ArticleiScience2022
Regional representation of wind stakeholders' end-of-life behaviors and their impact on wind blade circularity.
Article in iScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Conceptualising systems thinking and complexity modelling for circular economy quantification: A systematic review and critical analysis.Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA · 2026Pooled it
- Hail as a damage vector for renewable energy.iScience · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The growing number of end-of-life (EOL) wind blades could further strain US landfills or be a valuable composite materials source, depending on stakeholders' behaviors. Technical solutions based on circular economy (CE) principles have been proposed but are not guaranteed to solve the issue of EOL management. Transitioning to CE implies changing how business models, supply chains, and behaviors deal with products and waste. A spatially resolved agent-based modeling combined with a machine-learning metamodel shows that including behavioral factors is crucial to designing effective policies. Logistical barriers and transportation costs significantly affect the results: lowering blade shredding costs by a third before transportation makes EOL blades a source of valuable materials, decreasing the 2050 cumulative landfill rate below 50%. In another scenario, parameter settings simulating policy interventions aiming at boosting early adoption incites new social norms favorable to recycling, lowering the cumulative landfill rate below 10%.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.