Biological treatment of municipal wastewater using fixed rope media technology: Impact of aeration scheme
Bibliographic record
Abstract
This paper characterized a new fixed rope media system to upgrade decentralized and small-scale wastewater treatment plants. A primary effluent of municipal wastewater was treated using two pilot-scale reactors equipped with full-scale sized fixed rope media technology, one of the reactors was aerated using a coarse bubble tube and the other using a custom fine bubble aeration system. The study examined the impact of the aeration scheme and intensities and the COD/NH3-N ratio on ammonia and COD removal rates, excessive biofilm growth, slough-off, and microbial communities’ composition. The average biofilm ammonia and COD removal rates ranged from 0.23 ± 0.15 to 0.38 ± 0.26 gNH 3-N/m2.d and 1.35 ± 0.95 to 3.05 ± 1.21 gCOD/m2.d, respectively. The fine and coarse bubble reactors showed comparable carbon oxidation rates; however, the fine bubble reactor showed a higher nitrification rate than the coarse bubble reactor at lower aeration intensities despite the similar dissolved oxygen concentration. Correspondingly, an increase in COD/NH3-N and excessive biofilm growth decreased the NH3-N removal performance but did not affect the COD removal efficiency. Further analysis of the microbial communities composition revealed that the reactors supported a relatively substantial amount of AOB (55 and 63%) and denitrifying bacteria (36 and 21%) with a relatively lower NOB (7 and 8%) and anammox (1 and 8%) species in the fine and coarse bubble aeration reactors, respectively. Overall this study demonstrated the feasibility of one stage fixed rope media to treat COD and ammonia and meet treatment objectives, thus providing an alternative solution to decentralized and smaller plant upgrades.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".