Matching Items (19)
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
Contrary to many previous travel demand forecasts there is increasing evidence that vehicle travel in developed countries may be peaking. The underlying causes of this peaking are still under much debate and there has been a mobilization of research, largely focused at the national scale, to study the explanatory drivers but research focused at the metropolitan scale, where transportation policy and planning are frequently decided, is relatively thin. Additionally, a majority of this research has focused on changes within the activity system without considering the impact transportation infrastructure has on overall travel demand. Using Los Angeles County California, we investigate Peak Car and whether the saturation of automobile infrastructure, in addition to societal and economic factors, may be a suppressing factor. After peaking in 2002, vehicle travel in Los Angeles County in 2010 was estimated at 78 billion and was 20.3 billion shy of projections made in 2002. The extent to which infrastructure saturation may contribute to Peak Car is evaluated by analyzing social and economic factors that may have impacted personal automobile usage over the last decade. This includes changing fuel prices, fuel economy, population growth, increased utilization of alternate transportation modes, changes in driver demographics , travel time and income levels. Summation of all assessed factors reveals there is at least some portion of the 20 billion VMT that is unexplained in all but the worst case scenario. We hypothesize that the unexplained remaining VMT may be explained by infrastructure supply constraints that result in suppression of travel. This finding has impacts on how we see the role of hard infrastructure systems in urban growth and we explore these impacts in the research.
ContributorsFraser, Andrew (Author) / Chester, Mikhail V (Thesis advisor) / Pendyala, Ram M. (Committee member) / Seager, Thomas P (Committee member) / Arizona State University (Publisher)
Created2014
Description
The environmental and economic assessment of neighborhood-scale transit-oriented urban form changes should include initial construction impacts through long-term use to fully understand the benefits and costs of smart growth policies. The long-term impacts of moving people closer to transit require the coupling of behavioral forecasting with environmental assessment. Using new light rail and bus rapid transit in Los Angeles, California as a case study, a life-cycle environmental and economic assessment is developed to assess the potential range of impacts resulting from mixed-use infill development. An integrated transportation and land use life-cycle assessment framework is developed to estimate energy consumption, air emissions, and economic (public, developer, and user) costs. Residential and commercial buildings, automobile travel, and transit operation changes are included and a 60-year forecast is developed that compares transit-oriented growth against growth in areas without close access to high-capacity transit service. The results show that commercial developments create the greatest potential for impact reductions followed by residential commute shifts to transit, both of which may be effected by access to high-capacity transit, reduced parking requirements, and developer incentives. Greenhouse gas emission reductions up to 470 Gg CO2-equivalents per year can be achieved with potential costs savings for TOD users. The potential for respiratory impacts (PM10-equivalents) and smog formation can be reduced by 28-35%. The shift from business-as-usual growth to transit-oriented development can decrease user costs by $3,100 per household per year over the building lifetime, despite higher rental costs within the mixed-use development.
ContributorsNahlik, Matthew (Author) / Chester, Mikhail V (Thesis advisor) / Pendyala, Ram (Committee member) / Fraser, Matthew (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
A major obstacle to sustainable solar technologies is end-of-life solar modules. In this thesis, a recycling process is proposed for crystalline-Si solar modules. It is a three-step process to break down Si modules and recover various materials. Over 95% of a module by weight can be recovered with this process. Two new technologies are demonstrated to enable the proposed recycling process. One is sequential electrowinning which allows multiple metals to be recovered one by one from Si modules, Ag, Pb, Sn and Cu. The other is sheet resistance monitoring by the 4-point probe which maximizes the amount of solar-grade Si recovered from Si modules with high throughput. The purity of the recovered metals is above 99% and the recovery rate can achieve between 70~80%. The recovered Si meets the specifications for solar-grade Si and at least 91% of Si from c-Si solar cells can be recovered. The recovered Si and metals are new feedstocks to the solar industry and generate over $12/module in revenue. This revenue enables a profitable recycling business for Si modules without any government support. The chemicals for recycling are carefully selected to minimize their environmental impact and also the cost. A network for collecting end-of-life solar modules is proposed based on the current distribution network for solar modules to contain the collection cost. As a result, the proposed recycling process for c-Si modules is technically, environmentally and financially sustainable.
ContributorsHuang, Wenxi (Author) / Tao, Meng (Thesis advisor) / Alford, Terry (Committee member) / Sinha, Parikhit (Committee member) / Arizona State University (Publisher)
Created2018
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
There has been much work done predicting the effects of climate change on transportation systems, this research parallels that past work and focuses on the effect of changes in precipitation on roadway drainage systems. On a macro level, this work addresses the process that should be taken to make predictions about the vulnerability of this system due to changes in precipitation. This work also addresses the mechanisms of failure of these drainage systems and how they may be affected by changes in precipitation due to climate change. These changes may entail more frequent failure by certain mechanisms, or a shift in the mechanisms for particular infrastructure. A sample water basin in the urban environment of Phoenix, Arizona is given as a case study. This study looks at the mechanisms of failure of the infrastructure therein, as well as provides a process of analyzing the effects of increases in precipitation to the vulnerability of this infrastructure. It was found that drainage structures at roadways being currently designed will see increases from 20-30% in peak discharge, which will lead to increased frequency of failure.
ContributorsHolt, Nathan Thomas (Author) / Chester, Mikhail V (Thesis director) / Mascaro, Giuseppe (Committee member) / Underwood, Benjamin S. (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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
Photovoltaics (PV) is an environmentally promising technology to meet climate goals and transition away from greenhouse-gas (GHG) intensive sources of electricity. The dominant approach to improve the environmental gains from PV is increasing the module efficiency and, thereby, the renewable electricity generated during use. While increasing the use-phase environmental benefits, this approach doesn’t address environmentally intensive PV manufacturing and recycling processes.
Lifecycle assessment (LCA), the preferred framework to identify and address environmental hotspots in PV manufacturing and recycling, doesn’t account for time-sensitive climate impact of PV manufacturing GHG emissions and underestimates the climate benefit of manufacturing improvements. Furthermore, LCA is inherently retrospective by relying on inventory data collected from commercial-scale processes that have matured over time and this approach cannot evaluate environmentally promising pilot-scale alternatives based on lab-scale data. Also, prospective-LCAs that rely on hotspot analysis to guide future environmental improvements, (1) don’t account for stake-holder inputs to guide environmental choices in a specific decision context, and (2) may fail in a comparative context where the mutual differences in the environmental impacts of the alternatives and not the environmental hotspots of a particular alternative determine the environmentally preferable alternative
This thesis addresses the aforementioned problematic aspects by (1)using the time-sensitive radiative-forcing metric to identify PV manufacturing improvements with the highest climate benefit, (2)identifying the environmental hotspots in the incumbent CdTe-PV recycling process, and (3)applying the anticipatory-LCA framework to identify the most environmentally favorable alternative to address the recycling hotspot and significant stakeholder inputs that can impact the choice of the preferred recycling alternative.
The results show that using low-carbon electricity is the most significant PV manufacturing improvement and is equivalent to increasing the mono-Si and multi-Si module efficiency from a baseline of 17% to 21.7% and 16% to 18.7%, respectively. The elimination of the ethylene-vinyl acetate encapsulant through mechanical and chemical processes is the most significant environmental hotspot for CdTe PV recycling. Thermal delamination is the most promising environmental alternative to address this hotspot. The most significant stake-holder input to influence the choice of the environmentally preferable recycling alternative is the weight assigned to the different environmental impact categories.
Lifecycle assessment (LCA), the preferred framework to identify and address environmental hotspots in PV manufacturing and recycling, doesn’t account for time-sensitive climate impact of PV manufacturing GHG emissions and underestimates the climate benefit of manufacturing improvements. Furthermore, LCA is inherently retrospective by relying on inventory data collected from commercial-scale processes that have matured over time and this approach cannot evaluate environmentally promising pilot-scale alternatives based on lab-scale data. Also, prospective-LCAs that rely on hotspot analysis to guide future environmental improvements, (1) don’t account for stake-holder inputs to guide environmental choices in a specific decision context, and (2) may fail in a comparative context where the mutual differences in the environmental impacts of the alternatives and not the environmental hotspots of a particular alternative determine the environmentally preferable alternative
This thesis addresses the aforementioned problematic aspects by (1)using the time-sensitive radiative-forcing metric to identify PV manufacturing improvements with the highest climate benefit, (2)identifying the environmental hotspots in the incumbent CdTe-PV recycling process, and (3)applying the anticipatory-LCA framework to identify the most environmentally favorable alternative to address the recycling hotspot and significant stakeholder inputs that can impact the choice of the preferred recycling alternative.
The results show that using low-carbon electricity is the most significant PV manufacturing improvement and is equivalent to increasing the mono-Si and multi-Si module efficiency from a baseline of 17% to 21.7% and 16% to 18.7%, respectively. The elimination of the ethylene-vinyl acetate encapsulant through mechanical and chemical processes is the most significant environmental hotspot for CdTe PV recycling. Thermal delamination is the most promising environmental alternative to address this hotspot. The most significant stake-holder input to influence the choice of the environmentally preferable recycling alternative is the weight assigned to the different environmental impact categories.
ContributorsTriplican Ravikumar, Dwarakanath (Author) / Seager, Thomas P (Thesis advisor) / Fraser, Matthew P (Thesis advisor) / Chester, Mikhail (Committee member) / Sinha, Parikhit (Committee member) / Tao, Meng (Committee member) / Arizona State University (Publisher)
Created2016