Fate of triclosan in tertiary wastewater treatment: chlorination
Bibliographic record
Abstract
Behavior of the antimicrobial triclosan (5-chloro-2-(2,4-dichlorophenoxy)phenol) was investigated under laboratory chlorination conditions and in a wastewater treatment plant discharging 380 million liters daily to the Delaware River, USA. Reactions of triclosan with chlorine were investigated using concentrations and exposure time typical of municipal wastewater treatment plants, i.e., 1 h contact time and average 1–2 mg/L residual chlorine. In reagent water, triclosan reacted quickly, transforming into mono- and dichlorinated species and further into dichlorophenol and trichlorophenol. However, triclosan remained stable for up to 2 h in wastewater samples chlorinated under these conditions. To confirm observed behavior under field conditions, a liquid chromatography tandem mass spectrometry-based analytical method capable of monitoring triclosan and its transformation products in wastewater was developed. Qualitative and quantitative wastewater characterization before and after chlorination are presented. Triclosan was present at the same concentration (P > 0.05) in pre-chlorination and post-chlorination aqueous wastewater samples (mean 368 ng/L). This finding is consistent with the non-detection of specific triclosan transformation products above sample reporting limits (30.0–100 ng/L), but contrasts markedly with detection of chlorination transformation products reported in reagent water. These data suggest the importance of influent matrix components in chlorination reactions of triclosan in contaminated wastewater under treatment plant conditions.
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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 | 0.001 | 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".