No description available.

No description available.

This study examined the effect of in-situ biosparging on pentachlorophenol (PCP) degradation and bacterial communities in PCP contaminated groundwater. Bacteria were identified by sequencing the 16s rDNA fragment from DNA extracted from groundwater cultures and comparing those sequences to a database using a basic local alignment search tool, BLAST. The PCP-degraders Burkholderia cepacia and Flavobacterium (Sphingobium) chlorophenolicum were identified in multiple wells, as were the 4-chlorophenol degrader Herbaspirillum sp., and the common soil bacteria Pseudomonas sp., Aquaspirillum sp., and Rhodocista sp., among others. Numerous bacterial samples also appeared in the results as “uncultured”. Bacterial community changes were observed using terminal restriction fragment length polymorphism (TRFLP) analysis to identify operational taxonomic units of bacteria at various locations inside and outside the biosparging zone of treatment over time. Diversity measures including species richness, Simpson’s and Shannon’s indices, and species evenness were calculated from operational taxonomic unit results for each well at each sampling point in order to better understand changes in the bacterial community. Species richness tended to be higher at wells further away from the biosparging line, while diversity and evenness varied throughout the area. Correlations between PCP concentration, operational taxonomic units, and distance from biosparging wells were determined by Pearson’s product-moment correlation and Spearman’s rank correlation. Positive correlations were found between distance from biosparging wells and PCP concentration, species richness and distance, and to a smaller degree, diversity and distance. Biosparging remediation has a significant impact on the types of PCP-degrading bacteria within the groundwater matrix, and installations of this type of treatment should be applied to maximize the use of the native bacteria to assist in degradation of the contaminant.

Posttraumatic stress disorder (PTSD) is associated with significant functional impairments and disruptions in cognitive functioning. Functional recovery and remediation of cognitive difficulties are oft over-looked treatment targets in this population, despite their significant contribution to the burden of PTSD to the individual and to society. Existing literature suggests that functional impairment and cognitive dysfunction may not respond to first-line treatments for PTSD. Thus, the focus of this thesis was to examine symptom dimensions associated with cognitive dysfunction and functional impairment among individuals with PTSD, and to investigate a novel approach to cognitive remediation, Goal Management Training (GMT), in this population. Study one in this thesis is a review in which we identified a strong relation between dissociative symptoms and neuropsychological functioning, transdiagnostically and among individuals with PTSD. The hypothesis that dissociative symptoms would be strongly related to functional impairment among individuals with PTSD was explored in study two. We found that dissociative symptoms mediated the relation between PTSD symptoms and functional impairment among a sample of military members, veterans, and first responders with PTSD. Study three identified that emotion regulation difficulties and dissociative symptoms most strongly predicted functional impairment among civilians with PTSD and high rates of exposure to childhood abuse and neglect. In study four we investigated the effectiveness of a cognitive training program, Goal Management Training (GMT), in improving cognitive functioning, clinical symptoms, and functional impairment among inpatients with PTSD. Participation in GMT was associated with improved cognitive functioning and increased ability to engage in goal directed behaviours when highly emotional. This thesis highlights the importance of assessing emotion regulation difficulties and dissociative symptoms in order to target functional impairment and cognitive dysfunction among individuals with PTSD. Moreover, it provides evidence for a potential treatment approach to ameliorate these difficulties. / Thesis / Doctor of Philosophy (PhD) / Posttraumatic stress disorder (PTSD) is a mental health condition that develops after exposure to a traumatic event. It is associated with reduced functioning in important areas of life, including social relationships, work performance, and self-care. PTSD is also associated with reduced cognitive functioning in areas such as memory, planning, and organization. This thesis focuses on examining variables that may be related to these difficulties, including specific symptoms such as difficulty managing emotions and difficulties remaining in the present moment (dissociation). We also investigate a treatment program, Goal Management Training (GMT), aimed at teaching skills to improve cognitive and daily functioning. By understanding what contributes to cognitive functioning and functional difficulties in individuals with PTSD and by providing evidence for a treatment that can improve these difficulties, we hope to improve the lives of individuals with PTSD.

Remedial ground densification is commonly used to reduce the liquefaction susceptibility of loose, saturated sand deposits, wherein controlled liquefaction is typically induced as the first step in the densification process. Assuming that the extent of induced liquefaction is approximately equal to the extent of ground densification, the purpose of this research is to assess the feasibility of using earthquake liquefaction data in remedial ground densification design via energy-based concepts. The energy dissipated by frictional mechanisms during the relative movement of sand grains is hypothesized to be directly related to the ability of a soil to resist liquefaction (i.e., Capacity). This hypothesis is supported by energy-based pore pressure generation models, which functionally relate dissipated energy to residual excess pore pressures. Assuming a linearized hysteretic model, a "simplified" expression is derived for computing the energy dissipated in the soil during an earthquake (i.e., Demand). Using this expression, the cumulative energy dissipated per unit volume of soil and normalized by the initial mean effective confining stress (i.e., normalized energy demand: NED) is calculated for 126 earthquake case histories for which the occurrence or non-occurrence of liquefaction is known. By plotting the computed NED values as a function of their corresponding SPT penetration resistance, a correlation between the normalized energy capacity of the soil (NEC) and SPT penetration resistance is established by the boundary giving a reasonable separation of the liquefaction / no liquefaction data points. NEC is the cumulative energy dissipated per unit volume of soil up to initial liquefaction, normalized by the initial mean effective confining stress, and the NEC correlation with SPT penetration resistance is referred to as the Capacity curve. Because the motions induced during earthquake shaking and remedial ground densification significantly differ in amplitude, duration, and frequency content, the dependency of the derived Capacity curve on the nature of the loading needs to be established. Towards this end, the calibration parameters for energy-based pore pressure generation models are examined for their dependence on the amplitude of the applied loading. The premise being that if the relationship between dissipated energy and pore pressure generation is independent of the amplitude of loading, then the energy required to generate excess pore pressures equal to the initial effective confining stress should also be independent of the load amplitude. However, no conclusive statement could be made from results of this review. Next, first order numerical models are developed for computing the spatial distribution of the energy dissipated in the soil during treatment using the vibratory probe method, deep dynamic compaction, and explosive compaction. In conjunction with the earthquake-derived Capacity curves, the models are used to predict the spatial extent of induced liquefaction during soil treatment and compared with the predicted spatial extent of improvement using empirical expressions and guidelines. Although the proposed numerical models require further validation, the predicted extent of liquefaction and improvement are in very good agreement, thus giving credence to the feasibility of using the Capacity curve for remedial ground densification design. Although further work is required to develop energy-based remedial densification design procedures, the potential benefits of such procedures are as follows. By using the Capacity curve, the minimum dissipated energy required for successful treatment of the soil can be determined. Because there are physical limits on the magnitude of the energy that can be imparted by a given technique, such an approach may lead to improved feasibility assessments and initial designs of the densification programs. / Ph. D.

Permeable reactive barrier (PRB) technology is increasingly considered for in situ treatment of contaminated groundwater; however, current design formulas for PRBs are limited and do not properly account for all major physical and attenuation processes driving remediation. This study focused on developing a simple methodology to design PRBs that is easy to implement while improving accuracy and being more conservative than the available design methodologies. An empirical design equation and a simple analytical design equation were obtained to calculate the thickness of a PRB capable of degrading a contaminant from a source contaminant concentration to a maximum contaminant level at a Point of compliance . Both equations integrate the fundamental components that drive the natural attenuation process of the aquifer and the reactive capacity of the PRB.The empirical design equation was derived from a dataset of random hypothetical cases that used the solutions of the PRB conceptual model (Solution I). The analytical design equation was derived from particular solutions of the model (Solution II) which the study showed fit the complex solutions of the model well. Using the hypothetical cases, the analytical equation has shown that it gives an estimated thickness of the PRB just 15 % lower or higher than the real thickness of the PRB 95 percent of the time. To calculate the design thickness of a PRB, Natural attenuation capacity of the aquifer can be estimated from the observed contaminant concentration changes along aquifer flowpaths prior to the installation of a PRB. Bench-scale or pilot testing can provide good estimates of the required residence times ( Gavaskar et al. 2000) , which will provide the reactive capacity of the PRB needed for the calculation. The results of this study suggest also that the installation location downgradient from the source of contaminant is flexible. If a PRB is installed in two different locations, it will achieve the same remediation goals. This important finding gives engineers and scientists the choice to adjust the location of their PRBs so that the overall project can be the most feasible and cost effective. / Master of Science

One of the most promising technologies in groundwater contaminant remediation is the active use of natural microbial activity to reduce aromatic hydrocarbons and other contaminants to simpler, non-toxic compounds. Biological treatment technologies which clean an aquifer without removing aquifer material fall into the broad category of in situ bioremediation, and have the potential to provide cost-effective remediation plans. Mathematical models used to simulate in situ bioremediation must deal with spatial variation in contaminant and electron acceptor concentration, microbial population, and media properties. Research has shown that the use of sequential electron acceptors significantly impacts biodegradation results. Aquifer conditions may switch between primary and secondary electron accepting conditions, further complicating the modeling process. This research examines the two-dimensional, sequential electron acceptor computer model SEAM2D, developed by Widdowson (1992), and extends the SEAM2D model by developing the equations and coding for the newly recognized solid phase, iron(Ill)-based contaminant reduction. Both a sensitivity investigation and field simulations are provided. The sensitivity investigation identifies which input parameters most significantly impact model results (i.e. changes in contaminant mass and concentration). The modeling simulations provide an illustration of model capabilities and documents procedures used in applying SEAM2D to a USGS study site in Laurel Bay, South Carolina. The Laurel Bay site and subsequent model simulations are unique in that the natural, sequential electron acceptor process of oxygen-iron(Ill) reduction is specifically monitored and modeled. / Master of Science

No description available.

This work describes the development of a Monte Carlo simulation toolkit built on the Geant4 framework for applied health physics applications. The toolkit is designed to construct complex radiation fields and measure how radiation detectors respond to those fields, specifically radiation fields expected to be encountered in environmental and safety applications. The toolkit, along with its development and validation, is described. The use of the toolkit for performing minimum detectable concentration evaluations is outlined, following methods described in the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) and Nuclear Regulatory Guidance Manual 1507, which detail Minimum Detectable Concentrations for Typical Radiation Surveys using Instruments for Various Contaminants and Field Conditions. Results and implications from the findings of these evaluations are also discussed. This work demonstrates the simulation toolkit’s ability to replicate real-world scenarios through simulation validation against real laboratory data before showcasing its use. Minimum detectable concentration evaluations completed with this toolkit are compared to commercially available software traditionally used for these evaluations when employing methods outlined in NUREG- 1507. The evaluations completed using simulations developed from this toolkit agree well with the commercially available software, except for sources with primary photon emissions below 100 keV, where the toolkit simulation shows a significant deviation. This work also underscores the importance for individuals using regulatory guidance manuals for performing minimum detectable concentration analysis to consider the motion of detectors and soil moisture content for sources with low-energy photon emissions. Furthermore, the toolkit demonstrates its effectiveness in developing Monte Carlo simulations that recreate radiation survey data for large open land areas.

Phosphorus (P) pollution in stormwater runoff poses a significant threat to water quality, contributing to eutrophication and ecosystem degradation. This research evaluates the potential of volcanic scoria (VSco), an abundant and cost-effective resource in Utah, USA, to influence P concentrations in urban stormwater systems. Batch adsorption experiments examined the behavior of VSco across three particle sizes—fine (<0.841 mm), medium (0.841–2 mm), and granular (2.38–9.5 mm)—under conditions mimicking stormwater scenarios. The results reveal that fine VSco exhibited higher adsorption efficiency than medium and granular sizes, achieving notable P removal at higher concentrations. However, at lower concentrations, fine VSco showed potential for P release due to desorption of pre-existing P. Medium and granular VSco showed minimal adsorption capacity and, in some cases, acted as P sources, highlighting a dual potential depending on stormwater conditions. Adsorption isotherms indicate that the adsorption behavior of fine VSco aligns with the Langmuir model, with a finite and relatively low adsorption capacity. Calculated distribution coefficient (Kd) values for fine VSco ranged from 0.04 to 0.005 L/g, indicating weak adsorption efficiency compared to materials like activated carbon (1–10 L/g) or soils with moderate adsorption capacity (0.1–0.5 L/g). Loss-on-ignition tests confirmed that VSco’s performance is driven by its physical and chemical properties, particularly its calcium content, rather than organic matter. The study emphasizes caution in applying fine VSco for stormwater remediation due to its potential to release P under typical runoff conditions. However, fine VSco may still be viable in specific scenarios where P levels are higher, such as in stormwater hotspots or localized areas with elevated concentrations, allowing for targeted remediation. The research underscores the need for further testing to refine VSco’s applications, particularly in low-impact development (LID) practices, such as infiltration basins and rain gardens, to effectively manage P levels while supporting ecological and aesthetic goals. These findings contribute to understanding the complex role of VSco in urban stormwater systems, offering insights for sustainable water quality management and nutrient cycling in urban landscapes.