Approaches to the remediation of a polychlorinated biphenyl (PCB) contaminated soil–a laboratory study
Bibliographic record
Abstract
A soil that had been historically contaminated with Aroclor 1242, 1248, 1254 and 1260 was decontaminated by two surfactant-mediated cleaning procedures that had been chosen to mimic ex-situ washing and in-situ soil flushing processes. A preliminary screening selected four surfactants (from 17 commercial formulations) for their ability to mobilise PCBs from the soil while suffering minimal losses to the supercritical carbon dioxide (scCO2) that was used in a separate back-extraction procedure. The mobilisation was enhanced, with minimal foam formation, by the presence of 17% (v/v) IBMK in the surfactant suspension. Each of the four surfactants, at 1, 3, or 5% (v/v) concentration, was evaluated by (i) 15 successive 10 min sonication-filtrations and (ii) continuous soil column flushing during 20 h. Each filtrate from (i) and samples, taken at hourly intervals, from (ii) were analysed for their PCB and surfactant content. Both extraction procedures mobilised PCBs efficiently when extended for longer periods and were modelled accurately as the sum of a constant and single-term exponential increase to a maximum. The predicted number of replicate stages required to mobilise 50% of the toxicants (t50) varied from 7 to 3 for sonication-washing of the soil (10 g) or from 6.8 to 2.8 h for column flushing of 30 g soil and decreased as the concentration of surfactant in the aqueous phase was increased. The combined PCB-laden aqueous suspensions were then back-extracted efficiently with scCO2 and the eluate was dechlorinated quantitatively as it traversed a short, heated column of silver-iron bimetallic mixture.
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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 | 0.001 | 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".