Matching Items (15)

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Effect of Climate Change on Arizona Roadway Drainage Infrastructure

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

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.

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Created

Date Created
  • 2016-12

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Peak travel in a megacity: exploring the role of infrastructure saturation on the suppression of automobile use

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

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.

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Created

Date Created
  • 2014

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Techno-economic analysis of a concentrating solar power plant using reduction/oxidation metal oxides for thermochemical energy storage

Description

Concentrating Solar Power (CSP) plant technology can produce reliable and dispatchable electric power from an intermittent solar resource. Recent advances in thermochemical energy storage (TCES) can offer further improvements to

Concentrating Solar Power (CSP) plant technology can produce reliable and dispatchable electric power from an intermittent solar resource. Recent advances in thermochemical energy storage (TCES) can offer further improvements to increase off-sun operating hours, improve system efficiency, and the reduce cost of delivered electricity. This work describes a 111.7 MWe CSP plant with TCES using a mixed ionic-electronic conducting metal oxide, CAM28, as both the heat transfer and thermal energy storage media. Turbine inlet temperatures reach 1200 °C in the combined cycle power block. A techno-economic model of the CSP system is developed to evaluate design considerations to meet targets for low-cost and renewable power with 6-14 hours of dispatchable storage for off-sun power generation. Hourly solar insolation data is used for Barstow, California, USA. Baseline design parameters include a 6-hour storage capacity and a 1.8 solar multiple. Sensitivity analyses are performed to evaluate the effect of engineering parameters on total installed cost, generation capacity, and levelized cost of electricity (LCOE). Calculated results indicate a full-scale 111.7 MWe system at $274 million in installed cost can generate 507 GWh per year at a levelized cost of $0.071 per kWh. Expected improvements to design, performance, and costs illustrate options to reduce energy costs to less than $0.06 per kWh.

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Created

Date Created
  • 2017

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Anticipating and adapting to increases in water distribution infrastructure failure caused by interdependencies and heat exposure from climate change

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

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.

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Created

Date Created
  • 2019

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Contingency Analysis for Coupled Power-Water Networks

Description

A mathematical approach was developed to evaluate the resilience of coupled power-water networks using a variant of contingency analysis adapted from electric transmission studies. In particular, the “what if” scenarios

A mathematical approach was developed to evaluate the resilience of coupled power-water networks using a variant of contingency analysis adapted from electric transmission studies. In particular, the “what if” scenarios explored in power systems research were extended and applied for coupled power-water network research by evaluating how stressors and failures in the water network can propagate across system boundaries and into the electric network. Reduction in power system contingency reserves was the metric for determining violation of N-1 contingency reliability. Geospatial considerations were included using high-resolution, publicly available Geographic Information System data on infrastructure in the Phoenix Metropolitan Area that was used to generate a power network with 599 transmission lines and total generation capacity of 18.98 GW and a water network with 2,624 water network lines and capacity to serve up to 1.72M GPM of surface water. The steady-state model incorporated operating requirements for the power network—e.g., contingency reserves—and the water network—e.g., pressure ranges—while seeking to meet electric load and water demand. Interconnections developed between the infrastructures demonstrated how alternations to the system state and/or configuration of one network affect the other network, with results demonstrated through co-simulation of the power network and water network using OpenDSS and EPANET, respectively. Results indicate four key findings that help operators understand the interdependent behavior of the coupled power-water network: (i) two water failure scenarios (water flowing out of Waddell dam and CAP canal flowing west of Waddell dam) are critical to power-water network N-1 contingency reliability above 60% power system loading and at 100% water system demand, (ii) fast-starting natural gas generating units are necessary to maintain N-1 contingency reliability below 60% power system loading, (iii) Coolidge Station was the power plant to most frequently undergo a reduction in reserves amongst the water failure scenarios that cause a violation of N-1 reliability, (iv) power network vulnerability to water network failures was non-linear because it depends on the generating units that are dispatched, which can vary as line thermal limits or unit generation capacities are reached.

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Created

Date Created
  • 2020

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Investigation of heat-driven polygeneration and adsorption cooling systems

Description

Just for a moment! Imagine you live in Arizona without air-conditioning systems!

Air-conditioning and refrigeration systems are one of the most crucial systems in anyone’s house and car these days. Energy

Just for a moment! Imagine you live in Arizona without air-conditioning systems!

Air-conditioning and refrigeration systems are one of the most crucial systems in anyone’s house and car these days. Energy resources are becoming more scarce and expensive. Most of the currently used refrigerants have brought an international concern about global warming. The search for more efficient cooling/refrigeration systems with environmental friendly refrigerants has become more and more important so as to reduce greenhouse gas emissions and ensure sustainable and affordable energy systems. The most widely used air-conditioning and refrigeration system, based on the vapor compression cycle, is driven by converting electricity into mechanical work which is a high quality type of energy. However, these systems can instead be possibly driven by heat, be made solid-state (i.e., thermoelectric cooling), consist entirely of a gaseous working fluid (i.e., reverse Brayton cycle), etc. This research explores several thermally driven cooling systems in order to understand and further overcome some of the major drawbacks associated with their performance as well as their high capital costs. In the second chapter, we investigate the opportunities for integrating single- and double-stage ammonia-water (NH3–H2O) absorption refrigeration systems with multi-effect distillation (MED) via cascade of rejected heat for large-scale plants. Similarly, in the third chapter, we explore a new polygeneration cooling-power cycle’s performance based on Rankine, reverse Brayton, ejector, and liquid desiccant cycles to produce power, cooling, and possibly fresh water for various configurations. Different configurations are considered from an energy perspective and are compared to stand-alone systems. In the last chapter, a new simple, inexpensive, scalable, environmentally friendly cooling system based on an adsorption heat pump system and evacuated tube solar collector is experimentally and theoretically studied. The system is destined as a small-scale system to harness solar radiation to provide a cooling effect directly in one system.

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Created

Date Created
  • 2018

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Transit-oriented smart growth can reduce life-cycle environmental impacts and household costs in Los Angeles

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 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.

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Created

Date Created
  • 2014

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Addressment of uncertainty and variability in attributional environmental life cycle assessment

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

'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.

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Created

Date Created
  • 2016

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Photovoltaic capacity additions: the optimal rate of deployment with sensitivity to time-based GHG emissions

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

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.

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Created

Date Created
  • 2013

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Stochastic Multi Attribute Analysis for comparative life cycle assessment

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.

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.

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Created

Date Created
  • 2015