1. THE RELATIONSHIP BETWEEN SHALE GAS PRODUCTION AND CARBON CAPTURE AND STORAGE UNDER CO2 TAXES: MARKAL MODELING Nadja Victor and Chris Nichols Pittsburgh, October 27, 2015 NETL Pittsburgh PA and Morgantown WV

2. 2 This Presentation was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. The views and opinions of authors expressed therein do not necessarily state or reflect those of the United States Government or any agency thereof. Disclaimer

3. 3 In August 2015, President Obama and EPA established the CPP, which put the U.S. on a path toward a 32 % reduction in CO2 by 2030. The 80% to 50% CO2 reduction targets in the U.S. by 2050 are consistent with global goals of GHG atmospheric stabilization at 450 to 550 ppm To achieve reductions in GHG emissions at low cost, economists often favor policies that effectively establish a price of emissions. Many analysts suggest that a uniform price on CO2 emissions regardless of source of the emissions, will produce the most efficient carbon reductions throughout the economy. The SCC is an estimate of the economic damages associated with an small increase in CO2 emissions and represents the value of damages avoided for a small emission reduction or the benefit of a CO2 reduction. EPA and other U.S. federal agencies use SCC to estimate the climate benefits of rulemakings. We explore the relationship between natural gas abundance and CCS under CO2 taxation based on the high end estimates of SCC using the MARKAL energy system multi-regional model Motivation:

4. 4 What is MARKAL? An energy-technology-environment model Uses a bottom-up representation of energy-producing, -transforming, and –consuming technologies Finds a least cost set of technologies to satisfy end-use energy service demands AND policies specified by the user Calculates resulting environmental emissions and water consumption/withdrawals Identifies the most cost-effective pattern of resource use and technology deployment over time. Quantifies the sources of emissions from the associated energy system. Provides a framework for exploring and evaluating alternative futures, and the role of various technology and policy options. Quantifies the system-wide effects of energy and environmental policies

5. 5 EPA’s U.S. 9 regions MARKAL databases Developed by EPA, publically available and transparent Take into account driving forces including –Technological options –Energy supply and price –Current environmental and energy policies Gather data from the major stakeholders, industry, academia, Department of Energy and Transportation Allows us to cover the range of possible futures and respond to others' technology assessments

6. 6 Data Source: NOAA (2014) Scenarios Definitions ScenariosDatabase Modifications Base EPAUS9r2014 database Baseline scenario was modified as a following: Changing natural gas supply curve to improve consistency with AEO 2014. Using AEO 2014 reference case for oil prices and natural gas prices. Changing demand to improve consistency with AEO 2014. HighGas Base scenario with natural gas supply curve represent AEO 2014 High Resource case. LowGas Base scenario with natural gas supply curve represent AEO 2014 Low Resource case. Base395Base scenario with carbon taxes in 2020–2055 based on the 95th percentile SCC estimate across all three models at 3% discount rate. HighGas395 HighGas scenario with carbon taxes in 2020–2055 based on the 95th percentile SCC estimate across all three models at 3% discount rate. LowGas395 LowGas scenario with carbon taxes in 2020–2055 based on the 95th percentile SCC estimate across all three models at 3% discount rate.

7. 7 Social Costs of CO2, 2010–2050 (‘2005$US/tCO2) Data Source: EPA (2013) Discount rate5.0%3.0%2.5% 3.0% Year, 95th 201010314985 2015113655103 2020114161122 2025134566136 2030154972150 2035185477166 2040205982181 2045236287195 2050266793209 2055*2974100234

8. 8 Total CO2 Emissions

9. 9 Contribution to CO2 Emission Reduction

10. 10 Electricity Generation Mix by Technology and by Scenario

11. 11 Electricity Generational Prices

12. 12 Discounted Total System Costs, Electricity Shadow Price and Cumulative CO2 Abatement by 2055

13. 13 DISCUSSION AND CONCLUSIONS In the scenarios without CO2 reduction policy increases in shale gas supply could substantially change the electricity system without producing appropriate changes in CO2 emissions in long-term. CO2 taxations reduce CO2 emissions by 53-54% in 2035 and by 46- 50% in 2055; additional system-wide reductions do not obtain in the model. Though shale gas boom fundamentally changes the energy sector landscape, it will take time and policies for the infrastructure to catch up. In the long-term future, in high natural gas supply scenarios, natural gas not only replaces coal power plants, but it also depresses nuclear and renewables deployments as a sustained low natural gas price may discourage investment in zero carbon technologies.

14. 14 DISCUSSION AND CONCLUSIONS (CONTINUE) Scenarios with CO2 taxes show substantial CCS technologies deployments. The big questions are whether and when CCS will become available, and how quickly it could be deployed. Because projects to construct facilities with CCS take years to build, the potential benefits of CCS are greater for coal-fired plants, and there is no certainty about future of high natural gas supply, the use of CCS at coal-fired facilities will probably remain at the forefront of the technology development. Whether replacing old coal power plants or meeting CPP, the new gas plants will be around for decades. Currently coal is the primary focus of most of the CCSs for power generation, but applying CCS to natural gas facilities will be increasingly important as the use of natural gas grows.

15. 15 Questions and discussion

16. 16 Developed under the Energy Technology Systems Analysis Program of IEA Linear programming type optimization ; based on Reference Energy System Detailed modeling of energy resources and supply chains Includes electricity generation and transmission planning How MARKAL Does It?

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