Structural characterization of water-soluble atmospheric organic matter by ultrahigh-resolution mass spectrometry

Isolated water-soluble analytes extracted from fog water collected during a radiation fog event near Fresno, CA were analyzed using collision induced dissociation and ultrahigh-resolution mass spectrometry. Tandem mass analysis was performed on scan ranges between 100-400 u to characterize the structures of nitrogen and/or sulfur containing species. CHNO, CHOS, and CHNOS compounds were targeted specifically because of the high number of oxygen atoms contained in their molecular formulas. The presence of 22 neutral losses corresponding to fragment ions was evaluated for each of the 1308 precursors. Priority neutral losses represent specific polar functional groups (H2O, CO2, CH3OH, HNO3, SO3, etc., and several combinations of these). Additional neutral losses represent non-specific functional groups (CO, CH2O, C3H8, etc.) Five distinct monoterpene derived organonitrates, organosulfates, and nitroxy-organosulfates were observed in this study, including C10H16O7S, C10H17NO7S, C10H17 NO8S, C10H17NO9S, and C10H17NO10S. Nitrophenols and linear alkyl benzene sulfonates were present in high abundance. Liquid chromatography/mass spectrometery methodology was developed to isolate and quantify nitrophenols based on their fragmentation behavior.

In-situ measurement and characterization of cloud particles using digital in-line holography

Satellite measurement validations, climate models, atmospheric radiative transfer models and cloud models, all depend on accurate measurements of cloud particle size distributions, number densities, spatial distributions, and other parameters relevant to cloud microphysical processes. And many airborne instruments designed to measure size distributions and concentrations of cloud particles have large uncertainties in measuring number densities and size distributions of small ice crystals. HOLODEC (Holographic Detector for Clouds) is a new instrument that does not have many of these uncertainties and makes possible measurements that other probes have never made. The advantages of HOLODEC are inherent to the holographic method. In this dissertation, I describe HOLODEC, its in-situ measurements of cloud particles, and the results of its test flights. I present a hologram reconstruction algorithm that has a sample spacing that does not vary with reconstruction distance. This reconstruction algorithm accurately reconstructs the field to all distances inside a typical holographic measurement volume as proven by comparison with analytical solutions to the Huygens-Fresnel diffraction integral. It is fast to compute, and has diffraction limited resolution. Further, described herein is an algorithm that can find the position along the optical axis of small particles as well as large complex-shaped particles. I explain an implementation of these algorithms that is an efficient, robust, automated program that allows us to process holograms on a computer cluster in a reasonable time. I show size distributions and number densities of cloud particles, and show that they are within the uncertainty of independent measurements made with another measurement method. The feasibility of another cloud particle instrument that has advantages over new standard instruments is proven. These advantages include a unique ability to detect shattered particles using three-dimensional positions, and a sample volume size that does not vary with particle size or airspeed. It also is able to yield two-dimensional particle profiles using the same measurements.

Digital processing and data compilation approach for using remotely sensed imagery to identify geological lineaments in hard-rock terrains : an application for groundwater explorations in Nicaragua

Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.

EVOLUTION OF SELECTED ISOPRENE OXIDATION PRODUCTS IN DARK AQUEOUS AMMONIUM SULFATE

The aqueous phase processing of glyoxylic acid, pyruvic acid, oxalic acid and methylglyoxal was studied simulating dark and radical free atmospheric aqueous aerosol. A novel observation of the cleavage of a carbon-carbon bond in pyruvic acid and glyoxylic acid leading to their decarboxylation was made in the presence of ammonium salts but no decarboxylation was observed from oxalic acid. The empirical rate constants for decarboxylation were determined. The structure of the acid, ionic environment of solution and concentration of species found to affect the decarboxylation process. A tentative set of reaction mechanisms was proposed involving nucleophilic attack by ammonia on the carbonyl carbon leading to fragmentation of the carbon-carbon bond between the carbonyl and carboxyl carbons. Whereas, the formation of high molecular weight organic species was observed in the case of methylglyoxal. The elemental compositions of the species were determined. It was concluded that, additional pathways that are not currently known likely contribute to aqueous phase processing leading to high molecular weight organic species. Under similar conditions in atmospheric aerosol, the aqueous phase processing will markedly impact the physicochemical properties of aerosol.

EXTRACTION OF PICTORIAL ENERGY INFORMATION FROM CAMPUS UNMETERED BUILDINGS USING IMAGE PROCESSING TECHNIQUES

In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.