Polychlorinated biphenyl (PCB) recovery under a building with an in situ technology using micellar solutions
Bibliographic record
Abstract
This paper presents laboratory studies, numerical modelling, and a soil washing field test as a remedial technology for mass reduction in a source zone of soil contaminated with the polychlorinated biphenyl (PCB) Aroclor 1248 beneath an industrial building. Due to its high viscosity, the Aroclor 1248 is almost immobile in soils at this site. The objective was therefore to select products capable of dissolving the Aroclor in situ. In the laboratory phase, two surfactants and three alcohols were selected using 52 distinct phase diagrams. Alcohols and surfactants used either alone or in combination were tested in sand columns with contaminated soil from the site. The washing solution used in the field test was composed of an anionic surfactant (Nansa HS 85 S, a dodecylbenzene sulfonate) and an alcohol (n-butanol). In laboratory trials, this solution recovered 99% of initial PCBs by dissolution after the injection of 10 pore volumes of solution. During the field test, however, recovery rates reached only 25%. Low recovery can be explained by the presence of a surfactant in the soil prior to the experiment. This surfactant spilled accidentally within the ongoing production activity of the factory was similar to that injected in the experimental cell. It modified the ratio of alcohol to surfactant of the injected washing solution in the soil and caused the formation of a viscous gel, which partially plugged the porous media. Phase diagrams and sand column tests performed with the recovered viscous gel led to the selection of an alcohol (ethanol) that is able to dissolve the gel and recover 99% of the initial PCBs contained in the contaminated soil by dissolution, following the injection of three pore volumes of solution. These laboratory tests showed that in situ flushing technology using micellar and (or) alcohol solutions can potentially be used to reduce the mass of PCB in the source zone, but the application of in situ technologies at industrial facilities is difficult to control because of the risk of presence of other chemicals that might interfere and concrete and other buried structures that might alter the flow behavior.Key words: soil washing, surfactant, alcohol, PCB, in situ technology, porous media clogging.
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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) | 0.001 | 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".