Sustainable development embraces a broad spectrum of social, economic and ecological aspects. Thus, a sustainable transformation process of energy systems is inevitably multidimensional and needs to go beyond climate impact and cost considerations. An approach for an integrated and interdisciplinary sustainability assessment of energy system transformation pathways is presented here. It first integrates energy system modeling with a multidimensional impact assessment that focuses on life cycle-based environmental and macroeconomic impacts. Then, stakeholders’ preferences with respect to defined sustainability indicators are inquired, which are finally integrated into a comparative scenario evaluation through a multi-criteria decision analysis (MCDA), all in one consistent assessment framework. As an illustrative example, this holistic approach is applied to the sustainability assessment of ten different transformation strategies for Germany. Applying multi-criteria decision analysis reveals that both ambitious (80%) and highly ambitious (95%) carbon reduction scenarios can achieve top sustainability ranks, depending on the underlying energy transformation pathways and respective scores in other sustainability dimensions. Furthermore, this research highlights an increasingly dominant contribution of energy systems’ upstream chains on total environmental impacts, reveals rather small differences in macroeconomic effects between different scenarios and identifies the transition among societal segments and climate impact minimization as the most important stakeholder preferences.

In order to analyse long-term transformation pathways, energy system models generally focus on economical and technical characteristics. However, these models usually do not consider sustainability aspects such as environmental impacts. In contrast, life cycle assessment enables an extensive estimate of those impacts. Due to these complementary characteristics, the combination of energy system models and life cycle assessment thus allows comprehensive environmental sustainability assessments of technically and economically feasible energy system transformation pathways. We introduce FRITS, a FRamework for the assessment of environmental Impacts of Transformation Scenarios. FRITS links bottom-up energy system models with life cycle impact assessment indicators and quantifies the environmental impacts of transformation strategies of the entire energy system (power, heat, transport) over the transition period. We apply the framework to conduct an environmental assessment of multi-sectoral energy scenarios for Germany. Here, a ‘Target’ scenario reaching 80% reduction of energy-related direct CO₂ emissions is compared with a ‘Reference’ scenario describing a less ambitious transformation pathway. The results show that compared to 2015 and the ‘Reference’ scenario, the ‘Target’ scenario performs better for most life cycle impact assessment indicators. However, the impacts of resource consumption and land use increase for the ‘Target’ scenario. These impacts are mainly caused by road passenger transport and biomass conversion.

Energy scenarios represent a prominent tool to support energy system transitions towards sustainability. In order to better fulfil this role, two elements are widely missing in previous work on designing, analyzing, and using scenarios: First, a more systematic integration of social and socio-technical characteristics of energy systems in scenario design, and, second, a method to apply an accordingly enhanced set of indicators in scenario assessment. In this article, an integrative scenario assessment methodology is introduced that combines these two requirements. It consists of: (i) A model-based scenario analysis using techno-economic and ecological indicators; (ii) a non-model-based analysis using socio-technical indicators; (iii) an assessment of scenario performances with respect to pre-determined indicator targets; (iv) a normalization method to make the two types of results (model-based and non-model-based) comparable; (v) an approach to classify results to facilitate structured interpretation. The combination of these elements represents the added-value of this methodology. It is illustrated for selected indicators, and exemplary results are presented. Methodological challenges and remaining questions, e.g., regarding the analysis of non-model-based indicators, resource requirements, or the robustness of the methodology are pointed out and discussed. We consider this integrative methodology being a substantial improvement of previous scenario assessment methodologies.