Efficiency of five chemical protective clothing materials against nano and submicron aerosols when submitted to mechanical deformations

Type de document

Études primaires

Année de publication

2016

Langue

Anglais

Titre de la revue

Journal of Occupational and Environmental Hygiene

Première page

425

Dernière page

433

Résumé

Due to their potential toxicity, the use of nanoparticles in the workplace is a growing concern. Some studies indicate that nanoparticles can penetrate the skin and lead to adverse health effects. Since chemical protective clothing is the last barrier to protect the skin, this study aims to better understand nanoparticle penetration behaviour in dermal protective clothing under mechanical deformation. For this purpose, five of the most common types of fabrics used in protective clothing, one woven and four nonwoven, were chosen and submitted to different simulated exposure conditions. They were tested against polydispersed NaCl aerosols having an electrical-mobility diameter between 14 and 400 nm. A bench-scale exposure setup and a sampling protocol was developed to measure the level of penetration of the aerosols through the material samples of disposable coveralls and lab coat, while subjecting them to mechanical deformations to simulate the conditions of usage in the workplace. Particle size distribution of the aerosol was determined upstream and downstream using a scanning mobility particle sizer (SMPS). The measured efficiencies demonstrated that the performances of nonwoven materials were similar. Three nonwovens had efficiencies above 99%, while the woven fabric was by far, the least effective. Moreover, the results established that mechanical deformations, as simulated for this study, did not have a significant effect on the fabrics' efficiencies.

Mots-clés

Vêtement de protection, Protective clothing, Aérosol, Aerosol, Nanoparticule, Nanoparticle, Essai du matériel, Equipment testing

Numéro de projet IRSST

n/a

Ce document n'est pas disponible pour le moment.

Partager

COinS