An Evaluation of the Ideality of Benzene, Toluene, Ethylbenzene, and Xylene on Activity Coefficients in Gas Condensate and the Implications for Dissolution in Groundwater
Bibliographic record
Abstract
Studies were conducted to measure aqueous concentrations of benzene and xylene in BTEX (benzene, ethylbenzene, toluene, xylene) mixtures and in groundwater contaminated with gas-condensates, to support the remediation of contaminated subsurface environments at gas plants in western Canada. Volume ratios investigated were 20:5:2:2:2:2 and 40:5:2:2:2:2 for B:T:E:o-X:p-X:m-X. and 1:1 for sour-gas condensate and benzene mixtures. As expected, the equilibrium concentrations of benzene partitioning in the water for hydrocarbon mixtures could be estimated using Raoult’s Law. However, this was not the case for T, E, X where there was poor agreement with Raoult’s Law. In particular, the measured concentration for xylene was 2 to 10 times higher than that expected for ideal behaviour and was in the range 30–45 mg/L for aqueous BTEX mixtures and 8–30 mg/L for gas condensate contaminated groundwater. It is shown that this non-ideal behaviour was due to the high activity coefficients (γ > 1) of TEX in the gas condensate. In general, values of γ for BTEX in petroleum mixtures could be estimated to within an error of 25% of measured values using the empirical equation γ = 0.224 S−0.402, where S is the aqueous solubility (mg/L) of the pure component.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".