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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".