Degradation of Toluene, Xylene, and Trimethylbenzene Vapors by Biofiltration: A Comparison
Bibliographic record
Abstract
This paper presents a comparative study of the biodegradation of three aromatic volatile compounds in a compost-based biofilter: toluene, xylene, and 1,2,4-trimethylbenzene, used in the course of this work for the first time in the field of biofiltration. Hence, three identical biofiltration units have been operated at the laboratory scale. During the experiments, nitrogen (as urea) was supplied at various concentrations to each reactor, via irrigated nutrient solutions. A comparative analysis of the results showed that the biodegradability scale followed the degree of substitution around the aromatic ring: toluene > xylene > trimethylbenzene, with 95, 80, and 70% maximum conversions, respectively. In addition, and despite the different removal levels achieved in the three bioreactors, it was established that from a reaction viewpoint, the degradation of the three compounds seemed to follow similar metabolic pathways involving methylcatechol isomers. Finally, by varying the nitrogen input concentrations in the three reactors, three degradation regimes have been highlighted: an N-limitation regime and an N-optimum regime, common to the three solvents, and an N-excess regime, favorable to the colonization of the filter beds by nitrifying species, which particularly affected the xylene and trimethylbenzene 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".