Coupling ultraviolet photolysis and biofiltration for enhanced degradation of aromatic air pollutants
Bibliographic record
Abstract
Abstract Coupling UV photolysis and biofiltration was evaluated as an effective treatment strategy for the enhanced degradation of hardly biodegradable aromatic volatile organic compounds (VOCs). o‐Xylene, a recalcitrant and poorly water‐soluble VOC, was used as a model compound and treated in two parallel treatment systems with and without UV pretreatment. Contaminated streams with flow rates of 0.186–0.384 m3 h−1 and inlet o‐xylene concentrations of up to 0.22 g m−3 were passed through the treatment system. About 20% (between 10 and 35%) of o‐xylene was converted into water‐soluble intermediates during the UV photolysis stage, which partially oxidized o‐xylene to more water‐soluble and biodegradable byproducts. The untreated contaminant along with the byproducts of UV photolysis was then removed effectively in the biofiltration stage, with improvements of up to 100% compared with the control biofiltration process. The results suggested that combined UV photolysis–biofiltration is promising as an effective technique to eliminate hydrophobic and recalcitrant organic compounds from contaminated air steams. Copyright © 2005 Society of Chemical Industry
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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 | 0.000 |
| 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) | 0.001 | 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".