation in future scenarios resulted in significant contributions to mineral and metal resource depletion and to land use impacts. The high penetration of renewable energy sources in future scenarios was also associated with important seasonal and hourly variations, demonstrating the importance of addressing intra-year temporal variations. Moreover, complementing an average with a marginal demand perspective provided insight on potential impacts of demand changes. When considering a marginal demand perspective, future scenarios offered no clear benefits in terms of global warming, for example. The research demonstrated the need for comprehensive and detailed environmental impact assessments with fine time resolution, which can assess seasonal and intra-daily variations, and the evaluation of environmental impacts with both average and marginal demand perspectives highlighted the complementary nature of the two in providing insightful results. The approach is fully replicable to other countries and regions - it can improve LCAs of electricity generation and supply and provide robust results to adequately inform decision-making on electricity generation and demand management, toward more sustainable energy systems.