Laboratory study of solvent extraction of polychlorinated biphenyls in soil
Bibliographic record
Abstract
Polychlorinated biphenyls (PCBs) are toxic, stable organic contaminants that are present in air, water, soil, plants and animals all around the world. The market for PCB treatment technologies is estimated to be $300 to $600 million (Canadian dollars) for the year 2000, and will expand in future years. Existing treatment technologies to remove PCBs from soil are underutilized because they are more expensive than landfilling and incineration. This thesis presents a laboratory study of an innovative PCB remediation process that will extract PCBs from soil in-situ for subsequent destruction above ground. This remedy will remove PCBs from surficial soil without the need for excavation. Two laboratory studies were conducted on field-contaminated soil. The first experiment evaluated the effectiveness of hexane, methyl isobutyl ketone, and ethyl acetate in removing PCBs from soil. Ethyl acetate and MIBK were equally effective, removing 99% and 98% of PCBs from dry soil in 4 days, respectively. In the second experiment, soil was exposed to ethyl acetate for varying amounts of time, and some of the samples were treated a second time with fresh solvent. PCB removal increased as treatment time was increased from 10 minutes to 50, 250, and 1250 minutes, but the rate of PCB removal decreased as treatment time increased. The second 10-minute extraction removed an additional 1--10% of the remaining PCBs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".