Matching Items (4)
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- All Subjects: Environmental engineering
- All Subjects: Hydrological modeling
- Genre: Academic theses
Description
Current policies subsidizing or accelerating deployment of photovoltaics (PV) are typically motivated by claims of environmental benefit, such as the reduction of CO2 emissions generated by the fossil-fuel fired power plants that PV is intended to displace. Existing practice is to assess these environmental benefits on a net life-cycle basis, where CO2 benefits occurring during use of the PV panels is found to exceed emissions generated during the PV manufacturing phase including materials extraction and manufacture of the PV panels prior to installation. However, this approach neglects to recognize that the environmental costs of CO2 release during manufacture are incurred early, while environmental benefits accrue later. Thus, where specific policy targets suggest meeting CO2 reduction targets established by a certain date, rapid PV deployment may have counter-intuitive, albeit temporary, undesired consequences. Thus, on a cumulative radiative forcing (CRF) basis, the environmental improvements attributable to PV might be realized much later than is currently understood. This phenomenon is particularly acute when PV manufacture occurs in areas using CO2 intensive energy sources (e.g., coal), but deployment occurs in areas with less CO2 intensive electricity sources (e.g., hydro). This thesis builds a dynamic Cumulative Radiative Forcing (CRF) model to examine the inter-temporal warming impacts of PV deployments in three locations: California, Wyoming and Arizona. The model includes the following factors that impact CRF: PV deployment rate, choice of PV technology, pace of PV technology improvements, and CO2 intensity in the electricity mix at manufacturing and deployment locations. Wyoming and California show the highest and lowest CRF benefits as they have the most and least CO2 intensive grids, respectively. CRF payback times are longer than CO2 payback times in all cases. Thin film, CdTe PV technologies have the lowest manufacturing CO2 emissions and therefore the shortest CRF payback times. This model can inform policies intended to fulfill time-sensitive CO2 mitigation goals while minimizing short term radiative forcing.
ContributorsTriplican Ravikumar, Dwarakanath (Author) / Seager, Thomas P (Thesis advisor) / Fraser, Matthew P (Thesis advisor) / Chester, Mikhail V (Committee member) / Sinha, Parikhit (Committee member) / Arizona State University (Publisher)
Created2013
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
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
Pluvial Flood Risk Modeling, Assessment, and Management under Evolving Urban Climates and Land Cover
Description
Pluvial flooding is a costly, injurious, and even deadly phenomenon with which cities will always contend. However, cities may reduce their risk of flood exposure by changing historically dominant patterns of development that have removed natural landscape features and reduce the damages that flooding causes by identifying and supporting vulnerable populations. Accomplishing either goal requires the development and application of appropriate frameworks for modeling or recording flood exposure. In this dissertation, I used modeling and surveying methods for assessing pluvial flood exposure in two cities, first in Valdivia, Chile, and then in Hermosillo, México. I open with a summary on pluvial flood risk in the present day and the threat it may pose under changing climates. In the second chapter, I explored how a form of urban ecological infrastructure (UEI), the wetland, is being wielded in Valdivia toward pluvial flood mitigation, and found that wetland daily, seasonal, and interannual changes in wetland surface and soil water storage alter pluvial flood risk in the city. In the third chapter, I used a mixed methodology, including projections of future land cover generated by cellular automata models with inputs from visioning workshops conducted by the Urban Resilience to Extremes Sustainability Research Network (UREx SRN), and found that wetland loss in future land configurations may lead to increased pluvial flood risk. In the fourth chapter, I combined these land cover models from the third chapter with downscaled climate data on precipitation, also generated by the UREx SRN, and found that wetland conservation can help to mitigate the pluvial flood risk posed by changing patterns of rainfall. In the fifth chapter, I applied the Arc-Malstrøm method for pluvial flood assessment in Hermosillo, México, and compared it with the more traditional rational method for flood assessment, and through accompanying surveys found that perception of flood risk is significantly affected by flood dimensions and impacts. This dissertation concludes with a synthesis of pluvial flood risk assessment, suggestions for improvements to modeling, as well as suggestions for future research on pluvial flood risk assessment in cities. This dissertation advances the understanding of the utility of inland wetland UEI in cities under present and future land cover and climate conditions. It also qualifies the utility of common and new pluvial flood risk assessments and offers research directions for future pluvial flood assessments.
ContributorsSauer, Jason R (Author) / Grimm, Nancy B (Thesis advisor) / Chester, Mikhail V (Committee member) / Cook, Elizabeth M (Committee member) / Childers, Daniel L (Committee member) / Eakin, Hallie (Committee member) / Arizona State University (Publisher)
Created2022