Assessing the eco-efficiency of offshore wind energy using a combined life cycle assessment and data envelopment analysis approach

This study develops an integrated Life Cycle Assessment (LCA)–Data Envelopment Analysis (DEA) framework to evaluate the material eco-efficiency of 20 operational offshore wind farms in the United Kingdom. The framework incorporates a contribution-analysis step to identify the most environmentally relevant inventory flows before efficiency assessment. Harmonised cradle-to-grave inventories were constructed from the MEAOW model and remapped to ecoinvent v3.12 background processes. Environmental impacts were quantified using ReCiPe 2016 Midpoint (H), covering 18 impact categories, in SimaPro. Contribution analysis identified five dominant physical material inputs: low-alloy steel (49.37%), copper (21.99%), chromium steel (2.98%), glass fibre (2.26%), and aluminium (2.05%). These materials were incorporated into an input-oriented Slack-Based Measure DEA model under variable returns to scale, using lifetime electricity generation as the output. Nine wind farms were classified as efficient, whereas the remaining eleven obtained efficiency scores between 0.584 and 0.795. Material-specific reduction targets were transferred to the corresponding life-cycle inventories while holding electricity generation and non-DEA inventory flows constant. A second LCA showed reductions across all 18 impact categories for every inefficient wind farm. Median improvements ranged from 8.85% for fossil resource scarcity to 30.32% for terrestrial and freshwater ecotoxicity, while maximum reductions reached 59.18%. Sensitivity analysis indicated high stability in efficiency classifications, rankings, and reduction targets. The proposed framework links environmental hotspot identification, efficiency benchmarking, and impact reassessment, providing material-focused improvement potentials for offshore wind planning and design. These targets should be interpreted as comparative benchmarks rather than directly implementable engineering prescriptions.