Western Canadian bitumen is becoming a predominant source of energy for North American markets. The bitumen extraction and upgrading processes in the oil sands industry require vast quantities of energy, in the form of power, H2, steam, hot water, diesel fuel, and natural gas. These energy commodities are almost entirely produced using fossil feedstocks/fuels, which results in significant CO2 atmospheric emissions. CO2 capture and storage (CCS) technologies are recognized as viable means to mitigate CO2 emissions. Coupling CCS technologies to H2 and power plants can drastically reduce the CO2 emissions intensity of the oil sands industry. The CO2 streams from such plants can be used in Enhanced Oil Recovery, Enhanced Coal Bed Methane, and underground CO2 storage. The above CO2 sinks currently exist in Alberta and roughly half of its territory is deemed suitable for geological storage of CO2. This study investigates the relationship between energy demands, energy costs and CO2 emissions associated with current and proposed oil sands operations using various energy production technologies. Accordingly, two computer models have been developed to serve as energy planning and economic optimization tools for the public and private sectors. The first model is an industry-wide mathematical model, called the Oil Sands Operations Model (OSOM). It serves to quantify the demands for power, H2, steam, hot water, process fuel, and diesel fuel of the oil sands industry for given production levels of bitumen and synthetic crude oil (SCO), by mining and/or thermal extraction techniques. The second model is an optimal economic planning model for large-scale energy production featuring CCS technologies to reduce CO2 emissions in the oil sands industry. Its goal is to feasibly answer the question: What is the optimal combination of energy production technologies, feedstocks, and CO2 capture processes to use in the oil sands industry that will satisfy energy demands at minimal cost while attaining CO2 reduction targets for given SCO and bitumen production levels? In 2003, steam, H2, and power production are the leading sources of CO2 emissions, accounting for approximately 80% of the total emissions of the oil sands industry. The CO2 intensities calculated by the OSOM range from 0.080 to 0.087 tonne CO2 eq/bbl for SCO and 0.037 tonne CO2 eq/bbl for bitumen. The energy costs in 2003 are $13.63/bbl and $5.37/bbl for SCO and bitumen, respectively. The results from the OSOM indicate that demands for steam, H2, and power will catapult between 2003 and 2030. Steam demands for thermal bitumen extraction will triple between 2003-2012 and triple again between 2012-2030. The H2 demands of the oil sands industry will triple by 2012 and grow by a factor of 2.7 thereafter. Power demands will roughly double between 2003 and 2012 and increase by a factor of 2.4 by 2030. The optimal energy infrastructures featured in this work reveal that natural gas oxyfuel and combined-cycle power plants plus coal gasification H2 plants with CO2 capture hold the greatest promise for optimal CO2-constrained oil sands operations. In 2012, the maximum CO2 reduction level attainable with the optimal infrastructure is 25% while in 2030 this figure is 39% with respect to “business as usual” emissions. The optimal energy costs at maximum CO2 reduction in 2012 are $21.43/bbl (mined SCO), $22.48/bbl (thermal SCO) and $7.86/bbl (bitumen). In 2030, these costs are $29.49/bbl (mined SCO), $31.03/bbl (thermal SCO), and $10.32/bbl (bitumen). CO2 transport and storage costs account for between 2-5% of the total energy costs of SCO and are negligible in the case of bitumen. The optimal energy infrastructures are mostly insensitive to variations in H2 and power plant capital costs. The energy costs are sensitive to changes in natural gas prices and insensitive to changes in coal prices. Variations in CO2 transport and storage costs have little impact on SCO energy costs and a null impact on bitumen energy costs. Likewise, all energy costs are insensitive to changes in the length of the CO2 pipeline for transport.

The expansion of supply chains into global networks has drastically increased the distance travelled along shipping lanes in a logistics system. Inherently, the increase in travel distances produces increased carbon emissions from transport vehicles. When increased emissions are combined with a carbon tax or emissions trading system, the result is a supply chain with increased costs attributable to the emission generated on the transportation routes. Most traditional supply chain design models do not take emissions and carbon costs into account. Hence, there is a need to incorporate emission costs into a supply chain optimization model to see how the optimal supply chain configuration may be affected by the additional expenses. This thesis presents a mathematical programming model for the design of green supply chains. The costs of carbon dioxide (CO2) emissions were incorporated in the objective function, along with the fixed and transportation costs that are typically modeled in traditional facility location models. The model also determined the unit flows between the various nodes of the supply chain, with the objective of minimizing the total cost of the system by strategically locating warehouses throughout the network. The literature shows that CO2 emissions produced by a truck are dependent on the weight of the vehicle and can be modeled using a concave function. Hence, the carbon emissions produced along a shipping lane are dependent upon the number of units and the weight of each unit travelling between the two nodes. Due to the concave nature of the emissions, the addition of the emission costs to the problem formulation created a nonlinear mixed integer programming (MIP) model. A solution algorithm was developed to evaluate the new problem formulation. Lagrangian relaxation was used to decompose the problem by echelon and by potential warehouse site, resulting in a problem that required less computational effort to solve and allowed for much larger problems to be evaluated. A method was then suggested to exploit a property of the relaxed formulation and transform the problem into a linear MIP problem. The solution method computed the minimum cost for a complete network that would satisfy all the needs of the customers. A primal heuristic was introduced into the Lagrangian algorithm to generate feasible solutions. The heuristic utilized data from the Lagrangian subproblems to produce good feasible solutions. Due to the many characteristics of the original problem that were carried through to the subproblems, the heuristic produced very good feasible solutions that were typically within 1% of the Lagrangian bound. The proposed algorithm was evaluated through a number of tests. The rigidity of the problem and cost breakdown were varied to assess the performance of the solution method in many situations. The test results indicated that the addition of emission costs to a network can change the optimal configuration of the supply chain. As such, this study concluded that emission costs should be considered when designing supply chains in jurisdictions with carbon costs. Furthermore, the tests revealed that in regions without carbon costs it may be possible to significantly reduce the emissions produced by the supply chain with only a small increase in the cost to operate the system.

The organic wheat supply chain in Canada operates in a relatively new sector for which there is very little public information to aid in price discovery. Organic wheat producers must use available information in order to decide when to sell their wheat and whom to sell to. The relatively low degree of market information, especially for producers, suggests a problem of information asymmetry, which may have ramifications for efficiency and the distribution of rents in the organic wheat supply chain. The literature on Transaction Cost Economics, Agency Theory and the Economics of Information is used in the thesis to theorize differences between methods of selling organic wheat that vary in terms of vertical coordination. The analysis involves a comparison of selling to large and small grain companies, selling through Producer-Owned Firms (POFs) and selling directly to processors. The theory predicts that producers gain from using a POF because of savings in transaction costs and higher prices. These theorized differences in transaction costs and price are due to increased sharing of information between the producer and the marketing agent, enhanced producer control over the marketer, and incentive for the marketer to provide producers with a high price. These benefits can also be realized by selling directly to a processor, but only if the producer can effectively and efficiently perform his or her own marketing functions. Average cost, price and profit margins are used as a metric for comparing each of the four governance structures. A survey of organic wheat producers in Saskatchewan was undertaken in order to collect data on organic Hard Red Spring Wheat (HRSW) transactions. The results indicate that governance structure has a statistically significant effect on organic HRSW prices and on producer transaction costs. The analysis concludes that the producer receives the greatest profit margin from selling through the vertically coordinated POF, while a marketer receives the greatest profit margin if it operates as a large grain company and purchases HRSW on the spot market. The results also suggest that organic producers that eliminate the middleman and sell directly to processors cannot market as efficiently and effectively compared with producers that use a POF. The results of this thesis emphasize that increased coordination between producer and marketer through a POF can be advantageous for the producer, but not necessarily for the marketer, due to the difference in the distribution of rents.

Currently, the labeling of functional food products is highly regulated in Canada. Although certain nutrient content claims and five generic health claims have been allowed, the inability to make additional nutrient content and health claims decreases functional food firms incentives to produce and commercialize new and healthy food products. This, in turn, has consequences for functional food demand, consumer welfare, and health care costs. The primary objective of this thesis is to examine the potential welfare implications of functional food labeling for Canadian society.<p>A benefit cost analysis is conducted to examine a specific case study of omega-3 enriched eggs. The benefit cost analysis evaluates the welfare effects of functional food labeling policy and helps realize the magnitude of potential benefits that could be gained if not for restrictive and complicated labeling regulations. Based on a range of assumptions and using three different scenarios to cover a range of estimates, the health benefits from the reduction in the risk of coronary heart disease due to the current consumption of omega-3 enriched eggs, and the production and labeling-related costs are estimated. By comparing the estimated benefits and costs, the results indicate that the current consumption of omega-3 enriched eggs provides a considerable net economic gain. Therefore, labeling information on health components can contribute to facilitating a healthy lifestyle with reduced medical costs, stimulating agricultural innovation, and increasing economic welfare.<p>Realizing the positive overall impact that the current consumption of omega-3 enriched eggs has on consumers health and economy in Canada, a possible policy that could regulate all eggs to be enriched with omega-3 fatty acids is proposed. This policy could potentially be used to correct not only information asymmetry but also the negative externalities that are created by health and disability insurances. The benefit cost analysis show that the health benefits would be greatly increased while costs would slightly increase due to reduced labeling-related costs. Therefore, the results indicate that the net economic gain is even stronger if the mandatory development of omega-3 enriched eggs were required.

Abstract It is well known that geographical distances between nations cause differences in cul-tural resemblances as well as affinity. Defined, affinity is inheriting similarities between nations in familiarity, language and mutual understanding. It cause variations in the uni-lateral trade volume flowing towards the destination countries and can be estimated by a traditional gravity model (GM). So far Swedish affinity towards Czech Republic (CZ) has remained unexplored. Hence, this paper investigates Swedish firm´s export perfor-mance and affinity towards CZ, both through the aggregate export and the extensive margin (average number of exporters). The investigation aims to seek clarification of what particular factors influence unilateral export towards CZ as well as stronger affini-ty in contrast to similar markets. To answer those questions, a one sided GM is re-gressed on two gravity equations, covering panel data for 177 destination countries from year 1997 to 2006. Results are in line with the expected behavior of the GM and show evidently; distance as well as land lock features have negative effects on unilateral ex-ports to CZ. Additionally, evidence of positive influence on unilateral export is found for GDP and familiarity to the nation. Both regressions for the gravity equations are showing high goodness of fit for the panel data. Findings of positive residuals in both the equations conclude that Swedish export have stronger affinity to CZ and solider country characteristics than its resembling countries Slovenia and Slovakia. However, positive residuals also indicate larger export flows to CZ than motivated by the tradi-tional GM coefficients. Various explanations are suggested as origins for those, such as differences in purchasing power and regions, were Prague was found to be the most suitable option for export and other regions rather for outsourcing possibilities.

Die Arbeit ist ein Beitrag zur betrieblich-ökonomischen Optimierung der Eisenbahninfrastruktur auf der Grundlage ihres Kosten-Nutzen-Verhältnisses. Der wesentliche Inhalt der Arbeit ist die Erarbeitung einer Methodik, mit deren Hilfe die Kosten einer Eisenbahnstrecke je fahrbarer Zugtrasse, basierend auf Streckenstandards, der Deutsche Bahn AG, berechnet werden können.

<p>Consumers often lack objective information about product acquisition costs. In such cases, consumers must rely on estimates of acquisition costs in making their choices. The current work examines the influence of mental simulations of product acquisition on estimates of acquisition costs. We suggest that simulations of product acquisition lead estimates to reflect the influence of consumers' current physical states on the experience of a particular cost. Specifically, carrying a heavy burden leads consumers to estimate higher distances to targets when they engage in simulation of walking to targets, but not when they do not engage in such simulation.</p><p>Simulation can be either deliberate or spontaneous. Deliberate simulation is engaged when consumers intentionally simulate an action. Spontaneous simulation requires particular conditions for its occurrence, but does not require conscious intent. The specific conditions for the occurrence of spontaneous simulation are the availability of situational inputs and that action be possible in the given situation. We support these ideas in a series of studies.</p><p>Study 1 demonstrates preference shifts that occur as a consequence of participants carrying heavy burdens. Participants in this study shifted their preference from an option located a visible but undefined distance away towards one that was available at their current location. Study 2 supports the theory that this shift occurs as a consequence of alterations in estimates of acquisition costs by showing that burdened participants estimate distances as greater than do unburdened participants. </p><p>Study 3 provides evidence for the role of mental simulation in producing such changes in estimated acquisition costs by showing that the distance expansion first demonstrated in study 2 occurs when targets are visible, but not when targets are not visible. This result is consistent with the central contention of this dissertation that visibility is critical for spontaneous simulation. Together, the studies support the role of spontaneous simulation in burden leading to distance expansion. Study 4 provides further support for the role of simulation in producing the effects of physical state on estimated acquisition costs by showing deliberate simulation results in similar distance to that of spontaneous simulation. </p><p>Studies 5 and 6 further demonstrate the dual roles of spontaneous and deliberate simulation on distance expansion. They show that expansion does not occur when targets are not reachable because they are up in the air (study 5). However, deliberate simulation of realistic (climbing - study 5) or unrealistic (flying - study 6) action restores distance expansion in those circumstances, supporting the role of simulation in leading to consideration of physical state in estimated acquisition costs.</p><p>The final study ties together these results by demonstrating the effects of both spontaneous and deliberate simulation in a single setting. Varying both the availability of conditions supporting spontaneous simulation and instructions for deliberate simulation the study allows an examination of the comparative effects of the two types of simulation and of their potential interaction. The study finds that deliberate simulation may produce effects that are larger than those of spontaneous simulation, but spontaneous simulation does not seem to enhance the effects of deliberate simulation.</p> / Dissertation

<p>Chapter 1: Although there are widely accepted theoretical explanations for overexploitation of common-pool resources, empirically we have limited information about the micro-level mechanisms that cause individually efficient exploitation to result in macro inefficiency. This paper conducts the first empirical investigation of common-pool resource users' dynamic and strategic behavior at the micro level. With an application to the North Carolina shrimp fishery, we examine fishermen's strategies in a fully dynamic game that accounts for latent resource dynamics and other players' actions. Combining a simulation-based Conditional Choice Probability estimator and a Pseudo Maximum Likelihood estimator, we recover the profit structure of the fishery from fishermen's repeated choices. Using the estimated structural parameters, we compare the fishermen's actual exploitation path to the socially optimal one under a time-specific limited entry system with transferrable permits, and then quantify the dynamic efficiency costs of common-pool resource use. We find that individual fishermen respond to other users by exerting a higher level of exploitation effort than what is socially optimal. Based on our counterfactual experiments, we estimate the efficiency costs of this behavior to be 17.39\% of the annual revenues from the fishery, which translates into 31.4\% of the rent without deducting the cost of capital. </p><p>Chapter 2: Although hypoxia is a threat to coastal ecosystems, policy makers have limited information about the potential economic impacts on fisheries. Studies using spatially and temporally aggregated data generally fail to detect statistically significant fishery effects of hypoxia. Limited recent work using disaggregated fishing data (microdata) reports modest effects of hypoxia on catches of recreationally harvested species. These prior studies have not accounted for important spatial and temporal aspects of the system, however. For example, the effects of hypoxia on catches may not materialize instantaneously but instead may involve a lagged process with catches reflecting cumulative past exposure to environmental conditions. This paper develops a differenced bioeconomic model to account for the lagged effects of hypoxia on the North Carolina brown shrimp fishery. It integrates high-resolution oxygen monitoring data with fishery-dependent microdata from North Carolina's trip ticket program to investigate the detailed spatial and temporal relationships of hypoxia to commercial fishery harvest. The main finding is that hypoxia potentially resulted in a 12.9\% annual decrease in brown shrimp harvest from 1999-2005. The paper also develops two alternative models---a non-differenced model and a polynomial distributed lag model---and results are consistent with the main model.</p><p>Chapter 3: The emergence of ecosystem-based management suggests that traditional fisheries</p><p>management and protection of environmental quality are increasingly interrelated. Fishery managers, however, have limited control over most sources of marine and estuarine pollution and at best can only adapt to environmental conditions. We develop a bioeconomic model of optimal harvest of an annual species that is subject to an environmental disturbance. We parameterize the model to analyze the effect of hypoxia (low dissolved oxygen) on the optimal harvest path of brown shrimp, a commercially important species that is fished in hypoxic waters in the Gulf of Mexico and in estuaries in the southeastern United States. We find that hypoxia alters the qualitative pattern of optimal harvest and shifts the season opening earlier in the year; more severe hypoxia leads to even earlier season openings. However, the quantitative effects of adapting fishery management to hypoxia in terms of fishery rents are small. This suggests that it is critical for other regulatory agencies to control estuarine pollution, and fishery managers need to generate value from the fishery resources through other means such as rationalization.</p> / Dissertation

<p>Locomotion in any environment requires the use of energy to overcome the physical</p><p>forces inherent in the environment. Most large marine vertebrates have evolved</p><p>streamlined fusiform body shapes to minimize the resistive force of drag when in</p><p>a neutral position, but nearly all behaviors result in some increase in that force.</p><p>Too much energy devoted to locomotion may reduce the available surplus necessary</p><p>for population-level factors such as reproduction. The population of North Atlantic</p><p>right whales has not recovered following legal protection due to decreased fecundity,</p><p>including an increase in the intercalf interval, an increase in the years to first calf and</p><p>an increase in the number of nulliparous females in the population. This reproductive</p><p>impairment appears to be related to deficiencies in storing enough energy to meet the</p><p>costs of reproduction. The goal of this study was to determine whether increases in</p><p>moving between prey patches at the cost of decreased foraging opportunities could</p><p>shift these whales into a situation of negative energy gain. The first step is to</p><p>understand the locomotor costs for this species for the key behaviors of traveling and</p><p>foraging.</p><p>This study investigated the cost of locomotion in right whales by recording the</p><p>submerged diving behaviors of free-ranging individuals in both their foraging habitat</p><p>in the Bay of Fundy and their calving grounds in the South Atlantic Bight with a</p><p>suction-cupped archival tag. The data from the tags were used to quantify the oc-</p><p>currence of different behaviors and their associated swimming behaviors and explore</p><p>three behavioral strategies that reduce locomotor costs. First, the influence that</p><p>changes in blubber thickness has on the buoyancy of these whales was investigated</p><p>by comparing the descent and ascent glide durations of individual whales with differ-</p><p>ent blubber thicknesses. Next, the depth of surface dives made by animals of different</p><p>sizes was related to the depth where additional wave drag is generated. Finally, the</p><p>use of intermittent locomotion during foraging was investigated to understand how</p><p>much energy is saved by using this gait. The final piece in this study was to deter-</p><p>mine the drag related to traveling and foraging behaviors from glides recorded by</p><p>the tags and from two different numerical simulations of flow around whales. One, a</p><p>custom developed algorithm for multiphase flow, was used to determine the relative</p><p>drag, while a second commercial package was used to determine the absolute mag-</p><p>nitude of the drag force on the simplest model, the traveling animal. The resulting</p><p>drag estimates were then used in a series of theoretical models that estimated the</p><p>energetic profit remaining after shifts in the occurrence of traveling and searching</p><p>behaviors.</p><p>The diving behavior of right whales can be classified into three stereotyped be-</p><p>haviors that are characterized by differences in the time spent in different parts of the</p><p>water column. The time budgets and swimming movements during these behaviors</p><p>matched those in other species, enabling the dive shapes to be classified as foraging,</p><p>searching and traveling behaviors. Right whales with thicker blubber layers were</p><p>found to perform longer ascent glides and shorter descent glides than those with</p><p>thinner blubber layers, consistent with the hypothesis that positive buoyancy does</p><p>influence their vertical diving behavior. During horizontal traveling, whales made</p><p>shallow dives to depths that were slightly deeper than those that would cause ad-</p><p>ditional costs due to wave drag. These dives appear to allow whales to both avoid</p><p>the costs of diving as well as the costs of swimming near the surface. Next, whales</p><p>were found to glide for 12% of the bottom phases of their foraging dives, and the</p><p>use of `stroke-glide' swimming did not prolong foraging duration from that used by</p><p>continuous swimmers. Drag coefficients estimated from these glides had an average</p><p>of 0.014 during foraging dives and 0.0052 during traveling, values which fall in the</p><p>range of those reported for other marine mammals. One numerical simulation deter-</p><p>mined drag forces to be comparable, while the other drastically underestimated the</p><p>drag of all behaviors. Finally, alterations to the behavioral budgets of these animals</p><p>demonstrated their cost of locomotion constitutes a small portion (8-12%) of the</p><p>total energy consumed and only extreme increases in traveling time could result in a</p><p>negative energy balance. In summary, these results show that locomotor costs are no</p><p>more expensive in this species than those of other cetaceans and that when removed</p><p>from all the other stressors on this population, these whales are not on an energetic</p><p>`knife edge'.</p> / Dissertation

This thesis studies the optimization of a variable speed, three blade, horizontal-axis wind turbine. The design parameters considered are the rotor diameter, hub height and generator capacity. The levelized cost of energy and simple payback are the figures of merit being minimized. Blade element momentum theory is used to calculate the power produced by the wind turbine rotor. Increasing the rotor diameter increases the power delivered to the generator at all wind speeds up to the limit of generator capacity. Increasing the generator capacity raises the limit on maximum power output. Increasing the hub height of a wind turbine increases power output due to the higher wind speeds at increased heights. However, all of these design changes involve an increase in capital cost. Furthermore, wind characteristics vary between wind resources. Therefore, the optimal wind turbine design will change depending on the wind resource. The model developed in this thesis is used to minimize the levelized cost of energy for various wind resources. The results of this study provide a guideline for the optimum wind turbine design in various wind resources. The model is also used to compare the difference between minimizing the levelized cost of energy and minimizing simple payback of a wind turbine located off the coast of Georgia. Simple payback is calculated by considering not only the total annual electricity produced and capital cost of the turbine but also the revenue the turbine will generate. Revenue is calculated from a time-dependent valuation of electrical power. The results of this study show that minimizing levelized cost of energy and minimizing simple payback result in the same optimum design for this particular site. The results show, however, that using a time-dependent valuation of electricity results in a different simple payback than when an average value of electricity is used.