Power-to-Gas technologies (PtG) are regarded as promising options to defossilize the energy system by converting and storing renewable electricity to gases. When combined with carbon capture and utilization from large point sources, such as energy intensive and hard-to-abate sectors, where a major part of CO2 emissions cannot be avoided, PtG technologies can also play a role to mitigate CO2 emissions. However, these technologies have several environmental impacts throughout their lifetimes that must be assessed, due to the use of resources, materials, and energy, as well as the formation of chemical by-products. Using a Life Cycle Assessment (LCA) methodology, this paper aims to assess the most significant environmental impacts of an integrated PtG system including the conversion of renewable energy to hydrogen through water wind-based electrolysis, that is further converted to synthetic natural gas (SNG) by reacting with captured CO2 from a cement plant flue gas. More precisely, the present work innovates on both the technical and methodological perspectives. An advanced CO2 capture process is implemented, using mixed amines solvent and innovative configuration to reduce the energy consumption to 2.3 GJ per tCO2 captured, and include an optimized heat integration with the CO2 conversion step. A hybrid approach combining physical and economic input data is also considered for the life cycle inventory. Additionally, both subdivision and system expansion via substitution approaches are applied to consider the multi-functionality of the systems. Simulation results show that the PtG process with CO2 captured from cement plants flue gas reduces the overall GHG emissions by 76%. Similarly, the fossil resource scarcity is drastically reduced by over 80% thanks to the heat integration between the CO2 capture and the CO2 conversion processes, but also thanks to the substitution of natural gas by the CO2-based SNG. Nevertheless, environmental impacts of PtG are higher than conventional natural gas production for other impact categories, including freshwater eutrophication, terrestrial acidification, and mineral resource scarcity. Both data uncertainties, assessing the knowledge base underlying the input data parameters, and sensitivity analysis, assessing the value range of the parameters respectively to the environmental indicators, are conducted to test the results and highlight the uncertainty hotspots.
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