Promoting the Biological Oxidation of Reduced Sulphur Compounds by pH Adjustment in a High Temperature Membrane Bioreactor Treating Kraft Pulp Mill Foul Condensate
Bibliographic record
Abstract
Abstract Over 99% of the reduced sulphur compounds (RSC) contained in a synthetic foul evaporator condensate were removed during treatment using a high temperature membrane bioreactor (MBR). At a neutral pH, the removal of the RSC was entirely due to stripping by the aeration system. It was possible to reduce the amount of RSC that was stripped to the atmosphere by promoting the biological oxidation of RSC through pH adjustment. A pH of less than approximately 4.5 was required to establish biological oxidation of RSC in the MBR. However, even at a pH of 3, which has been reported by others to be the optimal pH for the growth of thermophilic sulphur-oxidizing microorganisms, biological oxidation accounted for only approximately 50% of the RSC removed during treatment. The removal of the remaining 50% of the RSC removed during treatment was still due to stripping by the aeration system. The results further suggested that the long-term stability of a high temperature MBR operated at a low pH is questionable. In addition, the biological oxidation of methanol, which is considered to be the primary contaminant of concern contained in evaporator condensate, was significantly inhibited at a pH of less than approximately 4.5. Consequently, the simultaneous biological removal of methanol and RSC from foul evaporator condensate using a high temperature MBR was concluded to be impractical.
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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".