Chemical fingerprinting of naphthenic acids and oil sands process waters—A review of analytical methods for environmental samples
Bibliographic record
Abstract
This article provides a review of the routine methods currently utilized for total naphthenic acid analyses. There is a growing need to develop chemical methods that can selectively distinguish compounds found within industrially derived oil sands process affected waters (OSPW) from those derived from the natural weathering of oil sands deposits. Attention is thus given to the characterization of other OSPW components such as oil sands polar organic compounds, PAHs, and heavy metals along with characterization of chemical additives such as polyacrylamide polymers and trace levels of boron species. Environmental samples discussed cover the following matrices: OSPW containments, on-lease interceptor well systems, on- and off-lease groundwater, and river and lake surface waters. There are diverse ranges of methods available for analyses of total naphthenic acids. However, there is a need for inter-laboratory studies to compare their accuracy and precision for routine analyses. Recent advances in high- and medium-resolution mass spectrometry, concomitant with comprehensive mass spectrometry techniques following multi-dimensional chromatography or ion-mobility separations, have allowed for the speciation of monocarboxylic naphthenic acids along with a wide range of other species including humics. The distributions of oil sands polar organic compounds, particularly the sulphur containing species (i.e., OxS and OxS2) may allow for distinguishing sources of OSPW. The ratios of oxygen- (i.e., Ox) and nitrogen-containing species (i.e., NOx, and N2Ox) are useful for differentiating organic components derived from OSPW from natural components found within receiving waters. Synchronous fluorescence spectroscopy also provides a powerful screening technique capable of quickly detecting the presence of aromatic organic acids contained within oil sands naphthenic acid mixtures. Synchronous fluorescence spectroscopy provides diagnostic profiles for OSPW and potentially impacted groundwater that can be compared against reference groundwater and surface water samples. Novel applications of X-ray absorption near edge spectroscopy (XANES) are emerging for speciation of sulphur-containing species (both organic and inorganic components) as well as industrially derived boron-containing species. There is strong potential for an environmental forensics application of XANES for chemical fingerprinting of weathered sulphur-containing species and industrial additives in 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".