International audienceThis study presents an analysis of the environmental performances of Enhanced Geothermal Systems (EGS) located in central Europe based on life cycle assessment (LCA) of ten significant design options. Each of those is identified with a set of several technical parameters including the risk of induced seismicity. Results show that EGS impacts are comparable to those of other renewable energy technologies and significantly lower than those of conventional power plants. A comparison of the ten scenarios enables us to formulate recommendations on the environmental suitability of their design. Moreover, it emerges from this study that the risk of induced seismicity is a key discriminating factor, as it increases proportionally to the environmental benefit. The model based on five impact categories presented in this paper provides a useful tool for obtaining an overview of the environmental constraints of EGS installations and can be replicated to evaluate possible analogous installations exploring other design options

In the life cycle assessment (LCA) context, global sensitivity analysis (GSA) has been identified by several authors as a relevant practice to enhance the understanding of the model's structure and ensure reliability and credibility of the LCA results. GSA allows establishing a ranking among the input parameters, according to their influence on the variability of the output. Such feature is of high interest in particular when aiming at defining parameterized LCA models. When performing a GSA, the description of the variability of each input parameter may affect the results. This aspect is critical when studying new products or emerging technologies, where data regarding the model inputs are very uncertain and may cause misleading GSA outcomes, such as inappropriate input rankings. A systematic assessment of this sensitivity issue is now proposed. We develop a methodology to analyze the sensitivity of the GSA results (i.e. the stability of the ranking of the inputs) with respect to the description of such inputs of the model (i.e. the definition of their inherent variability). With this research, we aim at enriching the debate on the application of GSA to LCAs affected by high uncertainties. We illustrate its application with a case study, aiming at the elaboration of a simple model expressing the life cycle greenhouse gas emissions of enhanced geothermal systems (EGS) as a function of few key parameters. Our methodology allows identifying the key inputs of the LCA model, taking into account the uncertainty related to their description.

Background: The development of 'enhanced geothermal systems' (EGS), designed to extract energy from deep low-enthalpy reservoirs, is opening new scenarios of growth for the whole geothermal sector. A relevant tool to estimate the environmental performances of such emerging renewable energy (RE) technology is Life Cycle Assessment (LCA). However, the application of this cradle-to-grave approach is complex and time-consuming. Moreover, LCA results available for EGS case studies cover a fairly high variability range.