Matching Items (15)
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- All Subjects: Sustainability
- Genre: Doctoral Dissertation
- Creators: Chester, Mikhail V
- Creators: Boone, Christopher
Description
The lack of substantive, multi-dimensional perspectives on civic space planning and design has undermined the potential role of these valuable social and ecological amenities in advancing urban sustainability goals. Responding to these deficiencies, this dissertation utilized mixed quantitative and qualitative methods and synthesized multiple social and natural science perspectives to inform the development of progressive civic space planning and design, theory, and public policy aimed at improving the social, economic, and environmental health of cities. Using Phoenix, Arizona as a case study, the analysis was tailored to arid cities, yet the products and findings are flexible enough to be geographically customized to the social, environmental, built, and public policy goals of other urbanized regions. Organized into three articles, the first paper applies geospatial and statistical methods to analyze and classify urban parks in Phoenix based on multiple social, ecological, and built criteria, including landuse-land cover, `greenness,' and site amenities, as well as the socio- economic and built characteristics of park neighborhoods. The second article uses spatial empirical analysis to rezone the City of Phoenix following transect form-based code. The current park system was then assessed within this framework and recommendations are presented to inform the planning and design of civic spaces sensitive to their social and built context. The final paper culminates in the development of a planning tool and site design guidelines for civic space planning and design across the urban-to-natural gradient augmented with multiple ecosystem service considerations and tailored to desert cities.
ContributorsIbes, Dorothy (Author) / Talen, Emily (Thesis advisor) / Boone, Christopher (Committee member) / Crewe, Katherine (Committee member) / Arizona State University (Publisher)
Created2013
Description
Extreme hot-weather events have become life-threatening natural phenomena in many cities around the world, and the health impacts of excessive heat are expected to increase with climate change (Huang et al. 2011; Knowlton et al. 2007; Meehl and Tebaldi 2004; Patz 2005). Heat waves will likely have the worst health impacts in urban areas, where large numbers of vulnerable people reside and where local-scale urban heat island effects (UHI) retard and reduce nighttime cooling. This dissertation presents three empirical case studies that were conducted to advance our understanding of human vulnerability to heat in coupled human-natural systems. Using vulnerability theory as a framework, I analyzed how various social and environmental components of a system interact to exacerbate or mitigate heat impacts on human health, with the goal of contributing to the conceptualization of human vulnerability to heat. The studies: 1) compared the relationship between temperature and health outcomes in Chicago and Phoenix; 2) compared a map derived from a theoretical generic index of vulnerability to heat with a map derived from actual heat-related hospitalizations in Phoenix; and 3) used geospatial information on health data at two areal units to identify the hot spots for two heat health outcomes in Phoenix. The results show a 10-degree Celsius difference in the threshold temperatures at which heat-stress calls in Phoenix and Chicago are likely to increase drastically, and that Chicago is likely to be more sensitive to climate change than Phoenix. I also found that heat-vulnerability indices are sensitive to scale, measurement, and context, and that cities will need to incorporate place-based factors to increase the usefulness of vulnerability indices and mapping to decision making. Finally, I found that identification of geographical hot-spot of heat-related illness depends on the type of data used, scale of measurement, and normalization procedures. I recommend using multiple datasets and different approaches to spatial analysis to overcome this limitation and help decision makers develop effective intervention strategies.
ContributorsChuang, Wen-Ching (Author) / Gober, Patricia (Thesis advisor) / Boone, Christopher (Committee member) / Guhathakurta, Subhrajit (Committee member) / Ruddell, Darren (Committee member) / Arizona State University (Publisher)
Created2013
Description
Diarrheal diseases caused by poor water, sanitation and hygiene continue to kill more children in Sub-Saharan Africa's burgeoning informal urban settlements than in any other part of the world. In recent years, Delegated Management Model (DMM), a partnership in which a utility delegates service management to slum residents have been promoted as new models to improve services.
This dissertation examines the benefits of DMM by comparing water services in three informal settlements in Kisumu city, Kenya: two slums where DMM has been implemented, and one, a control, where it has not. In addition, the research examined how school-based hygiene interventions could be designed to improve safe water and hygiene knowledge in urban informal settlements. This study compared outcomes of two approaches to hygiene education, one which combined messages with participatory water testing; the second used hygiene messages alone.
Results of the DMM study showed that DMM implementation had lowered water cost and improved provider accountability. However, unhygienic water collection and handling practices on the part of the service users could contaminate drinking water that was clean at the delivery point, thus preventing the intended health outcomes of DMM from being realized. Results of the hygiene education intervention showed that one week after the inventions, hygiene knowledge among students who received the intervention that combined hygiene messages with participatory water testing was significantly improved. Evaluation of the intervention 12 months after implementation showed that the hygiene knowledge gained was sustained.
The research findings suggest that: i) regular monitoring of water quality at the kiosks is essential to ensure that the DMM model achieves intended health outcomes, ii) sanitation conditions at kiosk sites need to be regulated to meet minimum hygiene standards, and iii) customers need to be educated on safe water collection and storage practices. Finally, school-based hygiene education could be made more effective by including hands-on water testing by students. Making sustainable impact on health and wellbeing of slum residents requires not only building effective partnerships for water delivery, but also paying close attention to the other points of intervention within the water system.
This dissertation examines the benefits of DMM by comparing water services in three informal settlements in Kisumu city, Kenya: two slums where DMM has been implemented, and one, a control, where it has not. In addition, the research examined how school-based hygiene interventions could be designed to improve safe water and hygiene knowledge in urban informal settlements. This study compared outcomes of two approaches to hygiene education, one which combined messages with participatory water testing; the second used hygiene messages alone.
Results of the DMM study showed that DMM implementation had lowered water cost and improved provider accountability. However, unhygienic water collection and handling practices on the part of the service users could contaminate drinking water that was clean at the delivery point, thus preventing the intended health outcomes of DMM from being realized. Results of the hygiene education intervention showed that one week after the inventions, hygiene knowledge among students who received the intervention that combined hygiene messages with participatory water testing was significantly improved. Evaluation of the intervention 12 months after implementation showed that the hygiene knowledge gained was sustained.
The research findings suggest that: i) regular monitoring of water quality at the kiosks is essential to ensure that the DMM model achieves intended health outcomes, ii) sanitation conditions at kiosk sites need to be regulated to meet minimum hygiene standards, and iii) customers need to be educated on safe water collection and storage practices. Finally, school-based hygiene education could be made more effective by including hands-on water testing by students. Making sustainable impact on health and wellbeing of slum residents requires not only building effective partnerships for water delivery, but also paying close attention to the other points of intervention within the water system.
ContributorsNzengya, Daniel (Author) / Aggarwal, Rimjhim (Thesis advisor) / Hartwell, Leland (Committee member) / Boone, Christopher (Committee member) / Arizona State University (Publisher)
Created2014
Description
Comparative life cycle assessment (LCA) evaluates the relative performance of multiple products, services, or technologies with the purpose of selecting the least impactful alternative. Nevertheless, characterized results are seldom conclusive. When one alternative performs best in some aspects, it may also performs worse in others. These tradeoffs among different impact categories make it difficult to identify environmentally preferable alternatives. To help reconcile this dilemma, LCA analysts have the option to apply normalization and weighting to generate comparisons based upon a single score. However, these approaches can be misleading because they suffer from problems of reference dataset incompletion, linear and fully compensatory aggregation, masking of salient tradeoffs, weight insensitivity and difficulties incorporating uncertainty in performance assessment and weights. Consequently, most LCA studies truncate impacts assessment at characterization, which leaves decision-makers to confront highly uncertain multi-criteria problems without the aid of analytic guideposts. This study introduces Stochastic Multi attribute Analysis (SMAA), a novel approach to normalization and weighting of characterized life-cycle inventory data for use in comparative Life Cycle Assessment (LCA). The proposed method avoids the bias introduced by external normalization references, and is capable of exploring high uncertainty in both the input parameters and weights.
ContributorsPrado, Valentina (Author) / Seager, Thomas P (Thesis advisor) / Chester, Mikhail V (Committee member) / Kullapa Soratana (Committee member) / Tervonen, Tommi (Committee member) / Arizona State University (Publisher)
Created2015
Description
Electricity infrastructure vulnerabilities were assessed for future heat waves due to climate change. Critical processes and component relationships were identified and characterized with consideration for the terminal event of service outages, including cascading failures in transmission-level components that can result in blackouts. The most critical dependency identified was the increase in peak electricity demand with higher air temperatures. Historical and future air temperatures were characterized within and across Los Angeles County, California (LAC) and Maricopa County (Phoenix), Arizona. LAC was identified as more vulnerable to heat waves than Phoenix due to a wider distribution of historical temperatures. Two approaches were developed to estimate peak demand based on air temperatures, a top-down statistical model and bottom-up spatial building energy model. Both approaches yielded similar results, in that peak demand should increase sub-linearly at temperatures above 40°C (104 °F) due to saturation in the coincidence of air conditioning (AC) duty cycles. Spatial projections for peak demand were developed for LAC to 2060 considering potential changes in population, building type, building efficiency, AC penetration, appliance efficiency, and air temperatures due climate change. These projections were spatially allocated to delivery system components (generation, transmission lines, and substations) to consider their vulnerability in terms of thermal de-rated capacity and weather adjusted load factor (load divided by capacity). Peak hour electricity demand was projected to increase in residential and commercial sectors by 0.2–6.5 GW (2–51%) by 2060. All grid components, except those near Santa Monica Beach, were projected to experience 2–20% capacity loss due to air temperatures exceeding 40 °C (104 °F). Based on scenario projections, and substation load factors for Southern California Edison (SCE), SCE will require 848—6,724 MW (4-32%) of additional substation capacity or peak shaving in its LAC service territories by 2060 to meet additional demand associated with population growth projections.
ContributorsBurillo, Daniel (Author) / Chester, Mikhail V (Thesis advisor) / Ruddell, Benjamin (Committee member) / Johnson, Nathan (Committee member) / Arizona State University (Publisher)
Created2018
Description
Energy use within urban building stocks is continuing to increase globally as populations expand and access to electricity improves. This projected increase in demand could require deployment of new generation capacity, but there is potential to offset some of this demand through modification of the buildings themselves. Building stocks are quasi-permanent infrastructures which have enduring influence on urban energy consumption, and research is needed to understand: 1) how development patterns constrain energy use decisions and 2) how cities can achieve energy and environmental goals given the constraints of the stock. This requires a thorough evaluation of both the growth of the stock and as well as the spatial distribution of use throughout the city. In this dissertation, a case study in Los Angeles County, California (LAC) is used to quantify urban growth, forecast future energy use under climate change, and to make recommendations for mitigating energy consumption increases. A reproducible methodological framework is included for application to other urban areas.
In LAC, residential electricity demand could increase as much as 55-68% between 2020 and 2060, and building technology lock-in has constricted the options for mitigating energy demand, as major changes to the building stock itself are not possible, as only a small portion of the stock is turned over every year. Aggressive and timely efficiency upgrades to residential appliances and building thermal shells can significantly offset the projected increases, potentially avoiding installation of new generation capacity, but regulations on new construction will likely be ineffectual due to the long residence time of the stock (60+ years and increasing). These findings can be extrapolated to other U.S. cities where the majority of urban expansion has already occurred, such as the older cities on the eastern coast. U.S. population is projected to increase 40% by 2060, with growth occurring in the warmer southern and western regions. In these growing cities, improving new construction buildings can help offset electricity demand increases before the city reaches the lock-in phase.
In LAC, residential electricity demand could increase as much as 55-68% between 2020 and 2060, and building technology lock-in has constricted the options for mitigating energy demand, as major changes to the building stock itself are not possible, as only a small portion of the stock is turned over every year. Aggressive and timely efficiency upgrades to residential appliances and building thermal shells can significantly offset the projected increases, potentially avoiding installation of new generation capacity, but regulations on new construction will likely be ineffectual due to the long residence time of the stock (60+ years and increasing). These findings can be extrapolated to other U.S. cities where the majority of urban expansion has already occurred, such as the older cities on the eastern coast. U.S. population is projected to increase 40% by 2060, with growth occurring in the warmer southern and western regions. In these growing cities, improving new construction buildings can help offset electricity demand increases before the city reaches the lock-in phase.
ContributorsReyna, Janet Lorel (Author) / Chester, Mikhail V (Thesis advisor) / Gurney, Kevin (Committee member) / Reddy, T. Agami (Committee member) / Rey, Sergio (Committee member) / Arizona State University (Publisher)
Created2016
Description
'Attributional' Life Cycle Assessment (LCA) quantitatively tracks the potential environmental impacts of international value chains, in retrospective, while ensuring that burden shifting is avoided. Despite the growing popularity of LCA as a decision-support tool, there are numerous concerns relating to uncertainty and variability in LCA that affects its reliability and credibility. It is pertinent that some part of future research in LCA be guided towards increasing reliability and credibility for decision-making, while utilizing the LCA framework established by ISO 14040.
In this dissertation, I have synthesized the present state of knowledge and application of uncertainty and variability in ‘attributional’ LCA, and contribute to its quantitative assessment.
Firstly, the present state of addressment of uncertainty and variability in LCA is consolidated and reviewed. It is evident that sources of uncertainty and variability exist in the following areas: ISO standards, supplementary guides, software tools, life cycle inventory (LCI) databases, all four methodological phases of LCA, and use of LCA information. One source of uncertainty and variability, each, is identified, selected, quantified, and its implications discussed.
The use of surrogate LCI data in lieu of missing dataset(s) or data-gaps is a source of uncertainty. Despite the widespread use of surrogate data, there has been no effort to (1) establish any form of guidance for the appropriate selection of surrogate data and, (2) estimate the uncertainty associated with the choice and use of surrogate data. A formal expert elicitation-based methodology to select the most appropriate surrogates and to quantify the associated uncertainty was proposed and implemented.
Product-evolution in a non-uniform manner is a source of temporal variability that is presently not considered in LCA modeling. The resulting use of outdated LCA information will lead to misguided decisions affecting the issue at concern and eventually the environment. In order to demonstrate product-evolution within the scope of ISO 14044, and given that variability cannot be reduced, the sources of product-evolution were identified, generalized, analyzed and their implications (individual and coupled) on LCA results are quantified.
Finally, recommendations were provided for the advancement of robustness of 'attributional' LCA, with respect to uncertainty and variability.
In this dissertation, I have synthesized the present state of knowledge and application of uncertainty and variability in ‘attributional’ LCA, and contribute to its quantitative assessment.
Firstly, the present state of addressment of uncertainty and variability in LCA is consolidated and reviewed. It is evident that sources of uncertainty and variability exist in the following areas: ISO standards, supplementary guides, software tools, life cycle inventory (LCI) databases, all four methodological phases of LCA, and use of LCA information. One source of uncertainty and variability, each, is identified, selected, quantified, and its implications discussed.
The use of surrogate LCI data in lieu of missing dataset(s) or data-gaps is a source of uncertainty. Despite the widespread use of surrogate data, there has been no effort to (1) establish any form of guidance for the appropriate selection of surrogate data and, (2) estimate the uncertainty associated with the choice and use of surrogate data. A formal expert elicitation-based methodology to select the most appropriate surrogates and to quantify the associated uncertainty was proposed and implemented.
Product-evolution in a non-uniform manner is a source of temporal variability that is presently not considered in LCA modeling. The resulting use of outdated LCA information will lead to misguided decisions affecting the issue at concern and eventually the environment. In order to demonstrate product-evolution within the scope of ISO 14044, and given that variability cannot be reduced, the sources of product-evolution were identified, generalized, analyzed and their implications (individual and coupled) on LCA results are quantified.
Finally, recommendations were provided for the advancement of robustness of 'attributional' LCA, with respect to uncertainty and variability.
ContributorsSubramanian, Vairavan (Author) / Golden, Jay S (Thesis advisor) / Chester, Mikhail V (Thesis advisor) / Allenby, Braden R. (Committee member) / Dooley, Kevin J (Committee member) / Arizona State University (Publisher)
Created2016
Description
Our dependence on fossil fuels is driving anthropogenic climate change. Solar energy is the most abundant and cleanest alternative to fossil fuels, but its practicability is influenced by a complex interplay of factors (policy, geospatial, and market) and scales (global, national, urban). This thesis provides a holistic evaluation of these factors and scales with the goal of improving our understanding of the mechanisms and challenges of transitioning to solar energy.
This analysis used geospatial, demographic, policy, legislative record, environmental, and industry data, plus a series of semi-structured, in-person interviews. Methods included geostatistical calculation, statistical linear regression and multivariate modeling, and qualitative inductive analysis. The results reveal valuable insights at each scale, but moreover a gestalt model across the factors and scales draws out a larger pattern at play of the transmutational weighting and increasing complexity of interplay as the level of analysis cascades down through the three geographic scales.
This analysis used geospatial, demographic, policy, legislative record, environmental, and industry data, plus a series of semi-structured, in-person interviews. Methods included geostatistical calculation, statistical linear regression and multivariate modeling, and qualitative inductive analysis. The results reveal valuable insights at each scale, but moreover a gestalt model across the factors and scales draws out a larger pattern at play of the transmutational weighting and increasing complexity of interplay as the level of analysis cascades down through the three geographic scales.
ContributorsHerche, Wesley (Author) / Melnick, Rob (Thesis advisor) / Boone, Christopher (Committee member) / Pasqualetti, Martin J (Committee member) / Arizona State University (Publisher)
Created2017
Description
Traditional infrastructure design approaches were born with industrialization. During this time the relatively stable environments allowed infrastructure systems to reliably provide service with networks designed to precise parameters and organizations fixated on maximizing efficiency. Now, infrastructure systems face the challenge of operating in the Anthropocene, an era of complexity. The environments in which infrastructure systems operate are changing more rapidly than the technologies and governance systems of infrastructure. Infrastructure systems will need to be resilient to navigate stability and instability and avoid obsolescence. This dissertation addresses how infrastructure systems could be designed for the Anthropocene, assessing technologies able to operate with uncertainty, rethinking the principles of technology design, and restructuring infrastructure governance. Resilience, in engineering, has often been defined as resistance to known disturbances with a focus on infrastructure assets. Resilience, more broadly reviewed, includes resistance, adaptation, and transformation across physical and governance domains. This dissertation constructs a foundation for resilient infrastructure through an assessment of resilience paradigms in engineering, complexity and deep uncertainty (Chapter 2), ecology (Chapter 3), and organizational change and leadership (Chapter 4). The second chapter reconciles frameworks of complexity and deep uncertainty to help infrastructure managers navigate the instability infrastructure systems face, with a focus on climate change. The third chapter identifies competencies of resilience in infrastructure theory and practice and compares those competencies with ‘Life’s Principles’ in ecology, presenting opportunities for growth and innovation in infrastructure resilience and highlighting the need for satisficed (to satisfy and suffice) solutions. The fourth chapter navigates pressures of exploitation and exploration that infrastructure institutions face during periods of stability and instability, proposing leadership capabilities to enhance institutional resilience. Finally, the dissertation is concluded with a chapter synthesizing the previous chapters, providing guidance for alternative design approaches for advancing resilient infrastructure. Combined, the work challenges the basic mental models used by engineers when approaching infrastructure design and recommends new ways of doing and thinking for the accelerating and increasingly uncertain conditions of the future.
ContributorsHelmrich, Alysha Marie (Author) / Chester, Mikhail V (Thesis advisor) / Grimm, Nancy B (Committee member) / Garcia, Margaret (Committee member) / Meerow, Sara (Committee member) / Arizona State University (Publisher)
Created2021
Description
Infrastructure managers are continually challenged to reorient their organizations to mitigate disturbances. Disturbances to infrastructure constantly intensify, and the world and its intricate systems are becoming more connected and complex. This complexity often leads to disturbances and cascading failures. Some of these events unfold in extreme ways previously unimagined (i.e., Black Swan events). Infrastructure managers currently seek pathways through this complexity. To this end, reimagined – multifaceted – definitions of resilience must inform future decisions. Moreover, the hazardous environment of the Anthropocene demands flexibility and dynamic reprioritization of infrastructure and resources during disturbances. In this dissertation, the introduction will briefly explain foundational concepts, frameworks, and models that will inform the rest of this work. Chapter 2 investigates the concept of dynamic criticality: the skill to reprioritize amidst disturbances, repeating this process with each new disturbance. There is a dearth of insight requisite skillsets for infrastructure organizations to attain dynamic criticality. Therefore, this dissertation searches other industries and finds goals, structures, sensemaking, and strategic best practices to propose a contextualized framework for infrastructure. Chapters 3 and 4 seek insight into modeling infrastructure interdependencies and cascading failure to elucidate extreme outcomes such as Black Swans. Chapter 3 explores this concept through a theoretical analysis considering the use of realistic but fictional (i.e., synthetic) models to simulate interdependent behavior and cascading failures. This chapter also discusses potential uses of synthetic networks for infrastructure resilience research and barriers to future success. Chapter 4 tests the preceding theoretical analysis with an empirical study. Chapter 4 builds realistic networks with dependency between power and water models and simulates cascading failure. The discussion considers the future application of similar modeling efforts and how these techniques can help infrastructure managers scan the horizon for Black Swans. Finally, Chapter 5 concludes the dissertation with a synthesis of the findings from the previous chapters, discusses the boundaries and limitations, and proposes inspirations for future work.
ContributorsHoff, Ryan Michael (Author) / Chester, Mikhail V (Thesis advisor) / Allenby, Braden (Committee member) / Johnson, Nathan (Committee member) / McPhearson, Timon (Committee member) / Arizona State University (Publisher)
Created2023