Improving the performance of membrane bioreactors by powdered activated carbon dosing with cost considerations
Bibliographic record
Abstract
Effects of powdered activated carbon (PAC) dosing on the overall performance of membrane bioreactors (MBR) were investigated in two bench-scale submerged MBRs. Positive impacts of PAC dosing on membrane fouling and the removal of 17beta-estradiol (E2) and 17alpha-ethyinylestradiol (EE2) were demonstrated over a six-month stable operational period. PAC dosing in the MBR increased the removal rates of E2 and EE2 by 3.4% and 15.8%, respectively. The average soluble extracellular polymeric substances (EPS) and colloidal total organic carbon (TOC) concentrations in the PAC-MBR sludge was 60.1% and 61.8% lower than the control MBR sludge, respectively. Lower soluble EPS and colloidal TOC concentrations in the PAC-MBR sludge resulted in a slower rate of trans-membrane pressure (TMP) increase during MBRs operation, which could prolong the lifespan of membranes. Cost assessment showed that PAC dosing could reduce the operating cost for membrane cleaning and/or membrane replacement by about 25%. The operating cost for PAC dosing could be offset by the benefit from its reducing the cost for membrane maintenance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".