Public perception of carbon capture and storage in relation to hydraulic fracturing: content analyses, survey results, and policy proposals

Carbon capture and storage (CCS) can contribute significantly to addressing the global greenhouse gas (GHG) emissions problem. Despite widespread political support, CCS remains unknown to the general public. Public perception researchers have found that, when asked, the public is relatively unfamiliar with CCS yet many individuals voice specific safety concerns regarding the technology. We believe this leads many stakeholders conflate CCS with the better-known and more visible technology hydraulic fracturing (fracking). We support this with content analysis of media coverage, web analytics, and public lobbying records. Furthermore, we present results from a survey of United States residents. This first-of-its-kind survey assessed participants’ knowledge, opinions and support of CCS and fracking technologies. The survey showed that participants had more knowledge of fracking than CCS, and that knowledge of fracking made participants less willing to support CCS projects. Additionally, it showed that participants viewed the two technologies as having similar risks and similar risk intensities. In the CCS stakeholder literature, judgment and decision-making (JDM) frameworks are noticeably absent, and public perception is not discussed using any cognitive biases as a way of understanding or explaining irrational decisions, yet these survey results show evidence of both anchoring bias and the ambiguity effect. Public acceptance of CCS is essential for a national low-carbon future plan. In conclusion, we propose changes in communications and incentives as programs to increase support of CCS.

Temporal analysis of land use and transportation investments with geographic information system

Land use and transportation interaction has been a research topic for several decades. There have been efforts to identify impacts of transportation on land use from several different perspectives. One focus has been the role of transportation improvements in encouraging new land developments or relocation of activities due to improved accessibility. The impacts studied have included property values and increased development. Another focus has been on the changes in travel behavior due to better mobility and accessibility. Most studies to date have been conducted in metropolitan level, thus unable to account for interactions spatially and temporally at smaller geographic scales. ^ In this study, a framework for studying the temporal interactions between transportation and land use was proposed and applied to three selected corridor areas in Miami-Dade County, Florida. The framework consists of two parts: one is developing of temporal data and the other is applying time series analysis to this temporal data to identify their dynamic interactions. Temporal GIS databases were constructed and used to compile building permit data and transportation improvement projects. Two types of time series analysis approaches were utilized: univariate models and multivariate models. Time series analysis is designed to describe the dynamic consequences of time series by developing models and forecasting the future of the system based on historical trends. Model estimation results from the selected corridors were then compared. ^ It was found that the time series models predicted residential development better than commercial development. It was also found that results from three study corridors varied in terms of the magnitude of impacts, length of lags, significance of the variables, and the model structure. Long-run effect or cumulated impact of transportation improvement on land developments was also measured with time series techniques. The study offered evidence that congestion negatively impacted development and transportation investments encouraged land development. ^

Impact of Water Supply and Sanitation on Diarrheal Morbidity among Young Children in the Socioeconomic and Cultural Context of Rwanda (Africa)

This project studied the frequency and of water contamination at the source, during transportation, and at home to determine the causes of contamination and its impact on the health of children aged 0 to 5 years. The methods used were construction of the infrastructure for three sources of potable water, administration of a questionnaire about socioeconomic status and sanitation behavior, anthropometric measurement of children, and analysis of water and feces. The contamination, first thought to be only a function of rainfall, turned out to be a very complex phenomenon. Water in homes was contaminated (43.4%) with more than 1100 total coliforms/100 ml due to the use of unclean utensils to transport and store water. This socio-economic and cultural problem should be ad- dressed with health education about sanitation, The latrines (found in 43.8% of families) presented a double-edged problem. The extremely high population density reduced the surface area of land per family, which resulted in a severe nutritional deficit (15% of the children) affecting mainly young children, rendering them more susceptible to diarrhea (three episodes/child/year).

Data partitioning and replication management in distributed geographic information system (GIS) database

This research presents several components encompassing the scope of the objective of Data Partitioning and Replication Management in Distributed GIS Database. Modern Geographic Information Systems (GIS) databases are often large and complicated. Therefore data partitioning and replication management problems need to be addresses in development of an efficient and scalable solution. ^ Part of the research is to study the patterns of geographical raster data processing and to propose the algorithms to improve availability of such data. These algorithms and approaches are targeting granularity of geographic data objects as well as data partitioning in geographic databases to achieve high data availability and Quality of Service(QoS) considering distributed data delivery and processing. To achieve this goal a dynamic, real-time approach for mosaicking digital images of different temporal and spatial characteristics into tiles is proposed. This dynamic approach reuses digital images upon demand and generates mosaicked tiles only for the required region according to user's requirements such as resolution, temporal range, and target bands to reduce redundancy in storage and to utilize available computing and storage resources more efficiently. ^ Another part of the research pursued methods for efficient acquiring of GIS data from external heterogeneous databases and Web services as well as end-user GIS data delivery enhancements, automation and 3D virtual reality presentation. ^ There are vast numbers of computing, network, and storage resources idling or not fully utilized available on the Internet. Proposed "Crawling Distributed Operating System "(CDOS) approach employs such resources and creates benefits for the hosts that lend their CPU, network, and storage resources to be used in GIS database context. ^ The results of this dissertation demonstrate effective ways to develop a highly scalable GIS database. The approach developed in this dissertation has resulted in creation of TerraFly GIS database that is used by US government, researchers, and general public to facilitate Web access to remotely-sensed imagery and GIS vector information. ^

The analytical determination of the uniqueness and persistence of the volatile components of human scent using optimized collection methods

The Locard exchange principle proposes that a person can not enter or leave an area or come in contact with an object, without an exchange of materials. In the case of scent evidence, the suspect leaves his scent in the location of the crime scene itself or on objects found therein. Human scent evidence collected from a crime scene can be evaluated through the use of specially trained canines to determine an association between the evidence and a suspect. To date, there has been limited research as to the volatile organic compounds (VOCs) which comprise human odor and their usefulness in distinguishing among individuals. For the purposes of this research, human scent is defined as the most abundant volatile organic compounds present in the headspace above collected odor samples. ^ An instrumental method has been created for the analysis of the VOCs present in human scent, and has been utilized for the optimization of materials used for the collection and storage of human scent evidence. This research project has identified the volatile organic compounds present in the headspace above collected scent samples from different individuals and various regions of the body, with the primary focus involving the armpit area and the palms of the hands. Human scent from the armpit area and palms of an individual sampled over time shows lower variation in the relative peak area ratio of the common compounds present than what is seen across a population. A comparison of the compounds present in human odor for an individual over time, and across a population has been conducted and demonstrates that it is possible to instrumentally differentiate individuals based on the volatile organic compounds above collected odor samples. ^

Variables affecting the collection and preservation of human scent components through instrumental and biological evaluations

In certain European countries and the United States of America, canines have been successfully used in human scent identification. There is however, limited scientific knowledge on the composition of human scent and the detection mechanism that produces an alert from canines. This lack of information has resulted in successful legal challenges to human scent evidence in the courts of law. ^ The main objective of this research was to utilize science to validate the current practices of using human scent evidence in criminal cases. The goals of this study were to utilize Headspace Solid Phase Micro Extraction Gas Chromatography Mass Spectrometry (HS-SPME-GC/MS) to determine the optimum collection and storage conditions for human scent samples, to investigate whether the amount of DNA deposited upon contact with an object affects the alerts produced by human scent identification canines, and to create a prototype pseudo human scent which could be used for training purposes. ^ Hand odor samples which were collected on different sorbent materials and exposed to various environmental conditions showed that human scent samples should be stored without prolonged exposure to UVA/UVB light to allow minimal changes to the overall scent profile. Various methods of collecting human scent from objects were also investigated and it was determined that passive collection methods yields ten times more VOCs by mass than active collection methods. ^ Through the use of polymerase chain reaction (PCR) no correlation was found between the amount of DNA that was deposited upon contact with an object and the alerts that were produced by human scent identification canines. Preliminary studies conducted to create a prototype pseudo human scent showed that it is possible to produce fractions of a human scent sample which can be presented to the canines to determine whether specific fractions or the entire sample is needed to produce alerts by the human scent identification canines. ^

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Lattice Boltzmann modeling of fluid flow and solute transport in karst aquifers

A novel modeling approach is applied to karst hydrology. Long-standing problems in karst hydrology and solute transport are addressed using Lattice Boltzmann methods (LBMs). These methods contrast with other modeling approaches that have been applied to karst hydrology. The motivation of this dissertation is to develop new computational models for solving ground water hydraulics and transport problems in karst aquifers, which are widespread around the globe. This research tests the viability of the LBM as a robust alternative numerical technique for solving large-scale hydrological problems. The LB models applied in this research are briefly reviewed and there is a discussion of implementation issues. The dissertation focuses on testing the LB models. The LBM is tested for two different types of inlet boundary conditions for solute transport in finite and effectively semi-infinite domains. The LBM solutions are verified against analytical solutions. Zero-diffusion transport and Taylor dispersion in slits are also simulated and compared against analytical solutions. These results demonstrate the LBM’s flexibility as a solute transport solver. The LBM is applied to simulate solute transport and fluid flow in porous media traversed by larger conduits. A LBM-based macroscopic flow solver (Darcy’s law-based) is linked with an anisotropic dispersion solver. Spatial breakthrough curves in one and two dimensions are fitted against the available analytical solutions. This provides a steady flow model with capabilities routinely found in ground water flow and transport models (e.g., the combination of MODFLOW and MT3D). However the new LBM-based model retains the ability to solve inertial flows that are characteristic of karst aquifer conduits. Transient flows in a confined aquifer are solved using two different LBM approaches. The analogy between Fick’s second law (diffusion equation) and the transient ground water flow equation is used to solve the transient head distribution. An altered-velocity flow solver with source/sink term is applied to simulate a drawdown curve. Hydraulic parameters like transmissivity and storage coefficient are linked with LB parameters. These capabilities complete the LBM’s effective treatment of the types of processes that are simulated by standard ground water models. The LB model is verified against field data for drawdown in a confined aquifer.

Exploring the Relationship Between Hotel Characteristics and Crime

Knowledge of crimes that have occurred in hotels has been scares. The authors explore the nature and causes of hotel crimes in a U.S. metropolitan area. Levels of crimes were directly related to size of the hotel, target market of business travelers, access to public transportation, and an unsafe image of the environment surrounding the hotel. Crime prevention programs based on the findings can be developed to protect the safety of guests and property.

Lattice Boltzmann Modeling of Fluid Flow and Solute Transport in Karst Aquifers

A novel modeling approach is applied to karst hydrology. Long-standing problems in karst hydrology and solute transport are addressed using Lattice Boltzmann methods (LBMs). These methods contrast with other modeling approaches that have been applied to karst hydrology. The motivation of this dissertation is to develop new computational models for solving ground water hydraulics and transport problems in karst aquifers, which are widespread around the globe. This research tests the viability of the LBM as a robust alternative numerical technique for solving large-scale hydrological problems. The LB models applied in this research are briefly reviewed and there is a discussion of implementation issues. The dissertation focuses on testing the LB models. The LBM is tested for two different types of inlet boundary conditions for solute transport in finite and effectively semi-infinite domains. The LBM solutions are verified against analytical solutions. Zero-diffusion transport and Taylor dispersion in slits are also simulated and compared against analytical solutions. These results demonstrate the LBM’s flexibility as a solute transport solver. The LBM is applied to simulate solute transport and fluid flow in porous media traversed by larger conduits. A LBM-based macroscopic flow solver (Darcy’s law-based) is linked with an anisotropic dispersion solver. Spatial breakthrough curves in one and two dimensions are fitted against the available analytical solutions. This provides a steady flow model with capabilities routinely found in ground water flow and transport models (e.g., the combination of MODFLOW and MT3D). However the new LBM-based model retains the ability to solve inertial flows that are characteristic of karst aquifer conduits. Transient flows in a confined aquifer are solved using two different LBM approaches. The analogy between Fick’s second law (diffusion equation) and the transient ground water flow equation is used to solve the transient head distribution. An altered-velocity flow solver with source/sink term is applied to simulate a drawdown curve. Hydraulic parameters like transmissivity and storage coefficient are linked with LB parameters. These capabilities complete the LBM’s effective treatment of the types of processes that are simulated by standard ground water models. The LB model is verified against field data for drawdown in a confined aquifer.

Effective energy conservation and management in the building sector : the answer to the energy predicament

Modern civilization has developed principally through man's harnessing of forces. For centuries man had to rely on wind, water and animal force as principal sources of power. The advent of the industrial revolution, electrification and the development of new technologies led to the application of wood, coal, gas, petroleum, and uranium to fuel new industries, produce goods and means of transportation, and generate the electrical energy which has become such an integral part of our lives. The geometric growth in energy consumption, coupled with the world's unrestricted growth in population, has caused a disproportionate use of these limited natural resources. The resulting energy predicament could have serious consequences within the next half century unless we commit ourselves to the philosophy of effective energy conservation and management. National legislation, along with the initiative of private industry and growing interest in the private sector has played a major role in stimulating the adoption of energy-conserving laws, technologies, measures, and practices. It is a matter of serious concern in the United States, where ninety-five percent of the commercial and industrial facilities which will be standing in the year 2000 - many in need of retrofit - are currently in place. To conserve energy, it is crucial to first understand how a facility consumes energy, how its users' needs are met, and how all internal and external elements interrelate. To this purpose, the major thrust of this report will be to emphasize the need to develop an energy conservation plan that incorporates energy auditing and surveying techniques. Numerous energy-saving measures and practices will be presented ranging from simple no-cost opportunities to capital intensive investments.

Mitigating Inconsistencies by Coupling Data Cleaning, Filtering, and Contextual Data Validation in Wireless Sensor Networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Variables Affecting the Collection and Preservation of Human Scent Components through Instrumental and Biological Evaluations

In certain European countries and the United States of America, canines have been successfully used in human scent identification. There is however, limited scientific knowledge on the composition of human scent and the detection mechanism that produces an alert from canines. This lack of information has resulted in successful legal challenges to human scent evidence in the courts of law. The main objective of this research was to utilize science to validate the current practices of using human scent evidence in criminal cases. The goals of this study were to utilize Headspace Solid Phase Micro Extraction Gas Chromatography Mass Spectrometry (HS-SPME-GC/MS) to determine the optimum collection and storage conditions for human scent samples, to investigate whether the amount of DNA deposited upon contact with an object affects the alerts produced by human scent identification canines, and to create a prototype pseudo human scent which could be used for training purposes. Hand odor samples which were collected on different sorbent materials and exposed to various environmental conditions showed that human scent samples should be stored without prolonged exposure to UVA/UVB light to allow minimal changes to the overall scent profile. Various methods of collecting human scent from objects were also investigated and it was determined that passive collection methods yields ten times more VOCs by mass than active collection methods. Through the use of polymerase chain reaction (PCR) no correlation was found between the amount of DNA that was deposited upon contact with an object and the alerts that were produced by human scent identification canines. Preliminary studies conducted to create a prototype pseudo human scent showed that it is possible to produce fractions of a human scent sample which can be presented to the canines to determine whether specific fractions or the entire sample is needed to produce alerts by the human scent identification canines.