Simultaneous Soil Cd and PCB Decontamination using a Surfactant/Ligand Solution
Bibliographic record
Abstract
The simultaneous desorption of Cd and PCBs, from a contaminated soil, was investigated using a surfactant/ligand solution. The test surfactants were combinations of a nonionic surfactant [polyethylene oxide (PEO) of chain length 7.5 (Triton X-114), 9.5 (Triton X-100), 30 (Triton X-305), or 40 units (Triton X-405)], with iodide (I-). Triplicate 1 g soil samples were equilibrated, during 24h, with 15 mL of surfactant/ligand solution, at 0.025 or 0.50 and 0.0, 0.168, or 0.336 mol L(-1), respectively. The supernatant fraction was then separated from the particulates by centrifugation and analyzed for Cd to determine Cd desorption efficiency. After five consecutive washings, the treated soil samples were analyzed for PCB content to determine the desorption efficiency of this class of toxicant. Desorption of Cd increased with both increasing ligand concentration and decreasing surfactant chain length and concentration. The maximum Cd desorption efficiency (61%), was obtained with Triton X-100 at 0.025 mol L(-1), in the presence of I at 0.336 mol L(-1). After 5 successive washings, virtually quantitative PCB desorption (below limits of detection for tetra-, penta-, and hexachloro biphenyl compounds) had been achieved with most of surfactant/ligand combinations. Maximum desorption efficiency was achieved using either shorter chain length surfactant (n = 7.5 or 9.5) in combination with a higher ligand concentration, or using longer chain length surfactants (n = 30 and 40) with a lower ligand concentration. Thus, heavy metals and PCBs can be desorbed simultaneously from a contaminated soil with the same washing reagents, namely a surfactant-ligand combination. The optimum surfactant-ligand combination for the simultaneous desorption of both heavy metals and PCBs was a short chain length (n = 7.5 or 9.5) surfactant at low concentration admixed with 0.336 mol L(-1) I-.
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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 | 0.001 | 0.001 |
| 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".