Radiative cooling in New York/New Jersey metropolitan areas by wildfire particulate matter emitted from the Canadian wildfires of 2023
Bibliographic record
Abstract
Wildfire particulate matter from Canadian forest fires significantly impacted the air quality in the northeastern United States during the summer of 2023. Here, we used real-time and time-integrated instrumentation to characterize the physicochemical properties and radiative effects of wildfire particulate matter reaching the metropolitan areas of New Jersey/ New York during this extreme incident. The radiative forcing of −352.4 W/m2 derived here based on the measured optical properties of wildfire particulate matter explains, to some extent, the ground level temperature reduction of about 3 °C observed in New Jersey/ New York City during this incident. Such negative radiative forcing in densely populated megacities may limit natural ventilation, increase the residence time of wildfire particulate matter and background air pollutants, exacerbating public health risks. This study highlights the importance of radiative effects from wildfire particulate matter in densely populated areas and their potential implications for climate, air quality and public health. Wildfire particulate matter emitted from the 2023 Canadian wildfires contributed to a reduction in temperature of 3 °C over New York and New Jersey area, according to real-time particulate matter monitoring combined with transport modelling.
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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 | 0.000 | 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 | 0.001 | 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 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".