Carbon Mitigation Initiative
CMI

CMI Technology

CMI Technology

CMI Technology studies energy conversion in conjunction with CO2 capture and storage. Capture studies include both biological and fossil fuel inputs. Storage studies emphasize leakage pathways and now also investigate storage in shales. The program on advanced batteries continues.

Research Highlights – At a Glance

Michael Celia: Modeling of CO2 injection in the Marcellus shale formation reveals the need for a very large number of injection wells—approximately 100 additional wells brought online every year—to store CO2 emissions from Pennsylvania’s five largest coal-fired power plants over a 40 year lifetime.

Howard Stone: Theoretical and laboratory-scale models for the characterization of CO2-inspired flow in porous media have led to analytical formulae for ready modeling of leakage in sequestration projects.

Craig Arnold: Correlation between a battery’s electrochemical properties and the mechanical stress of its internal materials provides measurements of its state of charge and state of health, which inform the optimization of battery performance for grid systems and portable applications.

Athanassios Panagiotopoulos, Pablo Debenedetti, and Jeroen Tromp: Molecular-based computational tools for predicting fundamental physical and chemical characteristics of H2O+CO2 and H2O-NaCl binary systems are being developed to help interpret the rational design of CO2 separation processes and long-term CO2 storage in geological formations.

Eric Larson, Robert Williams, and Thomas Kreutz: Analysis of smaller scale systems for the manufacture of low- or negative-carbon synthetic fuels from biomass and from biomass + natural gas feedstocks reveals that, in the presence of a strong carbon mitigation policy, such systems might be competitive at crude oil prices of less than $100 per barrel and would offer the opportunity for fossil fuel providers to exploit more of their fossil fuel reserves under a carbon budget constraint.


CO2 Injection into Depleted Shale-gas Wells
Principal Investigator: Michael Celia

At a Glance

Modeling of CO2 injection in the Marcellus shale formation reveals the need for a very large number of injection wells—approximately 100 additional wells brought online every year—to store CO2 emissions from Pennsylvania’s five largest coal-fired power plants over a 40 year lifetime.

Research Highlight

Research in the Celia group has continued with modeling general aspects of carbon dioxide (CO2) injection1-7 into conventional formations and measuring methane leakage along old wells8-10. In addition, a study of the feasibility of injection of CO2 into depleted shale-gas formations has continued. The idea to inject CO2 into depleted shale formations has been advanced recently as an alternative or complement to injection into conventional reservoirs. Initial estimates from the literature indicated very large (static) storage capacities11,12; the current research focuses on realistic estimates of injection rates and the logistical feasibility of different injection scenarios. To address this issue, the Celia group conducted a thorough review of gas production data for the Barnett formation in Texas as well as two different regions of the Marcellus shale formation in Pennsylvania (Southwest Pennsylvania (SW PA) and Northeast Pennsylvania (NE PA)). The Celia group developed a model for multi-component gas flow within the various formations, including the movement of methane (CH4) and CO2. The model includes equations of state, sorption of both CH4 and CO2, and formation parameters derived from matching production data.

The results in Figure 2.1.1 show cumulative injected mass of CO2 into a typical well in the three formations as a function of time. The NE PA region has the best performance, because the formation is much thicker in the northeast than in the southwest, and because length of horizontal wells has become noticeably longer in NE PA. While the northeast location has the best behavior, the amount that can be injected into one well is still orders-of-magnitude smaller than the emissions from a typical coal-fired power plant: ultimate cumulative mass injected in one well is about 0.5 Million Tonnes (Mt) CO2, while the output from one large coal-fired power plant over that time (40 years) is on the order of 200 Mt CO2. It is worth noting the total mass injected has an upper limit due to the assumptions of the one-dimensional model; more detailed simulations may show some additional capacity, but the additional amount is expected to be insignificant.

Large stationary sources in Pennsylvania were identified and the CO2 emissions were mapped to existing (both drilled and permitted) shale-gas wells. Figure 2.1.2 shows both sources and wells. If the CO2 produced by the large sources in southwest Pennsylvania is injected into wells in southwest PA, essentially all wells in the region (approximately 6,400) are needed over a time period of 40 years (more than 150 new wells each year). If the higher-injectivity wells in Northeast Pennsylvania are used instead, then the number of wells will be 3,800 (about 100 wells per year). Note that use of wells in Northeast PA requires longer pipelines to be built.

For either of these cases, it is reasonable to ask if it is more economically and logistically feasible to build a large pipeline west of the Illinois Basin, and use conventional reservoirs such as the Mt Simon formation to sequester the CO2. A comprehensive economic and feasibility study is currently ongoing, to clarify advantages and disadvantages among these different options for CO2 transport and injection.

Figure 2.1.1
Figure 2.1.1. Cumulative mass of CO2 injected as a function of time for a typical well in the Barnett, Southwest PA Marcellus, and Northeast PA Marcellus formations. Note that half of the ultimate capacity is reached after about 5 years for all three curves. (Figure courtesy of the Celia group.)
Figure 2.1.2
Figure 2.1.2. Stationary sources of CO2 (triangles with size scaled to amount of emissions), and existing and permitted shale-gas wells (all dots). The gray shaded region indicates the Marcellus shale formation in Pennsylvania. Purple dots (6,400 or them) identify wells needed to store 40 years of emissions from the five large sources in southwest Pennsylvania (orange triangles); green dots (3,800 of them) identify wells in northeast Pennsylvania to store the same emissions. (Figure courtesy of the Celia group.)

References

  1. Bandilla, K.W., M.A. Celia, and E. Leister, 2014. Impact of Model Complexity on CO2 Plume Modeling at Sleipner. Energy Procedia, 63: 3405-3415. doi:10.1016/j.egypro.2014.11.369.
  2. Bandilla, K., M.A. Celia, J.T. Birkholzer, A. Cihan, and E.C. Leister, 2015. Multi-phase Modeling of Geologic Carbon Sequestration in Saline Aquifers. Ground Water, February 6, 2015 (online). doi:10.1111/gwat.12315.
  3. Zheng, Z., B. Guo, I. Christov, M. Celia, and H. Stone, 2015. Flow Regimes for Fluid Injection into a Confined Porous Medium. J. Fluid Mech., 767: 881-909. doi:10.1017/jfm.2015.68.
  4. Huang, X., K.W. Bandilla, M.A. Celia, and S. Bachu, 2014. Basin-scale Modeling of CO2 Storage using Models of Varying Complexity. Int. J. Greenh. Gas Control, 20: 73-86. doi:10.1016/j.ijggc.2013.11.004
  5. Guo, B., K.W. Bandilla, F. Doster, E. Keilegavlen, and M.A. Celia, 2014. A Verticallyintegrated Model with Vertical Dynamics for CO2 Storage. Water Resour. Res., 50(8): 6269-6284. doi:10.1002/2013WR015215.
  6. Guo, B., K.W. Bandilla, E. Keilegavlen, F. Doster, and M.A. Celia, 2014. Application of Verticallyintegrated Models with Subscale Vertical Dynamics to Field Sites for CO2 Sequestration. Energy Procedia, 63: 3523-3531. doi:10.1016/j.egypro.2014.11.381.
  7. Kang, M., J.M. Nordbotten, F. Doster, and M.A. Celia, 2014. Analytical Solutions for Two-phase Subsurface Flow to a Leaky Fault considering Vertical Flow Effects and Fault Properties. Water Resour. Res., 50(4): 3536-3552. doi:10.1002/2013WR014628.
  8. Kang, M., C. Kanno, M. Reid, X. Zhang, D.L. Mauzerall, M.A. Celia, Y. Chen, and T.C. Onstott, 2014. Direct Measurements of Methane Emissions from Abandoned Oil and Gas Wells in Pennsylvania. Proc. Natl. Acad. Sci., December 8, 2014 (online). doi:10.1073/pnas.1408315111.
  9. Kang, M., E. Baik, A.R. Miller, K.W. Bandilla, and M.A. Celia, 2015. Effective Permeabilities of Abandoned Oil and Gas Wells: Analysis of Data from Pennsylvania. Environ. Sci. Technol., March 13, 2015. doi:10.1021/acs.est.5b00132.
  10. Kang, M., D.L. Mauzerall, D.Z. Ma, and M.A. Celia, 2015. Estimating and Mitigation Methane Emissions from Abandoned Oil and Gas Wells in Pennsylvania. Environ. Sci. Technol., under review.
  11. Tao, Z. and A. Clarens, 2013. Estimating the Carbon Sequestration Capacity of Shale Formations using Methane Production Rates. Environ. Sci. Technol., 47(19):11318-11325. doi:10.1021/es401221j.
  12. Godec, M., G. Koperna, R. Petrusak, and A. Oudinot, 2013. Assessment of Factors Influencing CO2 Storage Capacity and Injectivity in Eastern U.S. Gas Shales. Energy Procedia, 37: 6644-6655. doi:10.1016/j.egypro.2013.06.597.

Analytical and Laboratory-Scale Models for the Characterization of CO2-inspired Flows in Porous Media
Principal Investigator: Howard A. Stone

At a Glance

Theoretical and laboratory-scale models for the characterization of CO2-inspired flow in porous media have led to analytical formulae for ready modeling of leakage in sequestration projects.

Research Highlight

The Stone Group has investigated a variety of subsurface fluid flow problems inspired by carbon dioxide (CO2) sequestration. In these applications it is critical to characterize the rates at which two fluid phases (e.g. supercritical CO2 and water) rearrange in a porous medium. The fluid dynamics will be influenced by confinement of the flowing fluids, and it is critical to model processes such as fluid injection, buoyancy-driven spreading, and leakage. In particular, leakage could occur from an edge (or crack) in the porous medium, or along a porous boundary; such modeled processes may be very useful to characterize leakage from underground sequestration sites. The research program’s models are inspired by the various processes relevant to field studies, and are simplified representations of large-scale numerical simulations common to industrial-scale studies. That said, the model has been refined in collaboration with Michael Celia, to more accurately approximate a field situation. This collaboration has benefitted both research groups and has been made possible by the unique research partnerships afforded by the CMI initiative. Figure 2.2 summarizes research results for confined configurations without leakage, as a phase diagram that describes how the shape of the fluid-fluid interface during fluid injection can vary with time (T is a dimensionless time, defined as the real time rescaled by a characteristic time for the fluid flow in the porous medium) for different ratios M of the displaced fluid to the injected fluid.

The Stone Group has made several new modeling contributions to the field of fluid flow in porous media, in particular analytical descriptions that practitioners may use to rapidly estimate spreading and/or leakage rates for geometries typical of many underground environments. Analytical descriptions provide simple formulae for important physical processes such as fluid spreading during or after a fluid injection process. Such results allow the inclusion of important physical parameters such as the fluid density and viscosity, the porosity and permeability of the porous medium (which help to characterize the resistance of the medium to flow), and leakage paths for the fluid into the surrounding matrix. Also, laboratory experiments have been performed to test the basic premises of the different models and to check the analytical predictions for spreading and leakage rates. The laboratory studies also provide a convenient platform for visualizing the kinds of dynamics envisioned as relevant for subsurface flow. The focus on confinement effects for various flow regimes may be relevant for the transport of fluids (e.g. CO2, H2O) in pipelines.

The results of this research provide analytical formulae for easy modeling of flow in underground reservoirs. These results can readily inform policy and regulatory frameworks by providing firstorder estimates for the leakage rate and the horizontal span of a CO2 sequestration project. The Stone group is planning to use this approach of analytical and laboratory-scale models of geophysical phenomena to study ice flows in narrow straits. This problem was introduced to the group by scientists at the Geophysical Fluid Dynamics Laboratory (GFDL) who currently utilize complex numerical simulations to model climate change and the dynamics of ice flow relevant to the Arctic. It is anticipated this alternative approach to the problem will lead to a synergistic collaboration with the GFDL.

Figure 2.2
Figure 2.2. Flow regimes for fluid injection into a confined porous medium. Five distinct dynamical regimes are identified, depending on two dimensionless groups: M, the viscosity ratio of the displaced fluid to the injected fluid, and T, the dimensionless time. The regime boundaries are indicated by symbols (numerical estimates) and dashed curves (analytical estimates). Typical shapes of the fluid-fluid interface are also shown in each of the individual regimes1.

Reference

  1. Zheng, Z., B. Guo, I.C. Christov, M.A. Celia, and H.A. Stone, 2015. Flow regimes for fluid injection into a confined porous medium. J. Fluid Mech., 767: 881-909. doi:10.1017/jfm.2015.68.

Measuring and Optimizing Battery Performance
Principal Investigator: Craig Arnold

At a Glance

Correlation between a battery’s electrochemical properties and the mechanical stress of its internal materials provides measurements of its state of charge and state of health, which inform the optimization of battery performance for grid systems and portable applications.

Research Highlight

Energy storage is playing an increasingly important role throughout the energy infrastructure, from powering hybrid and electric vehicles to offsetting the inherent intermittency of renewable energy generation. Electrochemical batteries are a particularly attractive option for energy storage and come in many form factor shapes and sizes. However, two key challenges affecting the adoption of batteries in grid level and portable applications are

  • the ability to obtain an accurate measure of the amount of charge stored at any given time (state of charge); and
  • the ability to obtain an accurate measure of how much longer the battery can last before it needs to be replaced (state of health).

The Arnold group is studying novel means to measure the state of charge and state of health, in order to manage optimal battery performance under demanding real-time applications. The focus of this research is on understanding the relationship and coupling between mechanical and electrochemical properties.

Figure 2.3.1 demonstrates how the mechanical stress (force per unit area) in a lithium-ion battery varies as a function of the amount of charge stored in it1. As the battery charges, lithium ions in the battery move into the negative electrode, leading to internal expansion and an increase in the measured mechanical stress inside the battery. The stress increases approximately linearly with respect to the amount of charge stored in the battery cell. As the battery discharges, the internal stress decreases as lithium is now removed from the negative electrode. Thus, the measured stress of the battery directly correlates with the amount of charge stored in the cell, i.e. the state of charge.

Figure 2.3.2 demonstrates the peak mechanical stress in a battery as a function of the state of health2. State of health is a ratio of the amount of charge delivered by the battery for a given cycle to the amount of charge delivered when the battery is new. Thus, the state of health represents the number of charging and discharging cycles: 100% state of health represents a fresh battery and typically 85% would represent a battery needing replacement. Over time, the maximum stress in the battery cell gradually increases due to irreversible transitions in the battery materials. Correlating this stress to the amount of charge stored in the cell gives a simple linear dependence and an accurate measure of the amount of lifetime left in a usable cell, to directly predict when batteries should be replaced before catastrophic failure.

As batteries charge and discharge, changes in the shape and mechanical properties of their materials occur. Over time, permanent changes in these materials lead to a degradation in electrochemical performance—the ability to store charge and to transfer charge quickly with little dissipation— resulting in an end of usable battery life. The Arnold group has found such electrochemical degradation to manifest as changes in battery mechanical properties, which can be easily measured without disassembling the cell. Thus, a simple mechanical measurement enables inference of the electrochemical state—the state of charge and state of health—of a battery, making it possible to manage charging and discharging for the optimization of energy storage performance either at the grid level or in portable storage applications. Engineers and system designers can easily incorporate the locally linear relationship between mechanical and electrochemical properties, as real-time information for the control and optimization of battery systems.

The Arnold Group continues to investigate the underlying physical principles for measuring electrochemical performance, with plans to develop a commercial device based on these principles that permits use of the basic technology in real-time within an industrial setting.

Figure 2.3.1
Figure 2.3.1. Oscillations in the measured stress of a battery as a function of the charging and discharging that occurs over many cycles1.
Figure 2.3.2
Figure 2.3.2. Battery state of health (SOH) compared to measured peak stress in the cell. 100% SOH represents a fresh battery and typically 85% would represent a battery needing replacement2.

Reference

  1. Cannarella, J., and C. B. Arnold, 2014. Stress evolution and capacity fade in constrained lithium ion pouch cells. J. Power Sources, 245: 745-751. doi:10.1016/j.jpowsour.2013.06.165.
  2. Cannarella, J., and C. B. Arnold, 2014. State of health and charge measurements in lithium-ion batteries using mechanical stress. J. Power Sources, 269: 7-14. doi:10.1016/j.jpowsour.2014.07.003.

Molecular Modeling of CO2 Capture and Storage
Principal Investigators: Athanassios Panagiotopoulos, Pablo Debenedetti, and Jeroen Tromp

At a Glance

Molecular-based computational tools for predicting fundamental physical and chemical characteristics of H2O+CO2 and H2O-NaCl binary systems are being developed to help interpret the rational design of CO2 separation processes and long-term CO2 storage in geological formations.

Research Highlight

Over the past year, the research collaboration between Panagiotopoulos and Debenedetti (CBE), and Tromp (Geosciences) has focused on obtaining the phase behavior and transport properties for the H2O+CO2 and H2O-NaCl binary systems. For the engineering design of carbon dioxide (CO2) sequestration processes, accurate predictions of properties for these mixtures at conditions found in geological reservoirs are required. Experimental data are often not available over the complete range of conditions of interest; predictive, molecular-based models coupled with computer simulations can reliably interpolate and (it is hypothesized) extrapolate from limited experimental information. These simulations can also help discriminate among conflicting sets of experimental data.

The research group found that phase partitioning and interfacial properties of these systems can be predicted with moderate accuracy using existing atomistic models. However, it appears that future modeling needs will require development of improved force fields (intermolecular potential models). Several force field combinations were examined for the H2O+NaCl system and used to calculate the vapor pressure, liquid density, viscosity and vapor-liquid interfacial tension as a function of salt content. The group has also optimized the intermolecular potential parameters for the H2O+CO2 system1 in an attempt to reconcile conflicting sets of experimental measurements2,3, as shown in Figure 2.4.

The long-term goals of this work include the development of reliable, molecular-based models for the thermophysical and adsorption properties of components and systems involved in geological carbon sequestration. The group plans to focus efforts on the development and testing of polarizable force fields4,5, which can accurately capture both aqueous and non-aqueous solution environments. These have not been as well developed as non-polarizable force fields because of their higher computational cost.

Figure 2.4
Figure 2.4. On left, a schematic representation of a two-phase system with a CO2-rich top phase and a H2O-rich bottom phase; on right, the composition of the coexisting phases predicted from simulations with different models (points) and sets of experimental data (lines)1. There is significant disagreement among experimental measurements1-2 for the top (CO2-rich) phase.

Reference

  1. Orozco, G.A., I. G. Economou, and A. Z. Panagiotopoulos, 2014. Optimization of Intermolecular Potential Parameters for the CO2/H2O Mixture. J. Phys. Chem. B, 118: 11504-11511. doi:10.1021/ jp5067023.
  2. Todheide, K., and E.U. Frank, 1963. Das Zweiphasengebie Und Die Kritische Kurve Im System Kohlenoxid-Wasser Bis Zu Drucken Von 3500 bar. Z. Phys. Chem. Neue Folge, 37: 387−401. doi:10.1524/zpch.1963.37.5_6.387.
  3. Takenouchi, S., and G. C. Kennedy, 1964. Binary system H2O-CO2 at high temperatures + pressures. Am. J. Sci., 262: 105.
  4. Paricaud, P., M. Predota, A. A. Chialvo, and P. T. Cummings, 2005. From dimer to condensed phases at extreme conditions: Accurate predictions of the properties of water by a Gaussian charge polarizable model. J. Chem. Phys., 122: 244511. doi:10.1063/1.1940033.
  5. Kiss, P.T., and A. Baranyai, 2013. A systematic development of a polarizable potential of water. J. Chem. Phys., 138: 204507. doi:10.1063/1.4807600.

Negative-Emission Biofuels
Principal Investigators: Eric Larson, Robert Williams, and Thomas Kreutz

At a Glance

Analysis of smaller scale systems for the manufacture of low- or negative-carbon synthetic fuels from biomass and from biomass + natural gas feedstocks reveals that, in the presence of a strong carbon mitigation policy, such systems might be competitive at crude oil prices of less than $100 per barrel and would offer the opportunity for fossil fuel providers to exploit more of their fossil fuel reserves under a carbon budget constraint.

Research Highlight

The Energy Systems Analysis group, led by Eric Larson, Robert Williams, and Thomas Kreutz, is investigating the prospective performance and economics of gasification-based systems for producing electricity and synthetic fuels from an input feedstock that is biomass or a combination of biomass and natural gas, with most carbon dioxide (CO2) emissions captured and stored (CCS systems). The group has designed systems that consume no more than 1 million dry tonnes of biomass per year, a logistical maximum that may be truck-delivered in the US to a single site. Two systems designed produce 3,500 and 7,000 barrels per day of Fischer-Tropsch (FT) synfuels, respectively, and are small relative to “gas-to-liquid” plants, such as the Pearl project in Qatar producing 140,000 barrels per day.

There are four principal arguments for investigating smaller systems:

  • in contrast to the high costs for large, advanced fossil-only projects (e.g., Southern Company’s Kemper County $6.2 B integrated gasification combined cycle plant with CCS) the financial risk for investing in moderate output energy systems is lower;
  • exhausted shale gas wells may offer inexpensive storage for small volumes of CO2 (280 to 720 thousand tonnes per year for the systems investigated here);
  • at small scales, biomass gasifiers operated at atmospheric pressure can be used, which greatly facilitates feeding biomass into the gasifier; and
  • improved synthesis economics with recent commercial development of advanced, factoryproducible reactors for catalytic synthesis of fuels in modules with capacities of a few hundred barrels per day (see Figure 2.5.1). This is far smaller than the 20,000 barrels per day capacity of conventional reactor modules used at the Pearl project.

This research examines a biomass-only “Bio/CCS+” and a hybrid natural gas “BioNG/CCS” system, each consuming about ⅔ of the maximum biomass. The hybrid system’s feedstock is about half biomass and half natural gas (on an energy basis). The outputs are synthetic FT fuels and CO2, with a small net electricity co-product (7% to 15% of energy products). Removal of CO2 from synthesis gas is already required for fuels synthesis, so there is very little incremental cost for capturing this CO2 (the expense is mainly for CO2 compression).

In collaboration with Lynn Loo (design of the plant)1 and Michael Celia (CO2 storage in shale gas wells)2, the group has explored systems that may be located over the Marcellus shale formation, a region where biomass, cheap shale gas, and pre-drilled CO2 storage sites exist. The Celia group has estimated prospective rates at which CO2 can be injected into depleted shale gas wells in the Marcellus formation, and these are well-matched to the CO2 capture rates for the two systems.

The lifecycle greenhouse gas (GHG) emissions (in metric tonnes of equivalent CO2eq per unit of liquid fuel energy, denoted as t CO2eq), including contributions from the plant and from fuel combustion in a vehicle, are significantly lower than from equivalent petroleum-derived fuels: if petroleum-fuel emissions are taken, for reference, to be +1, emissions for BioNG/CCS are +0.42 and for BioCCS+ are -0.82. In the BioNG/CCS case, CO2 storage accounts for 15% of the carbon in the feedstocks, and 36% is vented at the plant. In the Bio/CCS+ case, 59% of input biomass carbon is stored underground as CO2, and only 4% is vented.

Figure 2.5.2 shows bands of prices of crude oil that would make each of these options competitive with petroleum-derived fuels, at various GHG emissions prices. The tops of the bands represent firstof- a-kind (FOAK) plants with capital costs assumed to be twice those developed in this conceptual estimating study3. Experience might lead to cost reductions (“learning by doing”) equivalent to fractions of these bands. The calculations assume a well-head gas price of $3 per million BTU and a biomass cost of $5 per million BTU, with CO2 stored in nearby spent shale gas wells. With FOAK capital costs and with zero GHG emissions price, fuels produced via a BioNG/CCS built in the near term would be competitive with petroleum-derived fuels when the oil price is $120 per barrel while Bio/CCS+ requires a crude oil price 70% higher. The BioNG/CCS is more competitive than Bio/ CCS+ due primarily to lower feedstock costs and secondarily to scale-economy benefits and process efficiency improvements. A price on GHG emissions makes both systems more competitive and affects the Bio/CCS+ system the most, i.e., the breakeven oil price for Bio/CCS+ falls rapidly with increasing GHG emission price. The two cost lines for FOAK systems cross at $65 per barrel, when the GHG emissions price is about $130/t CO2eq.

According to the Intergovernmental Panel on Climate Change (IPCC), if the global community were on an energy track consistent with limiting global warming to 2°C under market-based climatechange- mitigation policies, the GHG emissions price would rise (in 2012 $) from almost $60/t CO2 in 2020 to $100/t in 2032 and to more than $220/t in 20504. This work suggests that for such an emissions price trajectory BioNG/CCS might be economically deployed early in the next decade, and that Bio/CCS+ systems could become attractive options soon thereafter. The IPCC has also shown that if likely global warming is to be limited to no more than 2°C, biomass energy with carbon capture and storage (BECCS) technologies that provide negative emissions will probably be needed4 to stay within the allowable remaining cumulative CO2 emissions (about 1 trillion tonnes5): BECCS systems with negative emissions could provide an opportunity for carbon credits that would enable a fossil fuel provider to use more of its fossil fuel reserves under such a carbon budget constraint.

The Energy Systems Analysis Group will expand its investigation of alternative processes for production of low and negative emissions liquid transportation fuels, including pyrolytic and biochemical systems, as well as additional gasification-based pathways with and without fossil fuel coprocessing.

Figure 2.5.1
Figure 2.5.1. Module for FT synthesis at small scale (about 175 barrels per day liquids production)6.
Figure 2.5.2
Figure 2.5.2. Prospective economics of negative emissions biofuels (Bio/CCS+) improve more rapidly with increasingly stringent carbon policy than those for hybrid biomass/natural gas systems (BioNG/CCS). Inset table results are taken from Ref.1.

Reference

  1. Hailey, A.K., J.C. Meerman, E.D. Larson, and Y-L. Loo, 2015. Co-processing Biomass and Natural Gas into Clean Transportation Fuels at Small Scale. Manuscript in preparation, February, 2015.
  2. Edwards, R.W.J., M.A, Celia, C.M. Kanno, K.W Bandilla, and F. Doster, 2014. Investigating the Potential for Large-Scale Carbon Dioxide Sequestration in Shale Gas Formations. Abstract H1D-03, AGU Fall Meeting (San Francisco, CA), 15-19 December, 2014.
  3. Greig, C., A. Garnett, J. Oesch, and S. Smart, 2014. Guidelines for Scoping and Estimating Early Mover CCS Projects, Milestone 5, Final Report. Univ. Queensland, Brisbane, Australia, 19 June, 2014.
  4. Intergovernmental Panel on Climate Change (IPCC), 2014. Climate Change 2014: Mitigation of Climate Change, Working Group III contribution to the Fifth Assessment Report, April, 2014.
  5. Intergovernmental Panel on Climate Change (IPCC), 2014. Climate Change 2014: Mitigation of Climate Change, Working Group I contribution to the Fifth Assessment Report, April, 2014.
  6. McDaniel, J. (Velocys, Inc.), 2014. Commercial deployment of smaller scale GTL in North America. Energy Frontiers Gas-to-Market and Energy Conversion Forum (Pittsburgh, PA), October, 2014.

Technology Publications

Bandilla, K., M.A. Celia, J.T. Birkholzer, A. Cihan, and E.C. Leister, 2015. Multi-phase Modeling of Geologic Carbon Sequestration in Saline Aquifers. Ground Water, February 6, 2015 (online). doi:10.1111/gwat.12315.

Bandilla, K.W., M.A. Celia, and E. Leister, 2014. Impact of Model Complexity on CO2 Plume Modeling at Sleipner. Energy Procedia, 63: 3405-3415. doi:10.1016/j.egypro.2014.11.369.

Cannarella, J., and C. B. Arnold, 2014. Stress evolution and capacity fade in constrained lithium ion pouch cells. J. Power Sources, 245: 745-751. doi:10.1016/j.jpowsour.2013.06.165.

Cannarella, J., and C. B. Arnold, 2014. State of health and charge measurements in lithium-ion batteries using mechanical stress. J. Power Sources, 269: 7-14. doi:10.1016/j. jpowsour.2014.07.003.

Guo, B., K.W. Bandilla, F. Doster, E. Keilegavlen, and M.A. Celia, 2014. A Vertically-integrated Model with Vertical Dynamics for CO2 Storage. Water Resour. Res., 50(8): 6269-6284. doi:10.1002/2013WR015215.

Guo, B., K.W. Bandilla, E. Keilegavlen, F. Doster, and M.A. Celia, 2014. Application of Vertically-integrated Models with Subscale Vertical Dynamics to Field Sites for CO2 Sequestration. Energy Procedia, 63: 3523- 3531. doi:10.1016/j.egypro.2014.11.381.

Hai-Akbari, A., R.S. DeFever, S. Sarupria, and P.G. Debenedetti, 2014. Suppression of Sub-Surface Freezing in Free-Standing Thin Films of a Coarse-Grained Model of Water. Phys. Chem. Chem. Phys., 16: 25916-27. doi:10.1039/c4cp03948c.

Hailey, A.K., J.C. Meerman, T.G. Kreutz, E.D. Larson, and Y-L. Loo, 2015. Co-processing Biomass and Natural Gas into Clean Transportation Fuels at Small Scale. Poster displayed at E-ffiliates Retreat, Andlinger Center for Energy and the Environment, Chauncey Conf. Center, 5 Feb. 2015.

Huang, X., K.W. Bandilla, M.A. Celia, and S. Bachu, 2014. Basin-scale Modeling of CO2 Storage using Models of Varying Complexity. Int. J. Greenh. Gas Control, 20: 73-86. doi:10.1016/j.ijggc.2013.11.004.

Kang, M., J.M. Nordbotten, F. Doster, and M.A. Celia, 2014. Analytical Solutions for Two-phase Subsurface Flow to a Leaky Fault considering Vertical Flow Effects and Fault Properties. Water Resour. Res., 50(4): 3536- 3552. doi:10.1002/2013WR014628.

Kang, M., C. Kanno, M. Reid, X. Zhang, D.L. Mauzerall, M.A. Celia, Y. Chen, and T.C. Onstott, 2014. Direct Measurements of Methane Emissions from Abandoned Oil and Gas Wells in Pennsylvania. Proc. Natl. Acad. Sci., December 8, 2014 (online). doi:10.1073/ pnas.1408315111.

Kang, M., E. Baik, A.R. Miller, K.W. Bandilla, and M.A. Celia, 2015. Effective Permeabilities of Abandoned Oil and Gas Wells: Analysis of Data from Pennsylvania. Environ. Sci. Technol., March 13, 2015. doi:10.1021/acs. est.5b00132.

Kang, M., D.L. Mauzerall, D.Z. Ma, and M.A. Celia, 2015. Estimating and Mitigation Methane Emissions from Abandoned Oil and Gas Wells in Pennsylvania. Environ. Sci. Technol., in review.

Liu, G., and E.D. Larson, 2014. Comparison of Coal/Biomass Co-processing Systems with CCS for Production of Low-carbon Synthetic Fuels: Methanol-to-Gasoline and Fischertropsch. Energy Procedia, 63: 7315-7329. doi:10.1016/j.egypro.2014.11.768.

Liu, G., and E.D. Larson, 2014. Gasoline from Coal via DME with Electricity Co-production and CO2 Capture. Energy Procedia, 63: 7367- 7378. doi:10.1016/j.egypro.2014.11.773.

Liu, G., E.D. Larson, R.H. Williams, and X. Guo, 2015. Gasoline from Coal and/or Biomass with CO2 Capture and Storage, 1. Process Designs and Performance Analysis. Energy and Fuels, 29(3): 1830-1844. doi:10.1021/ef502667d.

Liu, G., E.D. Larson, R.H. Williams, and X. Guo, 2015. Gasoline from Coal and/or Biomass with CO2 Capture and Storage, 2. Economic Analysis and Strategic Context. Energy and Fuels, 29(3):1845-1859. doi:10.1021/ef502668n.

Orozco, G.A., I. G. Economou, and A. Z. Panagiotopoulos, 2014. Optimization of Intermolecular Potential Parameters for the CO2/H2O Mixture. J. Phys. Chem. B, 118: 11504-11. doi:10.1021/jp5067023.

Orozco, G.A., O. A. Moultos, H. Jiang, I. G. Economou, and A. Z. Panagiotopoulos, 2014. Molecular Simulation of Thermodynamic and Transport Properties for the H2O + NaCl System. J. Chem. Phys. 141: 234507. doi:10.1063/1.4903928.

Spinelli, M., S. Campanari, M.C. Romano, S. Consonni, T.G. Kreutz, H. Ghezel-Ayagh, S. Jolly, and M. Di Nitto, 2015. Using Molten Carbonate Fuel Cells for Clean Power Generation and CO2 Capture Retrofitting Coal Power Plants And Combined Cycles. Proc. ASME 2015 Power and Energy Conversion Conf. (San Diego, CA), June 28- July 2, 2015.

Williams, R.H., 2014. Capture technology cost buydown in CO2 EOR market applications under an Alternative Energy Portfolio Standard. Energy Procedia, 63: 7913-7928. doi:10.1016/j.egypro.2014.11.826.

Williams, R.H., 2014. Capture technology cost buydown in CO2 EOR market applications under a state or regional Alternative Energy Portfolio Standard. Poster presented at GHGT-12 (Austin, TX), 6-9 October, 2014.

Williams, R.H., 2014. Comments by Dr. Robert H. Williams of Princeton University’s Princeton Environmental Institute on Carbon Pollution Emission Guidelines for Existing Stationary Sources: Electric Utility Generating Units: Proposed Rule. Federal Register, 79(117) (June 18, 2014), 40 CFR Part 60, filed at Docket ID No. EPAHQ- OAR-2013-0602 of the United States Environmental Protection Agency, filed December 1, 2014.

Zheng, Z., I.C. Christov, and H.A. Stone, 2014. Influence of heterogeneity on secondkind self-similar solutions for viscous gravity currents. J. Fluid Mech., 747: 218-246. doi:10.1017/jfm.2014.148

Zheng, Z., B. Guo, I.C. Christov, M. A. Celia, and H.A. Stone, 2015. Flow regimes for fluid injection into a confined porous medium. J. Fluid Mech., 767: 881-909. doi:10.1017/ jfm.2015.68.

Zheng, Z., H. Kim, and H.A. Stone, 2015. Controlling viscous fingering using timedependent strategies. Phys. Rev. Lett., in review.

Zheng, Z., S. Shin, and H.A. Stone, 2015. Converging gravity currents over a permeable substrate. J. Fluid Mech., in review.

Zheng, Z., L. Rongy, and H.A. Stone, 2015. Viscous fluid injection into a confined channel. Phys. Fluids, in review.

<< Previous  |  Table of Contents  |  Next >>

 
Feedback: cmi@princeton.edu
Last update: April 03 2015
BP Princeton Environmental Institute © 2017 The Trustees of Princeton University
CMI is sponsored by BP.