Reducing vehicle-miles traveled: an argument for land use as a policy lever

(Georgia Institute of Technology, 2012-11-15) Sundquist, Eric William

Reducing vehicle-miles traveled (VMT) has become an important goal for improving environmental outcomes and reducing the costs of travel and infrastructure. One way to accomplish such reductions could be to enact policies that foster more compact development. However, while it is accepted that compact development is associated with lower VMT, there remain disagreements about the efficacy of this policy lever. One issue casting doubt on the power of compact development relates to travelers' exposure to density. A conventional view holds that many travelers' neighborhoods are "locked in place" because change in established neighborhoods is slow. Additionally, conventional explanations of the effect of denser development focus on travelers' own neighborhoods, or on the metro area as a whole, failing to isolate the effect of densifying nodes near, but outside of, the travelers' neighborhoods. This study employs housing and travel data from the Seattle-Tacoma, Wash., where policies aimed at encouraging compact development have been in place since the mid-1990s. Findings suggest that 1) in established neighborhood, incremental change often results in exposure to substantially higher density, and 2) that even where localized density is constant, increases in density at intentional nodes or other areas near, but outside of, a traveler's own neighborhood, has a strong effect on VMT. The findings tend to undermine some of the key doubts about using land use as a policy lever for VMT reduction.
Economic and environmental input-output modeling: building material recycling

(Georgia Institute of Technology, 2012-11-14) Choi, Taelim

A key dimension to improving urban economic and environmental sustainability is the efficient use of resources through recycling. A thriving recycling system requires not only effective institutional policies and community-wide diversion efforts, but also a competent local and regional recycling industry. Although the recycling industry has traditionally been recognized as a local service and fringe industry, it has noticeably transformed into an integral segment of industrial production systems as manufacturers have increasingly begun to adopt the principle of extended producer responsibility. Despite such changes, urban and regional theory and planning research has largely disregarded the industrial aspect of recycling, contributing to the dearth of information about the organizational and spatial patterns of the recycling industry and the impact of the establishment of recycling systems on local and regional scales. Given the knowledge gap, this dissertation addresses two questions: 1) What is the logic of the industry organization and spatial pattern of recycling industry in different institutional contexts? and 2) How is the economic and environmental impact of recycling systems determined in cases of construction and demolition waste recycling and waste carpet recycling? To answer the first question, this research develops a theoretical model that explains how recycling industrial activities are spatially distributed in light of institutional and organizational theories. The theoretical model characterizes organizational decisions pertaining to recycling functions and suggests spatial patterns of recycling systems. With respect to the second question, this research constructs a regional environmental input-output model on the metropolitan scale. It estimates regionalized energy use coefficients and greenhouse gas emission coefficients using various sources of data mainly compiled from the Manufacturing Energy Consumption Survey 2006, the State Energy Consumption Estimates, and the Commodity Flow Survey 2007. Based on regional input-output tables coupled with the regionalized environmental coefficients, this research quantifies, through simulations, the net economic and environmental impact of a localized construction and demolition waste recycling system in the San Francisco metropolitan area and regional carpet recycling systems in the Atlanta and Seattle metropolitan areas. Results of the simulations reveal that 1) the localized construction and demolition waste recycling system provides moderate economic benefits because of the limited job creation potential of mechanized recycling processes and yields relatively small environmental benefits with respect to the total weight processed; 2) wider adoption of the deconstruction technique expands job opportunities, increases energy savings, and reduces greenhouse gas emissions during the course of construction and demolition waste recycling; 3) regional-scale waste carpet recycling systems, in particular recycled nylon 6 production, create sizable new job opportunities and provides environmental benefits of energy savings and greenhouse gas emission reduction despite the long-distance transportation of waste carpet. These results suggest that policies that promote recycling industrial activities can significantly contribute to the economic and environmental sustainability of metropolitan areas.
Planning for the new urban climate: interactions of local environmental planning and regional extreme heat

(Georgia Institute of Technology, 2012-11-12) Vargo, Jason Adam

The Earth's climate is changing and cities are facing a warmer future. As the locus of economic activity and concentrated populations on the planet, cities are both a primary driver of greenhouse gas emissions and places where the human health impacts of climate change are directly felt. Cities increase local temperatures through the conversion of natural land covers to urban uses, and exposures to elevated temperatures represent a serious and growing health threat for urban residents. This work is concerned with understanding the interactions of global trends in climate with local influences tied to urban land covers. First, it examines temperatures during an extended period of extreme heat and asks whether changes in land surface temperatures during a heat wave are consistent in space and time across all land cover types. Second, the influences of land covers on temperatures are considered for normal and extreme summer weather to find out which characteristics of the built environment most influence temperatures during periods of extreme heat. Finally, the distribution of health vulnerabilities related to extreme heat in cities are described and examined for spatial patterns. These topics are investigated using meteorology from the summer of 2006 to identify extremely hot days in the cities of Atlanta, Chicago, Philadelphia, and Phoenix and their surrounding metropolitan regions. Remotely sensed temperature data were examined with physical and social characteristics of the urban environment to answer the questions posed above. The findings confirm that urban land covers consistently exhibit higher temperatures than surrounding rural areas and are much more likely to be among the hottest in the region, during a heat wave specifically. In some cities urban thermal anomalies grew between the beginning and end of a heat wave. The importance of previously recognized built environment thermal influences (impervious cover and tree canopy) were present, and in some cases, emphasized during extreme summer weather. Extreme heat health health vulnerability related to environmental factors coincided spatially with risks related to social status. This finding suggests that populations with fewer resources for coping with extreme heat tend to reside in built environments that increase temperatures, and thus they may be experiencing increased thermal exposures. Physical interventions and policies related to the built environment can help to reduce urban temperatures, especially during periods of extremely hot weather which are predicted to become more frequent with global climate change. In portions of the city where populations with limited adaptive capacity are concentrated, modification of the urban landscape to decrease near surface longwave radiation can reduce the chances of adverse health effects related to extreme heat. The specific programs, policies, and design strategies pursued by cities and regions must be tailored with respect to scale, location, and cultural context. This work concludes with suggestions for such strategies.
The impact of natural disasters on neighborhood change:longitudinal data analysis

(Georgia Institute of Technology, 2012-09-18) Lee, Dalbyul

This dissertation seeks to explore the association between natural disasters and neighborhood change and further to examine the differential impact of natural disasters on neighborhood change according to the disaster itself, the rehabilitation efforts of local jurisdictions, and the characteristics of the affected neighborhoods. Using the longitudinal model, it examines the shifts in neighborhood change trajectory before and after natural disaster for three indicators (home values, poverty rate and racial diversity). The results find that natural disasters have a significant impact on the trend of neighborhood change, reducing variation in the indicators within neighborhood. Home values and racial diversity of neighborhoods are likely to immediately decrease after natural disasters but not to shift in subsequent rate of change,while poverty rates are likely to instantly increase in the aftermath of the disasters and to annually decline over time. This dissertation also explores the differential effects on neighborhood change according to intensity of natural disaster, neighborhoods? average income and the location. The results of the analyses are like the following: 1) the neighborhoods which the more intense disasters hit are more likely to experience the rapid decline in home values and an instant increase in their poverty rates than those which the less intense disaster hit. On the other hand, the more intense natural disasters are more likely to increase neighborhoods? racial diversity than the less intense natural disasters, while natural disasters themselves are likely to decrease it. 2) natural disasters might have the more adverse impacts on low- and high-income neighborhoods than moderate-income neighborhoods and that the impacts on low-income neighborhoods are most severe. More importantly, the adverse impacts in low-income neighborhoods might be long lasting. 3)neighborhoods in suburban areas, compared to neighborhoods in the central cities, are likely to decrease in their home values after natural disasters and to increase in their poverty rates. Finally, the findings of this dissertation confirms its main arguments that a natural disaster affects the trend of neighborhood change and intervenes in the path of change over time and that natural disasters differentially shift neighborhoods according to their characteristics. Further it suggests that these neighborhood changes, once accelerated by a natural disaster, further polarize residential populations on a metropolitan neighborhood scale.
Integrated performance framework to guide facade retrofit

(Georgia Institute of Technology, 2012-08-27) Sanguinetti, Paola

The façade retrofit market faces some key barriers: the selection of performance criteria and the reliability of the performance data. On the demand side, the problem is approached from an investment perspective which creates "split incentives" between the stakeholders who pay for the investment and those who benefit from it. On the supply side, there is an inherent complexity in modeling these options because of the incomplete knowledge of the physical and cost parameters involved in the performance evaluation. The thermal comfort of the building occupant is an important component of the retrofit performance assessment. This research attempts to fill a gap in the approach to façade retrofit decision by 1) quantifying uncertainties in these three dimensions of performance, 2) incorporating new financing models available in the retrofit market, 3) considering the target and risk attitude of the decision maker. The methodology proposed in this research integrates key indicators for delivery process, environmental performance, and investment performance. The purpose is to provide a methodological framework for performance evaluation. A residential case study is conducted to test the proposed framework. Three retrofit scenarios including the financing structure are examined. Each façade retrofit scenario is then evaluated based on the level of confidence to meet or exceed a specific target improvement for the Net Present Value and the risk to fall below a minimum improvement threshold. The case study results confirm that risk must be considered for more reliable façade retrofit decision-making. Research findings point to further research needed to expand the understanding of the interdependencies among uncertain parameters.
Making “invisible architecture” visible: a comparative study of nursing unit typologies in the United States and China

(Georgia Institute of Technology, 2012-08-14) Cai, Hui

China is engaged in the largest healthcare construction program in history, expecting to build more than 2,000 hospitals and a large number of healthcare facilities at all scale over the next few years. This once-in-a-lifetime construction boom provides a valuable opportunity to rethink Chinese hospital design, and especially to consider how to design modern hospitals that are effective and efficient in delivering care, and are responsive to the cultural needs of the Chinese people as well. This dissertation seeks to rigorously define these issues and develop metrics that link design to key healthcare processes. This study uses a range of concepts and analysis tools drawn from cross-culture organizational communications, evidence-based design, space syntax and other research traditions. This thesis develops and refines metrics for four main drivers of nursing unit design: space economy, staff efficiency, natural light and cultural preferences for communication. Communication among Chinese healthcare workers is strongly influenced by cultural preferences for patterns of authority and decision-making reflected in organizational culture and rooted in Confucian principles of hierarchical social structure (Dengji), social network (Guanxi) and face (Mianzi). While the dissertation builds on a longstanding tradition of research focusing on healthcare space economy and staff efficiency, new measures for cultural preferences are proposed and tested. Based on emerging theories of cross-cultural organizational communication by Hofstede and other scholars, and space syntax, this study particularly explores how cultural preferences for face-to-face communication are reflected in the design of Chinese nursing units. Based on the proposed metrics, the dissertation analyzes six pairs of Chinese and US nursing units, matched on layout type. While the Chinese nursing units appear Western, deeper quantitative analysis of their layouts reveals significant national differences in the application of unit typologies in China when compared to those in the U.S. It shows that Chinese hospital design is rooted in cultural preferences such as for positive energy (qi) based on Fengshui theory, and in Confucian principles of hierarchy, social networking and face.
A model based framework for semantic interpretation of architectural construction drawings

(Georgia Institute of Technology, 2012-04-24) Babalola, Olubi Oluyomi

The study addresses the automated translation of architectural drawings from 2D Computer Aided Drafting (CAD) data into a Building Information Model (BIM), with emphasis on the nature, possible role, and limitations of a drafting language Knowledge Representation (KR) on the problem and process. The central idea is that CAD to BIM translation is a complex diagrammatic interpretation problem requiring a domain (drafting language) KR to render it tractable and that such a KR can take the form of an information model. Formal notions of drawing-as-language have been advanced and studied quite extensively for close to 25 years. The analogy implicitly encourages comparison between problem structures in both domains, revealing important similarities and offering guidance from the more mature field of Natural Language Understanding (NLU). The primary insight we derive from NLU involves the central role that a formal language description plays in guiding the process of interpretation (inferential reasoning), and the notable absence of a comparable specification for architectural drafting. We adopt a modified version of Engelhard's approach which expresses drawing structure in terms of a symbol set, a set of relationships, and a set of compositional frameworks in which they are composed. We further define an approach for establishing the features of this KR, drawing upon related work on conceptual frameworks for diagrammatic reasoning systems. We augment this with observation of human subjects performing a number of drafting interpretation exercises and derive some understanding of its inferential nature therefrom. We consider this indicative of the potential range of inferential processes a computational drafting model should ideally support. The KR is implemented as an information model using the EXPRESS language because it is in the public domain and is the implementation language of the target Industry Foundation Classes (IFC) model. We draw extensively from the IFC library to demonstrate that it can be applied in this manner, and apply the MVD methodology in defining the scope and interface of the DOM and IFC. This simplifies the IFC translation process significantly and minimizes the need for mapping. We conclude on the basis of selective implementations that a model reflecting the principles and features we define can indeed provide needed and otherwise unavailable support in drafting interpretation and other problems involving reasoning with this class of diagrammatic representations.
Agent-based modeling of commercial building stocks for energy policy and demand response analysis

(Georgia Institute of Technology, 2012-04-04) Zhao, Fei

Managing a sustainable built environment with a large number of buildings rests on the ability to assess and improve the performance of the building stock over time. Building stock models are cornerstones to the assessment of the combined impact of energy-related building interventions across different spatial and temporal scales. However, such models, particularly those accounting for both physical formulation and social behaviors of the underlying buildings, are still in their infancy. This research strives to more thoroughly examine how buildings perform aggregately in energy usage by focusing on how to tackled three major technical challenges: (1) quantifying building energy performance in an objective and scalable manner, (2) mapping building stock model space to real-world data space, and (3) quantifying and evaluating energy intervention behaviors of a building stock. This thesis hypothesizes that a new paradigm of aggregation of large-scale building stocks can lead to (1) an accurate and efficient intervention analysis model and (2) a functionally comprehensive decision support tool for building stock energy intervention analysis. Specifically, this thesis presents three methodologies. To address the first challenge, this thesis develops a normative building physical energy model that can rapidly estimate single building energy performance with respect to its design and operational characteristics. To address the second challenge, the thesis proposes a statistical procedure using regression and Markov chain Monte Carlo (MCMC) sampling techniques that inverse-estimate building parameters based on building stock energy consumption survey data. The outcomes of this statistical procedure validate the approach of using prototypical buildings for two types of intervention analysis: energy retrofit and demand response. These two cases are implemented in an agent-based modeling and simulation (ABMS) framework to tackle the third challenge. This thesis research contributes to the body of knowledge pertaining to building energy modeling beyond the single building scale. The proposed framework can be used by energy policy makers and utilities for the evaluation of energy retrofit incentives and demand-response program economics.
Effects of sub-optimal component performance on overall cooling system energy consumption and efficiency

(Georgia Institute of Technology, 2012-04-04) Khazaii, Javad

Predicted cooling system performance plays an important role in choices among alternative system selections and designs. When system performance is expressed in proper indicators such as "overall system energy consumption" or "overall system efficiency", it can provide the decision makers with a quantitative measure of the extent to which a cooling system satisfies the system design requirements and objectives. Predictions of cooling system energy consumption and efficiency imply assumptions about component performance. Quantitative appraisal of the uncertainty (lack of knowledge) in these assumptions can be used by design practitioners to select and design systems, by energy contractors to guarantee future system energy cost savings, and codes and standards officials to set proper goals to conserve energy. Our lack of knowledge has different sources, notably unknown tolerances in equipment nameplate data, and unpredictable load profiles. Both cause systems to under-perform current predictions, and as a result decrease the accuracy of the outcomes of energy simulations that commonly are used to verify system performance during the design and construction stages. There can be many other causes of unpredictable system behavior, for example due to bad workmanship in the installation, occurrence of faults in the operation of certain system parts, deterioration over time and other. These uncertainties are typically much harder to quantify and their propagation into the calculated energy consumption is much harder to accomplish. In this thesis, these categories of failures are not considered, i.e. the treatment is limited to component tolerances and load variability. In this research the effects of equipment nameplate tolerances and cooling load profile variability on the overall energy consumption and efficiency of commonly used commercial cooling systems are quantified. The main target of this thesis is to present a methodology for calculating the chances that a specific cooling system could deviate from a certain efficiency level by a certain margin, and use these results to guide practitioners and energy performance contractors to select, and guarantee system performances more realistically. By doing that, the plan is to establish a systematic approach of developing expressions of risk, in commercial cooling system consumption and efficiency calculations, and thus to advocate the use of expressions of risk as design targets. This thesis makes a contribution to improving our fundamental understanding of performance risk in selecting and sizing certain HVAC design concepts.
A real options model for the financial valuation of infrastructure systems under uncertainty

(Georgia Institute of Technology, 2012-04-03) Haj Kazem Kashani, Hamed

Build-Operate-Transfer (BOT) is a form of Public-Private Partnerships that is commonly used to close the growing gap between the cost of developing and modernizing transportation infrastructure systems and the financial resources available to governments. When assessing the feasibility of a BOT project, private investors consider revenue risk - which is stemmed from the uncertainty about future traffic demand - as a critical factor. A potential approach to mitigating the revenue risk is the offering of revenue risk sharing mechanisms such as Minimum Revenue Guarantee options by the government. In addition to Minimum Revenue Guarantee options, a mechanism known as Traffic Revenue Cap options may also be negotiated, which makes the government entitled to a share of revenue when it grows beyond a specified threshold. Financial valuation of investments in BOT projects should take into account uncertainty about future traffic demand, as well as Minimum Revenue Guarantee and Traffic Revenue Cap options. The conventional valuation methods including Net Present Value (NPV) analysis are not capable of integrating the uncertainty about future traffic demand in the valuation of BOT projects and properly pricing Minimum Revenue Guarantee and Traffic Revenue Cap options. Real options analysis can be used as an alternative approach to valuation of investments in transportation projects under uncertainties. However, the appropriate application of real options analysis to valuation of investments in transportation projects is conditioned upon overcoming specific theoretical challenges. Current real options models do not provide a systematic method for estimating the project volatility, which measures the variability of investment value. Existing models do not provide a method for calculating the market value of Minimum Revenue Guarantee and Traffic Revenue Cap options. Also, current models are not able to characterize the impact of Minimum Revenue Guarantee and Traffic Revenue Cap options on private investors' financial risk profile. The overarching objective of this research is to apply the real options theory in order to price Minimum Revenue Guarantee and Traffic Revenue Cap options under the uncertainty about future traffic demand. To achieve this objective, a real options model is created that characterizes the long-term traffic demand uncertainty in BOT projects and determines investors' financial risk profile under uncertainty about future traffic demand. This model presents a novel method for estimating the project volatility for real options analysis. This model devises a market-based option pricing approach to determine the correct value of Minimum Revenue Guarantee and Traffic Revenue Cap options. An appropriate procedure is created for characterizing the impact of Minimum Revenue Guarantee and Traffic Revenue Cap options on the investors' financial risk profile. The proposed real options model is applied to a BOT project to illustrate the valuation process. The limitations of the proposed real options model, as well as the barriers to its implementation, are identified and recommendations for future research are offered. This research contributes to the state of knowledge by presenting a new method for estimating the project volatility, which is required for the real options analysis of transportation investments. It also introduces a risk-neutral valuation method for pricing the market value of Minimum Revenue Guarantee and Traffic Revenue Cap options in BOT projects. The research also contributes to the state of practice by introducing a novel class of assessment tools for decision makers that characterize the investors' financial risk profile under uncertainty about future traffic demand. Proper methods for pricing of Minimum Revenue Guarantee and Traffic Revenue Cap options are useful to public and private investors, in order to avoid wasting capital in transportation projects.