Total organic carbon measurements reveal large discrepancies in reported petrochemical emissions
Bibliographic record
Abstract
Oil sands are a prominent unconventional source of petroleum. Total organic carbon measurements via an aircraft campaign (Spring-Summer 2018) revealed emissions above Canadian oil sands exceeding reported values by 1900-6300%. The “missing” compounds were predominantly intermediate- and semi-volatile organic compounds, which are prolific precursors to secondary organic aerosol formation. Here we use a novel combination of aircraft-based measurements (including total carbon emissions measurements) and offline analytical instrumentation to characterize the mixtures of organic carbon and their volatility distributions above oil sands facilities. These airborne, real-time observations are supplemented by laboratory experiments identifying substantial, unintended emissions from waste management practices, emphasizing the importance of accurate facility-wide emissions monitoring and total carbon measurements to detect potentially vast missing emissions across sources.Detailed chemical speciation confirms these observations near both surface mining and in-situ facilities were oil sands-derived, with facility-wide emissions around 1% of extracted petroleum—a comparable loss rate to natural gas extraction. Total emissions, spanning extraction through waste processing, were equivalent to total Canadian anthropogenic emissions from all sources. These results demonstrate that the full air quality and environmental impacts of oil sands operations cannot be captured without complete coverage of a wider volatility range of emissions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".