Meteorological influences on the spatial and temporal variability of NO<sub>2</sub> in Toronto and Hamilton
Bibliographic record
Abstract
The spatial and temporal variability of nitrogen dioxide (NO2) concentrations and their relationships with meteorology was evaluated in the Toronto–Hamilton urban airshed. NO2 concentrations were highest in the early morning and late evening. Mean concentrations were highest in winter, although individual one‐hour NO2 concentrations were found to be highest in summer. Wind direction was the strongest control on hourly NO2 concentration, and temperature and wind speed also had an effect. Our analysis of NO2 concentration variation by wind direction showed that areas downwind of major highways, urban centres and industry were exposed to higher pollutant concentrations. Seasonal patterns of NO2 concentration displayed significant spatial heterogeneity, in particular, in Toronto. Onshore winds sheltered coastal inhabitants from the full extent of NO2 exposure they would otherwise experience. Seasonal variations in meteorology and emissions mean that the degree of spatial variability in NO2 concentrations changes from season to season. This study will help to improve existing land‐use regression‐based NO2 prediction models by incorporating meteorological controls on NO2 distributions for health effect studies.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".