Sediment Monitored Natural Recovery Evidenced by Compound Specific Isotope Analysis and High-Resolution Pore Water Sampling
Bibliographic record
Abstract
Monitoring natural recovery of contaminated sediments requires the use of techniques that can provide definitive evidence of in situ contaminant degradation. In this study, a passive diffusion sampler, called “peeper”, was combined with Compound Specific Isotope Analysis to determine benzene and monochlorobenzene (MCB) stable carbon isotope values at a fine vertical resolution (3 cm) across the sediment water interface at a contaminated site. Results indicated significant decrease in concentrations of MCB from the bottom to the top layers of the sediment over 25 cm, and a 3.5 ‰ enrichment in δ 13 C values of MCB over that distance. Benzene was always at lower concentrations than MCB, with consistently more depleted δ 13 C values than MCB. The redox conditions were dominated by iron reduction along most of the sediment profile. These results provide multiple lines of evidence for in situ reductive dechlorination of MCB to benzene. Stable isotope analysis of contaminants in pore water is a valuable method to demonstrate in situ natural recovery of contaminated sediments. This novel high-resolution approach is critical to deciphering the combined effects of parent contaminant (e.g., MCB) degradation and both production and simultaneous degradation of daughter products, especially 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 | 0.000 | 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".