Development of an odor management plan for industrial stationary sources in an urban environment: A case study for Broward County, Florida

Objectionable odors remain at the top of air pollution complaints in urban areas such as Broward County that is subject to increasing residential and industrial developments. The odor complaints in Broward County escalated by 150 percent for the 2001 to 2004 period although the population increased by only 6 percent. It is estimated that in 2010 the population will increase to 2.5 million. Relying solely on enforcing the local odor ordinance is evidently not sufficient to manage the escalating odor complaint trends. An alternate approach similar to odor management plans (OMPs) that are successful in managing major malodor sources such as animal farms is required. ^ This study aims to develop and determine the feasibility of implementing a comprehensive odor management plan (COMP) for the entire Broward County. Unlike existing OMPs for single sources where the receptors (i.e. the complainants) are located beyond the boundary of the source, the COMP addresses a complex model of multiple sources and receptors coexisting within the boundary of the entire county. Each receptor is potentially subjected to malodor emissions from multiple sources within the county. Also, the quantity and quality of the source/receptor variables are continuously changing. ^ The results of this study show that it is feasible to develop a COMP that adopts a systematic procedure to: (1) Generate maps of existing odor complaint areas and malodor sources, (2) Identify potential odor sources (target sources) responsible for existing odor complaints, (3) Identify possible odor control strategies for target sources, (4) Determine the criteria for implementing odor control strategies, (5) Develop an odor complaint response protocol, and (6) Conduct odor impact analyses for new sources to prevent future odor related issues. Geographic Information System (GIS) is used to identify existing complaint areas. A COMP software that incorporates existing United States Environmental Protection Agency (EPA) air dispersion software is developed to determine the target sources, predict the likelihood of new complaints, and conduct odor impact analysis. The odor response protocol requires pre-planning field investigations and conducting surveys to optimize the local agency available resources while protecting the citizen's welfare, as required by the Clean Air Act. ^

Performance of FRP-concrete bridges under blast loading

Catastrophic failure from intentional terrorist attacks on surface transportation infrastructure could he detrimental to the society. In order to minimize the vulnerabilities and to ensure a safe transportation system, the issue of security for transportation structures, primarily bridges, which are subjected to man-made hazards is investigated in this study. A procedure for identifying and prioritizing "critical bridges" using a screening and prioritization processes is established. For each of the "critical" bridges, a systematic risk-based assessment approach is proposed that takes into account the combination of threat occurrence likelihood, its consequences, and the socioeconomic importance of the bridge. A series of effective security countermeasures are compiled in the four categories of deterrence, detection, defense and mitigation to help reduce the vulnerability of critical bridges. The concepts of simplified equivalent I-shape cross section and virtual materials are proposed for integration into a nonlinear finite element model, which helps assess the performance of reinforced concrete structures with and without composite retrofit or hardening measures under blast loading. A series of parametric studies are conducted for single column and two-column pier frame systems as well as for an entire bridge. The parameters considered include column height, column type, concrete strength, longitudinal steel reinforcement ratio, thickness, fiber angle and tensile strength of the fiber reinforced polymer (FRP) tube, shape of the cross section, damping ratio and different bomb sizes. The study shows the benefits of hardening with composites against blast loading. The effect of steel reinforcement on blast resistance of the structure is more significant than the effect of concrete compressive strength. Moreover, multiple blasts do not necessarily lead to a more severe destruction than a single detonation at a strategically vulnerable location on the bridges.

An exergy based engineering and economic analysis of sustainable building

To achieve the goal of sustainable development, the building energy system was evaluated from both the first and second law of thermodynamics point of view. The relationship between exergy destruction and sustainable development were discussed at first, followed by the description of the resource abundance model, the life cycle analysis model and the economic investment effectiveness model. By combining the forgoing models, a new sustainable index was proposed. Several green building case studies in U.S. and China were presented. The influences of building function, geographic location, climate pattern, the regional energy structure, and the technology improvement potential of renewable energy in the future were discussed. The building’s envelope, HVAC system, on-site renewable energy system life cycle analysis from energy, exergy, environmental and economic perspective were compared. It was found that climate pattern had a dramatic influence on the life cycle investment effectiveness of the building envelope. The building HVAC system energy performance was much better than its exergy performance. To further increase the exergy efficiency, renewable energy rather than fossil fuel should be used as the primary energy. A building life cycle cost and exergy consumption regression model was set up. The optimal building insulation level could be affected by either cost minimization or exergy consumption minimization approach. The exergy approach would cause better insulation than cost approach. The influence of energy price on the system selection strategy was discussed. Two photovoltaics (PV) systems—stand alone and grid tied system were compared by the life cycle assessment method. The superiority of the latter one was quite obvious. The analysis also showed that during its life span PV technology was less attractive economically because the electricity price in U.S. and China did not fully reflect the environmental burden associated with it. However if future energy price surges and PV system cost reductions were considered, the technology could be very promising for sustainable buildings in the future.

The use of computing technology in highway construction contractor companies as a Total Jobsite Management Tool (TJMT)

The integration of automation (specifically Global Positioning Systems (GPS)) and Information and Communications Technology (ICT) through the creation of a Total Jobsite Management Tool (TJMT) in construction contractor companies can revolutionize the way contractors do business. The key to this integration is the collection and processing of real-time GPS data that is produced on the jobsite for use in project management applications. This research study established the need for an effective planning and implementation framework to assist construction contractor companies in navigating the terrain of GPS and ICT use. An Implementation Framework was developed using the Action Research approach. The framework consists of three components, as follows: (i) ICT Infrastructure Model, (ii) Organizational Restructuring Model, and (iii) Cost/Benefit Analysis. The conceptual ICT infrastructure model was developed for the purpose of showing decision makers within highway construction companies how to collect, process, and use GPS data for project management applications. The organizational restructuring model was developed to assist companies in the analysis and redesign of business processes, data flows, core job responsibilities, and their organizational structure in order to obtain the maximum benefit at the least cost in implementing GPS as a TJMT. A cost-benefit analysis which identifies and quantifies the cost and benefits (both direct and indirect) was performed in the study to clearly demonstrate the advantages of using GPS as a TJMT. Finally, the study revealed that in order to successfully implement a program to utilize GPS data as a TJMT, it is important for construction companies to understand the various implementation and transitioning issues that arise when implementing this new technology and business strategy. In the study, Factors for Success were identified and ranked to allow a construction company to understand the factors that may contribute to or detract from the prospect for success during implementation. The Implementation Framework developed as a result of this study will serve to guide highway construction companies in the successful integration of GPS and ICT technologies for use as a TJMT.

Development of risk based treatability and engineering measures for reducing exposure to lead contaminated media in the Miami inner city, Florida

A major consequence of contamination at the local level’s population as it relates to environmental health and environmental engineering is childhood lead poisoning. Environmental contamination is one of the pressing environmental concerns facing the world today. Current approaches often focus on large contaminated industrial size sites that are designated by regulatory agencies for site remediation. Prior to this study, there were no known published studies conducted at the local and smaller scale, such as neighborhoods, where often much of the contamination is present to remediate. An environmental health study of local lead-poisoning data in Liberty City, Little Haiti and eastern Little Havana in Miami-Dade County, Florida accounted for a disproportionately high number of the county’s reported childhood lead poisoning cases. An engineering system was developed and designed for a comprehensive risk management methodology that is distinctively applicable to the geographical and environmental conditions of Miami-Dade County, Florida. Furthermore, a scientific approach for interpreting environmental health concerns, while involving detailed environmental engineering control measures and methods for site remediation in contained media was developed for implementation. Test samples were obtained from residents and sites in those specific communities in Miami-Dade County, Florida (Gasana and Chamorro 2002). Currently lead does not have an Oral Assessment, Inhalation Assessment, and Oral Slope Factor; variables that are required to run a quantitative risk assessment. However, various institutional controls from federal agencies’ standards and regulation for contaminated lead in media yield adequate maximum concentration limits (MCLs). For this study an MCL of .0015 (mg/L) was used. A risk management approach concerning contaminated media involving lead demonstrates that the linkage of environmental health and environmental engineering can yield a feasible solution.

Eulerian-Lagrangian two phase debris flow model

The main objective of this work is to develop a quasi three-dimensional numerical model to simulate stony debris flows, considering a continuum fluid phase, composed by water and fine sediments, and a non-continuum phase including large particles, such as pebbles and boulders. Large particles are treated in a Lagrangian frame of reference using the Discrete Element Method, the fluid phase is based on the Eulerian approach, using the Finite Element Method to solve the depth-averaged Navier-Stokes equations in two horizontal dimensions. The particle’s equations of motion are in three dimensions. The model simulates particle-particle collisions and wall-particle collisions, taking into account that particles are immersed in a fluid. Bingham and Cross rheological models are used for the continuum phase. Both formulations provide very stable results, even in the range of very low shear rates. Bingham formulation is better able to simulate the stopping stage of the fluid when applied shear stresses are low. Results of numerical simulations have been compared with data from laboratory experiments on a flume-fan prototype. Results show that the model is capable of simulating the motion of big particles moving in the fluid flow, handling dense particulate flows and avoiding overlap among particles. An application to simulate debris flow events that occurred in Northern Venezuela in 1999 shows that the model could replicate the main boulder accumulation areas that were surveyed by the USGS. Uniqueness of this research is the integration of mud flow and stony debris movement in a single modeling tool that can be used for planning and management of debris flow prone areas.

A methodological framework for modeling pavement maintenance costs for projects with performance-based contracts

Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

An improved framework for dynamic origin-destination (O-D) matrix estimation

This dissertation aims to improve the performance of existing assignment-based dynamic origin-destination (O-D) matrix estimation models to successfully apply Intelligent Transportation Systems (ITS) strategies for the purposes of traffic congestion relief and dynamic traffic assignment (DTA) in transportation network modeling. The methodology framework has two advantages over the existing assignment-based dynamic O-D matrix estimation models. First, it combines an initial O-D estimation model into the estimation process to provide a high confidence level of initial input for the dynamic O-D estimation model, which has the potential to improve the final estimation results and reduce the associated computation time. Second, the proposed methodology framework can automatically convert traffic volume deviation to traffic density deviation in the objective function under congested traffic conditions. Traffic density is a better indicator for traffic demand than traffic volume under congested traffic condition, thus the conversion can contribute to improving the estimation performance. The proposed method indicates a better performance than a typical assignment-based estimation model (Zhou et al., 2003) in several case studies. In the case study for I-95 in Miami-Dade County, Florida, the proposed method produces a good result in seven iterations, with a root mean square percentage error (RMSPE) of 0.010 for traffic volume and a RMSPE of 0.283 for speed. In contrast, Zhou's model requires 50 iterations to obtain a RMSPE of 0.023 for volume and a RMSPE of 0.285 for speed. In the case study for Jacksonville, Florida, the proposed method reaches a convergent solution in 16 iterations with a RMSPE of 0.045 for volume and a RMSPE of 0.110 for speed, while Zhou's model needs 10 iterations to obtain the best solution, with a RMSPE of 0.168 for volume and a RMSPE of 0.179 for speed. The successful application of the proposed methodology framework to real road networks demonstrates its ability to provide results both with satisfactory accuracy and within a reasonable time, thus establishing its potential usefulness to support dynamic traffic assignment modeling, ITS systems, and other strategies.

An integrated multi-agent framework for optimizing time, cost and environmental impact of construction processes

Environmentally conscious construction has received a significant amount of research attention during the last decades. Even though construction literature is rich in studies that emphasize the importance of environmental impact during the construction phase, most of the previous studies failed to combine environmental analysis with other project performance criteria in construction. This is mainly because most of the studies have overlooked the multi-objective nature of construction projects. In order to achieve environmentally conscious construction, multi-objectives and their relationships need to be successfully analyzed in the complex construction environment. The complex construction system is composed of changing project conditions that have an impact on the relationship between time, cost and environmental impact (TCEI) of construction operations. Yet, this impact is still unknown by construction professionals. Studying this impact is vital to fulfill multiple project objectives and achieve environmentally conscious construction. This research proposes an analytical framework to analyze the impact of changing project conditions on the relationship of TCEI. This study includes green house gas (GHG) emissions as an environmental impact category. The methodology utilizes multi-agent systems, multi-objective optimization, analytical network process, and system dynamics tools to study the relationships of TCEI and support decision-making under the influence of project conditions. Life cycle assessment (LCA) is applied to the evaluation of environmental impact in terms of GHG. The mixed method approach allowed for the collection and analysis of qualitative and quantitative data. Structured interviews of professionals in the highway construction field were conducted to gain their perspectives in decision-making under the influence of certain project conditions, while the quantitative data were collected from the Florida Department of Transportation (FDOT) for highway resurfacing projects. The data collected were used to test the framework. The framework yielded statistically significant results in simulating project conditions and optimizing TCEI. The results showed that the change in project conditions had a significant impact on the TCEI optimal solutions. The correlation between TCEI suggested that they affected each other positively, but in different strengths. The findings of the study will assist contractors to visualize the impact of their decision on the relationship of TCEI.

A methodology to estimate time varying user responses to travel time and travel time reliability in a road pricing environment

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

Development of safety performance functions for SafetyAnalyst applications in Florida

In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency's safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.

Frameworks for Systemic and Structural Analysis of Financial Innovations in Infrastructure

Financial innovations have emerged globally to close the gap between the rising global demand for infrastructures and the availability of financing sources offered by traditional financing mechanisms such as fuel taxation, tax-exempt bonds, and federal and state funds. The key to sustainable innovative financing mechanisms is effective policymaking. This paper discusses the theoretical framework of a research study whose objective is to structurally and systemically assess financial innovations in global infrastructures. The research aims to create analysis frameworks, taxonomies and constructs, and simulation models pertaining to the dynamics of the innovation process to be used in policy analysis. Structural assessment of innovative financing focuses on the typologies and loci of innovations and evaluates the performance of different types of innovative financing mechanisms. Systemic analysis of innovative financing explores the determinants of the innovation process using the System of Innovation approach. The final deliverables of the research include propositions pertaining to the constituents of System of Innovation for infrastructure finance which include the players, institutions, activities, and networks. These static constructs are used to develop a hybrid Agent-Based/System Dynamics simulation model to derive propositions regarding the emergent dynamics of the system. The initial outcomes of the research study are presented in this paper and include: (a) an archetype for mapping innovative financing mechanisms, (b) a System of Systems-based analysis framework to identify the dimensions of Systems of Innovation analyses, and (c) initial observations regarding the players, institutions, activities, and networks of the System of Innovation in the context of the U.S. transportation infrastructure financing.

Assessment of policies for innovative financing in infrastructure systems

Infrastructure systems are drivers of the economy in the nation. A dollar spent on infrastructure development yields roughly double the initial spending in ultimate economic output in the short term; and over a twenty-year period, and generalized ‘public investment’ produces an aggregated $3.21 of economic activity per $1.00 spent [1]. Thus, formulation of policies pertaining to infrastructure investment and development is of significance affecting the social and economic wellbeing of the nation. The aim of this policy brief is to evaluate innovative financing in infrastructure systems from two different perspectives: (1) through consideration of the current condition of infrastructure in the U.S., the current trends in public spending, and the emerging innovative financing tools; (2) through evaluation of the roles and interactions of different agencies in the creation and the diffusion of innovative financing tools. Then using the example of transportation financing, the policy brief provides an assessment of policy landscapes which could lead to the closure of infrastructure financing gap in the U.S and proposes strategies for citizen involvement to gain public support of innovative financing.

Time, Cost, and Environmental Impact Analysis for Sustainable Design at Multiple Building Levels

Construction projects are complex endeavors that require the involvement of different professional disciplines in order to meet various project objectives that are often conflicting. The level of complexity and the multi-objective nature of construction projects lend themselves to collaborative design and construction such as integrated project delivery (IPD), in which relevant disciplines work together during project conception, design and construction. Traditionally, the main objectives of construction projects have been to build in the least amount of time with the lowest cost possible, thus the inherent and well-established relationship between cost and time has been the focus of many studies. The importance of being able to effectively model relationships among multiple objectives in building construction has been emphasized in a wide range of research. In general, the trade-off relationship between time and cost is well understood and there is ample research on the subject. However, despite sustainable building designs, relationships between time and environmental impact, as well as cost and environmental impact, have not been fully investigated. The objectives of this research were mainly to analyze and identify relationships of time, cost, and environmental impact, in terms of CO2 emissions, at different levels of a building: material level, component level, and building level, at the pre-use phase, including manufacturing and construction, and the relationships of life cycle cost and life cycle CO2 emissions at the usage phase. Additionally, this research aimed to develop a robust simulation-based multi-objective decision-support tool, called SimulEICon, which took construction data uncertainty into account, and was capable of incorporating life cycle assessment information to the decision-making process. The findings of this research supported the trade-off relationship between time and cost at different building levels. Moreover, the time and CO2 emissions relationship presented trade-off behavior at the pre-use phase. The results of the relationship between cost and CO2 emissions were interestingly proportional at the pre-use phase. The same pattern continually presented after the construction to the usage phase. Understanding the relationships between those objectives is a key in successfully planning and designing environmentally sustainable construction projects.

Dynamic Behavior and Fatigue Life of Highway Bridges Due to Doubling Heavy Vehicles

An increase in the demand for the freight shipping in the United States has been predicted for the near future and Longer Combination Vehicles (LCVs), which can carry more loads in each trip, seem like a good solution for the problem. Currently, utilizing LCVs is not permitted in most states of the US and little research has been conducted on the effects of these heavy vehicles on the roads and bridges. In this research, efforts are made to study these effects by comparing the dynamic and fatigue effects of LCVs with more common trucks. Ten Steel and prestressed concrete bridges with span lengths ranging from 30’ to 140’ are designed and modeled using the grid system in MATLAB. Additionally, three more real bridges including two single span simply supported steel bridges and a three span continuous steel bridge are modeled using the same MATLAB code. The equations of motion of three LCVs as well as eight other trucks are derived and these vehicles are subjected to different road surface conditions and bumps on the roads and the designed and real bridges. By forming the bridge equations of motion using the mass, stiffness and damping matrices and considering the interaction between the truck and the bridge, the differential equations are solved using the ODE solver in MATLAB and the results of the forces in tires as well as the deflections and moments in the bridge members are obtained. The results of this study show that for most of the bridges, LCVs result in the smallest values of Dynamic Amplification Factor (DAF) whereas the Single Unit Trucks cause the highest values of DAF when traveling on the bridges. Also in most cases, the values of DAF are observed to be smaller than the 33% threshold suggested by the design code. Additionally, fatigue analysis of the bridges in this study confirms that by replacing the current truck traffic with higher capacity LCVs, in most cases, the remaining fatigue life of the bridge is only slightly decreased which means that taking advantage of these larger vehicles can be a viable option for decision makers.