Browsing by Author "Wiesner, Mark R"

As biological challenges to environmental health, such as the proliferation of antibiotic resistance genes, continue to emerge there is a greater need for the generation of models capable of predicting the fate and transport of biological particles. For over 100 years, Smoluchowski’s watershed 1917 work has provided a foundation for the construction of such models. Classically, this approach has been used for inert nano-scale particles. However, given that several of the most pressing challenges are biological in nature, it is imperative that predictive models of particle transport be adapted to include particles with a biological signature.This work uses modified Smoluchowskian aggregation modeling parameters to investigate the transport of three primary biological particles: bacteriophages, extracellular vesicles, and extracellular DNA, each of them often existing on the nanoscale. This was done by 1) using modified Smoluchowskian aggregation parameters to predict phage-induced host lysis, 2) characterize phage-kaolinite heteroaggregation, and 3) construct a multi-particle predictive model incorporating the heteroaggregation of all three particle types. This work found that modified Smoluchowskian aggregation parameters used in concert with appropriate population balances were largely successful in predicting such particles’ transport and provided unique insight into possible design features for engineered environmental systems.

Surface chemistry plays an essential role in determining the reactivity, bioaccessibility, bioavailability and toxicity of nanoparticles (NPs) in the environment. Processes such as aggregation, deposition and biouptake are controlled in part by the attachment efficiency, α, between particles and the surfaces they encounter. One premise of this research is that surface hydrophobicity is a pivotal property of NP surfaces that can affect the behavior of NPs in aquatic environment and potentially decide the fate and transport of NPs. However, there are multiple challenges in the characterization of hydrophobicity for NPs. Methods developed for macroscopic surfaces or organic compounds may not be readily applied or interpreted for the case of nano-scale surfaces. This dissertation addresses theoretical basis for applying methods to determining hydrophobicity of NPs. The use of an octanol-water partitioning method analogous to that used for organic compounds was evaluated on the basis of trends anticipated by thermodynamics, and by experimental observations. This work shows that partitioning of NPs in two phases systems, such as water and octanol, is not uniquely determined by hydrophobicity, but also influenced by surface charge and particle size. The water-oil interface rather than the bulk phases becomes the thermodynamically favored location for NP accumulation once NPs are larger than 1-10 nm and/or the surface is amphiphilic.

Nonetheless, the relative hydrophobicity of selected NPs, as characterized by adsorption of molecular probes (i.e. organic dye and naphthalene), was consistent with the macroscopic contact angle measurements and octanol-water distribution coefficients. The in-situ adsorption of these molecular probes offers the most solid grounds for measurement of hydrophobicity. Other measure of hydrophobicity or hydrophilicity such as water-affinity based methods that measure water vapor adsorption to nanomaterial powders, or immersion microcalorimetry and thermogravimetric analysis, yielded similar results to the molecular probes. However, possible physical or chemical transformations to NP surfaces during characterization by these other methods limited the use of results to infer hydrophobicity based on a rigorous thermodynamic model.

Column experiments suggested that the attachment efficiency of NPs to biofilm was generally greater for more hydrophobic NPs, though polymeric coatings might stabilize NPs against the attachment. The affinity of NPs for a variety of bacterial surfaces (i.e. different species, planktonic or biofilm, with or without extracellular polymeric substances (EPS)) of different hydrophobicities, which correlated with the quantity of proteins in EPS, was also investigated. It was found that the attachment of hydrophobic NPs increased with the hydrophobicity of bacterial surfaces, but not for hydrophilic NPs. Environmental conditions such as divalent ions and pH influenced the affinity of nanoparticle for bacterial surface by changing the bacterial surface hydrophobicity and electric double layer interaction, respectively.

This work considers the transport and attachment of nanoscale particles to surfaces and the associated phenomena that dictate particle-surface interactions. A consideration of the deposition of nano-scale particles on surfaces is a natural outgrowth of more than a century of research in the area of colloid science, and has taken on new pertinence in the context of understanding the fate and transport of engineered nanoparticles in aqueous environments. More specifically, the goal of this work is to better understand the effects of particle size, surface polymer coatings, and aggregation state on the kinetics of nanoparticle deposition. Theoretical tools such as those developed by Derjaguin-Landau-Verwey-Overbeek (DLVO) and Flory-Krigbaum , as well as the soft particle theory and surface element integration scaling methods are employed to address certain problems that were not considered with the existing theoretical frameworks for the conventional colloidal problems. Consequences of theoretical predictions are evaluated experimentally using column experiments or the quartz crystal microbalance techniques to monitor deposition kinetics. One of the key findings of this work is the observation that polymer coatings may stabilize nanoparticles against deposition or increase deposition, depending on whether the polymer coatings exist on both of the interacting surfaces and the interaction between the polymer and the collector surface. Both steric and bridging mechanisms are possible depending on whether contact between the polymer and collector surface can result in successful attachment. In addition, limitations in the use of conventional, equilibrium-based DLVO theory to describe the deposition of nano-scale particles at very low ionic strength are also identified and discussed. Moreover, it is demonstrated that the interaction between the aggregated nano-scale particles and environmental surfaces is controlled by the characteristic size of the primary particles rather than that of the aggregates. Thus despite an increase in hydrodynamic diameter, aggregation is predicted to reduce deposition only from the hydrodynamic aspects, but not from the colloidal interaction aspect. The affinity between aggregated nanoparticles and a surface may be increased at the initial stage of deposition while being unaffected by aggregation state during later stages of deposition. The results of this study lead to better understandings, at least on a qualitative level, of the factors that controlling the kinetics of deposition and, in a broader sense, the fate and transport of nanoscale particles in the aqueous environment.

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The study and application of materials possessing size dimensions in the nano scale range and, as a result, unique properties have led to the birth of a new field; nanotechnology. Scientists and engineers have discovered and are exploiting the novel physicochemical characteristics of nanoparticles (NPs) to enhance consumer products and technologies in ways superior to their bulk counterparts. Escalating production and use of NPs will unavoidably lead to release and exposure to environmental systems. This introduction of emerging potential contaminant NPs will provide new and interesting challenges for exposure and risk forecasting as well as environmental endurance.

The ultimate goal of this research is to develop a framework that incorporates experimental and computational efforts to assess and better understand the exposure of metal and metal-oxide NPs released to wastewater treatment plants (WWTPs) and further implications on land application units (LAUs) where biosolids can be applied. The foundation of the computational effort is comprised of Monte Carlo mass balance models that account for the unique processes affecting NP fate and transport through the different technical compartments of a WWTP and LAU. Functional assay and bioreactor experiments in environmental media were used to determine parameters capable of describing the critical processes that impact the fate of NPs in wastewater.

The results of this research indicate that a simplified, but still environmentally relevant nano-specific exposure assessment is possible through experimentation to parameterize adapted models. Black box modeling efforts, which have been shown in previous studies, show no disadvantage relative to discretization of technical compartments as long as all key transport and fate mechanisms are considered. The distribution coefficient (_), an experimentally determined, time-dependent parameter, can be used to predict the distribution of NPs between the liquid and solid phase in WWTPs. In addition, this parameter can be utilized a step further for the estimation of the more fundamental, time independent attachment efficiency between the NPs and the solids in wastewater. The NP core, size, and surface coating will influence the value of these parameters in addition to the background particle characteristics as the parameters are specific to the environmental system of study. For the metal and metal-oxide NPs studied, preferential overall association of approximately 90% or greater with the solid phase of wastewater was observed and predicted.

Furthermore, NP transformations including dissolution, redox reactions, and adsorption can potentially impact exposure. For example, experimental results showed that nano-CeO2 is reduced from Ce(IV) to Ce(III) when in contact with wastewater bacteria where Ce2S3 will likely govern the Ce(III) phase in biosolids. From the literature, similar transformations have been observed with Ag and ZnO NPs to Ag2S and ZnS. With respect to TiO2 NPs, studies indicated that due to high insolubility, these NPs would not undergo transformation in WWTPs. The distribution and transformation rate coefficients can then be used in fate models to predict the NP species exposed to aquatic and terrestrial systems and environmentally relevant concentrations released from WWTPs.

Upon completion of the WWTP model, the predicted concentrations of NPs and NP transformation byproducts released in effluent and biosolids were attainable. A simple mass balance model for NP fate in LAUs was then developed to use this output. Results indicate that NP loading on LAUs would be very low but that build up over time to steady state could result in mass concentrations on the order of the typical level for the background metal in soil. Transport processes of plant uptake and leaching were expected to greatly impact the solid phase concentration of the NPs remaining in the LAU, while rainfall did not impart a significant influence upon variation between low and high annual amounts. The significance of this research is the introduction of a method for NP exposure assessment in WWTPs and subsequently in LAUs. This work describes and quantifies the key processes that will impact Ag, TiO2, CeO2 and ZnO NP fate and transport, which can inform future studies, the modeling community and regulatory agencies.

Nanomaterials are being increasingly produced and used across a myriad of applications while their novel properties are still in the midst of being designed and explored. Thus the full implications of introducing these materials into the environment cannot be understood, yet the need to assess potential risks is already upon us. This work discusses a comprehensive view of environmental impact with respect to material flows from across the value chain into all compartments of the environment, whereby interactions and potential hazardous effects become possible. A subset of this broad system is then chosen for evaluation; a model is derived to describe the fate of nanomaterials released to wastewater.

This analysis considers the wastewater treatment plant (WWTP) as a complete mixed reactor aerobic secondary clarifier, and predicts whether nanomaterials will associate with effluent or sludge to project potential concentrations in each. The concentration of nanomaterials reaching a WWTP is estimated based on a linear weighting of total production, and the fate of nanomaterials within the WWTP is based on a characteristic inherent to the material, partition coefficient, and on design parameters of the WWTP, such as retention times and suspended solids concentration.

Due to the uncertainty inherent to this problem, a probabilistic approach is employed. Monte Carlo simulation is used, sampling from probability distributions assigned to each of the input parameters to calculate a distribution for the predicted concentrations in sludge and effluent. Input parameter distributions are estimated from values reported in the literature where possible. Where data do not yet exist, studies are carried out to enable parameter estimation. In particular, nanomaterial production is investigated to provide a basis to estimate the magnitude of potential exposure. Nanomaterial partitioning behavior is also studied in this work, through laboratory experiments for several types of nano-silver.

The results presented here illustrate the use of nanomaterial inventory data in predicting environmentally relevant concentrations. Estimates of effluent and sludge concentrations for nano-silver with four different types coatings suggest that these surface treatments affect the removal efficiency; the same nanomaterial with different coatings may have different environmental fates. Effluent concentration estimates for C60 and nano-TiO2 suggest that these nanomaterials could already be present at problematic concentrations at current levels of annual production.

Estimates of environmentally relevant concentrations may aid in interpretation of nanotoxicology studies. These relative estimates are also useful in that they may help inform future decisions regarding where to dedicate resources for future research. Beyond attempting to estimate environmental concentrations of nanomaterials, this type of streamlined model allows the consideration of scenarios, focusing on what happens as various input parameters change. Production quantity and the fraction of this quantity that is released to wastewater are found to greatly influence the model estimates for wastewater effluent concentrations; in the case of wastewater sludge concentrations, the model is sensitive to those parameters in addition to solids retention time.

This work presents an improved aggregation model that accounts for two types of particles and simulates the heterogeneous aggregation between these particles. By accounting for the sizes, concentrations, and affinities of the nano- and background particles, the model can evaluate e.g. how the nanoparticles affect an existing distribution of natural aggregates or how quickly the nanoparticles will settle out of a given system, and can help determine which parameter to change in order to eliminate the nanoparticles from a system faster. The model could provide a powerful tool to evaluate the exposure of nanoparticles in environmental and engineered waters.

The prevalence of nanoparticles in the environment is expected to grow in the coming years due to their increasing pervasiveness in consumer and industrial applications. Once released into the environment, nanoparticles encounter conditions of pH, salinity, UV light, and other solution conditions that may alter their surface characteristics and lead to aggregation. The unique properties that make nanoparticles desirable are a direct consequence of their size and increased surface area. Therefore, it is critical to recognize how aggregation alters the reactive properties of nanomaterials, if we wish to understand how these properties are going to behave once released into the environment. The size and structure of nanoparticle aggregates depend on surrounding conditions, including hydrodynamic ones. Depending on these conditions, aggregates can be large or small, tightly packed or loosely bound. Characterizing and measuring these changes to aggregate morphology is important to understanding the impact of aggregation on nanoparticle reactive properties. Examples of decreased reactivity due to aggregation include the case where tightly packed aggregates have fewer available surface sites compared to loosely packed ones; also, photocatalytic particles embedded in the center of large aggregates will experience less light when compared to particles embedded in small aggregates. However, aggregation also results in an increase in solid-solid interfaces between nanoparticles. This can result in increased energy transfer between neighboring particles, surface passivation, and altered surface tension. These phenomena can lead to an increase in reactivity. The goal of this thesis is to examine the impacts of aggregation on the reactivity of a select group of nanomaterials. Additionally, we examined how aggregation impacts the removal efficiency of fullerene nanoparticles using membrane filtration.

The materials we selected to study include ZnS - a metal chalcogenide nanoparticle that photoluminesces after exposure to UV; TiO2 and ZnO nanoparticles - photocatalytic nanoparticles that generate reactive oxygen species upon UV irradition; and, fullerene nanoparticles used in the filtration experiments, selected for their potential use, small size, and surface chemistry. Our primary methods used to characterize particle and aggregate characteristics include dynamic light scattering used to describe particle size, static light scattering used to characterize aggregate structure (fractal dimension), transmission electron microscopy used to verify primary particle sizes, and electrophoretic mobility measurements to evaluate suspension stability. The reactive property of ZnS that was measured as a function of aggregation was photoluminescence, which was measured using a spectrofluorometer. The reactive property of TiO2 and ZnO that was studied was their ability to generate hydroxyl radicals; these were measured by employing a fluorescent probe that becomes luminescent upon interaction with the hydroxyl radical. To detect the presence of fullerene nanoparticles and calculate removal efficiencies, we used total organic carbon measurements. Additionally, we used UV-vis spectroscopy to approximate the impact of particle shadowing in TiO2 and ZnO aggregates, and Fourier transformed infrared spectroscopy to determine how different electrolytes interact with fullerene surface groups.

Our findings indicate that the impact of aggregation on nanoparticle reactivity is material specific. ZnS nanoparticles exhibit a 2-fold increase in band-edge photoluminescence alongside a significant decrease in defect-site photoluminescence. This is attributed to aggregate size-dependent surface tension. Additionally, we used photoluminescence measurements to develop a new method for calculating the critical coagulation concentration of a nanoparticle suspension.

The ability of both TiO2 and ZnO to generate hydroxyl radicals was significantly hampered by aggregation. The decline in hydroxyl radical generation could be attributed to two key parameters. First, increased aggregate size was associated with increased particle shadowing, as determined from the observed decrease in the rate of optically induced transitions. Secondly, aggregate structure was associated both with increased shadowing (denser aggregates exhibited more shadowing than similarly sized loose aggregates), and with an increase in radical quenching on neighboring particle surfaces in an aggregate.

Aggregation had a positive impact on hydroxylated fullerene membrane separation, increasing removal efficiency to around 80%, regardless of transmembrane pressure. However, the type of electrolyte used determined whether aggregation was successful at increasing removal. Divalent ions, capable of forming strong covalent bonds with surface oxygen groups, increased removal efficiency and made it pressure insensitive. In contrast, monovalent ions increased removal efficiency slightly, but maintained the pressure dependence of the removal efficiency. Evidence is presented to support the hypothesis that divalently aggregated hydroxylated fullerenes deform under increased pressure and partially penetrate the membrane.

Finally, nanoparticle reactive properties depend on the primary particle aggregation state. Both size and structure are key factors when evaluating nanomaterial reactivity under aggregation-inducing conditions. However, the impact of aggregation is not easily predicted. Some materials exhibit a decreased reactivity while others experience an increase. Therefore, the impact of aggregation on nanoparticle reactive properties must be evaluated on a material-by-material basis, while considering all of the particle and aggregate characteristics as well as environmental ones.

Abstract

As natural resource scarcity and industrial productivity continue to rise, membrane filtration technologies provide a compelling solution for the production of clean water. Membranes are versatile, energy-efficient, and highly effective, yet they suffer from the indomitable problem of fouling. Abundant research has been conducted on this topic, but new methods for understanding and assessing fouling are still emerging, and are nevertheless needed. The present work endeavors to study membrane fouling from yet another perspective using a powerful electrochemical technique known as electrochemical impedance spectroscopy (EIS). EIS is a non-destructive electrical perturbative method, thus it can be performed during filtration. While some research groups have applied EIS for membrane characterization, none have yet incorporated conductive polymeric membranes into the electrochemical setup.

The primary objectives of this study were to (1) synthesize a robust and sufficiently conductive polymeric membrane for use as a working electrode; (2) develop a non-invasive non-Faradaic EIS method to characterize membrane fouling in real time; (3) separate contributions to total fouling from processes happening on the membrane surface and within the interior pore network. Membrane fouling was studied using three model foulants, bovine serum albumin (BSA), humic acid, and colloidal silica in a supporting electrolyte of phosphate buffered saline (PBS) and potassium nitrate (KNO3), respectively. To better understand the spatial position and magnitude of fouling, EIS spectra were interpreted by fitting equivalent circuits informed by the physical structures of the membrane surface and interior.

Data from the EIS fouling tests showed good agreement between changes in impedance, conductance, and capacitance and reduction in permeate flow, which is the conventional parameter used to monitor fouling severity. The conductive coating also allowed for fouling to be differentiated between the surface and interior layers of the membrane. Moreover, experiments with feed solutions containing separate foulants in different solution chemistries verified that EIS is sensitive enough to differentiate between various membrane fouling effects as well as irreversible fouling phenomena. These results suggest that conductive membranes can be used alongside EIS to spatially and temporally characterize membrane fouling as it happens in real time without the need to remove or damage the membrane for analysis.

Direct contact membrane distillation (DCMD) technology has the potential to disrupt the water treatment industry by greatly reducing the cost of seawater desalination and industrial wastewater treatment. However, in order for DCMD technology to be developed for these applications, better characterizations of DCMD treatment capabilities are needed. Prior research has shown that DCMD technology has high salt rejection, but few studies have addressed the potential for volatile and semi-volatile contaminant accumulation in the DCMD effluent. Accounting for additional treatment processes to reduce the concentration of these volatile contaminants is vital for determining the cost-effectiveness of DCMD systems.

To improve characterizations of DCMD treatment capabilities, the work in this dissertation describes a novel method for predicting the quality of DCMD effluent and develops feed water guidelines for DCMD applications. The DCMD effluent contaminant concentration was modeled using a mass balance approach to account for the Fickian diffusion of contaminants into the permeate collection stream and the contaminant losses due to evaporation and sorption during DCMD operation. This represents a novel approach to modeling the quality of effluent produced by the DCMD system. Validation of the contaminant concentration model showed that the model had good agreement with the results from bench-scale DCMD testing (within 12% average normalized root-mean-squared-error).

The validated contaminant concentration model was used to assess the performance of commercial-scale DCMD systems and identify contaminants that accumulated the most in the DCMD effluent. The results showed that compounds with very low Henry’s constants (Henry’s constants less than 28PaL/mol) were rejected by the DCMD system, while the concentrations of more volatile compounds were magnified in the DCMD effluent. These findings illustrate that contaminant accumulation in DCMD effluent is a significant issue that must be considered when designing DCMD systems.

To address the high contaminant magnification, the operating conditions of the DCMD system were optimized to reduce the contaminant concentration. Operating the DCMD system using conditions that minimized the contaminant accumulation, instead of conditions that maximized the water flux, decreased the accumulation of some contaminants by over 3x. The contaminant accumulation at these conditions was used to identify the maximum feed water contaminant concentrations for two prominent DCMD applications, seawater desalination and oil and gas produced water treatment. These feed water quality guidelines are an important tool for determining what applications DCMD is suitable for.

The contaminant concentrations in representative seawaters and produced waters were compared to the feed water guidelines for a stand-alone DCMD system to determine if these waters were adequately treated by DCMD for either potable water usage or discharge to publicly owned treatment works. The results of the comparison showed that the contaminant concentrations in the seawaters were within the feed water guidelines, indicating that DCMD seawater desalination is a good treatment method for producing potable water. However, the contaminant concentrations in the produced waters were greater than the limits described in the produced water treatment feed water guidelines. This finding indicated that additional treatment should be used in conjunction with DCMD processing of produced waters, which may increase treatment costs. The contaminant concentration model for predicting the contaminant concentration in the DCMD effluent and the feed water quality guidelines provide a significant advance in characterizing the performance capabilities of DCMD systems, and using these tools is vital for determining applications for DCMD technology.

When considering the complex communication patterns between diverse collections of organisms in the environment, extracellular vesicles must be considered. Extracellular vesicles (EVs) are nanoscale, colloidal particles that are secreted by all cell types. While the functions of EVs have been investigated in a variety of environmental contexts, including nutrient scavenging, immune responses, and genetic material delivery, the exact mechanisms by which they are transported in the environment have been overlooked. This prevents a deeper understanding of the intercellular or inter-organismal communication that occurs in different environmental compartments and highlights a need to investigate EV transport. To be able to evaluate or predict transport most effectively, a foundational understanding of the surface properties of EVs must be first established. Through this dissertation, factors (pH, ionic strength, organic content) influencing the surface properties of EVs are investigated to better determine their transport tendencies in the environment. Moreover, three organisms’ EVs (Gram-negative bacteria Pseudomonas fluorescens, Gram-positive bacteria Staphylococcus aureus, and yeast Saccharomyces cerevisiae) are studied to provide a kingdom-spanning perspective on the range of possible surface properties, and thus transport patterns.

To evaluate their surfaces, two primary colloidal properties of EVs were studied: zeta potential and attachment efficiency. A proxy for surface charge, zeta potential provides initial characterizations for the electrostatic trends of EVs. From these data, conditions where humic acid concentration are high or ionic strength is low seem to most impact zeta potential values, while other conditions have a minimal impact on EV zeta potential. In addition, the relationship of the zeta potential of EVs to that of their corresponding parent cell is significantly different for all three organisms in this study. For attachment efficiency, the deposition potential of EVs generally seems to correlate with the electrostatic trends. For higher concentrations of humic acid and for EVs from P. fluorescens, other forces including steric or hydrophobic forces may be at play, causing deviations from expected attachment efficiencies. Beyond these two metrics, the effect of EV preparation methods is described, showing that upstream preparation methods, in particular varied size exclusion steps, influence downstream measurements. Finally, from these data, a model for EV transport is developed, showing both possible concentration profiles of EVs through a hypothetical soil column, but also the sensitivity of EVs to changes in system parameters such as flow velocity and attachment efficiency.

From these findings, EVs can clearly be transported long distances, but are heavily influenced by a variety of factors, with low ionic strength, organic content, and variations in pH seeming to cause the largest changes to surface properties. For the three organisms in this study, a range of surface chemistries exists. These results have implications for future study of EVs in the environment. The diversity of EVs will likely mirror that of the cells from which they come, resulting in different capacities for transport. These trends seem to be species-dependent, calling for much more colloidal evaluation of various microbes. The conditions examined and the model developed in this dissertation can help to guide any future work for engineering EVs for specified fate outcomes as well. But, any future study of EVs in the environment must carefully consider what biases may be introduced from EV preparation methods.

As the use of renewable energy is spreading, the degrading effects of pollutant accumulation on the surface of photovoltaic (PV) panels become more apparent, especially in arid climates. Dust deposition reduces light transmittance to the panel and decreases the energy output. Cleaning of PV modules can cost millions of dollars per year; therefore, it is important to study the reversibility of the soiling process. Mitigation strategies would not only increase energy production and revenues, but also the attractiveness of more PV installations due to lengthened optimal performance. Hence, soiling losses are widely monitored to understand the complex process driven by several factors, such as system design, soiling material, or environmental conditions. This work aims to fill the gap in knowledge on how the reversibility of solar panel fouling varies with the composition of dust in the atmosphere and panel surface features. The primary objectives of this study were to (1) characterize the attachment efficiency of dust particles at different locations; (2) determine whether particle composition influences particle-surface interactions through direct adhesion force measurements; (3) relate particle adhesion to particle detachment through centrifugation; (4) evaluate the feasibility of the centrifugal detachment technique to analyze PV panel coating performance and durability. The experimental methods were first tested using model pollutants that represented the major classes of soiling material, followed by dust samples obtained from the field. In addition to the laboratory studies, the impact of prolonged outdoor exposure was also tested to consider the complex mechanisms relevant to PV panel soiling. The comparison of predicted soiling loss based on a dust deposition model with collected soiled mass revealed that the attachment efficiency of dust varies seasonally and spatially, which could be influenced by changes in dust composition. This was confirmed by adhesion and detachment studies, as organic and carbon-based materials exhibited a significantly larger adhesion force to the glass surface than the rest of the samples. The centrifugal detachment technique could successfully measure the soiling rate on coated solar panels both with model pollutants and outdoor exposure. Coatings significantly differed in their ability to decrease particle accumulation on the surface, but all treatments lost at least 30% of their original hydrophobicity at the end of the 34-week exposure period. The results suggest that local dust composition influences solar panel soiling and should be considered for predictive models and maintenance needs. In addition, detachment studies could be used to establish a metric to quantitatively describe the efficiency of various PV panel surface treatments.

The ability of photocatalytic nanoparticles (NPs) to produce reactive oxygen species (ROS) has inspired research into several new applications and technologies, including water purification, contaminant remediation, and self-cleaning surface coatings. As a result, NPs continue to be incorporated into a wide variety of increasingly complex products. With the increased use of NPs and nano-enabled products and their subsequent disposal, NPs will make their way into the environment. Currently, many unanswered questions remain concerning how changes to the NP surface chemistry that occur in natural waters will impact reactivity. This work seeks to investigate potential influences on photoreactivity – specifically the impact of functionalization, the influence of anions, and interactions with biological objects - so that ROS generation in natural aquatic environments may be better understood.

To this aim, titanium dioxide nanoparticles (TiO2) and fullerene nanoparticles (FNPs) were studied in terms of their reactive endpoints: ROS generation measured through the use of fluorescent or spectroscopic probe compounds, virus and bacterial inactivation, and contaminant degradation. Physical characterization of NPs included light scattering, electron microscopy and electrophoretic mobility. These systematic investigations into the effect of functionalization, sorption, and aggregation on NP aggregate structure, size, and reactivity improve our understanding of trends that impact nanoparticle reactivity.

Engineered functionalization of FNPs was shown to impact NP aggregation, ROS generation, and viral affinity. Fullerene cage derivatization can lead to a greater affinity for the aqueous phase, smaller mean aggregate size, and a more open aggregate structure, favoring greater rates of ROS production. At the same time however, fullerene derivatization also decreases the 1O2 quantum yield and may either increase or decrease the affinity for a biological surface. These results suggest that the biological impact of fullerenes will be influenced by changes in the type of surface functionalization and extent of cage derivatization, potentially increasing the ROS generation rate and facilitating closer association with biological targets.

Investigations into anion sorption onto the surface of TiO2 indicate that reactivity will be strongly influenced by the waters they are introduced into. The type and concentration of anion impacted both aggregate state and reactivity to varying degrees. Specific interactions due to inner sphere ligand exchange with phosphate and carbonate have been shown to stabilize NPs. As a result, waters containing chloride or nitrate may have little impact on inherent reactivity but will reduce NP transport via aggregation, while waters containing even low levels of phosphate and carbonate may decrease “acute” reactivity but stabilize NPs such that their lifetime in the water column is increased.

Finally, ROS delivery in a multicomponent system was studied under the paradigm of pesticide degradation. The presence of bacteria or chlorpyrifos in solution significantly decreased bulk ROS measurements, with almost no OH detected when both were present. However, the presence of bacteria had no observable impact on the rate of chlorpyrifos degradation, nor chlorpyrifos on bacterial inactivation. These results imply that investigating reactivity in simplified systems may significantly over or underestimate photocatalytic efficiency in realistic environments, depending on the surface affinity of a given target.

This dissertation demonstrates that the reactivity of a system is largely determined by NP surface chemistry. Altering the NP surface, either intentionally or incidentally, produces significant changes in reactivity and aggregate characteristics. Additionally, the photocatalytic impact of the ROS generated by a NP depends on the characteristics of potential targets as well as on the characteristics of the NP itself. These are complicating factors, and the myriad potential exposure conditions, endpoints, and environmental systems to be considered for even a single NP highlight the need for functional assays that employ environmentally relevant conditions if risk assessments for engineered NPs are to be made in a timely fashion so as not to be outpaced by, or impede, technological advances.

Chemicals in consumer products can influence our risk for developing adverse health conditions. This research addresses knowledge gaps in our ability to evaluate chemical safety, particularly for emerging substances on the market. Acknowledging the need for more high-throughput exposure and hazard models to support risk assessment, computational frameworks leveraging machine learning strategies and "big data" from public databases and mass social data sources were tested.

First, to understand consumer exposure, we require a better understanding of ingredient concentrations in products. A computational framework was developed to estimate chemical weight fractions for consumer products containing emerging substances. Nanomaterial-enabled products were used as a case study to represent such substances with limited physicochemical property data. Feature variables included chemical properties, functional use categories (e.g., antimicrobial), the type of product and its matrix. Weight fractions were classified as low, medium or high using a random forest or nonlinear support vector classifier. Performance of machine learning models was qualitatively compared with that of models from a second framework trained on data-rich, bulk-scale organic chemical product data. Models could roughly stratify material-product observations into weight fraction bins with moderate success. The best model achieved an average balanced accuracy of 73% on nanomaterials product data. Chemical functional use features served as particularly insightful predictors, suggesting that functional use data may be useful in evaluating the safety and sustainability of emerging chemicals. Investment in chemical and product data collection could see continued improvement of such machine learning models.

Shifting focus to the impact of chemicals on consumers, data on personal care products, ingredients, and customer reviews from online retailers and databases was collected to see if certain chemicals might increase risk of adverse reactions to products. The study scope was narrowed to shampoo products for hypothesis testing. Processing steps in the data pipeline included informatics and machine learning methods, namely, natural language processing for interpreting product reviews, text extraction from images of product labels, and feature reduction using chemical structure and ingredient source data. Fifty-one ingredient clusters were identified as having a significant correlation with higher adverse reaction rates in consumers when present in shampoos. Among these, there were a few common plant-based ingredients and synthetic preservatives known for causing skin sensitivity or irritation. In comparison with other constituents, however, the positively correlated ingredient groups had a general lack of published structural, physicochemical property and toxicity data. Results suggest an urgent need for targeted, higher-throughput chemical evaluations to safeguard consumers.

Together, these proof-of-concept studies progress our ability to quantify exposure and hazard of emerging and data-poor substances in consumer products. The outcomes of the computational frameworks can help prioritize potentially problematic substances for additional study to characterize risk.

Microplastics (MPs) are becoming an emerging problem due to increased consumption of plastic. Despite research on MPs acting as sinks of contaminants, the potential of leaching additives out of MPs has been given little attention. Given challenges like the slow release rates of additives and the variety of physical chemical properties of MPs, mathematical models are great tools to explore this problem. In this study, the internal controlled diffusion model was used to describe release behaviors of additives from MPs into aqueous environments. This model was then applied to study Bisphenol A (BPA) and 4-t-butylphenol (TBP) leaching from epoxy MPs. Simulations on the influence of properties of microplastics and various temperatures were completed. Calculated diffusion coefficients of BPA and TBP based on leaching experiments data range from 10-13.3 cm2/s to 10-14.3 cm2/s and 10-12.1 cm2/s to 10-12.7 cm2/s, respectively. Though at low release rates, the release process was accelerated significantly by smaller sizes and irregular shapes of MPs. With a particle radius reduced from 1mm to 100 nm, the half-life of BPA changes from 3000 years to several minutes, and from 30 years to several seconds for TBP. Also, temperature dependence of migration obeys the Arrhenius equation and activated energies for BPA and TBP are 48.9 kJ/mol and 27.0 kJ/mol, respectively. To sum up, simpler plastic structures, smaller sizes, rough surfaces, smaller additive molecules, and the higher temperature facilitate the release process. This model contributes to the risk assessment of additives releasing from MPs. Yet the real problem might be far more complex considering special properties of plastics materials and environmental conditions. Thus, more research is required for a deeper understanding of this problem.