Analysis of Naphthenic Acid–Salt Interactions in Simulated Oil Sands Process Water
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The extraction of bitumen from oil sands involves the use and reuse of large volumes of water. When water reaches a point where it can no longer be recycled, it is termed oil sands process-affected water (OSPW). OSPW contains a mixture of residual hydrocarbons, including naphthenic acids, and has elevated salinity. This work presents new insights based on a laboratory-based study of how salinity influences the naphthenic acid compounds observed in water. Laboratory bench-scale simulations were set up to measure how water chemistry changes, with both time and under different salt conditions, using Milli-Q water and a simulated OSPW water matrix. Samples were analyzed for basic water chemistry and by high-resolution Orbitrap mass spectrometry. Data are discussed with regard to overall quantification of organic species and naphthenic acid fraction compounds (NAFCs) in the water, as well as by hydrocarbon class, double-bond equivalent, and carbon number. Mass spectral quantitation and characterization showed that the presence of salts and ions in the simulated OSPW (i) increases the concentration of measured species and (ii) changed the relative distribution of oxygenated polar hydrocarbons. For example, a depletion of the aqueous O2-NAFCs occurred over time with a corresponding increase in the levels of the aqueous O3-NAFCs in saline waters. These findings on temporal changes in concentration and molecular level distributions of NAFCs may have implications for the clean-up and remediation of saline OSPW.
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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) | 0.001 | 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".