Abstract:
In this thesis I present an analytical optimization of the Synchrotron Radiation X-Ray Fluorescence (SR-XRF) technique for applications in unmanned aircraft aerosol studies. In environmental and atmospheric science, there is a pressing need for aerosol measurements at various altitudes in the atmosphere and spanning large regions. This need is currently either ignored, or met to a limited degree by studies that employ manned aircraft. There is, however, a great deal of opportunity to improve and expand on these studies using the emerging technology of unmanned aircraft systems. A newly developed aerosol sampler makes this opportunity a near-reality by its ability to collect aerosol samples in-situ from unmanned aircraft platforms. The challenge lies in analyzing these samples for elemental composition. In airborne aerosol studies, the ability to resolve where a sample was collected both spatially and temporally is limited by the sensitivity of the analysis technique. In aircraft-based aerosol collection, the length of the aerosol sample spot corresponds to distance. Thus the spatial resolution of an airborne study is limited by the amount of mass that must be collected for analysis. The SR-XRF optimizations outlined in this thesis decrease the amount of sample mass required for detectable elemental concentrations, allowing aerosol samples to be analyzed in smaller areas corresponding to smaller time steps. Since, in a flight path, time steps are directly correlated with distance, analysis of smaller time steps results in the ability to measure aerosols at higher spatial resolution. Four SR-XRF analysis configurations were experimentally tested: monochromatic beam, white beam, filtered white beam, and filtered white beam-filtered detector to determine which configuration gave the highest elemental sensitivity and selectivity. Of these tested methods, the straight polychromatic white beam configuration resulted in the best sensitivity for elements across a large range of x-ray energies for small amounts of mass collected on thin film substrates. The research in this thesis provides researchers with an optimized method for non-destructively analyzing a wide variety of environmental samples with high elemental sensitivity and selectivity. This research also has important implications for the ability to perform in-situ aerosol studies with unmanned aircraft on a systematic basis.
