The overall goals of this doctoral dissertation are to provide knowledge of workers' exposure to nanomaterials and to assist in the development of standard methods to measure personal exposure to nanomaterials in workplace environments.
To achieve the first goal, a field study investigated airborne particles generated from the weighing of bulk carbon nanotubes (CNTs) and the manual sanding of epoxy test samples reinforced with CNTs. This study also evaluated the effectiveness of three local exhaust ventilation (LEV) conditions (no LEV, custom fume hood and biosafety cabinet) for control of exposure to particles generated during sanding of CNT-epoxy nanocomposites. Particle number and respirable mass concentrations were measured with direct-read instruments, and particle morphology was determined by electron microscopy. Sanding of CNT-epoxy nanocomposites released respirable size airborne particles with protruding CNTs very different in morphology from bulk CNTs that tended to remain in clusters (>1µm). Respirable mass concentrations in the operator's breathing zone were significantly greater when sanding took place in the custom hood (p <0.0001) compared to the other LEV conditions. This study found that workers' exposure was to particles containing protruding CNTs rather than to bulk CNT particles. Particular attention should be placed in the design and selection of hoods to minimize exposure.
Two laboratory studies were conducted to realize the second goal. Collection efficiency of submicrometer particles was evaluated for nylon mesh screens with three pore sizes (60, 100 and 180 µm) at three flow rates (2.5, 4, and 6 Lpm). Single-fiber efficiency of nylon mesh screens was then calculated and compared to a theoretical estimation expression. The effects of particle morphology on collection efficiency were also experimentally measured. The collection efficiency of the screens was found to vary by less than 4% regardless of particle morphology. Single-fiber efficiency of the screens calculated from experimental data was in good agreement with that estimated from theory for particles between 40 and 150 nm but deviated from theory for particles outside of this range. New coefficients for the single-fiber efficiency model were identified that minimized the sum of square error (SSE) between the experimental values and those estimated with the model. Compared to the original theory, the SSE calculated using the modified theory was at least threefold lower for all screens and flow rates. Since nylon fibers produce no significant spectral interference when ashed for spectrometric examination, the ability to accurately estimate collection efficiency of submicrometer particles makes nylon mesh screens an attractive collection substrate for nanoparticles.
In the third study, laboratory experiments were conducted to develop a novel nanoparticle respiratory deposition (NRD) sampler that selectively collects nanoparticles in a worker's breathing zone apart from larger particles. The NRD sampler consists of a respirable cyclone fitted with an impactor and a diffusion stage containing eight nylon- mesh screens. A sampling criterion for nano-particulate matter (NPM) was developed and set as the target for the collection efficiency of the NRD sampler. The sampler operates at 2.5 Lpm and fits on a worker's lapel. The cut-off diameter of the impactor was experimentally measured to be 300 nm with a sharpness of 1.53. Loading at typical workplace levels was found to have no significant effect (2-way ANOVA, p=0.257) on the performance of the impactor. The effective deposition of particles onto the diffusion stage was found to match the NPM criterion, showing that a sample collected with the NRD sampler represents the concentration of nanoparticles deposited in the human respiratory system.
| Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-2320 |
| Date | 01 May 2011 |
| Creators | Cena, Lorenzo |
| Contributors | Peters, Thomas M. |
| Publisher | University of Iowa |
| Source Sets | University of Iowa |
| Language | English |
| Detected Language | English |
| Type | dissertation |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | Copyright 2011 Lorenzo Cena |
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