Toluene NAPL Oxidation by Ferrous Activated Persulfate in a Fractured Rock Glass Replica
Bibliographic record
Abstract
Abstract Non‐aqueous phase liquids (NAPLs), such as toluene, often contaminate the subsurface. In this study, we focus on the transformation of toluene NAPL trapped in a single glass replica of a rock fracture via in situ chemical oxidation (ISCO) with ferrous activated persulfate. The trapped toluene consisted of a main trapped blob surrounded by smaller blobs. Over 53 days, successive persulfate injections into the fracture were interspersed with periods of water flushing. During persulfate injections, effluent toluene concentrations were below 0.04 mM. The rebound toluene concentrations during intervening water flushing periods decreased from 0.9 to 0.3 mM over the study. The smaller toluene blobs were removed by dissolution and partial oxidation. The main toluene blob was reduced in area by 35.5% and in volume by 37.3% due to dissolution and partial oxidation. The main blob changed in shape with reduction in size and there was also formation of an oxidation by‐product zone around the blob. The reduction in toluene effluent concentrations with time over successive persulfate injections and periods of water flushing was attributed to reductions in the NAPL‐water interfacial area of the blob and the formation of the by‐product zone surrounding the blob, which resulted in limited toluene dissolution. Analysis of by‐products of toluene oxidation by ferrous activated persulfate suggests that oligomers were part of the by‐product zone formed in the fracture. Gas bubbles were also observed in the fracture and may have formed from toluene oxidation and persulfate decomposition.
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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) | 0.001 | 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".