Release of polycyclic aromatic hydrocarbons from contaminated soils by surfactant and remediation of this effluent by<i>Penicillium</i>spp
Bibliographic record
Abstract
Abstract Studies in which surfactants have been employed to increase the bioavailability of soil-bound polycyclic aromatic hydrocarbons (PAHs) have not yielded consistent results. Surfactant mobilization of high molecular weight (MW) PAHs from contaminated soils has not been extensively studied; therefore, the purpose of this research was to compare the extent of release of freshly added high MW 14C-PAH with aged PAH from four different PAH-contaminated soils using a nonionic detergent, Tween 80, and to determine whether Tween 80-solubilized 14C-PAH in soil washings could be degraded by indigenous microorganisms or by added Penicillium spp. Only very high concentrations of Tween 80 (>1,000 times the critical micelle concentration [CMC] for 3 of 4 soils) were able to mobilize bound 14C-pyrene, -chrysene, and -benzo[a]pyrene. The concentration of surfactant required to release 50% of bound 14C-PAH (the SC50 value) ranged from 5 to 30 g/L depending on soil type; a modest correlation was found (0.512) between the fraction of organic carbon in the soil and the SC50 value. At 104 × CMC, Tween 80 released an average of 75% of bound 14C-PAH and 64% of the aged PAH, indicating that the 14C-PAH release only slightly overestimated PAH mobilization from weathered soil. An exception was one soil that had been previously remediated in which <30% of the PAHs were released. The PAH structure had a negligible effect on the mobilization by surfactant because the solubilization curves for all three PAHs were very similar. Tween 80-solubilized 14C-pyrene readsorbed to soil when the surfactant concentration dropped below 103 × CMC. Greater than 90% of the 14C-pyrene in the soil washing effluent could be removed by the addition of spores of active PAH-oxidizing Penicillium spp. plus nutrients. In contrast, <10% of 14C-pyrene was oxidized by the indigenous soil bacteria under the same conditions.
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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 | 0.001 | 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".