Ammonium removal from coking wastewater in a pilot‐scale two‐stage aerobic biofilm system: Biokinetic analysis
Bibliographic record
Abstract
Abstract A novel four‐stage pilot‐scale anaerobic/anoxic/oxic/oxic (A2/O2) biofilm process was successfully developed to treat coking wastewater with high ammonium loading. In this study, three different dynamical models including the first‐order substrate removal model, the Monod‐biological contact oxidation (Monod‐BCO) model, and the modified Stover‐Kincannon model were particularly applied to analyze kinetics of ammonium removal in a two‐step aerobic stage. For the O1 reactor, all models were appropriate for describing ammonium removal and the correlation coefficients of first‐order substrate removal model, BCO model, and modified Stover‐Kincannon model were 0.8974, 0.9210, and 0.9726, respectively. The model verification indicated that the modified Stover‐Kincannon model was slightly more applicable to predict ammonium removal in the O1 reactor. It was demonstrated that the maximum removal rate of ammonium was 0.208 kg/(m3 · d) by the Stover‐Kincannon model. For the O2 reactor, the modified Stover‐Kincannon model turned out to be the best fitting kinetic model for ammonium removal compared to the first‐order substrate removal model (R2 = 0.1556) and Monod‐BCO model (R2 = 0.5022). The maximum ammonium conversion rate (Um2‐O2) by the modified Stover‐Kincannon model was 1.180 kg/(m3 · d), while saturation rate constant k3‐O2 was 1.221 kg/(m3 · d). Furthermore, the determination coefficient between measured and predicted values obtained by the modified Stover‐Kincannon model was quite high (R2 = 0.9788) in the O2 process and a lower average residual square (6.60 × 10−6) was also obtained. The results of kinetic studies by the Stover‐Kincannon model can predict ammonia removal efficiency well in two‐step aerobic biofilm reactors of a coking wastewater treatment combined system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
| 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".