Comparative Performance of A<sup>2</sup>/O and a Novel Membrane‐Bioreactor‐Based Process for Biological Nitrogen and Phosphorus Removal
Bibliographic record
Abstract
The comparison between a novel membrane bioreactor (MBR) system and a conventional anaerobic-anoxic-aerobic (A2/O) system was conducted using synthetic wastewater (SWW) and municipal wastewater (MWW). Each system was operated at an overall hydraulic retention time of 8 hours and solids retention time of 10 days. The MBR exhibited better overall system performance than the A2/O system, in terms of phosphorus removal. Nitrogen removal efficiencies were close in the two systems at 73 to 74% in both runs, while phosphorus removal efficiencies were 96 and 74% (SWW run) and 80 and 75% (MWW run), for the MBR and A2/O, respectively. Effluent soluble chemical oxygen demand (COD) was less than 15 mg/L in the two systems during both runs. Phosphorus uptake by denitrifying phosphate-accumulating organisms accounted for 49% of the total uptake in the MBR compared with 33% in the A2/O during the SWW run. The dynamic test clearly showed that the MBR had better denitrification capacity than the A2/O system. The MWW run indicated that MBR ferments particulate COD better than A2/ O. The effect of the intermediate clarifier on MBR phosphorus removal was significant, with phosphorus uptake of 0.16 g/d in the SWW run and phosphorus release of 0.08 g/d in the MWW run, thus enhancing thetotal phosphorus removal in both cases.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".