Exposures to Polycyclic Aromatic Hydrocarbons and Their Mitigation in Wildland Firefighters in Two Canadian Provinces
Notice bibliographique
Résumé
OBJECTIVES: We aimed to characterize polycyclic aromatic hydrocarbons (PAHs) in the breathing zone and on the skin of wildland firefighters and to assess their contribution to urinary 1-hydroxypyrene (1-HP) over repeated firefighting rotations. We asked if improved skin hygiene or discretionary use of an N95 mask would reduce absorption. METHODS: In collaboration with wildfire services of two Canadian provinces, Alberta and British Columbia (BC), we recruited wildland firefighters from crews willing to be followed up over successive rotations and to be randomly assigned to normal practice, enhanced skin hygiene (ESH), or ESH plus discretionary use of an N95 mask. We collected spot urine samples at the beginning and end of up to four rotations/firefighter. On designated fire days, as close as possible to the end of rotation, we collected skin wipes from the hands, throat, and chest at the beginning and end of the fire day and, in BC, start of fire-day urine samples. Volunteers carried air monitoring pumps. Participants completed questionnaires at the beginning and end of rotations. Exposure since the start of the fire season was estimated from fire service records. Urinary 1-HP was analyzed by LC-MS-MS. Analysis of 21 PAHs on skin wipes and 27 PAHs from air sampling was done by GC-MS-MS. Statistical analysis used a linear mixed effects model. RESULTS: Firefighters in Alberta were recruited from five helitack crews and two unit crews, and in BC from two unit crews with 80 firefighters providing data overall. The fire season in BC was very active with five monitored fire days. In Alberta, with more crews, there were only seven fire days. Overall, log 1-HP/creatinine (ng/g) increased significantly from the start (N = 145) to end of rotation (N = 136). Only three PAHs (naphthalene, phenanthrene, and pyrene) were found on >20% of skin wipes. PAHs from 40 air monitoring pumps included 10 PAHs detected on cassette filters (particles) and 5 on sorbent tubes (vapor phase). A principal component extracted from air monitoring data represented respiratory exposure and total PAH from skin wipes summarized skin exposure. Both routes contributed to the end of rotation urinary 1-HP. The ESH intervention was not demonstrated to effect absorption. Allocation of an N95 mask was associated with lower 1-HP when modeling respiratory exposure (β = -0.62, 95% CI -1.15 to -0.10: P = 0.021). End of rotation 1-HP was related to 1-HP at the start of the next rotation (β = 0.25, 95% CI 0.12 to 0.39: P < 0.001). CONCLUSIONS: Exposures to PAHs during firefighting were significant, with samples exceeding the American Conference of Governmental Industrial Hygienists Biological Exposure Index for 1-HP suggesting a need for control of exposure. PAH exposure accumulated during the rotation and was not fully eliminated during the break between rotations. Both respiratory and skin exposures contributed to 1-HP. While improved skin hygiene may potentially reduce dermal absorption, that was not demonstrated here. In contrast, those allocated to discretionary use of an N95 mask had reduced 1-HP excretion. Wildland firefighters in North America do not use respiratory protection, but the results of this study support more effective interventions to reduce respiratory exposure.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».