Effects of bioporous carriers on the performance and microbial community structure in side-stream anaerobic membrane bioreactors
Bibliographic record
Abstract
The aim of this study was to investigate the effects of a volcanic rock porous carrier (VRPC) on sludge reduction, pollutant removal, and microbial community structure in an anaerobic side-stream reactor (ASSR). Three lab-scale membrane bioreactors (MBRs), including an anoxic–oxic MBR, which served as the control (C-MBR), an ASSR-coupled MBR (A-MBR), and an A-MBR filled with VRPC (FA-MBR) were stably and simultaneously operated for 120 days. The effect of the three reactors on the removal of chemical oxygen demand (COD) was almost negligible (all greater than 95%), but the average removal efficiency of ammonium nitrogen, total nitrogen, and total phosphorus was significantly improved by the insertion of an ASSR, especially when the ASSR was filled with VRPC. Finally, A-MBR and FA-MBR achieved 16.2% and 26.4% sludge reduction rates, with observed sludge yields of 0.124 and 0.109 g mixed liquid suspended solids/g COD, respectively. Illumina MiSeq sequencing revealed that microbial diversity and richness were highest in the VRPC, indicating that a large number of microorganisms formed on the carrier surface in the form of a biofilm. Abundant denitrifying bacteria (Azospira, Comamonadaceae_unclassified, and Flavobacterium) were immobilized on the carrier biofilm, which contributed to increased nitrogen removal. The addition of a VRPC to the ASSR successfully immobilized abundant hydrolytic, fermentative, and slow-growing microorganisms, which all contributed to reductions in sludge yield.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".