Effects of powdered activated carbon dosing on sludge characteristics and estrogen removal in membrane bioreactors
Bibliographic record
Abstract
Sludge characteristics associated with filterability as well as the removal of a natural estrogen 17beta-estradiol (E2) and a synthetic estrogen 17alpha-ethyinylestradiol (EE2) were investigated in submerged membrane bioreactors (MBR) with and without the addition of powdered activated carbon (PAC) under the same experimental conditions. Positive impacts of PAC dosing on membrane fouling and the removal of E2 and EE2 were demonstrated over a six months stable operational period. Experimental results showed that PAC dosing resulted in lower concentrations of soluble extracellular polymeric substances (EPS) and colloidal total organic carbon (TOC) in the PAC-MBR sludge. The average soluble EPS and colloidal TOC concentrations in the PAC-MBR sludge was 60.1% and 61.8% lower than the control MBR sludge, respectively. Regardless of PAC dosing, concentrations of colloidal TOC were strongly related to concentrations of soluble EPS and soluble carbohydrates in the sludge. In addition, the mean flocs size of the sludge with PAC dosing was shifted from 49.4 microm to 60.3 microm. PAC dosing in the MBR increased the removal rates of E2 and EE2 by 3.4% and 15.8%, respectively.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".