Effect of substrate variability on activated sludge kinetics during the treatment of bleached kraft mill effluent
Bibliographic record
Abstract
Solids retention time (SRT) is the primary control parameter for activated sludge units. However, treatment performance in full-scale systems at pulp mills does not appear to be a direct function of SRT. To determine the extent to which substrate variability masks the effects of SRT, the effect of SRT on activated sludge treatment kinetics and stoichiometry during bleached kraft mill effluent (BKME) treatment were investigated during a three year laboratory study. The treatment performance was monitored by biochemical oxygen demand (BOD), chemical oxygen demand (COD), and respirometric assays using BKME, methanol, formate, and acetate as substrates to monitor the activity of different populations of biomass. BOD removal was unaffected by SRT, however COD removal increased with increasing SRT and increasing influent BOD concentration. The BKME respirometric kinetics were constant with respect to SRT. The methanol and acetate degradation rates were variable, but were not a function of SRT. The maximum formate degradation rate increased with SRT, as did the yield on formate. Changing wastewater characteristics produced larger changes in treatment kinetics than those produced by changing the SRT (over a range from 6 to 30 days) or by the addition of an aerobic selector. The proportion of the formate metabolic rate relative to the methanol metabolic rate varied over the course of the project with the wastewater composition. The time required to adapt to different BKME batches varied from 5 to 30 days, and did not seem to depend on any of the measured variables (BOD, COD, or SRT).Key words: activated sludge, respirometry, kinetics, BKME, SRT, selector.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".