Occurrence and removal of pharmaceutically active compounds in sewage treatment plants with different technologies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Occurrence of eight selected pharmaceutically active compounds (PhACs; caffeine, carbamazepine, triclosan, gemfibrozil, diclofenac, ibuprofen, ketoprofen and naproxen) were investigated in effluents from fifteen sewage treatment plants (STPs) across South Australia. In addition, a detailed investigation into the removal of these compounds was also carried out in four STPs with different technologies (Plant A: conventional activated sludge; plant B: two oxidation ditches; plant C: three bioreactors; and plant D: ten lagoons in series). The concentrations of these compounds in the effluents from the fifteen STPs showed substantial variations among the STPs, with their median concentrations ranging from 26 ng/L for caffeine to 710 ng/L for carbamazepine. Risk assessment based on the "worst case scenario" of the monitoring data from the present study suggested potential toxic risks to aquatic organisms posed by carbamazepine, triclosan and diclofenac associated with such effluent discharge. With the exception of carbamazepine and gemfibrozil, significant concentration decreases between influent and effluent were observed in the four STPs studied in more detail. Biodegradation was found to be the main mechanism for removing concentrations from the liquid waste stream for the PhACs within the four STPs, while adsorption onto sludge appeared to be a minor process for all target PhACs except for triclosan. Some compounds (e.g. gemfibrozil) exhibited variable removal efficiencies within the four STPs. Plant D (10 lagoons in series) was least efficient in the removal of the target PhACs; significant biodegradation of these compounds only occurred from the sixth or seventh lagoon.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it