Impact of Canadian Wildfires 2023 on North Atlantic’s Region Air Quality: An Analysis Using ASDC Data
Bibliographic record
Abstract
The escalating threat of wildfires in North America raises significant concerns regarding their adverse effects on air quality and public health, as recent wildfires have resulted in widespread smoke plumes that transcend international borders. This study focuses on the exposure of the North Atlantic region to smoke from Canadian wildfires, underscoring the profound implications for public health and environmental well-being. To assess the air quality impact, we analyze satellite data obtained from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, in conjunction with ground-based measurements and atmospheric modeling outputs. Specifically, we investigate concentrations of atmospheric aerosols, notably PM2.5 particulate matter originating from Canadian wildfires, dispersion patterns, and the duration and intensity of smoke events affecting the North Atlantic. Utilizing data from multiple instruments — including those from the Earth Polychromatic Imaging Camera (EPIC), the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP Lidar), and Measurement of Pollution in the Troposphere (MOPITT) — strengthens the conclusions drawn from the impact assessment and estimation of aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes.The study's findings enhance understanding of the repercussions of Canadian wildfires on air quality in the North Atlantic region, underscoring the necessity of monitoring and prediction of transboundary smoke events through the integration of data from diverse sources, such as those provided by the ASDC. This information is pivotal for policymakers, public health officials, and residents in affected areas to formulate effective strategies in mitigating health risks associated with wildfire smoke and improving air quality during wildfire seasons. The study emphasizes the critical role of atmospheric remote sensing, particularly the use of ASDC data, in addressing the challenges posed by wildfires and their consequences on regional scales.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".