The contribution of pharmaceutically active compounds from healthcare facilities to a receiving sewage treatment plant in Canada
Bibliographic record
Abstract
Concentrations and percent loadings of pharmaceutically active compounds (PhACs) and other emerging contaminants released from healthcare facilities (2 hospitals and a long-term care facility) to a sewage treatment plant (STP) in a large urban sewershed were evaluated. An additional hospital outside the sewershed was also monitored. Fourteen of the 24 steroids/hormones and 88 of the 117 PhACs and emerging contaminants were detected at least once. Commonly used substances, including cotinine, caffeine and its metabolite 1,7-dimethylxanthine, ibuprofen and naproxen (analgesics), venlafaxine (antidepressant), and N,N-diethyl-meta-toluamide (insect repellant), were detected in all samples at all sites. Concentrations detected in the large specialty hospital outside the sewershed were similar to those within the sewershed. Cytotoxic drugs (tamoxifen and cyclophosphamide) and x-ray contrast media (iopamidol and diatrizoic acid) were infrequently detected in hospital effluents. Analysis for antibiotics indicated that azithromycin, clarithromycin, ciprofloxacin, erythromycin, ofloxacin, and sulfamethoxazole were consistently detected in hospital wastewaters, as was triclosan (antibacterial agent). Fifteen compounds individually contributed greater than 1% to the total PhAC and emerging contaminant load to the STP from the 2 hospitals in the sewershed, and 9 compounds in the STP effluent exceeded ecotoxicological criteria. The present survey demonstrates that point source discharges from healthcare facilities in this sewershed make a small contribution to the overall PhAC and emerging contaminant loading compared with the total concentrations entering the receiving STP.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".