Impact of Reduced Anthropogenic Emissions Associated With COVID‐19 Lockdown on PM<sub>2.5</sub> Concentration and Canopy Urban Heat Island in Canada
Bibliographic record
Abstract
Abstract Extensive lockdowns during the COVID‐19 pandemic caused a remarkable decline in human activities that have influenced urban climate, especially air quality and urban heat islands. However, the impact of such changes on local climate based on long term ground‐level observations has hitherto not been investigated. Using air pollution measurements for the four major Canadian metropolitan areas (Toronto, Montreal, Vancouver, and Calgary), we find that PM2.5 markedly decreased during and after lockdowns with peak reduction ranging between 42% and 53% relative to the 2000–2019 reference period. Moreover, we show a substantial decline in canopy urban heat island intensity during lockdown and in the post lockdowns periods with peak reduction ranging between 0.7°C and 1.6°C in comparison with the 20‐year preceding period. The results of this study may provide insights for local policymakers to define the regulation strategies to facilitate air quality improvement in urban areas.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".