Bisphenol A Contamination in Canadian Municipal and Industrial Wastewater and Sludge Samples
Why this work is in the frame
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Bibliographic record
Abstract
Abstract A large-scale study on bisphenol A (BPA) contamination in Canadian municipal and industrial wastewater and sludge has been completed. A total of about 200 samples were collected, including those from 31 sewage treatment plants and 15 pulp and paper mills across Canada, as well as 13 industrial facilities in the Toronto area. The samples were extracted by previously developed solid-phase and supercritical carbon dioxide extraction procedures and were analyzed by gas chromatography-mass spectrometry. BPA contamination was detected in all of the 72 sewage samples, with concentrations ranging from 0.080 to 4.98 µg/L (median 0.329 µg/L) for the influent, and from 0.010 to 1.08 µg/L (median 0.136 µg/L) for the effluent. Of the 36 influent/effluent sample pairs studied, BPA in the influent is removed by the sewage treatment process at a median reduction rate of 68%. Levels of BPA accumulation in sewage sludge, for the 50 samples tested, ranged from 0.033 to 36.7 µg/g, on a dry weight basis. A wide range of BPA concentrations, from 0.23 to 149.2 µg/L, were observed for the wastewater collected from selected industrial facilities in the Toronto area. The more contaminated samples came from the sectors of chemicals and chemical products, commercial dry cleaning, as well as packaging and paper products. Based on these data, on-site releases of BPA by industrial facilities seem to be much more widespread than the National Pollutant Release Inventory (NPRI) database has suggested. While relatively high levels of BPA were found in some of the primary treated effluent collected from the deinking mills, BPA concentrations in the secondary treated effluent of all pulp and paper mills were low, with a range from < 0.005 to 0.0406 µg/L. Except for the samples derived from a few deinking mills, BPA contaminication in pulp and paper mill sludge was either low or undetected.
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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 | 0.004 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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