Climate change mitigation requires the rapid defossilisation of the German electricity sector. While energy system models are extensively used to evaluate climate change mitigation strategies, they generally consider environmental aspects in a limited manner, often focusing on direct operational emissions. To overcome this limitation, this thesis aims to investigate how the environmental impacts of energy systems can be evaluated through an integrated approach that combines Life Cycle Assessment into an energy system model. Integrating both methodologies enables a more comprehensive evaluation by including upstream and downstream environmental impacts and indicators related to ecosystems, human health and resources. However, the integration is challenging due to data inconsistencies. A core contribution of this thesis is developing a systematic process to compile and automate input parameters to ensure a consistent collection of data relevant to both methodologies. The integration approach enables the generation of consistent scenarios that are tested within the model. The modelled use case is a simplified representation of the European electricity system and is built on Calliope, an open-source Python-based framework for energy system modelling. This thesis conducts a more detailed analysis of Germany within the model, focusing on offshore wind due to its strategic role in the country's renewable energy expansion and the significant technological advancements expected by 2030 and 2050, which existing integration approaches fail to capture. For the first time, this thesis develops and tests an integrated approach that systematically harmonises prospective life cycle, economic, and technical data with the technological, geographical, and temporal scope of both Life Cycle Assessment and the energy system modelling. This approach enables the evaluation of technologies, particularly offshore wind, within a broader electricity system while resolving methodological inconsistencies. The primary scientific contribution of this thesis lies in the methodological innovation that allows for the systematic alignment of assumptions between environmental and economic indicators and the assessment of trade-offs between cost and environmental impacts. For instance, the results show that while offshore can reduce the impact on greenhouse gas emissions in 2030 by up to 80 % compared to current levels, the associated investment, however, is up to 40 % higher than other technological alternatives. In addition, offshore wind can increase impacts on ecotoxicity, and water use due to its used materials and manufacturing processes. This integrated modelling approach facilitates not only the assessment of trade-offs between cost and environmental indicators, but also the provision of deeper insights into the implications of future technologies and supports more informed decision-making for a sustainable energy transition.
Alicia Benitez (Wed,) studied this question.