No description available.

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Thesis (M.S.)--Oregon State University, 2011. / Printout. Includes bibliographical references (leaf 23). Also available on the World Wide Web.

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The purpose of this research, based on classical diffusion of innovations theory, was to examine factors related to the probable adoption or nonadoption of energy-efficient housing alternatives, specifically passive and active solar and earth sheltered/underground dwellings. Three types of factors were examined: demographics (geographical location by state, type of household, stage in family life cycle, race, age, and educational level); energy (belief in the energy crisis, the impact of energy on housing decisions, efforts to reduce utility costs, average monthly utility costs, and the presence of energy-conserving features in the dwelling); and, local regulatory codes for building (the presence of housing alternatives in the locality, the presence of regulatory codes, and the prior need for variances in order to construct alternative forms of housing). The study utilized daca collected as part of a regional research project, S-141, Housing for Low- and Moderate-Income Families. Data from households were collected by means of an interview schedule using a random sample of 1804 households from four counties selected in each of seven southern states after stratification on the basis of income and the number of nonfarm households. Data from local building officials in the same counties were collected using mailed questionnaires. Techniques of analysis utilized included the chi-squared test, analysis of variance, analysis of covariance, the t-test, and discriminant analysis. Findings indicated that probable adopters of the housing alternatives were usually younger, had more education, were in the earlier stages of the family life cycle, believed in the energy crisis, believed the energy situation had impacted housing decisions, had attempted to reduce utility costs, and lived in houses with more energy-conserving features than probable nonadopters. / Ph. D.

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Air pollution is the world’s greatest environmental health risk factor and reducing exposure remains an ongoing challenge around the world. Among the world’s poor, marginalized, and rural populations, household air pollution from the inefficient burning of biomass fuels like firewood, charcoal, dung, and agricultural residues for daily household energy needs is a leading cause of morbidity and mortality, especially for children under the age of five years. However, household air pollution exposure is a modifiable risk factor and clean-burning cooking fuels like gas and electricity promise substantial health benefits for the 2.8 billion people reliant on biomass fuels. But, clean fuels remain prohibitively expensive or inaccessible for those most reliant on biomass fuels. It is in this context that I examine Ecuador – where substantial cooking gas subsidies have facilitated a nationwide transition to household clean fuel use over four decades – as a long-term case study to understand the potential for widespread clean fuel uptake to reduce air pollution exposure and improve children’s health. Chapter 1 provides background information that contextualizes the work presented in this dissertation. In Chapter 2, I discuss the development of Ecuador’s clean fuel policies. Originally established as a part of broad social support reforms in the 1970s, direct-to-consumer subsidies that lowered the cost of liquefied petroleum gas (LPG) – a popular clean-burning cooking fuel used widely around the world – have driven a transition from 80% of households cooking primarily with firewood in the 1970s to now 90% relying primarily on LPG. However, widespread clean fuel use has come at a cost; each year, the Government of Ecuador spends approximately 1% of the national growth domestic product subsidizing LPG (300-700 million USD). To reduce this financial burden, the government has offered incentives to households to install and use induction electric stoves, which can be powered by the nation’s growing hydroelectric capacity, thereby reducing the cost of LPG subsidies and greenhouse gas emissions. To supplement national data, I administered household energy surveys in a northern province, finding that while all households regularly used LPG, 80% still used firewood for cooking. In these remote regions along the Colombian border, limited access to LPG cylinder refills remains a significant barrier to exclusive LPG use, even after decades of building a robust distribution system. In Chapter 3, I describe results from tailored household surveys – covering energy end uses, costs and access to fuels, and fuel use preferences – administered in 808 households across coastal and Andean Ecuador. Nearly all participants reported using LPG for more than a decade and having frequent, convenient access to cheap LPG cylinder refills. Nonetheless, half of rural households and one-fifth of peri-urban households relied on firewood for cooking and to meet specific household energy needs, like space heating or heating water for bathing. Induction stoves were rare and many induction stove owners reported zero use because the required equipment had never been installed by electricity companies, their stove had broken, or they feared high electricity costs. Here, I show that nationally-representative surveys reporting only “primary cooking fuel” use may underestimate solid fuel use as a secondary option, particularly in rural areas where LPG fuel availability issues play an important role in cooking fuel decision making. These findings additionally indicate that persistent biomass use may curtail the benefits from even the most aggressive clean fuel policies and suggest that additional targeted interventions may be needed to more fully displace biomass. Furthermore, they highlight the need for more nuanced nationally- and subnationally-representative surveys to better understand the extent to which biomass fuels are used secondary to LPG throughout all regions of Ecuador. In Chapter 4, I present results from a sensor monitoring study where we measured personal PM2.5 exposure and stove use for 48-hour monitoring periods among 157 households in peri- urban and rural Ecuador. Firewood-using participants had higher distributions of 48-hour and 10-minute PM2.5 exposure as compared with primary LPG and induction stove users. Accounting for within-subject clustering, contemporaneous firewood stove use was associated with 101 μg/m3 higher 10-min PM2.5 exposure (95% confidence interval: 94–108 μg/m3). Cooking events with clean fuels were not associated with contemporaneous increases in PM2.5 exposure. These findings confirm our expectations that in a region with low ambient air pollution, long-term cooking gas subsidies can lead to relatively low personal air pollution exposures. And yet, persistent secondary firewood use led to higher average and peak exposures, further motivating the displacement of firewood use to reduce health risks from air pollution. I also outline the methodological challenges faced in combining time-resolved sensor data on participant location, stove use monitors, and PM2.5 concentration and offered advice for future studies. In Chapter 5, I assess whether Ecuador’s increased clean cooking fuel use has resulted in improvements in under-5 lower respiratory infection (LRI) mortality. Globally, LRIs are the leading cause of death for children under-5 and household air pollution exposure is a leading risk factor. I employ public use data on cooking fuel use and cause-coded mortalities from 1990 to 2019 to estimate the association between clean cooking fuel use and the rate of under-5 LRI mortalities at the canton (county) level in Ecuador. Using generalized additive mixed models with fixed effects for canton and study period, I observed a significant, non-linear negative association providing evidence that when more than 60% of households in a canton cook primarily with a clean fuel, increased clean fuel use is associated with reductions in under-5 LRI mortality. In total, I estimated that increased clean cooking fuel use is associated with 7,343 under-5 LRI mortalities averted since 1990. In Chapter 6, I conclude by discussing the broader implications of my work. Energy is an important thread connecting climate change, air pollution, and human health, and pathways towards cleaner energy generation will be important drivers of climate change mitigation, reduced environmental exposures, and improved population health. Investments in clean cookstoves have had mixed results over the last 40 years, with many studies revealing only limited uptake of intervention stoves and substantial continued use of polluting traditional fuels, resulting in lower-than-expected exposure reductions and health benefits. Ecuador’s transition has been remarkable in the context of its peer low- and middle-income countries in the rest of Latin America and beyond. The findings presented in this dissertation demonstrate that cooking gas is popular; when it is made cheap and available, gas significantly displaces the use of polluting fuels. Nevertheless, even under ideal cost and access circumstances, my work also reveals that policies and interventions will need to consider specific local needs – like space heating in cold climates – to further encourage a transition toward cleaner indoor air. In the context of efforts to eliminate the use of polluting fuels in the Americas, my work offers hope that ambitious clean cooking fuel policies will improve health.

Installation and utilization of residential distribution transformers has not changed substantially over a long period of time. Utilities typically size their transformers based on a formula that takes into account broadly what types and how many dwellings will be connected. Most new residential dwellings feature 200 Amp service per household with an anticipated energy demand of under 20,000 kWh per year. Average electrical energy consumption varies from state to state but averages to 11,280 kWh per year. Energy demand is expected to fall into a typical residential load curve that shows increased demand early in the morning, then decreasing during the day and another peak early to late evening. Distribution transformers are sized at the limit of the combined evening peak with the assumption that the transformer has enough thermal mass to absorb short overloads that may occur when concurrent loading situations among multiple dwellings arise. The assumption that concurrent loading is of short duration and the transformer can cool off during the night time has been validated over the years and has become standard practice. This has worked well when dwelling loads follow an averaging scheme and low level of coincidence. With the arrival of electric vehicles (EV's) this assumption has to be reevaluated. The acquisition of an electric vehicle in a household can drive up energy demand by over 4000 kWh per year. Potentially problematic is the increased capacity of battery packs and the resulting proliferation of Level 2 chargers. The additional load of a single Level 2 charger concurring with the combined evening peak load will push even conservatively sized distribution transformers over their nameplate rating for a substantial amount of time. Additionally, unlike common household appliances of similar power requirements such as ovens or water heaters, a Level 2 battery charger will run at peak power consumption for several hours, and the current drawn by the EVs has very high levels of harmonic distortion. The excessive loading and harmonic profile can potentially result in damaging heat build-up resulting in asset degradation. In this thesis I present a device and method that monitors pole mounted distribution transformers for overheating, collect and wirelessly upload data and initiate commands to chargers to change output levels from Level 2 to Level 1 or shut down EV charging altogether until the transformer returns into safe operational range.

In recent years, due to the increasing efficiency and availability of information technologies for collecting massive amounts of data (e.g., smart meters and sensors), a variety of advanced technologies and decision-making strategies in the civil engineering sector have shifted in leaps and bounds to a data-driven manner. While there is still no consensus in industry and academia on the latest advances, challenges, and trends in some innovative data-driven methods related to, e.g., deep learning and neural networks, it is undeniable that these techniques have been proven to be considerably effective in helping our academics and engineers solve many real-life tasks related to the smart city framework. This dissertation systematically presents the investigation and development of the cutting-edge data-driven methods related to two specific areas of civil engineering, namely, Residential Electricity Modeling (REM) and Structural Health Monitoring (SHM). For both components, the presentation of this dissertation starts with a brief review of classical data-driven methods used in particular problems, gradually progresses to an exploration of the related state-of-the-art technologies, and eventually lands on our proposed novel data-driven strategies and algorithms. In addition to the classical and state-of-the-art modeling techniques focused on these two areas, this dissertation also put great emphasis on the proposed effective feature extraction and selection approaches. These approaches are aimed to optimize model performance and to save computational resources, for achieving the ideal characterization of the information embedded in the collected raw data that is most relevant to the problem objectives, especially for the case of modeling deep neural networks. For the problems on REM, the proposed methods are validated with real recorded data from multi-family residential buildings, while for SHM, the algorithms are validated with data from numerically simulated systems as well as real bridge structures.

The perception of thermal comfort is an important factor influencing the acceptability of residential heating strategies. The perceived thermal comfort may affect a person's inclination to try a strategy or to use it on a long-term basis. In the study, perceived thermal comfort was assessed in relation to room temperature, humidity, clothing worn, preferred room temperatures, personal control over the temperatures, and energy consumption. The relationships among these variables were examined for five families participating in a live-in study comparing five residential heating strategies. The strategies tested included closing off bedroom vents/doors, setting the thermostat at 65°F, and the use of a solar greenhouse and a woodstove as supplemental heat sources. The families lived in a retrofitted solar test house for a period of four to six weeks. The house was equipped with a computer which monitored 37 channels of information at ten-second intervals and recorded the data hourly. The data collected included temperatures in every room, inside and outside humidity, wind velocity, and other variables that interplay in comfort levels and energy use. The ten adult respondents completed daily and weekly questionnaires containing Likert-type scales of thermal comfort and checklists of clothing worn. The results suggest the following conclusions: 1) the use of a residential setting to measure thermal comfort under varying environmental conditions can be successfully accomplished, 2) psychological variables such as personal control should be considered and tested by persons involved in standards development for the thermal environment, 3) the ability and experience of the persons to use a strategy can affect the achieved energy saving benefits of the strategy, 4) personal preference in the amount of personal effort a person is willing or able to give will impact on the decision on whether to use certain strategies, 5) heating strategies that can produce a direct source of heat or at least some warmer areas were rated higher by the project participants, and 6) weather can play an important role in the effectiveness of the solar greenhouse as a heating source. / Ph. D. / incomplete_metadata