Research

Assessing the sustainability of nuclear energy poses a particular methodological challenge because nuclear technologies have impacts that occur across highly diverse temporal and spatial scales and also vary significantly in terms of their probabilities and institutional prerequisites. This leads to discrepancies and inconsistencies in previous sustainability assessments. The central challenge here is the methodological integration of different types of impacts and normative requirements. This project therefore aims to develop a methodologically robust, scientific, comprehensive, and transparent approach—legitimized through stakeholder participation—that enables the systematic assessment of sustainability in the nuclear energy sector. In doing so, social and governance aspects, such as participation, risk awareness, intergenerational responsibility, or institutional stability, must be given equal consideration alongside ecological and economic criteria. The assessment framework must also be sufficiently differentiated to adequately reflect the nuclear-specific sustainability risks associated with severe accidents, the final disposal of radioactive waste, and proliferation risks. On this basis, the project will ultimately conduct a scientifically sound analysis of the nuclear value chain in comparison with a reference technology.

Austria’s transition to climate neutrality by 2040 requires innovative approaches to managing flexible energy systems, including photovoltaics (PV), battery storage systems, electric vehicles (EVs), and heat pumps. A key component of this transition is the integration of decentralized energy producers and consumers into energy communities (ECs). Achieving optimal energy use and grid stability in ECs, however, demands advanced operational strategies that are inseparably linked to user behavior patterns and entail significant challenges regarding privacy, security, and trust. The TRUST-EC feasibility study examines the transformative potential of responsible and ethical artificial intelligence (AI) to optimize energy management and enhance EC functionality. Adopting an exploratory approach, the study addresses critical uncertainties and risks—technical, regulatory, and sustainability-related—that currently impede the deployment of AI-driven solutions in ECs. By systematically investigating these barriers, the project aims to lay the groundwork for a future research and development (R&D) initiative that goes beyond the current state of the art.

Prospective approaches to risk assessment have gained significance beyond the field of technology assessment and are now also being adopted and promoted at the regulatory level. Their particular advantage lies in their ability to assess potential risks early on in innovation processes. In this way, they enable safety assessments to be targeted and technologies to be designed with risk mitigation in mind. To enable prospective risk assessment as early as possible in the development process, a number of methods have been developed in recent years. These methods account for as broad a spectrum as possible of risk-relevant properties of nanomaterials and advanced materials without requiring extensive experimental testing of these materials. The project aims to further develop these methods and adapt them to the requirements of specific materials such as nanocarriers or micro- and nanoplastic particles.