Evaluation of Mutual Connections between Zero‐Valent Iron Reactivity and Groundwater Composition in Trichloroethylene Degradation
Bibliographic record
Abstract
Zero-valent iron Permeable Reactive Barriers (PRBs) are an efficient and relatively low cost in situ technology for the remediation of aquifers polluted by chlorinated solvents. The groundwater composition and the zero-valent iron reactive material are linked by mutual connections. The groundwater, to a certain extent depending on its composition, is able to oxidize the metallic iron, thus decreasing its reactivity; on the other hand, the dechlorination process and the leaching of chemical species from the reactive substrate may deeply modify groundwater composition. In this study the results of some batch and leaching column tests, performed by means of Connelly iron (Environmental Technologies Inc., Canada) and different aqueous phases (distilled water and an artificial groundwater) are compared, to evaluate the influence of groundwater composition on the reactivity of the iron material for trichloroethylene (TCE) remediation. The degradation mechanisms of the pollutant are discussed. On the grounds of the gathered results the aqueous phase composition shows a strong influence on TCE degradation kinetics obtained by means of Connelly iron; in fact the presence of dissolved substances accelerates TCE degradation.
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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 | 0.001 | 0.001 |
| 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".