Nutrient removal in an electrically enhanced membrane bioreactor
Bibliographic record
Abstract
Integration of the membrane bioreactor (MBR) into wastewater treatment facilities has gained popularity in recent years due to increasingly stringent discharge permits. However, up to now no research has been conducted on the combination of nitrification, denitrification and electrochemical phosphorus removal into a MBR system. In this study a novel electrically enhanced MBR (EMBR) system was used. Without pH adjustment and external carbon source supplementation, using synthetic feed, ammonium-nitrogen was completely eliminated; COD, total nitrogen and ortho-phosphorus were removed by 94.3%, 77% and 86.6%, respectively. The power consumption was 0.22 kW/m(3) of the influent synthetic wastewater. With a control MBR run in parallel, the applied voltage gradient of 1.82 V/cm did not exhibit adverse influence on the microbial growth. This system has the potential to achieve phosphorus removal through alternating the direct current intensity.
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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) | 0.000 | 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 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".