Wind turbine blade circularity: an overview of composite recycling methods, global markets and policies, and opportunities for Canadian development
Bibliographic record
Abstract
Wind turbine blades are typically comprised of glass or carbon fibre bonded with resin. This material is technically recyclable, but due to the complexity of these recycling processes, has been almost exclusively landfilled worldwide up until now. However, with the rise in national composite landfill bans, and the anticipated surge in wind turbine blade waste in the next few decades due to a global exponential increase in the adoption of the technology, landfilling is rapidly becoming an unfavourable end-of-life option. This paper reviews the existing recycling options for decommissioned wind turbine blades (grinding, cement kiln co-processing, pyrolysis, solvolysis, high voltage fragmentation, and refurbishment), as well as the utility of recycled composite fibres in industry, including the emissions profile deriving from the recycling methods themselves. The Canadian wind energy market is discussed, highlighting the lack of recycling facilities or infrastructure, despite the recent increase in wind farm installations countrywide. Decommissioning requirements for new Canadian wind farms lack detail on blade disposal plans. Several pathways are identified to improve circularity and environmental outcomes: designating robust decommissioning requirements for new wind farms, the establishing national and international knowledge hubs on wind turbine blade waste generation, movement, and storage; conducting a comprehensive analysis on the emissions profile of wind turbine blade recycling processes, the development of a universal wind turbine blade recyclability class system, as well as a recycled wind turbine blade fibre grading system; and the inclusion of cold-weather turbine blades in recycling testing to gauge the impact of de-icing measures on the recycling process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".