Organic solvents improve hydrocarbon desorption and biodegradation in highly contaminated weathered soils
Bibliographic record
Abstract
Slurry phase laboratory microcosms were used to investigate the effect of selected solvents (hexane, benzene, toluene, n-butanol, acetone, and methanol) on desorption and the resulting microbial biodegradation of hydrocarbons in highly contaminated weathered soils. For nonpolar solvents, solubility and desorption of hydrocarbons increased linearly as polarity increased. In desorption and biodegradation assays, toluene significantly increased hydrocarbon consumption by twice as much, in comparison to the control without solvent. After 30 culture days, the initial hydrocarbon concentration in soil (Soxhlet method), 237.2 g kg–1 of dry soil, diminished 21% when toluene was initially added. Saturated and aromatic fractions became degraded to a greater extent in the presence of toluene, 11% and 50%, respectively. The results in this research indicated that the use of solvents is effective in improving both hydrocarbons desorption and biodegradation in highly polluted weathered soils. Key words: slurry phase, overall hydrocarbon biodegradation, solvents, hydrocarbon fractions, biodegradation.
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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 | 0.001 |
| 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".