Polybrominated diphenyl ethers in an advanced wastewater treatment plant. Part 1: Concentrations, patterns, and influence of treatment processes
Bibliographic record
Abstract
Concentrations and patterns of the mono- through deca-substituted polybrominated diphenyl ether (PBDE) flame retardants were determined in all major unit operations and processes within a tertiary-level wastewater treatment plant (WWTP) having post-filtration ultraviolet light disinfection. The results show that PBDEs do not appear to be degraded substantially or otherwise removed by wastewater treatment processes such as anaerobic, anoxic, and aerobic biological treatment, anaerobic digestion, dissolved air flotation, or sand–anthracite filtration. An overall removal efficiency of 93% was observed for PBDEs in the WWTP due to sorption onto wastewater sludges, well below that predicted by equilibrium partitioning models. High levels observed in the resulting WWTP biosolids (~2.4 mg·kg–1 dry weight) may contaminate a wider environment through their use as a soil amendment. Lower concentrations of PBDEs contained within high volumes of aqueous WWTP effluent (~26 ng·L–1) may result in a large PBDE flux into receiving waters, posing a potential threat to drinking water supplies and fisheries resources. Key words: polybrominated diphenyl ethers (PBDEs), flame retardants, municipal wastewater treatment, domestic sewage, mass balance, congener patterns.
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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) | 0.001 | 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".