Airflow resistance and bio-filtering performance of carbon nanotube filters and current facepiece respirators

This study aimed to study airflow resistance of carbon nanotube (CNT)-based filtration material and compare its bioaerosol filtering performances with commercially available facepiece respirators. Firstly, we developed a manikin-based system to evaluate the filtering performances of six respiratory masks for biological aerosol particles using an Ultraviolet Aerodynamic Particle Sizer (UV-APS). Secondly, CNT filters with a base filter with a pore size of 10 mu m were prepared using single-walled carbon nanotube (SWNT) loadings of 0.05, 0.1 and 0.2 mg/cm(2). In addition, mask filter membranes were also made by manually cutting the materials of the tested respiratory masks, and their filtration efficiencies and pressure drops were measured and compared with those of CNT-based filters. Results indicated that most of the studied respirator masks achieved a practical protection efficiency of > 90%, while N95 types obtained more than 99% absolute protection efficiency under fully sealed conditions. Increasing CNT loading was shown to increase the quality factor (QF) for the CNT filter given all the sizes considered. For the loading of 0.2 mg/cm2, CNT filters achieved 87% filtration efficiency against indoor viable bioaerosols and 70% for outdoor aerosol particles; and its QF was significantly higher than those of base filter, activated carbon and surgical mask filters. Different from other mask filters, CNT filters were observed to have higher biological aerosol particle filtration efficiencies than the total aerosol particles. Future work in improving air permeability of CNT filter and CNT distribution on filter support would lead to next generation respiratory mask. (C) 2014 Elsevier Ltd. All rights reserved.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000347660800006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Engineering, ChemicalEngineering, MechanicalEnvironmental SciencesMeteorology & Atmospheric SciencesSCI(E)EI4ARTICLEyao@pku.edu.cn61-717