Kinetics of anaerobic methane oxidation coupled to denitrification in the membrane biofilm reactor
Bibliographic record
Abstract
Abstract Anaerobic oxidation of methane coupled to denitrification (AOM‐D) in a membrane biofilm reactor (MBfR), a platform used for efficiently coupling gas delivery and biofilm development, has attracted attention in recent years due to the low cost and high availability of methane. However, experimental studies have shown that the nitrate‐removal flux in the CH4‐based MBfR (<1.0 g N/m2‐day) is about one order of magnitude smaller than that in the H2‐based MBfR (1.1–6.7 g N/m2‐day). A one‐dimensional multispecies biofilm model predicts that the nitrate‐removal flux in the CH4‐based MBfR is limited to <1.7 g N/m2‐day, consistent with the experimental studies reported in the literature. The model also determines the two major limiting factors for the nitrate‐removal flux: The methane half‐maximum‐rate concentration (K2) and the specific maximum methane utilization rate of the AOM‐D syntrophic consortium (kmax2), with kmax2 being more important. Model simulations show that increasing kmax2 to >3 g chemical oxygen demand (COD)/g cell‐day (from its current 1.8 g COD/g cell‐day) and developing a new membrane with doubled methane‐delivery capacity (Dm) could bring the nitrate‐removal flux to ≥4.0 g N/m2‐day, which is close to the nitrate‐removal flux for the H2‐based MBfR. Further increase of the maximum nitrate‐removal flux can be achieved when Dm and kmax2 increase together.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".