Geological carbon sequestration, as a method of atmospheric greenhouse gas reduction, is at the technological forefront of the climate change movement. During sequestration, carbon dioxide (CO���) gas effluent is captured from coal fired power plants and is injected into a storage saline aquifer or depleted oil reservoir. In an effort to fully understand and optimize CO��� trapping efficiency, the capillary trapping mechanisms that immobilize subsurface CO��� were analyzed at the pore-scale. Pairs of proxy fluids representing the range of in situ supercritical CO��� and brine conditions were used during experimentation. The two fluids (identified as wetting and non-wetting) were imbibed and drained from a flow cell apparatus containing a sintered glass bead column. Experimental and fluid parameters, such as interfacial tension, fluid viscosities and flow rate, were altered to characterize their relative impact on capillary trapping. Computed x-ray microtomography (CMT) was used to identify immobilized CO��� (non-wetting fluid) volumes after imbibition and drainage events. CMT analyzed data suggests that capillary behavior in glass bead systems do not follow the same trends as in consolidated natural material systems. An analysis of the disconnected phases in both the initial and final flood events indicate that the final (residual) amount of trapped non-wetting phase has a strong linear dependence on the original amount of non-wetting phase (after primary imbibition), which corresponds to the amount of gas or oil present in the formation prior to CO��� injection. More importantly, the residual trapped gas was also observed to increase with increasing non-wetting fluid phase viscosity. This suggests that CO��� sequestration can be optimized in two ways: through characterization of the trapped fluid present in the formation prior to injection and through alterations to the viscosity of supercritical CO2. / Graduation date: 2013

In recent years, the issues of energy dependency and renewable energy options have gained recognition with not only policy-makers but also mainstream consumers. Understanding consumer beliefs and preferences related to these issues is therefore relevant as innovative renewable energy markets have the potential to change conventional consumer purchasing decisions. This paper investigates the beliefs and behaviors of U.S. consumers related to E85 ethanol from corn and cellulosic feedstocks. Four distinct market segments are created so that the ethanol market can be investigated more in-depth. Overall familiarity with ethanol as an alternative fuel is high; however, individual segments vary on beliefs related to corn and cellulosic ethanol, purchasing Flex-Fuel Vehicles, general concern for the environment, and many other factors. In order to successfully market ethanol to a diverse market, the preferences, beliefs and behaviors of these four distinct segments should be taken into account. While environmental concern has waxed and waned over time, issues like as climate change have come to the forefront of both domestic and international discussion and policy. The role of greenhouse gas emissions in contributing to climate change has been acknowledged. As a major source of emissions, transportation fuels are an obvious source of potential reductions in greenhouse gas emissions. This study segments consumers into four distinct market segments and uses a contingent choice method to determine willingness to pay for reductions in greenhouse gas emissions through purchases of E85 ethanol blends. Overall, willingness to pay is estimated at about 0.18 cents per gallon for each percentage in emissions reductions when compared with gasoline containing no ethanol (E0). Willingness to pay for emissions reductions varies in significance and degree across the four market segments. The diversity between the four segments implies that marketing plans should take into account the heterogeneity of consumers and make efforts to account for their varied needs and preferences.

The Earth's atmosphere is expected to warm in response to increasing atmospheric concentrations of greenhouse gases (GHG). The response of the Earth's complex and chaotic climate system to the GHG emissions is, however, difficult to assess. In this thesis, two issues of importance for the assessment of this response are studied. The first concerns the magnitude of the natural and anthropogenic emissions of CO2. An atmospheric transport model is used, combined with inventories of anthropogenic CO2 emissions and estimates of natural emissions, to compare modelled and observed variations in the concentration of CO2 at an Arctic monitoring site. The anthropogenic and natural emissions are shown to exert approximately equal influence on Arctic CO2 variations during winter. The primary focus of this thesis is the response of the climate system to the enhanced GHG forcing. It has been proposed that this response may project onto the leading modes of variability. In the present thesis, this hypothesis is tested against the alternative that the spatial patterns of variability change in response to the enhanced forcing. The response of the atmospheric circulation to the enhanced GHG forcing as simulated by a specific coupled global climate model (CGCM) is studied. The response projects strongly onto the leading modes of present-day variability. The spatial patterns of the leading modes are however changed in response to the enhanced GHG forcing. These changes in the spatial patterns are associated with a strengthening of the waveguide for barotropic Rossby waves in the Southern Hemisphere. The Northern Hemisphere waveguide is however unchanged. The magnitude of the global mean responses to an enhanced GHG forcing as simulated by CGCMs vary. Moreover, the regional responses vary considerably among CGCMs. In this thesis, it is hypothesised that the inter-CGCM differences in the spatial patterns of the response to the enhanced GHG forcing are partially explained by inter-CGCM differences in zonal-mean properties of the atmospheric flow. In order to isolate the effect of these differences in the zonal-mean background state from the effects of other sensitivities, a simplified model with idealised forcing is employed. The model used is a global three-level quasi-geostrophic model. The sensitivity of the stationary wave pattern (SWP) to changes in the zonal-mean wind and tropopause height of similar magnitude as those found in response to the enhanced GHG forcing in CGCMs is investigated. The SWP in the simplified model shows a sensitivity of comparable magnitude to the analogous response in CGCMs. These results indicate that the CGCM-simulated response is sensitive to relatively small differences in the zonal-mean background state. To assess the uncertainties in the regional response to the enhanced forcing associated with this sensitivity, ensemble simulations of climate change are of great importance.

Landscape scale quantification enables farmers to pool resources and expertise. However, the problem remains of how to quantify these gains. This article considers current greenhouse gas (GHG) quantification methods that can be used in a landscape scale analysis in terms of relevance to areas dominated by smallholders in developing countries. In landscape scale carbon accounting frameworks, measurements are an essential element. Sampling strategies need careful design to account for all pools/fluxes and to ensure judicious use of resources. Models can be used to scale-up measurements and fill data gaps. In recent years a number of accessible models and calculators have been developed which can be used at the landscape scale in developing country areas. Some are based on the Intergovernmental Panel on Climate Change (IPCC) method and others on dynamic ecosystem models. They have been developed for a range of different purposes and therefore vary in terms of accuracy and usability. Landscape scale assessments of GHGs require a combination of ground sampling, use of data from census, remote sensing (RS) or other sources and modelling. Fitting of all of these aspects together needs to be performed carefully to minimize uncertainties and maximize the use of scarce resources. This is especially true in heterogeneous landscapes dominated by smallholders in developing countries.

This doctoral thesis contains three essays on the economics of climate change and the electricity sector. The first essay deals with the subject of greenhouse gas (GHG) emissions and economic growth. The second essay addresses the issues of climate change policies, especially the role of the emergent innovative technologies, and the restructuring of the electricity sector. The third essay presents a model of transmission investments in electric power networks. Chapter One studies the impacts of climate change on economic growth in the world economies. The paper contains explicit formalization of the depletion process of exhaustible fossil fuels and the phase of technology substitution. The impacts of climate change on capital flows and welfare across countries are also investigated. The restructuring of the electricity sector is studied in Chapter Two. It also analyzes how climate change policies can benefit from emergent innovative technologies and how emergent innovative technologies can lower GHG emissions. It is shown that the price of electricity is strictly rising before emergent innovative firms with zero GHG emissions enter the market, but strictly declining as the entry begins. In Chapter Three, a model of electricity transmission investments from the perspective of the regulatory approach is formulated. The Mid-West region of Western Australia, a sub-system of the South West Interconnected System is considered. In contrast with most models in the literature that deal only with network deepening, this model deals with both network deepening and network widening. Moreover, unlike the conventional investment models which are static and deal only with the long run, this model is dynamic and focuses on the timing of the infrastructure investments. The paper is a study of an optimal transmission investment program which is part of the optimal investment program for an integrated model in which investments in transmission and investments in generation are made at the same time.

As the third most important greenhouse gas, nitrous oxide (N2O) is a stable greenhouse gas and also plays a significant role in stratospheric ozone destruction. The primary anthropogenic source of N2O stems from the use of nitrogen in agriculture, with soils being the major contributors. Currently, the annual N2O emissions from this “soil–microbe-plant” system is more than 2.6 Tg (one Tg equals a million metric tons) of N2O-N globally. My doctoral studies aimed to explore innovative strategies for N2O mitigation, in the context of environmental microbiology’s potential contribution to alleviating global warming. The bacterial enzyme nitrous oxide reductase (N2OR), naturally found in some soils, is the only known enzyme capable of catalyzing the final step of the denitrification pathway, conversion of N2O to N2. Therefore, to “scrub” or reduce N2O emissions, bacterial N2OR was heterologously expressed inside the leaves and roots of transgenic plants. Others had previously shown that the functional assembly of the catalytic centres (CuZ) of N2OR is lacking when only nosZ is expressed in other bacterial hosts. There, coexpression of nosZ with nosD, nosF and nosY was found to be necessary for production of the catalytically active holoenzyme. I have generated transgenic tobacco plants expressing the nosZ gene, as well as tobacco plants in which the other four nos genes were coexpressed. More than 100 transgenic tobacco lines, expressing nosZ and nosFLZDY under the control of rolD promoter and d35S promoter, have been analyzed by PCR, RT-PCR and Western blot. The activity of N2OR expressed in transgenic plants, analyzed with the methyl viologen-linked enzyme assay, showed detectable N2O reducing activity. The N2O-reducing patterns observed were similar to that of the positive control purified bacterial N2OR. The data indicated that expressing bacterial N2OR heterologously in plants, without the expression of the accessory Nos proteins, could convert N2O into inert N2. This suggests that atmospheric phytoremediation of N2O by plants harbouring N2OR could be invaluable in efforts to reduce emissions from crop production fields.

The shift to strong hybrid and electrified vehicle architectures engenders controversy and brings about many unanswered questions. It is unclear whether developed markets will have the infrastructure in place to support and successfully implement them. To date, limited effort has been made to comprehend if the energy and transportation solutions that work well for one city or geographic region may extend broadly. A region's capacity to supply a fleet of EVs, or plug-in hybrid vehicles with the required charging infrastructure, does not necessarily make such vehicle architectures an optimal solution. In this study, a mix of technologies ranging from HEV to PHEV and EREV through to Battery Electric Vehicles were analyzed and set in three Canadian Provinces and 3 U.S. Regions for the year 2020. Government agency developed environmental software tools were used to estimate greenhouse gas emissions and energy use. Projected vehicle technology shares were employed to estimate regional environmental implications. Alternative vehicle technologies and fuels are recommended for each region based on local power generation schemes. / UOIT

Methane fluxes were calculated from measurements carried out at a temperate upland forest in Central Ontario using the eddy covariance method over five months in the summer and fall seasons of 2011. Measurements were made by an off-axis integrated cavity output spectrometer Fast Greenhouse Gas Analyzer (FGGA) which simultaneously measured methane (CH4), carbon dioxide (CO2), and water at 10 Hz sampling rates. Observed methane fluxes showed net uptake of methane over the measurement period with an average uptake flux value (±standard deviation of the mean) of -2.7±0.13 nmol m-2 s-1. Methane fluxes showed a diurnal pattern of increased uptake during the day and increasing uptake with seasonal progression. There was also a significant correlation in methane fluxes with soil water content and wind speed. Comparison of the FGGA measurements to those using a static chamber method and canister sampling showed close agreement in flux and mixing ratio values respectively.

Methane fluxes were calculated from measurements carried out at a temperate upland forest in Central Ontario using the eddy covariance method over five months in the summer and fall seasons of 2011. Measurements were made by an off-axis integrated cavity output spectrometer Fast Greenhouse Gas Analyzer (FGGA) which simultaneously measured methane (CH4), carbon dioxide (CO2), and water at 10 Hz sampling rates. Observed methane fluxes showed net uptake of methane over the measurement period with an average uptake flux value (±standard deviation of the mean) of -2.7±0.13 nmol m-2 s-1. Methane fluxes showed a diurnal pattern of increased uptake during the day and increasing uptake with seasonal progression. There was also a significant correlation in methane fluxes with soil water content and wind speed. Comparison of the FGGA measurements to those using a static chamber method and canister sampling showed close agreement in flux and mixing ratio values respectively.

Buildings are a significant energy consumer and are responsible for an increasingly large percent of worldwide greenhouse gas emissions, currently between 30 and 40 percent. Energy efficiency presents unique opportunities for building owners to reduce their environmental footprint and add value through cost savings, tax deductions, and increased market value. An analysis of 183 samples of efficiency measures in seven technology categories found that 74% of efficiency investments had a positive net present value. Building automation system and chiller plant improvements had the highest mean energy and carbon dioxide savings per square foot. Additionally, building automation systems had, on average the highest return on investment, approximately $800 above the cost of implementation per one thousand square feet. Only building envelope modifications had a negative mean return on investment. Building automation system upgrades avoided an average of 350 pounds of CO2e for every dollar spent, reducing a building’s total carbon footprint by as much as 28%. The results suggest that a significant opportunity for cost, energy, and emission savings is available across all technology categories.