Date of Award

1-1-2015

Document Type

Dissertation

Degree Name

Ph.D.

Organizational Unit

Chemistry and Biochemistry

First Advisor

Brian J. Majestic, Ph.D.

Second Advisor

David Patterson

Third Advisor

Bryan Cowen

Fourth Advisor

Alex Huffman

Fifth Advisor

Keith Miller

Keywords

Atmospheric particles, Particle pulse, Nanotechnology-enabled consumer spray

Abstract

The work presented herein details the measurement of particle-bound metals in environmental samples with specific interests in iron (Fe) in atmospheric particulate matter. Metals were measured in ambient PM2.5 to study the effects and contributions of a light rail system on the concentrations of metals in atmospheric particles. Particulate matter samples were collected on board trains, near the tracks, and at an urban background location in Denver, CO. Metals were found to be enriched in particles collected on board the trains more so than at the other locations. Fe speciation was also measured in the soluble fraction of the sample and the results showed the contribution of anthropogenic iron to the collected particles.

Lab-created simulated marine particles were used to study the different variables affecting Fe solubility in atmospheric particulate matter during atmospheric transport. The effects of particle size, mineralogy, exposure to sulfur dioxide, and relative humidity were investigated. Particle size and mineralogy were shown to have the largest effect on iron solubility with particles with smaller aerodynamic diameters containing more soluble Fe. Sulfur was incorporated onto the particles however XANES measurements showed no effect on Fe chemistry or speciation.

Fe, Au, and Ag nanoparticles in aquatic matrices were also investigated as part of a two-fold spICPMS experiment. The first study focused on observing formation of Fe nanoparticles in seawater. This led to the development of a new way to introduce a sample to the instrument as well as the second study; identifying a particle pulse in the presence of dissolved analyte. Using well characterized Au particles, a mathematical method using the mode and standard deviation of the dataset was developed and successfully used to distinguish a particle signal pulse from that of the background. This method was validated using a nanotechnology-enabled consumer spray containing both dissolved and particle Ag. This method allows for more universal use of spICPMS.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Benton T. Cartledge

Provenance

Received from ProQuest

File Format

application/pdf

Language

en

File Size

107 p.

Discipline

Chemistry, Atmospheric Chemistry

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