Cosolvency Effects of Monoethanolamine and Triethanolamine: Implications for the Remediation of Benzene in Groundwater at Sour-Gas Plants
Bibliographic record
Abstract
Studies were conducted to measure the cosolvency effect of monoethanolamine (MEA) and triethanolamine (TEA) on the aqueous solubility of benzene in support of the remediation of contaminated subsurface environments at gas plants in western Canada. Experiments utilized sodium chloride solutions of the amines in the concentration range of 0–0.065 volume fractions, and non-saline waters in the range 0–1 volume fractions. The measured values of the cosolvency power σ for MEA and TEA, based on the log-linear model, were 1.86 ± 0.05 and 2.21 ± 0.04, respectively. The corresponding values for the semi-cosolvency power σ0.5 were 1.22 ± 0.005 and 1.19 ± 0.005, respectively. It is postulated that the difference in the values of σ and σ0.5 may be linked to cosolvent polarity of the amines in water. In 0.2 Mol/L NaCl saline water, the solubility of benzene increased linearly from 1660 mg/L to 2170 mg/L and 1960 mg/L for cosolvents MEA and TEA (0–0.065 volume fractions), respectively. As evidenced by the measured 30% increase in the solubility of benzene, remediation strategies of groundwater at sour-gas plants should therefore take into account the levels of these amines and their effects on the transport of hydrocarbon contaminants.
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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) | 0.000 | 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) | 0.000 | 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".