Respirator Performance Against Nanoparticles Under Simulated Workplace Activities (Dataset)
Dataset
Public Domain
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2019/01/22
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Description:Filtering facepiece respirators (FFRs) and elastomeric half-mask respirators (EHRs) are commonly used by workers for protection against potentially hazardous particles, including engineered nanoparticles (i.e., particles measuring less than 100 nanometers (nm). The purpose of this study was to evaluate the performance of these types of respirators against 10-400 nm particles using human subjects exposed to NaCl aerosols under simulated workplace activities. Simulated workplace protection factors (SWPFs) were measured for eight combinations of respirator models (2 N95 FFRs, 2 P100 FFRs, 2 N95 EHRs, and 2 P100 EHRs) worn by 25 healthy test subjects (13 females and 12 males) with varying face sizes. Before beginning a SWPF test for a given respirator model, each subject had to pass a quantitative fit test. Each SWPF test was performed using a protocol of six exercises for three minutes each: (i) normal breathing, (ii) deep breathing, (iii) moving head side to side, (iv) moving head up and down, (v) bending at the waist, and (vi) a simulated laboratory-vessel cleaning motion. Two scanning mobility particle sizers were used simultaneously to measure the upstream (outside the respirator) and downstream (inside the respirator) test aerosol; SWPF was then calculated as a ratio of the upstream and downstream particle concentrations. In general, geometric mean SWPF trend holds true for nanoparticles (10-100 nm), larger size particles (100-400 nm), and the 'all size' range (10-400 nm). All respirators provided better or similar performance levels for 10-100 nm particles as compared to larger 100-400 nm particles. This study found that class P100 respirators provided higher SWPFs compared to class N95 respirators (P < 0.05) for both FFR and HER types. All respirators provided expected performance (i.e. fifth percentile SWPF > 10) against all particle size ranges tested. Download Data: The data for this study is available in CVS and XLS formats. Data Collection Methods: This data was collected using a human subject model. Twenty-five healthy subjects with varying face sizes were used. The panel consisted of 13 females and 12 males ranging from 19 to 65 years of age. The PortaCount Fit Factor was calculated for each respirator on each subject prior to SWPF testing using a particle generator, a PortaCount Plus instrument, and the standard fit test method. The PortaCount plus instrument measured the ratio of upstream and downstream concentrations during each exercise in the fit test regime, and then calculated the harmonic mean of these ratios. This harmonic mean is the reported value. For the SWPF testing, subjects performed a regime of six exercises for three minutes each, while wearing each respirator type/model in a sodium chloride aerosol-filled chamber. Each subject tested each respirator type three times. Scanning mobility particle sizers (SMPS) measured the concentration and size distribution of particles upstream and downstream, simultaneously. The SWPF for each exercise was calculated as a ratio of the upstream and downstream particle concentrations and is displayed in the data. More detailed data collection methods and materials can be found in Vo et al. (2015). [Description provided by NIOSH]
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NIOSHTIC Number:nn:20054381
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Citation:Pittsburgh, PA: U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Research Dataset RD-1009-2019-0, 2019 Jan; :dataset
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Contact Point Address:Kevin Strickland, NIOSH, National Personal Protective Technology Laboratory, Research Branch, 626 Cochrans Mill Road, Pittsburgh, PA, 15236-0070. Telephone: (412) 386-6111
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Email:nwc4@cdc.gov
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Federal Fiscal Year:2019
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Peer Reviewed:False
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Source Full Name:Respirator performance against nanoparticles under simulated workplace activities
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Main Document Checksum:urn:sha-512:76a7117855c49637c99beba70a0bbf2a4fefde696f9cac2dde066678325486f645a20d7bc3b8f5d63d05fb0d2da51eff65782692c9394249df9a6820bb92ee17
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