Nutrient Removal with Methanol as a Carbon Source Full-Scale Continuous Inflow SBR Application
Bibliographic record
Abstract
Methanol was applied to a full-scale continuous inflow SBR, as a carbon source for denitrification and possible phosphorus removal. This research was conducted at the District of Kent Wastewater Treatment Plant in Agassiz, British Columbia, Canada. This plant employs two SBR's working in parallel; one unit was used as a control, without the addition of methanol. There was no difference in the overall total nitrogen removal efficiency through methanol addition, however,the additional carbon source significantly shortened the denitrification reaction time in the existing reactor. The high nitrogen removal efficiency, with or without methanol addition, was primarily due to the advantages provided by continuous-flow SBR carbon loading. The phosphorus removal efficiency in the experimental SBR was also consistently higher than in the control SBR. The solids production from methanol addition wa s estimated to vary between 0.18 and 0.29gVSS/gCH3OH. Methanol addition also had an influence on the settling qualities of the sludge.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".