Reducing microplastic fiber shedding from hand-washed polyester
Bibliographic record
Abstract
The presence of microplastic fibers (MPFs) in oceans, soil and humans is a major ecological and health concern. A significant amount of MPFs are generated through the washing of textiles. Two-thirds of the world does not have access to laundry machines; the majority of garment washing is done by hand. However, most MPF research has focused on machine-laundered fabric. Moreover, while mitigation strategies such as coatings have been introduced to prevent MPF release, every prior study on MPF-reducing coatings utilized machine laundering. The aim of this work was to understand if such coatings are also effective at reducing MPF release when fabrics are washed by hand. This investigation focused on MPF release during hand washing, utilizing two different constructions (dyed black and green) of 100% polyester fabrics (coated and uncoated) hand-washed in deionized (DI) water, tap water, and water sourced from Lake Ontario. Our data indicates that water containing more total dissolved solids (TDS) results in a greater number of MPFs released per wash regardless of the fabric coating. Uncoated fabrics hand washed in water sourced from Lake Ontario released ~ 200% and 240% more MPFs/g compared to samples washed in DI water, for the green and black polyester, respectively. Additionally, the increase observed in the number MPFs released for the coated samples were ~ 540% and 210%, respectively. However, hand-washing in higher-TDS water significantly decreased the length distribution of released MPFs. The mean length of MPFs released from the uncoated black polyester hand-washed in DI water was ~ 1.2 mm, whereas it was only ~ 0.5 mm for polyester hand-washed in water sourced from Lake Ontario, with zero MPFs longer than 2 mm observed. This indicates that hand washing in higher-TDS water can further fracture MPFs even after their initial release. A coating shown to lower MPF release during machine laundering was also explored, to understand its efficacy at reducing MPF release during hand washing. The efficacy of the coating varied substantially between fabric constructions. MPF release was reduced 92%, 88%, and 77% when the green polyester was hand washed in DI, tap, and lake water, respectively, whereas these reductions were only 30%, 26%, and 37%, respectively, for the black polyester. This work confirms the efficacy of anti-MPF coatings when the fabric is subjected to hand-washing, and highlights the critical role of water TDS on the amount of MPFs ultimately released into the wash water.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 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".