Since 2006 California has been pursuing the most ambitious climate change policy in the United States, implementing a suite of greenhouse gas reduction measures ranging from automobile refrigerant disposal rules to clean energy standards for electric power utilities. The most significant of these measures is the creation of a cap‐and‐trade program. Through this program, regulators seek to create a knowable price‐signal to incentivize emissions reductions among polluters. Using a suite of ethnographic methods, this dissertation looks at the people, ideas, and institutions that have been mobilized in the creation of California’s cap‐and‐ trade program. Substantively, the dissertation engages with three key aspects of the program. First, the way that economic theory is deployed in the creation of the rules of exchange, and how that theory is made to take a compromised but still structuring role in light of the political pressures on regulators in writing the rules of exchange in financial representations of greenhouse gases. Second, the dissertation examines the diverse values, economic and non‐economic, in play during the creation of financial representations of greenhouse gases; and third, the environmental and social justice ramifications of structuring an emissions reduction program around the motivation of doing so at the lowest possible cost to polluters. Theoretically, this dissertation is informed by political ecology on the commodification of nature, commodity theory drawn from economic geography and political economy, and sociological theories of economic practice primarily originating from the social studies of finance. The conclusion of the dissertation is that the result of countless hours of work by regulators and their interlocutors is a suite of market‐like mechanisms that ultimately function more like the administrative tool that environmental markets’ early advocates envisioned rather than the full‐blown financialization of the atmosphere, though with potentially detrimental environmental impacts for vulnerable communities.

In recent decades, climate change has become one of the most crucial challenges for humanity. Climate change has a direct correlation with global warming, caused mainly by the green house gas emissions (GHG). The Environmental Protection Agency in the U.S. (EPA) attributes carbon dioxide to account for approximately 82\% of the GHG emissions. Unfortunately, the energy sector is the main producer of carbon dioxide, with China and the U.S. as the highest emitters. Therefore, there is a strong (positive) correlation between energy production, global warming, and climate change. Stringent carbon emissions reduction targets have been established in order to reduce the impacts of GHG. Achieving these emissions reduction goals will require implementation of policies like as cap-and-trade and carbon taxes, together with transformation of the electricity grid into a smarter system with high green energy penetration. However, the consideration of policies solely in view of carbon emissions reduction may adversely impact other market outcomes such as electricity prices and consumption. In this dissertation, a two-layer mathematical-statistical framework is presented, that serves to develop carbon policies to reduce emissions level while minimizing the negative impacts on other market outcomes. The bottom layer of the two layer model comprises a bi-level optimization problem. The top layer comprises a statistical model and a Pareto analysis. Two related but different problems are studied under this methodology. The first problem looks into the design of cap-and-trade policies for deregulated electricity markets that satisfy the interest of different market constituents. Via the second problem, it is demonstrated how the framework can be used to obtain levels of carbon emissions reduction while minimizing the negative impact on electricity demand and maximizing green penetration from microgrids. In the aforementioned studies, forecasts for electricity prices and production cost are considered. This, this dissertation also presents anew forecast model that can be easily integrated in the two-layer framework. It is demonstrated in this dissertation that the proposed framework can be utilized by policy-makers, power companies, consumers, and market regulators in developing emissions policy decisions, bidding strategies, market regulations, and electricity dispatch strategies.

Electricity generating units (EGUs) are major emitters of both nitrogen oxides (NOx) and CO₂, and cap-and-trade programs are either currently used or proposed as management strategies for both pollutants. Emission cap and trade programs for these two pollutants have generally been considered independently, but since each EGU will have a characteristic NOx to CO₂ emission ratio, these programs are inherently connected. This thesis examines the extent to which CO₂ emission pricing and NOx emission markets are likely to influence each other, using Texas as a case study. The relationship is first demonstrated with a simple scenario of four power plants, followed by a second scenario accounting for the largest 34 plants in Texas. The analysis demonstrates that future CO₂ pricing will cause NOx emissions markets to be inefficient at reducing emissions through changes in the dispatching order. There will also exist a greater potential for NOx price spikes. Two plausible alternatives to this problem are suggested: a temporally- and spatially-variable NOx program, or increased emphasis on retrofitting the existing fleet of power plants for NOx reduction. / text

In this dissertation, I study the effect of environmental regulation on firm behavior. In the first chapter, I use a dynamic model to quantify the effects on exit, entry, investment and welfare of different allocation schemes of a cap-and-trade program. I focus on allocation rules regarding closing plants and new entrants. I calibrate the model with data from the US power plants and perform two policy experiments: first I quantify the effects of the introduction of a cap-and-trade program; second, I do a counterfactual where I switch the allocation rule and study the effect on the new equilibrium and welfare. In the second chapter of this dissertation, I ask whether multinational firms are harmful for a host country environment. I use plant-level data from Chile and find empirical evidence that multinational are cleaner than domestic plants. Based on the trade literature, I build a model where I add environmental regulation and a technology choice. The model proposes a new explanation of why multinationals firms might be cleaner than their domestic peers. I get policy implications from the model and test them with the data. In the third chapter, I study the relation between free permit allocation in a cap-and-trade program and financial constraints. I use the change in the permit prices and the heterogeneity in permit allocation to identify financial constraints for the investor-owned utilities in the electricity sector. / text

The Western Regional Climate Action Initiative (WCI) was signed by the governors of Arizona, California, New Mexico, Oregon, and Washington, on February 26, 2007. Upon the release of the September 2008 Design Recommendations for the WCI Regional Cap-and-Trade Program, the WCI also included Montana, Utah, and the Canadian provinces of British Columbia, Manitoba, Ontario, and Quebec. A WCI goal is to reduce regional greenhouse gas (GHG) emissions 15% below 2005 levels by 2020. It has previously been recognized that the region’s forests can be important carbon sinks and sources, and it has been suggested that the carbon-storage capacity of forests may have economic value. Here, connections between forests and the developing WCI cap-and-trade system design are examined. Qualitative comparative analysis is used to examine characteristics of US states participating in the WCI. Content analysis is used to identify what advocacy groups promote what forest-related WCI cap-and-trade rules. A combination of low per capita GHG emissions, and strong environmental politics, is found to be related to regional climate initiative participation by US states, with important exceptions among WCI participants. Forest industry presence alone does not obviously influence participation. Electric utility and industry groups, including the forestry sector, are found to support an extensive WCI carbon offset system. Forest industry groups are also found to support the carbon neutrality of forest biomass combustion, and oppose regulating forest carbon emissions. Several environmental non-governmental organizations are found to oppose extensive carbon offset use, and oppose the unconditional consideration of biomass combustion as carbon neutral. Forest related aspects of the WCI Design Recommendations of September 2008 are found to largely agree with forest industry advocated policies. Some WCI provisions may provide incentives for forest carbon loss, or weaken the GHG emissions cap. Three recommendations are made: consideration should be given to appropriately discounting forest offset projects to address carbon emissions leakage; forest carbon emissions from land conversion should be accounted for; combustion of forest biomass from old-growth forests should not be considered carbon neutral. / Thesis (Master, Environmental Studies) -- Queen's University, 2009-10-29 22:29:48.499

The purpose of this thesis is to analyze climate change initiatives in China, the United States, and California, determine where they fall on a spectrum from climate change leader to climate change laggard, and evaluate the need for more effective collaboration among these entities in order to collectively tackle the global threat of climate change. This thesis supplements existing literature in the field by synthesizing the climate change activities of three important players in the global arena: China, the United States, and California. This thesis is different from other research, however, by underscoring the collaboration between these three entities and specifically recommending cap and trade as a mechanism through which to reduce greenhouse gas emissions. In this thesis, I claim that on a spectrum from climate change laggard to climate change leader, the United States settles as a laggard, California emerges as a leader, and contrary to popular belief, I argue that China is transitioning between the two. Moreover, I emphasize the importance of more collaboration – especially more substantive collaboration – between these key players in order to achieve significant global emissions reductions because they will stimulate other partnerships around the world and trigger more collective action on climate change. Finally, I offer cap and trade as a viable option through which these three entities can work together to reduce their contribution to global greenhouse gas emissions.

<div>This dissertation consists of three chapters about the European Union Emissions Trading Scheme (EU ETS). All chapters contributes to the scarce but recently great developing literature on installation and firm-level studies in the EU ETS. The first chapter evaluates the policy effectiveness and efficiency by theoretical modelling and</div><div>empirical assessment of firms’ emission abatement activities. The second chapter overviews the global emission trading market, documents the institutional background</div><div>of emission trading, and analyzes firms’ emission trading patterns in light of the broader empirical literature. The last chapter studies productivity and firms’ emission</div><div>permit trading behaviors by considering a complete set of options. In the first chapter, I investigate how firms reduce emissions under continuous adjustment of the policy by using the implementation of the three phases of EU ETS</div><div>as a cost shock. I develop a model of emission abatement with heterogeneous firms by introducing two channels: Reallocation and Investment which incur variable and</div><div>fixed abatement costs respectively. More productive firms are cleaner as they put more effort on Investment. However, the policy effect is ambiguous driven by the magnitude</div><div>and correlation of the proposed abatement technology parameters, which highlights the importance of the current abatement technology for firms’ responses to climate</div><div>policy. I then empirically test the model by using a novel dataset that matches firms’ financial, production and emission data. In addition to providing the elasticity of</div><div>emission intensity, the elasticity of Reallocation and Investment, the model enabled me to estimate the firm’s abatement technology parameters and decompose the emissions into the proposed two channels. The results indicate that firms have a higher efficiency on abatement in utilizing of inputs than green technology investment. The emission change is primarily driven by the channel of Reallocation and is concentrated in non-metallic</div><div>mineral companies. The green innovation is limited under the policy with a small emission intensity decrease even though there is large emission reductions. The second chapter reviews the global rise of emission trading, documents the institutional background of emission trading, and summarizes firms’ emission trading patterns. To the best of my knowledge, this study is one of the first to empirically analyze the trading behaviors of all ETS firms covering all three phases in the EU ETS. I use two micro-level datasets to investigate the permit trading behaviors of all types of trading in the market, including international offset permits. Some explanations of the identified trading patterns are provided in this paper. Additionally, this study also discusses the patterns in light of the broader empirical literature. The last chapter contributes to the literature on the firms’ permit trading behaviors. The development of the EU ETS has complicated firms’ decisions around carbon trading and offered firms more options to offset emissions. We provide a first look at the determinants behind firms’ participation in the EU ETS as well as their trading behaviors by considering a complete portfolio of permit trade markets</div><div>in the EU ETS. Based on a comprehensive permit transaction dataset linked with individual level firm’s characteristics, we quantitatively analyze firms’ participation</div><div>decisions and trading patterns. We focus on the impact of firms’ productivity, endowment position, and endowment value on market choice and trading amount. Our</div><div>results suggest that productive firms are more likely to participate in permits trading and to purchase the permits in the secondary and international markets. Conditional</div><div>on firms’ market choice, the permit trading amount is also correlated with a firm’s productivity and endowment value. In addition, firms in power and energy sector are</div><div>more likely to participate in permit trading than other manufacturing firms. Overall, the empirical results indicate that less productive firms have disadvantages competing</div><div>in the permit trade market.</div>

This dissertation is composed of three essays. In the first essay, I construct a supply and demand model for crude oil markets. I then fit the model to historical price and quantity data to be able to project future oil prices. Ex-post forecasts using this model predict historical price trends more accurately than most oil forecasting models. The second essay incorporates the supply and demand model from the previous paper into a complex systems model that also includes oil futures markets. Adaptive-agent investors in futures markets choose from a set of rules for predicting future prices that includes the rational expectations equilibrium rule, as well as rules that rely on more short-term information. The set of available rules evolves following a genetic algorithm; agents choose which rules to follow based on their past performance. While outcomes vary depending on the specific assumptions made, under a plausible set of assumptions investors can fail to anticipate shortages properly, leading to significant price spikes that would not occur in the rational expectations equilibrium. The last essay addresses the impacts of carbon cap-and-trade policies on consumers. I calculate how higher carbon prices would affect the prices of different consumer goods, how consumers would respond to the price changes, and how the price changes, along with revenue recycling, would impact consumers of different income levels.

In order to meet the US EPA's National Ambient Air Quality Standards as set under the provisions of the Clean Air Act, states and regions throughout the United States are designing cap and trade programs aimed at reducing the emissions of the two dominant precursors for ozone, nitrogen oxides (NOx) and Volatile Organic Compounds (VOCs). While emission cap and trade programs are becoming more common, relatively few analyses have examined the air quality implications of moving emissions from one location to another (due to trading of emissions between facilities), from one sector to another (due to the use of technologies such as Plug-in Electric Hybrid Vehicles - PHEVs), and changing the temporal distribution of emissions (through emissions trading among facilities with different temporal profiles). This thesis will examine, in detail, the air quality implications of two emission cap and trade programs. The first program is a NOx trading program that covers Electricity Generating Units (EGUs) in the Northeastern United States. Results show that refining the temporal limits on this cap and trade program, by charging facilities more to emit NOx on days when ozone is most likely to form, has the potential to significantly reduce NOx emissions and ozone concentrations. Additionally, this research also shows that, for this region, the spatial redistribution of NOx emissions due to trading leads to greater ozone reductions than similar amounts of NOx emission reductions applied evenly across all facilities. Analyses also indicate that displacing emissions from the on-road mobile sector (vehicles) to the EGU sector through the use of PHEVs decreases ozone in most areas, but some highly localized areas show increases in ozone concentration. The second trading program examined in this thesis is limited to Houston, Texas, where a VOC trading program is focused on a sub-set of four Highly Reactive Volatile Organic Compounds (HRVOCs), which have been identified as having substantial ozone formation potential. Work presented in this thesis examined whether this trading program, in its current form or in an expanded form, could lead to air pollution hot spots, due to spatial reallocation of emissions. Results show that the program as currently designed is unlikely to lead to ozone hot spots, so no further spatial limitations are required for this program. Expanding the trading to include Other VOCs, fugitive emissions and chlorine emissions, based on reactivity weighted trading, is also unlikely to lead to the formation of ozone hot spots, and could create more flexibility in a trading market that is currently not very active. Based on these air quality modeling results, policy suggestions are provided that may increase participation in the trading market. These case studies demonstrate that use of detailed air analyses can provide improved designs for increasingly popular emission cap and trade programs, with improved understanding of the impacts of modifying spatial and temporal distributions of emissions. / text

Carbon capture and storage (CCS) and a point of electricity generation is a promising option for mitigating greenhouse gas emissions. One issue with respect to CCS is the design of carbon dioxide transport, storage and injection system. This dissertation develops a model, OptimaCCS, that combines economic and spatial optimization for the integration of CCS transport, storage and injection infrastructure to minimize costs. The model solves for the lowest-cost set of pipeline routes and storage/injection sites that connect CO2 sources to the storage. It factors in pipeline costs, site-specific storage costs, and pipeline routes considerations involving existing right of ways and land use. It also considers cost reductions resulting from networking the pipelines segment from the plants into trunk lines that lead to the storage sites. OptimaCCS is demonstrated for a system involving carbon capture at 14 Texas coal-fired power plants and three potential deep-saline aquifer sequestration sites. In turn OptimaCCS generates 1) a cost-effective CCS pipeline network for transporting CO2 from all the power plants to the possible storage sites, and 2) an estimate of the costs associated with the CO2 transport and storage. It is used to examine variations in the configuration of the pipeline network depending on differences in storage site-specific injection costs. These results highlight how various levels of cooperation by CO2 emitters and difference in injection costs among possible storage sites can affect the most cost-effective arrangement for deploying CCS infrastructure. This study also analyzes CCS deployment under the features in a piece of legislation the draft of American Power Act (APA) - that was proposed in 2010 which contained a goal of CCS capacity for emissions from 72 Gigawatt (GW) by 2034. A model was developed that simulates CCS deployment while considering different combinations of carbon price trajectories, technology progress, and assumed auction prices. The model shows that the deployment rate of CCS technology under APA is affected by the available bonus allowances, carbon price trajectory, CCS incentive, technological adaptation, and auction process. Furthermore it demonstrates that the 72GW objective can only be achieved in a rapid deployment scenario with quick learning-by-doing and high carbon price starting at 25 dollars in 2013 with a 5 percent annual increase. Furthermore under the slow and moderate deployment scenarios CCS capacity falls short of achieving the 72 GW objective.