Prolonged operation of a methane biofilter from acclimation to the failure stage
Bibliographic record
Abstract
Global warming needs immediate attention to reduce major greenhouse gas emissions such as methane (CH4). Bio-oxidation of dilute CH4 emissions in packed-bed bioreactors such as biofilters has been carried out over recent years at laboratory and large scales. However, a big challenge is to keep CH4 biofilters running for a long period. In this study, a packed-bed lab-scale bioreactor with a specialized inorganic-based filter bed was successfully operated over four years for CH4 elimination. The inoculation of the bioreactor was the active leachate of another CH4 biofilter which resulted in a fast acclimation and removal efficiency (RE) reached 80% after seven weeks of operation for CH4 inlet concentrations ranging from 700 to 800 ppmv and an empty bed residence time (EBRT) of 6 min. During four years of operation, the bioreactor often recorded REs higher than 65% for inlet concentrations in the range of 1900–2200 ppmv and an EBRT of 6 min. The rate and interval of the nutrient supply played an important role in maintaining the bioreactor’s high performance over the long operation. Forced shutdowns were unavoidable during the 4-year operation and the bioreactor fully tolerated them with a partial recovery within one week and a progressive recovery over time. In the end, the bioreactor’s filter bed started to deteriorate due to a long shutdown of twelve weeks and the extended operation of four years when the RE dropped to below 8% with no sign of returning to its earlier performance.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".