Matching Items (171)
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Intimate coupling of Ti2 photocatalysis and biodegradation (ICPB) offers potential for degrading biorecalcitrant and toxic organic compounds much better than possible with conventional wastewater treatments. This study reports on using a novel sponge-type, Ti2-coated biofilm carrier that shows significant adherence of Ti2 to its exterior and the ability to accumulate

Intimate coupling of Ti2 photocatalysis and biodegradation (ICPB) offers potential for degrading biorecalcitrant and toxic organic compounds much better than possible with conventional wastewater treatments. This study reports on using a novel sponge-type, Ti2-coated biofilm carrier that shows significant adherence of Ti2 to its exterior and the ability to accumulate biomass in its interior (protected from UV light and free radicals). First, this carrier was tested for ICPB in a continuous-flow photocatalytic circulating-bed biofilm reactor (PCBBR) to mineralize biorecalcitrant organic: 2,4,5-trichlorophenol (TCP). Four mechanisms possibly acting of ICPB were tested separately: TCP adsorption, UV photolysis/photocatalysis, and biodegradation. The carrier exhibited strong TCP adsorption, while photolysis was negligible. Photocatalysis produced TCP-degradation products that could be mineralized and the strong adsorption of TCP to the carrier enhanced biodegradation by relieving toxicity. Validating the ICPB concept, biofilm was protected inside the carriers from UV light and free radicals. ICPB significantly lowered the diversity of the bacterial community, but five genera known to biodegrade chlorinated phenols were markedly enriched. Secondly, decolorization and mineralization of reactive dyes by ICPB were investigated on a refined Ti2-coated biofilm carrier in a PCBBR. Two typical reactive dyes: Reactive Black 5 (RB5) and Reactive Yellow 86 (RY86), showed similar first-order kinetics when being photocatalytically decolorized at low pH (~4-5), which was inhibited at neutral pH in the presence of phosphate or carbonate buffer, presumably due to electrostatic repulsion from negatively charged surface sites on Ti2, radical scavenging by phosphate or carbonate, or both. In the PCBBR, photocatalysis alone with Ti2-coated carriers could remove RB5 and COD by 97% and 47%, respectively. Addition of biofilm inside macroporous carriers maintained a similar RB5 removal efficiency, but COD removal increased to 65%, which is evidence of ICPB despite the low pH. A proposed ICPB pathway for RB5 suggests that a major intermediate, a naphthol derivative, was responsible for most of the residual COD. Finally, three low-temperature sintering methods, called O, D and DN, were compared based on photocatalytic efficiency and Ti2 adherence. The DN method had the best Ti2-coating properties and was a successful carrier for ICPB of RB5 in a PCBBR.
ContributorsLi, Guozheng (Author) / Rittmann, Bruce E. (Thesis advisor) / Halden, Rolf (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2011
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As the return to normality in the wake of the COVID-19 pandemic enters its early stages, the necessity for accurate, quick, and community-wide surveillance of SARS-CoV-2 has been emphasized. Wastewater-based epidemiology (WBE) has been used across the world as a tool for monitoring the pandemic, but studies of its efficacy

As the return to normality in the wake of the COVID-19 pandemic enters its early stages, the necessity for accurate, quick, and community-wide surveillance of SARS-CoV-2 has been emphasized. Wastewater-based epidemiology (WBE) has been used across the world as a tool for monitoring the pandemic, but studies of its efficacy in comparison to the best-known method for surveillance, randomly selected COVID-19 testing, has limited research. This study evaluated the trends and correlations present between SARS-CoV-2 in the effluent wastewater of a large university campus and random COVID-19 testing results published by the university. A moderately strong positive correlation was found between the random testing and WBE surveillance methods (r = 0.63), and this correlation was strengthened when accommodating for lost samples during the experiment (r = 0.74).

ContributorsWright, Jillian (Author) / Halden, Rolf (Thesis director) / Driver, Erin (Committee member) / School of Music, Dance and Theatre (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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An analysis of university flight emissions, carbon neutrality goals, and the global impact of university sanctioned flight.

ContributorsKoehler, Megan Anne (Author) / Halden, Rolf (Thesis director) / Driver, Erin (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Fluoroquinolone antibiotics have been known to cause severe, multisystem adverse side effects, termed fluoroquinolone toxicity (FQT). This toxicity syndrome can present with adverse effects that vary from individual to individual, including effects on the musculoskeletal and nervous systems, among others. The mechanism behind FQT in mammals is not known, although

Fluoroquinolone antibiotics have been known to cause severe, multisystem adverse side effects, termed fluoroquinolone toxicity (FQT). This toxicity syndrome can present with adverse effects that vary from individual to individual, including effects on the musculoskeletal and nervous systems, among others. The mechanism behind FQT in mammals is not known, although various possibilities have been investigated. Among the hypothesized FQT mechanisms, those that could potentially explain multisystem toxicity include off-target mammalian topoisomerase interactions, increased production of reactive oxygen species, oxidative stress, and oxidative damage, as well as metal chelating properties of FQs. This review presents relevant information on fluoroquinolone antibiotics and FQT and explores the mechanisms that have been proposed. A fluoroquinolone-induced increase in reactive oxygen species and subsequent oxidative stress and damage presents the strongest evidence to explain this multisystem toxicity syndrome. Understanding the mechanism of FQT in mammals is important to aid in the prevention and treatment of this condition.

ContributorsHall, Brooke Ashlyn (Author) / Redding, Kevin (Thesis director) / Wideman, Jeremy (Committee member) / Borges, Chad (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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This dissertation explores the use of bench-scale batch microcosms in remedial design of contaminated aquifers, presents an alternative methodology for conducting such treatability studies, and - from technical, economical, and social perspectives - examines real-world application of this new technology. In situ bioremediation (ISB) is an effective remedial approach for

This dissertation explores the use of bench-scale batch microcosms in remedial design of contaminated aquifers, presents an alternative methodology for conducting such treatability studies, and - from technical, economical, and social perspectives - examines real-world application of this new technology. In situ bioremediation (ISB) is an effective remedial approach for many contaminated groundwater sites. However, site-specific variability necessitates the performance of small-scale treatability studies prior to full-scale implementation. The most common methodology is the batch microcosm, whose potential limitations and suitable technical alternatives are explored in this thesis. In a critical literature review, I discuss how continuous-flow conditions stimulate microbial attachment and biofilm formation, and identify unique microbiological phenomena largely absent in batch bottles, yet potentially relevant to contaminant fate. Following up on this theoretical evaluation, I experimentally produce pyrosequencing data and perform beta diversity analysis to demonstrate that batch and continuous-flow (column) microcosms foster distinctly different microbial communities. Next, I introduce the In Situ Microcosm Array (ISMA), which took approximately two years to design, develop, build and iteratively improve. The ISMA can be deployed down-hole in groundwater monitoring wells of contaminated aquifers for the purpose of autonomously conducting multiple parallel continuous-flow treatability experiments. The ISMA stores all sample generated in the course of each experiment, thereby preventing the release of chemicals into the environment. Detailed results are presented from an ISMA demonstration evaluating ISB for the treatment of hexavalent chromium and trichloroethene. In a technical and economical comparison to batch microcosms, I demonstrate the ISMA is both effective in informing remedial design decisions and cost-competitive. Finally, I report on a participatory technology assessment (pTA) workshop attended by diverse stakeholders of the Phoenix 52nd Street Superfund Site evaluating the ISMA's ability for addressing a real-world problem. In addition to receiving valuable feedback on perceived ISMA limitations, I conclude from the workshop that pTA can facilitate mutual learning even among entrenched stakeholders. In summary, my doctoral research (i) pinpointed limitations of current remedial design approaches, (ii) produced a novel alternative approach, and (iii) demonstrated the technical, economical and social value of this novel remedial design tool, i.e., the In Situ Microcosm Array technology.
ContributorsKalinowski, Tomasz (Author) / Halden, Rolf U. (Thesis advisor) / Johnson, Paul C (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Bennett, Ira (Committee member) / Arizona State University (Publisher)
Created2013
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Nitrate is the most prevalent water pollutant limiting the use of groundwater as a potable water source. The overarching goal of this dissertation was to leverage advances in nanotechnology to improve nitrate photocatalysis and transition treatment to the full-scale. The research objectives were to (1) examine commercial and synthesized photocatalysts,

Nitrate is the most prevalent water pollutant limiting the use of groundwater as a potable water source. The overarching goal of this dissertation was to leverage advances in nanotechnology to improve nitrate photocatalysis and transition treatment to the full-scale. The research objectives were to (1) examine commercial and synthesized photocatalysts, (2) determine the effect of water quality parameters (e.g., pH), (3) conduct responsible engineering by ensuring detection methods were in place for novel materials, and (4) develop a conceptual framework for designing nitrate-specific photocatalysts. The key issues for implementing photocatalysis for nitrate drinking water treatment were efficient nitrate removal at neutral pH and by-product selectivity toward nitrogen gases, rather than by-products that pose a human health concern (e.g., nitrite). Photocatalytic nitrate reduction was found to follow a series of proton-coupled electron transfers. The nitrate reduction rate was limited by the electron-hole recombination rate, and the addition of an electron donor (e.g., formate) was necessary to reduce the recombination rate and achieve efficient nitrate removal. Nano-sized photocatalysts with high surface areas mitigated the negative effects of competing aqueous anions. The key water quality parameter impacting by-product selectivity was pH. For pH < 4, the by-product selectivity was mostly N-gas with some NH4+, but this shifted to NO2- above pH = 4, which suggests the need for proton localization to move beyond NO2-. Co-catalysts that form a Schottky barrier, allowing for localization of electrons, were best for nitrate reduction. Silver was optimal in heterogeneous systems because of its ability to improve nitrate reduction activity and N-gas by-product selectivity, and graphene was optimal in two-electrode systems because of its ability to shuttle electrons to the working electrode. "Environmentally responsible use of nanomaterials" is to ensure that detection methods are in place for the nanomaterials tested. While methods exist for the metals and metal oxides examined, there are currently none for carbon nanotubes (CNTs) and graphene. Acknowledging that risk assessment encompasses dose-response and exposure, new analytical methods were developed for extracting and detecting CNTs and graphene in complex organic environmental (e.g., urban air) and biological matrices (e.g. rat lungs).
ContributorsDoudrick, Kyle (Author) / Westerhoff, Paul (Thesis advisor) / Halden, Rolf (Committee member) / Hristovski, Kiril (Committee member) / Arizona State University (Publisher)
Created2013
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Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are

Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are observed during residency for judgment of their skills. Although the value of this method of skills assessment cannot be ignored, novel methodologies of objective skills assessment need to be designed, developed, and evaluated that augment the traditional approach. Several sensor-based systems have been developed to measure a user's skill quantitatively, but use of sensors could interfere with skill execution and thus limit the potential for evaluating real-life surgery. However, having a method to judge skills automatically in real-life conditions should be the ultimate goal, since only with such features that a system would be widely adopted. This research proposes a novel video-based approach for observing surgeons' hand and surgical tool movements in minimally invasive surgical training exercises as well as during laparoscopic surgery. Because our system does not require surgeons to wear special sensors, it has the distinct advantage over alternatives of offering skills assessment in both learning and real-life environments. The system automatically detects major skill-measuring features from surgical task videos using a computing system composed of a series of computer vision algorithms and provides on-screen real-time performance feedback for more efficient skill learning. Finally, the machine-learning approach is used to develop an observer-independent composite scoring model through objective and quantitative measurement of surgical skills. To increase effectiveness and usability of the developed system, it is integrated with a cloud-based tool, which automatically assesses surgical videos upload to the cloud.
ContributorsIslam, Gazi (Author) / Li, Baoxin (Thesis advisor) / Liang, Jianming (Thesis advisor) / Dinu, Valentin (Committee member) / Greenes, Robert (Committee member) / Smith, Marshall (Committee member) / Kahol, Kanav (Committee member) / Patel, Vimla L. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Contaminants of emerging concern (CECs) present in wastewater effluent can threat its safe discharge or reuse. Additional barriers of protection can be provided using advanced or natural treatment processes. This dissertation evaluated ozonation and constructed wetlands to remove CECs from wastewater effluent. Organic CECs can be removed by hydroxyl radical

Contaminants of emerging concern (CECs) present in wastewater effluent can threat its safe discharge or reuse. Additional barriers of protection can be provided using advanced or natural treatment processes. This dissertation evaluated ozonation and constructed wetlands to remove CECs from wastewater effluent. Organic CECs can be removed by hydroxyl radical formed during ozonation, however estimating the ozone demand of wastewater effluent is complicated due to the presence of reduced inorganic species. A method was developed to estimate ozone consumption only by dissolved organic compounds and predict trace organic oxidation across multiple wastewater sources. Organic and engineered nanomaterial (ENM) CEC removal in constructed wetlands was investigated using batch experiments and continuous-flow microcosms containing decaying wetland plants. CEC removal varied depending on their physico-chemical properties, hydraulic residence time (HRT) and relative quantities of plant materials in the microcosms. At comparable HRTs, ENM removal improved with higher quantity of plant materials due to enhanced sorption which was verified in batch-scale studies with plant materials. A fate-predictive model was developed to evaluate the role of design loading rates on organic CEC removal. Areal removal rates increased with hydraulic loading rates (HLRs) and carbon loading rates (CLRs) unless photolysis was the dominant removal mechanism (e.g. atrazine). To optimize CEC removal, wetlands with different CLRs can be used in combination without lowering the net HLR. Organic CEC removal in denitrifying conditions of constructed wetlands was investigated and selected CECs (e.g. estradiol) were found to biotransform while denitrification occurred. Although level of denitrification was affected by HRT, similar impact on estradiol was not observed due to a dominant effect from plant biomass quantity. Overall, both modeling and experimental findings suggest considering CLR as an equally important factor with HRT or HLR to design constructed wetlands for CEC removal. This dissertation provided directions to select design parameters for ozonation (ozone dose) and constructed wetlands (design loading rates) to meet organic CEC removal goals. Future research is needed to understand fate of ENMs during ozonation and quantify the contributions from different transformation mechanisms occurring in the wetlands to incorporate in a model and evaluate the effect of wetland design.
ContributorsSharif, Fariya (Author) / Westerhoff, Paul (Thesis advisor) / Halden, Rolf (Committee member) / Fox, Peter (Committee member) / Herckes, Pierre (Committee member) / Arizona State University (Publisher)
Created2013
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This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems

This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
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The living world we inhabit and observe is extraordinarily complex. From the perspective of a person analyzing data about the living world, complexity is most commonly encountered in two forms: 1) in the sheer size of the datasets that must be analyzed and the physical number of mathematical computations necessary

The living world we inhabit and observe is extraordinarily complex. From the perspective of a person analyzing data about the living world, complexity is most commonly encountered in two forms: 1) in the sheer size of the datasets that must be analyzed and the physical number of mathematical computations necessary to obtain an answer and 2) in the underlying structure of the data, which does not conform to classical normal theory statistical assumptions and includes clustering and unobserved latent constructs. Until recently, the methods and tools necessary to effectively address the complexity of biomedical data were not ordinarily available. The utility of four methods--High Performance Computing, Monte Carlo Simulations, Multi-Level Modeling and Structural Equation Modeling--designed to help make sense of complex biomedical data are presented here.
ContributorsBrown, Justin Reed (Author) / Dinu, Valentin (Thesis advisor) / Johnson, William (Committee member) / Petitti, Diana (Committee member) / Arizona State University (Publisher)
Created2012