Occurrence of cyclo-siloxanes in wastewater treatment plants - quantification and monitoring
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
Siloxanes are persistent, bio-accumulative and toxic emerging contaminants introduced to wastewater from common healthcare and biomedical products, and various industrial processes. They remain unchanged through wastewater treatment and a considerable portion ends up in surface waters through effluent discharge. 30 to 60 ng/L Decamethylcyclopentasiloxane (D5) was detected in two UK Rivers, while ~400 ng/L of D5 may be found in wastewater effluents. Hence, siloxanes are under consideration by Canadian Environmental Assessment Agency and UK Environment Agency for drinking water regulations. Siloxanes are hydrophobic and also accumulate in activated sludge and biogas, causing mechanical problems due to scaling. This research aims: to quantify the siloxanes in sludge samples obtained from Loveland, CO wastewater treatment plant (WWTP); and to study their removal. A method was developed to effectively extract siloxanes from activated sludge samples using liquid extraction followed by quantification with gas chromatography/mass spectrometry. Results for Loveland Wastewater Treatment Plant samples indicated that Octamethylcyclotetrasiloxane (D4) and Decamethylcyclopentasiloxane D5 are present up to 17.11 µg/g dried-sludge. The effectiveness of H2O2 in siloxane removal was investigated. Sludge samples were spiked with D4 and D5 at 12 mg/g and were treated with 1ml, 3ml, and 5ml of 30% H2O2 for 1hr, 2hr, and 3hr reaction time each. Results indicated a 72% reduction in D4 and D5 levels after 3 hrs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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