Microbial treatment of a styrene-contaminated air stream in a biofilter with high elimination capacities
Bibliographic record
Abstract
A styrene-utilizing mixed microbial culture was isolated and utilized in a biofilter for the biological treatment of a contaminated air stream. Biofilter media consisted of composted wood bark and yard waste. The biofilters were acclimated at 120 s residence time and further evaluated at 60 and 30 s gas residence times. The biofilters received organic loading rates of up to 350 g/m(3) h. The styrene volumetric removal rate was a function of the organic loading rate and increased with increasing loading rates. Average volumetric removal rates of 69-118 g/m(3) h observed in our studies were higher than reported values for styrene biofilters. Average styrene removal efficiencies ranged from 65% to 75% (maximum 100%). Axial analysis of styrene concentration along the column indicated that the bulk of the styrene removal occurred in the first section of the biofilter. Analyses of the media indicated that the moisture content of the first section (50-55% w/w) was significantly lower than in the second and third sections (65-70% w/w). The pressure drops across the biofilter were low due to the high concentration of large media particles. The total pressure drops were 1-3, 4-6, and 10-16 mm for the 120-, 60-, and 30-s residence time periods, respectively.
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".