Sources of Personal Exposure to Fine Particles in Toronto, Ontario, Canada
Bibliographic record
Abstract
Individuals are exposed to particulate matter from both indoor and outdoor sources. The aim of this study was to compare the relative contributions of three sources of personal exposure to fine particles (PM2.5) by using chemical tracers. The study design incorporated repeated 24-hr personal exposure measurements of air pollution from 28 cardiac-compromised residents of Toronto, Ontario, Canada. Each study participant wore the Rupprecht & Patashnick ChemPass Personal Sampling System 1 day a week for a maximum of 10 weeks. During their individual exposure measurement days the subjects reported to have spent an average of 89% of their time indoors. Particle phase elemental carbon, sulfate, and calcium personal exposure data were used in a mixed-effects model as tracers for outdoor PM2.5 from traffic-related combustion, regional, and local crustal materials, respectively. These three sources were found to contribute 13% +/- 10%, 17% +/- 16%, and 7% +/- 6% of PM2.5 exposures. The remaining fraction of the personal PM2.5 is hypothesized to be predominantly related to indoor sources. For comparison, central site outdoor PM2.5 measurements for the same dates as personal measurements were used to construct a receptor model using the same three tracers. In this case, traffic-related combustion, regional, and local crustal materials were found to contribute 19% +/- 17%, 52% +/- 22%, and 10% +/- 7%, respectively. Our results indicate that the three outdoor PM2.5 sources considered are statistically significant contributors to personal exposure to PM2.5. Our results also suggest that among the Toronto subjects, who spent a considerable amount of time indoors, exposure to outdoor PM2.5 includes a greater relative contribution from combustion sources compared with outdoor PM2.5 measurements where regional sources are the dominant contributor.
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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 | 0.001 | 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 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".