Influence of carbon source on nutrient removal performance and physical–chemical characteristics of aerobic granular sludge
Bibliographic record
Abstract
The impact of carbon source variation on the physical and chemical characteristics of aerobic granular sludge and its biological nutrient (nitrogen and phosphorus) removal performance was investigated. Two identical sequencing batch reactors, R1 and R2, were set up. Granular biomass was cultivated to maturity using acetate-based synthetic wastewater. After mature granules in both reactors with simultaneous chemical oxygen demand (COD), ammonium and phosphorus removal capability were achieved, the feed of R2 was changed to municipal wastewater and R1 was continued on synthetic feed as control. Biological phosphorus removal was completely inhibited in R2 due to lack of readily biodegradable COD; however, the biomass maintained high ammonium and COD removal efficiencies. The disintegration of the granules in R2 occurred during the first two weeks after the change of feed, but it did not have significant impacts on settling properties of the sludge. Re-granulation of the biomass in R2 was then observed within 30 d after granules' disintegration when the biomass acclimated to the new substrate. The granular biomass in R1 and R2 maintained a Sludge Volume Index close to 60 and 47 mL g(-1), respectively, during the experimental period. It was concluded that changing the carbon source from readily biodegradable acetate to the more complex ones present in municipal wastewater did not have significant impacts on aerobic granular sludge characteristics; it particularly did not affect its settling properties. However, sufficient readily biodegradable carbon would have to be provided to maintain simultaneous biological nitrate and phosphorus removal.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".