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8In life cycle assessments of wind turbines and, more generally, of Renewable Energy Systems (RES), environmental 9 impacts are usually normalized by electricity production to express their performance per kilowatt-hour. For most RES, 10 manufacture and installation dominate the impacts. Hence, results are sensitive to parameters governing both impacting 11 phases and electricity production. Most available studies present the environmental performance of generic wind 12 turbines with assumed fixed values for sensitive parameters (e.g. electricity production) that often vary between studies 13 and fail to reflect specificities of wind farm projects. This study presents an approach to build a comprehensive 14 parameterized model that generates unique wind turbine life cycle inventories conditioned by technologically, 15 temporally and geographically-sensitive parameters. This approach allows for the characterization of the carbon 16 footprint of five sets of turbines in Denmark, where wind power is highly developed. The analysis shows disparities 17 even between turbines of similar power output, mostly explained by the service time, load factor and components 18 weights but also by background processes (evolution of electricity mix and recycled steel content). Project-specific 19 inventories with technologically, temporally and geographically-sensitive parameters are essential for supporting RES 20 development projects. Such inventories are especially important to evaluate highly-renewable electricity mixes, such as 21 that of Denmark. 22 Keywords: wind turbine, parameterized model, life-cycle assessment, spatio-temporal variability, carbon footprint. 23 24 2 2 1 Introduction 25 Increasingly competing with conventional energy sources, Renewable Energy Systems (RES) offer a way out of fossil 26 fuels dependency and allow to reduce greenhouse gas emissions (GHG) associated with the generation of electricity [1]. 27The latter, together with heat production, still represents 42% of the world GHG emissions in 2015 per the International 28 Energy Agency. The importance of RES is visible as the installed capacity of these systems increased by 30% 29 worldwide in the last 40 years. However, their development must be intensified and combined with energy efficiency 30 measures to reduce the GHG emissions at a global level, since the electricity demand has more than doubled during that 31 same period [2]. 32In parallel to this development, numerous Life Cycle Assessment (LCA) studies analyzed the performance of RES and 33 their increasing role in regional and national electricity mixessee [3] in the context of Denmarkas well as at 34 worldwide levelsee [4]. LCA has proven to be a relevant tool to analyze the performance of different electricity 35 generation systems [5][6][7][8]. LCA includes all the environmentally-relevant phases of the value chain of electricity 36 production system: from the capture and conversion of primary energy, via the construction, maintenance and disposal 37 of the plant to transform it, down to i...

Renewable energy systems are essential in coming years to ensure an efficient energy supply while maintaining environmental protection. Despite having low environmental impacts during operation, other phases of the life cycle need to be accounted for. This study presents a geo-located life cycle assessment of an emerging technology, namely, floating offshore wind farms. It is developed and applied to a pilot project in the Mediterranean Sea. The materials inventory is based on real data from suppliers and coupled to a parameterized model which exploits a geographic information system wind database to estimate electricity production. This multi-criteria assessment identified the extraction and transformation of materials as the main contributor to environmental impacts such as climate change (70% of the total 22.3 g CO 2 eq/kWh), water use (73% of 6.7 L/kWh), and air quality (76% of 25.2 mg PM2.5/kWh), mainly because of the floater's manufacture.The results corroborate the low environmental impact of this emerging technology compared to other energy sources. The electricity production estimates, based on geo-located wind data, were found to be a critical component of the model that affects environmental performance. Sensitivity analyses highlighted the importance of the project's lifetime, which was the main parameter responsible for variations in the analyzed categories. Background uncertainties should be analyzed but may be reduced by focusing data collection on significant contributors. Geo-located modeling proved to be an effective technique to account for geographical variability of renewable energy technologies and contribute to decision-making processes leading to their development. K E Y W O R D Sfloating offshore wind farm, geo-located mode, industrial ecology, life cycle assessment, renewable energy, wind energy