Biofiltration Kinetics of a Gaseous Aldehyde Mixture Using a Synthetic Matrix
Bibliographic record
Abstract
Although aldehydes contribute to ozone and particulate matter formation, there has been little research on the biofiltration of these volatile organic compounds (VOCs), especially as mixtures. Biofiltration degradation kinetics of an aldehyde mixture containing hexanal, 2-methylbutanal (2-MB), and 3-methylbutanal (3-MB) was investigated using a bench-scale, synthetic, media-based biofilter. The adsorption capacity of the synthetic media for a model VOC, 3-methylbutanal, was 10 times that of compost. Periodic residence time distribution analysis (over the course of 1 yr) via a tracer study (84-99% recovery), indicated plug flow without channeling in the synthetic media and lack of compaction in the reactor. Simple first-order and zero-order kinetic models both equally fit the experimental data, yet analysis of the measured rate constants versus fractional conversion suggested an overall first-order model was more appropriate. Kinetic analysis indicated that hexanal had a significantly higher reaction rate (k = 0.09 +/- 0.005 1/sec; 23 +/- 1.3 ppmv) compared with the branched aldehydes (k = 0.04 +/- 0.0036 1/sec; 31 +/- 1.6 ppmv for 2-MB and 0.03 +/- 0.0051 1/sec; 22 +/- 1.3 ppmv for 3-MB). After 3 months of operation, all three compounds reached 100% removal (50 sec residence time, 18-46 ppmv inlet). Media samples withdrawn from the biofilter and observed under scanning electron microscopy analysis indicated microbial growth, suggesting removal of the aldehydes could be attributed to biodegradation.
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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) | 0.000 | 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 | 0.000 |
| 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".