Remediation of trichloroethylene by zero-valent iron permeable reactive barriers
Bibliographic record
Abstract
Trichloroethylene (TCE), belonging to the class of Dense Non-Aqueous Phase Liquids (DNAPLs), is a contaminant which is very persistent and widespread in groundwater because of its massive industrial use in past decades (i.e. in the metallurgical, textile and dye production industries). Among the in situ remediation technologies for the recovery of groundwaters polluted by chlorinated solvents, zero-valent iron Permeable Reactive Barriers (PRBs) have a primary importance; this technique, developed in Canada in the nineties, is based on the reductive action of zero-valent iron in a dechlorination process. The PRB is set perpendicularly to the groundwater flow direction, and chlorinated solvents are converted to non-toxic products, such as alkanes and alkenes, through various reaction pathways. In this work a zero-valent iron PRB is proposed as a cleanup methodology for the polluted groundwater of a site near Turin (Northern Italy), used in the past as an industrial landfill for the waste coming from a cast iron foundry. A zero-valent iron (Connelly iron, purchased from Environmental Technologies Inc., Canada), after characterization by means of particle-size and chemical analyses, was evaluated as reactive material. A leaching test, to verify the environmental impact of the material on the groundwater, was also performed on Connelly iron. Batch and column laboratory tests were performed using at first distilled water, and then an aqueous phase with a chemical composition similar to the polluted groundwater. The degradation mechanisms of TCE, hypothesizing a first order kinetic, were discussed, and the values of the kinetic constant and the necessary residence time in the PRB (the period necessary to lower the pollutant concentration below the Italian law limits for groundwater) obtained from the batch and column tests were compared and discussed.
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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) | 0.000 | 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 teacher head, 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".