As the strategy of green building becomes more and more popular due to a combination of environmental and economic concerns, there develops a need for clearly being able to understand the potential implications for choosing green strategies over conventional building practices. Some of the regions of interest consist of the additional upfront costs associated with green practices, potential life-cycle benefits associated with green building components, potential energy savings, and the ability to reduce emissions. Many of these areas can potentially be forecasted with a fair degree of certainty (e.g. energy consumption, additional upfront costs); however, some elements of green building are less well defined. One such area consists of the ability of green buildings to improve the productivity and well-being of its inhabitants through an improved indoor environmental quality (IEQ). It is difficult to grasp just how much a healthier and cleaner environmental can impact a person’s cognitive functions, mental state, and physical health. Several studies shown in the literature review of this paper lead show a positive correlation between green buildings and reductions in asthma symptoms, depression symptoms, improved well-being due to reductions in contaminants, a reduction in sick building syndrome (SBS) and building related illness (BRI). This paper aims to do what many have done before in attempting to quantify the potential impact that sustainable buildings can have on its occupants; however, the scope and methods to determine these potential correlations will differ. Perhaps the most noticeable difference will be in the paper’s focus on attempting to measure the potential impact that LEED (Leadership in Energy and Environmental Design) accredited schools have on their student occupants by measuring their productivity via the use of standardized test scores and attendance rates compared to those students in conventional (non-LEED) schools. To develop a balanced analysis, the paper will control for various school-related and socio-economic factors (e.g. economic status, race, percent of teachers with a Master’s degree or higher). To make a judgement on the effect that sustainability has on academic achievement and student wellbeing, 2 sample t-tests, regression analysis, and M5P decision trees will be implemented to determine if there are significant differences between LEED and conventional schools and to determine the relationship between LEED and non-LEED parameters on student achievement and wellbeing metrics. To ensure that a large population of students from across the nation are accounted for, the study intends on investigating at least three states-worth of student data. These states (Florida, New York and Virginia) are in different climates, thus allowing for an examination of the potential differences between the various climate zones and building codes. Lastly, a case study building information model (BIM) of College Park Elementary School (located in Virginia) will be run through the energy modeling (EM) software, Ecotect, to provide information related to the school’s annual energy consumption, acoustics, and daylight and lighting values. An optimization equation, developed using previous literature and findings from this study, will use information from the case study in an attempt to optimize its academic performance. The equation will attempt to minimize construction and operational costs while maximizing student performance metrics. The optimization equation will be run through NEOS server’s Nonlinearly Constrained Optimization, Knitro. The purpose of this study is to inform those decision-makers involved in the construction of schools, and who may be interested in obtaining LEED certification for the school, to what extent the LEED schools benefit the school’s student academic achievement levels. Accounting for soft benefits (e.g. productivity, morale, general wellbeing) in a cost-benefit analysis invites an element of risk due to the difficulties in soliciting, obtaining, and accurately measuring these performance metrics. When considering fields involving knowledge work, accurately measuring productivity is an inexact science that normally requires building occupants to perform self-examinations. The results from these examinations are reliant on the occupant’s perceptions and could be open to bias. This study avoids self-assessments through its use of standardized testing as a measure for productivity. The proposed outcome of this paper is that the impacts of LEED schools on their occupants’ academic achievement, health, and wellbeing will be better understood and easier to quantify. The authors hypothesize that LEED schools will outperform conventional schools, which can be attributed to improved IEQ due to tighter building envelopes, increased ventilation rates, better filtration, a reduction in building or cleaning products containing volatile organic compounds, etc. An absence of this data could point to the inability of LEED schools to directly impact their students in a meaningful way, particularly its Indoor Environmental Quality credits, which means that LEED could have to rethink its standards if it wishes to truly improve the productivity and wellbeing of its occupants. / A Dissertation submitted to the Department of Civil and Environmental Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2018. / May 29, 2018. / Indoor Environmental Quality, LEED, Machine Learning, Optimization, Sustainable Design / Includes bibliographical references. / Walter Boot, University Representative; John O. Sobanjo, Committee Member; Lisa Spainhour, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_647218 |
| Contributors | Doczy, Ryan Daniel (author), Boot, Walter Richard (university representative), Sobanjo, John Olusegun, 1958- (committee member), Spainhour, Lisa (committee member), Florida State University (degree granting institution), College of Engineering (degree granting college), Department of Civil and Environmental Engineering (degree granting departmentdgg) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text, doctoral thesis |
| Format | 1 online resource (319 pages), computer, application/pdf |
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