Review on MBR Technologies for Emerging Pollutant Removal from Wastewater and Their Associated Antifouling Strategies
Bibliographic record
Abstract
It was necessary to reclaim water from wastewater to tackle water scarcity issues. However, it was difficult to treat waste-water for resue purpose through conventinal treatment technologies due to the wastewater contains various emerging contaminants. Membrane bioreactors (MBRs) were promising techniques to reclaim wastewater, which hybrid activity sludge and membrane technol- ogies. Although it was a challenge to eliminate the emerging contaminants efficiently through conventional MBRs due to specific chem- ical structures of these chemicals, more and more novel hybrid MBRs were applied to the removal of emerging contaminants. The evo- lution of MBR systems for treating emerging pollutants was summarized in this review. In addition, the process of biofouling on mem- branes and the development of relevant antifouling technologies were investigated. Besides, the perspectives of MBR systems on the ap- plication of emerging pollutant treatment were provided, which would help support the research and development of technologies in the field of water reclaiming in the future.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".