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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 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:
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THE RELATIONSHIP BETWEEN SHALE GAS PRODUCTION AND CARBON CAPTURE AND
STORAGE UNDER CO2 TAXES: MARKAL MODELING
Nadja Victor and Chris NicholsPittsburgh, October 27, 2015
NETL Pittsburgh PA and Morgantown WV
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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
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• 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:
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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
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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 Data Source: NOAA (2014)
Scenarios DefinitionsScenarios Database 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.
Base395 Base 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.
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Social Costs of CO2, 2010–2050 (‘2005$US/tCO2)
Data Source: EPA (2013)
Discount rate 5.0% 3.0% 2.5% 3.0% Year,
95th2010 10 31 49 85
2015 11 36 55 103
2020 11 41 61 122
2025 13 45 66 136
2030 15 49 72 150
2035 18 54 77 166
2040 20 59 82 181
2045 23 62 87 195
2050 26 67 93 209
2055* 29 74 100 234
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0
1000
2000
3000
4000
5000
6000
1955 1965 1975 1985 1995 2005 2015 2025 2035 2045 2055
MtC
O2
BS14_NEW
Base395
HighGas
HighGas395
LowGas
LowGas395
53-54%CO2 reduction
46-50%CO2 reduction
Total CO2 Emissions
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Contribution to CO2 Emission Reduction
0
1000
2000
3000
4000
5000
6000
7000
2010 2015 2020 2025 2030 2035 2040 2045 2050 2055
MtC
O2
Base395: Contribution to CO2Emission Reduction in Electricity Generation Sector, 2010–2055
Avoided by lowerelectricity demand
Avoided by nuclear
Avoided by renewables
Avoided by CCS
Avoided by fuel switchand efficiency gain
0
1000
2000
3000
4000
5000
6000
7000
2010 2015 2020 2025 2030 2035 2040 2045 2050 2055
MtC
O2
HighGas395: Contribution to CO2Emission Reduction in Electricity Generation Sector, 2010–2055
Avoided by lowerelectricity demand
Avoided by nuclear
Avoided by renewables
Avoided by CCS
Avoided by fuel switchand efficiency gain
0
1000
2000
3000
4000
5000
6000
7000
2010 2015 2020 2025 2030 2035 2040 2045 2050 2055
MtC
O2
LowGas395: Contribution to CO2Emission Reduction in Electricity Generation Sector, 2010–2055
Avoided by lowerelectricity demand
Avoided by nuclear
Avoided by renewables
Avoided by CCS
Avoided by fuel switchand efficiency gain
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Electricity Generation Mix by Technology and by Scenario
-
5,000
10,000
15,000
20,000
25,000
2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055
Qua
ntity
(PJ)
BaseIndustrial CHP
Distributed Solar PV
Central Solar Thermal
Wind Power
Hydropower
Geothermal Power
MSW and LFG
Biomass to IGCC
Conventional Nuclear Power
Diesel to Combustion Turbine
NGA to Combined-Cycle
NGA to Combustion Turbine
Coal to IGCC-CCS
Coal to IGCC-CCS Retro
Coal to IGCC
Coal to Steam-CCS Retro
Coal to Steam -
5,000
10,000
15,000
20,000
25,000
2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055
Qua
ntity
(PJ)
HighGas
Industrial CHP
Distributed Solar PV
Wind Power
Hydropower
Geothermal Power
MSW and LFG
Conventional Nuclear Power
NGA to Combined-Cycle
NGA to Combustion Turbine
NGA to Steam Electric
Coal to Existing Steam
BASE -
5,000
10,000
15,000
20,000
25,000
2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055
Qua
ntity
(PJ)
LowGasIndustrial CHP
Distributed Solar PV
Central Solar Thermal
Wind Power
Hydropower
Geothermal Power
MSW and LFG
Biomass to Steam
Conventional Nuclear Power
NGA to Combined-Cycle
NGA to Combustion Turbine
Coal to IGCC-CCS Retro
Coal to IGCC
Coal to Steam
Coal to Existing Steam
BASE
-
5,000
10,000
15,000
20,000
25,000
2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055
Qua
ntity
(PJ)
Base395Industrial CHP
Distributed Solar PV
Central Solar Thermal
Wind Power
Hydropower
Geothermal Power
MSW and LFG
Biomass to IGCC-CCS
Biomass to IGCC
Conventional Nuclear Power
NGA to Combined-Cycle-CCS RetroNGA to Combined-Cycle
NGA to Combustion Turbine
Coal to Steam
Coal to Existing Steam-CCSRetroCoal to Existing Steam
Base
-
5,000
10,000
15,000
20,000
25,000
2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055
Qua
ntity
(PJ)
HighGas395Industrial CHP
Distributed Solar PV
Central Solar Thermal
Wind Power
Hydropower
Geothermal Power
MSW and LFG
Biomass to IGCC-CCS
Biomass to IGCC
Biomass to Steam
Conventional Nuclear Power
NGA to Combined-Cycle-CCSRetroNGA to Combined-Cycle
NGA to Combustion Turbine
Coal to Steam-CCS Retro
Coal to Existing Steam-CCSRetroCoal to Existing Steam
Base -
5,000
10,000
15,000
20,000
25,000
2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055
Qua
ntity
(PJ)
LowGas395 Industrial CHP
Distributed Solar PV
Central Solar Thermal
Wind Power
Hydropower
Geothermal Power
MSW and LFG
Biomass to IGCC-CCS
Biomass to IGCC
Biomass to Steam
Conventional Nuclear Power
NGA to Combined-Cycle-CCSRetroNGA to Combined-Cycle
NGA to Combustion Turbine
Coal to IGCC-CCS Retro
Coal to Existing Steam-CCS Retro
Coal to Existing Steam
Base
11
Electricity Generational Prices
$-
$0.10
$0.20
$0.30
$0.40
$0.50
$0.60
$0.70
$0.80
$0.90
1955 1965 1975 1985 1995 2005 2015 2025 2035 2045 2055
'2005
$US/
tCO2
Base
Base395
HighGas
HighGas395
LowGas
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Discounted Total System Costs, Electricity Shadow Price and Cumulative CO2 Abatement by 2055
$-
$0.20
$0.40
$0.60
$0.80
$1.00
$1.20
90 91 92 93 94 95 96 97
'2005
$US/
kWh
GtCO2
LowGas395
BaseGas395HighGas395
0.0
0.5
1.0
1.5
2.0
2.5
3.0
HighGas LowGas Base395 HighGas395LowGas395
Trillio
n $20
05US
Discounted Total System Costs: Difference to Base Scenario
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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.
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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.
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Questions and discussion
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The MARKAL Energy PerspectiveThe MARKAL Energy Perspective
Industry, e.g.-Process steam-Motive power
Services, e.g.-Cooling-Lighting
Households, e.g.-Space heat-Refrigeration
Agriculture, e.g.-Water supply
Transport, e.g.-Person-km
Demand for Energy Service
Industry, e.g.-Steam boilers-Machinery
Services, e.g.-Air conditioners-Light bulbs
Households, e.g.-Space heaters-Refrigerators
Agriculture, e.g.-Irrigation pumps
Transport, e.g.-Gasoline Car-Fuel Cell Bus
End-UseTechnologies
ConversionTechnologies
Primary Energy Supply
Fuel processingPlants e.g.-Oil refineries-Hydrogen prod.-Ethanol prod.
Power plants e.g.-ConventionalFossil Fueled
-Solar-Wind-Nuclear-CCGT-Fuel Cells-Combined Heat
and Power
Renewables e.g. -Biomass-Hydro
Mining e.g.-Crude oil-Natural gas-Coal
Imports e.g.-crude oil -oil products
Exports e.g.-oil products-coal
Stock changes
(Final Energy) (Useful Energy)
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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