Master of Science (MS), Ohio University, 2024, Civil Engineering (Engineering and Technology)

Practical considerations for the design of an AMD treatment plant located in the Sunday Creek watershed were investigated. A mixed culture of bacteria originally from and AMD site located at Wolf Run, Noble County, OH, was enriched under various conditions in AMD from the Sunday Creek site. Following the work of Almomani (2023), the effects of inoculum size (1%, 2%, 5%, and 10%), nutrient enrichment conditions (reagent-grade ammonium and phosphate, no nutrient addition, and commercially available fertilizers), and temperature (8 °C, room temperature, and 32 °C) on the iron-oxidation kinetics of this culture were investigated. Inoculum size had no statistically significant effect on oxidation rates, although the oxidation rate at 5% and 10% inoculum (0.175 and 0.171 h^-1 , respectively) were observed to be nearly twice the oxidation rate at 1% inoculum (0.107 h^- 1 ). There was no significant difference between the oxidation rates of samples containing 0.1 M ammonium sulfate and 5 mM potassium phosphate (0.156 h^-1 ) and samples containing only inoculum (0.108 h^-1 ), and commercial fertilizer was observed to decrease iron oxidation rates (0.0547 h^-1 ), although the total time from inoculation to total iron oxidation was similar to that of the samples containing only inoculum. Iron oxidation rates increased with temperature, and the oxidation kinetics were fitted using the Arrhenius model yielding an activation energy of 70.1 kJ mol^-1 °K^-1 and a pre-exponential factor of 2.21 ∙ 10^11 h^-1 . A pilot-scale batch reaction experiment was conducted in field conditions at the Sunday Creek site in a 1250 gal clarifier. Oxidation rates were observed to be 0.012 h^-1 after the second subculturing, which was lower than any rate observed in the laboratory experiments. This was explained by a combination of suboptimal factors, including low temperatures and inclusion of commercial fertilizer as a secondary nutrient source. Finally, a process optimiz (open full item for complete abstract)

Master of Science in Engineering, Youngstown State University, 2024, Department of Civil/Environmental and Chemical Engineering

The 108-mile-long Mahoning River, historically one of the most contaminated rivers in the U.S., contains metals above the EPA aquatic criteria. This study identifies the contamination levels, spatiotemporal patterns, sources, speciation, and bioaccessibility of metals (As, Ba, Fe, Pb, Ni, Zn) in the water and sediment of the lower Mahoning River. Sediment analysis showed that all metals exceeded the Sediment Reference Value, except for Ba. Regression analysis showed a significant decrease of Pb and Fe (p < 0.05) in water from 1993-2021, suggests that the water quality of the river with respect to Pb and Fe is improving comparatively in the past three decades. The contamination factor indicated that metals in water were uncontaminated (< 1), while metals in sediment were moderately to highly polluted (3-15). Inverse distance weighting in sediments illustrated decreasing concentrations towards downstream for Ni, while increasing concentrations towards downstream for As, Ba, Fe, Pb, and Zn in sediment. The inverse distance weighting patterns may be associated with land use, as the river traversed the agricultural region upstream, the urbanized region downstream, and mixed-land areas in the last stretch. Speciation analysis revealed metals in water and sediments were in divalent forms (HM2+), except Pb (PbOH+, PbCO3), indicating high bioaccessibility and potential plant uptake in the aquatic environment.

Doctor of Philosophy (PhD), Ohio University, 2024, Civil Engineering (Engineering and Technology)

Colloidal aggregation is a critical phenomenon influencing various environmental processes. However, limited research has been conducted on the aggregation of particles with heterogeneous physical and chemical properties, which are more representative of practical environmental systems than homogeneous particles. The central hypothesis of this dissertation is that primary particle size polydispersity along with chemical and material heterogeneity of primary particles exert non-trivial effects on the aggregate growth rate and the fractal dimensions of aggregates. In this dissertation, the aggregation and stability of heterogeneous nano- and sub-micrometer particles in aqueous systems were investigated using in situ microscopy and image analysis. Initially, the study examined the growth kinetics and structures of aggregates formed by polystyrene microplastics in mono- and bidisperse systems. Findings indicated that while the primary particle size distribution did not affect the scaling behavior of aggregate growth, it delayed the onset of rapid aggregation. Structural analysis revealed a power law dependence of the aggregate fractal dimension in both mono- and bidisperse systems, with mean fractal dimensions consistent with aggregates from diffusion-limited cluster aggregation. The results also suggested that aggregate fractal dimension was insensitive to shape anisotropy. The dissertation further explored the structure of DLCA aggregates in heterogeneous systems composed of particles with varying sizes, surface charges, and material compositions. The fractal dimensions of DLCA aggregates in these heterogeneous particle systems were similar, ranging from 1.6 to 1.7, and consistent with theoretical predictions and experimental evidence for homogeneous DLCA aggregates. This confirmed the universality of aggregate structures in the DLCA regime, regardless of particle composition. Additionally, a scaling relationship was demonstrated between aggregat (open full item for complete abstract)

PhD, University of Cincinnati, 2024, Engineering and Applied Science: Environmental Science

Per- and polyfluoroalkyl substances (PFAS) are a class of fluorinated, synthetic chemicals recently regulated in drinking water in the United States to mitigate exposure and related health effects. Anion exchange (AEX) resins are one treatment technology that has demonstrated effectiveness for removal of PFAS from drinking water; however, fundamental parameters are scarcely reported in literature and impacts of background water quality are poorly understood, presenting barriers to achieving optimal design, operation, and compliance of AEX systems. To address these gaps, batch- and column-scale studies were conducted to obtain estimates for equilibrium and mass transfer parameters and to better characterize effects of major inorganic anions (IAs) and natural organic matter (NOM) during PFAS AEX treatment. First, to investigate AEX behavior of IAs, selectivity with respect to chloride (Kx/Cl) was determined on three strong-base, gel-type, AEX resins (CalRes 2304, PFA694E, and PSR2 Plus) via batch binary isotherms. Kx/Cl results (bicarbonate < sulfate = nitrate at studied conditions) predicted competitive behavior in a multi-solute batch isotherm and corroborated elution order of IAs from column experiments at 2- and 4-min empty-bed contact times (EBCTs). An ion exchange column model (IEX-CM; https://github.com/USEPA/Water_Treatment_Models) was validated for IAs by comparing with experiment-generated data. Minimal NOM impacts were observed on IAs breakthrough. IEX-CM simulations of water quality changes resulting from AEX startup revealed corrosion implications; however, the effects were short-lived (hours to days) compared with expected runtimes for PFAS applications (months to years). Second, to obtain reliable estimates for intraparticle diffusion coefficients (Ds), a centrifugal stirrer device was adapted from literature to reduce external mass transfer resistance in batch kinetic studies. Initial experiments with CalRes2304 were conducted across mixing spee (open full item for complete abstract)

MS, University of Cincinnati, 2024, Engineering and Applied Science: Environmental Engineering

In-vehicle air quality is a crucial aspect of environmental health, impacting millions of commuters globally. With urbanization and increased vehicle usage, understanding the exposure to air pollutants inside the vehicles is vital for developing strategies to mitigate associated health issues. In-vehicle air quality influences the comfort of the driver during long commutes and has gained significant interest. This study focuses on studying the in-vehicle particulate matter using low-cost sensors in the San Francisco Bay Area, an urban setting with significant traffic congestion and varied air quality conditions. Traditionally, air pollution monitoring used stationary devices, limiting its applications but with the evolution of sensor technology, sensors with various attributes are available. This work employs two low-cost portable sensors, Temtop M2000 and Flow 2 to simultaneously measure in-vehicle pollutants (PM2.5, PM10, and CO2) from May 2023 to February 2024. These sensors are portable, low-cost, and provide real-time data, making them ideal for dynamic environments like moving vehicles. Data collection occurred during morning and evening rush hours to capture variations in exposure. Concurrently with the pollutant measurements, GPS coordinates were logged by the Flow 2 sensor, to calculate the vehicle speed during commute using the Haversine formula, allowing for a comprehensive analysis of how speed influences the in-vehicle PM. Morning and evening rush hour pollutant concentrations were compared, and seasonality was studied. Morning PM concentrations were frequently higher than evening concentrations. Monthly variations were observed with higher PM during certain months; however, the morning and evening rush hour averages were below the 24-hour California/ National ambient air quality standards for PM. Ambient local air quality data was sourced from EPA local monitoring stations to compare in-vehicle PM2.5 with local PM2.5 concentratio (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Chemical Engineering

The ill effects of climate change are unfolding in real time, as species and ecosystems face irreversible destruction. Climate action is needed now more than ever, as ambitious targets set by the Paris Agreement seem far-reaching in the wake of global average temperatures above 1.5C over their pre-industrial levels recorded over a continuous 12 month period for the first time. Countries, organizations, and companies alike have pledged to limit their net greenhouse gas (GHG) emissions to the environment to zero, via nationally determined contributions and corporate net-zero commitments. Such commitments remain unattainable in the absence of guidance like convergent carbon accounting methods, systems models, and roadmapping frameworks. This dissertation seeks to bridge this gap for the chemicals and materials industry (CMI). The chemical industry generates the “hardest to abate” emissions among the industrial sector due to the fixed carbon content of its products. However, as chemical energy carriers such as hydrogen and methanol gain prominence as solutions to the intermittency issues of renewable energy, the net-zero transition of chemicals becomes tied to the net-zero goals of more expansive and ubiquitous industries such as the power sector. The decarbonization of chemicals to this end, requires estimation of material and carbon flows, and baseline emissions of its current global operations. The frameworks in literature lack appropriate structure and comprehensiveness for such analysis, and relevant process and price data are inaccessible and cost prohibitive. We therefore develop an inventory of first principle based, mass balance compliant, publicly available process and cost data for CMI processes, sourced from the public domain. We devise a regression framework capable of handling conflict ridden data, and an algorithm to map resource, intermediate, product, and emission flows of any chemical system with known product capacities. The resulting Global (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Food, Agricultural and Biological Engineering

As catchments become increasingly impervious, urban stormwater pollutant loads, erosional force, and flooding increases. The practice of stormwater management is critical environmental protection that became regulated by the US federal government in the 1970s. With the need to attenuate peak flow rates and reduce the excess stormwater volumes generated from impervious catchments, stormwater control measures (SCMs) were developed such as stormwater detention basins, retention ponds, drainage ditches, and subsurface stormwater detention. Having a variety of SCMs available provides stakeholders with the ability to target specific aspects of stormwater management, including runoff quantity, runoff quality, or other ecosystem services. Regulations have evolved over time to have a greater emphasis on stormwater quality. As such, SCM design has evolved to address pollutant removal in stormwater. Green infrastructure (GI) practices, also called low impact development (LID) SCMs, have gained popularity for stormwater management since the start of the 21st century and incorporate principles of ecological engineering into stormwater management. Examples of GI include a variety of practices that use infiltration through filter media such as rain gardens, bioretention cells (BRCs), and high rate biofiltration (HRBF), permeable pavements, green roofs, and constructed stormwater wetlands (CSWs). The use of GI has benefits in addition to peak flow, volume, and pollutant reduction such as creating habitat for pollinators, cooling urban spaces, and adding attractive green space. Pollutant removal mechanisms vary between GI practices with some systems providing greater sedimentation and treatment of particulates and some providing greater treatment of dissolved pollutants through microbially-mediated transformation, plant uptake, and/or adsorption. Performance of SCMs varies based on design, site characteristics (e.g. topography, soil texture and infiltration capacity, depth to wa (open full item for complete abstract)

PhD, University of Cincinnati, 2024, Engineering and Applied Science: Environmental Engineering

Granular activated carbon (GAC) adsorption is a viable technology for treatment of per- and polyfluoroalkyl substances (PFAS) in drinking water. However, due to the complexity of adsorption, current knowledge gaps on fundamental adsorption behavior of PFAS, and the lack of assessment of affecting factors, practical challenges exist in conducting adsorption tests for accurate evaluation of GAC performance to provide the optimum design of GAC adsorbers. The first step in ensuring the accuracy of batch experiments is maintaining the properties of the bulk GAC when grinding is used for the batch experiments. The study compared three common grinding methods (blender, mortar and pestle (MP), and ball milling unit (BMU)) for particle size reduction efficiency and impacts on the properties of two GACs. Blender and MP were the most and the least time efficient for particle size reduction, respectively. The shock (particle fracturing) mechanism in MP grinding produced ground particles similar in properties to the bulk Filtrasorb 400 (F400). Shear (outer layer removal) mechanism was at play in the blender and the ball milling unit (BMU) and led to more core particles with lower specific surface area and greater oxygen content compared to bulk F400 in larger size fractions (e.g., 20×40 mesh). For smaller size fractions (e.g., 100×200 mesh), all three grinding methods maintained the properties of bulk F400. The BMU was chosen for grinding GAC for the subsequent batch studies as the blender produced large amounts of fines. Subsequently, single-solute kinetic and isotherm experiments were conducted for nine drinking-water relevant PFAS and three commonly used GACs in buffered Type 1 water (18.2 MO·cm resistivity). The kinetic experiments provided necessary estimates of mass transfer and equilibrium parameters for designing isotherm experiments. The isotherm experiments established adsorption isotherms for the nine PFAS and three GACs in a standardized, reproducibl (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Civil Engineering

The human-induced increase in greenhouse gas (GHG) concentrations is the primary driver of recent global warming, leading to a series of climate changes, including sea level rise, ocean acidification, and more frequent and severe weather extremes. These changes have profound impacts on global ecosystems and human societies. The world has recognized the necessity for countries to cooperate in combating climate change, resulting in international treaties such as the Kyoto Protocol and the Paris Agreement. The success of international cooperation depends on a portfolio of various approaches to eliminate, reduce, substitute, and compensate for GHG emissions. The transition from fossil fuels to renewable energy can effectively mitigate GHG emissions. Wind and solar energy have experienced substantial growth over the past decade, yet the development of geothermal energy remains stagnant despite its immense potential. Considering its additional advantages, such as the dual benefits of generating both electricity and heat, the stability of energy generation, and the synthesis with carbon capture and storage, more focus should be placed on geothermal energy. Meanwhile, most efforts to address climate change have focused on mitigating carbon dioxide (CO2) emissions and removing their accumulation from the atmosphere. While there is ~210x more CO2 than methane (CH4) in the atmosphere, the atmospheric concentration of CH4 has increased faster and alone contributes an amount of radiative forcing that is about 30% of the contribution from CO2. With positive temperature-driven feedbacks that release CH4 to the atmosphere as temperatures rise, a shorter atmospheric lifetime than CO2, and continued reliance on natural gas, a portfolio approach is urgently needed to slow, stop, and reverse the accumulation of CH4 in the atmosphere. To provide insights to address the above issues, this dissertation focuses on optimizing strategies for geothermal heat mining and CH4 control. Cha (open full item for complete abstract)

Master of Science in Engineering, University of Akron, 2024, Civil Engineering

Under typical dry night conditions, standard road markings tend to remain clearly visible. However, this visibility is substantially deteriorated in wet conditions during nighttime. This study aims to investigate the effectiveness of the wet reflective pavement marking materials and their performance in enhancing visibility during wet nights, thereby reducing accidents occurring on wet nights, these various types of this innovative markings were installed by the Ohio Department of Transportation (ODOT) across several locations statewide. In this research work, 17 sites were selected, featuring diverse materials such as wet reflective tape, epoxy with large glass beads, epoxy with elements for all-weather conditions, thermoplastic with large glass beads, thermoplastic with all-weather elements, and waterborne traffic paint embedded with large glass beads. The initial assessment of these materials was conducted within the first thirty days following their application. Further performance evaluations were carried out roughly every six months over a period of at least two years after their application, covering at least two winter seasons, to monitor the long-term performance of these road markings. The evaluations focused on various parameters, including dry and wet reflectivity, color, durability, and the retention of reflective media. A handheld Delta LTL-X retro-reflectometer was utilized to measure the retroreflectivity of pavement markings in accordance with ASTM standards using a 30-m geometry to simulate the roadway being illuminated by the headlights of a car. Daytime color measurements were taken using a MiniScan XE Plus (Model 4500L) colorimeter. Durability was evaluated using a subjective rating as an integer on a scale of 0 (the material is completely missing) to 10 (where 100% of the material remains). The projected service life of each material employed was determined and forecasted by analyzing reflectivity measurements collected throughout the duratio (open full item for complete abstract)

Master of Science, The Ohio State University, 2024, Civil Engineering

Numerous means of providing for power demand flexibility in buildings have been articulated and studied. Existing research has studied occupant comfort during modulation of thermal conditions indoors for the purpose of shedding thermal loads during demand management events. However, there has been little research on how the reduction of ventilation, which can substantially lower power demand in buildings during peak times, affects the comfort of building occupants. To fill this gap, we surveyed 91 college students over an hour period in a controlled environment under four different scenarios: 1) Normal operation with default ventilation and cooling (i.e., control); 2) Temperature rise but default ventilation; 3) Ventilation shut off but temperature kept at default levels; and 4) ventilation and cooling air shut off. We placed participants in a small study room in which we controlled the VAV system and allowed them to study, read, or use their computers. Every fifteen minutes participants completed survey measures regarding their subjective evaluation of their environment. Results show no significant differences in occupant comfort between the four treatment groups across the hour-long experiment. Importantly, our findings suggest that temporary (i.e., one-hour) systematic ventilation suppression can be a useful strategy for lessening the energy demand of buildings because it does not have a significant impact on occupant comfort.

Doctor of Philosophy (PhD), Ohio University, 2024, Chemical Engineering (Engineering and Technology)

The imperative to mitigate environmental degradation from the direct application of animal wastewater and the rising costs of commercial fertilizers has spurred the exploration of nutrient recovery through electro-precipitation, focusing on producing solid fertilizer efficiently. In the first study, an investigation on the electrochemical treatment of synthetic animal wastewater at initial pH levels of 5.9 and 6.6 discovered that pH 6.6 favored higher phosphorus recovery rates and proved more energy efficient. Analysis of solid byproducts through scanning electron microscopy and energy-dispersive X-ray spectroscopy highlighted the co-precipitation of struvite and brushite incredibly efficiently at the higher pH level. This pH-dependent outcome suggests the potential for tailored nutrient recovery strategies in waste management. In the second study, the focus shifted to multivariate screening analyses using the Plackett-Burman design on Synthetic Animal Wastewater (SAW) with an initial pH of 6.6 to discern the effects of temperature, cathodic potential, turbulence, and ion concentration on nutrient removal from wastewater. The Mg:Ca molar ratio was identified as the most significant factor in phosphorus recovery. The findings emphasized that controlling the Mg:Ca ratio, temperature, and N: P ratio could yield competitive energy consumption with existing industrial methods. The preference for struvite formation at lower temperatures indicated temperature's critical role in nutrient recovery optimization. In the third study, response surface methodology (RSM) and artificial neural networks (ANN) were combined to optimize phosphorus recovery from synthetic animal wastewater (SAW). The combination of a multi-layer feed-forward network and Box-Behnken design enabled the approach to be adapted to various environmental and wastewater scenarios. The dual-model system accurately forecasted the recovery efficiency, substantiated by significant R2 values and minimal root (open full item for complete abstract)

Master of Science (MS), Ohio University, 2024, Civil Engineering (Engineering and Technology)

The goal of this thesis is to compare the current methods to generate pigment from AMD, test the pigments for their chemical and elemental compositions, and determine whether the pigments generated meet ASTM and market standards. The pigments were also evaluated to find their associated color numbers and compared to existing pigments collected from pigment companies. Iron oxide sludge was generated and collected from Truetown, OH by oxidizing and settling AMD. This sludge was tested for quality with the intent of making pigments from dried iron oxide. The sludge was dewatered or washed to represent potential treatment methods, then dried and ground into a fine powder. The powder was tested for iron oxide, sulfates, lead, organic coloring matter, moisture content, and ignition loss using ASTM standard methods. It was tested for its X-ray patterns using X-ray diffraction and for 31 elements using X-ray fluorescence. It was finally tested for its performance as an oil paint and its color spectrophotometry. These experiments were repeated for several examples of pigments from existing industry, including artistry and concrete dyeing. The results of these experiments showed that AMD pigments are generally lower in impurities than artist pigments, but higher than expected in sulfates. They are also amorphous but contain no toxic levels of metals. The experiments consistently showed that pressing was more effective than washing for removing impurities. The AMD pigments were also determined to be a different color than any of the collected pigments on the market, and would need to be identified as its own, separate color. Based on these conclusions and its derivation from AMD, it is suspected to be the iron oxide mineral known as Shwertmannite.

Master of Science in Engineering, Youngstown State University, 2024, Department of Civil/Environmental and Chemical Engineering

The Mahoning River is identified as one of the top five most polluted rivers in the United States. The main aim of this research is to explore the impacts of groundwater conditions and geology on heavy metal concentration in groundwater in the Mahoning River Basin. Physico-chemical parameters and heavy metals for four monitoring wells were analyzed statistically. Piper diagrams, GIS-generated maps and Gibbs diagrams were utilized to visually represent the spatial distribution of key water quality parameters and hydro-geochemical facies. Both Physico-chemical parameters and heavy metals showed spatio-temporal variabilities linked to geogenic and anthropogenic influences. Minimum seasonal groundwater pH was below USEPA aquatic life criteria (USEPA, 2023) and lead concentration of Garrettsville wellfield exceeded permissible USEPA aquatic life criteria. Average groundwater pH was more variable in spring than autumn, whereas the converse existed for groundwater TDS and hardness. The standard deviation of groundwater pH was 0.49 in Spring and 0.42 in Autumn. TDS and hardness had standard deviations of 88.17 and 97.79 respectively in Autumn and 88.14 and 88.43 respectively in Spring. The variability of groundwater hardness in the autumn season is about 10.6% higher than that of spring season. Cu, Ni, Cr and Zn showed lowest (ranging from 2.00-17.00 μg/L) and highest (ranging from 13.00-22.00 μg/L) concentrations in southern and northeastern and parts of the study area respectively, whilst Fe had high levels in northwestern (ranging from 1001.00-1940.00 μg/L) and low levels (ranging from 50.00-1000.00 μg/L) in northeastern, central, and southern parts of the research area. It was found that Hiram and Garrettsville wells had Fe concentrations of ~1.40 to 6.62 times more than USEPA aquatic life criteria. The study revealed that Cu, Ni and Cr are higher in wells found in geological formations containing shale and sandstone and lower in wells found in geological formations con (open full item for complete abstract)

MS, Kent State University, 2022, College of Architecture and Environmental Design

The construction industry's environmental impact is a growing concern, necessitating a shift towards sustainable practices. The construction industry is the leading cause of carbon emissions and greenhouse gases (Globalabc, 2019). The global construction industry is increasingly likely to fall short of the promise of the Paris Agreement to decarbonize by 2050 (Paris Agreement, 2015). To reach the goal, our standard for sustainability and environmental sustainability must be higher. As the paradigm of construction and materials shifts towards sustainable practices, we must conduct a comprehensive assessment of different materials and processes. This research introduces a comprehensive approach to the environmental assessment of Mass Timber, specifically cross-laminated timber (CLT) using the Environmental Value Engineering (EVE) methodology. When comparing different environmental assessment methodologies such as cost-benefit analysis, Life Cycle Cost Analysis, Input-Output Analysis, EMERGY analysis, and EVE analysis it was found that only EVE is the unique methodology that incorporates all the inputs of Environment, Fuel, Goods, and Services throughout the life cycle. Acknowledging the environmental challenges posed by construction, the study focuses on comparing the environmental effects of CLT. Analyzing each life cycle phase, including the resource formation stages, is crucial as the raw material for mass timber is renewable and comes from nature. Grounded in the need for a holistic assessment method, the study aims to bridge gaps in the evaluation of the environmental effect of cross-laminated timber. It employs a quantitative and qualitative approach, utilizing EMERGY values as the cornerstone for the analysis. From the EVE analysis, the Transformity of the cross-laminated timber was determined to be 6.48E+11 solar emjoules/board foot. The EMERGY of a 20'X10' CLT panel was calculated to be 8.91E+14 SEJ. The analysis of individual life cycle phases revealed tha (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 0, Civil Engineering

Kinetic models offer a promising avenue for expediting risk assessments, minimizing resource demands, and advancing our comprehension of the environmental fate of chemicals. This research aimed to develop kinetic models benefiting a diverse range of users, including policymakers, industry entities, scientific researchers, and others, for the aforementioned purposes. Given the complexity of environmental conditions and the diversity of chemical contaminants, there is an urgent need to develop predictive models with wide applicability. Moreover, chemical reactivity, which influences chemical transformation in the environment, also governs chemical interactions and reactions with other molecules in the environment. This underscores the need for kinetic modeling to facilitate our understanding of chemical transformation mechanisms. On one front, comprehensive kinetic models, devoid of detailed understanding of reaction mechanisms, were formulated to predict the abiotic reduction rate constants of both organic and inorganic chemicals by Fe(II)-associated reductants. The research methodology involved compiling a comprehensive dataset encompassing diverse chemical structures and environmental conditions. Conventional Quantitative Structure-Activity Relationships (QSARs) approaches and machine learning algorithms were employed to develop predictive models based on the comprehensive dataset. These models were designed to capture intricate relationships between chemical properties, environmental factors, and abiotic reduction rate constants. The dissertation also explored the interpretability of the developed models, shedding light on the influential features and mechanisms governing abiotic reduction processes. On the other front, mechanism-based kinetic models were developed to elucidate the enhanced oxidation of catechol by MnO2 under alkaline air conditions, uncovering the pivotal role of surface Mn(III)-catalyzed oxidation in the abiotic humification of polyphenols (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Civil Engineering

The global health risks presented by waterborne pathogens are of significant concern. Waterborne pathogens can survive treatment processes and show resistance to disinfectants, which potentially resulting in disease that greatly threatens human health. Despite efforts put into eliminating waterborne pathogens, they are still detected in engineered aquatic environments such as wastewater treatment plants (WWTP) and drinking water distribution systems (DWDS), which are potential sites of human exposure. Antibiotic resistant bacteria (ARB), with their transmissible antibiotic resistant genes (ARG), and opportunistic pathogens (OP), with their virulence factors and persistence in biofilms to resist disinfectants, have captured a lot attention. The seriousness of bacterial diseases transmitted through water prompts the investigation of how engineered disinfection technologies impact water microbiomes to limit dissemination of OP and prevent ARB infections. Ultraviolet (UV) irradiation is an advantageous disinfection technology that causes DNA or protein damage with little to no production of toxic by-products. However, investigations regarding the interactions between ARB and OP with different UV wavelengths, and the differences of UV disinfection on lab-scale strains compared to field or clinical samples and how UV impacts microbial communities are still needed. The research addresses these gaps through three objectives. (1) Investigate the impact of UV wavelengths on ARB at cell and molecular levels and explore the underlying mechanisms of different wavelengths using a lab strain ARB. A complementary study was done to further explore the existence of ARB collected from field WWTP influents and investigate impact of UV disinfection on ARB in this environment. (2) Explore UV disinfection of OP using typical lab strains and clinical isolates of nontuberculous mycobacteria (NTM) at cell and molecular levels, focusing on UV resistance differences related to pathogenicity (open full item for complete abstract)

Master of Science in Engineering, Youngstown State University, 2024, Department of Civil/Environmental and Chemical Engineering

The Mill Creek watershed is located in the Northeast Ohio and covers an area of 78.3 square miles within the Mahoning River basin. The river has been experiencing significant water quality problems due to pollution from point and nonpoint source contributions from its tributaries. Before joining the Mahoning River, the river flows through several areas, including the City of Columbiana, Beaver Township, Boardman Township, and Youngstown. Mill Creek comprises seven major tributaries, namely Anderson Run, Cranberry Run, Indian Run, Bears Run, Ax Factory Run, Sawmill Run, and Turkey Run, all of which contribute to the degradation of the river water quality in terms of algal bloom, turbidity, and bacterial contamination. The water quality of rivers is significantly affected by several sources of contamination, such as combined sewer overflows, failing septic systems, animal waste, and runoff from agricultural and urban areas. Despite several studies conducted in the past, a hydrologic and hydraulic investigation in the context of water quality modeling has not been conducted in Mill Creek yet. To address this concern, monitoring stations were established in different locations along the river to record real-time flow depth data using HOBO loggers. In addition, sporadic water quality data from the past and the recent data collected by the Environmental Science Program at YSU have been used for water quality calibration and validation. The hydrologic and hydraulic model was developed using the Personal Computer Storm Water Management (PCSWMM) model. Data sourced from the National Oceanic and Atmospheric Administration (NOAA) of the National Climatic Data Center (NCDC), the Digital Elevation Model (DEM) from the United States Geological Survey (USGS), land cover data from the National Land Cover Datasets (NLCD), and soil data from the United States Department of Agriculture (USDA) were utilized to construct the model. The calibration and validation of the model were carrie (open full item for complete abstract)

Master of Science, The Ohio State University, 2024, Civil Engineering

Reclamation of abandoned surface mine lands (AML) with coal combustion residuals (CCRs) may reduce AML hazards and beneficially reuse the waste product of coal combustion, CCRs. CCRs pose a risk of leaching harmful trace elements into the environment, endangering human and ecological receptors. Quantification of risk should be site and material specific, to capture the leaching mechanisms and the concentrations of trace elements. This study analyzed two types of Leaching Environmental Assessment Framework (LEAF) leaching experiment data, as well as over 7 years of site water quality analysis from an AML reclaimed with CCRs. In this work, we applied statistical methods and developed geochemical models to evaluate the expected leachate composition and predict future risk of arsenic (As), selenium (Se), and boron (B) from CCR leachate. The expectation of As, Se, and B to leach from a type of CCR, stabilized flue gas desulfurization (SFGD), was calculated with interval censored parametric bootstrapping for mean. The geochemical model was calibrated with Bayesian Inversion methods, allowing highly uncertain mobilization mechanisms of the proposed calcium mineral host phases to be uncovered. Our results indicate the potential for Se and B to leach from SFGD above the chronic aquatic health criteria in a lab setting and As to pose increased cancer risk. However, in a field application, we do not observe elevated risk of As and Se to human or ecological systems. At the site in Conesville, OH, B poses risk to ecological systems and may be sourced from the CCRs placed in the AML, alterations in groundwater flow, or other site minerals. This work contributes an integrated approach to risk analysis. We include both a statistical analysis and geochemical model to predict the expected leachate composition from SFGD. The statistical analysis may be applied to any LEAF experiments conducted for evaluation of beneficial reuse of CCR. The geochemical model, calibrated with Bayesian I (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Civil Engineering

Microbial water quality in drinking water distribution systems (DWDS) must be managed appropriately to protect public health. Ultraviolet (UV) disinfection effectively inactivates a wide range of microorganisms while generating minimal to no disinfection byproducts (DBPs), but does not provide a disinfection residual for protecting water quality from treatment to tap. Regulated drinking water quality is an important standard for health reasons, but end user perceptions of drinking water are a commonly overlooked issue of drinking water treatment and distribution. This dissertation explores the interrelatedness of end users and drinking water quality and investigates UV-based solutions to manage drinking water and prevent bacterial contamination in centralized and distributed applications. In Chapter 2, a coupled human-natural systems approach was used to determine the connections among drinking water quality, end user perception, and causal factors in drinking water systems. Interviews and water sampling from twenty-four households in a chlorinated DWDS in rural Ohio were conducted. An aggregated index of drinking water perceptions (safety, satisfaction, overall quality) was correlated with experiences of household water issues, but not necessarily explained by measured tap water quality. Water quality varied spatially throughout the DWDS. Analysis of community level cognitive maps revealed that customers perceived environmental quality, pollution, infrastructure quality, and water system service performance as other indicators of tap water quality. In Chapter 3, hydropowered UV disinfection technology for point-of-use applications was prototyped and evaluated by bench-scale flow through testing for disinfection performance. Hydropowered UV disinfection may offer a decentralized solution for maintaining microbial water quality in DWDS (e.g., booster disinfection). Currently, the technology is feasible at scales of point-of-entry and above, but economic analyse (open full item for complete abstract)