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Description
Reductive dechlorination by members of the bacterial genus Dehalococcoides is a common and cost-effective avenue for in situ bioremediation of sites contaminated with the chlorinated solvents, trichloroethene (TCE) and perchloroethene (PCE). The overarching goal of my research was to address some of the challenges associated with bioremediation timeframes by improving the rates of reductive dechlorination and the growth of Dehalococcoides in mixed communities. Biostimulation of contaminated sites or microcosms with electron donor fails to consistently promote dechlorination of PCE/TCE beyond cis-dichloroethene (cis-DCE), even when the presence of Dehalococcoides is confirmed. Supported by data from microcosm experiments, I showed that the stalling at cis-DCE is due a H2 competition in which components of the soil or sediment serve as electron acceptors for competing microorganisms. However, once competition was minimized by providing selective enrichment techniques, I illustrated how to obtain both fast rates and high-density Dehalococcoides using three distinct enrichment cultures. Having achieved a heightened awareness of the fierce competition for electron donor, I then identified bicarbonate (HCO3-) as a potential H2 sink for reductive dechlorination. HCO3- is the natural buffer in groundwater but also the electron acceptor for hydrogenotrophic methanogens and homoacetogens, two microbial groups commonly encountered with Dehalococcoides. By testing a range of concentrations in batch experiments, I showed that methanogens are favored at low HCO3 and homoacetogens at high HCO3-. The high HCO3- concentrations increased the H2 demand which negatively affected the rates and extent of dechlorination. By applying the gained knowledge on microbial community management, I ran the first successful continuous stirred-tank reactor (CSTR) at a 3-d hydraulic retention time for cultivation of dechlorinating cultures. I demonstrated that using carefully selected conditions in a CSTR, cultivation of Dehalococcoides at short retention times is feasible, resulting in robust cultures capable of fast dechlorination. Lastly, I provide a systematic insight into the effect of high ammonia on communities involved in dechlorination of chloroethenes. This work documents the potential use of landfill leachate as a substrate for dechlorination and an increased tolerance of Dehalococcoides to high ammonia concentrations (2 g L-1 NH4+-N) without loss of the ability to dechlorinate TCE to ethene.
ContributorsDelgado, Anca Georgiana (Author) / Krajmalnik-Brown, Rosa (Thesis advisor) / Cadillo-Quiroz, Hinsby (Committee member) / Halden, Rolf U. (Committee member) / Rittmann, Bruce E. (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2013
Description
Complex dynamical systems consisting interacting dynamical units are ubiquitous in nature and society. Predicting and reconstructing nonlinear dynamics of units and the complex interacting networks among them serves the base for the understanding of a variety of collective dynamical phenomena. I present a general method to address the two outstanding problems as a whole based solely on time-series measurements. The method is implemented by incorporating compressive sensing approach that enables an accurate reconstruction of complex dynamical systems in terms of both nodal equations that determines the self-dynamics of units and detailed coupling patterns among units. The representative advantages of the approach are (i) the sparse data requirement which allows for a successful reconstruction from limited measurements, and (ii) general applicability to identical and nonidentical nodal dynamics, and to networks with arbitrary interacting structure, strength and sizes. Another two challenging problem of significant interest in nonlinear dynamics: (i) predicting catastrophes in nonlinear dynamical systems in advance of their occurrences and (ii) predicting the future state for time-varying nonlinear dynamical systems, can be formulated and solved in the framework of compressive sensing using only limited measurements. Once the network structure can be inferred, the dynamics behavior on them can be investigated, for example optimize information spreading dynamics, suppress cascading dynamics and traffic congestion, enhance synchronization, game dynamics, etc. The results can yield insights to control strategies design in the real-world social and natural systems. Since 2004, there has been a tremendous amount of interest in graphene. The most amazing feature of graphene is that there exists linear energy-momentum relationship when energy is low. The quasi-particles inside the system can be treated as chiral, massless Dirac fermions obeying relativistic quantum mechanics. Therefore, the graphene provides one perfect test bed to investigate relativistic quantum phenomena, such as relativistic quantum chaotic scattering and abnormal electron paths induced by klein tunneling. This phenomenon has profound implications to the development of graphene based devices that require stable electronic properties.
ContributorsYang, Rui (Author) / Lai, Ying-Cheng (Thesis advisor) / Duman, Tolga M. (Committee member) / Akis, Richard (Committee member) / Huang, Liang (Committee member) / Arizona State University (Publisher)
Created2012
Description
Traditional public health strategies for assessing human behavior, exposure, and activity are considered resource-exhaustive, time-consuming, and expensive, warranting a need for alternative methods to enhance data acquisition and subsequent interventions. This dissertation critically evaluated the use of wastewater-based epidemiology (WBE) as an inclusive and non-invasive tool for conducting near real-time population health assessments. A rigorous literature review was performed to gauge the current landscape of WBE to monitor for biomarkers indicative of diet, as well as exposure to estrogen-mimicking endocrine disrupting (EED) chemicals via route of ingestion. Wastewater-derived measurements of phytoestrogens from August 2017 through July 2019 (n = 156 samples) in a small sewer catchment revealed seasonal patterns, with highest average per capita consumption rates in January through March of each year (2018: 7.0 ± 2.0 mg d-1; 2019: 8.2 ± 2.3 mg d-1) and statistically significant differences (p = 0.01) between fall and winter (3.4 ± 1.2 vs. 6.1 ± 2.9 mg d-1; p ≤ 0.01) and spring and summer (5.6 ± 2.1 vs. 3.4 ± 1.5 mg d-1; p ≤ 0.01). Additional investigations, including a human gut microbial composition analysis of community wastewater, were performed to support a methodological framework for future implementation of WBE to assess population-level dietary behavior. In response to the COVID-19 global pandemic, a high-frequency, high-resolution sample collection approach with public data sharing was implemented throughout the City of Tempe, Arizona, and analyzed for SARS-CoV-2 (E gene) from April 2020 through March 2021 (n = 1,556 samples). Results indicate early warning capability during the first wave (June 2020) compared to newly reported clinical cases (8.5 ± 2.1 days), later transitioning to a slight lagging indicator in December/January 2020-21 (-2.0 ± 1.4 days). A viral hotspot from within a larger catchment area was detected, prompting targeted interventions to successfully mitigate community spread; reinforcing the importance of sample collection within the sewer infrastructure. I conclude that by working in tandem with traditional approaches, WBE can enlighten a comprehensive understanding of population health, with methods and strategies implemented in this work recommended for future expansion to produce timely, actionable data in support of public health.
ContributorsBowes, Devin Ashley (Author) / Halden, Rolf U (Thesis advisor) / Krajmalnik-Brown, Rosa (Thesis advisor) / Conroy-Ben, Otakuye (Committee member) / Varsani, Arvind (Committee member) / Whisner, Corrie (Committee member) / Arizona State University (Publisher)
Created2022