Compound-Specific Isotope Analysis (CSIA) Application for Source Apportionment and Natural Attenuation Assessment of Chlorinated Benzenes
Bibliographic record
Abstract
In light of the complex management of chlorobenzene (CB) contaminated sites, at which a hydraulic barrier (HB) for plumes containment is emplaced, compound-specific stable isotope analysis (CSIA) has been applied for source apportionment, for investigating the relation between the upgradient and downgradient of the HB, and to target potential CB biodegradation processes. The isotope signature of all the components potentially involved in the degradation processes has been expressed using the concentration-weighted average δ13C of CBs + benzene (δ13Csum). Upgradient of the HB, the average δ13Csum of −25.6‰ and −29.4‰ were measured for plumes within the eastern and western sectors, respectively. Similar values were observed for the potential sources, with δ13Csum values of −26.5‰ for contaminated soils and −29.8‰ for the processing water pipeline in the eastern and western sectors, respectively, allowing for apportioning of these potential sources to the respective contaminant plumes. For the downgradient of the HB, similar CB concentrations but enriched δ13Csum values between −24.5‰ and −25.9‰ were measured. Moreover, contaminated soils showed a similar δ13Csum signature of −24.5‰, thus suggesting that the plumes likely originate from past activities located in the downgradient of the HB. Within the industrial property, significant δ13C enrichments were measured for 1,2,4-trichlorobenzene (TCB), 1,2-dichlorobenzene (DCB), 1,3-DCB, and 1,4-DCBs, thus suggesting an important role for anaerobic biodegradation. Further degradation of monochlorobenzene (MCB) and benzene was also demonstrated. CSIA was confirmed to be an effective approach for site characterization, revealing the proper functioning of the HB and demonstrating the important role of natural attenuation processes in reducing the contamination upgradient of the HB.
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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 | 0.000 | 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) | 0.000 | 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".