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 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 | 0.001 | 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 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".