Abstract
Nowadays, wind energy is taking on primary role within renewable energies scenario. However, impact of wind energy industry on the environment still requires to be fully understood and better quantified. This study provides an updated review of Life Cycle Assessment (LCA) studies of electricity produced from onshore and offshore wind turbines (WTs). Special emphasis is put on results harmonization and simplified LCA models existing in the literature. The synthesis of the results is performed for wide range of WTs capacities, providing an exhaustive and general frame of the environmental impacts of WTs systems. Moreover, new simplified LCA models, which make use of a non-linear regression, were developed in this work for the following impact categories: Acidification Potential (AP), Eutrophication Potential (EP), Global Warming Potential (GWP) and Cumulative Energy Demand (CED) and for onshore (1–5000 kW) and offshore (500–8000 kW) WTs. Nonlinear data fitting models are provided with a sufficiently high correlation coefficient for total life cycle impacts. Moreover, the proposed simplified LCA models predict the final results with acceptable uncertainty. This indicates that the one-term power series describes the behavior of the impact indicators accurately, providing a useful correlation to estimate the life cycle environmental performance for a specific turbine model with a given nominal power. Furthermore, obtained simplified LCA models were generalized for different site-specific wind conditions, i.e. wind speeds and wind classes. By analyzing all the considered impact indicators for electricity generation, we notice that the highest values of life cycle impacts of electricity, for a particular WT correspond to the highest wind velocities. This is particularly valid for low nominal power turbines, which seem to be significantly affected by wind conditions. The trends exhibit an asymptotic behavior, indicating that, on the contrary, wind conditions are a minor contributor to the environmental impact of large-scale systems.