Bed load sediment particles move as complex motions over the surface of a stream bed, accelerating and decelerating in response to the near-bed turbulence and due to particle-bed interactions. Detailed measurements of individual sand grains moving on a streambed allow us to obtain a deeper understanding of the characteristics of particle motions and evaluate spatial and temporal properties of particle diffusion, entrainment and disentrainment. I track bed load particle motions, measured start-to-stop, from high-speed (250 Hz) imaging of uniform, coarse-grained sand from two flume experiments, which have different mean fluid velocities near the bed. This work utilizes rich data sets to provide foundational support for a statistical mechanics approach to bed load transport. First, using these data, we characterize the underlying ensemble distributions of key measures of particle motions (particle velocities, accelerations, hop distances, and travel times). These distributions best represent the probabilistically expected behavior of sediment motions consistent with the macroscopic sediment and flow conditions, and thus provide a clear target for further analyses of transport, including statistical mechanics theory and numerical simulations. We then investigate the diffusive contribution to the sediment flux to demonstrate that conventional measures of particle spreading reveal different attributes of bed load particle behavior depending on details of the calculation. Our results indicate that while there are similarities between bed load transport and Brownian systems, care is needed in suggesting anomalous behavior when appealing to conventional measures of diffusion formulated for ideal particle systems. Finally, we analyze patterns and controls on sediment entrainment and disentrainment. Here we focus on entrainment and disentrainment in relation to near-bed fluid velocity measurements. This suggests that the connection between the fluid and particle entrainment is complex and will require a clearer understanding of the factors that jointly influence entrainment at the particle scale. Furthermore, this highlights and reveals important aspects of the mechanical behavior of particles during entrainment and disentrainment, and ultimately shows that these processes involve more than 'starting' and 'stopping'.

Urban arterial corridors are landscapes that give rise to short and long-term exposures to transportation-related pollution. With high traffic volumes, congestion, and a wide mix of road users and land uses at the road edge, urban arterial environments are important targets for improved exposure assessment to traffic-related pollution. Applying transportation management strategies to reduce emissions along arterial corridors could be enhanced if the ability to quantify and evaluate such actions was improved. However, arterial roadsides are under-sampled in terms of air pollution measurements in the United States and using observational data to assess such effects has many challenges such as lack of control sites for comparisons and temporal autocorrelation. The availability of traffic-related data is also typically limited in air monitoring and health studies. The work presented here uses unique long-term roadside air quality monitoring collected at the intersection of an urban arterial in Portland, OR to characterize the roadside atmospheric environment. This air quality dataset is then integrated with traffic-related data to assess various methods for improving exposure assessment and the roadside environment. Roadside nitric oxide (NO), nitrogen dioxide (NO2), and particle number concentration (PNC) measurements all demonstrated a relationship with local traffic volumes. Seasonal and diurnal characterizations show that roadside PM2.5 (mass) measurements do not have a relationship with local traffic volumes, providing evidence that PM2.5 mass is more tied to regional sources and meteorological conditions. The relationship of roadside NO and NO2 with traffic volumes was assessed over short and long-term aggregations to assess the reliability of a commonly employed method of using traffic volumes as a proxy for traffic-related exposure. This method was shown to be insufficient for shorter-time scales. Comparisons with annual aggregations validate the use of traffic volumes to estimate annual exposure concentrations, demonstrating this method can capture chronic but not acute exposure. As epidemiology and exposure assessment aims to target health impacts and pollutant levels encountered by pedestrians, cyclists, and those waiting for transit, these results show when traffic volumes alone can be a reliable proxy for exposure and when this approach is not warranted. Next, it is demonstrated that a change in traffic flow and change in emissions can be measured through roadside pollutant concentrations suggesting roadside pollution can be affected by traffic signal timing. The effect of a reduced maximum traffic signal cycle length on measurements of degree of saturation (DS), NO, and NO2 were evaluated for the peak traffic periods in two case studies at the study intersection. In order to reduce bias from covariates and assess the effect due to the change in cycle length only, a matched sampling method based on propensity scores was used to compare treatment periods (reduced cycle length) with control periods (no change in cycle length). Significant increases in DS values of 2-8% were found along with significant increases of 5-8ppb NO and 4-5ppb NO2 across three peak periods in both case studies. Without matched sampling to address the challenges of observational data, the small DS and NOx changes for the study intersection would have been masked and matched sampling is shown to be a helpful tool for future urban air quality empirical investigations. Dispersion modeling evaluations showed the California Line Source Dispersion Model with Queuing and Hotspot Calculations (CAL3QHCR), an approved regulatory model to assess the impacts of transportation projects on PM2.5, performed both poor and well when predictions were compared with PM2.5 observations depending on season. Varying levels of detail in emissions, traffic signal, and traffic volume data for model inputs, assessed using three model scenarios, did not affect model performance for the study intersection. Model performance is heavily dependent on background concentrations and meteorology. It was also demonstrated that CAL3QHC can be used in combination with roadside PNC measurements to back calculate PNC emission factors for a mixed fleet and major arterial roadway in the U.S. The integration of roadside air quality and traffic-related data made it possible to perform unique empirical evaluations of exposure assessment methods and dispersion modeling methods for roadside environments. This data integration was used for the assessment of the relationship between roadside pollutants and a change in a traffic signal setting, a commonly employed method for transportation management and emissions mitigation, but rarely evaluated outside of simulation and emissions modeling. Results and methods derived from this work are being used to implement a second roadside air quality station, to design a city-wide integrated network of air quality, meteorological, and traffic data including additional spatially resolved measurements with feedback loops for improved data quality and data usefulness. Results and methods are also being used to design future evaluations of transportation projects such as freight priority signaling, improved transit signal priority, and to understand the air quality impacts of changes in fleet composition such as an increase in electric vehicles.

<p>Over three hundred million people throughout the world receive supply from piped drinking water distribution networks that operate intermittently. This dissertation evaluates the effects of intermittent supply on water quality, pipe damage and service reliability in four study zones (one continuous and three intermittent) in a peri-urban drinking water distribution network in Arraijan, Panama. Normal water quality in all zones was good, with 97% of routine water quality grab samples from the distribution system and household taps having turbidity < 1 NTU, total coliform and E. coli bacteria concentrations < 1 MPN / 100 mL, and ? 0.3 mg/L free chlorine residual. However, negative pressures that represent a risk for contaminant intrusion and backflow were detected in three of the four study zones, and water quality during the first flush when supply resumed after an outage was sometimes degraded. High and transient pressures that could cause pipe damage were detected in study zones with intermittent pumping, but filling and emptying of distribution pipes due to intermittent supply was not associated with transient or extreme pressures. Operational challenges, including frequent infrastructure failures, difficulty monitoring the network, and a lack of system information, resulted in unreliable supply in the intermittent zones. Continuous pressure and flow monitoring methods used in this research could be helpful tools for operators of intermittent distribution networks to provide more reliable service and identify hydraulic conditions that could lead to contaminant intrusion or pipe breaks.

<p> Though humans have over a century of experience with catastrophic marine and terrestrial oil spills, response plans and cleanup techniques are still active areas of research and development. This work evaluated the oil degradation potential and changes in the microbial community following nutrient additions in polluted marine sediment and desert soil. </p><p> Biostimulation experiments on Alaskan beach sediment still contaminated by the <i>Exxon Valdez</i> tanker oil spill demonstrated that ambient air and hydrogen peroxide both serve as suitable sources of oxygen to stimulate aerobic microbial degradation of the oil. The addition of oxygen to the oil-contaminated sediment stimulated the growth of Proteobacteria, which made up 77-92% of the population in the presence of ambient oxygen and 76-88% with hydrogen peroxide. These experiments also revealed that sediment samples collected from a non-contaminated portion of the beach also contained a large fraction of microbial species that are known oil degraders. A phytoremediation experiment using mesquite trees in motor-oil-contaminated desert soil indicated that the use of compost as a soil amendment enhanced oil degradation, while biochar hindered degradation activity.</p>

<p>Soil erosion by water is a major driven force causing land degradation. Laboratory experiments, on-site field study, and suspended sediments measurements were major fundamental approaches to study the mechanisms of soil water erosion and to quantify the erosive losses during rain events. The experimental research faces the challenge to extent the result to a wider spatial scale. Soil water erosion modeling provides possible solutions for scaling problems in erosion research, and is of principal importance to better understanding the governing processes of water erosion. However, soil water erosion models were considered to have limited value in practice. Uncertainties in hydrological simulations are among the reasons that hindering the development of water erosion model. Hydrological models gained substantial improvement recently and several water erosion models took advantages of the improvement of hydrological models. It is crucial to know the impact of changes in hydrological processes modeling on soil erosion simulation. </p><p>This dissertation work first created an erosion modeling tool (GEOtopSed) that takes advantage of the comprehensive hydrological model (GEOtop). The newly created tool was then tested and evaluated at an experimental watershed. The GEOtopSed model showed its ability to estimate multi-year soil erosion rate with varied hydrological conditions. To investigate the impact of different hydrological representations on soil erosion simulation, a 11-year simulation experiment was conducted for six models with varied configurations. The results were compared at varied temporal and spatial scales to highlight the roles of hydrological feedbacks on erosion. Models with simplified hydrological representations showed agreement with GEOtopSed model on long temporal scale (longer than annual). This result led to an investigation for erosion simulation at different rainfall regimes to check whether models with different hydrological representations have agreement on the soil water erosion responses to the changing climate. Multi-year ensemble simulations with different extreme precipitation scenarios were conducted at seven climate regions. The differences in erosion simulation results showed the influences of hydrological feedbacks which cannot be seen by purely rainfall erosivity method.</p> / Dissertation

Pesticides are used globally and are often found within bodies of water. The EPA investigates the potential environmental impact through computer modeling in order to help mitigate some of the regulatory burden of pesticide fate investigation. Currently when pesticides enter a water body, the Exposure Analysis Modeling System (EXAMS) estimates partitioning depth as 5 cm and assumes equal distribution. This assumption was tested with a wide variety of pesticides with varying Koc ranges and water solubilities. Savillex 150 ml Teflon tubes were filled with wetland and ricefield sediments with fresh and seawater as the aqueous phase. The seven pesticides tested included, quinclorac, bentazon, 2,4-D, atrazine, dicloran, flutolanil, and trifluralin had reported Koc ranges as low as 20 and as high as 15800. Pesticides were sprayed onto the top layer of water and allowed to partition over 24 hours. Once suspended, 0.5 cm segments were sonicated and analyzed by Agilent 1260 Infinity High Performance Liquid Chromatography. Normalized applied mass percentages were calculated by comparison to pesticide standards that ran simultaneously with all samples. The majority of pesticides were found in the overlying water layer and within the first 0.5 cm of sediment. Salinity of the aqueous phase was shown to increase pesticide sediment concentration, but did not increase partitioning depth.

<p> The objective of this doctoral dissertation is to develop a model to predict the phototoxicity of petroleum and petroleum components to aquatic organisms. Petroleum contains polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs and heterocyclic PAHs some of which absorb light in the ultraviolet light (UV) and visible (VIS) regions. The result is increased photo-enhanced toxicity, by a factor of two to greater than 1000 in the presence of light.</p><p> The PAHs in petroleum differ in their properties, such as octanol-water partitioning coefficients and molar absorption spectra, and each may exhibit phototoxicity. It is inefficient and impractical to conduct toxicity tests on all the chemicals and all the organisms of concern. Even if the testing was undertaken, it is not clear how to interpret the results and use them for phototoxic risk assessments where light conditions and time of exposure vary. Accordingly, there has been a considerable effort expended to develop models to predict the phototoxicity of PAHs to the aquatic organisms. In each of the previous modeling frameworks various combination of the underlying factors in phototoxicity were incorporated to varying degrees. However, no model included all elements in a unified modeling framework such that the model can be applicable to all PAHs, PAH mixtures, organisms, and light exposure conditions.</p><p> In this dissertation, a phototoxic target lipid model (PTLM) is developed to predict phototoxicity of single PAHs measured either as median lethal concentration (LC50) at a fixed duration of exposure or median lethal time (LT50) at a fixed concentration. The model accounts for differences in the physical and chemical properties of PAHs and test species sensitivities, as well as variations in light characteristics, such as length of exposure, and the light source irradiance spectrum and intensity. The PTLM is based on the narcotic target lipid model (NTLM) of PAHs. Both models rely on the assumption that mortality occurs when the toxicant concentration in the target lipid of the organism reaches a threshold concentration. The model is calibrated using 333 observations of LC50s and LT50s for 20 individual PAHs, 15 test species, and various UV light exposure conditions and times ranging from 1 hour to 100 hours. The LC50 concentrations range from less than 0.1 to greater that 10⁴ &mu;g/L. The model has two fitting parameters that are shown to be constant across PAHs and organisms. The compound specific parameters incorporated in the PTLM are the octanol-water partition coefficient and molar absorption coefficient. The critical target lipid body burden is the only organism specific parameter. The root mean square error (RMSE) of prediction for log(LC50) and log(LT50) are 0.473 and 0.382, respectively. Other phototoxic components of petroleum include alkylated PAHs (APAHs) and benzothiophenes. The PTLM is validated by predicting the observed phototoxic LT50 and LC50 of those chemicals exposed to four different species under different light conditions with RMSE = 0.478. The results support the PTLM capability to predict the phototoxicity of single PAHs for organisms with a wide range of sensitivity and for various light exposure conditions. </p><p> Modeling the phototoxicity of mixtures is accomplished by using the toxic unit (TU) approach and TU additivity. The model is validated by predicting the phototoxicity of the binary and ternary mixtures of three PAHs, pyrene, anthracene, and fluoranthene exposed to <i>Americamysis bahia</i> and <i>Menidia beryllina</i>. The comparison between the observed and predicted phototoxicity for the mixtures results in RMSE = 0.274.</p><p> The PTLM is applied to predict petroleum phototoxicity of the water accommodated fraction for three field collected oil samples, MASS (neat oil), CTC (moderately weathered oil), and Juniper (heavily weathered oil) exposed to four aquatic species indigenous to the Gulf of Mexico, <i>M. beryllina</i>, <i> A. bahia</i>, <i>Cyprinodon variegatus</i>, and <i>Fundulus grandis</i> using natural or simulated solar radiation. For cases in which no phototoxicity was observed, the PTLM predictions are correct in over 70% of the cases (10 out of 14 predictions). When toxicity was observed the RMSE = 0.321.</p>

As the environmental justice movement has spread and become more mainstream since its start in the 1980s, its framework and body of knowledge has expanded, and environmental justice activists, organizers, and scholars have developed and critiqued different methods through which environmental justice can be pursued. Among its relatively new concepts is the idea of slow violence, or the long-term and continuous impacts of environmental injustices on an afflicted community; and among the methods examined by scholars is environmental justice litigation, where legal action is taken, often with members of an affected community as plaintiffs, to remedy environmental injustices within that area. This thesis aims to analyze the efficacy of environmental justice litigation in its ability to address slow violence through two case studies, Hinkley Groundwater Contamination and Kettleman Hills Waste Facility, which both took place in the 1990s in California, a state now known for its progressive legislation and consideration of environmental justice. It concludes that, while the short-term nature of litigation is not necessarily compatible with the long-term nature of slow violence, successful litigation coupled with the empowerment and engagement of the local community increase the likelihood of litigation partially addressing and mitigating the effects of slow violence in the present and future.

No description available.

<p>The rapid development of nanotechnology and wider applications of engineered nanomaterials (ENMs) in the last few decades have generated concerns regarding their environmental and health risks. After release into the environment, ENMs undergo aggregation, transformation, and, for metal-based nanomaterials, dissolution processes, which together determine their fate, bioavailability and toxicity to living organisms in the ecosystems. The rates of these processes are dependent on nanomaterial characteristics as well as complex environmental factors, including natural organic matter (NOM). As a ubiquitous component of aquatic systems, NOM plays a key role in the aggregation, dissolution and transformation of metal-based nanomaterials and colloids in aquatic environments.</p><p>The goal of this dissertation work is to investigate how NOM fractions with different chemical and molecular properties affect the dissolution kinetics of metal oxide ENMs, such as zinc oxide (ZnO) and copper oxide (CuO) nanoparticles (NPs), and consequently their bioavailability to aquatic vertebrate, with Gulf killifish (Fundulus grandis) embryos as model organisms.</p><p>ZnO NPs are known to dissolve at relatively fast rates, and the rate of dissolution is influenced by water chemistry, including the presence of Zn-chelating ligands. A challenge, however, remains in quantifying the dissolution of ZnO NPs, particularly for time scales that are short enough to determine rates. This dissertation assessed the application of anodic stripping voltammetry (ASV) with a hanging mercury drop electrode to directly measure the concentration of dissolved Zn in ZnO NP suspensions, without separation of the ZnO NPs from the aqueous phase. Dissolved zinc concentration measured by ASV ([Zn]ASV) was compared with that measured by inductively coupled plasma mass spectrometry (ICP-MS) after ultracentrifugation ([Zn]ICP-MS), for four types of ZnO NPs with different coatings and primary particle diameters. For small ZnO NPs (4-5 nm), [Zn]ASV was 20% higher than [Zn]ICP-MS, suggesting that these small NPs contributed to the voltammetric measurement. For larger ZnO NPs (approximately 20 nm), [Zn]ASV was (79±19)% of [Zn]ICP-MS, despite the high concentrations of ZnO NPs in suspension, suggesting that ASV can be used to accurately measure the dissolution kinetics of ZnO NPs of this primary particle size.</p><p>Using the ASV technique to directly measure dissolved zinc concentration, we examined the effects of 16 different NOM isolates on the dissolution kinetics of ZnO NPs in buffered potassium chloride solution. The observed dissolution rate constants (kobs) and dissolved zinc concentrations at equilibrium increased linearly with NOM concentration (from 0 to 40 mg-C L-1) for Suwannee River humic acid (SRHA), Suwannee River fulvic acid and Pony Lake fulvic acid. When dissolution rates were compared for the 16 NOM isolates, kobs was positively correlated with certain properties of NOM, including specific ultraviolet absorbance (SUVA), aromatic and carbonyl carbon contents, and molecular weight. Dissolution rate constants were negatively correlated to hydrogen/carbon ratio and aliphatic carbon content. The observed correlations indicate that aromatic carbon content is a key factor in determining the rate of NOM-promoted dissolution of ZnO NPs. NOM isolates with higher SUVA were also more effective at enhancing the colloidal stability of the NPs; however, the NOM-promoted dissolution was likely due to enhanced interactions between surface metal ions and NOM rather than smaller aggregate size.</p><p>Based on the above results, we designed experiments to quantitatively link the dissolution kinetics and bioavailability of CuO NPs to Gulf killifish embryos under the influence of NOM. The CuO NPs dissolved to varying degrees and at different rates in diluted 5‰ artificial seawater buffered to different pH (6.3-7.5), with or without selected NOM isolates at various concentrations (0.1-10 mg-C L-1). NOM isolates with higher SUVA and aromatic carbon content (such as SRHA) were more effective at promoting the dissolution of CuO NPs, as with ZnO NPs, especially at higher NOM concentrations. On the other hand, the presence of NOM decreased the bioavailability of dissolved Cu ions, with the uptake rate constant negatively correlated to dissolved organic carbon concentration ([DOC]) multiplied by SUVA, a combined parameter indicative of aromatic carbon concentration in the media. When the embryos were exposed to CuO NP suspension, changes in their Cu content were due to the uptake of both dissolved Cu ions and nanoparticulate CuO. The uptake rate constant of nanoparticulate CuO was also negatively correlated to [DOC]×SUVA, in a fashion roughly proportional to changes in dissolved Cu uptake rate constant. Thus, the ratio of uptake rate constants from dissolved Cu and nanoparticulate CuO (ranging from 12 to 22, on average 17±4) were insensitive to NOM type or concentration. Instead, the relative contributions of these two Cu forms were largely determined by the percentage of CuO NP that was dissolved.</p><p>Overall, this dissertation elucidated the important role that dissolved NOM plays in affecting the environmental fate and bioavailability of soluble metal-based nanomaterials. This dissertation work identified aromatic carbon content and its indicator SUVA as key NOM properties that influence the dissolution, aggregation and biouptake kinetics of metal oxide NPs and highlighted dissolution rate as a useful functional assay for assessing the relative contributions of dissolved and nanoparticulate forms to metal bioavailability. Findings of this dissertation work will be helpful for predicting the environmental risks of engineered nanomaterials.</p> / Dissertation