Aerobic Biodegradation of Chlorinated Ethenes in a Fractured Bedrock Aquifer: Quantitative Assessment by Compound-Specific Isotope Analysis (CSIA) and Reactive Transport Modeling
Bibliographic record
Abstract
A model-based analysis of concentration and isotope data was carried out to assess natural attenuation of chlorinated ethenes in an aerobic fractured bedrock aquifer. Tetrachloroethene (PCE) concentrations decreased downgradient of the source, but constant delta13C signatures indicated the absence of PCE degradation. In contrast, geochemical and isotopic data demonstrated degradation of trichloroethene (TCE) and cis-1,2-dichloroethene (DCE) under the prevailing oxic conditions. Numerical modeling was employed to simulate isotopic enrichment of chlorinated ethenes and to evaluate alternative degradation pathway scenarios. Existing field information on groundwater flow, solute transport, geochemistry, and delta13C signatures of the chlorinated ethenes was integrated via reactive transport simulations. The results provided strong evidence for the occurrence of aerobic TCE and DCE degradation. The chlorinated ethene concentrations together with stable carbon isotope data allowed us to reliably constrain the assessment of the extent of biodegradation at the site and plume simulations quantitatively linked aerobic biodegradation with isotope signatures in the field. Our investigation provides the first quantitative assessment of aerobic biodegradation of chlorinated ethenes in a fractured rock aquifer based on compound specific stable isotope measurements and reactive transport modeling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 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".