AAAR 33rd Annual Conference
October 20 - October 24, 2014
Rosen Shingle Creek
Orlando, Florida, USA
Abstract View
Evaluation of Granular Bed with Glass Beads for Use in a Nanoparticle Respiratory Deposition (NRD) Sampler
JAE HONG PARK, Levi Mines, Imali Mudunkotuwa, T. Renee Anthony, Vicki Grassian, Thomas Peters, University of Iowa
Abstract Number: 75 Working Group: Instrumentation and Methods
Abstract The objective of this work was to broaden the applicability of an innovative nanoparticle respiratory deposition (NRD) sampler by identifying sampling media alternatives to the eight nylon mesh screens used, in the original NRD sampler, to collect and quantify multiple metals in nanoparticle aerosol samples. The new sampling media consisted of a granular bed with three layers of glass beads held in place by two coarse mesh screens (mesh/1-mm beads/200-µm beads/1-mm beads/mesh). The solidity of the total glass beads layers was 0.740. The collection efficiency by size was measured with a scanning mobility particle sizer in triplicate for metal particles generated from a spark discharge system. Measured collection efficiencies were compared to those calculated from theory. The number median diameter and total number concentration of test particles from the spark discharge system were 100 nm and 1.5×10$^5 particles/cm$^3, respectively. The particle collection efficiency of the granular bed was 80(±2)% at 30 nm, 45(±2)% at 100 nm, and 34(±7)% at 300 nm, yielding a 50% cutoff diameter of approximately 85 nm. The shape of the measured collection efficiency curve was similar to that estimated from theory, although measured collection efficiencies were considerably higher than theory (e.g., the 50% cutoff diameter from theory was 35 nm). These results show that a granular bed can be used as a diffusion media in the NRD sampler. Compared to the use of screens, this granular bed approach opens up a wide array of different materials that can be used for sampling media in the NRD sampler and more broadly, use in other diffusion-based samplers.
[Acknowledgment: This work was supported by National Institute for Occupational Safety and Health (1 R01 OH010238).]