Bibliographic record
Abstract
• First integration of mainstream anammox into an inverse fluidized bed bioreactor. • Developed a 3-hour biofilm attachment protocol enabling rapid and reproducible startup. • System achieved spontaneous axial biofilm uniformity and self-repair capability. • Maintained a nitrogen removal rate of 1.5 kg TN/m³·d under mainstream conditions. • Reduced reactor volume by 62 % while sustaining operating costs comparable to the MLE process. This study reports the first integration of mainstream anammox into inverse fluidized bed bioreactors, herein termed Invammox , synergizing respective strengths to overcome longstanding limitations of each process. A rapid (<3 h) biofilm attachment protocol was developed to effectively define optimal combination of initial particle loading as 30 % of the reactor by volume and initial seed biomass as 1 g VSS/L for startup. Upon seeding slow-growing anammox bacteria, Invammox spontaneously exhibited hydrodynamic uniformity, avoided biofilm overgrowth, and sustained resilient stability over 6,000 hours. The system demonstrated exceptional resilience and biomass retention under deliberately induced disturbances. Concurrently, internal liquid recirculation promoted thinner biofilms, sustained specific anammox activity up to 0.61 kg NH 4 + -N/kg VSS·d, threefold higher than the inoculated sidestream granular anammox biomass. A full-scale system treating 1.5 MGD municipal wastewater, designed based on the process kinetics, achieved a 62 % reduction in reactor volume (from 4,194 to 1,594 m³) with comparable operating costs. This work positions Invammox as a state-of-the-art platform for mainstream anammox, and partial nitrification/anammox, as well as establishes a complementary paradigm for scalable, energy-efficient nitrogen removal in biological wastewater treatment.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".