Fingerprinting TCE in a Bedrock Aquifer Using Compound‐Specific Isotope Analysis
Bibliographic record
Abstract
A dual isotope approach based on compound-specific isotope analysis (CSIA) of carbon (C) and chlorine (Cl) was used to identify sources of persistent trichloroethylene (TCE) that caused the shut-down in 1994 of a municipal well in an extensive fractured dolostone aquifer beneath Guelph, Ontario. Several nearby industrial properties have known subsurface TCE contamination; however, only one has created a comprehensive monitoring network in the bedrock. The impacted municipal well and many monitoring wells were sampled for volatile organic compounds (VOCs), inorganic parameters, and CSIA. A wide range in isotope values was observed at the study site. The TCE varies between -35.6‰ and -21.8‰ and from 1.6‰ to 3.2‰ for δ(13) C and δ(37) Cl, respectively. In case of cis-1,2-dichloroethene, the isotope values range between -36.3‰ and -18.9‰ and from 2.4‰ to 4.7‰ for δ(13) C and δ(37) Cl, respectively. The dual isotope approach represented by a plot of δ(13) C vs. δ(37) Cl shows the municipal well samples grouped in a domain clearly separate from all other samples from the property with the comprehensive well network. The CSIA results collected under non-pumping and short-term pumping conditions thus indicate that this particular property, which has been studied intensively for several years, is not a substantial contributor of the TCE presently in the municipal well under non-pumping conditions. This case study demonstrates that CSIA signatures would have been useful much earlier in the quest to examine sources of the TCE in the municipal well if bedrock monitoring wells had been located at several depths beneath each of the potential TCE-contributing properties. Moreover, the CSIA results show that microbial reductive dechlorination of TCE occurs in some parts of the bedrock aquifer. At this site, the use of CSIA for C and Cl in combination with analyses of VOC and redox parameters proved to be important due to the complexity introduced by biodegradation in the complex fractured rock aquifer. It is highly recommended to revisit the study when the municipal well is back into full operation.
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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) | 0.005 | 0.001 |
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; both teacher heads agree on what is shown here.
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".