Characterization of exposure to air pollutants for workers in and around fires.

IF 1.5 4区 医学 Q4 ENVIRONMENTAL SCIENCES
Karin Lovén, Lina Hagvall, Johannes Rex, Carina A Nilsson, Vilhelm Malmborg, Joakim Pagels, Bo Strandberg, Maria Hedmer
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引用次数: 0

Abstract

Firefighters can be occupationally exposed to a wide range of airborne pollutants during fire-extinguishing operations. The overall study aim was to characterize occupational exposure to smoke for several groups of workers responding to fires, with specific aims to determine the correlations between exposure markers and to biologically assess their systemic exposure to polycyclic aromatic hydrocarbons (PAHs) in urine. Personal exposure measurements of equivalent black carbon (eBC), elemental carbon (EC), organic carbon (OC), nitrogen dioxide (NO2), PAHs, lung deposited surface area (LDSA), and particle number concentration (PNC) of ultrafine particles were performed on firefighters, observers, and post-fire workers during firefighting exercises. Urine samples were collected before and after exposure and analyzed for PAH metabolites. Additional routes for PAH skin exposure were investigated by wipe sampling on defined surfaces: equipment, personal protective equipment (PPE), and vehicles. Among workers without PPE, observers generally had higher exposures than post-fire workers. The observers and post-fire workers had an occupational exposure to smoke measured e.g. as EC of 7.3 µg m-3 and 1.9 µg m-3, respectively. There was a good agreement between measurements of carbonaceous particles measured as EC from filters and as eBC with high time resolution, especially for the observers and post-fire workers. Ultrafine particle exposure measured as LDSA was two times higher for observers compared to the post-fire workers. The urinary levels of PAH metabolites were generally higher in firefighters and observers compared to post-fire workers. Investigation of PAH contamination on firefighters' PPE revealed high PAH contamination on surfaces with frequent skin contact both before and after cleaning. Exposure to smoke can be assessed with several different exposure markers. For workers residing unprotected around fire scenes, there can be high peak exposures depending on their behavior concerning the smoke plume. Several workers had high urinary PAH metabolite concentrations even though they were exposed to low air concentrations of PAHs, indicating skin absorption of PAH as a plausible exposure route.

火灾现场及周边工人接触空气污染物的特征。
消防员在灭火过程中可能会接触到多种空气污染物。研究的总体目标是确定几组救火人员的烟雾职业暴露特征,具体目标是确定暴露标记之间的相关性,并从生物学角度评估他们尿液中多环芳烃(PAHs)的系统暴露情况。在消防演习期间,对消防员、观察员和火场后工作人员进行了等效黑碳 (eBC)、元素碳 (EC)、有机碳 (OC)、二氧化氮 (NO2)、多环芳烃 (PAHs)、肺沉积表面积 (LDSA) 和超细粒子数量浓度 (PNC) 的个人暴露测量。在接触前和接触后收集尿液样本,并对多环芳烃代谢物进行分析。通过对特定表面(设备、个人防护设备 (PPE) 和车辆)进行擦拭取样,调查了皮肤接触 PAH 的其他途径。在没有个人防护设备的工人中,观察员的暴露量通常高于火灾后工人。观察员和火场后工人的职业烟雾暴露量(如以 EC 测量)分别为 7.3 µg m-3 和 1.9 µg m-3。用过滤器测量的碳质颗粒(EC)与用高时间分辨率测量的碳质颗粒(eBC)之间的测量结果非常一致,尤其是对观察者和火灾后工人而言。以 LDSA 测量的超细粒子暴露量,观察员是火后工人的两倍。与火后工人相比,消防员和观察员尿液中的多环芳烃代谢物水平普遍较高。对消防员个人防护设备上 PAH 污染情况的调查显示,在清洁前后,与皮肤频繁接触的表面上 PAH 污染较高。烟雾暴露可通过几种不同的暴露标记进行评估。对于居住在火灾现场周围未采取保护措施的工人来说,根据他们在烟羽中的行为,可能会出现较高的峰值暴露量。几名工人的尿液中多环芳烃代谢物浓度很高,尽管他们暴露在空气中的多环芳烃浓度很低,这表明皮肤吸收多环芳烃是一种合理的暴露途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Occupational and Environmental Hygiene
Journal of Occupational and Environmental Hygiene 环境科学-公共卫生、环境卫生与职业卫生
CiteScore
3.30
自引率
10.00%
发文量
81
审稿时长
12-24 weeks
期刊介绍: The Journal of Occupational and Environmental Hygiene ( JOEH ) is a joint publication of the American Industrial Hygiene Association (AIHA®) and ACGIH®. The JOEH is a peer-reviewed journal devoted to enhancing the knowledge and practice of occupational and environmental hygiene and safety by widely disseminating research articles and applied studies of the highest quality. The JOEH provides a written medium for the communication of ideas, methods, processes, and research in core and emerging areas of occupational and environmental hygiene. Core domains include, but are not limited to: exposure assessment, control strategies, ergonomics, and risk analysis. Emerging domains include, but are not limited to: sensor technology, emergency preparedness and response, changing workforce, and management and analysis of "big" data.
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