Determination of two cyclosiloxanes in waste activated sludge and removal by advanced oxidation.
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. 30-60 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 accumulate in 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 using advanced oxidation techniques. A method was developed to effectively extract siloxanes from sludge and gas chromatography/mass spectrometry was used for quantification. Results for Loveland WWTP samples indicated that octamethylcyclotetrasiloxane (D4) and D5 are present up to 9ug/g dried-sludge. To study siloxane removal hydrogen peroxide (H 2 O 2 ), UV, ozone and their combinations will be used. Currently effectiveness of H 2 O 2 is being investigated. Sludge samples were spiked with D4 and D5 at 12 mg/g and treated with 3ml, 5ml, 7ml of 30% H 2 O 2 for 1hr, 2hr, and 3hr reaction time each. Results indicated a 72% reduction in D4 and D5 levels after 3 hrs. Other treatment methods will be investigated next. The results will shed a light whether these methods can be used to remove siloxanes from the wastewater effluents to protect the source waters.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".