The Effects of Microplastics on Floc Formation, Nutrient Removal and Settleability in Wastewater Treatment
Bibliographic record
Abstract
Microplastics (MPs) are ubiquitous anthropogenic pollutants and contaminants of concern that are being manufactured as plastic materials are relied upon in daily life, including packaging, cosmetics and other production sectors. One of the ways that MPs enter the environment is via wastewater treatment plants (WWTPs). This study attempts to shed light on the potential interactions of these pollutants with microorganisms and some of the processes they facilitate in WWTPs by finding the effects of polyethylene (PE) MPs on the growth of wastewater (WW) microorganisms, nutrient removal (with a focus on nitrogen compounds), settleability of total suspended solids (TSS), and on the immediate and short-term floc formation. The two highest concentrations of PE MPs enhanced growth over an approximately 3-day period. Then, the absorbance values decreased, possible due to the formation of biofilms causing a decrease in planktonic cells. The high concentrations of PE MPs are seen to slow growth compared to the lower concentrations of MPs. PE MPs had a positive effect on nitrite oxidation but little to no effect on nitrification as a whole. Over the short term (1 to 7 days), MPs had little to no effect on floc size. Beyond 7 days, PE MPs had a positive effect on floc size. TSS was higher in reactors amended with MPs (528.9 mg/L) in comparison to the TSS values in the control reactors (212.2 mg/L) without MPs. The results indicate that MPs serve as nuclei for floc formation.
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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) | 0.000 | 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) | 0.000 | 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".