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Description
Cities are facing complex problems in urban water management due to unprecedented changes in climate, natural and built environment. The shift in urban hydrology from pre-development to post-development continues to accelerate the challenges of managing excess stormwater runoff, mitigating urban flood hazards and flood damages. Physically based hydrologic-hydraulic stormwater models are a useful tool for broad subset of urban flood management including risk and hazard assessment, flood forecasting, and infrastructure adaptation decision making and planning. The existing limitations in data availability, gaps in data, and uncertainty in data preclude reliable model construction, testing, deployment, knowledge generation, effective communication of flood risks, and adaptation decision making. These challenges that affect both the science and practice motivate three chapters of this dissertation. The first study conducts diagnostic analysis of the effects of stormwater infrastructure data completeness on model’s ability to simulate flood duration, flooding flow rate; and assesses the combined effects of data gaps and model resolution to simulate flood depth, extent and volume (chapter 2). The analysis showed the significance of complete stormwater infrastructure data and high model resolution to reduce error, bias and uncertainty; this study also presented an approach for filling infrastructure data gaps using available data and design standards. The second study addresses the lack of long-term hydrological observation in urban catchment by investigating the process and benefits of leveraging novel data sources in urban flood model construction and testing (chapter 3). A proof-of-concept demonstrated the application and benefits of leveraging novel data sources for urban flood monitoring and modeling. Furthermore, it highlights the need for developing and streamlining novel data collection infrastructure. The third study applies the hydrologic-hydraulic model as an adaptation planning tool and assess the effects of uncertainty in design precipitation estimates and land use change on the optimal configuration of green infrastructure (chapter 4). Several uncertainties affect infrastructure decision making as showed by variation in optimal green infrastructure configuration under precipitation estimates and land use change. Thus, the study further highlights the need of flexible planning process in infrastructure decision making.
ContributorsShrestha, Ashish (Author) / Garcia, Margaret (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Chester, Mikhail (Committee member) / Fletcher, Sarah (Committee member) / Arizona State University (Publisher)
Created2022
Description
This dissertation consists of three chapters that investigate the rapid adoption and complex implementation of city commitments to transition to 100% renewable energy (100RE). The first paper uses a two-stage, mixed methods approach to examine 100RE commitments across the US, combining a multivariate regression of demographic, institutional, and policy factors in adoption and six interview-based state case studies to discuss implementation. Adoption of this non-binding commitment progressed rapidly for city councils around the US. Results show that many cities passed 100RE commitments with no implementation plan and minimal understanding of implementation challenges. This analysis highlights that many cities will need new institutions and administrative capacities for successful implementation of these ambitious new policies. While many cities abandoned the commitment soon after adoption, collaboration allowed cities in a few states to break through and pursue implementation, examined further in the next two studies. The second paper is a qualitative case study examining policymaking for the Utah Community Renewable Energy Act. Process tracing methods are used to identify causal factors in enacting this legislation at the state level and complementary resolutions at the local level. This Act was passed through the leadership and financial backing of major cities and committed the investor-owned utility to fulfill any city 100RE resolutions passed through 2019. Finally, the third paper is a mixed-methods, descriptive case study of the benefits of Community Choice Aggregation (CCA) in California, which many cities are using to fulfill their 100RE commitments. Cities have adopted CCAs to increase their local voice in the energy process, while fulfilling climate and energy goals. Overall, this research shows that change in the investor-owned utility electricity system is in fact possible from the city scale, though many cities will need institutional innovation to implement these policies and achieve the change they desire. While cities with greater resources are better positioned to make an impact, smaller cities can collaborate to similarly influence the energy system. Communities are interested in lowering energy costs for customers where possible, but the central motivations in these cases were the pursuit of sustainability and increasing local voice in energy decision-making.
ContributorsKunkel, Leah Christine (Author) / Breetz, Hanna L (Thesis advisor) / Parker, Nathan (Committee member) / Salon, Deborah (Committee member) / Arizona State University (Publisher)
Created2022
Description
Plastic pollution is undoubtedly one of the most pressing challenges facing humanity today. Significant action is required in order to properly address this rapidly growing threat. The Circular Economy provides a promising model for solution design in terms of responsible consumption and production. Countdown: Circular Economy Solutions is an organization created by Jasmine Amoako-Agyei focused on addressing the threat of plastic pollution in the United States and Ghana, West Africa. The first part of this report will explain the severity of the global plastic pollution crisis and challenges with recycling. It will then present the Circular Economy as a viable model for a course of action. From there it will explain the efforts of Countdown: Circular Economy Solutions over the last two with a pathway forward. This venture leveraged the greater ASU ecosystem of resources such as Walton Sustainability Solutions, Precious Plastic ASU, the Luminosity Lab, Changemaker Central, Venture Devils, Engineering Projects in Community Service (ASU), Gary K. Herberger Young Scholars Academy, KNUST, and Ashesi D: Lab.
ContributorsAmoako-Agyei, Jasmine (Author) / Phelan, Pat (Thesis director) / Cho, Steve (Thesis director) / Loughman, Joshua (Committee member) / Barrett, The Honors College (Contributor) / Tech Entrepreneurship & Mgmt (Contributor) / Dean, W.P. Carey School of Business (Contributor) / School of Sustainability (Contributor)
Created2022-12
Description
This thesis focuses on the increasing emphasis on sustainability within the fashion industry and how brands, specifically H&M, can increase their market share through updating their in-store retail strategy. Seven common retail strategies are analyzed and recommendations in each area are made to enhance H&M’s emphasis on sustainability. To support these potential recommendations, two focus groups were conducted to evaluate some potential in-store marketing elements. Upon the conclusion of the focus group research, participant’s thoughts were taken into consideration to revise the recommended retail strategies. Overall, by implementing the recommended retail marketing strategies, H&M can incorporate their Conscious line more fully within their stores and promote their new sustainable focus to further their brand in the future.
ContributorsFoley, Jacqueline (Author) / Riker, Elise (Thesis director) / Schlacter, John (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor) / Department of Finance (Contributor)
Created2022-12
Description
Motor gasoline and diesel contribute 30% to total energy related carbon dioxide (CO2) emissions in the U.S. However, this estimate only accounts for emissions from direct combustion and does not include indirect emissions from processing and fuel movement, even though indirect (scope 3) CO2 emissions are a significant contributor. Gasoline and diesel flow through a complex supply chain from oil extraction to point of combustion and estimates of their indirect emissions are typically aggregated as national or regional averages and not available at county or city scale. This dissertation presents a novel method to quantify U.S. supply-chain CO2 emissions to the county-scale for gasoline and diesel consumed in the on-road sector. It considers how these fuels flow across the U.S. petroleum infrastructure consisting of pipelines, tankers, trucks, trains, refineries, and blenders. It resolves county-scale indirect CO2 emissions using publicly accessible data to allocate fuel movement between different links and transportation modes across the country. For most of the U.S., the exact volume of fuel moved between counties from combinations of refineries and transportation modes is not explicitly known. To estimate these fuel movements, I use linear optimization with supply and demand related constraints. Estimating on-road gasoline and diesel indirect CO2 emissions at high spatial resolution finds that on-road gasoline CO2 emissions increase by 24% and on-road diesel CO2 emissions increase by 18%.
For both fuels there are large variations in the carbon intensity (kgCO2/gal) across the country and the relationship of county carbon intensity with explanatory variables related to fuel supply infrastructure is tested. Regression results indicate that presence of interstate highways, refineries and blenders are inversely related to carbon intensity while presence of fuel pipelines increases diesel carbon intensity.
Finally, the on-road gasoline scope 3 CO2 emissions results are assessed in relation to indirect CO2 emissions from electricity consumption at the county scale to analyze the effectiveness of future electric vehicle (EV) transition actions. In this analysis, states with existing EV transition mandates (zero emission vehicle or ‘ZEV’ states) are shown to have on average 12% higher CO2 emissions reduction when transitioning to EVs, over non-ZEV states.
ContributorsMoiz, Taha (Author) / Gurney, Kevin R (Thesis advisor) / Dooley, Kevin J (Thesis advisor) / Parker, Nathan C (Committee member) / Arizona State University (Publisher)
Created2022
Description
Food safety incidents have constantly hit society and threatened human health. Hundreds of millions of people become sick after eating contaminated food every year. As the problem continues to emerge, consumers must take action to avoid purchasing risky food products. As one of the solutions, food traceability systems have been developed rapidly in many countries in recent years. More food products can now be provided with traceability information to assist consumers in making purchase decisions. To design services for grocery shoppers to access food information from food traceability systems possibly through modern technologies, this transdisciplinary user research study investigated shopper insights into food traceability information on produce provided at grocery stores, with a fusion of ideas from the disciplines of design and consumer behaviors. Through literature reviews, an online survey study, and an online interview study, this research revealed a series of shopper insights concerning (1) shoppers’ knowledge about food traceability information, (2) shoppers’ behaviors and motivations for using traceability information on produce, (3) shoppers’ perceptions towards providing traceability information on produce to them at grocery stores, (4) shoppers’ perceived important traceability information on produce, (5) shoppers’ behavior intentions of using specific ways to access traceability information on produce, and (6) shoppers’ thresholds to pay for traceability information on produce. Based on the results, this study identified design opportunities for the features, components, and mediums of the service design of future food traceability systems.
ContributorsWang, Anne (Author) / Takamura, John (Thesis advisor) / Fehler, Michelle (Committee member) / Grebitus, Carola (Committee member) / Arizona State University (Publisher)
Created2022
ContributorsKealoha, Alisia (Author) / Adamson, Joni (Thesis director) / Arcusa, Stéphanie (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor)
Created2024-05
ContributorsKealoha, Alisia (Author) / Adamson, Joni (Thesis director) / Arcusa, Stéphanie (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor)
Created2024-05
Description
The purpose of this research is to create predictive models for a leading sustainability certification - the B Corporation certification issued by the non-profit company B Lab based on the B Impact Assessment. This certification is one of many that are currently being used to assess sustainability in the corporate world, and this research seeks to understand the relationships between a corporation's characteristics (e.g. market, size, country) and the B Certification. The data used for the analysis comes from a B Lab upload to data.world, providing descriptive information on each company, current certification status, and B Impact Assessment scores. Further data engineering was used to include attributes on publicly traded status and years certified. Comparing Logistic Regression and Random Forest Classification machine learning methods, a predictive model was produced with 87.58% accuracy discerning between certified and de-certified B Corporations.
ContributorsBrandwick, Katelynn (Author) / Samara, Marko (Thesis director) / Tran, Samantha (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2024-05
Description
Supply chain sustainability has become an increasingly important topic for corporations
due to consumer demands, regulatory requirements, and employee retention and productivity.
Since more and more stakeholders are beginning to care about sustainability, companies are
looking at how they can reduce their carbon footprint without it leading to higher costs. Although
sustainable supply chain operations are often associated with higher costs, new technology has
surfaced within the last decade that makes this association come into question. This paper serves as an investigation on whether or not implementation of recent technology will not only make for more sustainable supply chains, but also bring cost savings to a company. For the sake of simplicity, this paper analyzes the topic within the context of the consumer packaged goods (CPG) industry. The three categories of technology that were evaluated are artificial intelligence, Internet of Things, and data integration systems. Internship projects and/or published case studies and articles were examined to explore the relationship between the technology, supply chain sustainability, and costs. The findings of this paper indicate that recent technology offers companies innovative sustainability solutions to supply chains without sacrificing cost. This calls for CPG companies to invest in and implement technology that allows for more sustainable supply chains. Shying away from this because of cost concerns is no longer necessary.
ContributorsDixon, Logan (Author) / Printezis, Antonios (Thesis director) / Macias, Jeff (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Dean, W.P. Carey School of Business (Contributor)
Created2024-05