Matching Items (161)
Polycyclic aromatic hydrocarbon (PAH) redistribution in extreme dust storms and processing in clouds
Description
Dust storms known as 'haboobs' occur in the City of Tempe, AZ during the North American monsoon season. A haboob classification method based on meteorological and air quality measurements is described. There were from 3 to 20 haboob events per year over the period from 2005 to 2014. The calculated annual TSP (total suspended particulate) dry deposition during haboobs is estimated to contribute 74% of the total particulate mass deposited in Tempe, AZ.
Dry deposition is compared with the aqueous chemistry of Tempe Town Lake. Water management and other factors may have a stronger impact on Tempe Town Lake chemistry than haboob dry-deposition. Haboobs alter the Polycyclic Aromatic Hydrocarbon (PAH) concentrations and distributions in Tempe, AZ. PAH isomer ratios suggest PM2.5 (particulate matter with aerodynamic diameters less than or equal to 2.5 μm) sources consistent with approximate thunderstorm outflow paths.
The importance of the atmospheric aqueous phase, fogs and clouds, for the processing and removal of PAHs is not well known. A multiphase model was developed to determine the fate and lifetime of PAHs in fogs and clouds. The model employed literature values that describe the partitioning between three phases (aqueous, liquid organic, and gas), in situ PAH measurements, and experimental and estimated (photo)oxidation rates. At 25 °C, PAHs with two, three and four rings were predicted to be primarily gas phase (fraction in the gas phase xg > 90 %) while five- and six-ring PAHs partitioned significantly into droplets (xg < 60 %) with aqueous phase fractions of 1 to 6 % and liquid organic phase fractions of 31 to 91 %. The predicted atmospheric lifetimes of PAHs in the presence of fog or cloud droplets (< 5 hours) were significantly shorter than literature predictions of PAH wet and dry deposition lifetimes (1 to 14 days and 5 to 15 months respectively) and shorter than or equal to predicted PAH gas phase / particle phase atmospheric lifetimes (1 to 300 hours). The aqueous phase cannot be neglected as a PAH sink due to the large aqueous volume (vs. organic volume) and the relatively fast aqueous reactions.
Dry deposition is compared with the aqueous chemistry of Tempe Town Lake. Water management and other factors may have a stronger impact on Tempe Town Lake chemistry than haboob dry-deposition. Haboobs alter the Polycyclic Aromatic Hydrocarbon (PAH) concentrations and distributions in Tempe, AZ. PAH isomer ratios suggest PM2.5 (particulate matter with aerodynamic diameters less than or equal to 2.5 μm) sources consistent with approximate thunderstorm outflow paths.
The importance of the atmospheric aqueous phase, fogs and clouds, for the processing and removal of PAHs is not well known. A multiphase model was developed to determine the fate and lifetime of PAHs in fogs and clouds. The model employed literature values that describe the partitioning between three phases (aqueous, liquid organic, and gas), in situ PAH measurements, and experimental and estimated (photo)oxidation rates. At 25 °C, PAHs with two, three and four rings were predicted to be primarily gas phase (fraction in the gas phase xg > 90 %) while five- and six-ring PAHs partitioned significantly into droplets (xg < 60 %) with aqueous phase fractions of 1 to 6 % and liquid organic phase fractions of 31 to 91 %. The predicted atmospheric lifetimes of PAHs in the presence of fog or cloud droplets (< 5 hours) were significantly shorter than literature predictions of PAH wet and dry deposition lifetimes (1 to 14 days and 5 to 15 months respectively) and shorter than or equal to predicted PAH gas phase / particle phase atmospheric lifetimes (1 to 300 hours). The aqueous phase cannot be neglected as a PAH sink due to the large aqueous volume (vs. organic volume) and the relatively fast aqueous reactions.
ContributorsEagar, Jershon (Author) / Herckes, Pierre (Thesis advisor) / Hayes, Mark (Committee member) / Shock, Everett (Committee member) / Arizona State University (Publisher)
Created2016
Description
N-Nitrosodimethylamine (NDMA), a probable human carcinogen, has been found in clouds and fogs at concentration up to 500 ng/L and in drinking water as disinfection by-product. NDMA exposure to the general public is not well understood because of knowledge gaps in terms of occurrence, formation and fate both in air and water. The goal of this dissertation was to contribute to closing these knowledge gaps on potential human NDMA exposure through contributions to atmospheric measurements and fate as well as aqueous formation processes.
Novel, sensitive methods of measuring NDMA in air were developed based on Solid Phase Extraction (SPE) and Solid Phase Microextraction (SPME) coupled to Gas Chromatography-Mass Spectrometry (GC-MS). The two measuring techniques were evaluated in laboratory experiments. SPE-GC-MS was applicable in ambient air sampling and NDMA in ambient air was found in the 0.1-13.0 ng/m3 range.
NDMA photolysis, the main degradation atmospheric pathway, was studied in the atmospheric aqueous phase. Water soluble organic carbon (WSOC) was found to have more impact than inorganic species on NDMA photolysis by competing with NDMA for photons and therefore could substantially increase the NDMA lifetime in the atmosphere. The optical properties of atmospheric WSOC were investigated in aerosol, fog and cloud samples and showed WSOC from atmospheric aerosols has a higher mass absorption efficiency (MAE) than organic matter in fog and cloud water, resulting from a different composition, especially in regards of volatile species, that are not very absorbing but abundant in fogs and clouds.
NDMA formation kinetics during chloramination were studied in aqueous samples including wastewater, surface water and ground water, at two monochloramine concentrations. A simple second order NDMA formation model was developed using measured NDMA and monochloramine concentrations at select reaction times. The model fitted the NDMA formation well (R2 >0.88) in all water matrices. The proposed model was then optimized and applied to fit the data of NDMA formation from natural organic matter (NOM) and model precursors in previously studies. By determining the rate constants, the model was able to describe the effect of water conditions such as DOC and pH on NDMA formation.
Novel, sensitive methods of measuring NDMA in air were developed based on Solid Phase Extraction (SPE) and Solid Phase Microextraction (SPME) coupled to Gas Chromatography-Mass Spectrometry (GC-MS). The two measuring techniques were evaluated in laboratory experiments. SPE-GC-MS was applicable in ambient air sampling and NDMA in ambient air was found in the 0.1-13.0 ng/m3 range.
NDMA photolysis, the main degradation atmospheric pathway, was studied in the atmospheric aqueous phase. Water soluble organic carbon (WSOC) was found to have more impact than inorganic species on NDMA photolysis by competing with NDMA for photons and therefore could substantially increase the NDMA lifetime in the atmosphere. The optical properties of atmospheric WSOC were investigated in aerosol, fog and cloud samples and showed WSOC from atmospheric aerosols has a higher mass absorption efficiency (MAE) than organic matter in fog and cloud water, resulting from a different composition, especially in regards of volatile species, that are not very absorbing but abundant in fogs and clouds.
NDMA formation kinetics during chloramination were studied in aqueous samples including wastewater, surface water and ground water, at two monochloramine concentrations. A simple second order NDMA formation model was developed using measured NDMA and monochloramine concentrations at select reaction times. The model fitted the NDMA formation well (R2 >0.88) in all water matrices. The proposed model was then optimized and applied to fit the data of NDMA formation from natural organic matter (NOM) and model precursors in previously studies. By determining the rate constants, the model was able to describe the effect of water conditions such as DOC and pH on NDMA formation.
ContributorsZhang, Jinwei (Author) / Herckes, Pierre (Thesis advisor) / Westerhoff, Paul (Thesis advisor) / Fraser, Matthew (Committee member) / Shock, Everett (Committee member) / Arizona State University (Publisher)
Created2016
Description
This dissertation is presented in two sections. First, I explore two methods of using stable isotope analysis to trace environmental and biogeochemical processes. Second, I present two related studies investigating student understanding of the biogeochemical concepts that underlie part one. Fe and Hg are each biogeochemically important elements in their own way. Fe is a critical nutrient for phytoplankton, while Hg is detrimental to nearly all forms of life. Fe is often a limiting factor in marine phytoplankton growth. The largest source, by mass, of Fe to the open ocean is windblown mineral dust, but other more soluble sources are more bioavailable. To look for evidence of these non-soil dust sources of Fe to the open ocean, I measured the isotopic composition of aerosol samples collected on Bermuda. I found clear evidence in the fine size fraction of a non-soil dust Fe source, which I conclude is most likely from biomass burning. Widespread adoption of compact fluorescent lamps (CFL) has increased their importance as a source of environmental Hg. Isotope analysis would be a useful tool in quantifying this impact if the isotopic composition of Hg from CFL were known. My measurements show that CFL-Hg is isotopically fractionated, in a unique pattern, during normal operation. This fractionation is large and has a distinctive, mass-independent signature, such that CFL Hg can be uniquely identified from other sources. Misconceptions research in geology has been a very active area of research, but student thinking regarding the related field of biogeochemistry has not yet been studied in detail. From interviews with 40 undergraduates, I identified over 150 specific misconceptions. I also designed a multiple-choice survey (concept inventory) to measure understanding of these same biogeochemistry concepts. I present statistical evidence, based on the Rasch model, for the reliability and validity of this instrument. This instrument will allow teachers and researchers to easily quantify learning outcomes in biogeochemistry and will complement existing concept inventories in geology, chemistry, and biology.
ContributorsMead, Chris (Author) / Anbar, Ariel (Thesis advisor) / Semken, Steven (Committee member) / Shock, Everett (Committee member) / Herckes, Pierre (Committee member) / Hartnett, Hilairy (Committee member) / Arizona State University (Publisher)
Created2014
Description
Extraordinary medical advances have led to significant reductions in the burden of infectious diseases in humans. However, infectious diseases still account for more than 13 million annual deaths. This large burden is partly due to some pathogens having found suitable conditions to emerge and spread in denser and more connected host populations, and others having evolved to escape the pressures imposed by the rampant use of antimicrobials. It is then critical to improve our understanding of how diseases spread in these modern landscapes, characterized by new host population structures and socio-economic environments, as well as containment measures such as the deployment of drugs. Thus, the motivation of this dissertation is two-fold. First, we study, using both data-driven and modeling approaches, the the spread of infectious diseases in urban areas. As a case study, we use confirmed-cases data on sexually transmitted diseases (STDs) in the United States to assess the conduciveness of population size of urban areas and their socio-economic characteristics as predictors of STD incidence. We find that the scaling of STD incidence in cities is superlinear, and that the percent of African-Americans residing in cities largely determines these statistical patterns. Since disparities in access to health care are often exacerbated in urban areas, within this project we also develop two modeling frameworks to study the effect of health care disparities on epidemic outcomes. Discrepant results between the two approaches indicate that knowledge of the shape of the recovery period distribution, not just its mean and variance, is key for assessing the epidemiological impact of inequalities. The second project proposes to study, from a modeling perspective, the spread of drug resistance in human populations featuring vital dynamics, stochasticity and contact structure. We derive effective treatment regimes that minimize both the overall disease burden and the spread of resistance. Additionally, targeted treatment in structured host populations may lead to higher levels of drug resistance, and if drug-resistant strains are compensated, they can spread widely even when the wild-type strain is below its epidemic threshold.
ContributorsPatterson-Lomba, Oscar (Author) / Castillo-Chavez, Carlos (Thesis advisor) / Towers, Sherry (Thesis advisor) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2014
Description
In enzyme induced carbonate precipitation (EICP), calcium carbonate (CaCO3) precipitation is catalyzed by plant-derived urease enzyme. In EICP, urea hydrolyzes into ammonia and inorganic carbon, altering geochemical conditions in a manner that promotes carbonate mineral precipitation. The calcium source in this process comes from calcium chloride (CaCl2) in aqueous solution. Research work conducted for this dissertation has demonstrated that EICP can be employed for a variety of geotechnical purposes, including mass soil stabilization, columnar soil stabilization, and stabilization of erodible surficial soils. The research presented herein also shows that the optimal ratio of urea to CaCl2 at ionic strengths of less than 1 molar is approximately 1.75:1. EICP solutions of very high initial ionic strength (i.e. 6 M) as well as high urea concentrations (> 2 M) resulted in enzyme precipitation (salting-out) which hindered carbonate precipitation. In addition, the production of NH4+ may also result in enzyme precipitation. However, enzyme precipitation appeared to be reversible to some extent. Mass soil stabilization was demonstrated via percolation and mix-and-compact methods using coarse silica sand (Ottawa 20-30) and medium-fine silica sand (F-60) to produce cemented soil specimens whose strength improvement correlated with CaCO3 content, independent of the method employed to prepare the specimen. Columnar stabilization, i.e. creating columns of soil cemented by carbonate precipitation, using Ottawa 20-30, F-60, and native AZ soil was demonstrated at several scales beginning with small columns (102-mm diameter) and culminating in a 1-m3 soil-filled box. Wind tunnel tests demonstrated that surficial soil stabilization equivalent to that provided by thoroughly wetting the soil can be achieved through a topically-applied solution of CaCl2, urea, and the urease enzyme. The topically applied solution was shown to form an erosion-resistant CaCO3 crust on fine sand and silty soils. Cementation of erodible surficial soils was also achieved via EICP by including a biodegradable hydrogel in the stabilization solution. A dilute hydrogel solution extended the time frame over which the precipitation reaction could occur and provided improved spatial control of the EICP solution.
ContributorsHamdan, Nasser M (Author) / Kavazanjian Jr., Edward (Thesis advisor) / Rittmann, Bruce (Thesis advisor) / Shock, Everett (Committee member) / Arizona State University (Publisher)
Created2015
Description
The taxonomic and metabolic profile of the microbial community inhabiting a natural system is largely determined by the physical and geochemical properties of the system. However, the influences of parameters beyond temperature, pH and salinity have been poorly analyzed with few studies incorporating the comprehensive suite of physical and geochemical measurements required to fully investigate the complex interactions known to exist between biology and the environment. Further, the techniques used to classify the taxonomic and functional composition of a microbial community are fragmented and unwieldy, resulting in unnecessarily complex and often non-consilient results.
This dissertation integrates environmental metagenomes with extensive geochemical metadata for the development and application of multidimensional biogeochemical metrics. Analysis techniques including a Markov cluster-based evolutionary distance between whole communities, oligonucleotide signature-based taxonomic binning and principal component analysis of geochemical parameters allow for the determination of correlations between microbial community dynamics and environmental parameters. Together, these techniques allow for the taxonomic classification and functional analysis of the evolution of hot spring communities. Further, these techniques provide insight into specific geochemistry-biology interactions which enable targeted analyses of community taxonomic and functional diversity. Finally, analysis of synonymous substitution rates among physically separated microbial communities provides insights into microbial dispersion patterns and the roles of environmental geochemistry and community metabolism on DNA transfer among hot spring communities.
The data presented here confirms temperature and pH as the primary factors shaping the evolutionary trajectories of microbial communities. However, the integration of extensive geochemical metadata reveals new links between geochemical parameters and the distribution and functional diversification of communities. Further, an overall geochemical gradient (from multivariate analyses) between natural systems provides one of the most complete predictions of microbial community functional composition and inter-community DNA transfer rates. Finally, the taxonomic classification and clustering techniques developed within this dissertation will facilitate future genomic and metagenomic studies through enhanced community profiling obtainable via Markov clustering, longer oligonucleotide signatures and insight into PCR primer biases.
This dissertation integrates environmental metagenomes with extensive geochemical metadata for the development and application of multidimensional biogeochemical metrics. Analysis techniques including a Markov cluster-based evolutionary distance between whole communities, oligonucleotide signature-based taxonomic binning and principal component analysis of geochemical parameters allow for the determination of correlations between microbial community dynamics and environmental parameters. Together, these techniques allow for the taxonomic classification and functional analysis of the evolution of hot spring communities. Further, these techniques provide insight into specific geochemistry-biology interactions which enable targeted analyses of community taxonomic and functional diversity. Finally, analysis of synonymous substitution rates among physically separated microbial communities provides insights into microbial dispersion patterns and the roles of environmental geochemistry and community metabolism on DNA transfer among hot spring communities.
The data presented here confirms temperature and pH as the primary factors shaping the evolutionary trajectories of microbial communities. However, the integration of extensive geochemical metadata reveals new links between geochemical parameters and the distribution and functional diversification of communities. Further, an overall geochemical gradient (from multivariate analyses) between natural systems provides one of the most complete predictions of microbial community functional composition and inter-community DNA transfer rates. Finally, the taxonomic classification and clustering techniques developed within this dissertation will facilitate future genomic and metagenomic studies through enhanced community profiling obtainable via Markov clustering, longer oligonucleotide signatures and insight into PCR primer biases.
ContributorsAlsop, Eric Bennie (Author) / Raymond, Jason (Thesis advisor) / Anbar, Ariel (Committee member) / Farmer, Jack (Committee member) / Shock, Everett (Committee member) / Walker, Sarah (Committee member) / Arizona State University (Publisher)
Created2014
Description
Urban scaling analysis has introduced a new scientific paradigm to the study of cities. With it, the notions of size, heterogeneity and structure have taken a leading role. These notions are assumed to be behind the causes for why cities differ from one another, sometimes wildly. However, the mechanisms by which size, heterogeneity and structure shape the general statistical patterns that describe urban economic output are still unclear. Given the rapid rate of urbanization around the globe, we need precise and formal mathematical understandings of these matters. In this context, I perform in this dissertation probabilistic, distributional and computational explorations of (i) how the broadness, or narrowness, of the distribution of individual productivities within cities determines what and how we measure urban systemic output, (ii) how urban scaling may be expressed as a statistical statement when urban metrics display strong stochasticity, (iii) how the processes of aggregation constrain the variability of total urban output, and (iv) how the structure of urban skills diversification within cities induces a multiplicative process in the production of urban output.
ContributorsGómez-Liévano, Andrés (Author) / Lobo, Jose (Thesis advisor) / Muneepeerakul, Rachata (Thesis advisor) / Bettencourt, Luis M. A. (Committee member) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2014
Description
The increased number of novel pathogens that potentially threaten the human population has motivated the development of mathematical and computational modeling approaches for forecasting epidemic impact and understanding key environmental characteristics that influence the spread of diseases. Yet, in the case that substantial uncertainty surrounds the transmission process during a rapidly developing infectious disease outbreak, complex mechanistic models may be too difficult to be calibrated quick enough for policy makers to make informed decisions. Simple phenomenological models that rely on a small number of parameters can provide an initial platform for assessing the epidemic trajectory, estimating the reproduction number and quantifying the disease burden from the early epidemic phase.
Chapter 1 provides background information and motivation for infectious disease forecasting and outlines the rest of the thesis.
In chapter 2, logistic patch models are used to assess and forecast the 2013-2015 West Africa Zaire ebolavirus epidemic. In particular, this chapter is concerned with comparing and contrasting the effects that spatial heterogeneity has on the forecasting performance of the cumulative infected case counts reported during the epidemic.
In chapter 3, two simple phenomenological models inspired from population biology are used to assess the Research and Policy for Infectious Disease Dynamics (RAPIDD) Ebola Challenge; a simulated epidemic that generated 4 infectious disease scenarios. Because of the nature of the synthetically generated data, model predictions are compared to exact epidemiological quantities used in the simulation.
In chapter 4, these models are applied to the 1904 Plague epidemic that occurred in Bombay. This chapter provides evidence that these simple models may be applicable to infectious diseases no matter the disease transmission mechanism.
Chapter 5, uses the patch models from chapter 2 to explore how migration in the 1904 Plague epidemic changes the final epidemic size.
The final chapter is an interdisciplinary project concerning within-host dynamics of cereal yellow dwarf virus-RPV, a plant pathogen from a virus group that infects over 150 grass species. Motivated by environmental nutrient enrichment due to anthropological activities, mathematical models are employed to investigate the relevance of resource competition to pathogen and host dynamics.
Chapter 1 provides background information and motivation for infectious disease forecasting and outlines the rest of the thesis.
In chapter 2, logistic patch models are used to assess and forecast the 2013-2015 West Africa Zaire ebolavirus epidemic. In particular, this chapter is concerned with comparing and contrasting the effects that spatial heterogeneity has on the forecasting performance of the cumulative infected case counts reported during the epidemic.
In chapter 3, two simple phenomenological models inspired from population biology are used to assess the Research and Policy for Infectious Disease Dynamics (RAPIDD) Ebola Challenge; a simulated epidemic that generated 4 infectious disease scenarios. Because of the nature of the synthetically generated data, model predictions are compared to exact epidemiological quantities used in the simulation.
In chapter 4, these models are applied to the 1904 Plague epidemic that occurred in Bombay. This chapter provides evidence that these simple models may be applicable to infectious diseases no matter the disease transmission mechanism.
Chapter 5, uses the patch models from chapter 2 to explore how migration in the 1904 Plague epidemic changes the final epidemic size.
The final chapter is an interdisciplinary project concerning within-host dynamics of cereal yellow dwarf virus-RPV, a plant pathogen from a virus group that infects over 150 grass species. Motivated by environmental nutrient enrichment due to anthropological activities, mathematical models are employed to investigate the relevance of resource competition to pathogen and host dynamics.
ContributorsPell, Bruce (Author) / Kuang, Yang (Thesis advisor) / Chowell-Puente, Gerardo (Committee member) / Nagy, John (Committee member) / Kostelich, Eric (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2016
Description
One goal of geobiochemistry is to follow geochemical energy supplies from the external environment to the inside of microbial cells. This can be accomplished by combining thermodynamic calculations of energy supplies from geochemical processes and energy demands for biochemical processes. Progress towards this goal is summarized here. A critique of all thermodynamic data for biochemical compounds involved in the citric acid cycle (CAC) and the formulation of metabolite properties allows predictions of the energy involved in each step of the cycle as well as the full forward and reverse cycles over wide ranges of temperature and pressure. These results allow evaluation of energy demands at the center of many microbial metabolic systems. Field work, sampling, and lab analyses from two low-temperature systems, a serpentinizing system, and a subglacial setting, provide the data used in these thermodynamic analyses of energy supplies. An extensive literature summary of microbial and molecular data from serpentinizing systems found is used to guide the evaluation and ranking of energy supplies used by chemolithoautotrophic microbes. These results constrain models of the distribution of microbial metabolisms throughout the low-temperature serpentinization systems in the Samail ophiolite in Oman (including locales of primary and subsequent alteration processes). Data collected from Robertson Glacier in Alberta, Canada, together with literature data from Lake Vida in Antarctica and bottom seawater, allowed thermodynamic analyses of low-temperature energy supplies in a glacial system. Results for 1460 inorganic redox reactions are used to fully inventory the geochemical energy sources that support the globally extensive cold biosphere.
ContributorsCanovas, Peter Anthony (Author) / Shock, Everett (Thesis advisor) / Hartnett, Hilairy (Committee member) / Sharp, Thomas (Committee member) / Tyburczy, James (Committee member) / Heimsath, Arjun (Committee member) / Arizona State University (Publisher)
Created2016
Description
The greatest barrier to understanding how life interacts with its environment is the complexity in which biology operates. In this work, I present experimental designs, analysis methods, and visualization techniques to overcome the challenges of deciphering complex biological datasets. First, I examine an iron limitation transcriptome of Synechocystis sp. PCC 6803 using a new methodology. Until now, iron limitation in experiments of Synechocystis sp. PCC 6803 gene expression has been achieved through media chelation. Notably, chelation also reduces the bioavailability of other metals, whereas naturally occurring low iron settings likely result from a lack of iron influx and not as a result of chelation. The overall metabolic trends of previous studies are well-characterized but within those trends is significant variability in single gene expression responses. I compare previous transcriptomics analyses with our protocol that limits the addition of bioavailable iron to growth media to identify consistent gene expression signals resulting from iron limitation. Second, I describe a novel method of improving the reliability of centroid-linkage clustering results. The size and complexity of modern sequencing datasets often prohibit constructing distance matrices, which prevents the use of many common clustering algorithms. Centroid-linkage circumvents the need for a distance matrix, but has the adverse effect of producing input-order dependent results. In this chapter, I describe a method of cluster edge counting across iterated centroid-linkage results and reconstructing aggregate clusters from a ranked edge list without a distance matrix and input-order dependence. Finally, I introduce dendritic heat maps, a new figure type that visualizes heat map responses through expanding and contracting sequence clustering specificities. Heat maps are useful for comparing data across a range of possible states. However, data binning is sensitive to clustering cutoffs which are often arbitrarily introduced by researchers and can substantially change the heat map response of any single data point. With an understanding of how the architectural elements of dendrograms and heat maps affect data visualization, I have integrated their salient features to create a figure type aimed at viewing multiple levels of clustering cutoffs, allowing researchers to better understand the effects of environment on metabolism or phylogenetic lineages.
ContributorsKellom, Matthew (Author) / Raymond, Jason (Thesis advisor) / Anbar, Ariel (Committee member) / Elser, James (Committee member) / Shock, Everett (Committee member) / Walker, Sarah (Committee member) / Arizona State University (Publisher)
Created2017