Oxidative potential of ambient particulate matter from community sites in Alberta's oil sands region
Bibliographic record
Abstract
Air pollution is a major environmental health risk and it has been associated with various diseases and mortality worldwide. The inhalation of fine particulate matter (PM) is an important cause of health effects from air pollution with one of underlaying mechanisms involving the induction of oxidative stress in the body. Oil sands mining is a major economic sector and a notable source of air pollution in northern Alberta, Canada. Despite this, studies investigating the potential health impacts associated with exposure to air pollutants in the region are rare. For the first time in this work, using an acellular • OH assay, we studied the oxidative potential (OP) of fine (<2.5 μm diameter) and coarse (2.5–10 μm diameter) PM from four community sites in the vicinity of oil sands production facilities. OP OH was found to be dominated by fine PM, which on average accounted for 70 % reactivity of the studied PM size range. The highest OP OH was found at the most populated sites located south of the open pit mines and with mixed emission sources, suggesting a cumulative effect of oil sands and non-oil sands sources. Nevertheless, OP OH was relatively small compared to values reported for urban sites influenced by traffic and industrial emissions in Canada. OP OH variation could not be linked with a statistical significance to changes in the concentrations of PM, trace metals, and secondary inorganic salts but, for a small set of samples, OP OH was associated with organic carbon and potassium, which suggests the influence of reactive organic species from biomass combustion. A larger sample size will be needed in order to examine more closely the links between various OP metrics and the aerosol composition and sources in the region. This work provides a proof of concept to support future studies aimed at assessing potential health impacts associated with exposure to air pollutants in the oil sands region.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".