Influence of temperature and pH on the kinetics of the Sharon nitritation process
Bibliographic record
Abstract
Abstract The SHARON (Single reactor High activity Ammonia Removal Over Nitrite) process is an innovative process that improves the sustainability of wastewater treatment, especially when combined with an Anammox process. It aims at ammonium oxidation to nitrite only, while preventing further nitrate formation. In order to optimize this process by means of modelling and simulation, parameters of the biological processes have to be assessed. Batch tests with SHARON sludge clearly showed that ammonia rather than ammonium is the actual substrate and nitrous acid rather than nitrite is the actual inhibitor of the ammonium oxidation in the SHARON process. From these batch tests the ammonia affinity constant, the nitrous acid inhibition constant and the oxygen affinity constant were determined to be 0.75 mgNH3‐N L−1, 2.04 mgHNO2‐N L−1 and 0.94 mgO2 L−1. The influence of pH and temperature on the oxygen uptake rate of SHARON biomass was determined, indicating the existence of a pH interval between 6.5 and 8 and a temperature interval from 35 to 45 °C where the biomass activity is maximal. The kinetic parameters of the SHARON process were determined based on batch experiments. These parameters can now be implemented in a simulation model for further optimization of the SHARON process. Copyright © 2007 Society of Chemical Industry
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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 | 0.001 |
| 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) | 0.001 | 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".