Evaluation of the BlueSky smoke forecasting system and its utility for public health protection in British Columbia
Notice bibliographique
Résumé
Wildfire smoke is a major contributor to extreme particulate matter (PM) air pollution events and has been associated with respiratory and cardiovascular health effects. With climate change, more frequent and intense wildfires are expected in the future and their impact on public health will likely increase. The existing exposure assessment tools such as the monitoring network and remote sensing platforms have limitations for measuring wildfire smoke, including inadequate coverage and measuring total column instead of ground-level concentrations. From the public health perspective, a system that can supplement these tools and predict smoke concentrations will be valuable. The Western Canada BlueSky Smoke Forecasting System, which can predict PM₂.₅ (PM <2.5μm in diameter) from wildfires up to 60 hours in advance, has been developed since 2008. So far, there has not been any systematic and quantitative evaluation of its performance. The first objective of this study was to evaluate the performance of BlueSky. We compared its forecasting output with monitoring measurements and remote sensing images with several different model evaluation statistics of temporal and spatial agreement. The second objective was to assess the association between BlueSky predictions and respiratory health indicators. Poisson regression was employed between BlueSky predictions and the health outcome indicators, including counts of prescriptions dispensed to relieve respiratory health symptoms and counts of physician visits for asthma. Results suggested that BlueSky predicted smaller smoke plumes within the plumes observed by remote sensing. It predicted PM₂.₅ concentrations comparable to monitor measurements in the middle of the fire period and in areas consistently impacted by wildfire smoke. More frequent and larger-scale overpredictions were observed. A 30μg/m³ increase in BlueSky 24-hour PM₂.₅ predictions was associated with 1% increase in medication dispensations and physician visits for asthma. The relative risks were smaller than those associated with monitoring measurements. Smoke plume coverage predicted by BlueSky was associated with relative risks comparable with those observed by remote sensing. In conclusion, BlueSky predictions were comparable with measurements from other smoke assessment tools and they were significantly associated with respiratory health outcomes. This study provides evidence to support the use of BlueSky in public health protection.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».