Today, and for the foreseeable future, coal and other fossil fuels will provide a major portion of the energy services demanded by both developed and developing countries around the word. In order to reduce the emissions of carbon dioxide associated with combustion of coal for electricity generation, a wide range of carbon capture technologies are being developed. This thesis models the oxyfuel carbon capture process for pulverized coal and presents performance and cost estimates of this system in comparison to other low-carbon fossil fuel generators. Detailed process models for oxygen production, flue gas treatment, and carbon dioxide purification have been developed along with the calculation strategies necessary to employ these components in alternative oxyfuel system configurations for different types of coal-fired power plants. These new oxyfuel process models have been implemented in the widely-used Integrated Environmental Control Model (IECM) to facilitate systematic comparisons with other low-carbon options employing fossil fuels. Assumptions about uncertainties in the performance characteristics of gas separation processes and flue gas duct sealing technology, as well as plant utilization and financing parameters, were found to produce a wide range of cost estimates for oxyfuel systems. In case studies of a new 500 MW power plant burning sub-bituminous Powder River Basin coal, the estimated levelized cost of electricity (LCOE) 95% confidence interval (CI) was 86 to 150 [$/MWh] for an oxyfuel system producing a high-purity [99.5 mol% CO2] carbon dioxide product while capturing 90% of the flue gas carbon dioxide. For a CoCapture oxyfuel system capturing 100% of the flue gas CO2 together with all other flue gas constituents, the estimated LCOE 95% CI was 90 to 153 [$/MWh] (all costs in constant 2012 US Dollars). Using the IECM, an oxyfuel system for CO2 capture also was compared under uncertainty to an existing amine-based post-combustion capture system for a new 500 MW power plant, with both systems capturing 90% of the CO2 and producing a high-purity stream for pipeline transport to a geological sequestration site. The resulting distribution for the cost of CO2 avoided showed the oxyfuel-based system had a 95% CI of 44 to 126 [$/tonne CO2] while the amine-based system cost 95% CI ranged from 50 to 133 [$/tonne CO2]. The oxyfuel cost distribution had a longer tail toward more expensive configurations but over 70% of the distribution showed the oxyfuel-based system to be ~10[$/tonne CO2] lower in cost compared to the amine-based capture system. An evaluation of several low-carbon generation options fueled by coal and natural gas further considered both direct and indirect greenhouse gas emissions. This analysis showed oxyfuel to be economically competitive with all capture system considered, and also indicated oxyfuel to be the preferred carbon capture technology for minimizing overall carbon intensity. Combined, these results suggest that oxyfuel is a promising carbon capture technology, and the only one which offers the unique ability to capture all the combustion gases to become a truly zero emission coal plant. Realization of the latter option, however, is contingent on the development of new regulatory policies for underground injection of mixed flue gas streams that is outside the scope of this thesis.

In this thesis, I present four research papers related by their focus on environmental and economic effects of low-carbon policies and technologies in electric power. The papers address a number of issues related to the operation and design of CCS-equipped plants with solvent storage and bypass, the effect of Renewable Portfolio Standards (RPS) on cycling of coal-fired power plants, and the EPA’s proposed CO2 emissions rule for existing power plants. In Chapter 2, I present results from a study of the design and operation of power plants equipped with CCS with flue gas bypass and solvent storage. I considered whether flue gas bypass and solvent storage could be used to increase the profitability of plants with CCS. Using a pricetaker profit maximization model, I evaluated the increase in NPV at a pulverized coal (PC) plant with an amine-based capture system, a PC plant with an ammonia-based capture system, and a natural gas combined-cycle plant with an amine-based capture system when these plants were equipped with an optimally sized solvent storage vessel and regenerator. I found that while flue gas bypass and solvent storage increased profitability at low CO2 prices, they ceased to do so at CO2 prices high enough for the overall plant to become NPV-positive. In Chapter 3, I present results from a Unit Commitment and Economic Dispatch model of the PJM West power system. I quantify the increase in cycling of coal-fired power plants that results when complying with a 20% RPS using wind power, accounting for cycling costs not usually included in power plant bids. I find that while additional cycling does increase cycling-related production costs and emissions of CO2, SO2, and NOX, these increases are small compared to the overall reductions in production costs and air emissions that occur with high levels of wind. In proposing its existing power plant CO2 emissions standard, the Environmental Protection Agency determined that significant energy efficiency would be available to aid in compliance. In Chapter 4, I use an expanded version of the model of Chapter 3 to evaluate compliance with the standard with and without this energy efficiency, as well as under several other scenarios. I find that emissions of CO2, SO2, and NOX are relatively insensitive to the amount of energy efficiency available, but that production costs increase significantly when complying without efficiency. In complying with the EPA’s proposed existing power plant CO2 emissions standard, states will have the choice of whether to comply individually or in cooperation with other states, as well as the choice of whether to comply with a rate-based standard or a mass-based standard. In Chapter 5, I present results from a linear dispatch model of the power system in the continental U.S. I find that cooperative compliance reduces total costs, but that certain states will prefer not to cooperate. I also find that compliance with a mass-based standard increases electricity prices by a larger margin than does compliance with a rate-based standard, with implications for the distribution of surplus changes between producers and consumers.

Carbon Capture and Storage (CCS) is an old technology matrix with new concept to mitigate climate change while utilizing fossil fuels by advancing the technology. The various level of advancement in technology has been successfully demonstrated in some part of the world. However the technology has inherent uncertainty of not having commercial CCS plant. Efforts to make CCS commercially viable unfold uncertainties in numerous aspects of CCS technology. Beside the uncertainties in technology many barriers restrain CCS to become a successful climate mitigation technology. However the growing energy demand and urgent need to mitigate climate change through emission reduction favours CSS as transition to clean energy production. FutureGen 2.0 is the only large commercial scale CCS project, initiated in 2003 to test the commercial viability of the technology and to meet the U.S energy demands besides emission reductions target. The project resurrection in 2010 as FutureGen 2.0 after FutureGen termination in 2008 provides an opportunity to understand and analyse numerous uncertainties. However through document analysis only major three uncertainties i.e. policy and regulatory, economic and financial and public acceptance uncertainties are identified and analysed. The interlinkages between these uncertainties are also analysed. The study results show that above uncertainties constrained the project engendering new uncertainties i.e. timeframe uncertainties. This study also provides an insight about the sustainability implication of CCS by evaluating economic, environmental and social impact of CCS technology. It is still early to term the CCS as Sustainable technological innovation however for many years CCS would upset and restrain investment in other clean energy technologies like Renewable technology system. This study gives an input in sustainability of CCS and technological assessment study. This study is helpful in managing uncertainties and planning new CCS projects.

This study geochemically characterized a proposed Carbon Capture and Storage project in northeast British Columbia, and presents new dissolution kinetics data for the proposed saline aquifer storage reservoir, the Keg River Formation. The Keg River Formation is a carbonate reservoir (89-93% Dolomite, 5-8% Calcite) at approximately 2200 m depth, at a pressure of 190 bar, and temperature of 105 °C. The Keg River brine is composed of Na, Cl, Ca, K, Mg, S, Si, and HCO3 and is of approximately 0.4 M ionic strength. Fluid analysis found the Keg River brine to be relatively fresh compared with waters of the Keg River formation in Alberta, and to also be distinct from waters in overlying units. These findings along with the physical conditions of the reservoir make the Keg River Formation a strong candidate for CO2 storage. Further work measured the dissolution rates of Keg River rock that will occur within the Keg River formation. This was performed in a new experimental apparatus at 105 °C, and 50 bar pCO2 with brine and rock sampled directly from the reservoir. Dissolution rate constants (mol!m-2s-1) for Keg River rock were found to be Log KMg 9.80 ±.02 and Log KCa -9.29 ±.04 for the Keg River formation. These values were found to be significantly lower compared to rate constants generated from experiments involving synthetic brines with values of Log KMg -9.43 ±.09, and Log KCa -9.23 ±.21. Differences in rates were posited as due to influences of other element interactions with the >MgOH hydration site, which was tested through experiments with brines spiked with SrCl2 and ZnCl2. Results for the SrCl2 spiked solution showed little impact on dissolution rates with rate constants of Log KMg -9.43 ±.09, and Log KCa -9.15 ±.21, however the ZnCl2 spiked solution did show some inhibition with rate constants of Log KMg -9.67 ±.04, and Log KCa -9.30 ±.04. Rate constants generated in this work are among the first presented which can actually be tested by full-scale injection of CO2. / Graduate

A model for the evaluation of CO2-EOR projects has been developed. This model includes both reservoir simulation to handle reservoir properties, fluid flow and injection and production schedules, and a numerical economic model that generates a monthly cash flow stream from the outputs of the reservoir model. This model is general enough to be used with any project and provide a solid common basis to all of them. This model was used to evaluate CO2-EOR injection and production strategies and develop an optimization workflow. Producer constraints (maximum oil and gas production rates) should be optimized first to generate a reference case. Further improvements can then be obtained by optimizing the injection starting date and the injection plateau rate. Investigation of sensitivity of CO2-EOR to the presence of an aquifer showed that CO2 injection can limit water influx in the reservoir and is beneficial to recovery, even with a strong water drive. The influence of some key parameters was evaluated: the producer should be completed in the top part of the reservoir, while the injector should be completed over the entire thickness; it is recommended but not mandatory that the injection should start as early as possible to allow for lower water cut limit. Finally, the sensitivity of the economics of the projects to some key parameters was evaluated. The most influent parameter is by far the oil price, but other parameters such as the CO2 source to field distance, the pipeline cost scenario, the CO2 source type or the CO2 market price have roughly the same influence. It is therefore possible to offset an increase of one of them by reducing another.

Flexible carbon capture and storage (CCS) has the potential to play a significant part in the decarbonisation of electricity generation portfolios which have significant penetration from intermittent renewable sources. Post-combustion capture (PCC) with amine solvents is a mature technology and is currently the state-of-the-art for CO2 emissions reduction from power stations. However, knowledge of the dynamic capture process is currently limited due to a dearth of dynamic datasets which reflect real plant operation, lack of a robust in-situ solvent analysis method for plant control and uncertainty about how changing plant design affects the response to dynamic operations. In addition, the nature of interfacial gas-liquid dynamics inside the absorber column are not well known and rely on correlations for effective mass transfer area and liquid holdup which may have uncertainties of up to +/- 13%. This could result in absorption columns being improperly sized for CCS operations. Two pilot-scale test campaigns are implemented in order to gain an understanding of how the capture plant responds to dynamic operations, the first on natural gas combined cycle (NGCC)-equivalent flue gas, the second on pulverised coal (PC)-equivalent. Changes in flue gas flow rates and steam supply which are designed to be representative of PCC operation on real NGCC and PC plant are implemented, using 30%wt monoethanolamine (MEA) as absorbent in both cases. Dynamic datasets are obtained for 5 scenarios with NGCC and 8 with PC flue gas. The test campaigns are carried out using two separate pilot-scale facilities and highlight the effect of plant design on hydrodynamics and hence, the response of the capture plant to dynamic operations. Finally, a novel solvent sensor is used to demonstrate, for the first time, control of the capture facility using in-situ measurements of solvent composition, combined with knowledge of test facility hydrodynamics and response times. Results from the pilot-scale test campaign are then used along with a mathematical NGCC capture plant scale up to investigate the potential effects of dynamic operations on total yearly CO2 emissions and the associated environmental penalties, depending on CO2 price. Manufacturers of column internals for CCS often rely on computational fluid dynamic (CFD) software tools for design, but existing commercial codes are unable to handle complex two-phase flows such as those encountered in the absorber column of a CO2 capture plant. An open-source direct numerical simulation (DNS) tool which will be capable of rigorously modelling two-phase flow with turbulence and mass transfer has been developed and could eventually replace the empirical methods currently used in packing design. The DNS code requires validation by experiment. For the purpose of validation a dual-purpose wetted-wall column is constructed, which in addition to mass transfer measurements can be used to determine liquid film thickness using an optical method. Measurements of average film thickness, wave amplitude, frequency, velocity and growth rate are provided for three liquid flow rates of fresh 30%wt MEA solution. Wave measurements are made with quiescent, laminar and turbulent gas flow, with and without mass transfer. These measurements can be used to validate the DNS code at its existing level of complexity, and in the future when turbulence and mass transfer are added.

I assess the potential of seismic and time-domain controlled-source electromagnetic (CSEM) methods to monitor carbon dioxide (CO2) migration through the application of a monitorability workflow. The monitorability workflow describes a numerical modelling approach to model variations in the synthetic time-lapse response due to CO2 migration. The workflow consists of fluid-flow modelling, rock-physics modelling and synthetic seismic or CSEM forward modelling. I model CO2 injected into a simple, homogeneous reservoir model before applying the workflow to a heterogeneous model of the Bunter Sandstone reservoir, a potential CO2 storage reservoir in the UK sector of the North Sea. The aim of this thesis is to model the ability of seismic and time-domain CSEM methods to detect CO2 plume growth, migration and evolution within a reservoir, as well as the ability to image a migrating front of CO2. The ability to image CO2 plume growth and migration within a reservoir has not been demonstrated in the field of CSEM monitoring. To address this, I conduct a feasibility study, simulating the time-lapse CSEM time-domain response of CO2 injected into a saline reservoir following the multi-transient electromagnetic (MTEM) method. The MTEM method measures the full bandwidth response. First, I model the response to a simple homogeneous 3D CO2 body, gradually increasing the width and depth of the CO2. This is an analogue to vertical and lateral CO2 migration in a reservoir. I then assess the ability of CSEM to detect CO2 plume growth and evolution within the heterogeneous Bunter Sandstone reservoir model. I demonstrate the potential to detect stored and migrating CO2 and present the synthetic results as time-lapse common-offset time sections. The CO2 plume is imaged clearly and in the right coordinates. The ability to image seismically a migrating front of CO2 remains challenging due to uncertainties regarding the pore-scale saturation distribution of fluids within the reservoir and, in turn, the most appropriate rock-physics model to simulate this: uniform or patchy saturation. I account for this by modelling both saturation models, to calculate the possible range of expected seismic velocities prior to generating and interpreting the seismic response. I demonstrate the ability of seismic methods to image CO2 plume growth and evolution in the Bunter Sandstone saline reservoir model and highlight clear differences between the two rock-physics models. I then modify the Bunter Sandstone reservoir to depict a depleted gas field by including 20% residual gas saturation. I assess the importance and implication of patchy saturation and present results which suggest that seismic techniques may be able to detect CO2 injected into depleted hydrocarbon fields.

Metal organic frameworks (MOFs) are a class of nanoporous materials composed through self-assembly of inorganic and organic structural building units (SBUs). MOFs show great promise for many applications due to their record-breaking internal surface areas and tunable pore chemistry. This thesis work focuses on gas separation applications of MOFs in the context of carbon capture and storage (CCS) technologies. CCS technologies are expected to play a key role in the mitigation of anthropogenic CO2 emissions in the near future. In the first part of the thesis, robust machine learning quantitative structure-property relationship (QSPR) models are developed to predict CO2 working capacity and CO2/H2 selectivity for pre-combustion carbon capture using the most topologically diverse database of hypothetical MOF structures constructed to date (358,400 MOFs, 1166 network topologies). The support vector regression (SVR) models are developed on a training set of 35,840 MOFs (10% of the database) and validated on the remaining 322,560 MOFs. The most accurate models for CO2 working capacities (R2 = 0.944) and CO2/H2 selectivities (R2 = 0.876) are built from a combination of six geometric descriptors and three novel y-range normalized atomic-property-weighted radial distribution function (AP-RDF) descriptors. 309 common MOFs are identified between the grand canonical Monte Carlo (GCMC) calculated and SVR-predicted top-1000 high-performing MOFs ranked according to a normalized adsorbent performance score. This work shows that SVR models can indeed account for the topological diversity exhibited by MOFs. In the second project of this thesis, computational simulations are performed on a MOF, CALF-20, to examine its chemical and physical properties which are linked to its exceptional water-resisting ability. We predict the atomic positions in the crystal structure of the bulk phase of CALF-20, for which only a powder X-ray diffraction pattern is available, from a single crystal X-ray diffraction pattern of a metastable phase of CALF-20. Using the predicted CALF-20 structure, we simulate adsorption isotherms of CO2 and N2 under dry and humid conditions which are in excellent agreement with experiment. Snapshots of the CALF-20 undergoing water sorption simulations reveal that water molecules in a given pore adsorb and desorb together due to hydrogen bonding. Binding sites and binding energies of CO2 and water in CALF-20 show that the preferential CO2 uptake at low relative humidities is driven by the stronger binding energy of CO2 in the MOF, and the sharp increase in water uptake at higher relative humidities is driven by the strong intermolecular interactions between water. In the third project of this thesis, we use computational simulations to investigate the effects of residual solvent on Ni-BPM’s CH4 and N2 adsorption properties. Single crystal X-ray diffraction data shows that there are two sets of positions (Set 1 and 2) that can be occupied by the 10 residual DMSO molecules in the Ni-BPM framework. GCMC simulations of CH4 and N2 uptake in Ni-BPM reveal that CH4 uptake is in closest agreement with experiment when the 10 DMSO’s are placed among the two sets of positions in equal ratio (Mixed Set). Severe under-prediction and over-prediction of CH4 uptake are observed when the DMSO’s are placed in Set1 and Set 2 positions, respectively. Through binding site analysis, the CH4 binding sites within the Ni-BPM framework are found to overlap with the Set 1 DMSO positions but not with the Set 2 DMSO positions which explains the deviations in CH4 uptake observed for these cases. Binding energy calculations reveal that CH4 molecules are most stabilized when the DMSO’s are in the Mixed Set of positions.

Microporous metal organic frameworks (MOFs) are a novel class of materials formed through self-assembly of inorganic and organic structural building units (SBUs). They show great promise for many applications thanks to record-breaking internal surface areas, high porosity as well as a wide variety of possible chemical compositions. Molecular simulation has been instrumental in the study of MOFs to date, and this thesis work aims to validate and expand upon these efforts through two distinct computational MOF investigations. Current separation technologies used for CO2/N2 mixtures, found in the greenhouse gas-emitting flue gas generated by coal-burning power plants, could greatly benefit from the improved cost-effective separation MOF technology offers. MOFs have shown great potential for CO2 capture due to their low heat capacities and high, selective uptake of CO2. To ensure that simulation techniques effectively predict quantitative MOF gas uptakes and selectivities, it is important that the simulation parameters used, such as force fields, are adequate. We show that in all cases explored, the force field in current widespread use for N2 adsorption over-predicts uptake by at least 50% of the experimental uptake in MOFs. We propose a new N2 model, NIMF (Nitrogen in MoFs), that has been parameterized using experimental N2 uptake data in a diverse range of MOFs found in literature. The NIMF force field yields high accuracy N2 uptakes and will allow for accurate simulated uptakes and selectivities in existing and hypothetical MOF materials and will facilitate accurate identification of promising materials for CO2 capture and storage as well as air separation for oxy-fuel combustion. We also present the results of grand canonical and canonical Monte Carlo (GCMC and canonical MC), DFT and molecular dynamics (MD) simulations as well as charge density analyses, on both CO2 and N,N-dimethylformamide adsorbed in Ba2TMA(NO3) and MIL-68(In), two MOFs with non-equivalent inorganic structural building units. We demonstrate the excellent agreement found between our simulation results and the solid-state NMR (SSNMR) experiments carried out by Professor Yining Huang (Western University) on these two MOFs. Molecular simulation enables discoveries which complement SSNMR such as the number, distribution and dynamics of guest binding sites within a MOF. We show that the combination of SSNMR and molecular simulation forms a powerful analytical procedure for characterizing MOFs, and this novel set of microscopic characterization techniques allows for the optimization of new and existing MOFs.

In this thesis computational chemistry has been used to accelerate experimental discovery in the fields of ice recrystallization inhibitors for cryopreservation and ultra-microporous MOFs for carbon dioxide capture and storage. Ice recrystallization is one of the leading contributors to cell damage and death during the freezing process. This occurs when larger ice crystal grains grow at the expense of smaller ones. Naturally occurring biological antifreeze molecules have been discovered but only operate up to -4oC and actually exasperate the problem at temperatures lower than this. Recently, the group of Dr. Robert Ben have been successful in synthesizing small organic molecules which are capable of inhibiting the growth of ice crystals during the freezing process. They have built a library of diverse compounds with varying functionalities and activity. Chemical intuition has been unsuccessful in finding a discernible trend with which to predict activity. Herein we present work where we have utilized a quantitative structure activity relationship (QSAR) model to predict whether a molecule is active or inactive. This was built from a database of 124 structures and was found to have a positive find rate of 82%. Proposed molecules that had yet to be synthesized were predicted to active or inactive using our method and 9/11 structures were indeed active which is strikingly consistent to the 82% find rate. Our efforts to aid in the discovery of these novel molecules will be described here. Metal organic frameworks (MOFs) are a relatively new class of porous materials which have taken the academic community by storm. These three-dimensional crystalline materials are built from a metal node and an organic linker. Depending on the metals and organic linkers used, MOFs can possess a vast range of topologies and properties that can be exploited for specific applications. Ultra-microporous MOFs possess relatively small pores in the range of 3.5 Å to 6 Å in diameter. These MOFs have some structural advantages compared to larger pored MOFs such as molecular sieving, smaller pores which promote strong framework-gas interactions and cooperative effects between guests, and longer shelf-life due to small void volumes and rigid frameworks. Here we present newly synthesized ultra-microporous MOFs based on isonicotnic acid as the organic linker with Ni and Mg as the metal centre. Despite having such small pores, Ni-4PyC exhibits exceptionally high CO2 uptake at high pressures. Furthermore, Mg-4PyC exhibits novel pressure dependent gate-opening behaviour. Computational simulations were employed to investigate the origin of high CO2 uptake, predict high pressure (>10bar) isotherms, quantify CO2 binding site positions and energies, and study uptake-dependent linker dynamics. This work hopes to provide experimentalists with some explanation to these interesting unexplained phenomena and also predict optimal properties for new applications.