Kinetics of simultaneous methane and toluene biofiltration in an inert packed bed
Bibliographic record
Abstract
Abstract BACKGROUND Biofiltration of methane is of particular interest to contribute to limiting the greenhouse gas effect of biogas emissions from landfills. The complexity of the biogas mixture from landfills has underlined the importance of the presence of non‐methane organic compounds. The aim of this study was to determine the effect of toluene on the microkinetic and macrokinetic parameters of methane biodegradation using an inorganic filter bed. RESULTS Two concentrations of toluene were tested, 0.7 and 3.4 gC m −3 , and compared with the case of methane biofiltration alone. The specific growth rates of methane decreased from 0.793 to 0.574 to 0.278 d −1 when the toluene concentration was increased from 0 to 0.7 to 3.4 gC m −3 , respectively. The maximum elimination capacity of methane decreased from 39.4 to 5.6 gC m −3 h −1 when toluene concentration was increased from 0 to 3.4 gC m −3 . The half‐saturation constants decreased from 4.6 to 1.6 gC m −3 and from 4.6 to 0.7 gC m −3 , respectively. CONCLUSIONS Results show that an inhibition occurred on methane biodegradation when toluene was introduced into the biofilter. © 2013 Society of Chemical Industry
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".