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 CO₂ 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.

中文翻译：

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根据供应商的数据和地理位置的风力数据，对海上浮动海上风电场进行现场特定生命周期评估

未来几年，可再生能源系统对于确保有效的能源供应并保持环境保护至关重要。尽管在操作过程中对环境的影响很小，但仍需要考虑生命周期的其他阶段。这项研究提出了一种新兴技术（即浮动海上风电场）的地理位置生命周期评估。它被开发并应用于地中海的试点项目。物料清单基于来自供应商的真实数据，并耦合至参数化模型，该模型利用地理信息系统风力数据库来估算电力生产。这项多标准评估确定材料的提取和转化是造成气候变化等环境影响的主要因素（占22.3 g CO ₂总量的70％eq / kWh），用水量（6.7 L / kWh的73％）和空气质量（25.2 mg PM2.5 / kWh的76％），主要是因为浮子的制造。结果证实了该新兴技术与其他能源相比对环境的影响小。根据地理位置风力数据得出的发电量估计值是影响环境绩效的模型的重要组成部分。敏感性分析强调了项目生命周期的重要性，这是导致所分析类别变化的主要参数。应该分析背景不确定性，但可以通过将数据收集集中在重要贡献者上来减少背景不确定性。