A Comparison of Particulate Matter Exposures Between a Student’s Private Vehicle and Public Bus Transit Commutes
Bibliographic record
Abstract
Daily commuters of public transportation and private vehicles are exposed to a wide range of traffic-related air pollution (TRAP). However, evidence of differences between commuting method has been building. In this study, the personal ultrafine particle (UFP) and black carbon (BC) air pollution exposures of a high school student were measured during their daily commute. In total, 39 commutes made between the student’s home and school were measured. These commutes were either by bus or private vehicle. Data was analysed using box plots and T-tests of statistical significance. Levels of BC were not significantly higher on buses (mean(SD) = 849(645) ng/m3) than cars (650(689) ng/m3) (p-value = 0.199). For UFP, levels were significantly higher for bus commutes (9393(6923) pts/cm3) than those of private vehicle (4234(6446) pts/cm3) (p-value = 0.045). Our findings suggest that bus commuters may experience higher exposure to UFP relative to private vehicle commuters. The higher UFP exposure may be accounted by the fact that city buses can have a higher air exchange rate due to the constant opening of doors. As well, buses are mainly diesel vehicles, which are a strong source of UFP.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".