Hydraulic and chemical cleaning efficiency for the release of microplastics retained during coagulation/flocculation-ultrafiltration
Bibliographic record
Abstract
• Increasing coagulant dosage inhibits the release of MPs during hydraulic cleaning. • Dissolution of Al precipitate during chemical cleaning improves the release of MPs. • Cleaning efficiency is comparatively low for 1-5 µm MPs vs. those >5 µm in size. • Cleaning practices are ineffective for eliminating irreversible retention of MPs. • The irreversible retention of MPs could affect long-term membrane performance. Microplastics (MPs) are ubiquitous in global drinking water sources (lakes, rivers), with reported concentrations ranging from 0.5 to >7,500 particles/L. Ultrafiltration (UF), widely applied in drinking water treatment, is anticipated to represent an effective barrier to MPs due to its pore size (0.01-0.1 µm), which can retain MPs of potential health concern. To-date limited studies have reported that MPs may contribute to UF fouling, albeit when considering concentrations up to 10 orders of magnitude higher than those typically observed in source waters. The present study evaluated the retention of MPs by UF membranes when incorporating coagulation/flocculation pre-treatment, as well as their release during hydraulic and chemical cleaning. Polyethylene (PE) fragments, representing a range of environmentally relevant sizes (1-50 µm) and concentrations (907 ± 293 particles/L), were spiked into untreated lake waters prior to coagulation/flocculation-UF. Results suggest that in the absence of coagulant (alum) addition, only 50% of MPs retained during UF permeation were subsequently released during hydraulic cleaning. The release of MPs during hydraulic cleaning decreased (<20%) at medium and high (8 mg/L, 15 mg/L) alum dosages when compared to the absence of coagulant addition. Chemical cleaning with sodium hypochlorite (500 mg/L) was only capable of releasing 20% to 60% of retained MPs. Both hydraulic and chemical cleaning were less effective for the release of MPs when compared to reversible fouling resistance, organic matter, and aluminum. As such, future research is required to determine if the accumulation of MPs leads to increased UF fouling over extended operating periods, in addition cleaning practices which specifically target MPs should be further examined. Low and medium alum dosages (2 mg/L, 8 mg/L) were observed to increase the release of retained MPs during chemical cleaning, suggesting that incorporation of coagulation pre-treatment is useful to increase the release of MPs and minimize potential long-term accumulation on membranes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".