Impact of mixing intensity on dissolved oxygen half-velocity constants in a sidestream deammonification environment
Bibliographic record
Abstract
Abstract A partial nitritation/anammox (PN/A) process was operated at two different mixing intensities to quantify the extent to which diffusional limitations impact process rates. At a steady-state operation, the total inorganic nitrogen removal efficiency in the bench-scale sequencing batch reactors was found to increase as mixing intensity decreased (62 and 84% for average velocity gradient (G) values of 15 and 5.3 s−1, respectively). The half-velocity constants with respect to bulk-phase dissolved oxygen (DO) concentration for ammonia-oxidizing bacteria (AOB) and anaerobic ammonium-oxidizing (anammox) organisms were estimated on the basis of nitrogen removal rates that were observed in activity tests. The activity tests were conducted over a range of bulk-phase DO concentrations. The best-fit values were estimated to be 0.68 ± 0.34 and 0.54 ± 0.56 mg O2/L for G values of 15 and 5.3 s−1, respectively. The AOB values were not statistically different (p = 0.19) between mixing conditions which were consistent with AOB dominating the surface of granules. The best-fit values were estimated to be 0.13 ± 0.09 and 0.55 ± 0.40 mg O2/L for G values of 15 and 5.3 s−1, respectively, and were statistically different . The results demonstrated that mixing conditions should be considered when designing PN/A processes and provide quantitative results that can be employed to improve models of these processes. This article has been made Open Access thanks to the kind support of CAWQ/ACQE (https://www.cawq.ca).
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 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".