Influence of carbon source on nutrient removal performance and physical–chemical characteristics of aerobic granular sludge
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.000 |
| 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 it