Impacts of the 2021 Northwestern Ontario and Manitoba Wildfires on the Chemical Composition and Oxidative Potential of Airborne Particulate Matter in Montréal, Canada
Bibliographic record
Abstract
In July and August 2021, wildfire smoke transported from Northwestern Ontario and Manitoba impacted the air quality in Montréal, Québec, Canada. To investigate the impact of the wildfire smoke on PM 10 composition in an urban environment, samples were collected and analyzed for organic carbon (OC), elemental carbon (EC), elements, water-soluble ions, sugars, and polycyclic aromatic hydrocarbons (PAHs) during contrasting periods of biomass burning and nonbiomass burning-influenced conditions. Biomass burning tracers in PM 10 (e.g., levoglucosan, mannosan, galactosan, rubidium, and water-soluble potassium) and other compounds associated with biomass burning emissions (e.g., OC, EC, oxalate, succinate, and NH 4 + ) increased by a factor of 2.0–5.0 during biomass burning periods. The influence of wildfires had little impact on trace elements (e.g., Ba, Co, Cu, Mn, Ni, Pb, Sr, and V) concentrations which did not increase significantly compared to the urban background. Major PM 10 constituents were carbonaceous matter, followed by crustal matter and secondary inorganic ions during both biomass and nonbiomass burning days. The contribution of carbonaceous matter increased significantly during biomass burning events representing up to 71% of the total PM 10 mass concentration. The ascorbic acid assay found no notable difference in intrinsic oxidative potential between biomass burning and nonbiomass burning days despite decreasing proportions of redox-active metals in PM 10 during episodes of biomass burning smoke. This observation indicates that other components of biomass burning PM 10 such as organic matter and sulfate may directly or indirectly contribute to the oxidative potential in a way that compensates for the decreasing proportion of redox-active metals that normally dominate the oxidative potential measured by the ascorbic acid assay.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".