Matching Items (9)
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- All Subjects: Sustainability
- Genre: Doctoral Dissertation
- Creators: Chester, Mikhail V
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
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
Description
This dissertation advances the capability of water infrastructure utilities to anticipate and adapt to vulnerabilities in their systems from temperature increase and interdependencies with other infrastructure systems. Impact assessment models of increased heat and interdependencies were developed which incorporate probability, spatial, temporal, and operational information. Key findings from the models are that with increased heat the increased likelihood of water quality non-compliances is particularly concerning, the anticipated increases in different hardware components generate different levels of concern starting with iron pipes, then pumps, and then PVC pipes, the effects of temperature increase on hardware components and on service losses are non-linear due to spatial criticality of components, and that modeling spatial and operational complexity helps to identify potential pathways of failure propagation between infrastructure systems. Exploring different parameters of the models allowed for comparison of institutional strategies. Key findings are that either preventative maintenance or repair strategies can completely offset additional outages from increased temperatures though-- improved repair times reduce overall duration of outages more than preventative maintenance, and that coordinated strategies across utilities could be effective for mitigating vulnerability.
ContributorsBondank, Emily (Author) / Chester, Mikhail V (Thesis advisor) / Ruddell, Benjamin L (Committee member) / Johnson, Nathan G (Committee member) / Seager, Thomas P (Committee member) / Arizona State University (Publisher)
Created2019
Description
As India expanded its grid infrastructure, decentralized renewable energy technologies, such as off-grid solar, also emerged in parallel as an electrification solution. This dissertation critically examines the role of off-grid solar in facilitating rural electrification efforts in India. Specifically, it applies the frameworks of the multi-level perspective, capabilities approach, and energy justice to achieve three objectives: (1) trace the evolution of off-grid solar in India; (2) understand the role of solar micro-grids in improving household capabilities and well-being; (1) examine whether and how community-scale solar micro-grids can operate as just means of electrification. This research relies on qualitative case-study methods. The historical research in Paper 1 is based on published policy documents and interviews with energy experts in India. It finds that landscape-regime-niche actor relations and politics were crucial in shaping off-grid solar transition outcomes. There is also a narrative component, as the key narratives of energy security, environmental degradation, climate change and energy for development converged to create spaces for state and non-state interactions that could nurture the development of off-grid solar. The community-level research in Papers 2 and 3 analyze a local energy initiative of community operated solar micro-grid using semi-structured interviews and participant observations from three villages in Maharashtra. Solar micro-grids play an important part in expanding people’s choices and opportunities. The benefits are not uniform across all people, however. Increases in energy-related capabilities vary by economic class and gender, and to some extent this means certain biases can get reinforced. In addition, the inability of solar micro-grids to keep up with the changing electrification landscape and daily practices means that the challenges of affordability, reliability and community engagement emerged as important concerns over-time. Empirically, this dissertation finds that off-grid energy initiatives must be carefully designed to be in alignment with local values and realities. Theoretically, it adds to debates on justice in energy transitions by showcasing the regime-led innovations, and temporality elements of energy justice local energy initiatives.
ContributorsRajagopalan, Sushil (Author) / Breetz, Hanna (Thesis advisor) / Klinsky, Sonja (Thesis advisor) / Singh, Kartikeya (Committee member) / Arizona State University (Publisher)
Created2021
Description
Extreme weather events, such as hurricanes, continue to disrupt critical infrastructure like energy grids that provide lifeline services for urban systems, thus making resilience imperative for stakeholders, infrastructure managers, and community leaders to strategize in the face of 21st-century challenges. In Puerto Rico after Hurricane Maria, for example, the energy system took over nine months to recover in parts of the island, thousands of lives were lost, and livelihoods were severely impacted. Urban systems consist of interconnected human networks and physical infrastructure, and the subsequent complexity that is increasingly difficult to make sense of toward resilience enhancing efforts. While the resilience paradigm has continued to progress among and between several disciplinary fields, such as social science and engineering, an ongoing challenge is integrating social and technical approaches for resilience research. Misaligned or siloed perspectives can lead to misinformative and inadequate strategies that undercut inherent capacities or ultimately result in maladaptive infrastructure, social hardship, and sunken investments. This dissertation contributes toward integrating the social and technical resilience domains and transitioning established disaster resilience assessments into complexity perspectives by asking the overarching question: How can a multiplicity of resilience assessments be integrated by geographic and network mapping approaches to better capture the complexity of urban systems, using Hurricane Maria in Puerto Rico as a case study? The first chapter demonstrates how social metrics can be used in a socio-technical network modeling framework for a large-scale electrical system, presents a novel framing of social hardship due to disasters, and proposes a method for developing a social hardship metric using a treatment-effect approach. A second chapter presents a conceptual analysis of disaster resilience indicators from a complexity perspective and links socio-ecological systems resilience principles to tenets of complexity. A third chapter presents a novel methodology for integrating social complexity with performance-based metrics by leveraging distributed ethnographies and a thick mapping approach. Lastly, a concluding chapter synthesizes the previous chapters to discuss a broad framing for socio-technical resilience assessments, the role of space and place as anchors for multiple framings of a complex system, caveats given ongoing developments in Puerto Rico, and implications for collaborative resilience research.
ContributorsCarvalhaes, Thomaz (Author) / Chester, Mikhail V (Thesis advisor) / Reddy, Agami T (Thesis advisor) / Allenby, Braden R (Committee member) / Arizona State University (Publisher)
Created2021