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- All Subjects: Energy consumption
- All Subjects: Life cycle costing
- Creators: Arizona State University. Center for Earth Systems Engineering and Management
- Creators: Parrish, Kristen
- Creators: Barnes, Elizabeth
This thesis attempts to achieve the research objectives by examining the LEED certified buildings on the Arizona State University (ASU) campus in Tempe, AZ, from two complementary perspectives: the Macro-level and the Micro-level. Heating, cooling, and electricity data were collected from the LEED-certified buildings on campus, and their energy use intensity was calculated in order to investigate the buildings' actual energy performance. Additionally, IEQ occupant satisfaction surveys were used to investigate users' satisfaction with the space layout, space furniture, thermal comfort, indoor air quality, lighting level, acoustic quality, water efficiency, cleanliness and maintenance of the facilities they occupy.
From a Macro-level perspective, the results suggest ASU LEED buildings consume less energy than regional counterparts, and exhibit higher occupant satisfaction than national counterparts. The occupant satisfaction results are in line with the literature on LEED buildings, whereas the energy results contribute to the inconclusive body of knowledge on energy performance improvements linked to LEED certification. From a Micro-level perspective, data analysis suggest an inconsistency between the LEED points earned for the Energy & Atmosphere and IEQ categories, on one hand, and the respective levels of energy consumption and occupant satisfaction on the other hand. Accordingly, this study showcases the variation in the performance results when approached from different perspectives. This contribution highlights the need to consider the Macro-level and Micro-level assessments in tandem, and assess LEED building performance from these two distinct but complementary perspectives in order to develop a more comprehensive understanding of the actual building performance.
New quantitative sustainability indices are proposed to capture the energy system environmental impacts, economic performance, and resilience attributes, characterized by normalized environmental/health externalities, energy costs, and penalty costs respectively. A comprehensive Life Cycle Assessment is proposed which includes externalities due to emissions from different supply and demand-side energy systems specific to the regional power generation energy portfolio mix. An approach based on external costs, i.e. the monetized health and environmental impacts, was used to quantify adverse consequences associated with different energy system components.
Further, this thesis also proposes a new performance-based method for characterizing and assessing resilience of multi-functional demand-side engineered systems. Through modeling of system response to potential internal and external failures during different operational temporal periods reflective of diurnal variation in loads and services, the proposed methodology quantifies resilience of the system based on imposed penalty costs to the system stakeholders due to undelivered or interrupted services and/or non-optimal system performance.
A conceptual diagram called “Sustainability Compass” is also proposed which facilitates communicating the assessment results and allow better decision-analysis through illustration of different system attributes and trade-offs between different alternatives. The proposed methodologies have been illustrated using end-use monitored data for whole year operation of a university campus energy system.
In the construction industry, the management of knowledge is becoming an increasingly important element for success. The successful management of knowledge helps general contractors to better compete which ultimately leads to more contracts and potentially greater prots. The Life Cycle Costing assessment presented here is a small step in understanding the complex decision of investing in BIM from general contractor's perspective. This assessment has identified the cost components for BIM and has allocated the cost for a typical project.
There is no ’typical’ production process for Legally Autonomous Adults (LAD). However, some very general inputs and flows can be assumed: Physical, mental, emotional, and social or cultural inputs are provided by primary caregivers throughout the process. LADs in Arizona in the 21st century are produced in small batches. Inputs tend to be provided by consistent sources according to unique values, and the production process does not actually stop cold at the factory gate, but continues on into the next phase.
Sometimes, due to externalities like substance dependence or domestic violence, the original production process either deprives the product of essential inputs or adds toxic inputs, causing damage. The damage can carry forward into the next phases, or even be so severe that the production process is terminated. When there is a risk of such damage, then the product – the child – is removed from his original production system, taken into the custody of a state-run institution (Child Protective Services), and placed in foster care.
LADs who have experienced a foster care intervention as part of their production process are less likely to have that obligatory property of Legal Autonomy, and more likely to have obligatory properties that are detrimental to society at large. Omitting other variables, they have higher rates of incarceration, homelessness, and substance abuse than LADs who have not been in out-of-home foster care. The financial and societal costs of those dependencies are imposed on the same stakeholders whose efforts and contributions make the foster care system possible.
CPS removal triggers a system expansion that expends energy and resources in an attempt to compensate for the missing inputs and to mitigate the toxic inputs, if any, that the child’s family was adding. In a material production system, it seems illogical to construct a complex system expansion which predictably results in products lacking their most important obligatory property. That contradiction was the impetus for this paper.
The goal of this life cycle analysis is to visualize that system expansion. Then, the project seeks to quantify and compare the difference between this system expansion and the generalized original process, in units of dollars per LAD. Finally, the project assesses the statistical impacts of the system expansion on LADs, and describes further impacts of these LADs on society at large.
The dissertation utilizes Interval Data (ID) and establishes three different frameworks to identify electricity losses, predict electricity consumption and detect anomalies using data mining, deep learning, and mathematical models. The process of energy analytics integrates with the computational science and contributes to several objectives which are to
1. Develop a framework to identify both technical and non-technical losses using clustering and semi-supervised learning techniques.
2. Develop an integrated framework to predict electricity consumption using wavelet based data transformation model and deep learning algorithms.
3. Develop a framework to detect anomalies using ensemble empirical mode decomposition and isolation forest algorithms.
With a thorough research background, the first phase details on performing data analytics on the demand-supply database to determine the potential energy loss reduction potentials. Data preprocessing and electricity prediction framework in the second phase integrates mathematical models and deep learning algorithms to accurately predict consumption. The third phase employs data decomposition model and data mining techniques to detect the anomalies of institutional buildings.
Vehicle trips presently account for approximately 50% of San Francisco’s greenhouse gas emissions (San Francisco County Transportation Authority, 2008). City and county officials have developed aggressive strategies for the future of passenger transportation in the metropolitan area, and are determined to move away from a “business as usual” future. This project starts with current-state source data from a life-cycle comparison of urban transportation systems (Chester, Horvath, & Madanat, 2010), and carries the inventoried emissions and energy usage through by way of published future scenarios for San Francisco.
From the extrapolated calculations of future emissions/energy, the implied mix of transportation modes can be backed out of the numbers. Five scenarios are evaluated, from “business as usual” through very ambitious “healthy environment” goals. The results show that when planners and policymakers craft specific goals or strategies for a location or government, those targets, even if met, are unlikely to result in the intended physical outcomes. City and state governments would be wise to support broad strategy goals (like 20% GHG reduction) with prioritized specifics that can inform real projects leading to the goals (for instance, add 5 miles of bike path per year through 2020, or remove 5 parking garages and replace them with transit depots). While these results should not be used as predictions or forecasts, they can inform the crafters of future transportation policy as an opportunity for improvement or a cautionary tale.
This LCA used data from a previous LCA done by Chester and Horvath (2012) on the proposed California High Speed Rail, and furthered the LCA to look into potential changes that can be made to the proposed CAHSR to be more resilient to climate change. This LCA focused on the energy, cost, and GHG emissions associated with raising the track, adding fly ash to the concrete mixture in place of a percentage of cement, and running the HSR on solar electricity rather than the current electricity mix. Data was collected from a variety of sources including other LCAs, research studies, feasibility studies, and project information from companies, agencies, and researchers in order to determine what the cost, energy requirements, and associated GHG emissions would be for each of these changes. This data was then used to calculate results of cost, energy, and GHG emissions for the three different changes. The results show that the greatest source of cost is the raised track (Design/Construction Phase), and the greatest source of GHG emissions is the concrete (also Design/Construction Phase).
The ultimate goal of this LCA is to give Arizona State University specific advice on possible changes in lighting systems that will reduce environmental impacts and support ASU’s sustainability efforts. The aim is to assess the potential for a decrease in specific environmental impacts (CO2 emissions and energy use) and economic impact (cost) from changing to a different type of lighting in a prototypical classroom in Wrigley Hall. The scope of this assessment is to analyze the impacts of T8 lamps lasting 50,000 hours. Thus, a functional unit was defined as 50,000 hours of use, maintaining roughly 825 lumens. To put this in perspective, 50,000 hours is equivalent to 8 hours of use per day, 365 days per year, for approximately 17.1 years.
An inter-temporal life cycle cost and greenhouse gas emissions assessment of the Los Angeles roadway network is developed to identify how construction decisions lead to embedded impacts and create an emergent behavior (vehicle miles traveled by users) in the long run.
A video of the growth of the network and additional information are available here.
Sustainable mobility policy for long-distance transportation services should consider emerging automobiles and aircraft as well as infrastructure and supply chain life-cycle effects in the assessment of new high-speed rail systems. Using the California corridor, future automobiles, high-speed rail and aircraft long-distance travel are evaluated, considering emerging fuel-efficient vehicles, new train designs and the possibility that the region will meet renewable electricity goals. An attributional per passenger-kilometer-traveled life-cycle inventory is first developed including vehicle, infrastructure and energy production components. A consequential life-cycle impact assessment is then established to evaluate existing infrastructure expansion against the construction of a new high-speed rail system. The results show that when using the life-cycle assessment framework, greenhouse gas footprints increase significantly and human health and environmental damage potentials may be dominated by indirect and supply chain components. The environmental payback is most sensitive to the number of automobile trips shifted to high-speed rail, and for greenhouse gases is likely to occur in 20–30 years. A high-speed rail system that is deployed with state-of-the-art trains, electricity that has met renewable goals, and in a configuration that endorses high ridership will provide significant environmental benefits over existing modes. Opportunities exist for reducing the long-distance transportation footprint by incentivizing large automobile trip shifts, meeting clean electricity goals and reducing material production effects.