Divergences of granules and flocs microbial communities and contributions to nitrogen removal under varied carbon to nitrogen ratios
Bibliographic record
Abstract
Aerobic granular sludge (AGS) reactors are promising for treating high ammonia wastewaters, yet the roles of granules and flocs in nitrogen removal under varying carbon to nitrogen (COD/N) ratios remain unclear. This study investigated microbial communities and their contributions to N removal as the COD/N ratio shifted from 6 to 4, and to 2. Results showed granules contributed 53-64 % nitrification capacity at higher COD/N ratios (6 and 4), but flocs contributed more (50-63 %) at a ratio of 2. Granules consistently exhibited higher denitrification capacity (>50 %). Heterotrophic bacteria dominated in both granules and flocs across all ratios. As the COD/N ratio reduced, the relative abundance of anaerobic ammonia oxidation microorganisms (Candidatus Anammoximicrobium) and filamentous bacteria increased in granules, while ammonia oxidizing bacteria (Nitrosomonas) and complex organic degraders increased in flocs. These findings highlight the importance of selectively retaining granules or flocs under varying COD/N ratios to optimize nitrogen removal efficiency.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 teacher head, 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".