A study of aerobic digester performance with the use of methanol for biological nutrient removal in a full-scale sequencing batch reactor
Bibliographic record
Abstract
The primary goal of this research was to determine whether the use of methanol in a full-scale sequencing batch reactor (SBR) affected the subsequent aerobic sludge digester performance. The methanol injection into an experimental SBR resulted in a significant increase in the solids level in the SBR, increased wasting into the digesters, and a lower sludge age. When the methanol dosage in the SBR was 81 L/d, the dissolved oxygen level in the subsequent aerobic digesters became inadequate for proper digestion. The net result was a drop in solids reduction efficiency. However, the methanol injection appeared to have no effect on the dewaterability of the digested sludge, as samples from the experimental and control units had very similar capillary suction time (CST) results. It was found that the dewaterability was affected not only by the total suspended solids concentration of the digested sludge, but even more by the temperature of the digested sludge, through a change in filtrate viscosity. Key words: aerobic digestion, biological nutrient removal, denitrification, methanol, sludge dewaterability.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".