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- All Subjects: Sustainability
- All Subjects: Environmental engineering
- Genre: Masters Thesis
- Language: English
Description
Biofuel from microbial biomass is a viable alternative to current energy production practices that could mitigate greenhouse gas levels and reduce dependency on fossil fuels. Sustainable production of microbial biomass requires efficient utilization of nutrients like phosphorus (P). P is a limited resource which is vital for global food security. This paper seeks to understand the fate of P through biofuel production and proposes a proof-of-concept process to recover P from microbial biomass. The photosynthetic cyanobacterium Synechocystis sp. PCC 6803 is found to contain 1.4% P by dry weight. After the crude lipids are extracted for biofuel processing, 92% of the intercellular P is found within the residual biomass. Most intercellular P is associated with nucleic acids which remain within the cell after lipids are extracted. Phospholipids comprise a small percentage of cellular P. A wet chemical advanced oxidation process of adding 30% hydrogen peroxide followed by 10 min of microwave heating converts 92% of the total cellular P from organic-P and polyphosphate into orthophosphate. P was then isolated and concentrated from the complex digested matrix by use of resins. An anion exchange resin impregnated with iron nanoparticles demonstrates high affinity for P by sorbing 98% of the influent P through 20 bed volumes, but only was able to release 23% of it when regenerated. A strong base anion exchange resin sorbed 87% of the influent P through 20 bed volumes then released 50% of it upon regeneration. The overall P recovery process was able to recover 48% of the starting intercellular P into a pure and concentrated nutrient solution available for reuse. Further optimization of elution could improve P recovery, but this provides a proof-of-concept for converting residual biomass after lipid extraction to a beneficial P source.
ContributorsGifford, James McKay (Author) / Westerhoff, Paul (Thesis advisor) / Rittmann, Bruce (Committee member) / Vannela, Ravindhar (Committee member) / Arizona State University (Publisher)
Created2012
Description
This study investigates how well prominent behavioral theories from social psychology explain green purchasing behavior (GPB). I assess three prominent theories in terms of their suitability for GPB research, their attractiveness to GPB empiricists, and the strength of their empirical evidence when applied to GPB. First, a qualitative assessment of the Theory of Planned Behavior (TPB), Norm Activation Theory (NAT), and Value-Belief-Norm Theory (VBN) is conducted to evaluate a) how well the phenomenon and concepts in each theory match the characteristics of pro-environmental behavior and b) how well the assumptions made in each theory match common assumptions made in purchasing theory. Second, a quantitative assessment of these three theories is conducted in which r2 values and methodological parameters (e.g., sample size) are collected from a sample of 21 empirical studies on GPB to evaluate the accuracy and generalize-ability of empirical evidence. In the qualitative assessment, the results show each theory has its advantages and disadvantages. The results also provide a theoretically-grounded roadmap for modifying each theory to be more suitable for GPB research. In the quantitative assessment, the TPB outperforms the other two theories in every aspect taken into consideration. It proves to 1) create the most accurate models 2) be supported by the most generalize-able empirical evidence and 3) be the most attractive theory to empiricists. Although the TPB establishes itself as the best foundational theory for an empiricist to start from, it's clear that a more comprehensive model is needed to achieve consistent results and improve our understanding of GPB. NAT and the Theory of Interpersonal Behavior (TIB) offer pathways to extend the TPB. The TIB seems particularly apt for this endeavor, while VBN does not appear to have much to offer. Overall, the TPB has already proven to hold a relatively high predictive value. But with the state of ecosystem services continuing to decline on a global scale, it's important for models of GPB to become more accurate and reliable. Better models have the capacity to help marketing professionals, product developers, and policy makers develop strategies for encouraging consumers to buy green products.
ContributorsRedd, Thomas Christopher (Author) / Dooley, Kevin (Thesis advisor) / Basile, George (Committee member) / Darnall, Nicole (Committee member) / Arizona State University (Publisher)
Created2012
Description
DehaloR^2 is a previously characterized, trichloroethene (TCE)-dechlorinating culture and contains bacteria from the known dechlorinating genus, Dehalococcoides. DehaloR^2 was exposed to three anthropogenic contaminants, Triclocarban (TCC), tris(2-chloroethyl) phosphate (TCEP), and 1,1,1-trichloroethane (TCA) and two biogenic-like halogenated compounds, 2,6-dibromophenol (2,6-DBP) and 2,6-dichlorophenol (2,6-DCP). The effects on TCE dechlorination ability due to 2,6-DBP and 2,6-DCP exposures were also investigated. DehaloR^2 did not dechlorinate TCC or TCEP. After initial exposure to TCA, half of the initial TCA was dechlorinated to 1,1-dichloroethane (DCA), however half of the TCA remained by day 100. Subsequent TCA and TCE re-exposure showed no reductive dechlorination activity for both TCA and TCE by 120 days after the re-exposure. It has been hypothesized that the microbial TCE-dechlorinating ability was developed before TCE became abundant in groundwater. This dechlorinating ability would have existed in the microbial metabolism due to previous exposure to biogenic halogenated compounds. After observing the inability of DehaloR^2 to dechlorinate other anthropogenic compounds, DehaloR^2 was then exposed to two naturally occurring halogenated phenols, 2,6-DBP and 2,6-DCP, in the presence and absence of TCE. DehaloR^2 debrominated 2,6-DBP through the intermediate 2-bromophenol (2-BP) to the end product phenol faster in the presence of TCE. DehaloR^2 dechlorinated 2,6-DCP to 2-CP in the absence of TCE; however, 2,6-DCP dechlorination was incomplete in the presence of TCE. Additionally, when 2,6-DBP was present, complete TCE dechlorination to ethene occurred more quickly than when TCE was present without 2,6-DBP. However, when 2,6-DCP was present, TCE dechlorination to ethene had not completed by day 55. The increased dehalogenation rate of 2,6-DBP and TCE when present together compared to conditions containing only 2,6-DBP or only TCE suggests a possible synergistic relationship between 2,6-DBP and TCE, while the decreased dechlorination rate of 2,6-DCP and TCE when present together compared to conditions containing only 2,6-DCP or only TCE suggests an inhibitory effect.
ContributorsKegerreis, Kylie (Author) / Krajmalnik-Brown, Rosa (Thesis advisor) / Halden, Rolf U. (Committee member) / Torres, César I (Committee member) / Arizona State University (Publisher)
Created2012
Description
Childhood obesity has been on the rise for the past decade, and it has been hypothesized that students' food choices may be influenced by easy access to food outlets near their schools that provide unhealthful options. But the results of recent studies on the relationship between the food environment around schools and student weight status are mixed and often contradictory. Most studies have used measures of weight and height that were self-reported by students, or have relied on data from a relatively small sample of students. I examine the association between weight status among school students and the food environment surrounding their schools using professionally-measured, student-level data across the full school-age spectrum. De-identified data were obtained for over 30,000 K-12 students in 79 public schools located in four New Jersey cities. Locations of alternative food-outlets (specifically, supermarkets, convenience stores, small grocery stores, and limited-service restaurants) were obtained from commercial sources and geocoded to develop proximity measures. A simplified social-ecological framework was used to conceptualize the multi-level the association between students' BMI and school proximity to food outlets and multivariate analyses were used to estimate this relationship controlling for student- and school-level factors. Over twenty percent of the students were obese, compared to the national average at 17% (Ogden, Carroll, Kit, & Flegal, 2012). On average, students had 2.6 convenience stores, 2.9 limited-service restaurants, and 0.1 supermarkets within a quarter mile of their school. This study suggests that easy access to small grocery stores (which this study uniquely examines as a separate food outlet category) that offer healthy choices including five types of fresh vegetable, five types of fresh fruits, low-fat dairy, and lean meats is associated with lower BMI z score and lower probability of being obese for middle and high school students. This suggests that improving access to such small food outlets may be a promising area for future investigation in obesity mitigation research. Also, this study separates students of pre-schools, kindergartens and elementary schools (neighborhood schools) from that of the middle and high schools (non-neighborhood) schools because the two groups of schools have different neighborhood characteristics, as well as open-school and bussing policies that result in different levels of exposure that students have to the food outlets around the schools. The result of this study suggests that the relationship between students' weight outcomes and food environment around schools is different in the two groups of schools.
ContributorsTang, Xuyang (Author) / Abbott, Joshua K (Thesis advisor) / Ohri-Vachaspati, Punam (Thesis advisor) / Aggarwal, Rimjhim (Committee member) / Arizona State University (Publisher)
Created2013
Description
In the past three decades alone, the United States has witnessed a dramatic rise in the prevalence of obesity and overweight in adults and children. Efforts towards obesity mitigation and prevention have produced promising recommendations and researchers and practitioners alike acknowledge that real solutions must match the complexity of the problem. Comprehensive approaches that target environmental, economic, socio-cultural, and knowledge-based factors that influence diet and physical activity are highly recommended. However, the literature yields little in the way of what such comprehensive obesity interventions actually entail and how they ought to be developed. In particular, there are knowledge gaps in how various stakeholder groups can bridge institutional barriers to collaborate in ways that maximize resources, build upon synergies, and avoid duplication of efforts; and how specific recommendations are actually implemented. This thesis aims to contribute to an emerging body of literature that fills this gap by presenting a practical case study on how to create a playground obesity intervention in the Gateway District of Phoenix, Arizona, in collaboration with researchers, health professionals, neighborhood residents, and city officials. The objectives were two-fold: 1. To outline concrete steps that will allow an organization to create a playground linked with healthy kids education program that aims to increase physical activity, perceptions of safety, and community cohesion; 2. To outline how diverse stakeholders can collaborate effectively to create such a cohesive, complex obesity intervention. A detailed, actionable intervention manual was drafted through semi-structured interviews, literature review, a survey, a stakeholder workshop, and an extended peer-review. The manual describes the sequence of actions necessary for creating an innovative playground that reinforces learning, encourages creative play, and increases physical activity. The sequence of actions was linked with existing local assets, stakeholder roles and responsibilities, costs, and potential barriers. This manual, as well as the process itself, can serve as a transferable model for helping organizations come together to build the capacity required in order to tackle complex health challenges.
ContributorsXiong, Angela (Author) / Wiek, Arnim (Thesis advisor) / Golub, Aaron (Committee member) / Otu, Essen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Residential energy consumption accounts for 22% of the total energy use in the United States. The consumer's perception of energy usage and conservation are very inaccurate which is leading to growing number of individuals who try to seek out ways to use energy more wisely. Hence behavioral change in consumers with respect to energy use, by providing energy use feedback may be important in reducing home energy consumption. Real-time energy information feedback delivered via technology along with feedback interventions has been reported to produce up to 20 percent declines in residential energy consumption through past research and pilot studies. There are, however, large differences in the estimates of the effect of these different types of feedback on energy use. As part of the Energize Phoenix Program, (a U.S. Department of Energy funded program), a Dashboard Study was conducted by the Arizona State University to estimate the impact of real-time, home-energy displays in conjunction with other feedback interventions on the residential rate of energy consumption in Phoenix, while also creating awareness and encouragement to households to reduce energy consumption. The research evaluates the effectiveness of these feedback initiatives. In the following six months of field experiment, a selected number of low-income multi-family apartments in Phoenix, were divided in three groups of feedback interventions, where one group received residential energy use related education and information, the second group received the same education as well as was equipped with the in-home feedback device and the third was given the same education, the feedback device and added budgeting information. Results of the experiment at the end of the six months did not lend a consistent support to the results from literature and past pilot studies. The data revealed a statistically insignificant reduction in energy consumption for the experiment group overall and inconsistent results for individual households when compared to a randomly selected control sample. However, as per the participant survey results, the study proved effective to foster awareness among participating residents of their own patterns of residential electricity consumption and understanding of residential energy use related savings.
ContributorsRungta, Shaily (Author) / Bryan, Harvey (Thesis advisor) / Reddy, Agami (Committee member) / Webster, Aleksasha (Committee member) / Arizona State University (Publisher)
Created2013
Description
We solve the problem of activity verification in the context of sustainability. Activity verification is the process of proving the user assertions pertaining to a certain activity performed by the user. Our motivation lies in incentivizing the user for engaging in sustainable activities like taking public transport or recycling. Such incentivization schemes require the system to verify the claim made by the user. The system verifies these claims by analyzing the supporting evidence captured by the user while performing the activity. The proliferation of portable smart-phones in the past few years has provided us with a ubiquitous and relatively cheap platform, having multiple sensors like accelerometer, gyroscope, microphone etc. to capture this evidence data in-situ. In this research, we investigate the supervised and semi-supervised learning techniques for activity verification. Both these techniques make use the data set constructed using the evidence submitted by the user. Supervised learning makes use of annotated evidence data to build a function to predict the class labels of the unlabeled data points. The evidence data captured can be either unimodal or multimodal in nature. We use the accelerometer data as evidence for transportation mode verification and image data as evidence for recycling verification. After training the system, we achieve maximum accuracy of 94% when classifying the transport mode and 81% when detecting recycle activity. In the case of recycle verification, we could improve the classification accuracy by asking the user for more evidence. We present some techniques to ask the user for the next best piece of evidence that maximizes the probability of classification. Using these techniques for detecting recycle activity, the accuracy increases to 93%. The major disadvantage of using supervised models is that it requires extensive annotated training data, which expensive to collect. Due to the limited training data, we look at the graph based inductive semi-supervised learning methods to propagate the labels among the unlabeled samples. In the semi-supervised approach, we represent each instance in the data set as a node in the graph. Since it is a complete graph, edges interconnect these nodes, with each edge having some weight representing the similarity between the points. We propagate the labels in this graph, based on the proximity of the data points to the labeled nodes. We estimate the performance of these algorithms by measuring how close the probability distribution of the data after label propagation is to the probability distribution of the ground truth data. Since labeling has a cost associated with it, in this thesis we propose two algorithms that help us in selecting minimum number of labeled points to propagate the labels accurately. Our proposed algorithm achieves a maximum of 73% increase in performance when compared to the baseline algorithm.
ContributorsDesai, Vaishnav (Author) / Sundaram, Hari (Thesis advisor) / Li, Baoxin (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
Description
To further the efforts producing energy from more renewable sources, microbial electrochemical cells (MXCs) can utilize anode respiring bacteria (ARB) to couple the oxidation of an organic substrate to the delivery of electrons to the anode. Although ARB such as Geobacter and Shewanella have been well-studied in terms of their microbiology and electrochemistry, much is still unknown about the mechanism of electron transfer to the anode. To this end, this thesis seeks to elucidate the complexities of electron transfer existing in Geobacter sulfurreducens biofilms by employing Electrochemical Impedance Spectroscopy (EIS) as the tool of choice. Experiments measuring EIS resistances as a function of growth were used to uncover the potential gradients that emerge in biofilms as they grow and become thicker. While a better understanding of this model ARB is sought, electrochemical characterization of a halophile, Geoalkalibacter subterraneus (Glk. subterraneus), revealed that this organism can function as an ARB and produce seemingly high current densities while consuming different organic substrates, including acetate, butyrate, and glycerol. The importance of identifying and studying novel ARB for broader MXC applications was stressed in this thesis as a potential avenue for tackling some of human energy problems.
ContributorsAjulo, Oluyomi (Author) / Torres, Cesar (Thesis advisor) / Nielsen, David (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Popat, Sudeep (Committee member) / Arizona State University (Publisher)
Created2013
Description
Despite the arid climate of Maricopa County, Arizona, vector-borne diseases have presented significant health challenges to the residents and public health professionals of Maricopa County in the past, and will continue to do so in the foreseeable future. Currently, West Nile virus is the only mosquitoes-transmitted disease actively, and natively, transmitted throughout the state of Arizona. In an effort to gain a more complete understanding of the transmission dynamics of West Nile virus this thesis examines human, vector, and environment interactions as they exist within Maricopa County. Through ethnographic and geographic information systems research methods this thesis identifies 1) the individual factors that influence residents' knowledge and behaviors regarding mosquitoes, 2) the individual and regional factors that influence residents' knowledge of mosquito ecology and the spatial distribution of local mosquito populations, and 3) the environmental, demographic, and socioeconomic factors that influence mosquito abundance within Maricopa County. By identifying the factors that influence human-vector and vector-environment interactions, the results of this thesis may influence current and future educational and mosquito control efforts throughout Maricopa County.
ContributorsKunzweiler, Colin (Author) / Boone, Christopher (Thesis advisor) / Wutich, Amber (Committee member) / Brewis-Slade, Alexandra (Committee member) / Arizona State University (Publisher)
Created2013
Description
There is growing concern over the future availability of water for electricity generation. Because of a rapidly growing population coupled with an arid climate, the Western United States faces a particularly acute water/energy challenge, as installation of new electricity capacity is expected to be required in the areas with the most limited water availability. Electricity trading is anticipated to be an important strategy for avoiding further local water stress, especially during drought and in the areas with the most rapidly growing populations. Transfers of electricity imply transfers of "virtual water" - water required for the production of a product. Yet, as a result of sizable demand growth, there may not be excess capacity in the system to support trade as an adaptive response to long lasting drought. As the grid inevitably expands capacity due to higher demand, or adapts to anticipated climate change, capacity additions should be selected and sited to increase system resilience to drought. This paper explores the tradeoff between virtual water and local water/energy infrastructure development for the purpose of enhancing the Western US power grid's resilience to drought. A simple linear model is developed that estimates the economically optimal configuration of the Western US power grid given water constraints. The model indicates that natural gas combined cycle power plants combined with increased interstate trade in power and virtual water provide the greatest opportunity for cost effective and water efficient grid expansion. Such expansion, as well as drought conditions, may shift and increase virtual water trade patterns, as states with ample water resources and a competitive advantage in developing power sources become net exporters, and states with limited water or higher costs become importers.
ContributorsHerron, Seth (Author) / Ruddell, Benjamin L (Thesis advisor) / Ariaratnam, Samuel (Thesis advisor) / Allenby, Braden (Committee member) / Williams, Eric (Committee member) / Arizona State University (Publisher)
Created2013