The influence of the gas flow rate during methane biofiltration on an inorganic packing material
Bibliographic record
Abstract
Abstract The influence of the gas flow rate (GFR), when varied between 1 and 5.5 L/min, on the conversion, the elimination capacity (EC) and the carbon dioxide production ${\rm (}P_{{\rm CO}_2 } )$ , during the biofiltration of methane using a biofilter charged with an inorganic packing material, has been investigated. The methane concentrations considered for this purpose were selected from the operating range of 1300–12 000 ppmv. The experiments involved were conducted, using a nitrogen minimal salt nutrient solution, for the biofilter periodic irrigation, in which the nitrogen concentration was maintained at 0.75 g/L, and the phosphorus concentration was of 0.3 or 1.5 g/L. The results obtained from this study have confirmed the view that the GFR is a important parameter, the optimum values found, leading to methane conversions of ≥90%, being ≤2 L/min for inlet loads ≤55 g/m3/h. Based on this result, it was then established that the maximum volumetric load (VL) of methane in the biofilter must be estimated at around 0.075 m3 (methane)/m3 (biofilter)/h, that is, 6.8 m3 (polluted gas)/m3 (biofilter)/h. In addition, when the GFR is selected between 1 and 4.2 L/min, it has an influence on the EC. However, the GFR does not affect the $P_{{\rm CO}_2 }$ within the biofilter. It has also been established that the high phosphorus level (i.e., 1.5 g/L), present in the nutrient solution, is to be preferred in the biofilter.
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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".