Matching Items (46)
Description
According to the U.S. Energy Information Administration, commercial buildings represent about 40% of the United State's energy consumption of which office buildings consume a major portion. Gauging the extent to which an individual building consumes energy in excess of its peers is the first step in initiating energy efficiency improvement. Energy Benchmarking offers initial building energy performance assessment without rigorous evaluation. Energy benchmarking tools based on the Commercial Buildings Energy Consumption Survey (CBECS) database are investigated in this thesis. This study proposes a new benchmarking methodology based on decision trees, where a relationship between the energy use intensities (EUI) and building parameters (continuous and categorical) is developed for different building types. This methodology was applied to medium office and school building types contained in the CBECS database. The Random Forest technique was used to find the most influential parameters that impact building energy use intensities. Subsequently, correlations which were significant were identified between EUIs and CBECS variables. Other than floor area, some of the important variables were number of workers, location, number of PCs and main cooling equipment. The coefficient of variation was used to evaluate the effectiveness of the new model. The customization technique proposed in this thesis was compared with another benchmarking model that is widely used by building owners and designers namely, the ENERGY STAR's Portfolio Manager. This tool relies on the standard Linear Regression methods which is only able to handle continuous variables. The model proposed uses data mining technique and was found to perform slightly better than the Portfolio Manager. The broader impacts of the new benchmarking methodology proposed is that it allows for identifying important categorical variables, and then incorporating them in a local, as against a global, model framework for EUI pertinent to the building type. The ability to identify and rank the important variables is of great importance in practical implementation of the benchmarking tools which rely on query-based building and HVAC variable filters specified by the user.
ContributorsKaskhedikar, Apoorva Prakash (Author) / Reddy, T. Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Runger, George C. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Through manipulation of adaptable opportunities available within a given environment, individuals become active participants in managing personal comfort requirements, by exercising control over their comfort without the assistance of mechanical heating and cooling systems. Similarly, continuous manipulation of a building skin's form, insulation, porosity, and transmissivity qualities exerts control over the energy exchanged between indoor and outdoor environments. This research uses four adaptive response variables in a modified software algorithm to explore an adaptive building skin's potential in reacting to environmental stimuli with the purpose of minimizing energy use without sacrificing occupant comfort. Results illustrate that significant energy savings can be realized with adaptive envelopes over static building envelopes even under extreme summer and winter climate conditions; that the magnitude of these savings are dependent on climate and orientation; and that occupant thermal comfort can be improved consistently over comfort levels achieved by optimized static building envelopes. The resulting adaptive envelope's unique climate-specific behavior could inform designers in creating an intelligent kinetic aesthetic that helps facilitate adaptability and resiliency in architecture.
ContributorsErickson, James (Author) / Bryan, Harvey (Thesis advisor) / Addison, Marlin (Committee member) / Kroelinger, Michael D. (Committee member) / Reddy, T. Agami (Committee member) / Arizona State University (Publisher)
Created2013
Description
For some time it has been recognized amongst researchers that individual and collective change should be the goal in educating for sustainability, unfortunately education has generally been ineffective in developing pro-environmental behaviors among students. Still, many scholars and practitioners are counting on education to lead us towards sustainability but suggest that in order to do so we must transition away from current information-intensive education methods. In order to develop and test novel sustainability education techniques, this research integrates pedagogical methods with psychological knowledge to target well-established sustainable behaviors. Through integrating education, behavior change, and sustainability research, I aim to answer: How can we motivate sustainable behavioral change through education programs? More specifically: How do diverse knowledge domains (declarative, procedural, effectiveness, and social) influence sustainable behaviors, both in general as well as before and after a sustainability education program? And: What are barriers hindering education approaches to changing behaviors? In answering these questions, this research involved three distinct stages: (1) Developing a theoretical framework for educating for sustainability and transformative change; (2) Implementing a food and waste focused sustainability educational program with K-12 students and teachers while intensively assessing participants' change over the course of one year; (3) Developing and implementing an extensive survey that examines the quantitative relationships between diverse domains of knowledge and behavior among a large sample of K-12 educators. The results from the education program demonstrated that significant changes in knowledge and behaviors were achieved but social knowledge in terms of food was more resistant to change as compared to that of waste. The survey results demonstrated that K-12 educators have high levels of declarative (factual or technical) knowledge regarding anthropocentric impacts on the environment; however, declarative knowledge does not predict their participation in sustainable behaviors. Rather, procedural and social knowledge significantly influence participation in sustainable food behaviors, where as procedural, effectiveness, and social knowledge impact participation in sustainable waste behaviors. Overall, the findings from this research imply that in order to effectively educate for sustainability, we must move away from nature-centric approaches that focus on declarative knowledge and embrace different domains of knowledge (procedural, effectiveness, and social) that emphasis the social implications of change.
ContributorsRedman, Erin (Author) / Larson, Kelli (Thesis advisor) / Eakin, Hallie (Committee member) / Spielmann, Katherine (Committee member) / Arizona State University (Publisher)
Created2013
Description
As climate change becomes a greater challenge in today's society, it is critical to understand young people's perceptions of the phenomenon because they will become the next generation of decision-makers. This study examines knowledge, beliefs, and behaviors among high school students. The subjects of this study include students from high school science classes in Phoenix, Arizona, and Plainfield, Illinois. Using surveys and small group interviews to engage students in two climatically different locations, three questions were answered:
1) What do American students know and believe about climate change? How is knowledge related to beliefs?
2) What types of behaviors are students exhibiting that may affect climate change? How do beliefs relate to behavioral choices?
3) Do climate change knowledge, beliefs, and behaviors vary between geographic locations in the United States?
The results of this study begin to highlight the differences between knowledge, beliefs, and behaviors around the United States. First, results showed that students have heard of climate change but often confused aspects of the problem, and they tended to focus on causes and impacts, as opposed to solutions. Related to beliefs, students tended to believe that climate change is caused by both humans and natural trends, and would affect plant and animal species more than themselves and their families. Second, students were most likely to participate in individual behaviors such as turning off lights and electronics, and least likely to take public transportation and eat a vegetarian meal. Individual behaviors seem to be most relevant to this age group, in contrast to policy solutions. Third, students in Illinois felt they would be more likely to experience colder temperatures and more precipitation than those in Arizona, where students were more concerned about rising temperatures.
Understanding behaviors, motivations behind beliefs and choices, and barriers to actions can support pro-environmental behavior change. Educational strategies can be employed to more effectively account for the influences on a young person's belief formation and behavior choices. Providing engagement opportunities with location-specific solutions that are more feasible for youth to participate in on their own could also support efforts for behavior change.
1) What do American students know and believe about climate change? How is knowledge related to beliefs?
2) What types of behaviors are students exhibiting that may affect climate change? How do beliefs relate to behavioral choices?
3) Do climate change knowledge, beliefs, and behaviors vary between geographic locations in the United States?
The results of this study begin to highlight the differences between knowledge, beliefs, and behaviors around the United States. First, results showed that students have heard of climate change but often confused aspects of the problem, and they tended to focus on causes and impacts, as opposed to solutions. Related to beliefs, students tended to believe that climate change is caused by both humans and natural trends, and would affect plant and animal species more than themselves and their families. Second, students were most likely to participate in individual behaviors such as turning off lights and electronics, and least likely to take public transportation and eat a vegetarian meal. Individual behaviors seem to be most relevant to this age group, in contrast to policy solutions. Third, students in Illinois felt they would be more likely to experience colder temperatures and more precipitation than those in Arizona, where students were more concerned about rising temperatures.
Understanding behaviors, motivations behind beliefs and choices, and barriers to actions can support pro-environmental behavior change. Educational strategies can be employed to more effectively account for the influences on a young person's belief formation and behavior choices. Providing engagement opportunities with location-specific solutions that are more feasible for youth to participate in on their own could also support efforts for behavior change.
ContributorsKruke, Laurel (Author) / Larson, Kelli (Thesis advisor) / Klinsky, Sonja (Committee member) / White, Dave (Committee member) / Arizona State University (Publisher)
Created2015
Description
With the ongoing drought surpassing a decade in Arizona, scholars, water managers and decision-makers have heightened attention to the availability of water resources, especially in rapidly growing regions where demand may outgrow supplies or outpace the capacity of the community water systems. Community water system managing entities and the biophysical and social characteristics of a place mediate communities' vulnerability to hazards such as drought and long-term climate change. The arid southwestern Phoenix metropolitan area is illustrative of the challenges that developed urban areas in arid climates face globally as population growth and climate change stress already fragile human-environmental systems. This thesis reveals the factors abating and exacerbating differential community water system vulnerability to water scarcity in communities simultaneously facing drought and rapid peri-urban growth. Employing a grounded, qualitative comparative case study approach, this thesis explores the interaction of social, biophysical and institutional factors as they effect the exposure, sensitivity and adaptive capacity of community water systems in Cave Creek and Buckeye, Arizona. Buckeye, once a small agricultural town in the West Valley, is wholly dependent on groundwater and currently planning for massive development to accommodate 218,591 new residents by 2020. Amid desert hills and near Tonto National Forest in the North Valley, Cave Creek is an upscale residential community suffering frequent water outages due to aging infrastructure and lack of system redundancy. Analyzing interviews, media accounts and policy documents, a narrative was composed explaining how place based factors, nested within a regional institutional water management framework, impact short and long-term vulnerability. This research adds to the library of vulnerability assessments completed using Polsky et al.'s Vulnerability Scoping Diagram and serves a pragmatic need assisting in the development of decision making tools that better represent the drivers of placed based vulnerability in arid metropolitan regions.
ContributorsZautner, Lilah (Author) / Larson, Kelli (Thesis advisor) / Bolin, Bob (Committee member) / Chhetri, Netra (Committee member) / Arizona State University (Publisher)
Created2011
Description
Buildings in the United States, account for over 68 percent of electricity consumed, 39 percent of total energy use, and 38 percent of the carbon dioxide emissions. By the year 2035, about 75% of the U.S. building sector will be either new or renovated. The energy efficiency requirements of current building codes would have a significant impact on future energy use, hence, one of the most widely accepted solutions to slowing the growth rate of GHG emissions and then reversing it involves a stringent adoption of building energy codes. A large number of building energy codes exist and a large number of studies which state the energy savings possible through code compliance. However, most codes are difficult to comprehend and require an extensive understanding of the code, the compliance paths, all mandatory and prescriptive requirements as well as the strategy to convert the same to energy model inputs. This paper provides a simplified solution for the entire process by providing an easy to use interface for code compliance and energy simulation through a spreadsheet based tool, the ECCO or the Energy Code COmpliance Tool. This tool provides a platform for a more detailed analysis of building codes as applicable to each and every individual building in each climate zone. It also facilitates quick building energy simulation to determine energy savings achieved through code compliance. This process is highly beneficial not only for code compliance, but also for identifying parameters which can be improved for energy efficiency. Code compliance is simplified through a series of parametric runs which generates the minimally compliant baseline building and 30% beyond code building. This tool is seen as an effective solution for architects and engineers for an initial level analysis as well as for jurisdictions as a front-end diagnostic check for code compliance.
ContributorsGoel, Supriya (Author) / Bryan, Harvey J. (Thesis advisor) / Reddy, T. Agami (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2011
Description
The green building movement has been an effective catalyst in reducing energy demands of buildings and a large number of `green' certified buildings have been in operation for several years. Whether these buildings are actually performing as intended, and if not, identifying specific causes for this discrepancy falls into the general realm of post-occupancy evaluation (POE). POE involves evaluating building performance in terms of energy-use, indoor environmental quality, acoustics and water-use; the first aspect i.e. energy-use is addressed in this thesis. Normally, a full year or more of energy-use and weather data is required to determine the actual post-occupancy energy-use of buildings. In many cases, either measured building performance data is not available or the time and cost implications may not make it feasible to invest in monitoring the building for a whole year. Knowledge about the minimum amount of measured data needed to accurately capture the behavior of the building over the entire year can be immensely beneficial. This research identifies simple modeling techniques to determine best time of the year to begin in-situ monitoring of building energy-use, and the least amount of data required for generating acceptable long-term predictions. Four analysis procedures are studied. The short-term monitoring for long-term prediction (SMLP) approach and dry-bulb temperature analysis (DBTA) approach allow determining the best time and duration of the year for in-situ monitoring to be performed based only on the ambient temperature data of the location. Multivariate change-point (MCP) modeling uses simulated/monitored data to determine best monitoring period of the year. This is also used to validate the SMLP and DBTA approaches. The hybrid inverse modeling method-1 predicts energy-use by combining a short dataset of monitored internal loads with a year of utility-bills, and hybrid inverse method-2 predicts long term building performance using utility-bills only. The results obtained show that often less than three to four months of monitored data is adequate for estimating the annual building energy use, provided that the monitoring is initiated at the right time, and the seasonal as well as daily variations are adequately captured by the short dataset. The predictive accuracy of the short data-sets is found to be strongly influenced by the closeness of the dataset's mean temperature to the annual average temperature. The analysis methods studied would be very useful for energy professionals involved in POE.
ContributorsSingh, Vipul (Author) / Reddy, T. Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2011
Description
Arizona has an abundant solar resource and technologically mature systems are available to capture it, but solar energy systems are still considered to be an innovative technology. Adoption rates for solar and wind energy systems rise and fall with the political tides, and are relatively low in most rural areas in Arizona. This thesis tests the hypothesis that a consumer profile developed to characterize the adopters of renewable energy technology (RET) systems in rural Arizona is the same as the profile of other area residents who performed renovations, upgrades or additions to their homes. Residents of Santa Cruz and Cochise Counties who had obtained building permits to either install a solar or wind energy system or to perform a substantial renovation or upgrade to their home were surveyed to gather demographic, psychographic and behavioristic data. The data from 133 survey responses (76 from RET adopters and 57 from non-adopters) provided insights about their decisions regarding whether or not to adopt a RET system. The results, which are statistically significant at the 99% level of confidence, indicate that RET adopters had smaller households, were older and had higher education levels and greater income levels than the non-adopters. The research also provides answers to three related questions: First, are the energy conservation habits of RET adopters the same as those of non-adopters? Second, what were the sources of information consulted and the most important factors that motivated the decision to purchase a solar or wind energy system? And finally, are any of the factors which influenced the decision to live in a rural area in southeastern Arizona related to the decision to purchase a renewable energy system? The answers are provided, along with a series of recommendations that are designed to inform marketers and other promoters of RETs about how to utilize these results to help achieve their goals.
ContributorsPorter, Wayne Eliot (Author) / Reddy, T. Agami (Thesis advisor) / Pasqualetti, Martin (Committee member) / Larson, Kelli (Committee member) / Kennedy, Linda (Committee member) / Arizona State University (Publisher)
Created2011
Description
Lighting systems and air-conditioning systems are two of the largest energy consuming end-uses in buildings. Lighting control in smart buildings and homes can be automated by having computer controlled lights and window blinds along with illumination sensors that are distributed in the building, while temperature control can be automated by having computer controlled air-conditioning systems. However, programming actuators in a large-scale environment for buildings and homes can be time consuming and expensive. This dissertation presents an approach that algorithmically sets up the control system that can automate any building without requiring custom programming. This is achieved by imbibing the system self calibrating and self learning abilities.
For lighting control, the dissertation describes how the problem is non-deterministic polynomial-time hard(NP-Hard) but can be resolved by heuristics. The resulting system controls blinds to ensure uniform lighting and also adds artificial illumination to ensure light coverage remains adequate at all times of the day, while adjusting for weather and seasons. In the absence of daylight, the system resorts to artificial lighting.
For temperature control, the dissertation describes how the temperature control problem is modeled using convex quadratic programming. The impact of every air conditioner on each sensor at a particular time is learnt using a linear regression model. The resulting system controls air-conditioning equipments to ensure the maintenance of user comfort and low cost of energy consumptions. The system can be deployed in large scale environments. It can accept multiple target setpoints at a time, which improves the flexibility and efficiency of cooling systems requiring temperature control.
The methods proposed work as generic control algorithms and are not preprogrammed for a particular place or building. The feasibility, adaptivity and scalability features of the system have been validated through various actual and simulated experiments.
For lighting control, the dissertation describes how the problem is non-deterministic polynomial-time hard(NP-Hard) but can be resolved by heuristics. The resulting system controls blinds to ensure uniform lighting and also adds artificial illumination to ensure light coverage remains adequate at all times of the day, while adjusting for weather and seasons. In the absence of daylight, the system resorts to artificial lighting.
For temperature control, the dissertation describes how the temperature control problem is modeled using convex quadratic programming. The impact of every air conditioner on each sensor at a particular time is learnt using a linear regression model. The resulting system controls air-conditioning equipments to ensure the maintenance of user comfort and low cost of energy consumptions. The system can be deployed in large scale environments. It can accept multiple target setpoints at a time, which improves the flexibility and efficiency of cooling systems requiring temperature control.
The methods proposed work as generic control algorithms and are not preprogrammed for a particular place or building. The feasibility, adaptivity and scalability features of the system have been validated through various actual and simulated experiments.
ContributorsWang, Yuan (Author) / Dasgupta, Partha (Thesis advisor) / Davulcu, Hasan (Committee member) / Huang, Dijiang (Committee member) / Reddy, T. Agami (Committee member) / Arizona State University (Publisher)
Created2015
Description
For the last 10 years, the American Southwest has been experiencing the most persistent drought conditions on record. Based on future climactic predictions, there is a dire need to reduce water usage within Phoenix. An environmentally responsible behavior such as low water use landscaping (xeriscaping), has been shown to reduce household water consumption by 40%-70%. While much is known regarding the relationship between socio-demographics and xeriscaping choices, the influence of other variables remains to be explored. Using data from the 2017 Phoenix Area Social Survey, this study investigates the influence of two additional variables - ecological worldview and place identity on xeriscaping choice. Data was analyzed using two models - Ordinary Least Squares (OLS) and Linear Probability Model (LPM). Ecological worldview and place identity, along with income, ethnicity, and gender, were all found to be positively related to xeriscape preference. Additionally, when compared to the LPM, the traditional OLS was found to still be the most robust and appropriate model when measuring landscape preference. Finally, results suggested that programs to foster identity with the local desert mountain parks may help to increase xeriscaping in the Valley and thus lower residential water use.
ContributorsSampson, Marena (Author) / Budruk, Megha (Thesis advisor) / Larson, Kelli (Committee member) / Gall, Melanie (Committee member) / Arizona State University (Publisher)
Created2018