Anaerobic Conversion of Chlorobenzene and Benzene to CH <sub>4</sub> and CO <sub>2</sub> in Bioaugmented Microcosms
Bibliographic record
Abstract
Chlorobenzene is a widespread groundwater contaminant found at many industrial sites. Reductive dechlorination of chlorobenzene requires input of electron donor and results in problematic accumulation of benzene, which is more toxic than chlorobenzene. We hypothesized that coupling a culture capable of reductive dechlorination of chlorobenzene to benzene with a second benzene-degrading methanogenic culture would completely detoxify chlorobenzene. To this end, active chlorobenzene-dechlorinating microcosms that were producing benzene were inoculated with a previously described enriched methanogenic benzene-degrading consortium. The combination resulted in the transformation of chlorobenzene via benzene to the nontoxic degradation products, CO2 and CH4. Sustainable degradation of chlorobenzene and benzene was observed in the microcosms and was further confirmed by shifts in the carbon isotopic ratios of chlorobenzene and benzene during degradation. Moreover, we could show that benzene derived electrons fueled chlorobenzene dechlorination removing the need to provide exogenous electron donor. The results have promising implications for sustainable bioremediation of sites contaminated with chlorinated benzenes and benzene.
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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 | 0.001 | 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".