Identification of Degradation Pathways of Chlorohydrocarbons in Saturated Low-Permeability Sediments Using Compound-Specific Isotope Analysis
Bibliographic record
Abstract
This study aims to investigate whether compound-specific carbon isotope analysis (CSIA) can be used to differentiate the degradation pathways of chlorohydrocarbons in saturated low-permeability sediments. For that purpose, a site was selected, where a complex mixture of chlorohydrocarbons contaminated an aquifer-aquitard system. Almost 50 years after contaminant releases, high-resolution concentration, CSIA, and microbial profiles were determined. The CSIA profiles showed that in the aquitard cis-dichloroethene (cDCE), first considered as a degradation product of trichloroethene (TCE), is produced by the dichloroelimination of 1,1,2,2-tetrachloroethane (TeCA). In contrast, TeCA degrades to TCE via dehydrohalogenation in the aquifer, indicating that the aquifer-aquitard interface separates two different degradation pathways for TeCA. Moreover, the CSIA profiles showed that chloroform (CF) is degraded to dichloromethane (DCM) via hydrogenolysis in the aquitard and, to a minor degree, produced by the degradation of carbon tetrachloride (CT). Several microorganisms capable of degrading chlorohydrocarbons were detected in the aquitard, suggesting that aquitard degradation is microbially mediated. Furthermore, numerical simulations reproduced the aquitard concentration and CSIA profiles well, which allowed the determination of degradation rates for each transformation pathway. This improves the prediction of contaminant fate in the aquitard and potential magnitude of impacts on the adjacent aquifer due to back-diffusion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".