Formation of nanoparticles during accelerated UV degradation of fleece polyester textiles
Bibliographic record
Abstract
Micro- and nanoplastics have emerged as critical pollutants in various ecosystems, posing potential environmental and human health risks. Washing of polyester textiles has been identified as one of the sources of nanoplastics. However, other stages of the textile life cycle may also release nanoparticles. This study aimed to examine nanoparticle release during UV degradation of polyester textiles under controlled and real-world conditions. Fleece polyester textiles were weathered under simulated sunlight for up to two months, either in air or submerged in water. We conducted bi-weekly SEM image analyses and quantified released nanoparticles using nanoparticle tracking analysis (NTA). At week 0, the fiber surface appeared smooth after prewashing. In the air group, nanoparticles appeared on the fiber surface after UV-exposure. In the group of textiles submerged in water, the surfaces developed more pits over time. The cumulative nanoparticle emission from the weathered textiles ranged from 1.4 × 1011 to 4.0 × 1011 particles per gram of fabric in the air group and from 1.6 × 1011 to 4.4 × 1011 particles per gram of fabric in the water group over two months. The predominant particle size fell into the 100 to 200 nm range. The estimated mass of the released nanoparticles was 0.06–0.26 g per gram of fabric, which is lower than the amount released during the washing of new textiles. Additionally, Scanning Transmission X-ray Microscopy (STXM) images indicated that the weathered nanoparticles underwent oxidation. Overall, the research offers valuable insights into nanoparticle formation and release from polyester textiles during UV degradation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".