Quantifying the Primary Emissions and Photochemical Formation of Isocyanic Acid Downwind of Oil Sands Operations
Bibliographic record
Abstract
Isocyanic acid (HNCO) is a known toxic species and yet the relative importance of primary and secondary sources to regional HNCO and population exposure remains unclear. Off-road diesel fuel combustion has previously been suggested to be an important regional source of HNCO, which implies that major industrial facilities such as the oil sands (OS), which consume large quantities of diesel fuel, can be sources of HNCO. The OS emissions of nontraditional toxic species such as HNCO have not been assessed. Here, airborne measurements of HNCO were used to estimate primary and secondary HNCO for the oil sands. Approximately 6.2 ± 1.1 kg hr –1 was emitted from off-road diesel activities within oil sands facilities, and an additional 116–186 kg hr –1 formed from the photochemical oxidation of diesel exhaust. Together, the primary and secondary HNCO from OS operations represent a significant anthropogenic HNCO source in Canada. The secondary HNCO downwind of the OS was enhanced by up to a factor of 20 relative to its primary emission, an enhancement factor significantly greater than previously estimated from laboratory studies. Incorporating HNCO emissions and formation into a regional model demonstrated that the HNCO levels in Fort McMurray (∼10–70 km downwind of the OS) are controlled by OS emissions; > 50% of the monthly mean HNCO arose from the OS. While the mean HNCO levels in Fort McMurray are predicted to be below the 1000 pptv level associated with potential negative health impacts, (∼25 pptv in August–September), an order of magnitude increase in concentration is predicted (250–600 pptv) when the town is directly impacted by OS plumes. The results here highlight the importance of obtaining at-source HNCO emission factors and advancing the understanding of secondary HNCO formation mechanisms, to assess and improve HNCO population exposure predictions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".