Modelling and Mapping Regional Indoor Radon Risk in British Columbia, Canada
Notice bibliographique
Résumé
Monitoring and mapping the presence and/or intensity of an environmental hazard through space, is an essential part of public health surveillance. Radon, a naturally occurring radioactive carcinogenic gas, is an environmental hazard that is both the greatest source of natural radiation exposure in human populations and the second leading cause of lung cancer worldwide. Concentrations of radon can accumulate in an indoor setting, and, though there is no safe concentration, various guideline values from different countries, organizations and regions provide differing threshold concentrations that are often used to delineate geographic areas at higher risk. Radon maps demarcate geographic areas more prone to higher concentrations but can underestimate or overestimate indoor radon risk depending on the concentration threshold used. The goals of this thesis are to map indoor radon risk in the province of British Columbia, identify areas more prone to higher concentrations and their associations with different radon concentration thresholds and lung cancer mortality trends. The first analysis was concerned with developing a data-driven method to predict and map ordinal classes of indoor radon vulnerability at aggregated spatial units. Spatially referenced indoor radon concentration data were used to define low, medium and high classes of radon vulnerability, which were then linked to regional environmental and housing data derived from existing geospatial datasets. A balanced random forests algorithm was used to model environmental predictors of indoor radon vulnerability and predict values for un-sampled locations. A model was generated and evaluated using accuracy, precision, and kappa statistics. We investigated the influence of predictor variables through variable importance and partial dependence plots. The model performed 34% better than a random classifier. Increased probabilities of high vulnerability were found to be associated with cold and dry winters, close proximity to major river systems, and fluvioglacial and colluvial soil parent materials. The Kootenays and Columbia-Shuswap regions were most at risk. We built upon the first analysis by assessing the difference between temporal trends in lung cancer mortality associated with areas of differing predicted radon risk. We assessed multiple scenarios of risk by using eight different radon concentration thresholds, ranging from 50 to 600 Bq m-3, to define low and high radon vulnerability. We then examined how the following parameters changed with the use of a different concentration threshold: the classification accuracy of each radon vulnerability model, the geographic characterizations of high risk, the population within high risk areas and the differences in lung cancer mortality trends between high and low vulnerability stratified by sex and smoking prevalence. We found the classification accuracy of the model improved as the threshold concentrations decreased and the area classified as high vulnerability increased. The majority of the population were found to live in areas of lower vulnerability regardless of the threshold value. Thresholds as low as 50 Bq m-3 were associated with higher lung cancer mortality trends, even in areas with relatively low smoking prevalence. Lung cancer mortality trends were increasing through time for women, while decreasing for men. We suggest a reference level as low as 50 Bq m-3 is justified for the province.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,003 | 0,000 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».