The injection of carbon dioxide (CO2) into saline formations for the purpose of limiting greenhouse gas emissions has been proposed as an alternative to the atmospheric venting of carbon dioxide. In the evaluation process for selecting a potential target saline formation for the disposal of carbon dioxide, flow characterisation of the disposed plume should be undertaken by reservoir simulation of the target formation. The movement of injected carbon dioxide in the saline formation is influenced by many factors including the physics of carbon dioxide at deep formation depths and pressure, physical interactions with formation rock and pore water and variations in the rock flow pathways through changes in formation heterogeneity. This thesis investigates the roles of physical interactions on the disposal of carbon dioxide and the ability to contain the injected gas through evaluation of trapping mechanisms such as dissolution of CO2 in formation water and residual gas trapping through the process of gas-water relative permeability hysteresis. Variable formation heterogeneity is evaluated for its impact on the migration of injected CO2 plume movement and the role of formation heterogeneity in impeding or accelerating the immobilisation of injected carbon dioxide. Multiple reservoir simulation studies were conducted to evaluate, initially, the role of different trapping mechanisms in immobilising the movement of injected carbon dioxide and subsequently, the role of variations in formation rock in the migration and trapping of and injected plume of carbon dioxide. The major simulation study shows that the selection process for identifying appropriate saline formations should not only consider their size and permeability but should also consider their degree of heterogeneity endemic to the formation. / A set of reservoir performance metrics were developed for the CO2 disposal projects. The metrics were applied to compare plume migration of injected CO2 (both vertically and laterally) and containment (through dissolution and residual phase trapping) in these studies. The findings demonstrate how formation heterogeneity has a significant impact on the subsurface behaviour of the carbon dioxide. Formation dip influences the rate of migration, with low formation dipping reservoirs having slower rates of vertical migration. Increasing the tortuousity of the migration flow path by either increasing the shale (non-reservoir) content or lengthening the shale baffles in the formation (corresponding to a gradual decrease in reservoir quality), can progressively inhibit the vertical flow of the plume whilst promoting its lateral flow. The increase in the tortuosity of the CO2 migration pathway delays the migration of CO2 and increases the residence time for the CO2 in the formation. Thus, formation heterogeneity impedes the onset of residual gas trapping through hysteresis effects. Ultimately less carbon dioxide is likely to collect under the seal in heterogeneous formations due to increased reservoir contact and long residence times, thereby reducing the risk of seepage to overlying formations. / Given sufficient permeability for economic injection of CO2, then low to mid net-to-gross heterogeneous saline formations with low formation dip and lengthy intra-bedded shales are desirable for selection for the geological disposal of CO2. Detailed reservoir characterisation of any potential geological disposal saline formations is required in order to accurately predict the range of outcomes in the long term flow characterisation of injected CO2 into those formations.

Greenhouse gases (GHGs) are vital components of the earth�s atmosphere, trapping heat around the earth, maintaining temperatures necessary for human existence. Until the Industrial Revolution, these gases existed in a natural equilibrium with the environment. Since that time, anthropogenic activities such as fossil fuel burning and land clearing have increased the quantity of GHGs, such as carbon dioxide (CO2) and methane (CH4), in the earth�s atmosphere. Evidence indicates that global warming is occurring as a result of the additional accumulation of GHGs in the atmosphere. International response to climate change resulted in the 1997 development of the Kyoto Protocol. If the Protocol is ratified, developed countries will be legally bound to reduce their GHG emissions in accordance with negotiated emission reduction targets. At the beginning of the year 2001, the Protocol was still to be ratified. With the possibility of future GHG emission restrictions, some Australian companies have started quantifying their GHG emission levels. One such company is Visy Industries, the largest privately owned paper packaging manufacturing company in the world. Visy�s core business is the manufacture of cardboard boxes from recycled paper. As part of its future operations, a kraft pulp and paper mill is presently being built in New South Wales, Australia. The environmental decision support tool, Life Cycle Assessment (LCA), was used to quantify Visy�s CO2 and CH4 emissions across the entire life cycle of the Visy paper recycling and virgin papermaking processes. Commercially defined LCA models were developed for both papermaking processes. GHG emissions estimated by each model were compared and the effect of different energy sources, technologies and manufacturing processes on CO2 and CH4 emissions were assessed. The majority of emissions in the two Visy papermaking models were due to fossil fuel derived energy sources and the decomposition of wood fibre in Solid Waste Disposal Sites (SWDSs). Results were used to propose appropriate GHG reduction strategies and business opportunities. GHG reduction strategies included increasing the use of renewable energy, reducing the volume of solid waste rejects sent to SWDS, incinerating solid waste rejects with energy recovery and sourcing steam from third party providers. Proposed GHG business opportunities included increasing the production of Greenpower from the pulp and paper mill for sale to the grid. This thesis is an example of the practical application of current GHG knowledge and LCA methodology that was undertaken in an environment where technical, political and commercial guidelines at both a national and international level were still evolving. Nevertheless, the thesis is not a critical review of LCA methodology. The LCA support tool was able to quantify CO2 and CH4 emissions across the life cycle of the Visy recycling and virgin papermaking processes. The chosen functional unit, the assumptions and exemptions made, and the placement of the system boundaries, were found to be critical to the Visy LCA results.

With the signing of the Kyoto Protocol, New Zealand must reduce its national greenhouse gas emissions. As New Zealand has a large proportion of its national emissions as methane (~31%), and methane (CH4) has a short atmospheric lifetime, it provides a good target for mitigation strategies. The initial aim of this research was to identify high and low CH4-emitting cattle to assess factors that contribute to low CH4 production. Initial studies using the SF6 tracer technique to estimate CH4 production could not identify consistently high and low CH4 emitters. Research was therefore undertaken to confirm whether this was due to high variation in estimated CH4 yields, and to quantify the within- and between-animal variation in CH4 production when using the SF6 technique. This research showed considerable within- (coefficient of variation, CV = 7-10%) and between-animal (CV = 7-18%) variation in CH4 yield (g CH4/kg DMI) over time when using the SF6 technique. This is larger than the within- (CV = 3%) and between-animal (CV = 10%) variation reported for calorimetry. This led to the recommendation that the SF6 technique not be used in identifying animals for high or low CH4 yield. A power analysis was developed based on the measured variances for the SF6 technique. Results from this analysis provide researchers with important information on the number of animals and measurements per animal required when undertaking CH4 experiments. One of the sources of variation with the SF6 technique is the SF6 release from permeation tubes. Estimated CH4 yield increases by approximately 8.5% when going from a release rate of 3 mg SF6/day to a rate of 5 mg SF6/day. Further, an in vitro study indicated that SF6 release from permeation tubes is approximately 8% lower in rumen fluid than in air. While further research is required to confirm these results, they emphasise the need to allow time for the release rate to stabilise in the rumen for 4-5 days prior to undertaking measurements. It also led to the recommendation that release rates used in experiments should be within a narrow range, and balanced across experimental treatments.

Australia’s economy is heavily dependent on coal-based energy and greenhouse gas intensive natural resource extraction and processing industries. As part of an international climate change mitigation effort Australia will have to undergo a national transformation to a low emissions society by mid century. Federal and State Governments in Australia, like their counterparts in other major developed economies, have been persuaded that reliance on fossil fuels in stationary energy industries such as electricity generation and minerals processing will be able to continue with the deployment of a value chain of technologies fitted to these installations for capturing carbon dioxide, transporting it to a disposal site, and then injecting it into subsurface geological formations for permanent storage (carbon capture and storage, or CCS). Understanding the likely effectiveness of CCS for reducing greenhouse gas emissions from stationary energy industries is therefore critical to policy formulation for, and management of, Australia’s emissions mitigation effort and national transformation over the decades ahead. / This thesis aims to offer a clearer understanding of the practicalities, limitations and uncertainties surrounding future CCS use in Australia and of the contribution CCS can make to mitigating emissions from the Australian stationary energy sector in the period to 2050. It considers two central questions: Is CCS a realistic option for emissions mitigation in Australia? Are Australian climate policies formulated to facilitate CCS deployment and optimise its potential contribution? The criteria employed in this thesis for answering these questions are restricted to those having an ascertainable causal impact on the timing, pace and ultimate scale of CCS deployment within Australia. The methodology used for the research is grounded in critical approaches and integrated assessment within a holistic, trans-disciplinary paradigm. / This thesis finds that under Australia’s existing climate policy framework it is unrealistic to expect CCS can contribute more than 75 million tonnes of CO2 per annum to emissions mitigation by 2050. Australia does have sufficient potential geological storage resources to expect some environmentally safe CCS infrastructure could be engineered over time, but commencement of large scale build-out is not likely before 2025. When CCS will become a commercial mitigation option in Australia is unpredictable and dependent more on the political economy of climate change than on Australian research, development and demonstration activities. / The thesis also finds that the existing climate policy framework is increasing rather than decreasing the risks to timing and usefulness of CCS even to the level of 75 million tonnes of CO2 per annum by 2050. This thesis concludes that Australian Governments are not developing the institutional capability to oversee a holistic decarbonisation of the stationary energy sector. This capability is required not only to address the risks to CCS deployment but also to prevent market failures that foreclose an optimal contribution from all other potential mitigation technologies. The thesis proposes that an Australian national CCS company be created with responsibility for CCS integration, transport and storage services in order to develop Australian capability rather than that of international corporations.

Ongoing climate change has emerged as a major scientific challenge in the current century. Grassland ecosystems are considered net carbon (C) sinks to mitigate climate change. However, they are in turn, influenced by climate change and management practices, providing feedback to climate change via soil microbial community and biogeochemical fluxes. In this thesis, I examined the impact of warming, altered precipitation, and defoliation on soil microbial composition and function, C and N dynamics, and fluxes in soil respiration (CO2), nitrous oxide (N2O) and methane (CH4), together with other belowground ecosystem functions, within two ecosites in a northern native temperate grassland in central Alberta, Canada, over a two-year period. Fungi-to-bacteria ratio was not affected by climatic parameters or defoliation, indicating a high degree of resistance in the below ground community to the treatments imposed. However, C substrate utilization was influenced by warming and defoliation, as was soil microbial biomass. In contrast, soil respiration (or C loss) was not. Soil respiration acclimatized rather quickly to warming, and N2O and CH4 effluxes showed minor responses to warming at both ecosites, regardless of defoliation. These results suggest warming is unlikely to lead to positive climate change feedback due to soil-based responses, regardless of ongoing land use. However, altered precipitation ( 50%) demonstrated greater impacts on C and N fluxes relative to warming and defoliation. Increased precipitation stimulated soil C loss to the atmosphere, potentially generating positive feedback for climatic warming in this northern temperate grassland. / Soil Science

Globally, the transport system faces a paradigmatic shift where, in addition to increased local traffic problems, climate change and depletion of fossil oil reserves will foster a successive transition to renewable fuels and a need for more resource-efficient mobility management and communication alternatives. Foresighted countries, cities or companies taking the lead in adapting to these tougher conditions might well not only solve those problems, but also turn the problems into business advantages. This thesis is based on six studies that attempt to develop future strategies based on rigorous principled emission and energy efficiency targets and to modulate the impact of travel policies, technical components and behaviours in economically advantageous ways. The modelling frameworks developed throughout the thesis build on a target-orientated approach called backcasting, where the following general components are applied: (1) target description at a conceptual level i.e. the potential for sustainable energy systems, emissions, costs, behavioural patterns, preferences, etc.; (2) mapping of the current situation in relation to target description; and (3) modelling of alternative sets of policies, technologies, behaviours and economic prerequisites to arrive at target achievement. Sustainable travel strategies are analysed from two main viewpoints. The first four studies focus on company travel planning, where behavioural modelling proved to be an important tool for deriving targetorientated travel policies consistent with employee preferences. The latter two studies focus on strategies and preconditions to meet future emission targets and energy efficiency requirements at a macroscopic regional level by 2030. Backcasting’s role as a generic methodology for effective strategic planning is discussed. / QC 20100816

The present thesis introduces an iterative expert-based Bayesian approach for assessing greenhouse gas (GHG) emissions from the 2030 German new vehicle fleet and quantifying the impacts of their main drivers. A first set of expert interviews has been carried out in order to identify technologies which may help to lower car GHG emissions and to quantify their emission reduction potentials. Moreover, experts were asked for their probability assessments that the different technologies will be widely adopted, as well as for important prerequisites that could foster or hamper their adoption. Drawing on the results of these expert interviews, a Bayesian Belief Network has been built which explicitly models three vehicle types: Internal Combustion Engine Vehicles (which include mild and full Hybrid Electric Vehicles), Plug-In Hybrid Electric Vehicles, and Battery Electric Vehicles. The conditional dependencies of twelve central variables within the BBN - battery energy, fuel and electricity consumption, relative costs, and sales shares of the vehicle types - have been quantified by experts from German car manufacturers in a second series of interviews. For each of the seven second-round interviews, an expert's individually specified BBN results. The BBN have been run for different hypothetical 2030 scenarios which differ, e.g., in regard to battery development, regulation, and fuel and electricity GHG intensities. The present thesis delivers results both in regard to the subject of the investigation and in regard to its method. On the subject level, it has been found that the different experts expect 2030 German new car fleet emission to be at 50 to 65% of 2008 new fleet emissions under the baseline scenario. They can be further reduced to 40 to 50% of the emissions of the 2008 fleet though a combination of a higher share of renewables in the electricity mix, a larger share of biofuels in the fuel mix, and a stricter regulation of car CO$_2$ emissions in the European Union. Technically, 2030 German new car fleet GHG emissions can be reduced to a minimum of 18 to 44% of 2008 emissions, a development which can not be triggered by any combination of measures modeled in the BBN alone but needs further commitment. Out of a wealth of existing BBN, few have been specified by individual experts through elicitation, and to my knowledge, none of them has been employed for analyzing perspectives for the future. On the level of methods, this work shows that expert-based BBN are a valuable tool for making experts' expectations for the future explicit and amenable to the analysis of different hypothetical scenarios. BBN can also be employed for quantifying the impacts of main drivers. They have been demonstrated to be a valuable tool for iterative stakeholder-based science approaches. / Die vorliegende Arbeit verfolgt zwei Forschungsziele - ein inhaltliches und ein methodisches. Auf der inhaltlichen Ebene wurde die Entwicklung der CO2-Emissionen der deutschen Neuwagenflotte bis 2030 untersucht. Es wurden verschiedene technische Möglichkeiten daraufhin überprüft, inwieweit sie zur Emissionsminderung beitragen können, wie wahrscheinlich es ist, dass sie umgesetzt werden, und welche Voraussetzungen und Rahmenbedingungen bedeutenden Einfluß haben. Die methodische Innovation dieser Arbeit besteht darin, subjektive Einschätzungen von Experten mit einem Bayesianischen Netzwerk zu verknüpfen, um die Anwendung solcher Netzwerke auf Situationen von Unsicherheit im Knight'schen Sinne zu erweitern, hier am Beispiel der zukünftigen, heute nicht vorhersagbaren Entwicklung der CO2-Emissionen der deutschen Neuwagenflotte. Ein erster Schritt dieser Untersuchung bestand in der Erhebung und Auswertung der Einschätzungen von 15 Experten in Bezug auf die Möglichkeiten, die CO2-Emissionen neuer PKW in Deutschland bis 2020 zu senken. Erhoben wurden Aussagen über verfügbare Technologien, ihre Einsparpotenziale, ihre Umsetzungswahrscheinlichkeiten sowie wichtige Rahmenbedingungen. Ziel war es, wesentliche Variablen und deren Abhängigkeiten zu identifizieren, um eine Grundlage für die spätere Modellierung zu schaffen. Um die Untersuchung auf eine breite Basis zu stellen, wurden Experten von Autobauern und Zulieferern, Nichtregierungsorganisationen, Verbänden sowie solche aus Wissenschaft und Journalismus einbezogen. Aufbauend auf diesen Ergebnissen wurde in einem zweiten Schritt ein Bayesianisches Netzwerk entwickelt, mit dem die CO2-Emissionen der deutschen Neuwagenflotte im Jahr 2030 quantifiziert werden können. Außerdem sollten die Marktchancen verschiedener Fahrzeugtypen untersucht werden. Ein weiteres Ziel war es, den Einfluss verschiedener technologischer und regulatorischer Einflussfaktoren zu quantifizieren, die in der ersten Interviewrunde identifiziert worden waren. Gegenüber der ersten Interviewrunde wurde der zeitliche Rahmen der Untersuchung um 10 Jahre auf das Jahr 2030 erweitert. Das Bayesianische Netz erstreckt sich auf die zukünftigen Eigenschaften und Marktchancen von drei Fahrzeugtypen: Verbrennungsmotorische Fahrzeuge einschließlich aller Hybridvarianten bis hin zum Vollhybrid, Plug-In Hybride und Batterie-Elektrofahrzeuge. Das Netzwerk umfasst 46 miteinander verknüpfte Variablen. Für zwölf entscheidende Variablen wurden per Expertenbefragung bedingte Wahrscheinlichkeiten erhoben. Befragt wurden sieben Experten, fast alle hochrangige F&E- oder Umweltexperten bei deutschen Autobauern. Für jeden Experten entstand ein individuell quantifiziertes Netzwerk. Um mögliche Technologie- und Emissionspfade zu untersuchen, wurden verschiedene Szenarien definiert, die unterschiedliche Regulierungen, Batterie-Entwicklungspfade und CO2-Intensitäten von Treibstoffen und elektrischer Energie in Betracht ziehen. Im Basis-Szenario liegen die Erwartungswerte der CO2-Emissionen der deutschen Neuwagenflotte 2030 nach Einschätzung der Experten bei 50 bis 65% der Emissionen der Neuwagenflotte 2008. Kombiniert man einen gesteigerten Anteil erneuerbarer Energien im Strommix, einen größeren Anteil von Biotreibstoffen im Treibstoff-Mix und eine strengere CO2-Emissionsregulierung seitens der Europäischen Union, liegen die erwarteten Emissionen der Neuwagenflotte 2030 bei 40 bis 50% der Emissionen der Neuwagen 2008. Die Erwartungswerte der Neuflotten-Emissionen 2030 können in den verschiedenen BBN auf minimale Werte von 18 bis 44% der Emissionen der deutschen Neuwagenflotte von 2008 festgelegt werden. Es ist in den BBN durchaus möglich, aber in den betrachteten Szenarien unwahrscheinlich, die Emissionen so stark zu senken. Neben der Untersuchung von Fahrzeugtechnologien und CO2-Emissionen bis 2030 verfolgte die vorliegende Arbeit das Ziel, eine innovative Methode zu erproben. Es hat meines Wissens bisher kein Experten-basiertes BBN gegeben, das zukünftige Entwicklungen untersucht. Eine weitere Besonderheit des Ansatzes ist, dass für jeden Experten ein eigenes BBN quantifiziert wurde, so dass eine Schar von Netzwerken entstanden ist, deren Aussagen verglichen werden können. Dadurch war es möglich, die Bandbreite der Erwartungen verschiedener Experten abzuleiten und festzustellen, wo Erwartungen relativ konsistent sind, und wo sie weit auseinander liegen. Daraus lassen sich wertvolle Schlüsse ableiten, an welchen Punkten weitere Forschung besonders erfolgversprechend ist. BBN haben sich damit als nützliches Werkzeug für Stakeholder-basierte iterative Forschungsprozesse erwiesen. Insgesamt hat es sich als fruchtbarer neuer Ansatz erwiesen, Experten-basierte Bayesianische Netzwerke zur Untersuchung zukünftiger Entwicklungsmöglichkeiten heranzuziehen. Die Methode ermöglicht es auch, den Einfluß von Rahmenbedingungen zu bestimmen.

Environmental regulations have historically been focused on individual emission points, facilities, or industrial sectors. However, recent and emerging regulations for greenhouse gas (GHG) emissions such as those contained in the Energy Independence and Security Act (EISA) of 2007 have introduced the concept of product life cycle limits on the emissions of transportation fuels. Thus, a complete life cycle assessment (LCA) of the transportation fuel must be completed where all emissions from field to the vehicle’s fuel tank and from tank to the vehicle’s exhaust must be assessed. However, although there have been extensive analysis of the GHG emissions associated with transportation fuels, there are substantial uncertainties associated with these estimates that can be attributed to poor data quality, inconsistent methodological choices, and model uncertainties, among others. This thesis evaluates the uncertainties present in LCA through the case study of fuel production using Fischer-Tropsch (F-T) synthesis of fuels derived from coal and biomass. Specifically, GHG emission estimates for F-T synthesis process scenarios are presented and the uncertainties in the estimates are discussed. Overall uncertainties in GHG emissions due to changes in the details of the process configurations in the F-T process can be up to 11%. This finding suggests that the details of fuel refining conditions will need to be specified in determining whether fuels meet GHG emission requirements, complicating the implementation of life cycle GHG regulations. / text

No description available.

The negative consequences of rising global energy use have led governments and businesses to pursue methods of reducing reliance on fossil fuels. Plug-In Hybrid Electric Vehicles (PHEVs) and wind power represent two practical methods for mitigating some of these negative consequences. PHEVs use large onboard batteries to displace gasoline with electricity obtained from the grid, while wind power generates clean, renewable power that has the potential to displace fossil-fuel power generation. The emissions reductions realized by these technologies will be highly dependent on the energy system into which they are integrated, and also how they are integrated. This research aims to assess to cost of reducing emissions through the integration of PHEVs and wind power in three Canadian jurisdictions, namely British Columbia, Ontario and Alberta. An Optimal Power Flow (OPF) model is used to assess the changes in generation dispatch resulting from the integration of wind power and PHEVs into the local electricity network. This network model captures the geographic distribution of load and generation in each jurisdiction, while simulating local transmission constraints. A linear optimization model is developed in the MATLAB environment and is solved using the ILOG CPLEX Optimization package. The model solves a 168-hour generation scheduling period for both summer and winter conditions. Simulation results provide the costs and emissions from power generation when various levels of PHEVs and/or wind power are added to the electricity system. The costs and emissions from PHEV purchase and gasoline displacement are then added to the OPF results and an overall GHG reduction cost is calculated. Results indicate that wind power is an expensive method of GHG abatement in British Columbia and Ontario. This is due to the limited environmental benefit of wind over the nuclear and hydro baseload mixtures. The large premium paid for displacing hydro or nuclear power with wind power does little to reduce emissions, and thus CO2e costs are high. PHEVs are a cheaper method of GHG abatement in British Columbia and Ontario, since the GHG reductions resulting from the substitution of gasoline for hydro or nuclear power are significant. In Alberta, wind power is the cheaper method of GHG abatement because wind power is closer in price to the coal and natural gas dominated Alberta mixture, while offering significant environmental benefits. PHEVs represent a more expensive method of GHG abatement in Alberta, since substituting gasoline for expensive, GHG-intense electricity in a vehicle does less to reduce overall emissions. Results also indicate that PHEV charging should take place during off-peak hours, to take advantage of surplus baseload generation. PHEV adoption helps wind power in Ontario and British Columbia, as overnight charging reduces the amount of cheap, clean baseload power displaced by wind during these hours. In Alberta, wind power helps PHEVs by cleaning up the generation mixture and providing more environmental benefit from the substitution of gasoline with electricity.