Growing environmental and economic concerns have driven recent efforts to produce more fuel efficient and lower emissions vehicles. These goals are reflected by the Partnership for a New Generation of Vehicles (PNGV), a government, industry, and educational partnership in the United States. The major goal of this partnership is to have production vehicles by 2010 to address these concerns. Ideally, these vehicles will achieve three times the current fuel economy while drastically lowering emissions levels, without sacrificing the features, comfort, and performance of current conventional automobiles. Hybrid Electric Vehicles (HEVs) are automobiles which have both electric drivetrains and fuel-consuming powerplants. HEVs provide some of the most promising designs with the capability of meeting the PNGV goals. However, the development of these vehicles within the next ten years will require accurate, flexible simulation tools. Such a simulation program is necessary in order to quickly narrow the technology focus of the PNGV to those HEV configurations and components which are best suited for these goals. Therefore, the simulation must be flexible enough to encompass the wide variety of components which could possibly be utilized. Finally, it must be able to assist vehicle designers in making specific decisions in building and testing prototype automobiles. One of the most widely used computer simulation tools for HEVs is the ADvanced VehIcle SimulatOR (ADVISOR) developed by the National Renewable Energy Laboratory. This program is flexible enough to operate on most platforms in the popular MATLAB/SIMULINK programming environment. The structure of ADVISOR makes it ideal for interchanging a variety of components, vehicle configurations, and control strategies. Its modern graphical user interface allows for easy manipulation of various inputs and outputs. Also, the capability to quickly perform parametric and sensitivity studies for specific vehicles is a unique and invaluable feature of ADVISOR. However, no simulation tool is complete without being validated against measured vehicle data so as to ensure the reliability of its predictions. ADVISOR has been tested using data from a number of student-built HEVs from the top engineering colleges and universities around the country. As ADVISOR evolves to meet the changing needs of the vehicle design teams, this testing continues to ensure that ADVISOR maintains its usefulness as a simulation tool. One current validation study was recently completed at Virginia Tech using the FutureCar Challenge entry. This paper details the validation of ADVISOR using the Virginia Tech Lumina, a series HEV. The basic structure of the ADVISOR code is covered to ensure the validity of the vehicle modeling techniques used. The modeling process is discussed in detail for each of the major components of the hybrid system: transmission, electric motor and inverter, auxiliary power unit (fuel and emissions), batteries, and miscellaneous vehicle parameters. The integration of these components into the overall ADVISOR model is also described. The results of the ADVISOR simulations are then explained and compared to measured vehicle data on energy consumption, fuel efficiency, emissions output, and control strategy function for a variety of driving cycles and test procedures. Uncertainties in the measured data are discussed. Finally, the discrepancies between predicted and actual behavior are analyzed. This validation process shows that ADVISOR has extensive value as a simulation tool for HEVs. The existing limitations of the program are also detailed, with recommendations for improvement. / Master of Science

Nonpoint source nitrogen runoff from agriculture is a significant contributor to eutrophication in the Chesapeake Bay. The state of Virginia has developed several market and incentive-based water quality credit trading programs to meet federal water quality objectives. In theory, these programs offer a mechanism to achieve environmental goals at least cost. However, in practice these programs face ongoing challenges arising from limited participation by farmers who supply water quality credits and, as a result, often fail to achieve cost efficiency. We build a flexible, accessible, and modular bioeconomic modeling system as a proof-of-concept to evaluate economic-environmental tradeoffs farmers face in an effort to support program participation and achieve environmental goals. We couple a biophysical nitrogen mass-balance model with an agricultural production model and apply the tool to study diverse agroforestry practices. We evaluate the relative efficiency of these practices by empirically estimating a production possibility frontier. We then use our bioeconomic modeling results to define the minimum willingness to accept of farmers, in terms of water quality credit prices, to adopt agroforestry practices that deliver water quality improvements. We extend our model results to estimate water quality credit premiums to compensate risk-averse farmers for undertaking production practices subject to relatively volatile prices in niche fruit markets. We demonstrate that the model generally simulates real-world credit prices, and highlight potential improvements in design for Virginia's trading program. In particular, quality credit trading programs could be more effective and efficient if credits awards reflect heterogeneity in the environmental benefits associated with nuanced land-use alternatives. Our modeling tool offers a framework to support incentive programs that are both economically sound and biophysically grounded. / Master of Science / High levels of nitrogen in the Chesapeake Bay have become an environmental concern for regulatory agencies. A significant portion of nitrogen pollution in the Chesapeake Bay comes from agricultural activities in the Chesapeake Bay watershed. Agricultural nitrogen pollution is not directly regulated at the federal level, so some states have adopted market-based mechanisms to curb emissions. However, some of these programs are seeing less farmer participation than expected. We suggest that part of the low participation rates may be due to program design, and the impact risk plays in farmer decision-making. In an effort to better understand participation in the programs, we develop a method to model these programs’ environmental and economic outcomes. Our method couples a mechanistic model of nitrogen pollution with an agricultural production model and evaluates tradeoffs between economic and environmental values. We find that the modeling method shows promise as a tool for policymakers, researchers, and farmers interested in pollution abatement programs. As a proof-of-concept, we apply the model to a Virginia market-based program and test our low-participation hypotheses. We find that the programs may be more effective if they recognize a greater diversity of farming practices. Our modeling tool offers a framework to support pollution abatement programs that are both economically feasible and environmentally effective.

Ammonia (NH₃) emissions from animal manure, such as poultry litter, can cause air quality problems. These emissions also result in excessive nitrogen (N) loading into aquatic environments which can lead to water quality problems where N is the limiting nutrient for eutrophication, such as the Chesapeake Bay. Poultry litter treatment (PLT, sodium bisulfate) is an acidic amendment that is applied to litter in poultry houses to decrease NH3 emissions, but currently it can only be applied before birds are placed in the houses. This project analyzed the effect of multiple PLT applications on litter properties and NH₃ release in a controlled and field environment. Volatility chambers with acid traps were used to compare multiple, single, and no applications of PLT to poultry litter. Both single and reapplied PLT caused a greater moisture content and lower pH in litter. Additionally, the E.coli in litter was decreased significantly with both single and reapplied PLT. After 15 days, NH₃ released from litter treated with reapplied PLT was significantly less than litter with both single and no applications. Furthermore, NH₄⁺-N content of litter was greatest in litter treated with reapplied PLT increasing its fertilizer value. The efficacy of a new farm scale system capable of applying several additions of PLT to poultry litter throughout the growth of a flock was also evaluated. Though litter pH, E.coli, and NH₃ volatilization were temporarily decreased with PLT application, the overhead reapplication auger system is not recommended at this time due to moisture and corrosion problems. / Ph. D.

Formaldehyde, an important feedstock in industrial processes and manufacture, is widely present in numerous consumer products. Emitted by many types of consumer products and indoor materials, indoor air can contain high concentrations of formaldehyde. Exposure to formaldehyde is hazardous to human health. Thus knowledge of formaldehyde mass-transfer properties is critical to efforts to reduce formaldehyde emissions and establish related standards and regulations. The primary objectives of this project include: 1) documenting and validating procedures and methods for analyzing and measuring formaldehyde mass-transfer characteristics; 2) evaluating and comparing formaldehyde mass-transfer properties in different materials using micro-balance sorption/desorption tests; 3) investigating observed formaldehyde mass-transfer irreversibility and the recently developed formaldehyde polymerization theory. The procedures and methods for analyzing and measuring formaldehyde mass-transfer characteristics were developed in an effort to minimize experimental variability and were strictly followed during the research. The formaldehyde mass-transfer properties of five polymer materials (polycarbonate, polystyrene, poly(methyl methacrylate), polyethylene and polypropylene) were measured through sorption/desorption testing. Results indicated that formaldehyde solubility was highest in polyethylene while the rate of diffusion was the highest in polypropylene. Results also showed that the diffusion process in the selected polymer materials was irreversible in all cases. Furthermore, additional testing showed no detectable polyformaldehyde formation on polymer surfaces after exposure to formaldehyde. The causes of observed mass-transfer irreversibility need further study. / Master of Science

Fiber reinforced polymers (FRP) are an efficient and inexpensive method of repairing deteriorating infrastructure. FRP sheets can be applied to spalling bridge sections and columns to prevent further deterioration and increase stiffness. However, the effect of the environment on the long-term durability of FRP and how the various damage mechanisms initiate and develop are not known. Systems for structural health monitoring are being sought as a means of managing important components in transportation systems as assets in light of modern life cycle cost concepts. This study characterizes a fiber optic sensor for use in detecting acoustic emissions (AE) in FRP. The results of AE analysis (signal amplitude, frequency spectra, MARSE, and in-plane displacement) caused by simulated fiber fracture experiments and other types of mechanical loading in FRP test coupons are reported. The applications to the development of FRP structural health monitoring systems are also discussed. / Master of Science

Herz-Kreislauf-Erkrankungen zählen zu den häufigsten Todesursachen weltweit. Ein ihr zugrundeliegender pathologischer Prozess ist die Atherosklerose. Die Ruptur eines atheroskelrotischen Plaques kann lebensbedrohlich sein. Derzeit existieren weder ein evaluierter Biomarker noch eine Bildgebungstechnik, die das Risiko einer solchen Plaqueruptur und eines nachfolgenden akuten kardiovaskulären Ereignisses vorhersagen können. Um die bildgebenden Verfahren zur Detektion der Atherosklerose zu optimieren, wurde in dieser Dissertationsarbeit untersucht, ob der PET/CT-Tracer 68Ga-Pentixafor im Vergleich zu 18F-FDG bessere Ergebnisse in der Diagnostik der Atherosklerose erzielen kann. Insgesamt wurden 144 onkologische Patienten in die Studie einbezogen, bei denen die 18F-FDG-PET/CT sowie 68Ga-Pentifaxor-PET/CT aus klinischen Gründen indiziert waren. Befunde, bei denen eine gegenüber dem Hintergrund vermehrte Speicherung ohne physiologische Erklärung nachgewiesen werden konnte, wurden als positiv bewertet. Um Unterschiede zwischen den Patienten außer Acht lassen zu können, wurde die target-to-background-ratio (TBR) berechnet. Zur Beschreibung der Speicherintensität einer Läsion wurde der standardized uptake value (SUV) bestimmt. Nach Auswertung der Daten zeigte sich eine mäßige Korrelation der Anzahl von 68Ga-Pentixafor-positiven Läsionen mit der Anzahl der 18F-FDG positiven Läsionen. Die CXCR4-gerichtete Bildgebung mit 68Ga-Pentixafor identifizierte mehr Läsionen als die 18F-FDG-PET/CT. Bezüglich ihres Verteilungsmusters wiesen die beiden Tracer eine geringe Korrelation auf. Die Aufnahmeintensität beider Tracer korrelierte umgekehrt mit dem Ausmaß der Verkalkung. Stark verkalkte Plaques zeigten die niedrigste Traceraufnahme für beide PET-Tracer. Weitere Studien zur Aufklärung der zugrunde liegenden biologischen Mechanismen und Quellen der CXCR4-Positivität sind in hohem Maße gerechtfertigt. / Cardiovascular diseases are among the most common causes of death worldwide. A pathological process underlying these diseases is atherosclerosis. The rupture of an atherosclerotic plaque can be life-threatening. Currently, there is neither an evaluated biomarker nor an imaging technique that can predict the risk of such a plaque rupture and subsequent acute cardiovascular event. To optimize imaging methods for the detection of atherosclerosis, this dissertation investigated whether the PET/CT tracer 68Ga-Pentixafor can achieve better diagnostic results for atherosclerosis compared to 18F-FDG. A total of 144 oncological patients were included in the study, for whom 18F-FDG-PET/CT and 68Ga-Pentixafor-PET/CT were clinically indicated. Lesions showing increased uptake compared to the background without physiological explanation were rated as positive. To disregard differences between patients, the target-to-background ratio (TBR) was calculated. To describe the uptake intensity of a lesion, the standardized uptake value (SUV) was determined. After evaluating the data, a moderate correlation was observed between the number of 68Ga-Pentixafor-positive lesions and the number of 18F-FDG-positive lesions. CXCR4-targeted imaging with 68Ga-Pentixafor identified more lesions than 18F-FDG-PET/CT. Regarding their distribution patterns, the two tracers showed a low correlation. The uptake intensity of both tracers inversely correlated with the extent of calcification. Highly calcified plaques exhibited the lowest tracer uptake for both PET tracers. Further studies to elucidate the underlying biological mechanisms and sources of CXCR4 positivity are highly warranted.

Atmospheric dust is the largest contributor to global aerosols from land. Dust emissions rate and properties are influenced by meteorological conditions, parent soil, and landscape, and in turn, it affects impacts on climate, ecosystems, and human societies through various pathways. This dissertation aims to explore the coupled dynamics of dust particle emissions and their essential properties in relation to topography, ecosystem, and atmospheric conditions by integrating information across multiple scales. Specifically, three research projects are pursued. First, the modulation of dust emissions by non-photosynthetic vegetation (NPV) is evaluated by implementing a satellite-based total vegetation dataset, which includes NPV, into a regional atmospheric chemistry model. Simulations of the entire year 2016 over the conterminous United States demonstrate that NPV reduces dust emissions by 10-70% from most dust sources in the southwest, particularly in spring. Second, the relationship between topographic wind conditions (i.e., speed and direction with respect to surface slope) and dust particle size distribution is investigated using a decade's worth of dust reanalysis data covering North Africa. Findings indicate that the fraction of coarse dust in emissions increases with wind speed and slope, particularly under uphill winds, the latter highlighting the role of topography in enhancing vertical transport for larger particles. These positive correlations weaken during the afternoon and summer events, suggesting that turbulence associated with haboob events suspends coarse particles. Finally, a series of air samples collected in Tenerife, Spain is revisited for a detailed study on the associated dust plume characteristics, which would facilitate the understanding of how environmental factors during transport influence airborne microbial assemblages. Using back trajectory analysis and dust optical depth reanalysis data, air samples impacted by African dust are identified. Seasonal variations in trajectories and associated environmental conditions reveal highly variable trans-Atlantic airflows. Elevated altitudes, higher temperatures, and lower relative humidity (RH) along summer trajectories implied the presence of Saharan Air Layer, whereas the frequent occurrence of higher RH (> 40%) and light precipitation in spring indicate more deposition of dust and associated microbes during transport. Overall, this work highlights the importance of accurately representing of various environmental elements that interact with the dust cycle, such as vegetation and topographic winds, which improves our ability to predict and manage the impacts of dust as well as other components of the Earth system. / Doctor of Philosophy / Dust particles can be lifted by strong winds from dry lands, and they are a major contributor to the amount of particles in the air. Suspended dust particles can alter temperatures and weather patterns, reduce visibility, and cause health problems. When settling back to land or oceans, they can carry nutrients and microbes that influence the growth of plants and animals. The movement and properties of dust are subject to various elements of the environment, spanning from microscopic scale to global scale. This dissertation aims to explore the interactions between dust and a few of these environmental elements that are not well understood. Specifically, we first provide information about brown vegetation, which was previously lacking, to a dust model, and find that the dust emissions in the southwestern United States is reduced by 10-70%, particularly in spring. Second, we examine how the changes of wind over slopes influence the size of dust particles in the air by analyzing data for 10 years that combine information from models and satellite observations. We find that faster winds and uphill slopes lead to more large dust particles in the atmosphere. The third study analyzes the pathways of air samples from Africa to Tenerife, Spain, to understand how the transport of dust might affect the types of bacteria that travel with it across the ocean. We find that the airflows from Africa to Tenerife vary greatly from case to case, and the environmental conditions, such as precipitation and relative humidity, varying significantly across seasons and during the dust travel. Overall, this dissertation provides a deeper understanding of the complex ways dust interacts with our world, offering insights that can help us manage its impacts on climate, ecosystems, and human society more effectively.

Yes / This study aims to address a critical gap in the literature by examining the incorporation of uncertainty in measuring carbon emissions using the greenhouse gas (GHG) Protocol methodology across all three scopes. By comprehensively considering the various dimensions of CO2 emissions within the context of organizational activities, our research contributes significantly to the existing body of knowledge. We address challenges such as data quality issues and a high prevalence of missing values by using information entropy, techniques for order preference by similarity to ideal solution (TOPSIS), and an artificial neural network (ANN) to analyze the contextual variables. Our findings, derived from the data sample of 56 companies across 18 sectors and 13 Brazilian states between 2017 and 2019, reveal that Scope 3 emissions exhibit the highest levels of information entropy. Additionally, we highlight the pivotal role of public policies in enhancing the availability of GHG emissions data, which, in turn, positively impacts policy-making practices. By demonstrating the potential for a virtuous cycle between improved information availability and enhanced policy outcomes, our research underscores the importance of addressing uncertainty in carbon emissions measurement for advancing effective climate change mitigation strategies. / The full-text of this article will be released for public view at the end of the publisher embargo on 3 Aug 2025.

Nitric oxide (NO) is a minor species in the Earth’s atmosphere whose densities have been measured to closely reflect solar energy deposition above 100 km. It is an efficient emitter in the infrared where the thermosphere is optically thin, and serves as an important source of radiative cooling between 100 - 200 km. The primary mechanism of this cooling involves the conversion of kinetic energy from the background atmosphere into vibrational energy in NO, followed by the radiative de-excitation of the NO molecule. This results in the production of a 5.3 µm photon which escapes the thermosphere and results in a net cooling of the region. While this process causes the excitation of ground state NO to its first vibrational level, nascent vibrational excitation to the (v≥ 1) levels may also occur from the reactions that produce NO in the thermosphere. The NO(v≥ 1) molecules produced from this secondary process can undergo a radiative cascade and emit multiple photons, thus forming a significant fraction of the 5.3 µm emission from NO in the thermosphere. Existing thermospheric models consider the collisional excitation of NO to be the only source of the 5.3 µm emission and assume the contribution from nascent excitation to be negligible. These models also tend to use a rate coefficient for the collisional excitation that is significantly larger than the values suggested in literature in order to obtain a temperature profile that is in agreement with empirical data. We address these discrepancies by presenting an updated calculation of the chemically produced emission by accounting for the v ≤ 10 level populations. By incorporating this process into a three dimensional global upper atmospheric model, it is shown that the additional emission contributes between 5 − 40% of the daytime emission from nitric oxide under quiet solar conditions, and is a significant source of energy loss during periods of enhanced solar energy deposition. Accounting for this process however does not resolve the model-data discrepancy seen with regards to the recovery times of thermospheric densities following geomagnetic storms, suggesting that an improved treatment of nitric oxide chemistry is required to resolve this issue. In order to improve our understanding of the thermospheric energy budget, we also develop the Atmospheric Chemistry and Energetics (ACE) 1D model using up-to-date aeronomic results. The model self-consistently solves the 1D momentum and energy equations to produce a global average profile of the coupled thermosphere and ionosphere system in terms of its constituent densities and temperatures. The model calculations of neutral densities and exospheric temperatures are found to be in good agreement with empirical data for a wide range of solar activity. It is concluded from the present work that while the magnitude of the chemically produced emission from nitric oxide has previously been underestimated, its effect on the thermospheric energy budget is relatively small. Including the secondary emission in thermospheric models results in an average reduction of 3% in the exospheric temperatures, which does not completely offset the change introduced by using a smaller rate coefficient for the collisional excitation of NO. However, thermospheric temperatures can still be accurately modeled by including these changes as part of broader improvements to calculations of the thermospheric energy budget. / Ph. D. / Nitric oxide (NO) is a molecule that is produced in the Earth’s thermosphere (the region of the atmosphere above 100 kilometers) as a consequence of solar energy deposition. As an important source of radiative cooling, its presence significantly influences the temperature structure of the region. An accurate understanding of the associated energetics is thus vital towards the development of numerical models used to describe the thermosphere. Energy loss from the thermosphere due to nitric oxide begins with the vibrational excitation of the molecule either due to collisions or chemical processes, followed by the emission of one or more infrared photons which returns the molecule to the ground state. The photons produced escape the thermosphere resulting in a net energy loss from this region of the atmosphere. Existing thermospheric models generally account for the vibrational excitation of nitric oxide only via collisions, and have assumed chemical processes to be a negligible source of thermospheric energy loss. These models also assume a rate of collisional excitation that is significantly larger than the values suggested in literature in order to obtain a temperature profile that is in agreement with empirical data. The present work demonstrates that the chemical excitation in fact contributes to between 5 − 40% of the total energy loss due to nitric oxide under quiet solar conditions on the dayside of the Earth, and is also an important energy loss mechanism during periods of enhanced solar activity. However, including this mechanism into existing models does not resolve outstanding model-data discrepancies regarding the rate at which the thermosphere returns to equilibrium following sudden enhancements in solar energy deposition. This suggests the need for an improved treatment of the nitric oxide chemistry in current thermospheric models. This work also presents the Atmospheric Chemistry and Energetics (ACE) 1D model, a new one dimensional upper atmospheric model developed in order to obtain a better understanding of the thermospheric energy budget. The model includes the effects of the chemically produced emissions from nitric oxide, and also uses a collisional cooling rate that is in line with the value suggested in literature. The model calculations of thermospheric densities and temperatures are shown to be in good agreement with empirical data over a wide range of solar activity.

Inland waters such as streams and lakes have recently been found to be supersaturated with both carbon dioxide (CO2) and methane (CH4) – the high concentrations resulting in significant natural emissions of greenhouse gases (GHGs). Previous studies have shown that streams emit particularly large amounts of GHGs per area covered, but the spatial variability is very high and has rarely been studied in detail. This study focuses on the variability of aquatic CO2 and CH4 concentrations with high spatial resolution in a hemi-boreal stream. The study area is a 7 km2 catchment in Skogaryd in southwest Sweden. 131 samples were collected and the stream was divided into groups depending on slope gradient and geographical placement. The results show that the concentrations had high spatial variability, especially regarding CH4, and that the concentrations are higher and more variable at lower slope gradients, which possibly indicates an increased gas exchange at higher slopes. The results also showed that concentrations can increase or decrease sharply over short distances in relation to changing slope gradient. This shows that frequent spatial sampling is needed to more accurately represent streams than what is often the case in many studies. A general distance between sampling locations could not be found due to the high variability of concentrations. Instead, the authors suggest that future studies of CO2 and CH4 concentrations in streams use a stratified random sampling strategy based on slope gradients.