Remediation of Gasoline Contaminated Soil Using Surfactant Enhanced Aquifer Remediation (SEAR)
Bibliographic record
Abstract
Leakage of gasoline from underground storage tanks into the subsurface poses a severe environmental problem. Surfactant Enhanced Aquifer Remediation (SEAR), which has advantages of lower cost and shorter duration time, is discussed in this paper as an emerging remediation technology. Laboratory phase behavior tests were used to determine the optimal surfactant solution (a mixture of surfactant, electrolyte and co-solvent) to remediate subsurface gasoline contamination. Winsor Type Phase Behavior of 348 surfactant solutions were used to determine the optimum surfactant solution: twelve surfactants were tested, sodium and calcium were tested as electrolyte at varying concentrations, and Sec.Bondary butyl alcohol and isopropanol were tested as co-solvents. Finally, the surfactant solution with 6% active by weight Sulfosuccinate Blend (Aerosol® LF-4), 9000 mg/l as calcium as electrolyte and 5% Sec.Bondary butyl alcohol as co-solvent was chosen for following 1-D column test, which is used to determine the amount of gasoline recovered from sand. Observed column test results showed that most (over 95%) of residual gasoline trapped in Ottawa sand was removed.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".